Nevin Manimala

Org Biomol Chem. 2026 Feb 13. doi: 10.1039/d6ob00094k. Online ahead of print.

ABSTRACT

Alzheimer’s disease (AD) is the most common type of dementia, accounting for at least two-thirds of dementia cases in people aged 65 and older. Numerous approaches have been studied for the treatment of this disease, including the cholinergic hypothesis. Acetylcholinesterase (AChE) is the most promising target studied within the cholinergic hypothesis for the treatment of AD. Therefore, it is necessary to develop predictive models for the identification of AChE inhibitors. Thus, general drug design models can assist chemical synthesis groups and biochemical testing laboratories by enabling virtual screening and drug design. In this work, the objective is to build a generic molecular screening prediction model for public, online and free use based on pIC₅₀, using a random forest model (RF). For this, a dataset with approximately 16 000 compounds and 134 classes of descriptors was used, resulting in more than 2 000 000 calculated descriptors. Other algorithms were studied, such as gradient boosting, XGBoost, LightGBM, and RF with descriptors from principal component analysis (PCA), but none demonstrated significantly superior results compared to the RF model. The final model studied obtained an R² = 0.76 with a 15% test set and obtained an R² = 0.73 with a 30% test set, with rigorous Y-scrambling confirming the absence of chance correlation. External validation performed on an independent test set comprising 10% of the data yielded an R² of 0.77 and an RMSE of 0.67, statistically confirming that the model retains high predictive accuracy for novel chemical scaffolds and is free from overfitting. It is suggested that compounds containing oxime groups (RR’C = NOH) and those with high structural branching (higher Balaban index) tend to be less potent AChE inhibitors (negative correlation). In addition, some descriptors indicate that electronic charge distribution, molecular surface area, and hydrophobicity play important roles in correlating with the inhibitory activity (pIC₅₀) of the compounds. The presence of linear alkane chains also seems relevant to activity (positive correlation and greater importance). The data and models are available at the following link: (https://colab.research.google.com/drive/1gMcuXAsrqTIBMNnsCEWG9xfkK7aaZAbn?usp=sharing).

PMID:41685429 | DOI:10.1039/d6ob00094k

J Clin Rheumatol. 2026 Feb 13. doi: 10.1097/RHU.0000000000002324. Online ahead of print.

ABSTRACT

BACKGROUND/OBJECTIVE: Depression among physicians is a growing concern due to its impact on personal health and clinical performance. This study aimed to determine the prevalence of depressive symptoms in rheumatologists from Latin America and identify demographic, professional, and psychosocial factors associated with depressive symptoms.

METHODS: This is a cross-sectional study between August and November 2020, using a multilingual (Spanish and Portuguese) online survey distributed by national rheumatology societies under the Pan-American League of Associations for Rheumatology. The survey included the Patient Health Questionnaire (PHQ-9) to assess depression and the Maslach Burnout Inventory for burnout. Depression was defined as a PHQ-9 score ≥10. Descriptive statistics, χ2, t tests, and multivariate logistic regression were used for analysis. A total of 297 rheumatologists over the age of 25 actively practicing in 15 Latin American countries were included.

RESULTS: Of 297 participants, 15.8% had moderate to severe depression, and 33% had mild symptoms. Burnout affected 56.6%. Depression was more prevalent among younger physicians, those with fewer years in practice, lower income (≤$25,000/year), shorter vacation time, and those experiencing burnout. In multivariate analysis, burnout and lower happiness were independently associated with depression.

CONCLUSIONS: Nearly half of Latin American rheumatologists reported depressive symptoms. Burnout and psychosocial stressors were major contributors. Early identification and institutional strategies to promote well-being and mental health are critical.

PMID:41685422 | DOI:10.1097/RHU.0000000000002324

Hematology. 2026 Dec;31(1):2626211. doi: 10.1080/16078454.2026.2626211. Epub 2026 Feb 13.

ABSTRACT

OBJECTIVES: Several observational studies have suggested an association between sleep traits and leukaemia. This study aimed to determine the causal association between sleep traits and leukaemia using two-sample Mendelian Randomization (MR) analysis.

METHODS: Publicly available databases were used to retrieve summary statistics from genome-wide association studies (GWAS) related to sleep traits (UK BioBank) and leukaemia (FinnGen database). Inverse Variance Weighted (IVW) method was utilized for the primary MR analysis. Subsequently, we conducted a reverse MR analysis. Sensitivity analyses and statistical power calculation validated the robustness of the research findings. The Steiger directionality test was employed to ascertain the direction of causality.

RESULTS: Univariable MR identified nominal associations between chronotype and higher risk of acute lymphoblastic leukaemia (OR = 2.15, P = 0.014) and chronic myeloid leukaemia (OR = 1.27, P = 0.016), as well as between short sleep duration and lower lymphoid leukaemia risk (OR = 0.06, P = 0.035). However, none remained significant after FDR correction. Sensitivity analyses revealed no evidence of heterogeneity or horizontal pleiotropy. Adjusting for smoking and BMI in multivariable MR abolished all associations. Colocalization suggested shared genetic variants, but reverse MR indicated a significant effect only from acute lymphoblastic leukaemia to chronotype (P_FDR = 0.0017).

CONCLUSIONS: Our MR study found several nominal associations that sleep traits causally influence leukaemia subtypes. Nominal associations were not significant after multiple testing correction, attenuated by adjustment for smoking and BMI, and potentially affected by pleiotropy or reverse causation.

PMID:41685402 | DOI:10.1080/16078454.2026.2626211

Cancer Med. 2026 Feb;15(2):e71634. doi: 10.1002/cam4.71634.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) is the third leading cause of cancer deaths in the United States for men and women combined but is preventable with timely screening. Evidence-based interventions (EBIs) provide promising opportunities to increase screening. There are few descriptive examples of the processes used to assess and implement EBIs to increase CRC screening.

PROJECT DESCRIPTION: The Colorectal Cancer Prevention Network (CCPN) in South Carolina facilitated an intensive quality improvement technical assistance project aimed to increase CRC screening in 25 primary care clinics. In this paper we provide a detailed description of the process used to implement EBIs, report on the changes in CRC screening rates, and examine the impact of the interventions across clinics with different attributes (such as clinic size and rurality).

METHODS: We used Chi-square to explore changes in screening rates from baseline to years two and three of clinic implementation. We used Difference-in-Differences analysis to assess changes in screening rates from baseline to third year for clinics with different attributes.

RESULTS AND CONCLUSIONS: Across all clinics, the CRC screening increased from 45% to 51% (p < 0.05) from baseline to third year of participation. Sixteen of out 25 clinics saw an increase in screening rates for their second year, and 14 out of 25 saw an increase in their third year. Clinics with smaller patient populations, rural clinics, clinics with fewer uninsured patients, and clinics with lower baseline rates saw greater percentage point improvements. Clinics onboarded in the second year saw the lowest gains. We conclude that a structured tailored approach to the selection of EBIs can have positive effects on CRC screening rates, but positive change may vary depending on clinic attributes.

PMID:41685389 | DOI:10.1002/cam4.71634

J Public Health Res. 2026 Feb 10;15(1):22799036251410258. doi: 10.1177/22799036251410258. eCollection 2026 Jan.

ABSTRACT

BACKGROUND: Over the past three decades, Iran’s fertility rate has declined sharply from 6.5 to 1.7, posing a critical demographic and public health challenge, a global trend that highlights the need to tackle multifaceted influences on childbearing intentions, including economic, social, emotional, and attitudinal factors.This study examined the factors influencing childbearing intentions among women.

DESIGN AND METHODS: This cross-sectional study surveyed 450 reproductive-age women in Tabriz, Iran. Data were collected using self-administered questionnaires to assess sociodemographic/obstetric characteristics, attitudes toward fertility/childbearing, subjective norms, marital satisfaction, perceived social support, childbearing/parental anxiety, and hope. Data were analyzed with SPSS v24 via descriptive statistics, chi-square/Fisher’s exact tests, independent t-tests, and hierarchical multiple logistic regression to identify predictors of childbearing intention.

RESULTS: Only 34.2% (95% CI: 29.8-38.8) of participants intended to have children. Adjusted logistic regression identified positive associations with childbearing intention for positive attitudes (OR = 1.113, 95% CI: 1.057-1.172), subjective norms (OR = 1.458, 95% CI: 1.292-1.646), social support (OR = 1.093, 95% CI: 1.020-1.172), hope (OR = 1.165, 95% CI: 1.043-1.172), and religious beliefs (OR = 12.789, 95% CI: 1.029-158.990); conversely, negative associations for pregnancy/childbirth anxiety (OR = 0.633, 95% CI: 0.422-0.949), age > 40 years (OR = 0.01, 95% CI: 0.000-0.279), and poor financial status (OR = 0.007, 95% CI: 0.000-0.347).

CONCLUSION: The findings highlight the multifaceted economic, social, emotional, and attitudinal influences on childbearing intentions among Iranian women. To promote fertility rates, targeted public health strategies are recommended, including counseling for emotional barriers, economic supports like infertility subsidies and family incentives, and community-based education on reproductive health benefits.

PMID:41685375 | PMC:PMC12891384 | DOI:10.1177/22799036251410258

Front Neurosci. 2026 Jan 28;20:1766192. doi: 10.3389/fnins.2026.1766192. eCollection 2026.

ABSTRACT

INTRODUCTION: Disruptions in functional connectivity (FC) within the default mode network (DMN) are well established as a key neuropathology underlying cognitive impairment in type 2 diabetes mellitus (T2DM). Subcortical nuclei, including the basal forebrain (BF) and mediodorsal thalamus, play critical roles in regulating DMN-associated cognitive processes and are particularly vulnerable to hyperglycemia and brain insulin resistance. However, the specific FC patterns between these subcortical nuclei and DMN cortical regions in patients with T2DM, as well as their potential associations with cognitive impairment, remain incompletely elucidated.

METHODS: Eighty-two patients with T2DM and 79 healthy controls (HCs) were enrolled in this study. Clinical data, neuropsychological assessments, and resting-state functional magnetic resonance imaging were collected from all participants. Resting-state (rs-FNC) and dynamic (dFNC) functional network connectivity analyses were performed to characterize connectivity between subcortical nuclei and DMN cortical regions. Correlation analyses explored associations between FNC metrics showing significant intergroup differences and participants’ clinical and cognitive parameters.

RESULTS: rs-FNC analysis revealed decreased FC between the BF and the dorsomedial prefrontal cortex (dMPFC), the BF and the temporal pole, and the dMPFC and the anteromedial prefrontal cortex in patients with T2DM (network-based statistic correction; edge p < 0.001, component p < 0.05). dFNC analyses indicated increased frequency and prolonged mean dwell time (MDT) of State 1 (high-frequency low-connectivity), as well as decreased frequency and shortened MDT of State 2 (high-frequency high-connectivity) compared with HCs (all p < 0.05). Reduced FC between the dMPFC and BF was positively correlated with Montreal Cognitive Assessment scores (r = 0.353, p = 0.001), whereas frequency (r = -0.434, p < 0.001) and MDT (r = -0.376, p = 0.001) of State 2 were negatively correlated with T2DM disease duration after Bonferroni correction.

CONCLUSION: These findings indicate that T2DM duration correlates with reduced highly efficient DMN connectivity, and that the BF may regulate cognitive function via the dMPFC subsystem. The results reveal temporal and functional specificity in abnormal DMN connectivity in patients with T2DM and enrich the neural atlas of DMN dysfunction in this population.

PMID:41685355 | PMC:PMC12891212 | DOI:10.3389/fnins.2026.1766192

J Arrhythm. 2026 Feb 10;42(1):e70285. doi: 10.1002/joa3.70285. eCollection 2026 Feb.

ABSTRACT

BACKGROUND: It remains unclear how P-wave morphology characteristics can be used to stratify the risk of late recurrence after catheter ablation (CA) for atrial fibrillation (AF).

METHODS: Patients with paroxysmal AF who underwent an initial CA were enrolled. We investigated the association between P-wave morphology (P-wave duration (Pd), PQ interval, P-wave amplitude (PWA) in leads II, V2, and V6) and late arrhythmia recurrence. Patients were classified into groups using statistical methods, and differences in recurrence and predictive scores for low voltage areas (LVA) among the groups were evaluated.

RESULTS: A total of 1005 paroxysmal AF patients undergoing initial CA were included. Cox regression identified female sex, Pd > 124 ms, PQ > 196 ms, and low PWA in leads II, V2, and V6 as predictors of late recurrence. Hierarchical clustering defined three phenotypes: Phenotype 1 (isolated low PWA), Phenotype 2 (isolated prolonged Pd) and Phenotype 3 (low PWA with prolonged Pd). At 1-year, cumulative recurrence rates were 10.1% (95% CI 0.8-15.7), 7.0% (4.7-9.6), and 36.2% (30.8-42.3) for Phenotypes 1-3; at 3-year, rates were 17.4% (12.8-23.3), 10.2% (7.4-14.0), and 61.2% (54.8-67.6). Phenotype 3 showed the highest risk, with HRs of 4.84 (95% CI 3.42-6.84) versus Phenotype 1 and 7.44 (4.34-12.8) versus Phenotype 2 (both p < 0.001). Phenotype 3 also had higher DR-FLASH and APPLE scores than the other phenotypes.

CONCLUSIONS: Low PWA across multiple leads (II, V2, and V6), especially when combined with prolonged Pd, correlates with late arrhythmia recurrence and suggests the potential presence of LVA.

PMID:41685353 | PMC:PMC12891814 | DOI:10.1002/joa3.70285

NAR Genom Bioinform. 2026 Feb 11;8(1):lqag012. doi: 10.1093/nargab/lqag012. eCollection 2026 Mar.

ABSTRACT

Synthetic data (SD) has become an increasingly important asset in the life sciences, helping address data scarcity, privacy concerns, and barriers to data access. Creating artificial datasets that mirror the characteristics of real data allows researchers to develop and validate computational methods in controlled environments. Despite its promise, the adoption of SD in life sciences hinges on rigorous evaluation metrics designed to assess their fidelity and reliability. To explore the current landscape of SD evaluation metrics in distinct life sciences domains, the ELIXIR Machine Learning Focus Group performed a systematic review of the scientific literature following the PRISMA guidelines. Six critical domains were examined to identify current practices for assessing SD. Findings reveal that, while generation methods are rapidly evolving, systematic evaluation is often overlooked, limiting researchers’ ability to compare, validate, and trust synthetic datasets across different domains. This systematic review underscores the urgent need for robust, standardized evaluation approaches that not only bolster confidence in SD but also guide its effective and responsible implementation. By laying the groundwork for establishing domain-specific yet interoperable standards, this scoping review paves the way for future initiatives aimed at enhancing the role of SD in scientific discovery, clinical practice and beyond.

PMID:41685350 | PMC:PMC12891913 | DOI:10.1093/nargab/lqag012

Front Genet. 2026 Jan 29;17:1729712. doi: 10.3389/fgene.2026.1729712. eCollection 2026.

ABSTRACT

OBJECTIVES: Hyperuricemia and gout are common public health problems, stemming from both genetic and lifestyle factors. Evidence from multi-ethnic regions in Yunnan Province remains limited. This preliminary study examined hyperuricemia and gout prevalence, related biomarkers, lifestyle patterns, and SLC2A9/SLC22A12 genetics variations among 88 participants from the Miao community in Yunnan Province China.

METHODS: A cross-sectional survey and biochemical study were conducted. Demographic and lifestyle data were collected, and blood samples were analyzed for serum biochemical indicators. Eight SNPs in SLC2A9 and SLC22A12 were genotyped. Logistic regression models were applied to allele and genotype data.

RESULTS: Demographic and clinical analyses for Miao villagers (n = 88) suggested that the morbidities of hyperuricemia and gout were more frequent in male and showed significant association with alcohol consumption, smoking, and elevated BMI. While dietary patterns showed no significant differences. Compared with non-hyperuricemia/non-gout individuals (n = 56), the hyperuricemia/gout group (n = 57) showed 56% higher uric acid (553.13 vs. 354.73 μmol/L), 37% elevated creatinine (84.66 vs. 61.80 μmol/L), and higher triglycerides (3.35 vs. 1.80 mmol/L), along with hematological abnormalities, e.g., elevated hemoglobin (162.77 vs. 147.50 g/L) and lower platelets counts (161.09 vs. 194.14 × 10⁹/L). Preliminary genetic analyses indicated a possible association between SLC2A9_rs10939650 and hyperuricemia/gout risk, whereas variant SLC22A12 polymorphisms showed no association. After Bonferroni correction, no SNPs remained statistically significant.

CONCLUSION: This preliminary study suggested that the relatively higher burden of hyperuricemia and gout in the Miao population may be influenced by ethnicity, sex, lifestyle factors, metabolic alteration, and potential genetic components. Given the small sample size, the genetic findings should be interpreted cautiously and validated in larger studies for that disease (hyperuricemia and gout) and for similar ethnic community.

PMID:41685348 | PMC:PMC12893670 | DOI:10.3389/fgene.2026.1729712

Shoulder Elbow. 2026 Feb 10:17585732261419033. doi: 10.1177/17585732261419033. Online ahead of print.

ABSTRACT

BACKGROUND: This study aimed to evaluate recovery of complex upper-limb movements from a kinematic and biomechanical perspective in patients undergoing Reverse Total Shoulder Arthroplasty (RSA), comparing movement quality during athletic gestures with healthy controls.

METHODS: Two groups were analyzed: patients with RSA and healthy individuals without shoulder pathology. Participants performed basic shoulder tasks (flexion-extension and abduction-adduction) and three athletic gestures of increasing complexity: boccia throw, golf swing, and padel víbora stroke. Kinematic data (joint angles, angular velocities, and accelerations) were collected using a wearable inertial motion analysis system (Movit System G1).

RESULTS: Controls demonstrated a greater range of motion (maximum joint angle: 184.0° vs. 144.03°), though differences were not statistically significant. Angular velocities and accelerations were largely comparable between groups, indicating that patients with RSA adopt conservative yet functional movement strategies. No significant differences were observed during the boccia throw or golf swing. The víbora stroke showed the highest variability but remained within functional limits in both groups.

CONCLUSIONS: This pilot feasibility study suggests that patients with RSA can perform complex upper-limb and sport-specific movements with biomechanical patterns comparable to healthy individuals. Although limited by small sample size, large effect sizes indicate clinically relevant differences, supporting the need for larger, confirmatory studies.

PMID:41685344 | PMC:PMC12890591 | DOI:10.1177/17585732261419033