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Review of Large Language Models for Genomic Data and Medical Text
Get PDFWith introduction of Transformer model in 2017 by a team of researchers at Google Brain, the field of Natural Language Processing was totally revolutionized. Google Translate started translating between two languages with more and more accuracy, as it was released from the clutches of legacy method of statistical machine translation and upgraded with Transformer model. Soon, these models were extended to other domains such as computer vision and time series data analysis. At the same time, the capabilities of these models were extended for a variety of genomic data for example whole genome sequences and protein sequences, the field of genomic data analysis was freed from Kmer count based hand-crafted features to sophisticated semantic capturing embeddings which were obtained with training of Transformer model using genomic data for certain biological tasks at hand for example enhancer prediction on epigenomics data or disease diagnosis using multi-omics data. This paper attempts to review and interpret the most recent large language models specially designed and trained for interpreting the semantics of whole genome sequence data and the medical text
Conformational Transition of the Mpro Enzyme: A Computational Approaches for Predicting Alternative Binding Sites of an Anti-COVID Molecule
Get PDFThe Mpro enzyme has gained popularity as a target in the life cycle of COVID-19 for the discovery of anti-COVID molecules. The current hypothesis focuses on seventy-two crystal structures of Mpro, both in Conformation A (ConA) and Conformation AB (ConAB) forms. However, no studies have yet evaluated the following aspects: (i) a comparative analysis of ligand-bound crystal structures versus their ligand-free counterparts in both ConA and ConAB forms; and (ii) the identification of alternative binding sites for anti-COVID molecules within the crystal structure of Mpro. The native state is more dynamic than the ligand-bound form, stabilizing after binding to the corresponding ligand. Moreover, Asn142 and Leu141 in ConAB-native, Asn277 and Thr304 in ConAB ligand-bound, Phe305 and Asn72 in ConA native and Ser46 and Glu47 in ConA ligand-bound structures are primarily flexible. During the transition from native to ligand-bound form, Val73, Lys100, Ser123, Cys128, Lys137, Cys156 and Phe294 residues have changed their structural position from buried to exposed in the ConA and Leu50, Arg60, Asn214, Ala285 and Phe305 in the ConAB, respectively. Similarly, Phe305 changed its structural conformation from exposure to burial in the ConA. Investigation on the multi-conformation analysis of 72 crystal structures highlighted that the residues His41, Glu189, Asn142 and Arg188 (apart from His163, Glu166 and Gln189) might act as a catalytic partner along with the Cys-His catalytic dyad and they may be considered alternative binding site of the anti-COVID molecule of the Mpro enzyme
Vascular Pathology: A Multifocal Cadaveric Analysis of Arterial Aneurysms
Get PDFThis case study aims to describe an extensive and rare case regarding the discovery of multisystemic aneurysms identified during cadaveric dissection spanning multiple vascular territories including the abdominal aorta, common and internal iliac, femoral, and popliteal arteries. This case serves to provide an understanding of anatomical diversity and the potential clinical implications for the development of widespread arterial aneurysms, including the prospective possibility regarding the influence of chronic obstructive pulmonary disease (COPD) and connective tissue disorders on aneurysm formation. Anatomic and pathologic observations were made of a phenol-fixed elderly male cadaveric donor with a known history of COPD during an eight-week anatomical dissection course. Biopsy tissue samples collected from the superior lobe of the right lung, left ventricle of the heart, left anterior descending coronary artery, lymph node, and right common iliac artery were histologically analyzed using hematoxylin and eosin (H&E) staining. Dissection revealed eleven atherosclerotic and non-ruptured aneurysms located in the abdominal aorta, bilateral common iliac, internal iliac, bilateral proximal and distal femoral, and popliteal arteries. No evidence of surgical intervention was found. This case illustrates widespread arterial aneurysms and emphasizes the value of cadaveric studies in detecting rare vascular presentations that may have significant implications for diagnosis, treatment planning, and surgical intervention. Additionally, the potential correlation with COPD and connective tissue disorders invites further investigation into systemic contributions to aneurysm formation
Hormonal Dysregulation in Major Depressive Disorder: A Systematic Review
Get PDFMajor Depressive Disorder (MDD) involves widespread hormone imbalances across the HPA, HPT, HPG, metabolic, and somatotropic axes. We performed a PRISMA-guided systematic review (2015–2025) of clinical and preclinical studies examining neuroendocrine contributions to MDD. Thirty-five studies met inclusion (N ≈ 250,000). Key findings: HPA-axis overactivity is nearly universal in acute MDD (meta-analytic SMD ≈ 1.18 for cortisol elevations). Thyroid dysfunction (especially overt hypothyroidism) modestly increases depression risk (OR ≈ 1.30 overall; OR ≈ 1.77 for overt cases). Sex steroid fluctuations (perimenstrual, postpartum, perimenopausal) heighten female vulnerability; estradiol therapy and adjunctive testosterone show benefit in selected trials/meta-analyses. Insulin resistance commonly accompanies “atypical” MDD, insulin-sensitizing agents (pioglitazone, metformin, GLP-1 agonists) produce moderate antidepressant benefits in trials and meta-analyses. GH/IGF-1 dysregulation (both excess and deficiency) associates with depressive symptoms. Neuropeptide modulation is an emerging target: intranasal neuropeptide Y (NPY) showed rapid MADRS improvement vs placebo in a randomized trial, while CRH1 antagonists (e.g., CP-316,311) failed in RCTs. Overall, MDD is best conceptualized as a systemic neuroendocrine disorder in many patients. Routine endocrine screening (cortisol, TSH/free T4, sex steroids, fasting insulin/HOMA-IR, and targeted neuropeptides where available) could enable precision augmentations (e.g., liothyronine, sex hormones, metformin, neurosteroids) tailored to endocrine subtypes. (Key metaanalytic and trial sources cited in Results/References)
Family-Centred Education and Training to Improve Quality of Life in Indonesian Adults with Type 2 Diabetes: A Community-Based Intervention Study
Get PDFObjective: To evaluate whether a family‑centred education and training programmed improves diabetes knowledge and quality of life in patients with type 2 Diabetes Mellitus (DM) in Tasikmalaya, Indonesia.
Methods: A quasi‑experimental community intervention was conducted at the Kahuripan primary health centre on 15 August 2025. Forty adults with type 2 DM and their family members participated. The programme comprised interactive lectures on diabetes and quality of life, practical training in self‑monitoring of blood glucose, foot care, healthy menu planning and stress management, and provision of a culturally adapted booklet (“Family Alert to Diabetes”). Knowledge was measured using a pre‑validated questionnaire before and after the intervention, while clinical data (age, blood pressure, fasting and post‑prandial glucose) and quality‑of‑life scores were recorded. Data were analysed descriptively; Shapiro‑Wilk tests assessed normality and a Wilcoxon signed‑rank test compared pre‑ and post‑test knowledge.
Results: Participants were predominantly older adults (mean age 62.7 years). Baseline mean systolic/diastolic blood pressure was 143/80 mmHg and fasting blood glucose was 149 mg dL⁻¹. Quality‑of‑life scores were low, particularly in the physical domain (mean 51.36%). Mean knowledge scores improved from 78.5 (pre‑test) to 81.8 (post‑test); however, the difference did not reach statistical significance (Wilcoxon W=186.5, p=0.055). Participants with lower baseline scores showed the greatest improvement. Families reported increased confidence in supporting dietary adherence, physical activity and foot care.
Conclusion: A short, family‑centred education and training programme enhanced diabetes knowledge and self‑care skills, although improvement was modest and not statistically significant. Longer follow‑up and integration of psychosocial support may be required to produce sustained, clinically meaningful gains in quality of life
Forecasting Inpatient Visits of Diabetes Mellitus Using ARIMA
Get PDFBackground: Diabetes Mellitus (DM) is a primary non‑communicable disease with a rising global burden. In Indonesia, inpatient admissions for diabetic complications are increasing, placing pressure on hospital resources. Reliable forecasting of patient visits is crucial for planning manpower, bed capacity, and supply chains.
Objective: To model and forecast monthly inpatient visits for diabetes mellitus at RSUD Banjar for 2025–2027 using Autoregressive Integrated Moving‑Average (ARIMA) time‑series models.
Methods: A retrospective time‑series study analyzed monthly inpatient visits for diabetes mellitus, both without and with complications, recorded from January 2020 to December 2024 (60 observations per series). Time‑series plots were inspected to identify trends or seasonality. The augmented Dickey–Fuller test was used to assess stationarity. The Auto Correlation Function (ACF) and Partial Autocorrelation Function (PACF) were reviewed to specify candidate ARIMA models. Missing observations were not present; potential outliers were screened using boxplots and retained because they represented actual clinical events. Candidate models were compared using the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and the Root Mean Squared Error (RMSE). Residuals were examined using the Ljung–Box Q test to verify independence. Forecasts with 95% confidence intervals were generated for 2025–2027.
Results: The uncomplicated DM series comprised ≈ 240 inpatient visits, whereas the complicated series comprised ≈ 320 visits. An ARIMA (1,0,1) model was selected for uncomplicated DM, and an ARIMA (1,1,0) model for complicated DM, based on AIC/BIC and residual diagnostics. Both models produced white‑noise residuals (Ljung–Box p>0.05). Forecasts suggested gradual increases for both series; uncomplicated visits were expected to rise from about 85 in 2025 to 95 in 2027, and complicated visits from 105 to 115. The upward trends were small and not statistically significant. Forecast confidence intervals indicated a margin of error of approximately ± 10% of the predicted values.
Conclusion: ARIMA models provided reasonable short‑term forecasts of inpatient visits for diabetes at RSUD Banjar. The predicted increases underscore the need for proactive planning of staffing, bed capacity and procurement. Future work should explore ARIMAX or hybrid ARIMA–machine‑learning models to improve predictive accuracy
Adaptive Strategies Transmission of High-Definition, 2K, 4K, 6K, 8K and 10K Streams in Multi-PLP DVB-T2 with Efficient Multiplexing Capabilities: A Spectrum Problem-Solving Approach Using Multi-PLP Multiplexing Systems
Get PDFThe rapid growth of High-Definition (HD) and Ultra-High-Definition (UHD) content, ranging from 2K to 10K resolutions, presents significant challenges for terrestrial broadcasting systems, particularly regarding spectrum utilization and reliable transmission. Digital Video Broadcasting-Terrestrial second generation (DVB T2) with Multi-Physical Layer Pipes (M-PLP) offers a flexible framework to deliver heterogeneous content streams efficiently. This study investigates spectrum-aware adaptive transmission strategies to optimize multi PLP DVB-T2 networks for high-resolution streaming, focusing on efficient multiplexing, error resilience and bandwidth management. Simulation analyses evaluate the performance of various multi-PLP configurations under different channel conditions, including low Signal to Noise Ratio (SNR) environments. Key metrics, such as throughput, Bit Error Rate (BER) and spectral efficiency, were assessed. Results indicate that adaptive allocation of PLPs according to stream resolution and channel conditions can significantly enhance system performance. For instance, multiplexing a 2K, 4K, 6K, 8K and 10K stream set using optimized PLP bandwidth allocations achieved a spectral efficiency improvement of 18% and a BER reduction from 10⁻³ to 10⁻⁵ at SNR levels of 3–5 dB compared to static PLP allocation schemes. Iterative modulation and coding adaptations further reduced transmission errors while maintaining low latency suitable for live broadcasting. The findings demonstrate that spectrum-aware adaptive transmission not only maximizes resource utilization but also ensures reliable reception across diverse resolutions. By dynamically matching PLP parameters to stream requirements and channel conditions, DVB-T2 broadcasters can efficiently deliver high-quality 2K-10K content even under constrained spectrum scenarios. This research provides a practical methodology for next-generation terrestrial broadcasting, contributing to improved spectrum efficiency, robust high-resolution transmission and enhanced user experience
Developing a Financial Product to De-risk and Finance Energy Efficiency Investments in India’s Built Environment
Get PDFEnergy Efficiency (EE) in India’s built environment offers a cost-effective pathway to achieve climate mitigation and energy security goals. However, large-scale adoption remains limited in commercial residential facilities due to systemic financial barriers, including perceived performance risk, small project sizes, limited collateral and misaligned incentives between building owners, tenants and financiers. Standalone financing instruments have delivered limited impact. This study aims to design, validate and pilot an integrated financial product that de-risks EE investments and mobilizes private capital at scale in India’s building sector. A mixed-methods, multi-stage approach was employed. Following a market diagnostic, the India Building Energy Efficiency (IBEE) Loan was developed, integrating a Partial Risk Guarantee Fund (PRGF), a tiered Measurement and Verification (M and V) framework and standardized contractual mechanisms including green leases. A hybrid System Dynamics–Agent-Based Model (SD–ABM) was used to simulate market adoption and portfolio performance under multiple scenarios. The product was subsequently pilot-tested across diverse building typologies and geographies.
Model simulations project cumulative EE lending of INR 1,450 crores within five years, compared to INR 150 crores under a business-as-usual scenario, while reducing portfolio default rates to 3.5%. Pilot results confirmed financial viability, with an average debt service coverage ratio of 1.34 and demonstrated operational resilience under stress-testing. ESCO capacity emerged as a critical bottleneck for scaling. The findings show that integrated financial product design combining risk mitigation, performance assurance and incentive alignment is essential for transforming EE into a scalable, bankable asset class. The IBEE Loan provides a replicable blueprint for mobilizing private capital to support India’s low-carbon transition
Technology Adoption and Workforce Performance in Public Service: Strategic Models and Institutional Perspectives
Get PDFIn today’s digitally driven environment, public sector institutions are increasingly expected to adopt technologies that enhance efficiency, transparency and accountability. This study, technology adoption and workforce performance in public service: strategic models and institutional perspectives, investigates how workforce performance and technology adoption are related using the national identity management commission in Nigeria as a case study. The specific goals for the study were to: determine how perceived ease of use influences contextual performance; assess the effect of perceived usefulness on productive behavior; examine the impact of behavioral intention on adaptive performance; investigate the role of facilitating conditions on task performance and explore how social influence affects innovation in the public sector. A descriptive survey design was used and a sample size of 361 respondents was used. Regression analysis using SPSS version 25 was utilized to test the hypotheses. In addition, SWOT and PESTEL frameworks were applied to provide strategic insights into internal and external influences on technology adoption. Findings revealed statistically significant relationships between perceived ease of use and contextual performance (p=0.012), perceived usefulness and productive behavior (p=0.001), and behavioral intention and adaptive performance (p=0.001). However, facilitating conditions (p=0.255) and social influence (p=0.287) did not significantly affect task performance and innovation respectively. The study was limited by constraints in accessing disaggregated organizational data and regional staff deployment. The study concludes that while technology adoption positively impacts workforce performance, more attention should be given to institutional support systems and strategic alignment
Unpacking the Effects of Revised FDI Policy on India's Life Insurance: Through the Lens of Profits/(Loss) and Equity
Get PDFThe Indian government has focused on attracting Foreign Direct Investment (FDI) to the insurance sector to drive innovation, increase competition, and improve access to insurance products. The FDI policy has undergone several changes to achieve these goals. The literature assessing the impacts of FDI policy and changes in it pertaining to the insurance sector has remained scarce in terms of the empirical investigations. The current study explores the statistical significance of the changes in FDI limit for insurance sector, from 26 percent to 49 percent that have been implemented in the beginning of the past decade. The scope of the study is limited to the life insurers only. For the purpose, it employs Granger causality test, Hausman test and difference in difference model. There are six model specifications of which three different specifications regress profits/loss after tax and another three different ones regress Indian equity investment on the suitable regressors. Different statistical information criteria support the choice of the best fit model and further these chosen models are checked for the validity and robustness with the help of plots of standardized residuals, tests for Heteroskedasticity-robust standard errors, Placebo test, Wald test and Sargan test. The results suggest that those life insurers which have received additional foreign direct investment due to the increase in the FDI limit from 26 to 49 percent have been benefitted differently in terms of profit earning capacity as well as attracting the Indian promoters. Such life insurers attracted more Indian promoters as well as earned hike in their profit after tax which is statistically confirmed by the positive nature of the relationship of response variables with the
DID coefficient.