Methyl CpG binding protein MBD2 has a regulatory role on the BRCA1 gene expression and its modulation by resveratrol in ER+, PR+ & triple-negative breast cancer cells.

BACKGROUND: Resveratrol has demonstrated its ability to regulate BRCA1 gene expression in breast cancer cells, and previous studies have established the binding of MBD proteins to BRCA1 gene promoter regions. However, the molecular mechanism underlying these interactions remains to be elucidated. The aimed to evaluate the impact of MBD proteins on the regulation of BRCA1, BRCA2, and p16 genes and their consequential effects on breast cancer cells. METHODS: Efficacy of resveratrol was assessed using the MTT assay. Binding interactions were investigated through EMSA, ChIP, & MeIP assay. Expression analyses of MBD genes and proteins were conducted using qRT-PCR and western blotting, respectively. Functional assays, including clonogenic, migratory, and sphere formation assays were used to assess cancer cells' colony-forming, metastatic, and tumor-forming abilities. The cytotoxicity of resveratrol on cancer cells was also tested using an apoptosis assay. RESULTS: The study determined an IC50 of 30µM for resveratrol. MBD proteins were found to bind to the BRCA1 gene promoter. Resveratrol exhibited regulatory effects on MBD gene expression, subsequently impacting BRCA1 gene expression and protein levels. Higher concentrations of resveratrol resulted in reduced colony and sphere formation, decreases migration of cancer cells, and an increases number of apoptotic cells in breast cancer cells. Impact Identification of MBD2-BRCA1 axis indicates their significant role in the induction of apoptosis and reduction of metastasis and proliferation in breast cancer cells. Further therapy can be designed to target these MBD proteins and resveratrol could be used along with other anticancer drugs to target breast cancer. CONCLUSIONS: In conclusion MBD2 protein interact to the BRCA1 gene promoter, and resveratrol modulates MBD2 gene expression, which in turn regulates BRCA1 gene expression, and inhibits cell proliferation, migration, and induces apoptosis in ER+, PR+ & Triple negative breast cancer cells.

Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer.

Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) records a very poor survival rate owing to its late diagnosis and several cancer cell-derived proteins have been reported as candidate biomarkers. However, given the pivotal role played by stellate cells (PSCs, which produce the collagenous stroma in PC), it is essential to also assess PSC-sEV cargo in biomarker discovery. Thus, this study aimed to isolate and characterise sEVs from mouse PC cells and PSCs cultured alone or as co-cultures and performed proteomic profiling and pathway analysis. Proteomics confirmed the enrichment of specific markers in the sEVs compared to their cells of origin as well as the proteins that are known to express in each of the culture types. Most importantly, for the first time it was revealed that PSC-sEVs are enriched in proteins (including G6PI, PGAM1, ENO1, ENO3, and LDHA) that mediate pathways related to development of diabetes, such as glucose metabolism and gluconeogenesis revealing a potential role of PSCs in pancreatic cancer-related diabetes (PCRD). PCRD is now considered a harbinger of PC and further research will enable to identify the role of these components in PCRD and may develop as novel candidate biomarkers of PC.

Education Intervention on 'Hearing Impairment - Its Assessment and Management' among Medical Practitioners in Sikkim, India.

BACKGROUND: Health care providers must be aware of the choices in aural rehabilitation methods and assessment procedures available presently to those with hearing impairment in order to facilitate early identification and intervention and ensure quality of care to those hearing impaired individuals. The referrals from the medical fraternities for the audiological services are not uniform across India. Part of reason may be that awareness about the roles of and responsibilities of audiologist's is poor among medical practitioners. In some regions of India medical practitioners may be only grossly be aware of audiologists per se. They may not know enough to refer all individuals with hearing or balance disorders for the required audiological services. AIM: To evaluate changes in pre survey and post survey after education intervention specifically planned for medical practitioners in the state of Sikkim, India. Education intervention included awareness about hearing impairment and its assessment and management by audiologists. METHOD: A pre and post survey comparison research design with purposive convenient sampling technique was applied. Participants were medical practitioners working in geographical area of Sikkim at the time of the study. Inspection of demographic data of respondents showed that they were in their age range of 24 and 60 years and with work experience ranging 1-40 years. Participants were invited for an awareness talk which included, information about hearing loss, early identification and early intervention, tests and management of hearing loss in different age groups, need for hearing aids/cochlear implants, auditory training, and the role of an audiologist in the management of hearing loss and ways to prevent hearing loss. A pre and post awareness program responses were collected from all the participants using a customized questionnaire tool. RESULTS: Respondents exhibited, in the pre-survey questionnaire, lack of awareness in many aspects of audiology, including assessing hearing impairment, diagnosing hearing loss, and the role of an audiologist. There was an overall, statistically significant difference in the level of performance on the pre-awareness and post-awareness responses. CONCLUSION: Following an awareness campaign among the medical professionals in Sikkim, there was a considerable change in their level of awareness of hearing impairment, its assessment, and management by audiologists. The reach of the awareness campaign was significant as around 70% of subjects showed significant change in their knowledge and attitude towards hearing impairment, its management.

Adaptation of Morningness-Eveningness Questionnaire (MEQ) in Bengali Language.

BACKGROUND: Morningness-Eveningness Questionnaire (MEQ) has been used to assess working efficiency of an individual. The self-reporting MEQ is available in English language, and its applicability to Indian scenario is limited to educated/ English proficient individuals only. Since, majority in India still depend on the regional languages for communication, it is difficult to make live translation of the questionnaire while administration and results may also vary due to tester's language proficiency. The present study focused on adapting MEQ in Bengali language. METHOD: The English version of Morningness-Eveningness Questionnaire (MEQ) was a self-assessment questionnaire consisting of 19 questions to measure whether a person's peak alertness was in the morning, evening or in between. The translation of the questionnaire was done using forward-backward-translation method by six experts in Bengali language, and was content validated by thirty native Bengali speakers. The speakers were asked to rate the questions on a 5-point rating scale with 1 being very familiar and 5 being not at all familiar. All the questions rated as 1 or 2 were considered for the Bengali version of MEQ, while those rated as 3 or above were reframed and revalidated. RESULT: The Bengali version of the MEQ has good reliability (Cronbach's alpha 0.74). Item analysis revealed it as a good consistent scale for estimating the circadian type of the participants. Participants were classified into 5 Circadian types based on the cut-off scores. Majority of participants are intermediate type, followed by Morningness. CONCLUSION: The application of MEQ will help in management of tinnitus.

Pharmacognostical studies of Eclipta prostrata (Linn. ) grown in Sri Lanka / Estudios farmacognósticos de Eclipta prostrate (Linn. ) cultivada en Sri Lanka

Eclipta prostrata Linn. is an annual herbaceous plant used in traditional medicine, commonly known as "Trailing Eclipta" or False Daisy in English, ' Keekirindiya ' in Sinhala and ' Kayyantakara' in Tamil. The aim of this study was to conduct a detailed pharmacognostical evaluation of E. prostrata found in Sri Lanka. Anatomical, physicochemical, phytochemical studies, and quantification of phyto - constituents were performed as per WHO guidelines. Whole plant was sequ entially extracted into solvents with different polarities. Phytochemical screening and Thin Layer Chromatography (TLC) fingerprinting were carried out. Anatomical study and powder microscopy revealed useful diagnostic features. Physicochemical parameters such as moisture content, ash values (total, acid insoluble, water soluble) and extractable matter in water and ethanol were evaluated. Phytochemical screening and TLC fingerprinting revealed the presence of different types of phyto - constituents. Alkaloid, tannin, saponin, total flavonoid and total polyphenol contents were quantified. In conclusion, pharmacognostical study aids in establishing the standardization parameters of E. prostrata found in Sri Lanka.

Eclipta prostrata Linn. es una planta herbácea anual utilizada en la medicina tradicional, comúnmente conocida como "Trailing Eclipta" o False Daisy en inglés, 'Keekirindiya' en sinhala y 'Kayyan takara' en tamil. El objetivo de este estudio fue realizar una evaluación farmacognóstica detallada de E. prostrata encontrada en Sri Lanka. Se llevaron a cabo estudios anatómicos, fisicoquímicos, fitoquímicos y cuantificación de fitoconstituyentes según l as directrices de la OMS. Se extrajo secuencialmente la planta entera en solventes con diferentes polaridades. Se realizaron pruebas de tamizaje fitoquímico y huellas dactilares de cromatografía en capa delgada (TLC). El estudio anatómico y la microscopía en polvo revelaron características diagnósticas útiles. Se evaluaron parámetros fisicoquímicos como el contenido de humedad, los valores de ceniza (total, insoluble en ácido, soluble en agua) y la materia extraíble en agua y etanol. Las pruebas de tamizaje fitoquímico y las huellas dactilares de TLC revelaron la presencia de diferentes tipos de fitoconstituyentes. Se cuantificaron los contenidos de alcaloides, taninos, saponinas, flavonoides totales y polifenoles totales. En conclusión, el estudio farmacogn óstico ayuda a establecer los parámetros de estandarización de E. prostrata encontrada en Sri Lanka.

Long-Term Outcomes and Risk of Pancreatic Cancer in Intraductal Papillary Mucinous Neoplasms.

Importance: Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cysts that can give rise to pancreatic cancer (PC). Limited population data exist on their prevalence, natural history, or risk of malignant transformation (IPMN-PC). Objective: To fill knowledge gaps in epidemiology of IPMNs and associated PC risk by estimating population prevalence of IPMNs, associated PC risk, and proportion of IPMN-PC. Design, Setting, and Participants: : This retrospective cohort study was conducted in Olmsted County, Minnesota. Using the Rochester Epidemiology Project (REP), patients aged 50 years and older with abdominal computed tomography (CT) scans between 2000 and 2015 were randomly selected (CT cohort). All patients from the REP with PC between 2000 and 2019 were also selected (PC cohort). Data were analyzed from November 2021 through August 2023. Main outcomes and Measures: CIs for PC incidence estimates were calculated using exact methods with the Poisson distribution. Cox models were used to estimate age, sex, and stage-adjusted hazard ratios for time-to-event end points. Results: The CT cohort included 2114 patients (1140 females [53.9%]; mean [SD] age, 68.6 [12.1] years). IPMNs were identified in 231 patients (10.9%; 95% CI, 9.7%-12.3%), most of which were branch duct (210 branch-duct [90.9%], 16 main-duct [6.9%], and 5 mixed [2.2%] IPMNs). There were 5 Fukuoka high-risk (F-HR) IPMNs (2.2%), 39 worrisome (F-W) IPMNs (16.9%), and 187 negative (F-N) IPMNs (81.0%). After a median (IQR) follow-up of 12.0 (8.1-15.3) years, 4 patients developed PC (2 patients in F-HR and 2 patients in F-N groups). The PC incidence rate per 100 person years for F-HR IPMNs was 34.06 incidents (95% CI, 4.12-123.02 incidents) and not significantly different for patients with F-N IPMNs compared with patients without IPMNs (0.16 patients; 95% CI, 0.02-0.57 patients vs 0.11 patients; 95% CI, 0.06-0.17 patients; P = .62). The PC cohort included 320 patients (155 females [48.4%]; mean [SD] age, 72.0 [12.3] years), and 9.8% (95% CI, 7.0%-13.7%) had IPMN-PC. Compared with 284 patients with non-IPMN PC, 31 patients with IPMN-PC were older (mean [SD] age, 76.9 [9.2] vs 71.3 [12.5] years; P = .02) and more likely to undergo surgical resection (14 patients [45.2%] vs 60 patients [21.1%]; P = .003) and more-frequently had nonmetastatic PC at diagnosis (20 patients [64.5%] vs 130 patients [46.8%]; P = .047). Patients with IPMN-PC had better survival (adjusted hazard ratio, 0.62; 95% CI, 0.40-0.94; P = .03) than patients with non-IPMN PC. Conclusions and Relevance: In this study, CTs identified IPMNs in approximately 10% of patients aged 50 years or older. PC risk in patients with F-N IPMNs was low and not different compared with patients without IPMNs; approximately 10% of patients with PC had IPMN-PC, and they had better survival compared with patients with non-IPMN PC.

Immune Checkpoint Inhibitor-Induced (Type 3) Autoimmune Pancreatitis.

PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICI) have revolutionized cancer care and work primarily by blocking CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), and/or PD-1 (programmed cell death protein 1), and/or PD-L1 (programmed death-ligand 1), thereby providing highly efficacious anti-tumor activity. However, this unmitigated immune response can also trigger immune related adverse events (irAEs) in multiple organs, with pancreatic irAEs (now referred to as type 3 Autoimmune pancreatitis (AIP) being infrequent. RECENT FINDINGS: Type 3 AIP is a drug-induced, immune mediated progressive inflammatory disease of the pancreas that may have variable clinical presentations viz., an asymptomatic pancreatic enzyme elevation, incidental imaging evidence of pancreatitis, painful pancreatitis, or any combination of these subtypes. Management is largely supportive with intravenous fluid hydration, pain control and holding the inciting medication. Steroids have not been shown to demonstrate a clear benefit in acute management. A rapid development pancreatic atrophy is observed on imaging as early as 1 year post initial injury. Type 3 AIP is a chronic inflammatory disease of the pancreas that though predominantly asymptomatic and mild in severity can lead to rapid organ volume loss regardless of type of clinical presentation and despite steroid therapy.

Blood-based Migration Signature Biomarker Panel Discriminates Early Stage New Onset Diabetes related Pancreatic Ductal Adenocarcinoma from Type 2 Diabetes.

BACKGROUND AND AIMS: While type 2 diabetes is a well-known risk factor for pancreatic ductal adenocarcinoma (PDAC), PDAC-induced new-onset diabetes (PDAC-NOD) is a manifestation of underlying PDAC. In this study, we sought to identify potential blood-based biomarkers for distinguishing PDAC-NOD from type 2 diabetes (T2DM) without PDAC. MATERIALS AND METHODS: By ELISA analysis, a migration signature biomarker panel comprising tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FNIII-C) and CA 19-9 was analyzed in plasma samples from 50 PDAC-NOD and 50 T2DM controls. RESULTS: Both TFPI (area under the curve (AUC) 0.71) and TNC-FNIII-C (AUC 0.69) outperformed CA 19-9 (AUC 0.60) in distinguishing all stages of PDAC-NOD from T2DM controls. The combined panel showed an AUC of 0.82 (95% CI = 0.73-0.90) (p = 0.002). In the PDAC-NOD early stage II samples, the three biomarkers had an AUC of 0.84 (95% CI = 0.73-0.93) vs CA 19-9, AUC = 0.60, (95% CI = 0.45-0.73), which also improved significance (p = 0.0123). CONCLUSION: The migration signature panel adds significantly to CA 19-9 to discriminate PDAC-NOD from T2DM controls and warrants further validation for high-risk group stratification.

Automated Artificial Intelligence Model Trained on a Large Data Set Can Detect Pancreas Cancer on Diagnostic Computed Tomography Scans As Well As Visually Occult Preinvasive Cancer on Prediagnostic Computed Tomography Scans.

BACKGROUND & AIMS: The aims of our case-control study were (1) to develop an automated 3-dimensional (3D) Convolutional Neural Network (CNN) for detection of pancreatic ductal adenocarcinoma (PDA) on diagnostic computed tomography scans (CTs), (2) evaluate its generalizability on multi-institutional public data sets, (3) its utility as a potential screening tool using a simulated cohort with high pretest probability, and (4) its ability to detect visually occult preinvasive cancer on prediagnostic CTs. METHODS: A 3D-CNN classification system was trained using algorithmically generated bounding boxes and pancreatic masks on a curated data set of 696 portal phase diagnostic CTs with PDA and 1080 control images with a nonneoplastic pancreas. The model was evaluated on (1) an intramural hold-out test subset (409 CTs with PDA, 829 controls); (2) a simulated cohort with a case-control distribution that matched the risk of PDA in glycemically defined new-onset diabetes, and Enriching New-Onset Diabetes for Pancreatic Cancer score ≥3; (3) multi-institutional public data sets (194 CTs with PDA, 80 controls), and (4) a cohort of 100 prediagnostic CTs (i.e., CTs incidentally acquired 3-36 months before clinical diagnosis of PDA) without a focal mass, and 134 controls. RESULTS: Of the CTs in the intramural test subset, 798 (64%) were from other hospitals. The model correctly classified 360 CTs (88%) with PDA and 783 control CTs (94%), with a mean accuracy 0.92 (95% CI, 0.91-0.94), area under the receiver operating characteristic (AUROC) curve of 0.97 (95% CI, 0.96-0.98), sensitivity of 0.88 (95% CI, 0.85-0.91), and specificity of 0.95 (95% CI, 0.93-0.96). Activation areas on heat maps overlapped with the tumor in 350 of 360 CTs (97%). Performance was high across tumor stages (sensitivity of 0.80, 0.87, 0.95, and 1.0 on T1 through T4 stages, respectively), comparable for hypodense vs isodense tumors (sensitivity: 0.90 vs 0.82), different age, sex, CT slice thicknesses, and vendors (all P > .05), and generalizable on both the simulated cohort (accuracy, 0.95 [95% 0.94-0.95]; AUROC curve, 0.97 [95% CI, 0.94-0.99]) and public data sets (accuracy, 0.86 [95% CI, 0.82-0.90]; AUROC curve, 0.90 [95% CI, 0.86-0.95]). Despite being exclusively trained on diagnostic CTs with larger tumors, the model could detect occult PDA on prediagnostic CTs (accuracy, 0.84 [95% CI, 0.79-0.88]; AUROC curve, 0.91 [95% CI, 0.86-0.94]; sensitivity, 0.75 [95% CI, 0.67-0.84]; and specificity, 0.90 [95% CI, 0.85-0.95]) at a median 475 days (range, 93-1082 days) before clinical diagnosis. CONCLUSIONS: This automated artificial intelligence model trained on a large and diverse data set shows high accuracy and generalizable performance for detection of PDA on diagnostic CTs as well as for visually occult PDA on prediagnostic CTs. Prospective validation with blood-based biomarkers is warranted to assess the potential for early detection of sporadic PDA in high-risk individuals.

Bounding box-based 3D AI model for user-guided volumetric segmentation of pancreatic ductal adenocarcinoma on standard-of-care CTs.

OBJECTIVES: To develop a bounding-box-based 3D convolutional neural network (CNN) for user-guided volumetric pancreas ductal adenocarcinoma (PDA) segmentation. METHODS: Reference segmentations were obtained on CTs (2006-2020) of treatment-naïve PDA. Images were algorithmically cropped using a tumor-centered bounding box for training a 3D nnUNet-based-CNN. Three radiologists independently segmented tumors on test subset, which were combined with reference segmentations using STAPLE to derive composite segmentations. Generalizability was evaluated on Cancer Imaging Archive (TCIA) (n = 41) and Medical Segmentation Decathlon (MSD) (n = 152) datasets. RESULTS: Total 1151 patients [667 males; age:65.3 ± 10.2 years; T1:34, T2:477, T3:237, T4:403; mean (range) tumor diameter:4.34 (1.1-12.6)-cm] were randomly divided between training/validation (n = 921) and test subsets (n = 230; 75% from other institutions). Model had a high DSC (mean ± SD) against reference segmentations (0.84 ± 0.06), which was comparable to its DSC against composite segmentations (0.84 ± 0.11, p = 0.52). Model-predicted versus reference tumor volumes were comparable (mean ± SD) (29.1 ± 42.2-cc versus 27.1 ± 32.9-cc, p = 0.69, CCC = 0.93). Inter-reader variability was high (mean DSC 0.69 ± 0.16), especially for smaller and isodense tumors. Conversely, model's high performance was comparable between tumor stages, volumes and densities (p > 0.05). Model was resilient to different tumor locations, status of pancreatic/biliary ducts, pancreatic atrophy, CT vendors and slice thicknesses, as well as to the epicenter and dimensions of the bounding-box (p > 0.05). Performance was generalizable on MSD (DSC:0.82 ± 0.06) and TCIA datasets (DSC:0.84 ± 0.08). CONCLUSION: A computationally efficient bounding box-based AI model developed on a large and diverse dataset shows high accuracy, generalizability, and robustness to clinically encountered variations for user-guided volumetric PDA segmentation including for small and isodense tumors. CLINICAL RELEVANCE: AI-driven bounding box-based user-guided PDA segmentation offers a discovery tool for image-based multi-omics models for applications such as risk-stratification, treatment response assessment, and prognostication, which are urgently needed to customize treatment strategies to the unique biological profile of each patient's tumor.

Comparison of HPV 16/18 Genotyping and p16/Ki67 Dual Staining for Detection of High-Grade Cervical Lesion in Patients with Low-Grade Cervical Smears.

Objective: To triage low-grade cervical smears (ASCUS/LSIL) by HPV 16/18 genotyping and dual staining with p16/Ki67 and to compare the sensitivity and specificity of these two triage methods for detection of high-grade cervical intraepithelial neoplasia (HGCIN). Methods: In this prospective cross-sectional study, we evaluated a total of 89 women with low-grade smears (54 ASCUS, 35 LSIL) recruited from a tertiary care hospital. All patients underwent colposcopy guided cervical biopsy. Histopathology was used as gold standard. All samples were subjected to HPV 16/18 genotyping (excluding 9) using DNA PCR and p16/Ki67 dual staining (excluding 4) using Roche® kit. We then compared the two triage methods to detect high-grade cervical lesions. Results: Overall, in all low-grade smears sensitivity, specificity and accuracy of HPV 16/18 genotyping, was found to be 66.7%, 77.1% and 76.2% respectively (p = 0.03). In low-grade smears sensitivity, specificity and accuracy of dual staining, was found to be 66.7%, 84.8% and 83.5% respectively (p = 0.01). Conclusions: Overall, in all low-grade smears the sensitivity of the two tests was comparable. However, dual staining had a higher specificity and accuracy than HPV 16/18 genotyping. It was concluded that both are effective triage methods but dual staining had a better performance than HPV 16/18 genotyping.

Association Between the Immunohistochemistry Expression of E-cadherin, Beta-Catenin, and CD44 in Colorectal Adenocarcinoma.

Background Colorectal cancer is a leading cause of cancer-related deaths worldwide, and epithelial-mesenchymal transition (EMT) plays an important role in cancer metastasis. In EMT, there is downregulation of E-cadherin, an intracellular adhesion molecule, as well as mutations in beta-catenin genes. On immunohistochemistry (IHC), the expression of CD44 portrays stem cell differentiation, which, in turn, is strongly associated with EMT. Thus, newer targeted therapies can be advised based on the expression of EMT and stem cell differentiation. Aims and objectives To determine the IHC expression of E-cadherin, beta-catenin, and CD44 in colorectal adenocarcinoma and find the association of the IHC expression of E-cadherin, beta-catenin, and CD44 with the histopathological grade, stage, lymph node metastasis, and lymphovascular invasion of colorectal adenocarcinoma. Materials and methods Fifty histologically proven cases of colorectal adenocarcinoma from 2016 to 2021 were included in this study, and clinicopathological data including age, gender, grading, TNM (tumour, node, and metastasis) staging, and lymph node metastasis were collected and hematoxylin and eosin slides were reviewed. IHC staining for E-cadherin, beta-catenin, and CD44 was done for all cases using the peroxidase and anti-peroxidase method, and the results were analysed. Results Peak incidence occurred in the 61-70 years age group (36%), and the most common site of the tumour was the rectal area (48%). The majority of the cases were in TNM stage II (37.3%), and a low expression of E-cadherin was found to be associated with higher T stage (p = 0.03), TNM staging (p = 0.04), as well as the presence of lymph node metastasis (p = 0.006). High beta-catenin expression was observed to have a significant correlation with a higher T stage (p = 0.006) and TNM staging (p = 0.005), while high CD44 expression was found to be associated with lymph node metastasis (p = 0.01). Altered expression of EMT-related proteins (E-cadherin and beta-catenin) showed a significant correlation with higher T stage (p = 0.03), TNM staging (p = 0.016), and lymph node metastasis (0.04). Conclusions EMT and cancer stem cell IHC markers are biomarkers for aggressive tumour growth and lymph node metastasis. Hence, EMT markers (E-cadherin and beta-catenin) and cancer stem cell markers (CD44) can be used as prognostic markers.

Imbalanced medical disease dataset classification using enhanced generative adversarial network.

In general, the imbalanced dataset is a major issue in health applications. The medical data classification faces the imbalanced count of data samples, here at least one class forms only a very small minority of the data, but it is a drawback of most of the machine learning algorithms. The medical datasets are mostly imbalanced in its class labels. When the dataset is imbalanced, the existing classification algorithms typically perform badly on minority class cases. To deal the class imbalance issue, an enhanced generative adversarial network (E-GAN) is proposed in this article. The proposed approach is the consolidation of deep convolutional generative adversarial network and modified convolutional neural network (DCG-MCNN). Initially, the imbalanced data is converted into balanced data in pre-processing process. Data preprocessing comprise of data cleaning, data normalization, data transformation and data reduction using Radius Synthetic minority oversampling technique (RSMOTE) method. The DCG is considered for balancing the dataset generating extra samples under training dataset. This training dataset based, the medical disease classification is enhanced by modified CNN diagnosis model. The proposed system performed is executed in MATLAB. The performance analysis is implemented under the Breast Cancer Wisconsin Dataset that provides the higher maximum geometry mean (MGM) of 8.686, 2.931 and 5.413%, and higher Matthews's correlation coefficient (MCC) of 9.776, 1.841 and 5.413% compared to the existing methods.

Risk Prediction of Pancreatic Cancer in Patients With Recent-onset Hyperglycemia: A Machine-learning Approach.

BACKGROUND: New-onset diabetes (NOD) has been suggested as an early indicator of pancreatic cancer. However, the definition of NOD by the American Diabetes Association requires 2 simultaneous or consecutive elevated glycemic measures. We aimed to apply a machine-learning approach using electronic health records to predict the risk in patients with recent-onset hyperglycemia. MATERIALS AND METHODS: In this retrospective cohort study, health plan enrollees 50 to 84 years of age who had an elevated (6.5%+) glycated hemoglobin (HbA1c) tested in January 2010 to September 2018 with recent-onset hyperglycemia were identified. A total of 102 potential predictors were extracted. Ten imputation datasets were generated to handle missing data. The random survival forests approach was used to develop and validate risk models. Performance was evaluated by c -index, calibration plot, sensitivity, specificity, and positive predictive value. RESULTS: The cohort consisted of 109,266 patients (mean age: 63.6 y). The 3-year incidence rate was 1.4 (95% confidence interval: 1.3-1.6)/1000 person-years of follow-up. The 3 models containing age, weight change in 1 year, HbA1c, and 1 of the 3 variables (HbA1c change in 1 y, HbA1c in the prior 6 mo, or HbA1c in the prior 18 mo) appeared most often out of the 50 training samples. The c -indexes were in the range of 0.81 to 0.82. The sensitivity, specificity, and positive predictive value in patients who had the top 20% of the predicted risks were 56% to 60%, 80%, and 2.5% to 2.6%, respectively. CONCLUSION: Targeting evaluation at the point of recent hyperglycemia based on elevated HbA1c could offer an opportunity to identify pancreatic cancer early and possibly impact survival in cancer patients.

Outcome of Treatment in Verrucous Carcinoma of Oral Cavity: A Tertiary Rural Hospital Experience.

Verrucous carcinoma of oral cavity is a highly well differentiated variant of squamous cell carcinoma with a low potential for invasion and metastasis. It is prevalent in the tobacco quid chewing population in our region. In this observational study, we reviewed the medical case records of 58 patients treated for oral verrucous carcinoma staged T2 to T4a. All patients underwent wide excision of tumour which included marginal mandibulectomy in 22 and hemimandibulectomy in 23 patients along with neck dissection saving the accessory nerve and internal jugular vein. 5 patients were found to have bone involvement along the alveolar sockets. 11 patients had other associated premalignant lesions in oral cavity. Only 2 patients had lymph node metastasis without extra nodal spread in submandibular region. With a mean follow up of 6 years and minimum follow up of 1 year, 3 patients had local recurrence. All these 3 patients had bone involvement and 2 of them had lymph node metastasis on histopathological examination. 3 patients who had associated premalignant lesions developed second primary in oral cavity after 3 years. In our experience, verrucous carcinoma has good prognosis when treated by surgery. Bone involvement along alveolar sockets and associated oral premalignant lesions adversely affect the outcome. There was no difference in the outcome between selective and modified radical neck dissection. Therefore selective neck dissection (supraomohyoid) would be adequate in treating these patients. Adjuvant radiotherapy can be reserved for T4a lesions or for positive margins.

Evaluation of Tumour Volume as a Prognostic Factor in Carcinoma Buccal Mucosa.

(1) To determine tumor volume by clinical measurement, imaging and histopathological examination in patients with squamous carcinoma of buccal mucosa. (2) To correlate tumor volume with lymph-node metastasis and loco-regional control. Retrospective Observational Study. Rural tertiary care hospital. 75 Patients undergoing surgery for T2 (68%) and T3 (32%) Oral squamous carcinomas were included in this observational study. Tumor volume-a product of maximum length, breadth and thickness, was determined clinically and by imaging. Tumor volume on histopathology was documented and correlated with lymph-node metastasis. After 13 months minimum follow-up, tumor volume was correlated with loco-regional control. Recurrences were analysed with regard to tumor volume, depth of invasion, lymph-node metastasis and resection margins. Average tumor volume was 7.1 cm3among T2 and 14.4 cm3among T3. 25% of T2 tumors had metastatic lymph-nodes compared to 33.3% in T3. There was positive correlation between tumor volume and lymph-node metastasis. Lymph-node metastasis was absent when tumor volume was < 8 cm3. There were 4 local and 2 regional recurrences in this study. Average histopathological tumor volume among patients who had local recurrence was 12.95 cm3. Regional recurrences occurred in tumors staged N2b and N3b on histopathology. Average depth of invasion in patients with recurrence was 10.33 mm.. Tumor volume represents actual tumor load and correlates with lymph node metastasis and prognosis in oral cancers. Depth of invasion and tumor thickness influence staging and prognosis. Large volume tumors have poor oncological outcome.

Large scale mortality in cultured Nile tilapia (Oreochromis niloticus): natural co-infection with Aeromonas hydrophila and Streptococcus iniae.

Background: Nile tilapia is a highly valuable fish in the aquaculture sector. A culture farm has reported heavy mortalities of tilapia. Aims: The present study aimed to identify the etiological agent responsible for the heavy mortality in cage cultured tilapia. Methods: The moribund and freshly dead fishes were analyzed for clinical signs. Biochemical and molecular characterizations were performed to identify the etiological agents of the disease. Also, polymerase chain reaction (PCR) assay was used to detect the presence of the virulence genes. The susceptibility of the isolates to various antibiotics was tested by the disk diffusion method. Results: The results of the biochemical tests and PCR assay confirmed that co-infection with Aeromonas hydrophila, and Streptococcus iniae was responsible for the disease severity. Phylogenetic analysis of the 16S rRNA gene showed that A. hydrophila and S. iniae isolates shared 99% and 98% sequence homology with A . hydrophila and S. iniae previously deposited in the Genbank database. The multiple antibiotic resistance (MAR) index of A. hydrophila was 0.16 and that of S. iniae was 0.71. The PCR test revealed that both pathogens harbored numerous virulence factors. The experimental infection study confirmed that the synergistic action of A. hydrophila and S. iniae led to increased mortality in tilapia. Histopathological changes were observed in the liver and spleen tissues of the co-infected fishes. Conclusion: These findings indicate that the disease outbreak in the tilapia culture farm occurred as a result of co-infection by A. hydrophila and S. iniae.

Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study.

PURPOSE: To determine if pancreas radiomics-based AI model can detect the CT imaging signature of type 2 diabetes (T2D). METHODS: Total 107 radiomic features were extracted from volumetrically segmented normal pancreas in 422 T2D patients and 456 age-matched controls. Dataset was randomly split into training (300 T2D, 300 control CTs) and test subsets (122 T2D, 156 control CTs). An XGBoost model trained on 10 features selected through top-K-based selection method and optimized through threefold cross-validation on training subset was evaluated on test subset. RESULTS: Model correctly classified 73 (60%) T2D patients and 96 (62%) controls yielding F1-score, sensitivity, specificity, precision, and AUC of 0.57, 0.62, 0.61, 0.55, and 0.65, respectively. Model's performance was equivalent across gender, CT slice thicknesses, and CT vendors (p values > 0.05). There was no difference between correctly classified versus misclassified patients in the mean (range) T2D duration [4.5 (0-15.4) versus 4.8 (0-15.7) years, p = 0.8], antidiabetic treatment [insulin (22% versus 18%), oral antidiabetics (10% versus 18%), both (41% versus 39%) (p > 0.05)], and treatment duration [5.4 (0-15) versus 5 (0-13) years, p = 0.4]. CONCLUSION: Pancreas radiomics-based AI model can detect the imaging signature of T2D. Further refinement and validation are needed to evaluate its potential for opportunistic T2D detection on millions of CTs that are performed annually.