"Heyde's enigma" in a patient with congenital annular aortic stenosis and its therapeutic challenges.

Heyde's syndrome is described as angio-dysplastic gastrointestinal (GI) bleeding in elderly patients with degenerative severe calcific aortic stenosis (AS), resulting in anaemia. It was first reported by Edward C. Heyde in 1958 and thus carried his name. Although this condition is considered to develop in 10-20% of severe AS, it is a less familiar entity in clinical practice. With the rising geriatric population in the communities, there is a proportionate increase in the incidence of AS and accompanying Heyde's syndrome. Heyde's syndrome has also been associated with hypertrophic cardiomyopathy, left ventricular assist device, ventricular septal defect, and patent ductus arteriosus. This article reports a case of Heyde's syndrome associated with congenital annular AS, successfully treated by aortic root enlargement and valve replacement. Supplementary Information: The online version contains supplementary material available at 10.1007/s12055-023-01636-y.

Infrared thermal images using PCSAN-Net-DBOA: An approach of breast cancer classification.

This manuscript proposes thermal images using PCSAN-Net-DBOA Initially, the input images are engaged from the database for mastology research with infrared image (DMR-IR) dataset for breast cancer classification. The adaptive distorted Gaussian matched-filter (ADGMF) was used in removing noise and increasing the quality of infrared thermal images. Next, these preprocessed images are given into one-dimensional quantum integer wavelet S-transform (OQIWST) for extracting Grayscale statistic features like standard deviation, mean, variance, entropy, kurtosis, and skewness. The extracted features are given into the pyramidal convolution shuffle attention neural network (PCSANN) for categorization. In general, PCSANN does not show any adaption optimization techniques to determine the optimal parameter to offer precise breast cancer categorization. This research proposes the dung beetle optimization algorithm (DBOA) to optimize the PCSANN classifier that accurately diagnoses breast cancer. The BCD-PCSANN-DBO method is implemented using Python. To classify breast cancer, performance metrics including accuracy, precision, recall, F1 score, error rate, RoC, and computational time are considered. Performance of the BCD-PCSANN-DBO approach attains 29.87%, 28.95%, and 27.92% lower computation time and 13.29%, 14.35%, and 20.54% greater RoC compared with existing methods like breast cancer diagnosis utilizing thermal infrared imaging and machine learning approaches(BCD-CNN), breast cancer classification from thermal images utilizing Grunwald-Letnikov assisted dragonfly algorithm-based deep feature selection (BCD-VGG16) and Breast cancer detection in thermograms using deep selection based on genetic algorithm and Gray Wolf Optimizer (BCD-SqueezeNet), respectively. RESEARCH HIGHLIGHTS: The input images are engaged from the breast cancer dataset for breast cancer classification. The ADQMF was used in removing noise and increasing the quality of infrared thermal images. The extracted features are given into the PCSANN for categorization. DBOA is proposed to optimize PCSANN classifier that classifies breast cancer precisely. The proposed BCD-PCSANN-DBO method is implemented using Python.

Hypertension treatment cascade among men and women of reproductive age group in India: analysis of National Family Health Survey-5 (2019-2021).

Background: Only a proportion of adults with hypertension are diagnosed and receive recommended prescriptions despite the availability of inexpensive and efficacious treatment. We aimed to estimate the prevalence of different stages of hypertension treatment cascade among the reproductive age groups in India at the national and state levels. We also identified the predictors of different stages of the hypertension treatment cascade. Methods: We used the nationally representative data from National Family Health Survey (NFHS)-5. We included all the males (15-54 years) and females aged 15-49. Socio-demographic factors, anthropometric measurements, habits, comorbid conditions, and healthcare access stratified the stages of the hypertension treatment cascade among hypertensives. We used multinomial logistic regression to identify the determinants of the treatment cascade levels. Findings: We had data from 1,267,786 individuals. The national prevalence of hypertension was 18.3% (95% CI: 18.1%-18.4%). Men (21.6%, 95% CI: 21.5%-21.7%) were found to have a higher prevalence as compared to women (14.8%, 95% CI: 14.7%-14.9%). Among hypertensive individuals, 70.5% (95% CI: 70.3%-70.7%) had ever received a BP measurement ("screened"), 34.3% (95% CI: 34.1%-34.5%) had been diagnosed prior to the survey ("aware"), 13.7% (95% CI: 13.5%-13.8%) reported taking a prescribed anti-hypertensive drug ("under treatment"), and 7.8% (95% CI: 7.7%-7.9%) had their BP under control ("controlled"). Males, illiterates, poor, never married, residents of rural areas, smokers/tobacco users, and alcoholic users were less likely to be in any of the treatment cascades. Interpretation: The prevalence of hypertension in India is high. The "Rule of half" of hypertension does not apply to India as the proportion of people screened, aware of their hypertension status, treated, and controlled are lower than 50% at each stage. Program managers must improve access to hypertension diagnosis and treatment, especially among men in rural areas and populations with lower household wealth. Funding: None.

A destabilizing Y891D mutation in activated EGFR impairs sensitivity to kinase inhibition.

EGFR tyrosine kinase inhibitors (TKIs) have transformed the treatment of EGFR-mutated non-small cell lung carcinoma (NSCLC); however, therapeutic resistance remains a clinical challenge. Acquired secondary EGFR mutations that increase ATP affinity and/or impair inhibitor binding are well-described mediators of resistance. Here we identify a de novo EGFR Y891D secondary alteration in a NSCLC with EGFR L858R. Acquired EGFR Y891D alterations were previously reported in association with resistance to first generation EGFR TKIs. Functional studies in Ba/F3 cells demonstrate reduced TKI sensitivity of EGFR L858R + Y891D, with the greatest reduction observed for first and second generation TKIs. Unlike other EGFR mutations associated with TKI resistance, Y891D does not significantly alter ATP affinity or promote steric hindrance to inhibitor binding. Our data suggest that the Y891D mutation destabilizes EGFR L858R, potentially generating a population of misfolded receptor with preserved signaling capacity but reduced sensitivity to EGFR inhibitors. These findings raise the possibility of protein misfolding as a mechanism of resistance to EGFR inhibition in EGFR-mutated NSCLC.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes.

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase with important roles in many cellular processes as well as in cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. How these dimers relate to higher-order EGFR oligomers seen in cell membranes, however, remains unclear. Here, we used single-particle tracking (SPT) and Förster resonance energy transfer imaging to examine how each domain of EGFR contributes to receptor oligomerization and the rate of receptor diffusion in the cell membrane. Although the extracellular region of EGFR is sufficient to drive receptor dimerization, we find that the EGF-induced EGFR slowdown seen by SPT requires higher-order oligomerization-mediated in part by the intracellular tyrosine kinase domain when it adopts an active conformation. Our data thus provide important insight into the interactions required for higher-order EGFR assemblies involved in EGF signaling.

Benzothiazole derivatives as p53-MDM2 inhibitors: in-silico design, ADMET predictions, molecular docking, MM-GBSA Assay, MD simulations studies.

Breast cancer stands as the most prevalent malignancy among the female populace. One of the pivotal domains in the therapeutic landscape of breast cancer revolves around the precise targeting of the p53-MDM2 inhibitory pathway. The advent of p53-MDM2 inhibition in the context of developing treatments for breast cancer marks a significant stride. In the quest for enhancing the efficacy of p53-MDM2 inhibition against breast cancer, a new series of benzothiazole compounds (B1-B30) was designed through in-silico methodologies in the present work. Using Schrodinger Maestro, the compounds underwent molecular docking assessments against the p53-MDM2 target (PDB: 4OGT). Compared to reference compounds, B25 and B12 exhibited notably elevated glide scores. Extensive in-silico studies, including ADMET and toxicity evaluations, were performed to predict pharmacokinetics, drug likeness, and toxicity. All compounds adhered to Lipinski criteria, signifying favorable oral drug properties. The MM-GBSA analysis indicated consistent binding free energies. Molecular dynamics simulations for B25 over 200 ns assessed complex stability and interactions. In summary, these compounds exhibit potential for future cancer therapy medication development.Communicated by Ramaswamy H. Sarma.

Molecular characterization of circadian gene expression and its correlation with survival percentage in colorectal cancer patients.

Colorectal cancer (CRC) is a form of cancer characterized by many symptoms and readily metastasizes to different organs in the body. Circadian rhythm is one of the many processes that is observed to be dysregulated in CRC-affected patients. In this study, we aim to identify the dysregulated physiological processes in CRC-affected patients and correlate the expression profiles of the circadian clock genes with CRC-patients' survival rates. We performed an extensive microarray gene expression pipeline, whereby 471 differentially expressed genes (DEGs) were identified, following which, we streamlined our search to 43 circadian clock affecting DEGs. The Circadian Gene Database was accessed to retrieve the circadian rhythm-specific genes. The DEGs were then subjected to multi-level functional annotation, i.e., preliminary analysis using ClueGO/CluePedia and pathway enrichment using DAVID. The findings of our study were interesting, wherein we observed that the survival percentage of CRC-affected patients dropped significantly around the 100th-month mark. Furthermore, we identified hormonal activity, xenobiotic metabolism, and PI3K-Akt signaling pathway to be frequently dysregulated cellular functions. Additionally, we detected that the ZFYVE family of genes and the two genes, namely MYC and CDK4 were the significant DEGs that are linked to the pathogenesis and progression of CRC. This study sheds light on the importance of bioinformatics to simplify our understanding of the interactions of different genes that control different phenotypes.

Identification of potential circadian genes and associated pathways in colorectal cancer progression and prognosis using microarray gene expression analysis.

Colorectal cancer (CRC) is third cancer causing death in the world. CRC is associated with disrupting the circadian rhythm (CR), closely associating the CRC progression and the dysregulation of genes involved in the biological clock. In this study, we aimed to understand the circadian rhythm changes in patients diagnosed with CRC. We used the GEO database with the ID GSE46549 for our analysis, which consists of 32 patients with CRC and one as normal control. Our study has identified five essential genes involved in CRC, HAPLN1, CDH12, IGFBP5, DCHS2, and DOK5, and had different enriched pathways, such as the Wnt-signaling pathway, at different time points of study. As a part of our study, we also identified various related circadian genes, such as CXCL12, C1QTNF2, MRC2, and GLUL, from the Circadian Gene Expression database, that played a role in circadian rhythm and CRC development. As circadian timing can influence the host tissue's ability to tolerate anticancer medications, the genes reported can serve as a potential drug target for treating CRC and become beneficial to translational settings.

Genetic analysis for semen quality traits in buffalo bulls.

This study was attempted to estimate the genetic parameters of semen quality traits in buffalo bulls. The study data consisted of 10975 ejaculates from 45 Murrah buffalo bulls (aged 24-72 months) used for breeding program during year 2010 to 2020. Semen quality traits (ejaculate volume, concentration of sperm, mass activity, initial and post-thaw motility, number of sperms per ejaculate, motile sperm number and discard rates) were studied. It was observed that average ejaculate volume was 2.82 ± 1.45 mL with mean concentration of 1040.12 ± 523.26 million/mL. Higher heritability was observed for number of sperms per ejaculate, number of motile sperm and sperm concentration. Significant phenotypic correlation was obtained between volume and number of sperms per ejaculate as well as volume and number of motile sperms. Likewise, significant phenotypic correlation was evident between sperm concentration with sperm number per ejaculate. Highest phenotypic correlation was obtained between sperm count per ejaculate and motile sperm count. Estimated genetic trends showed significant change in volume and motile sperm number. In conclusion, this study ascertains that genetic parameters of semen traits can be considered during the selection of buffalo bulls in breeding program.

Large Language Models in Hematology Case Solving: A Comparative Study of ChatGPT-3.5, Google Bard, and Microsoft Bing.

Background Large language models (LLMs), such as ChatGPT-3.5, Google Bard, and Microsoft Bing, have shown promising capabilities in various natural language processing (NLP) tasks. However, their performance and accuracy in solving domain-specific questions, particularly in the field of hematology, have not been extensively investigated. Objective This study aimed to explore the capability of LLMs, namely, ChatGPT-3.5, Google Bard, and Microsoft Bing (Precise), in solving hematology-related cases and comparing their performance. Methods This was a cross-sectional study conducted in the Department of Physiology and Pathology, All India Institute of Medical Sciences, Deoghar, Jharkhand, India. We curated a set of 50 cases on hematology covering a range of topics and complexities. The dataset included queries related to blood disorders, hematologic malignancies, laboratory test parameters, calculations, and treatment options. Each case and related question was prepared with a set of correct answers to compare with. We utilized ChatGPT-3.5, Google Bard Experiment, and Microsoft Bing (Precise) for question-answering tasks. The answers were checked by two physiologists and one pathologist. They rated the answers on a rating scale from one to five. The average score of the three models was compared by Friedman's test with Dunn's post-hoc test. The performance of the LLMs was compared with a median of 2.5 by a one-sample median test as the curriculum from which the questions were curated has a 50% pass grade. Results The scores among the three LLMs were significantly different (p-value < 0.0001) with the highest score by ChatGPT (3.15±1.19), followed by Bard (2.23±1.17) and Bing (1.98±1.01). The score of ChatGPT was significantly higher than 50% (p-value = 0.0004), Bard's score was close to 50% (p-value = 0.38), and Bing's score was significantly lower than the pass score (p-value = 0.0015). Conclusion The LLMs reveal significant differences in solving case vignettes in hematology. ChatGPT exhibited the highest score, followed by Google Bard and Microsoft Bing. The observed performance trends suggest that ChatGPT holds promising potential in the medical domain. However, none of the models was capable of answering all questions accurately. Further research and optimization of language models can offer valuable contributions to healthcare and medical education applications.

Structural analysis of the AICD central 12 residue peptide stretch and its interactions with metals and polyphenols, as a potential drug target for AD.

Structural analysis of the central 12 residue stretch of Amyloid precursor protein Intracellular Domain (AICD16-27: T-S-I-H-H-G-V-V-E-V-D-A) was carried out by NMR and homology modeling. Further, metal and polyphenol interactions were also carried out for these 12 residues stretch, as it contains two critical Histidine residues, which were observed to be perturbed via NMR. A full length 57 residues AICD model was generated via computational methods, to ascertain its overall conformation, as the entire structure was unavailable. An overlay of this AICD entire model with the full length Aß-42 structure matched well, implying similar properties. Docking studies with metals and polyphenols indicated involvement of the key Histidine residues highlighting their roles towards neurodegeneration and AD pathophysiology.Communicated by Ramaswamy H. Sarma.

Rhinofacial Conidiobolomycosis - A rare fungal infection of tropics.

Fungal sinusitis may be caused by filamentous fungi such as mucorales, aspergillus and entomophthorales. Mucormycosis and aspergillosis have immunocompromised states as specific risk factors, whereas entomophthorales may occur in apparently healthy persons having significant soil contact. This is, nonetheless, a rare condition with involvement of mucosa of the nose, para nasal sinuses and centrofacial soft tissues, without bony or angioinvasion. It grows relentlessly, however, and may mimic soft tissue neoplasm causing facial disfigurement.

Histone deacetylase (HDACs) inhibitors: Clinical applications.

Histone Deacetylases (HDACs) deacetylate lysine residues in histone and non-histone proteins. HDACs have been implicated in several diseases, including cancer, neurodegeneration, and cardiovascular disease. HDACs play an essential role in gene transcription, cell survival, growth, and proliferation, with histone hypoacetylation as one of the critical downstream signatures. HDAC inhibitors (HDACi) regulate gene expression epigenetically by restoring acetylation levels. Contrarily, only few HDACi have received FDA approval, and the majority are presently undergoing clinical trials to ascertain their effectiveness in the prevention and treatment of disease. In this book chapter, we give a detailed list of HDAC classes, and their functions in advancing diseases like cancer, cardiovascular, and neurodegeneration. Furthermore we touch upon novel and promising HDACi therapy approaches in the relevance of the current clinical scenario.

Distinct interactions stabilize EGFR dimers and higher-order oligomers in cell membranes.

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) with important roles in many cellular processes as well as cancer and other diseases. EGF binding promotes EGFR dimerization and autophosphorylation through interactions that are well understood structurally. However, it is not clear how these dimers relate to higher-order EGFR oligomers detected at the cell surface. We used single-particle tracking (SPT) and Förster resonance energy transfer (FRET) imaging to examine how each domain within EGFR contributes to receptor dimerization and the rate of its diffusion in the cell membrane. We show that the EGFR extracellular region is sufficient to drive receptor dimerization, but that the EGF-induced EGFR slow-down seen by SPT requires formation of higher order oligomers, mediated in part by the intracellular tyrosine kinase domain - but only when in its active conformation. Our data thus provide important insight into higher-order EGFR interactions required for EGF signaling.

Computational screening and structural analysis of Gly201Arg and Gly201Asp missense mutations in human cyclin-dependent kinase 4 protein.

The regulatory proteins, cyclins, and cyclin-dependent kinases (CDKs) control the cell cycle progression. CDK4 gene mutations are associated with certain cancers such as melanoma, breast cancer, and rhabdomyosarcoma. Therefore, understanding the mechanisms of cell cycle control and cell proliferation is essential in developing cancer treatment regimens. In this study, we obtained cancer-causing CDK4 mutations from the COSMIC database and subjected them to a series of in silico analyses to identify the most significant mutations. An overall of 238 mutations (119 missense mutations) retrieved from the COSMIC database were investigated for the pathogenic and destabilizing properties using the PredictSNP and iStable algorithms. Further, the amino acid position of the most pathogenic and destabilizing mutations were analyzed to understand the nature of amino acid conservation across the species during the evolution. We observed that the missense mutations G201R and G201D were more significant and the Glycine at position 201 was found to highly conserved. These significant mutations were subjected to molecular dynamics simulation analysis to understand the protein's structural changes. The results from molecular dynamics simulations revealed that both G201R and G201D of CDK4 are capable of altering the protein's native form. On comparison among the most significant mutations, G201R disrupted the protein structure higher than the protein with G201D.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach.

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.

Surgical and Survival Outcomes of Operable Gastric Cancer-Experience from a Tertiary Care Center in South India.

Gastric cancer is one of the leading cancers in Southern India. Data regarding the gastric cancers among the Indian population is sparse. Most patients in our country have locally advanced gastric cancers due to delayed presentation. In this article, we present our data regarding the presentation patterns, epidemiological demographics, surgical outcomes, and survival patterns from a tertiary care center in South India. This is a retrospective analysis of gastric cancer patients who underwent gastrectomy in our institution between January 2015 and November 2021 (n = 102). The data regarding patient characteristics, histopathology, and perioperative outcomes were analysed from medical records. The adjuvant treatment received and survival details were collected from the follow-up records and by telephonic interviews. A total of 128 patients were assessable, 102 patients underwent gastrectomy in a period of 6 years. The median age of presentation was 60 years and males were more commonly affected (70.6%). Most common presentation was pain abdomen followed by gastric outlet obstruction. Adenocarcinoma NOS (93%) was the most common histological type. Most of the Patients had antropyloric growths (79.4%) and subtotal gastrectomy with D2 lymphadenectomy was the most common surgery performed. Majority of the tumors were T4 tumors (55.9%) and nodal metastases were detected in 74% of the specimens. Predominant morbidity was wound infection (6.1%) followed by anastomotic leak (5.9%) with a combined overall morbidity of 16.7% and 30-day mortality of 2.9%. Seventy five (80.5%) patients were able to complete all planned 6 cycles of adjuvant chemotherapy. The median time of survival calculated by Kaplan-Meier method was 23 months with 2-year and 3-year overall survival rates of 31% and 22%, respectively. Lymphovascular invasion (LVSI) and lymph nodal burden were the risk factors associated with recurrences and deaths. The patient characteristics, histological factors, and perioperative outcomes revealed most of our patients presented in locally advanced stages with poor risk histological types and increased nodal burden contributing to the lower survival in our population. Inferior survival outcomes suggest the need to explore perioperative and neoadjuvant chemotherapy options in our population.

Risk factors associated with short-term complications in mandibular fractures: the MANTRA study-a Maxillofacial Trainee Research Collaborative (MTReC).

INTRODUCTION: Complications following mandibular fractures occur in 9-23% of patients. Identifying those at risk is key to prevention. Previous studies highlighted smoking, age and time from injury to presentation as risk factors but rarely recorded other possible confounders. In this paper, we use a collaborative snapshot audit to document novel risk factors and confirm established risks for complications following the treatment of mandibular fractures. METHODS: The audit was carried out by 122 OMFS trainees across the UK and Ireland (49 centres) over 6 months, coordinated by the Maxillofacial Surgery Trainees Research Collaborative. Variables recorded included basic demography, medical and social history, injury mechanism and type, management and 30-day outcome. RESULTS: Nine hundred and forty-seven (947) patients with fractured mandibles were recorded. Surgical management was carried out in 76.3%. Complications at 30 days occurred 65 (9%) of those who were managed surgically. Risk factors for complications included male sex, increasing age, any medical history, increasing number of cigarettes smoked per week, increasing alcohol use per week, worse oral hygiene and increased time from injury to presentation. DISCUSSION: We have used a large prospective snapshot audit to confirm established risk factors and identify novel risk factors. We demonstrate that time from injury to presentation is confounded by other indicators of poor health behaviour. These results are important in designing trial protocols for management of mandibular fractures and in targeting health interventions to patients at highest risk of complications.

Porous silicon Fabry-Pérot interferometer designed for sensitive detection of aflatoxin B1 in field crops.

Herein, a label-free sensing platform was designed for accurate, rapid and selective detection of aflatoxin B1 (AFB1), a potent mutagenic and carcinogenic substance in food and feedstuff. Minute AFB1 residues were assessed by competitive immunoassay facilitated on porous silicon Fabry-Pérot interferometer. The immunocomplex formation was biochemically amplified by enzymatic reaction products infiltrating the porous void and alternating the reflectivity spectra in correlation to the AFB1 content. The optical output presented high sensitivity toward target analyte detection in simulated conditions, as low as 0.03 ppb within the dynamic range of 0.01-10 ppb. The selectivity and specificity of the developed sensing platform were cross-validated versus commonly known interfering mycotoxins without compromising its performance values. Finally, the efficiency and the accuracy of the system were demonstrated in three matrices (maize, peanut and wheat) while demonstrating acceptable recovery values of 94-101 %, in compliance with the competitive ELISA standard assay and HPLC.