Objectives: The purpose of this article was to familiarize pediatricians with the diagnosis and management of pinworm infestation.

Methods: A search was conducted in August 2023 in PubMed Clinical Queries using the key terms “Enterobius vermicularis,” OR “enterobiasis,” OR “pinworm.” The search strategy included all clinical trials, observational studies, and reviews published within the past 10 years. Only papers published in the English literature were included in this review. The information retrieved from the above search was used in the compilation of the present article.

Results: Enterobiasis is a cosmopolitan parasitosis caused by Enterobius vermicularis. It affects approximately 30% of children worldwide and up to 60% of children in some developing countries. Predisposing factors include poor socioeconomic conditions, inadequate sanitation, poor personal hygiene, and overcrowding. Children aged 5 to 14 years have shown the highest prevalence of enterobiasis.. Egg transmission is mainly by the fecal-oral route. Approximately 30 to 40% of infested patients do not show any clinical symptoms of the disease. For symptomatic patients, the most common presenting symptom is nocturnal pruritus ani. The diagnosis of E. vermicularis infection is best established by the cellophane tape test. The sensitivity of one single test is around 50%; however, the sensitivity increases to approximately 90% with tests performed on three different mornings. If a worm is visualized in the perianal area or the stool, a pathological examination of the worm will yield a definitive diagnosis. As pinworms and eggs are not usually passed in the stool, examination of the stool is not recommended. The drugs of choice for the treatment of pinworm infestation are mebendazole (100 mg), pyrantel pamoate (11 mg/kg, maximum 1 g), and albendazole (400 mg), all of the above-mentioned drugs are given in a single dose and repeated in two weeks. Mebendazole and albendazole are both adulticidal and ovicidal, whereas pyrantel pamoate is only adulticidal. Given their safety and effectiveness, mebendazole and albendazole are currently the best available drugs for the treatment of pinworm infestation. For pregnant women, pyrantel is preferred to mebendazole and albendazole. Treatment of all household members should be considered, especially if there are multiple or repeated symptomatic infections because reinfection is common even when effective medication is given.

Conclusion: In spite of effective treatment of pinworm infestation, recurrences are common. Recurrences are likely due to repeated cycles of reinfection (particularly, autoinfection) because of the short life span of adult pinworms. Good personal hygiene, such as frequent handwashing, especially after bowel movements and before meals, clipping of fingernails, avoidance of finger-sucking, nail-biting, and scratching in the anogenital area, are important preventive measures. Treatment of all household members should be considered, especially if there are multiple or repeated symptomatic infections.

Objectives: Despite advancements in biological therapies, significant clinical needs persist. This review aims to discuss novel treatments, guiding future guidelines and drug discoveries for rheumatoid arthritis.

Methods: This review follows the 2020 PRISMA statement, utilising PubMed and Google Scholar for literature search and emphasizing recent meta-analyses on the safety and efficacy of targeted immunobiological medications.

Results: Small molecule inhibitors, whether utilised independently or in conjunction with Methotrexate, have been shown to contribute to effective disease management and have the potential for better adherence to the American College of Rheumatology criteria. Tocilizumab therapy demonstrates a significant reduction in disease activity and improves rates of disease remission when combined with Methotrexate. Investigations of mesenchymal stromal cell therapies have had promising outcomes, improving both cartilage quality (as evaluated by Macroscopic Cartilage Repair Assessment) and joint tenderness and swelling in clinical joint counts. Intra-articular administration of tolerogenic dendritic cells has displayed a capacity to alleviate pain, as measured by Visual Analog Scale scores, and enhance the Disease Activity Score across 28 joints. Resveratrol capsules supplemented with allopathic therapy show potential in reducing TNF-α and interleukin-6 serum levels.

Conclusion: More investigations and their analysis will improve patient outcomes and reduce adverse effects and the costs involved in developing and obtaining immunobiological drugs. Moreover, assessing the safety and efficacy of anti-RA properties of the bioactive compounds could offer less toxic and more cost-effective natural treatment options.

Objective: This study identifies the potential role of Fan in inducing apoptosis in Jurkat T cells.

Methods: First, we explored the biological process (BP) associated with SS development by performing a gene ontology analysis of SS salivary gland-related mRNA microarray data. The effect of Fan on Jurkat cells was investigated by analyzing the viability, proliferation, apoptosis, reactive oxygen species (ROS) production, and DNA damage.

Results: Biological process analysis showed that T cells played a role in salivary gland lesions in patients with SS, indicating the significance of T cell inhibition in SS treatment. Viability assays revealed that the half-maximal inhibitory concentration of Fan was 2.49 μM in Jurkat T cells, while the proliferation assay revealed that Fan had an inhibitory effect on the proliferation of Jurkat T cells. The results of the apoptotic, ROS, agarose gel electrophoresis, and immunofluorescence assays showed that Fan induced oxidative stress-induced apoptosis and DNA damage in a dosedependent manner.

Conclusion: These results indicate that Fan could significantly induce oxidative stress-induced apoptosis and DNA damage and inhibit the proliferation of Jurkat T cells. Moreover, Fan further enhanced the inhibitory effect on DNA damage and apoptosis by inhibiting the pro-survival Akt signal.

Objectives: This review aims to cover the natural excipients’ role in nanoformulations and associated prospects.

Methods: More than 500 manuscripts were collected from ScienceDirect, PubMed, google, and other sources; however the manuscripts were excluded based on their relevance to the subject and finally 80 manuscripts were analyzed for the data.

Results: The substation of synthetic lipids with natural and semisynthetic for developing lipid-based nano drug delivery, and the use of gelatin and chitosan in developing encapsulated and nano particulates are a few examples to understand the above-mentioned transition.

Conclusion: This review provides an overview of the types of excipients used in the formulation of novel drug delivery systems with special emphasis on their characteristics, safety aspects, benefits associated, and common methods through, which they are employed in nanoformulations.

Case Presentation: In this study, we report a case of a patient with fallopian tube leiomyoma. What makes this instance even more unique is the association of the leiomyoma with cystic degeneration, manifesting as a large abdominopelvic cystic mass. CT scan suspected that the mass might be an ovarian cystadenoma. However, ultrasonography, a widely used diagnostic tool, effectively assisted the clinicians in confidently ruling out the possibility that the tumor was originating from the ovaries. Ultimately, the patient underwent exploratory laparoscopy and the pathologic diagnosis was fallopian tube leiomyoma with cystic degeneration. To our knowledge, no instance of a fallopian tube leiomyoma of this size with cystic degeneration has been reported. Thus, it is worth mentioning.

Conclusion: In summary, fallopian tube leiomyomas are classified as uncommon benign gynecologic tumors, which pose challenges in clinical diagnosis. The combined use of multiple imaging modalities may be more helpful in the proper diagnosis of this disease entity.

Objective: This study aimed to determine the capability of ultrasonography (US)-based radiomics for presurgical prediction of metastasis in LN-prRLNs in PTC.

Methods: Patients were retrospectively enrolled and pathologically confirmed as LN-prRLN metastasis with PTC after surgery. Radiomic analysis based on preoperative US images with manual segmentation of targets was used to develop a radiomics model. US features described in ACR TI-RADS were collected to construct a clinical model. The Radiomics model, a combined model integrating radiomics and clinical model, were also developed for the presurgical prediction of metastasis in LN-prRLNs.

Results: A total of 570 patients, including 488 patients with non-LN-prRLN metastasis and 82 with LN-prRLN metastasis, were assessed. The 15 topperforming features finally remained significant for constructing the radiomics model. The combined model showed that US measured tumor size (OR: 1.036, P = 0.044), US suspected lateral lymph node metastasis (OR: 2.247, P = 0.009), multifocality (OR: 1.920, P = 0.021), Delphian lymph node metastasis (DLNM) (OR: 2.300, P = 0.039), VIa compartment metastasis (OR: 5.357, P = 0.000), the radiomics score (OR: 1.003, P = 0.001) were significant risk factors for predicting LN-prRLN metastasis. The combined model achieved a higher AUC of 0.849 than that of the clinical model (AUC: 0.826) and radiomics model (AUC: 0.759).

Conclusion: The US-based radiomics combined model can more effectively predict LN-prRLN metastasis in PTCs patients preoperatively. This approach had the potential to assist surgeons in decision-making regarding LN-prRLN dissection.

Objective: This study aimed to explore the value of T1 mapping and amide proton transfer weighted (APTw) imaging in predicting LN metastasis in patients with rectal cancer.

Methods: In a retrospective study, twenty-three patients with pathologically confirmed rectal adenocarcinoma who underwent MRI and surgery from August 2019 to August 2021 were selected. Then, 3.0T/MR sequences included conventional sequences (T1WI, T2WI, and DWI), APTw imaging, and T1 mapping. Patients were divided into LN metastasis (group A) and non-LN metastasis groups (group B). The intra-group correlation coefficient (ICC) was used to test the inter-observer consistency. Mann-Whitney U test was used to compare the differences between the two groups. Spearman correlation analysis was performed to evaluate the correlation between T1 and APT values. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter and their combination. The difference between AUCs was compared using the DeLong test.

Results: The APT value in patients with LN metastasis was significantly higher than in those without LN metastasis group (P=0.020). Also, similar results were observed for the T1 values (P=0.001). The area under the ROC curve of the APT value in the prediction of LN metastasis was 0.794; when the cutoff value was 1.73%, the sensitivity and specificity were 71.4% and 88.9%, respectively. The area under the ROC curve of the T1 value was 0.913; when the cutoff value was 1367.36 ms, the sensitivity and specificity were 78.6% and 100.0%, respectively. The area under the ROC curve of T1+APT was 0.929, with a sensitivity of 78.6% and specificity of 100.0%.

Conclusion: APT and T1 values show great diagnostic efficiency in predicting LN metastasis in rectal cancer.

Case Presentation: Here we present a rare case of primary thymic mucinous adenocarcinoma in the anterior mediastinum, including computed tomography (CT) and magnetic resonance imaging (MRI) findings. Chest computed tomography revealed a large anterior mediastinal mass with extensive calcifications with poor enhancement. MRI showed that anterior mediastinal mass showed intermediate signal intensity on T1-weighted images (T1WI), high SI on T2-weighted images (T2WI), and heterogeneous enhancement. Biopsy was performed and the anterior mediastinal tumor was diagnosed as thymic mucinous adenocarcinoma by histopathologic examination and immunohistochemical staining.

Conclusion: Thymic mucinous adenocarcinomas could be included in differential diagnoses of anterior mediastinal tumors showing extensive calcification, and common imaging findings of mucinous adenocarcinoma such as T2 high signal intensity and heterogeneous enhancement on MRI may be helpful to diagnose thymic mucinous adenocarcinoma.

Methods: The preprocessing techniques (smoothing, edge detection, filtering) and segmentation techniques (watershed) are applied to the online data set. The transfer learning technique is used as a classifier whose performance is measured in terms of classification accuracy. Resnet 50, Inception V3VGG16, and VGG19 models are used as classification algorithms. The proposed model is validated using different machine learning techniques considering hybrid features.

Results: 96% accuracy was obtained employing the Inception V3 model & 95% accuracy was attained using hybrid GLDS and GLCM features employing Support Vector Machine algorithm while 93% was attained using Probabilistic Neural Network and k Nearest Neighbor techniques.

Conclusion: Computer-aided systems gave much faster and more accurate results than image processing techniques.1.0% accuracy improvement was observed while using Inception V3 over GLDS + GLCM + SVM and 2.1% accuracy improvement using GLDS + GLCM + SVM over GLDS + GLCM + kNN.

Methods: Sixty-four patients with single pulmonary lesions (SPLs) received DCE-MRI at 3.0 T. Of them, 49 cases were diagnosed with lung cancer, and 15 with benign pulmonary nodules (8 inflammatory nodules, 5 tuberculosis, and 2 abscesses). SPLs were quantitatively analyzed to determine the pulmonary lesions-related perfusion parameters, including reflux constant (Kep), volume transfer constant (K_trans), the maximum slope of increase (MaxSlope), extravascular extracellular space volume fraction (Ve), apparent diffusion coefficient (ADC), the initial area in the signal intensitytime curve (IAUGC), and contrast-enhancement ratio (CER). In addition, a Student’s t-test was conducted to calculate statistical significance regarding the quantitatively analyzed perfusion parameters in benign SPLs compared to malignant SPLs. The area under (AUC) the receiver operating characteristic (ROC) curve was studied to investigate the performance of perfusion parameters in diagnosing lung cancer.

Results: Values of K_trans, Kep, Ve, MaxSlope, and IAUGC increased within malignant nodules relative to benign nodules (K_trans: 0.21 ±0.08 vs. 0.73 ±0.40, P = 0.0001; Kep: 1.21 ±0.66 vs. 1.83 ±0.90, P = 0.0163; Ve: 0.24 ±0.08 vs. 0.47 ±0.18, P < 0.0001; MaxSlope: 0.09 ±0.14 vs. 0.28 ±0.29, P = 0.0166; IAUGC: 0.18 ±0.09 vs. 0.55 ±0.34, P = 0.0001). Meanwhile, malignant nodules presented higher ADC than benign nodules (0.0016 ±0.0006 vs. 0.0012 ±0.0003, P = 0.0019). K_trans and IAUGC showed the best diagnostic performance with AUCs [1.0, 95%CI (0.99–1.0); 0.93, 95%CI(0.85–1.0), respectively].

Conclusion: Malignant pulmonary lesions had higher values of K_trans, Ve, Kep, MaxSlope, and IAUGC compared to benign pulmonary lesions. Overall, perfusion parameters of DCE-MRI facilitate discrimination between benign from malignant pulmonary nodules.

Objective: The objective of this study was to quantify the extent of interstitial lung abnormalities (ILA) in a non-smoking asymptomatic urban cohort in China using low-dose CT (LDCT) and to analyze the age-related pathological changes.

Methods: We retrospectively analyzed clinical data and chest LDCT images from a cohort of 733 subjects who were categorized into 3 groups: 18–39, 40-59, and ≥60 years old according to age. Furthermore, we selected 40 cases of wax-embedded lung tissue blocks archived after pulmonary bullectomy and the same age groups were categorized. Four representative CT signs of ILA, including interlobular septal thickening (ILST), intralobular interstitial thickening (ILIT), ground-glass opacity (GGO), and reticular shadow (RS), were semi-quantified based on the percentage of the affected area. The scores and distribution of four CT signs of ILA were compared between different sex and age groups. The age-related pathological changes were analyzed.

Results: The ILA findings were found predominantly in the lower lobes and the subpleural region. The semi-quantitative scores of four CT signs in all subjects under 40 were 0. However, in subjects over 40 years old, the scores gradually increased with age, although most of them remained low. The size of the alveoli increased, the number of alveoli decreased, the alveolar septum became thinner, and the number of ATII cells increased with age. A statistically significant difference was observed among the different age groups (χ²=50.624, P=0.033; χ²=80.000, P=0.043; χ²=33.833, P=0.000; χ²=13.525, P=0.031). The macrophage population and the percentage of collagen fibers in the alveolar septum increased, while the percentage of elastic fibers decreased with age. There was no significant difference among the different age groups (χ²=19.817, P=0.506; χ²=52.419, P=0. 682; χ²=54.868, P=0.518).

Conclusion: When the four CT signs mentioned above are in the upper central area, and the score has a medium or high score, it is crucial to determine the underlying pathological causes. ILA may be the result of chronic lung injury.

Aims: The main objective of the investigation is to utilize 2-D colored fundus retina scans to determine if an individual possesses DR or not. In this regard, Engineering-based techniques such as deep learning and neural networks play a methodical role in fighting against this fatal disease.

Methods: In this research work, a Computational Model for detecting DR using Convolutional Neural Network (DRCNN) is proposed. This method contrasts the fundus retina scans of the DR-afflicted eye with the usual human eyes. Using CNN and layers like Conv2D, Pooling, Dense, Flatten, and Dropout, the model aids in comprehending the scan's curve and color-based features. For training and error reduction, the Visual Geometry Group (VGG-16) model and Adaptive Moment Estimation Optimizer are utilized.

Results: The variations in a dataset like 50%, 60%, 70%, 80%, and 90% images are reserved for the training phase, and the rest images are reserved for the testing phase. In the proposed model, the VGG-16 model comprises 138M parameters. The accuracy is achieved maximum rate of 90% when the training dataset is reserved at 80%. The model was validated using other datasets.

Conclusion: The suggested contribution to research determines conclusively whether the provided OCT scan utilizes an effective method for detecting DRaffected individuals within just a few moments.

Objective: To address this problem, this paper proposes a joint model called mSegResRF-SPECT, which accomplishes for the first time the task of classifying whole-body bone scan images on a public SPECT dataset [BS-80K] for the diagnosis of bone metastases.

Methods: The mSegResRF-SPECT adopts a multi-bone region segmentation algorithm to segment the whole body image into 13 regions, ResNet34 as an extractor to extract the regional features, and a random forest algorithm as a classifier.

Results: The experimental results of the proposed model show that the average accuracy, sensitivity, and F1 score of the model on the BS-80K dataset reached SOTA.

Conclusion: The proposed method presents a promising solution for better bone scan classification methods.

Methods: The proposed methodology hinges on a patch antenna operating at 2.4 GHz and a bone phantom housing a simulated fracture, where the antenna is scanned. The collected signals are then processed with Delay-and-Sum (DAS), and Delay-Multiply-and-Sum (DMAS) reconstruction algorithms. The resulting images offer visual insights into the location of fractures.

Results: Through experimentation, the efficacy of the images varies considerably in terms of their capacity for noise and artifact suppression. While DAS exhibits reasonable effectiveness, it suppresses noise and artifacts comprehensively. In contrast, DMAS offers clearer and more precise images of bone fractures.

Conclusion: In summary, the research introduces a cost-effective and non-invasive strategy for detecting bone fractures. By involving a patch antenna at 2.4 GHz, along with image reconstruction algorithms like DMAS and DAS, one can effectively visualize the location of bone fractures. The experimental results highlight the superiority of DMAS over DAS in terms of contrast resolution, making it a highly promising avenue for fracture detection.

Case Presentation: We report a case of a 73-year-old patient with small intestinal smooth muscle sarcoma with hepatic metastasis. No significant abnormalities were seen on examination of the abdomen. We performed abdominal enhancement CT, contrast-enhanced ultrasonography (CEUS), and ultrasoundguided pelvic mass puncture biopsy, and we found a heterogeneous density and echogenicity of the pelvic mass, and the enhancement was progressive with sustained hyperenhancement. The postoperative pathology was smooth muscle sarcoma of the small intestine. The typical fast-in, fast-out bull's-eye sign of metastases, characterized the liver presented with multiple hypodense and echogenic nodules and the enhancement. The clinical presentation, imaging, histologic features, and treatment are also discussed in this article.

Conclusion: This article briefly reviews the literature on small intestinal leiomyosarcoma. The purpose of this case report is to emphasize the specificity of the case and evaluate the imaging presentation of ultrasound (US) and CEUS and the main differential diagnosis of this rare gastrointestinal tumor.

Case Presentation: A 64-year-old female presented with a huge thyroid mass resulting in compressive myelopathy and was diagnosed as CCV-PTC, not anaplastic carcinoma. After multidisciplinary discussions, we decided to proceed with otolaryngological, thoracic, and orthopaedic surgery. All tumours were unresectable, and we planned to proceed with R2 resection to resolve the gait disturbance and anterior fusion to resolve spinal instability.

Conclusion: Advanced-stage thyroid cancer is relatively uncommon, but desirable treatment effects can be expected through accurate pathological diagnosis. Immunohistochemical staining and tissue-specific markers can be helpful.

Methods: In this paper, we propose an improved method for the automatic classification of common liver lesions based on deep learning techniques and the variation of Hounsfield Unit densities on CT images with and without contrast. Hounsfield Unit is used to locate liver lesions accurately and support data labeling for classification. We construct a multi-phase classification model developed on the deep neural networks of Faster R-CNN, R-FCN, SSD, and Mask R-CNN with the transfer learning approach.

Results: The experiments are conducted on six scenarios with multi-phase CT images of common liver lesions. Experimental results show that the proposed method improves the detection and classification of liver lesions compared with recent methods because its accuracy achieves up to 97.4%.

Conclusion: The proposed models are very useful to assist doctors in the automatic segmentation and classification of liver lesions to solve the problem of depending on the clinician’s experience in the diagnosis and treatment of liver lesions.

Objective: To evaluate and compare the safety and effectiveness of aspiration-type semi-automatic cutting biopsy needles and non-aspiration-type biopsy needles when performing computed tomography (CT)-guided core needle biopsies (CNBs).

Methods: A total of 106 patients underwent CT-guided CNB for chest lesions between June 2013 and March 2020 at our hospital. Non-aspiration-type cutting biopsy needles were used in 47 of these patients, while aspiration-type needles were used in the remaining 59 patients. All needles used were 18- or 20-gauge biopsy needles. Parameters, like forced expiratory volume in 1-second percent (FEV1.0%), the maximum size of the target lesion, puncture pathway distance in the lung, number of needle passes, procedure time, diagnostic accuracy, and incidence of complications, were measured. Comparisons were made between the needle-type groups.

Results: No significant difference was observed in terms of diagnostic accuracy. However, the procedure time was shorter and a lesser number of needle passes were required with the aspiration-type cutting biopsy needle compared to the non-aspiration-type needle. Pneumothorax and pulmonary hemorrhage were the complications encountered, however, their incidence was not significantly different between the two types of needles.

Conclusion: The aspiration-type semi-automatic cutting biopsy needle had similar diagnostic accuracy as the non-aspiration-type biopsy needle, with added advantages of a lesser number of needle passes and shorter procedure time.

Purpose: This research aimed to create and assess non-invasive diagnostic techniques using pre-operative computed tomography (CT) radiomics models to predict the recurrence of MWA in pulmonary malignancies.

Materials and Methods: We retrospectively enrolled 116 eligible patients with pulmonary malignancies treated with MWA. we separated the patients into two groups: a recurrence group (n = 28) and a non-recurrence group (n = 88), following the modified Response Evaluation Criteria in Solid Tumors (m-RECIST) criteria. We segmented the preoperative tumor area manually. We expanded outward the tumor boundary 4 times, with a width of 3 mm, using the tumor boundary as the baseline. Five groups of radiomics features were extracted and screened using max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) regression. Weight coefficients of the aforementioned features were used to calculate the Radscore and construct radiomics models for both tumoral and peritumoral areas. The Radscore from the radiomics model was combined with clinical risk factors to construct a combined model. The performance and clinical usefulness of the combined models were assessed through the evaluation of receiver operating characteristic (ROC) curves, the Delong test, calibration curves, and decision curve analysis (DCA) curves.

Results: The clinical risk factor for recurrence after MWA was tumor diameter (P < 0.05). Both tumoral and four peritumoral radiomics models exhibited high diagnostic efficacy. Furthermore, the combined 1 (C1)-RO model and the combined 2 (C2)-RO model showed higher efficacy with area under the curve (AUCs) of 0.89 and 0.89 in the training cohort, and 0.93 and 0.94 in the validation cohort, respectively. Both combined models demonstrated excellent predictive accuracy and clinical benefit.

Conclusion: Preoperative CT radiomics models for both tumoral and peritumoral regions are capable of accurately predicting the recurrence of pulmonary malignancies after MWA. The combination of both models may lead to better performance and may aid in devising more effective preoperative treatment strategies.

Methods: We used the PICO (Patient/Population/Problem, Intervention, Comparison, Outcome) scheme to formulate the research question and construct our search terms. Studies were systematically examined from the available literature using the constructed search terms from PubMed, and ScienceDirect according to the PRISMA guidelines. The quality of the included studies was assessed using the QUADAS-2 checklist. The characteristics of each included study such as the study design, population, index test, and reference standard, were extracted. The sensitivity, specificity, and AUC for each study were also reported.

Results: In this systematic review, 14 studies were analyzed. Eight studies showed that AI was more accurate than radiologists in evaluating mammographic images, while one comprehensive study found AI to be less precise. Studies that reported sensitivity and specificity without radiologist intervention showed performance scores ranging from 16.0% to 89.71%. With radiologist intervention, sensitivity was between 62% to 86%. Only three studies reported a specificity of 73.5% to 79%. The AUC of the studies was between 0.79 and 0.95. Thirteen studies were retrospective, and one was prospective.

Conclusion: There's inadequate evidence on the effectiveness of AI-based deep learning for breast cancer screening in clinical settings. More research is needed, including studies evaluating accuracy, RCTs, and large-scale cohort studies. This systematic review found that AI-based deep learning improves radiologists' accuracy, especially for novice radiologists. Younger, tech-savvy clinicians may be more accepting of AI. Although it can't replace radiologists, the encouraging results suggest it will play a significant role in identifying breast cancer in the future.

Objective: This study aimed to explore the abnormality of brain functional networks in lung cancer patients with post-chemotherapy by modular edge analysis.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed on 40 patients after chemotherapy, 40 patients before chemotherapy and 40 normal controls. Patients in all three groups were age and sex well-matched. Then, modular edge analysis was applied to assess brain functional network alterations.

Results: Post-chemotherapy patients had the worst MoCA scores among the three groups (p < 0.001). In intra-modular connections, compared with normal controls, the patients after chemotherapy had decreased connection strengths in the occipital lobe module (p < 0.05). Compared with the nonchemotherapy group, the patients after chemotherapy had decreased connection strengths in the subcortical module (p < 0.05). In inter-modular connections, compared with normal controls, the patients after chemotherapy had decreased connection strength in the frontal-temporal lobe modules (p < 0.05). Compared with the non-chemotherapy group, the patients after chemotherapy had decreased connection strength in the subcortical-temporal lobe modules (p < 0.05).

Conclusion: The results reveal that chemotherapy can disrupt connections in brain functional networks. As far as we know, the use of modular edge analysis to report changes in brain functional brain networks associated with chemotherapy was rarely reported. Modular edge analysis may play a crucial part in predicting the clinical outcome for the patients after chemotherapy.

This page provides information about how to report adverse reactions to these medical devices, as well as what they are.

In many countries, post-marketing surveillance for medications has been initiated but is not as reliable and advanced as it is today. By monitoring adverse events related to medical devices, generating safety data, educating stakeholders, and recommending appropriate procedures and interventions, the Indian Pharmacopeia Commission established the committee on July 6, 2015.

Monitoring adverse events related to medical device usage can increase patient safety. On the basis of safety data gathered and generated, the Central Drugs Standard Control Organization (CDSCO) will make recommendations about the safe use of medical devices in the Indian population.]]> https://www.benthamscience.comarticle/139656Background: The recent advancements and detailed studies in the field of 3D bioprinting have made it a promising avenue in the field of organ shortage, where many patients die awaiting transplantation. The main challenges bioprinting faces are precision during printing, vascularization, and cell proliferation. Additionally, overcoming these shortcomings requires experts from engineering, medicine, physics, etc., and if accomplished, it will significantly benefit humankind.

Objective: This paper covers the general roadmap of the bioprinting process, different kinds of bioinks, and available bioprinters. The paper also includes designing the anatomical structure, which is the first phase of the bioprinting process, and how AI has facilitated this entire process of 3D printing in healthcare and associated applications like medical modelling and disease modelling.

Methods: The process of 3D bioprinting involves meticulous structure designing of the anatomical structure under study, which forms the base of the entire bioprinting process. One of the significant applications of 3D printing in healthcare is Medical Modelling and Disease Modelling, which requires the detection of disease in anatomy and its delineation from the rest of anatomy for meticulous creation of ROI using sophisticated segmentation software(s) for the construction of 3D models of diseased anatomy and healthy anatomical surroundings.

Conclusion: The study concluded that bioprinting is the future of the worldwide organ transplantation crisis. Anatomical accuracy is an important aspect that must be considered while producing 3D models. The reproduction of patient-specific 3D models requires human rights and ethics approval under four principles of ethics in healthcare: autonomy, non-maleficence, beneficence, and justice.

Materials and Methods: Using standard T2* relaxation time measurement protocols, in-vivo and ex-vivo MRI data with water and fat nominally in phase or out of phase relative to each other were acquired on a 7 T small animal scanner. Based on a total of 24 different echo times, PDFF maps were calculated in a magnitude-based approach. After identification of the decisive error-prone variables, pixel-wise error estimation was performed by simple propagation of uncertainty. The method was then used to evaluate PDFF data acquired for an explanted mouse liver and an in vivo mouse liver measurement.

Results: The determined error maps helped excluding measurement errors as cause of unexpected local PDFF variations in the explanted liver. For in vivo measurements, severe error maps gave rise to doubts in the acquired PDFF maps and triggered an in-depth analysis of possible causes, yielding abdominal movement or bladder filling as in vivo occurring reasons for the increased errors.

Conclusion: The combination of pixel-wise acquisition of PDFF data and the corresponding error maps allows for a more specific, spatially resolved evaluation of the PDFF value reliability.

Methods: A partial taxonomy of the GBM problems tackled with ML methods was formulated with 15 subcategories grouped into four categories: extraction of characteristics from tumoral regions, differentiation, characterization, and problems based on genetics.

Results: The dominant techniques in solving these problems are: Radiomics for feature extraction, Least Absolute Shrinkage and Selection Operator for feature selection, Support Vector Machines and Random Forest for classification, and Convolutional Neural Networks for characterization. A noticeable trend is that the application of Deep Learning on GBM problems is growing exponentially. The main limitations of ML methods are their interpretability and generalization.

Conclusion: The diagnosis, treatment, and characterization of GBM have advanced with the aid of ML methods and MRI data, and this improvement is expected to continue. ML methods are effective in solving GBM-related problems with different precisions, Overall Survival being the hardest problem to solve with accuracies ranging from 57%-71%, and GBM differentiation the one with the highest accuracy ranging from 80%-97%.

Objective: This study aimed to investigate the effectiveness of the ADC histogram analysis in showing the relationship between breast cancer prognostic factors and ADC parameters.

Methods: This study is a retrospective observational descriptive study. ADC histogram parameters were evaluated in all tumor volumes of 67 breast cancer patients. Minimum, 5, 10, 25, 50, 75, 90, 95 percentiles, maximum, mean, median ADC values, kurtosis, and skewness were calculated. Breast MRI examinations were performed on a 3T MR scanner. We evaluated the fibroglandular tissue density of bilateral breasts, background enhancement, localization of masses, multifocality-multicentricity, shape, rim, internal contrast enhancement, and kinetic curve on breast MRI. BIRADS scoring was performed according to breast MRI. Pathologically, histologic type, histologic grade, HER 2, Ki 67, ER-, and PR status were evaluated.

Results: A significant correlation was found between tumor volume and ADC scores. There is a significant correlation between min ADC values (p< 0.031), max ADC (p< 0.001), and skewness (p< 0.019). A significant correlation was found between tumor kurtosis and lymph nodes (p< 0.029). There was a significant difference in ADC _mean, ADC_10%, ADC_25%, ADC_50%, ADC_75%, ADC_90%, ADC _95% and ADC_max values depending on ER-and PRstatus. (for ER p = 0.004, p = 0.018, p = 0.010, p = 0.008, p = 0.004, p = 0.004, p = 0.02, p = 0.02 and p = 0.038, for PR p < 0.001, p = 0.028, p = 0.011, p = 0.001, p < 0.001, p =<0.001, p < 0.001, and p < 0.001, respectively; p < 0.05). These values were lower in ER-and PR-positive status than in ER-and PR-negative receptor status. According to HER2 status, there was a statistically significant difference in ADC_5% and measurements of the lesions (p = 0.041; p < 0.05). Our study found no significant correlation between other prognostic factors, such as histological grade, Ki-67 indices, and ADC values.

Conclusion: Our study found a significant difference between tumor volume, ER- and, PR status, HER2, and lymph node involvement, and some ADC values among prognostic factors for breast cancer. Furthermore, ADC histogram analysis can provide additional value in predicting some prognostic factors.

Objective: Task-fMRI based on Chinese character reading tasks with different intelligibility was used to explore activated brain regions and their cognitive changes.

Methods: Volunteers were randomly recruited using advertisements. Forty volunteers were recruited based on strict inclusion and exclusion criteria, and 40 volunteers were recruited. Brain function data of 40 healthy right-handed volunteers in fuzzy/clear Chinese reading tasks were collected using a Siemens Skyra 3.0T magnetic resonance scanner. Data were preprocessed and statistically analyzed using the statistical software SPM12.0 to observe the activation of the cortex and analyze its characteristics and possible changes in cognitive function.

Results: Task-fMRI analysis: (1) The main brain regions activated in fuzzy/clear reading tasks were located in the occipital visual cortex (P < 0.001); (2) a paired sample t-test suggested that there was a significant difference in BOLD signals in the brain regions activated by fuzzy/clear reading tasks (P < 0.001, equiv Z = 4.25). Compared with the fuzzy reading task, the brain regions more strongly activated in the clear reading task were mainly located in the right superior frontal gyrus and the bilateral temporal lobe. Compared with the clear reading task, the brain region that was more strongly activated in the fuzzy reading task was mainly located in the right fusiform gyrus.

Conclusion: Clear Chinese character information mainly activates the dorsal stream of the visual-spatial network. This reflects the information transmission of the brain after understanding the text content and is responsible for guiding and controlling attention. Fuzzy words that cannot provide clear text content activate the fusiform gyrus of the ventral stream of the visual-spatial network, strengthening the function of orthographic processing.

Case Presentation: A 46-year-old middle adulthood male presented with unexplained fever, night sweats, abdominal distension for 3 months, and weight loss of around 7kg during almost 6 months, which is extremely similar to lymphoma from the clinical features and imaging examinations. After a clear diagnosis, the case not only obtained the opportunity of surgery but was also exempted from radiotherapy. The treatment effect was good. We report a case of rare metastatic embryonal carcinoma, which can provide insight into the diagnosis and treatment of embryonal carcinoma.

Conclusion: Metastatic embryonal carcinoma of abdominal lymph nodes can be highly similar to lymphoma; the diagnosis can only be based on clinical manifestations and imaging examination but also combined with patient history, tumor markers and biochemical examination. However, the final diagnosis depends on pathological biopsy.

Methods: The clinical data and ultrasound images of 160 patients with superficial lymphadenopathy (58 benign lymph nodes, 62 lymphoma, 40 metastatic lymph nodes) admitted to our hospital from January 2020 to November 2022 were retrospectively studied. Patients were randomly divided into a training set and test set according to the ratio of 6:4. Firstly, the radiomics features of each lymph node were extracted, and then a series of statistical methods were used to avoid over-fitting. Then, the gradient boosting machine(GBM) was used to build the model. The area under receiver(AUC) operating characteristic curve, precision, recall rate and F1 value were calculated to evaluate the effectiveness of the model.

Results: Ten robust features were selected to build the model. The AUC values of benign lymph nodes, lymphoma and metastatic lymph nodes in the training set were 1.00, 0.98 and 0.99, and the AUC values of the test set were 0.96, 0.84 and 0.90, respectively.

Conclusion: It was a reliable and non-invasive method for the differential diagnosis of lymphadenopathy based on the model constructed by machine learning.

Background: Over recent years, diagnostic imaging has progressed from a state of commencement to an advanced level. Numerous modern imaging procedures have evolved. Although contemporary medical imaging comprises image exhibition together with image refining, computer-aided diagnosis (CAD), image inscribing and conserving, and image transference, the majority of which are embraced in picture documentation and communication processes.

Aim: This review targets to encapsulate toxicology information on skin cancer unpredictability essential to interpretation measures, report important factor that helps in defining skin cancer condition, and possible medical care alternatives or medical attention endorsed referring to diverse aspects involving the size and site of malignancy, the complications, patient’s priority and well being. We concisely review various therapy alternatives, methods of radiation autoimmunity, prime observational study designs of medical and distinct radiation resources and cancer risks, and current analysis methodologies and research precision.

Conclusion: The detail of this paper covers a brief review of research and evolution in medical imaging discipline and mechanism. This review considers the physiology of melanocytes and the pathogenesis of skin cancer using medical imaging. Also, a description of risk factors, prevention methods, screening, various diagnosis methods and different stages of skin cancer, sub-types and different types of treatment methods is provided in this paper for research and development.

Objective: To evaluate the relationship between the imaging and histopathological features of breast cancer in women aged under 40 years.

Methods: In our center, 537 suspicious lesions were detected in a total of 15,223 adult female patients under 40 years who were evaluated by breast ultrasonography (US). As a result of the mammographic, histopathological, and immunohistochemical analysis, 101 lesions meeting the study criteria were included in the sample.

Results: The luminal subtypes of breast cancer mostly visualized as irregularly shaped spiculated lesions with calcification and architectural distortion mammography and presented as masses that were sometimes accompanied by increased echogenicity in the surrounding tissue on US. The human epidermal growth factor receptor 2 (HER2) enriched subtypes mostly had microlobulated or indistinct margins with heterogeneous echoes accompanied by high calcification on mammography. The triple-negative (TN) subtypes generally appeared as microlobulated lesions with angular or indistinct margins, hypo echogenicity, posterior enhancement or shadowing, and vascularization.

Conclusion: Some radiological features of breast cancer in young women were found to be associated with molecular subtypes similar to other age groups in the literature. However, unlike other age groups, the incidences of the HER2-enriched subtype presenting with only calcification, TN subtypes presenting with circumscribed masses, and calcification were found to be low among the young women in our study.

Methods: This retrospective study collected the clinicopathological and imaging data of 218 patients with EC in Yuncheng Central Hospital from March 2018 to May 2022. The patients were randomly divided into training group (n=152) and validation group (n= 66) according to the ratio of 7: 3. Based on the ADC, CE-sag, CE-tra, DWI, T2WI-sag-fs, T2WI-tra sequence images of each patient, the region of interest was manually segmented and the features were extracted. The four-step dimensionality reduction method based on max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and radiomics model construction. Independent predictors of clinicopathological features were screened by multivariate logistic regression analysis. The imaging model based on ADC, CE-sag, CE-tra, DWI, T2WI-sag-fs, T2WI-tra single sequence and combined sequence and the fusion model with clinicopathological features were constructed, and the nomogram was made. ROC curve, correction curve and decision analysis curve were used to evaluate the efficacy and clinical benefits of the nomogram.

Results: There was no significant difference in general clinical data between the training and validation groups (P > 0.05). After screening the extracted features, 16 radiomics features were obtained, which were all related to LVSI in EC patients (P < 0.05). The area under the ROC curve (AUC) of the six independent sequence radiomics models in the training group was 0.807, 0.794, 0.826, 0.794, 0.828, 0.824, respectively. The AUC corresponding to the radiomics model constructed by the combined sequence was 0.884, and the diagnostic efficiency was the best, which was verified in the validation group. The AUC of the nomogram constructed by the combined radiomics model and age maximum tumor diameter(MTD), lymph node enlargement (LNE) in the training group and the validation group were 0.914 and 0.912, respectively. The correction curve shows that the nomogram has good correction performance. The decision curve suggests that taking radiomics nomogram to predict LVSI net benefit when the risk threshold is > 10% is better than considering all patients as LVSI+ or LVSI-.

Conclusion: The combined model based on multi-parametric MRI radiomics features and clinical features has good predictive value for LVSI status in EC patients.

Methods: A total of 25 healthy participants with an average age of 35 years (20 men and 5 women) were selected in April 2022. Thermogram images were captured using a FLIR T series thermal camera. Conventional image processing techniques, such as filtering and edge detection, were used to preprocess thermograms. Next, the level set approach was used with the edge-detected pattern as an input to an automated segmented region of interest (ROI).

Results: Five metrics, namely Dice Coefficient, Tanimoto Index, Jaccard Index, Volume Similarity, and Structural Similarity, were used to assess the performance of the segmentation technique compared to ground truth, which showed 97.5%, 92.5%, 94.5%, 96.5%, and 96.5% correlation, respectively, between the segmented and the ground truth images with average values for both the eyes. Statistical analysis demonstrated that the contralateral portions of the ocular thermograms were significantly different in terms of vascular distribution between the left and right eyes (p < 0.005).

Conclusion: The level set method efficiently segmented the ROI in ocular thermograms with maximum correlation. According to the segmentation’s results, the model showed the dissimilarity between the contralateral parts of the left and right eyes in healthy cases.

Methods: The clinical accuracy of medical issues is compromised because innumerable classical fusion methods struggle to conserve all the prominent features of the original images. Furthermore, complex implementation, high computation time, and more memory requirements are key problems of transform domain methods. With the purpose of solving these problems, this research suggests a fusion framework for multimodal medical images that makes use of a multi-scale edge-preserving filter and visual saliency detection. The source images are decomposed using a two-scale edge-preserving filter into base and detail layers. Base layers are combined using the addition fusion rule, while detail layers are fused using weight maps constructed using the maximum symmetric surround saliency detection algorithm.

Results: The resultant image constructed by the presumed method has improved objective evaluation metrics than other classical methods, as well as unhindered edge contour, more global contrast, and no ringing effect or artifacts.

Conclusion: The methodology offers a dominant and symbiotic arsenal of clinical symptomatic, therapeutic, and biomedical research competencies that have the prospective to considerably strengthen medical practice and biological understanding.

Objective: The objective of the research is to implement an advanced modified threshold segmentation and classification model for early and accurate detection of lung cancer from CT images.

Methods: Using the Support Vector Machines (SVM) classifier as well as the Artificial Neural Network (ANN) classifier, the authors propose using Modified adaptive threshold segmentation as a segmentation approach for cancer detection. Here, Lung Image Database Consortium (LIDC) datasets, a collection of CT scans, are used as the video frames in an investigation to authorize the recitation of the suggested technique.

Results: Both quantitative as well as qualitative analyses are used to analyze the segmentation function of the anticipated algorithm. Both the ANN and SVM classifiers used in the suggested technique for lung cancer diagnosis achieve world-record levels of accuracy, with the former achieving a 96.3% detection rate and the latter a 97% rate of accuracy.

Conclusion: This innovation may have a major impact on the worldwide rate of lung cancer rate due to its ability to detect lung tumors in their earliest stages when they are most amenable to being avoided and treated. This method is useful because it provides more information and facilitates quick, precise decision-making for doctors diagnosing lung cancer in their patients.

Materials and Methods: A total of 12 patients with MSI-H CRLM and 96 patients with MSS CRLM were randomly divided into the training group and internal validation group according to the ratio of 7: 3 (training: 75 cases, validation: 33 cases). From the enhanced CT (portal phase) image data of patients, 788 radiomics features were extracted, and a random forest model was established with the optimal features selected. The receiver operating characteristics (ROC) curve analysis was performed to assess the model’s diagnostic efficacy.

Results: The training group comprised 8 patients with MSI-H CRLM and 67 patients with MSS CRLM, and the internal validation group included 4 patients with MSI-H CRLM and 29 patients with MSS CRLM. After feature selection, 7 radiomics features good for distinguishing MSI-H CRLM and MSS CRLM were screened out. The ROC curve analysis demonstrated that the random forest model had the AUC (area under the ROC curve) value 0.88, accuracy 0.85, sensitivity 0.85, specificity 0.92, and F1 score 0.88 in the training group. The model had an AUC value of 0.75, accuracy of 0.74, sensitivity of 0.81, specificity of 0.85, and F1_score of 0.78 in the internal validation group in identifying the MSI-H from the MSS CRLM. In order to evaluate the robustness of the overall model, the 788 features obtained were all applied to the 5-fold cross-validation, with the model being built on the random forest and analyzed with the ROC curve analysis. The AUC value of the model was 0.86 (P<0.05), accuracy value 0.91, sensitivity 0.60, and specificity 0.95.

Conclusion: The random forest prediction model built on the radiometric features extracted from enhanced CT images can be used to identify the MSI-H from the MSS CRLM and may provide effective guidance for clinical immunotherapy of CRLM patients with unknown MSI status.

Methods: A descriptive cross-sectional study was conducted, and the data was collected using an online survey google forms questionnaire disseminated through social media (Telegram, WhatsApp, and Twitter) as an electronic link. A total of 70 participants responded to the survey directly, and then, the data was analyzed using SPSS (Statistical Package for Social Science).

Results: Regarding the awareness of TI and MI, 64.3% of the participants were aware of TI and 65.7% of MI as safety ultrasound indices; moreover, 74.3% of the participants were aware of the ALARA principle “As Low as Reasonably Achievable.” Participants' knowledge concerning more heat production in pulsed Doppler ultrasound modes was poor (31.5%). Most of the sonographers, i.e, 77.1% were aware of the relationship between the risk of cavitation and MI, and 58.6% of the participants were acquainted with the current FDA output limits. In comparison, 58.6% of the participants were aware of the bioeffects of ultrasound contrast agents. There was no significant correlation between the educational level and the degree of awareness of ultrasound bioeffects and safety (P-value> 0.05).

Conclusion: In this study, it was found that sonographers were aware of the theoretical principles of ultrasound safety indices and the ALARA principle, although they had poor knowledge of ultrasound bioeffects in Doppler mode.

Methods: We searched the literature for studies on Google Scholar and PubMed using the keywords “Segmentation,” “Classification,” “medical image,” and “generative adversarial network.” Specifically, the initial search revealed 5423 publications after the removal of duplicated and non-accessible fulltext publications. Then, after the title and abstract screening, 680 underwent full-text screening. Finally, 121 studies were included in our final analysis after full-text screening.

Results: The date range of the studies covered in this review is from January 1, 2017, to the present. After a thorough screening and qualification assessment, 121 studies involving GAN-based applications in seven areas of medical images were included in the final methodological review. These areas included synthesis, classification, segmentation, conversion, reconstruction, denoising, and lesion detection. We further classified and summarized these papers into clinical applications, classification methods, and imaging modalities.

Conclusion: We thoroughly examined the latest research progress of GAN-based medical image augmentation. These techniques effectively alleviate the challenge of limited training samples for medical image diagnosis and treatment models. Furthermore, several critical issues associated with GANs, such as pattern collapse, instability, and lack of interpretability, require attention in future research.

Methods: Multi-parametric MRI images of 136 breast cancer patients were retrospectively analyzed, 95 cases were stratified into the training cohort, and 41 cases were selected for the test group. According to the pathological molecular typing, the patients were divided into 23 cases of triple-negative breast cancer and 113 cases of non-triple-negative breast cancer. ITK software was used to manually delineate the lesion volume region of interest (VOI), and the Pyradiomics package was used to extract radiomic features for screening and model building. The platform was then used to analyze the clinical and imaging risk factors of breast cancer to build a characteristic model separately. Finally, a radiomic nomogram was constructed by integrating the radiomic and independent clinical image features. The diagnostic performance of the model was assessed using ROC curves.

Results: Univariate and multivariate analyses showed that the menstrual cycle, glandular density, and skin thickening were risk factors for clinical imaging characteristics of triple-negative breast cancer. The Area Under the Curve (AUC) was 0.839 and 0.826 for univariate and multivariate analysis, respectively. After screening, 11 radiomic features participated in the calculation of the radiomic score, and its AUC in the test set was 0.803. Combining it further with clinical models, the AUC improved to 0.899.

Conclusion: The radiomic nomogram developed in this study has great value in the diagnosis of triple-negative breast cancer.

Methods: A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results.

Results: Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively.

Conclusion: AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients.

Key Messages:

• The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation.

• The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies.

• AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.

Materials and Methods: Thoracic CT was collected from 120 advanced NSCLC patients who suffered progression on first- or second-generation TKIs. Radiomics signatures were retrieved from the entire tumor. Pearson correlation and the least absolute shrinkage and selection operator (LASSO) regression method were adopted to choose the most suitable radiomics features. Clinical and radiological factors were assessed using univariate and multivariate analysis. Three Machine Learning (ML) models were constructed according to three classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), and RandomForest (RF), combining clinical and radiomic features. A nomogram combining clinical features and the rad score signature was built. The predictive ability of the nomogram was assessed by the ROC curve, calibration curve, and decision curve analysis (DCA).

Results: Multivariate regression analysis showed that two clinicopathological characteristics and two radiological features were highly correlated with the acquired T790M mutation, including the progression-free survival (PFS) of first-line EGFR TKIs (P = 0.029), the initial EGFR profile (P = 0.01), vascular convergence (P = 0.043), and air bronchogram (P = 0.030). The AUCs of clinical, radiomics, and combined models using RF classifiers for T790M mutation detection were 0.951 (95% confidence interval [CI] 0.911,0.991), 0.917 (95%CI 0.856,0.978), and 0.961 (95%CI 0.927,0.995) in the training cohort, respectively, higher than those of other classifier models.The calibration curve and Hosmer-Lemeshow Test showed good calibration power, and the DCA demonstrated a significant net benefit.

Conclusion: A radiomics-clinical nomogram based on CT radiomics proved valuable in non-invasively and efficiently predicting the acquired T790M mutation in patients who suffered progression on first-line TKIs.

However, in the vascular representation, these techniques determine, albeit to different extents, a cut of the weak vessels due to the necessary application of wall filters that cut the disturbing frequencies responsible for artifacts generated by pulsations of the vascular walls and surrounding tissues.

These filters cut a specific range of disturbing frequencies, regardless of whether they may be generated by low-flow vessels.

Recently, a new technology, called Ultrasound Microvascular Imaging (MicroV) has been developed, which is particularly sensitive to slow flows. This new mode is based on new algorithms capable of better selecting the low frequencies according to the source of origin and cutting only the disturbing ones, saving the frequencies originating from really weak flows.

When Ultrasound microvascular imaging is used, the vascular map is more detailed and composed of macro and microvasculature, with more subdivision branches, facilitating the interpretation of the normal and, consequently, the pathological.

This review aims to describe the vascular architecture of the testis with Ultrasound Microvascular Imaging (MicroV) in healthy testis, compared to traditional color/power Doppler, related to normal anatomy.

Objective: This study aimed to investigate the ultrasonic characteristics of fetal SBO and determine the optimal cutoff value for intestinal diameter to enhance prenatal ultrasound diagnosis.

Methods: We retrospectively analyzed the ultrasonic characteristics and postpartum data of 76 cases diagnosed with SBO. Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cutoff value for dilated intestinal diameter.

Results: Among the 76 cases, 31 displayed the “double bubble sign” on ultrasound, with 20 cases identified as annular pancreas, 6 as duodenal atresia, and 5 as duodenal membranous stenosis. In 45 cases, the lesions were located in the jejunal or ileal segment and exhibited intestinal dilatation above the lesion site, including 27 cases of small bowel atresia, 7 cases of membranous jejunal stenosis, and 11 cases of small bowel volvulus. Out of the 76 cases, 9 showed no abnormalities after birth. ROC curve analysis determined optimal cutoff values of 17.5mm and 10.5mm for predicting “double bubble sign” lesions in the gastric and duodenal widths. For predicting small intestinal dilatation, the optimal cutoff values for dilated width and length of the intestinal tube were 11.5mm and 21.5mm, respectively, with high sensitivity and specificity.

Conclusion: Ultrasonic imaging and changes in intestinal diameter provide valuable information for prenatal diagnosis and management of SBO. Establishing these cutoff values can improve the accuracy of prenatal ultrasound diagnosis for SBO.

Objective: The primary aim of this review was to study and explore the Nano lipid carrier, its advantages, patent preferences, and advancement of NLCs use in nose-to-brain drug delivery.

Methods: The objective of this study was to conduct a literature review on the development of NLC for nose-to-brain drug delivery. The review focused on NLC, its significant role in nose-to-brain delivery, and relevant patents. To achieve this goal, different review articles searched, were studied, and summarized from various sources such as research articles, review articles, books, scientific reports, and patents.

Conclusion: This review article discusses the potential benefits of NLCs in brain-targeting drug delivery through the intranasal route and key aspects of NLCs, including their structure composition, formulation technique, and characterization, which are crucial for developing a reliable drug delivery.

Objective: The aim of the current investigation was to find novel 2-chloroquinoline-3-carboxamide derivatives that target the Ephrin B4 (EPHB4) receptor to treat cancer.

Materials and Methods: Chem Axon Marvin Sketch 5.11.5 was used to create derivatives of 2-chloroquinoline-3-carboxamide. The physicochemical characteristics of compounds as well as their toxicity were predicted using SwissADME& the admet SAR online software’s. Molecular docking technology was used to examine the ligand-receptor interactions of 2-chloroquinoline-3-carboxamide derivatives with the target receptor (PDB- 6FNM) using a variety of software’s, including Autodock1.1.2,Procheck, ProtParam tool, Biovia Discovery Studio Visualizer v20.1.0.19295, MGL Tools 1.5.6, PyMOL, and were all included.

Results: All developed compounds were determined to be orally bioavailable, less toxic, and have acceptable pharmacokinetic properties according to in silico studies. In comparison to the traditional medication Erdafitnib, all new compounds displayed higher docking scores.

Conclusion: The increase in binding energy and the number of H-bonds created by novel derivatives with interactions at distances below 3.40A provide a helpful starting point for formulating and synthesizing compounds that are most suitable for additional research. The application of the 2- chloroquinoline-3-carboxamide moiety as a potential new cancer treatment candidate is supported by its pharmacokinetics &toxicological profile, which may aid medicinal chemists in conducting more in-depth in vitro, in vivo chemical and pharmacological studies.

Methods: A prediction model was developed based on a dataset of radiomic features obtained from 132 patients with lung cancer receiving IMRT. Dimension reduction was performed for the features using the maximum-relevance and minimum-redundancy (mRMR) algorithm, and the least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection for the IMRT-sensitivity prediction model. The model was constructed using binary logistic regression analysis and was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic curve, and decision curve analysis.

Results: Fifty features were selected from 1348 radiomic features using the mRMR method. Of these, three radiomic features were selected by LASSO logistic regression to construct the radiomics nomogram. The C-index of the model was 0.776 (95% confidence interval: 0.689–0.862) and 0.791 (95% confidence interval: 0.607–0.974) in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful.

Conclusion: Radiomic features have the potential to be applied to predict the short-term efficacy of IMRT in patients with inoperable lung cancer.

Morphology : They contain a solid matrix at room temperature and are thought to be superior to many other conventional lipids-based nanocarriers, such as solid lipid nanoparticles (SLNs), nanoemulsions, and liposomes because of their improved stability, drug loading capacity, good biocompatibility, enhanced permeability, bioavailability, extended half-life, fewer side effects, tissue- specific delivery and wide range of potential applications.

Significance : NLCs have multiple applications in the manufacturing of pharmaceuticals and cosmetics due to their ease of preparation, the feasibility of scale-up, non-toxic, improved targeting efficiency and potential for site-specific delivery via various routes of administration.

Scope of Review: This review enlightens about the most recent developments of NLCs as a drug delivery system, types of NLCs, current techniques to prepare NLCs, and characterization techniques that are essential for the development of safe, effective and stable formulation. It also encompasses the potential of using NLCs for various administration routes and recent developments in pharmaceutical applications with successful outcomes.

Conclusion: This review certainly provide great insight into formulation considerations using design experts and modification strategies for improved targeting. On the whole, NLCs are broadly explored and preferred lipid nanocarrier systems with several advantages.

Methods: We synthesized EF-AuNps using a direct reduction method and characterized the NPs by employing various techniques, including UV-visible spectroscopy, DLS, XRD, EDX, TEM, and FT-IR. The anti-proliferative activity against MDA-MB-231 cells was assessed using MTT and colony formation assays, alongside evaluating cell viability with PI-FACS and live/dead assays. Furthermore, a Western blot was performed to determine the mechanism of action of EFAuNps in TNBC cells.

Result: We successfully synthesized triangular EF-AuNps (<100nm) and observed a substantial inhibition of cell proliferation (IC₅₀ 18μg/ml). Compared to EF alone, EF-AuNps significantly enhanced cell death in TNBC cells, as confirmed by flow cytometry and viability assays. Besides, Western blot analysis verified that the expression of apoptotic-related signal proteins, such as survivin, caspase 3, and caspase 9, were modulated by EF-AuNps.

Conclusion: EF-AuNps showed higher anti-cancer efficacy than EF in the MDA-MB-231 cell line. These findings suggest the therapeutic potential of EF-AuNps for TNBC treatment, advocating for further preclinical and clinical investigations into this promising anti-cancer formulation.

Case Presentation: Herein, we report the case of a 55-year-old woman with breast cancer. She previously underwent extensive excision of the breast lesion with adjuvant chemotherapy and endocrine therapy. After 9 years, she presented with neck discomfort and examination suggested right thyroid metastasis and lymph node metastasis in the neck. Imaging showed pulmonary and bone metastases. Furthermore, the patient received endocrine therapy. After 7 months of follow- up, the patient survived without any new distant metastases. Thyroid metastases originating from breast cancer often unfold with a subtle, intricate nature, making early detection challenging. They tend to emerge inconspicuously, intertwining with widespread systemic metastases, hinting at a less favorable prognosis.

Conclusion: Given the unusual clinical indicators, identifying heterochronic thyroid metastases in patients with tumors poses a distinct challenge, requiring clinicians to navigate the follow-up process with heightened sensitivity. The key lies in timely detection and early intervention, factors that can significantly enhance the overall quality of life for patients.

Method: An introduction to the epidemiology of UTIs and detailed herbal nanoformulation treatment approach through novel intravaginal route is intended through this narrative review. UTIs are associated with significant morbidity and mortality, and they affect the quality of life of the affected patients. Multidrug-resistant bacteria and recurrent UTIs are becoming more common. Development of resistance, adverse effects of antibiotics, and other associated problems lead to establishing the research framework to find out the alternative approaches in controlling UTIs. Antibiotic- free treatments for uncomplicated urinary tract infections UTIs should be used, saving drugs for severe infections. Herbal medication might be used instead of antibiotics for uncomplicated UTIs, in addition to analgesics for purely symptomatic treatment.

Conclusion: This review identifies the pathophysiology of UTI, distinguish the intravaginal route as an alternative to oral delivery route, summarizes the management of urinary tract infections and highlights the anti-uropathogenic and anti-bactericidal effects of herbal approaches to prevent or treat urinary tract infections.

Methods: Numerous studies have illuminated the neuroprotective characteristics of spirulina, contributing to its positive influence on brain functionality. Primarily, spirulina boasts antioxidants, like phycocyanin and beta-carotene, that effectively counter oxidative stress and curb inflammation within the brain. This is particularly significant as these factors play roles in the advancement of neurodegenerative conditions like Parkinson's and Alzheimer's disease. Additionally, spirulina has demonstrated the capacity to enhance cognitive capabilities and enrich memory and learning aptitudes.

Results: Animal-based investigations have revealed that introducing spirulina can bolster spatial learning and memory, as well as guard against cognitive decline linked to aging. Research has indicated its potential in shielding against neurotoxins, encompassing heavy metals and specific environmental pollutants. Its potential to neutralize heavy metals and counteract free radicals contributes to these protective effects, potentially thwarting neuronal harm.

Conclusion: In conclusion, the extant scientific literature proposes that spirulina integration can elicit advantageous outcomes for brain health. Its antioxidative, neuroprotective, cognitiveenhancing, and mood-regulating properties present a promising avenue for bolstering brain health and potentially diminishing the susceptibility to neurodegenerative ailments. Nonetheless, further research, notably well-designed human clinical trials, is imperative to ascertain the optimal dosing, duration, and enduring consequences of spirulina supplementation concerning brain health.

Methods: First, the basic properties of the synthesized PDB hydrogel and the gatifloxacin-loaded PDB hydrogel were assessed. Secondly, the in vitro degradation rate of the drug-loaded PDB was measured in a simulated body fluid environment with pH 7.4/5.5. The release behavior of the drug-loaded PDB was studied using a dialysis method with PBS solution of pH 7.4/5.5 as the release medium. Finally, a mouse model of bacterial keratitis was established, and tissue morphology was observed using hematoxylin-eosin staining. Additionally, mouse tear fluid was extracted to observe the antibacterial effect of the gatifloxacin-loaded PDB hydrogel.

Results: The results showed that the PDB hydrogel had a particle size of 124.9 nm and a zeta potential of -23.3 mV, with good porosity, thermosensitivity, viscosity distribution, rheological properties, and high cell compatibility. The encapsulation of gatifloxacin did not alter the physical properties of the PDB hydrogel and maintained appropriate swelling and stability, with a high drug release rate in acidic conditions. Furthermore, animal experiments demonstrated that the gatifloxacin- loaded PDB hydrogel exhibited superior therapeutic effects compared to gatifloxacin eye drops and displayed strong antibacterial capabilities against bacterial keratitis.

Conclusion: This study successfully synthesized PDB hydrogel and developed a gatifloxacin drug release system. The hydrogel exhibited good thermosensitivity, pH responsiveness, stability, and excellent biocompatibility, which can enhance drug retention, utilization, and therapeutic effects on the ocular surface.

]]> https://www.benthamscience.comarticle/137299Respiratory disorders, such as tuberculosis, cystic fibrosis, chronic obstructive pulmonary disease, asthma, lung cancer, and pulmonary inflammation, are among the most prevalent ailments in today’s world. Dextran, an exopolysaccharide formed by Leuconostoc mesenteroides (slimeproducing bacteria), and its derivatives are investigated for several therapeutic utilities. Dextranbased drug delivery system can become an innovative strategy in the treatment of several respiratory ailments as it offers numerous advantages, such as mucolytic action, airway hydration, antiinflammatory properties, and radioprotective effect as compared to other polysaccharides. Being biocompatible, flexible hydrophilic nature, biodegradable, tasteless, odourless, non-mutagenic, watersoluble and non-toxic edible polymer, dextran-based drug delivery systems have been explored for a wide range of therapeutic applications, especially in lungs and respiratory diseases. The present article comprehensively discusses various derivatives of dextran with their attributes to be considered for drug delivery and extensive therapeutic benefits, with a special emphasis on the armamentarium of dextran-based formulations for the treatment of respiratory disorders and associated pathological conditions. The information provided will act as a platform for formulation scientists as important considerations in designing therapeutic approaches for lung and respiratory diseases.

With an emphasis on lung illnesses, this article will offer an in-depth understanding of dextran-based delivery systems in respiratory illnesses.

Objective: To determine the prevalence of dizziness and its related factors among older adults in Ardakan city, Yazd province, Iran, in 2022.

Methods: This cross-sectional study was conducted in four comprehensive health centers of Ardakan city with the participation of 260 elderly people aged ≥60 years, who were randomly included in the study. Data were collected using a series of questionnaires which were completed by interviewing the participants. The variables of this study included demographic information, information related to the dizziness status, diseases, medications, use of mobility aids, physical activity level, fear of falling, quality of life and depression.

Results: The prevalence of dizziness among older adults of Ardakan city was 48.5%. In terms of the severity of dizziness, 38.8% had substantial dizziness, and 9.6% had mild dizziness. Dizziness was significantly related to physical activity (p<0.05), fear of falling (p <0.01), depression (p <0.05), history of falling (p <0.01), use of mobility aids (p <0.01), age (p<0.01), education level (p<0.01), gender (p <0.05) and diseases such as high blood pressure (p<0.05), hypothyroidism (p <0.01) and ear diseases(p <0.01). Also, elderly people with dizziness used significantly more medications such as sedatives (p<0.01), antihypertensive drugs (p <0.05) and cytotoxic drugs (p <0.01).

Conclusion: About half of the older adults experience dizziness, and this problem is associated with depression, fear of falling, history of falling, low physical activity, age, female gender, ear diseases, high blood pressure, and hypothyroidism. In addition, the use of medications such as anti- hypertensives, sedatives and cytotoxic drugs is related to dizziness. Families with elderly people, doctors and healthcare workers need to be educated and pay more attention to the above.

These innovative vesicular systems, based on bile salts, have been discussed in detail in the current review. The review addresses the composition of bilosomes, their creation and characterization processes. Previous research on bilosomes has been compiled, along with their applications and advantages over more traditional nanocarriers such as liposomes and niosomes. It also emphasizes the utilization of bilosomes and their stability.

The primary focus of nanomedicine is to engineer and utilize nanoscale materials, such as nanoparticles and nanostructures, to improve the effectiveness and precision of medical interventions. Nano-sized drug delivery systems can target specific cells or tissues, enhancing therapeutic outcomes and reducing side effects. These nanocarriers can penetrate biological barriers and accumulate at disease sites, enabling more efficient drug delivery and increasing the bioavailability of therapeutic agents. Furthermore, nanotechnology has opened new horizons in medical imaging. Nanoparticles can be engineered to be responsive to certain diseases or conditions, providing valuable information for early detection and precise diagnosis. Novel contrast agents based on nanomaterials have the potential to revolutionize imaging techniques, offering higher sensitivity and specificity, ultimately leading to improved patient outcomes.

Beyond diagnostics and drug delivery, nanotechnology is fostering breakthroughs in regenerative medicine. Nanomaterials can act as scaffolds, guiding tissue repair and promoting cellular regeneration. By harnessing the unique properties of nanoscale materials, tissue engineering, and organ transplantation may witness unparalleled advancements, bringing hope to countless patients awaiting life-saving treatments. However, the unprecedented potential of nanomedicine also raises ethical concerns that demand careful consideration. As nanotechnology progresses, concerns about the safety of nanomaterials, potential toxicity, and long-term effects must be addressed to ensure responsible and sustainable development.

Objective: This study is undertaken with the objective of examining the protective properties of melatonin against toxicity induced by high glucose in C28I2 human chondrocytes.

Methods: To determine non-cytotoxic concentrations of melatonin, various concentrations (10, 25, 50, 75, 100, 500, and 1000 μM) were assessed over different time periods (24, 48, and 72 hours) for their impact on C28I2 cell viability. Following this, cells underwent a pretreatment with melatonin (10 and 100 μM) for 6 hours. This was followed by subjecting the cells to a high concentration of glucose (75 mM) for 48 hours. Oxidative stress markers, including reactive oxygen species (ROS) and malondialdehyde (MDA), alongside the enzymatic activities of glutathione peroxidase, superoxide dismutase, and catalase were quantitatively assessed. To assess mitochondrial function, we evaluated the adenosine diphosphate (ADP)/adenosine triphosphate (ATP) ratio and measured the mitochondrial membrane potential (MMP).

Results: Elevated glucose levels significantly increased ROS and MDA levels, accompanied by reduced MMP, an elevated ADP/ATP ratio, and altered antioxidant enzyme activity. Pretreatment with melatonin effectively reversed the mitochondrial toxicity induced by high glucose (75 mM).

Conclusion: These results indicate that melatonin exhibits a protective influence against hyperglycemia- induced toxicity in chondrocyte mitochondria.

Methods: To achieve this, a comprehensive search was conducted in Persian medicine references and scientific databases to gather information on the traditional uses, chemical composition, and pharmacological effects of spinach. Studies that met the inclusion criteria were meticulously categorized, and relevant data were analyzed to draw insightful comparisons.

Results: Persian medicine describes spinach as a nutrient-rich, laxative, and fast-digesting agent with therapeutic effects on inflammation, lung diseases, back pain, sore throats, jaundice, urinary disorders, joint pain, eye inflammation, insomnia, dementia, and more. Modern studies have substantially corroborated these traditional uses, revealing that spinach possesses antioxidant, anti-inflammatory, anti-cancer, blood sugar-lowering, lipid-lowering, anti-obesity, neurological, ocular, and musculoskeletal effects.

Conclusion: Spinach exhibits a wide range of beneficial effects on various health conditions. Its widespread availability, low cost, and exceptional nutritional richness position it as a promising candidate for further investigation. Future studies should explore the clinical effectiveness of spinach in various diseases, while taking into consideration the principles emphasized in Persian medicine to guide research and inform therapeutic strategies.

Method: We crafted 29 distinct flavonoids using the aldol condensation mechanism via a chalcone intermediate to accomplish this. We meticulously characterized these newly formed compounds using a variety of spectroscopic techniques. We employed the widely recognized DPPH free radical method for the crucial antioxidant evaluation, a benchmark in such studies.

Result: The radical scavenging efficacy of our synthesized flavonoids was then meticulously compared to that of the positive control, ascorbic acid, renowned for its antioxidant prowess, and the IC50 values for each compound were calculated and examined. Surprisingly, our results showed that the flavonoids we tested had a wide range of antioxidant activity, with IC₅₀ values that ranged from 75.8 ± 8.30 to 397 ± 25.10 μg/mL.

Conclusion: Intriguingly, compounds US5, US13, US16, US17, US18, and US21 outshone even ascorbic acid in their antioxidant potential, displaying remarkable scavenging abilities against free radicals. This discovery holds promise for further exploration of these compounds as potential antioxidants with potential applications in health and wellness.

Methods: LIF was administered to rd12 mice by intravitreal microinjection. Apoptosis of retinal cells was analyzed by TUNEL assay. The degeneration of cone cells was evaluated by immunostaining of retinal sections and retinal flat-mounts. Signaling proteins regulated by LIF in the retinal and cultured cells were determined by immunoblotting.

Results: Intravitreal administration of LIF activated the STAT3 signaling pathway, thereby inhibiting photoreceptor apoptosis and preserving cones in rd12 mice. Niclosamide (NCL), an inhibitor of STAT3 signaling, effectively blocked STAT3 signaling and autophagy in cultured 661W cells treated with LIF. Co-administration of LIF with NCL to rd12 mice abolished the protective effect of LIF, suggesting that STAT3 signaling and autophagy mediate the protection.

Conclusion: LIF is a potent factor that protects cones in rd12 mice. This finding implies that LIF can be used in combination with gene therapy to achieve better therapeutic outcomes for patients with RPE65-associated LCA.

Objective: This review aims to summarize recent advances in the development of treatment strategies for FRDA, with a focus on potential drug candidates and their mechanisms of action.

Methods: A comprehensive literature search was conducted using various authentic scientific databases to identify studies published in the last decade that investigated potential treatment strategies for FRDA. The search terms used included “Friedreich's ataxia”, “treatment”, “drug candidates”, and “mechanisms of action”.

Results: To date, only one drug got approval from US-FDA in the year 2023; however, significant developments were achieved in FRDA-related research focusing on diverse therapeutic interventions that could potentially alleviate the symptoms of this disease. Several promising drug candidates have been identified for the treatment of FRDA, which target various aspects of frataxin deficiency and aim to restore frataxin levels, reduce oxidative stress, and improve mitochondrial function. Clinical trials have shown varying degrees of success, with some drugs demonstrating significant improvements in neurological function and quality of life in FRDA patients.

Conclusion: While there has been significant progress in the development of treatment strategies for FRDA, further research is needed to optimize these approaches and identify the most effective and safe treatment options for patients. The integration of multiple therapeutic strategies may be necessary to achieve the best outcomes in FRDA management.

Methods: We conducted a comprehensive analysis of the expression of SLC7A11 across 33 cancer types, employing datasets from public databases. Methods, such as Cox regression and survival analyses assessed its prognostic significance, while functional enrichment explored the biological processes tied to SLC7A11. The association between SLC7A11 expression, immune cell infiltration, and immune-related gene expression was also scrutinized.

Results: Notably, SLC7A11 expression was more pronounced in cancerous compared to normal samples and correlated with higher tumor grades. Increased SLC7A11 expression was linked to poor outcomes, particularly in liver hepatocellular carcinoma (LIHC). This protein's expression also showcased significant relationships with diverse molecular and immune subtypes.

Additionally, a prognostic nomogram was devised, integrating SLC7A11 expression and clinical variables. High SLC7A11 levels corresponded with cell growth and senescence pathways in various cancers and with lipid and cholesterol metabolism in LIHC. Furthermore, potential therapeutic compounds for LIHC with high SLC7A11 were identified. Real-time PCR (qPCR) and Western blot were conducted to explore the expression of SLC7A11 in tumor tissues and cancer cell lines.

Conclusion: In summation, this study emphasizes the prognostic and immunological importance of SLC7A11, spotlighting its potential as a therapeutic target in LIHC.

Methods: Its chemical component is completely complex combining honey, pollen, royal jelly, and propolis and consequently has a significant number of bioactive components such as nitro compounds, flavonoids, and polyphenols. It has shown various pharmacological impacts, such as anti-inflammatory, anti-viral, anti-microbial, and anti-tumor effects.

Results: In this review article, all relevant papers from various scholars and researchers were searched in Science Direct, Google Scholar, PubMed, and Scopus. Honeycomb has various activities and numerous pharmacological benefits and health advantages, and it can be considered a valuable source of nutraceuticals, and an effective natural medicine and organic product.

Conclusion: In this review, we have decided to discuss the importance of traditional treatment, and the pharmacological properties of Nidus Vespae.

Objective: This comprehensive review aims to elucidate the molecular targets of guggulipids and explore their cellular responses. Furthermore, it summarizes the findings from in-vitro, in-vivo, and clinical investigations related to arthritis and various inflammatory conditions.

Methods: A comprehensive survey encompassing in-vitro, in-vivo, and clinical studies has been conducted to explore the therapeutic capacity of guggulipid in the management of rheumatoid arthritis. Various molecular pathways, such as cyclooxygenase-2 (COX-2), vascular endothelial growth factor (VEGF), PI3-kinase/AKT, JAK/STAT, nitric oxide synthase (iNOS), and NFκB signaling pathways, have been targeted to assess the antiarthritic and anti-inflammatory effects of this compound.

Results: The research findings reveal that guggulipid demonstrates notable antiarthritic and anti-inflammatory effects by targeting key molecular pathways involved in inflammatory responses. These pathways include COX-2, VEGF, PI3-kinase/AKT, JAK/STAT, iNOS, and NFκB signaling pathways. in-vitro, in-vivo, and clinical studies collectively support the therapeutic potential of guggulipid in managing rheumatoid arthritis and related inflammatory conditions.

Conclusion: This review provides a deeper understanding of the therapeutic mechanisms and potential of guggulipid in the management of rheumatoid arthritis. The collective evidence strongly supports the promising role of guggulipid as a therapeutic agent, encouraging further research and development in guggulipid-based treatments for these conditions.