Prevalence of Psychiatric Morbidity and Alcohol use Disorders Among Adolescent Indigenous Tribals from Three Indian States.

Background: Among the Indian adolescents, the prevalence of psychiatric morbidity and alcohol use disorders (AUD) are 7.3% and 1.3%. However, no separate data are available for indigenous tribal populations. This study estimated the prevalence of psychiatric morbidity and AUD and associated socio-demographic factors among adolescents in the tribal communities in three widely varying states in India. Methods: Using validated Indian versions of the MINI 6.0, MINI Kid 6.0, and ICD-10 criteria, we conducted a cross-sectional survey from January to May 2019 in three Indian sites: Valsad, Gujarat (western India); Nilgiris, Tamil Nadu (south India); and East Khasi Hills district of Meghalaya (north-east India) on 623 indigenous tribal adolescents. Results: Aggregate prevalence of any psychiatric morbidity was 15.9% (95% CI: 13.1-19.0) (males: 13.6%, 95% CI: 10.0-18.1; females: 17.9%, 95% CI: 13.9-22.6), with site-wise statistically significant differences: Gujarat: 23.8% (95% CI: 18.1-30.2), Meghalaya: 17.1% (95% CI: 12.4-22.7), Tamil Nadu: 6.2% (95% CI: 3.2-10.5). The prevalence of diagnostic groups was mood disorders 6.4% (n = 40), neurotic- and stress-related disorders 9.1% (n = 57), phobic anxiety disorder 6.3% (n = 39), AUD 2.7% (n = 17), behavioral and emotional disorders 2.7% (n = 17), and obsessive-compulsive disorder 2.2% (n = 14). These differed across the sites. Conclusion: The prevalence of psychiatric morbidity in adolescent tribals is approximately twice the national average. The most common psychiatric morbidities reported are mood (affective) disorders, neurotic- and stress-related disorders, phobic anxiety disorder, AUD, behavioral and emotional disorders, andobsessive-compulsive disorder.

Best Practice Recommendations for Infertility Management.

Aim: The objective of this document is to provide guidance to the infertility specialist, gynecologist, embryologist, and counselors on the management of sub-fertility and brief them with the recent advances in the field. These recommendations will aid the aforementioned healthcare professionals in everyday clinical decisions about appropriate and effective care of their patients with the best available evidence. Participants: Extensive deliberations, discussion, and brainstorming was done between different reproductive medicine (RM) specialists, to develop the recommendations. Evidence: A systematic review of the literature published up to June 2019 was carried out using PubMed and Cochrane Collaboration Library. International guidelines, cohort studies, case series, observational studies, and randomized controlled trials currently available in the literature were reviewed. Indian data whatever available was also reviewed. Process: Primary meetings were held with leading reproductive medicine specialists. Each topic was brainstormed on by a group of reproductive medicine experts, who then prepared the first draft of the recommendation. These recommendations then were reviewed by Dr. Jaideep Malhotra, Dr. Gouri Devi, and Dr. Madhuri Patil along with the chief co-ordinator of each consensus to finalize the final draft. Conclusions: From the literature and discussion of the available evidence, several topics were identified for which evidence is inconsistent, insufficient, or non-existing. For the benefit of couples undergoing several treatments, the working committee recommends that future research, where possible in well-designed RCTs, will help in establishing evidence for a particular practice. In the Indian context, one also needs to take into consideration facilities and options available, cost, lack of insurance coverage, experimental nature of some advanced techniques used.

In silico network pharmacology analysis and molecular docking validation of Swasa Kudori tablet for screening druggable phytoconstituents of asthma.

Traditional medicines are impactful in treating a cluster of respiratory-related illnesses. This paper demonstrates screening active, druggable phytoconstituents from a classical Siddha-based poly-herbal formulation called Swasa Kudori Tablet to treat asthma. The phytoconstituents of Swasa Kudori are identified as Calotropis gigantea, Piper nigrum, and (Co-drug) Abies webbiana. Active chemical compounds are extracted with the Chemical Entities of Biological Interest (ChEBI) database. The gene targets of each compound are identified based on the pharmacological activity using the DIGEP-Pred database. Thirty-two genes showing Pa> 0.7 is screened, and the target markers are selected after performing gene overlap evaluation with the asthma genes reported in GeneCards and DisGeNET database. Ten markers are identified, such as ADIPOQ, CASP8, CAT, CCL2, CD86, FKBP5, HMOX1, NFE2L2, TIMP1, VDR, in common, listed as molecular targets. Pharmacokinetic assessment (ADME) revealed five natural drug compounds 2-5-7-trihydroxy-2-(4-hydroxyphenyl)-2,3-dihydro-4H-chromen-4-one, (+)-catechin-3'-methyl ether, futoenone, 5-hydroxy-4',7-dimethoxyflavanone, and pinocembrin showing better druggability. Further screening delineates the target (HMOX1) and drug (pinocembrin) for molecular docking evaluation. When docked with HO-1, Pinocembrin showed a binding affinity of -8.0 kcal/mol. MD simulation studies substantiate the docking studies as HO-1 in complex with pinocembrin remains stable in the simulated trajectory. The current findings exhibit the significance of traditional medicines as potential drug candidates against asthma.

In silico network pharmacology study on Glycyrrhiza glabra: Analyzing the immune-boosting phytochemical properties of Siddha medicinal plant against COVID-19.

Immunosenescence is a pertinent factor in the mortality rate caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The changes in the immune system are strongly associated with age and provoke the deterioration of the individual's health. Traditional medical practices in ancient India effectively deal with COVID-19 by boosting natural immunity through medicinal plants. The anti-inflammatory and antiviral properties of Glycyrrhiza glabra are potent in fighting against COVID-19 and promote immunity boost against the severity of the infection. Athimadhura Chooranam, a polyherbal formulation containing Glycyrrhiza glabra as the main ingredient, is recommended as an antiviral Siddha herb by the Ministry of AYUSH. This paper is intended to identify the phytoconstituents of Glycyrrhiza glabra that are actively involved in preventing individuals from COVID-19 transmission. The modulated pathways, enrichment study, and drug-likeness are calculated from the target proteins of the phytoconstituents at the pharmacological activity (Pa) of more than 0.7. Liquiritigenin and Isoliquiritin, the natural compounds in Glycyrrhiza glabra, belong to the flavonoid class and exhibit ameliorative effects against COVID-19. The latter compound displays a higher protein interaction to a maximum of six, out of which HMOX1, PLAU, and PGR are top-hub genes. ADMET screening further confirms the significance of the abovementioned components containing better drug-likeness. The molecular docking and molecular dynamics method identified liquiritigenin as a possible lead molecule capable of inhibiting the activity of the major protease protein of SARS-CoV-2. The findings emphasize the importance of in silico network pharmacological assessments in delivering cost-effective, time-bound clinical drugs.

Development of Artificial Intelligence-Teaching Assistant System for Undergraduate Nursing Students: A Field-Testing Study.

Keeping students engaged and motivated during online or class discussion may be challenging. Artificial intelligence has potential to facilitate active learning by enhancing student engagement, motivation, and learning outcomes. The purpose of this study was to develop, test usability of, and explore undergraduate nursing students' perceptions toward the Artificial Intelligence-Teaching Assistant System. The system was developed based on three main components: machine tutor intelligence, a graphical user interface, and a communication connector. They were included in the system to support contextual machine tutoring. A field-testing study design, a mixed-method approach, was utilized with questionnaires and focus group interview. Twenty-one undergraduate nursing students participated in this study, and they interacted with the system for 2 hours following the required activity checklist. The students completed the validated usability questionnaires and then participated in the focus group interview. Descriptive statistics were used to analyze quantitative data, and thematic analysis was used to analyze qualitative data from the focus group interviews. The results showed that the Artificial Intelligence-Teaching Assistant System was user-friendly. Four main themes emerged, namely, functionality, feasibility, artificial unintelligence, and suggested learning modality. However, Artificial Intelligence-Teaching Assistant System functions, user interface, and content can be improved before full implementation.

Genome-wide selection signatures address trait specific candidate genes in cattle indigenous to arid regions of India.

The peculiarity of Indian cattle lies in milk quality, resistance to diseases and stressors as well as adaptability. The investigation addressed selection signatures in Gir and Tharparkar cattle, belonging to arid ecotypes of India. Double digest restriction-site associated DNA sequencing (ddRAD-seq) yielded nearly 26 million high-quality reads from unrelated seven Gir and seven Tharparkar cows. In all, 19,127 high-quality SNPs were processed for selection signature analysis. An approach involving within-population composite likelihood ratio (CLR) statistics and between-population FST statistics was used to capture selection signatures within and between the breeds, respectively. A total of 191 selection signatures were addressed using CLR and FST approaches. Selection signatures overlapping 86 and 73 genes were detected as Gir- and Tharparkar-specific, respectively. Notably, genes related to production (CACNA1D, GHRHR), reproduction (ESR1, RBMS3), immunity (NOSTRIN, IL12B) and adaptation (ADAM22, ASL) were annotated to selection signatures. Gene pathway analysis revealed genes in insulin/IGF pathway for milk production, gonadotropin releasing hormone pathway for reproduction, Wnt signalling pathway and chemokine and cytokine signalling pathway for adaptation. This is the first study where selection signatures are identified using ddRAD-seq in indicine cattle breeds. The study shall help in conservation and leveraging genetic improvements in Gir and Tharparkar cattle.

A large aneurysmal bone cyst of mandible: A rare case report.

An aneurysmal bone cyst (ABC) is a rare benign tumor-like lesion, described as an expanding osteolytic lesion consisting of blood-filled spaces of variable sizes separated by connective tissue septa. It is frequently accompanied by multiple cystic lesions due to aggressive hemodynamics with reactive bone formation and a genetic predisposition. This lesion has been classified as an atypical giant cell tumor or benign bone cyst. ABC has an incidence of 0.5% and comprises approximately around 1.5% of all non-odontogenic and non-epithelial cysts of the jaws. About 50% of the ABCs are reported in long bones and the vertebral column and only 2% have been reported to involve jaw bones. This case report gives an overview of a very large size ABC of the mandible in a 14-year-old male patient.

Effectiveness of resilience interventions among cancer patients - A systematic review, meta-analysis, and meta-regression of randomised controlled trials.

PURPOSE: This systematic review, meta-analysis and meta-regression aimed to (1) evaluate the effects of resilience interventions on cancer patients' resilience and posttraumatic growth and (2) identify essential contents and features of resilience interventions. METHODS: A systematic review, meta-analysis, and meta-regression analyses were conducted. Published and unpublished randomised controlled trials evaluating the effects of resilience interventions among cancer patients were retrieved from nine databases, trial registries, and grey literature. The mean and standard deviation scores were used to compute the effect sizes. RESULTS: 23 randomised controlled trials comprising 3287 cancer patients were included. The random effects model found that resilience interventions had beneficial impacts on patients' resilience, posttraumatic growth, quality of life, anxiety, and depressive symptoms with moderate to large effects. The subgroup analyses concluded that theoretically guided interventions that adopted synchronous communication delivered physically had greater effect sizes. Interventions comprising skills that promote patients' cognitive flexibility, self-efficacy, self-esteem, self-regulation, and coping had greater effect in comparison with interventions lacking these components. The meta-regression analyses revealed that sample size has a significant effect on posttraumatic growth scores. More well-designed trials are needed to confirm the effects of resilience interventions. CONCLUSIONS: There is merit in utilizing resilience interventions to improve cancer patients' resilience and psychological well-being. Resilience interventions should be incorporated into the routine care for cancer patients and survivors.

Self-negligence and awareness among oral precancerous and cancer patients - A cross-sectional questionnaire study.

Background: The National Institute of Health and Family Welfare (NIHFW) reports that India has the highest global prevalence of oral cancers. The incidence is significantly more in developing countries when compared to the developed countries. Early detection is key to increasing the survival rate of the patients. Important causes for this late diagnosis could be self-negligence, lack of patient awareness about the causes and asymptomatic and subtle clinical presentation of the lesions. Aim: To assess the causes of self-neglect and awareness levels among oral cancer and pre-cancerous patients. Settings and Design: A cross-sectional questionnaire study was conducted among pre-cancerous and cancerous patients. Methods and Material: A questionnaire with 16 closed-ended questions was framed relating to the causes of self-neglect and awareness of the patients. A total of 45 patients were selected by convenient sampling technique from the Institutional Tumour Board register of which 62 per cent were male patients and 38 per cent were female patients. Statistical Analysis: Data analysis for demographic data, patients' awareness, and causes of self-neglect about precancer and cancer was done using SPSS Version 10. Results and Conclusions: The present study concluded that the patients had adequate awareness that deleterious habits could lead to cancer but had a low level of awareness about the other causes of cancer, symptoms and management options available to treat cancer. The study result emphasizes that the government should plan for more cancer-screening camps in order to prevent the progression of cancer and to increase the awareness. (Reference I.D.: 2015-05006 for funding the project. ICMR).

The global prevalence of overweight and obesity among nurses: A systematic review and meta-analyses.

BACKGROUND: Several studies have reported the prevalence of overweight and obesity in various countries but the global prevalence of nurses with overweight and obesity remains unclear. A consolidation of figures globally can help stakeholders worldwide improve workforce development and healthcare service delivery. OBJECTIVE: To investigate the global prevalence of overweight and obesity among nurses. DESIGN: Systematic review with meta-analysis. SETTING: 29 different countries across the WHO-classified geographical region. PARTICIPANTS: Nurses. METHODS: Eight electronic databases were searched for articles published from inception to January 2023. Two independent reviewers performed the article screening, methodological appraisal and data extraction. Methodological appraisal was conducted using Newcastle-Ottawa Scale (NOS). Inter-rater agreement was measured using Cohen's Kappa. Meta-analyses were conducted to pool the effect sizes on overweight, obesity and waist circumference using random effects model and adjusted using generalised linear mixed models and Hartung-Knapp method. Logit transformation was employed to stabilise the prevalence variance. Subgroup analyses were performed based on methodological quality and geographical regions. Heterogeneity was assessed using the I2 statistic. RESULTS: Among 10,587 studies, 83 studies representing 158,775 nurses across 29 countries were included. Based on BMI, the global prevalence of overweight and obesity were 31.2% (n = 55, 95% CI: 29%-33.5%; p < .01) and 16.3% (n = 76, 95% CI: 13.7%-19.3%, p < .01), respectively. Subgroup analyses indicated that the highest prevalence of overweight was in Eastern Mediterranean (n = 9, 37.2%, 95% CI: 33.1%-41.4%) and that of obesity was in South-East Asia (n = 5, 26.4%, 95% CI: 5.3%-69.9%). NOS classification, NOS scores, sample size and the year of data collected were not significant moderators. CONCLUSIONS: This review indicated the global prevalence of overweight and obesity among nurses along with the differences between regions. Healthcare organisations and policymakers should appreciate this increased risk and improve working conditions and environments for nurses to better maintain their metabolic health. PATIENT OR PUBLIC CONTRIBUTION: Not applicable as this is a systematic review. REGISTRATION: PROSPERO (ref: CRD42023403785) https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=403785. TWEETABLE ABSTRACT: High prevalence of overweight and obesity among nurses worldwide.

Monitoring early-season agricultural drought using temporal Sentinel-1 SAR-based combined drought index.

Early-season agricultural drought is frequent over South Asian region due to delayed or deficient monsoon rainfall. These drought events often cause delay in sowing and can even result in crop failure. The present study focuses on monitoring early-season agricultural drought in a semi-arid region of India over 5-year period (2016-2020). It utilizes hydro-climatic and biophysical variables to develop a combined drought index (CDI), which integrates anomalies in soil moisture conditions, rainfall, and crop-sown area progression. Synthetic aperture radar (SAR)-based soil moisture index (SMI) represents in situ measured soil moisture with reasonable accuracy (r=0.68). Based on the highest F1-score, SAR backscatter in VH (vertical transmit-horizontal receive) polarization with specific values for parameter threshold (-18.63 dB) and slope threshold (-0.072) is selected to determine the start of season (SoS) with a validation accuracy of 73.53%. The CDI approach is used to monitor early-season agricultural drought and identified drought conditions during June-July in 2019 and during July in 2018. Conversely, 2020 experienced consistently wet conditions, while 2016 and 2017 had near-normal conditions. Overall, the study highlights the use of SAR data for early-season agricultural drought monitoring, which is mainly governed by soil moisture-driven crop-sowing progression. The proposed methodology holds potential for effective monitoring, management, and decision-making in early-season agricultural drought scenarios.

Mechanistic Insights into Immune-Microbiota Interactions and Preventive Role of Probiotics Against Autoimmune Diabetes Mellitus.

Recent studies on genetically susceptible individuals and animal models revealed the potential role of the intestinal microbiota in the pathogenesis of type 1 diabetes (T1D) through complex interactions with the immune system. T1D incidence has been increasing exponentially with modern lifestyle altering normal microbiota composition, causing dysbiosis characterized by an imbalance in the gut microbial community. Dysbiosis has been suggested to be a potential contributing factor in T1D. Moreover, several studies have shown the potential role of probiotics in regulating T1D through various mechanisms. Current T1D therapies target curative measures; however, preventive therapeutics are yet to be proven. This review highlights immune microbiota interaction and the immense role of probiotics and postbiotics as important immunological interventions for reducing the risk of T1D.

Nutritional evaluation of some potential wild edible plants of North Eastern region of India.

Introduction: India's north-eastern hill region (NEH) is one of the biodiversity hotspots, inhabited by several tribal communities still maintaining their traditional food habits. Much of their food resources are drawn from wild sources. Materials and methods: Fourteen species of wild edible plants of high ethnic importance were collected from remote localities of Nagaland and Meghalaya states of the NEH region of India for nutritional profiling. Nutritional profiling of leaves of six species comprising Gynura cusimbua, Garcinia cowa, Herpetospermum operculatum, Plukenetia corniculata, Trichodesma khasianum, and Elatostemma sessile is conducted first time under present study. Samples were analyzed as per the Official Method of Analysis (AOAC) and standard methods. Results and discussion: The range of variation in proximate composition was observed for moisture (72-92%), protein (1.71-6.66%), fat (0.22-1.36%), dietary fibre (5.16-14.58%), sugar (0.30-3.41%), and starch (0.07-2.14%). The highest protein content (6.66%) was recorded in Herpetospermum operculatum, followed by Trichodesma khasianum (5.89%) and Plukenetia corniculata (5.27%). Incidentally, two of these also have high iron (>7.0 mg/100 g) and high zinc (>2.0 mg/100 g) contents, except Trichodesma khasianum, which has low zinc content. High antioxidant activities in terms of gallic acid equivalent (GAE) by the cupric ion reducing antioxidant capacity (CUPRAC) method ranged from 1.10 to 8.40 mg/100 g, and by the Fluorescence recovery after photobleaching (FRAP) method ranged from 0.10 to 1.9 mg/100 g, while phenol content ranged between 0.30 and 6.00 mg/100 g. These wild vegetables have high potential because of their nutritional properties and are fully capable of enhancing sustainability and improving ecosystem services. Efforts were also initiated to mainstream these resources, mainly for widening the food basket of native peoples.

Biochemical and antioxidant activity of wild edible fruits of the eastern Himalaya, India.

The eastern Himalayas, one of the important hotspots of global biodiversity, have a rich diversity of wild edible fruit trees. The fruits of these tree species have been consumed by the tribal people since time immemorial. However, there is limited information available on the biochemical and antioxidant properties of the fruits. Therefore, the present investigation was undertaken to study the physico-chemical and antioxidant properties of the nine most important wild fruit trees. Among the species, Pyrus pashia had the maximum fruit weight (37.83 g), while the highest juice (43.72%) and pulp content (84.67%) were noted in Haematocarpus validus and Myrica esculenta, respectively. Maximum total soluble solids (18.27%), total sugar (11.27%), moisture content (88.39%), ascorbic acid content (63.82 mg/100 g), total carotenoids (18.47 mg/100 g), and total monomeric anthocyanin (354.04 mg/100 g) were recorded in H. validus. Docynia indica had the highest total phenolic content (19.37 mg GAE/g), while H. validus recorded the highest total flavonoids and flavanol content. The antioxidant activities of the different fruits ranged from 0.17 to 0.67 IC50 for DPPH activity and 3.59-13.82 mg AAE/g for FRAP. These fruits had attractive pigmentation of both pulp and juice and were a good potential source for the extraction of natural edible color in the food industry. The fruits also possess high market prices; Prunus nepalensis fetched $ 34.10-$ 141.5 per tree. Therefore, these fruits are rich sources of antioxidants, pigments and have a high market value for livelihood and nutritional security.

Experiences of simulation-based learning among undergraduate nursing students: A systematic review and meta-synthesis.

OBJECTIVES: We aimed to examine the experiences of simulation-based learning (SBL) among undergraduate nursing students. DESIGN: We conducted a systematic review and meta-synthesis on the experiences among undergraduate nursing studies who received SBL. DATA SOURCES: We searched through six databases namely PubMed, CINAHL, Scopus, Web of Science, Embase, ProQuest, for qualitative studies published from January 2011 to January 2022. REVIEW METHODS: A meta-synthesis was conducted according to the three-stage framework outlined by Thomas and Harden (2008). Critical appraisal was performed using the Critical Appraisal Skills Program (CASP) checklist. A standardised data extraction form was developed with reference from JBI Qualitative Assessment and Review Instrument Data Extraction Tools for Qualitative Research (JBI-QARI) checklist for data extraction. RESULTS: Fifteen studies were included, and four themes emerged from the synthesis: (1) acquiring knowledge and skills through SBL; (2) positive experiences of using high-fidelity simulation (HFS) and virtual reality simulation (VRS) methods; (3) challenges encountered while using SBL methods and (4) drawing parallels between simulation and real clinical settings. CONCLUSION: SBL allowed undergraduate nursing students to gain knowledge, acquire skills and have a positive SBL experiences. However, the provision of innovative strategies and resources for nursing students to overcome SBL-based challenges are still needed.

An integrated investigation of structural and pathway alteration caused by PIK3CA and TP53 mutations identified in cfDNA of metastatic breast cancer.

In peripheral blood, cell-free DNA (cfDNA) contains circulating tumor DNA (ctDNA), which indicates molecular abnormalities in metastatic breast tumor tissue. The sequencing of cfDNA of Metastatic Breast Cancer (MBC) patients allows assessment of therapy response and noninvasive treatment. In the proposed study, clinically significant alterations in PIK3CA and TP53 genes associated with MBC resulting in a missense substitution of His1047Arg and Arg282Trp from an next-generation sequencing-based multi-gene panel were reported in a cfDNA of a patient with MBC. To investigate the impact of the reported mutation, we used molecular docking, molecular dynamics simulation, network analysis, and pathway analysis. Molecular Docking analysis determined the distinct binding pattern revealing H1047R-ATP complex has a higher number of Hydrogen bonds (H-bonds) and binding affinity with a slight difference compared to the PIK3CA-ATP complex. Following, molecular dynamics simulation for 200 ns, of which H1047R-ATP complex resulted in the instability of PIK3CA. Similarly, for TP53 mutant R282W, the zinc-free state (apo) and zinc-bounded (holo) complexes were investigated for conformational change between apo and holo complexes, of which the holo complex mutant R282W was unstable. To validate the conformational change of PIK3CA and TP53, 80% mutation of H1047R in the kinase domain of p110α expressed ubiquitously in PIK3CA protein that alters PI3K pathway, while R282W mutation in DNA binding helix (H2) region of P53 protein inhibits the transcription factor in P53 pathway causing MBC. According to our findings, the extrinsic (hypoxia, oxidative stress, and acidosis); intrinsic factors (MYC amplification) in PIK3CA and TP53 mutations will provide potential insights for developing novel therapeutic methods for MBC therapy.

Mandibular metastasis of follicular thyroid carcinoma.

ABSTRACT: The orofacial region may be the first site for the dissemination of malignancies from the remote regions in the jawbones. The most common location of metastatic lesions in the jawbones is the mandible, with the molar region the most frequently involved site. Radiotherapy, chemotherapy, and surgical resection can be an approach in the treatment protocol depending upon patient age and growth of tumor mass. This case report presents a case of follicular variant thyroid carcinoma, infiltrative type, pT1bN0Mx with mandibular metastasis affecting both hard and soft tissue in a 55-year-old female.

Analysis of Skin Cancer and Patient Healthcare Using Data Mining Techniques.

Skin cancer is the uncontrolled growth of irregular cancer cells in the human-skin's outer layer. Skin cells commonly grow in an uneven pattern on exposed skin surfaces. The majority of melanomas, aside from this variety, form in areas that are rarely exposed to sunlight. Harmful sunlight, which results in a mutation in the DNA and irreparable DNA damage, is the primary cause of skin cancer. This demonstrates a close connection between skin cancer and molecular biology and genetics. Males and females both experience the same incidence rate. Avoiding revelation to ultraviolet (UV) emissions can lower the risk rate. This needed to be known about in order to be prevented from happening. To identify skin cancer, an improved image analysis technique was put forth in this work. The skin alterations are routinely monitored by this proposed skin cancer categorization approach. Therefore, early detection of suspicious skin changes can aid in the early discovery of skin cancer, increasing the likelihood of a favourable outcome. Due to the blessing of diagnostic technology and recent advancements in cancer treatment, the survival rate of patients with skin cancer has grown. The strategy for detecting skin cancer using image processing technologies is presented in this paper. The system receives the image of the skin lesion as an input and analyses it using cutting-edge image processing methods to determine whether skin cancer is present. The Lesion Image Analysis Tools use texture, size, and shape assessment for image segmentation and feature phases to check for various cancer criteria including asymmetries, borders, pigment, and diameter. The image is classified as Normal skin and a lesion caused by skin cancer using the derived feature parameters.

Identifications of good and bad structural fragments of hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids with correlation intensity index and consensus modelling using Monte Carlo based QSAR studies, their molecular docking and ADME analysis.

The application of QSAR along with other in silico tools like molecular docking, and molecular dynamics provide a lot of promise for finding new treatments for life-threatening diseases like Type 2 diabetes mellitus (T2DM). The present study is an attempt to develop Monte Carlo algorithm-based QSAR models using freely available CORAL software. The experimental data on the α-amylase inhibition by a series of benzothiazole-linked hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids were selected as endpoint for the model generation. Initially, a total of eight QSAR models were built using correlation intensity index (CII) as a criterion of predictive potential. The model developed from split 6 using CII was the most reliable because of the highest numerical value of the determination coefficient of the validation set (r2VAL = 0.8739). The important structural fragments responsible for altering the endpoint were also extracted from the best-built model. With the goal of improved prediction quality and lower prediction errors, the validated models were used to build consensus models. Molecular docking was used to know the binding mode and pose of the selected derivatives. Further, to get insight into their metabolism by living beings, ADME studies were investigated using internet freeware, SwissADME.