Nevin Manimala

Adv Clin Exp Med. 2026 Mar 30. doi: 10.17219/acem/216746. Online ahead of print.

ABSTRACT

BACKGROUND: Crohn’s disease (CD) is a non-specific inflammatory bowel disorder for which no definitive cure is available. The primary management strategy is pharmacological treatment aimed at alleviating symptoms. However, many patients ultimately require surgical intervention to manage complications arising from the disease.

OBJECTIVES: The aim of this study was to investigate disease-related factors that may increase the risk of early postoperative complications in patients with CD.

MATERIAL AND METHODS: A meta-analysis was conducted based on studies examining early surgical and medical complications following abdominal surgery for CD. The analyzed risk factors included disease duration prior to surgery, history of previous surgeries, presence of concurrent perianal disease, intra-abdominal abscess during surgery, and Montreal classification subtypes A1-3, L1-4, and B1-3. A systematic review was performed using 4 major databases: PubMed, Cochrane Library, Academic Search Ultimate (EBSCO), and Google Scholar. Outcomes were assessed using the odds ratio (OR) and response ratio (R), together with 95% confidence intervals (95% CIs). Egger’s test was used to evaluate publication bias. Heterogeneity was assessed using the I2 statistic, with I2 > 50% indicating significant variability.

RESULTS: A total of 51 articles met the inclusion criteria. The analysis identified several significant risk-increasing factors: history of previous surgeries (OR = 1.39; 95% CI: 1.23-1.57), Montreal classification group B3 (OR = 1.26; 95% CI: 1.11-1.42), disease duration before surgery (R = 1.10; 95% CI: 1.02-1.18), and group L2 (OR = 1.38; 95% CI: 1.11-1.72). Conversely, factors associated with a reduced risk of postoperative complications included group L1 (OR = 0.81; 95% CI: 0.71-0.92) and group B2 (OR = 0.81; 95% CI: 0.71-0.91).

CONCLUSION: This meta-analysis aggregated data from a broad spectrum of patients and treatment settings across multiple institutions worldwide. Although some risk of bias and heterogeneity was observed, the findings nevertheless highlight the importance of considering disease subtype and progression when assessing the likelihood of postoperative complications in patients with CD. This knowledge may be valuable for optimizing treatment strategies.

PMID:41904989 | DOI:10.17219/acem/216746

Otolaryngol Head Neck Surg. 2026 Mar 29. doi: 10.1002/ohn.70218. Online ahead of print.

ABSTRACT

OBJECTIVE: There is increasing use of intraoperative parathyroid hormone (ioPTH) in minimally invasive parathyroidectomy (MIP). While ioPTH has improved cure rate, there is little evidence to suggest effectiveness in primary hyperparathyroidism (PHP) with concordant preoperative localisation. This study aims to determine if ioPTH improves cure rates in such cases.

DATA SOURCES: A search of PubMed, Embase, and Cochrane databases identified studies that compared MIP with and without ioPTH, in patients with concordant preoperative imaging of ultrasonography and technetium-99m sestamibi (MIBI) scans. Inclusion criteria were comparative studies between years 2000 and 2023.

REVIEW METHODS: Analysis was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. Primary outcome was the overall cure rate. Secondary outcomes analyzed include operative duration, and conversion to neck exploration.

RESULTS: Six studies involving 884 patients were eligible for inclusion. The overall cure rate was 97.3%, higher in those that had ioPTH than without, but this was not statistically significant (98.3% vs 96.0%, P = .18). Operative duration was reported in 2 studies, showing significantly longer duration in the ioPTH group. Overall conversion rate to bilateral neck exploration was 6.64% in the ioPTH group, with a success rate of 4.80%.

CONCLUSION: Use of ioPTH in MIP with concordant localization did not result in statistically significant higher cure rates. Operative time is potentially longer with use of ioPTH. It is difficult to justify the routine use of ioPTH for such cases based on cure rates alone; considerations should also be given to center-specific case volume, surgical experience, and overall cost outcomes.

PMID:41904980 | DOI:10.1002/ohn.70218

J Int Med Res. 2026 Mar;54(3):3000605261433691. doi: 10.1177/03000605261433691. Epub 2026 Mar 29.

ABSTRACT

BackgroundIntracerebral hemorrhage is associated with high mortality in intensive care settings. Current prognostic models have limitations, including poor interpretability and insufficient validation in critically ill populations. In this study, we developed an interpretable machine learning model to predict survival in intensive care unit patients with intracerebral hemorrhage.MethodsThis retrospective study used data from patients with intracerebral hemorrhage in the eICU Collaborative Research Database for model development and the Medical Information Mart for Intensive Care IV database for external validation. Clinical, laboratory, and physiological parameters within 24 h of intensive care unit admission were extracted. Six machine learning survival algorithms, including the Random Survival Forest, were implemented. Model performance was assessed using the time-dependent area under the curve, concordance index, and Brier score. Model interpretability was achieved through the SHapley Additive exPlanations framework.ResultsThe cohort comprised 5797 patients from eICU and 1423 patients from Medical Information Mart for Intensive Care IV. Random Survival Forest demonstrated superior performance, with a time-dependent area under the curve of 0.88 in internal validation and 0.82 on day 1 of external validation. SHapley Additive exPlanations analysis identified Glasgow Coma Scale score, Acute Physiology Score, age, creatinine, temperature, and systolic blood pressure as key predictors. Critical risk thresholds were Glasgow Coma Scale score <9.8, Acute Physiology Score >52.7, and age >62.9 years.ConclusionWe developed a machine learning survival prediction model that demonstrated robust performance and clinical utility. The web-based tool may enhance intensive care unit risk stratification and clinical decision-making.

PMID:41904977 | DOI:10.1177/03000605261433691

ChemSusChem. 2026 Apr 14;19(7):e70598. doi: 10.1002/cssc.70598.

ABSTRACT

Platinum-based catalysts are the core components for methanol oxidation reaction (MOR) in direct methanol fuel cells (DMFCs). Although platinum catalysts on nitrogen-doped carbon (NC) show promising MOR activity, the coupled variation between Pt and NC during synthesis obscures their individual contributions. Herein, a solid-phase interface reaction (SIR) successfully decouples their interactions, clarifying the role of each component. We define the ripple effect as the long-range electronic modulation induced by Pt-N coordination, which modulates the electronic state of Pt active sites in a long-range manner and thus significantly accelerates MOR reaction kinetics. Based on this, a metal-free catalytic promoter was developed. When combined with commercial 5 wt% Pt/C, the resulting Pt/C@NC-6hr composite exhibits 1.67 times and twice the mass activity of 5 and 20 wt% Pt/C. Furthermore, statistical results indicate that the mass activity derived solely from the Pt on NC is 4.74 times higher than that of the original 5 wt% Pt/C catalyst, demonstrating a remarkably substantial activity enhancement. After 3600 s chronoamperometry at 0.75 V (vs. RHE), it maintains superior current density. This work elucidates the mechanism of microenvironment-enhanced Pt catalysis via the ripple effect and offers a practical strategy for improving commercial Pt/C.

PMID:41904957 | DOI:10.1002/cssc.70598

Brain Behav. 2026 Apr;16(4):e71325. doi: 10.1002/brb3.71325.

ABSTRACT

INTRODUCTION AND AIMS: Cannabis use among university students is a growing concern, particularly in demanding medical programs. We estimated prevalence, identified predictors, and compared coping strategies among medical students in Uganda.

DESIGN AND METHODS: Cross-sectional survey of 318 undergraduates at Kampala International University (Western Campus). Cannabis use and hazardous/disordered use were screened with CUDIT-R (hazardous 8-11; probable use disorder ≥12, DSM-5-TR aligned). Coping was measured with the Brief COPE. Predictors were assessed using logistic regression; coping differences with the Wilcoxon rank-sum test.

RESULTS: Cannabis use prevalence was 30.8% (n = 98); 7.6% met criteria for hazardous use and 9.4% for probable cannabis use disorder. Independent predictors of use were being separated (AOR = 12.00), being single (AOR = 3.45), Catholic faith (AOR = 2.76), and longer time at campus (AOR = 1.16 per year). Users reported higher emotion-focused and avoidant coping; problem-focused coping did not differ.

DISCUSSION AND CONCLUSIONS: Cannabis use among Ugandan medical students is common and associated with relationship status, religion, and time at campus. Coping profiles suggest greater reliance on maladaptive strategies among users. Findings support campus policies and mental-health programs that integrate substance-use screening and strengthen adaptive coping skills.

PMID:41904942 | DOI:10.1002/brb3.71325

Acta Psychol (Amst). 2026 Mar 26;265:106694. doi: 10.1016/j.actpsy.2026.106694. Online ahead of print.

ABSTRACT

Previous research has demonstrated that basing self-esteem on performance in a specific context can yield both favorable and adverse outcomes. To assist high achievers whose performance is strongly connected to their self-worth, an important initial step is to identify when this becomes problematic. From a theoretical standpoint, we hypothesize that shame following performance failure may help explain the association between basing self-esteem on performance and negative outcomes related to performance and health. That is, it may be when basing self-esteem on performance develops into shame following performance failure that such consequences emerge. To explore this hypothesis, we conducted a cross-sectional study with 176 elite athletes to examine whether shame following performance failure statistically mediates the associations between basing self-esteem on performance and competitive anxiety and athlete burnout. The findings in the present study were consistent with the idea that shame following performance failure could play a key explanatory role. Initial analyses showed significant direct associations between basing self-esteem on performance and five out of six dimensions of competitive anxiety and athlete burnout, with correlation coefficients ranging from 0.42** to -0.22**. However, when shame following performance failure was statistically tested as a potential mediator, these direct effects were substantially reduced and became non-significant (ranging from 0.08 to -0.02). This pattern is statistically consistent with mediation, although it should not be interpreted causally given the cross-sectional nature of the data. Despite limitations, this study may offer an important step toward a better understanding of when, and under what circumstances, basing self-esteem on performance leads to negative outcomes.

PMID:41904927 | DOI:10.1016/j.actpsy.2026.106694

Cytokine. 2026 Mar 27;202:157139. doi: 10.1016/j.cyto.2026.157139. Online ahead of print.

ABSTRACT

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by a lack of targeted therapies and poor prognosis. The tumor microenvironment (TME) plays a pivotal role in TNBC progression, with immune mediators such as cytokines, chemokines, growth factors, and immune checkpoints driving inflammation, angiogenesis, and immune evasion.

METHODS: We conducted a comparative analysis of 81 immune-related proteins in serum samples from 137 participants: 49 healthy controls (HC), 63 non-TNBC (NTNBC) patients, and 25 TNBC patients. Protein expression was quantified using multiplex immunoassays (ProcartaPlex and MILLIPLEX MAP® panels). Statistical analyses included principal component analysis (PCA), hierarchical clustering, receive operating curves (ROC), and pathway enrichment to identify diagnostic biomarkers and molecular networks associated with TNBC aggressiveness. Ou results revealed distinct immune dysregulation in TNBC, characterized by significant overexpression of pro-inflammatory cytokines (IFN-γ, IL-12p70, IL-8), chemokines (MIP-1α, Fractalkine), growth factors (VEGF-A, SCF), and immune checkpoints (LAG-3, PD-L1). ROC curve analyses identified LAG-3, Fractalkine, and VEGF-A as the top biomarkers distinguishing healthy controls from TNBC, while IL-5, IL-27, and TNF-β effectively discriminated TNBC from NTNBC. Cytokine network analysis highlighted TSLP, IL-12p70, and IL-17 A as central hubs coordinating Th1/Th17 inflammatory responses, stromal remodeling, and immune evasion, with strong interactions between IL-17 A-ENA-78-SCF and IL-3-IL-21 axes driving TNBC aggressiveness. Stratified analyses further demonstrated stage, grade, and metastasis revealed that IL-12p70, MIP-1α, and IL-18 were elevated in late-stage TNBC; IL-17 A, IL-5, and TWEAK were significantly overexpressed in high-grade tumors; and IFN-γ, IL-8, CTLA-4 and TSLP peaked in metastatic TNBC.

CONCLUSION: Our findings identify immune mediator panels as promising diagnostic and prognostic biomarkers for TNBC.

PMID:41904922 | DOI:10.1016/j.cyto.2026.157139

Neural Netw. 2026 Mar 21;201:108885. doi: 10.1016/j.neunet.2026.108885. Online ahead of print.

ABSTRACT

Sentiment analysis remains challenging due to the complex, intertwined relationships among sentiment expressions, contextual cues, and emotional features distributed across heterogeneous data sources. Conventional deep learning and transformer-based models often treat sentiments as isolated units, failing to capture these rich, multi-perspective interactions. To address these limitations, this study introduces a Two-Fold Multi-Perspective Heterogeneous Graph Neural Network (TFMPHGNN) that jointly models sentiment, emotion, and contextual dependencies within a dual-stage heterogeneous graph framework. The first stage employs a meta-path-based encoder integrated with a capsule network to capture hierarchical semantic relationships among sentiment-emotion-context nodes, while the second stage utilizes a multi-channel graph convolutional network (MC-GCN) to learn complementary topological, semantic, and collaborative representations of sentiment-emotion pairs. A variational autoencoder (VAE) further denoises and refines latent embeddings. Experiments on the newly developed VaKSent-2025 corpus show that TFMPHGNN outperforms eight state-of-the-art graph-based baselines by 4.67% in accuracy, 2.7% in F1-micro, and 4.2% in F1-weighted, with statistical significance testing confirming the reliability of these gains. An extended ablation analysis further demonstrates that the collaborative fusion channel achieves 0.9387 accuracy, representing improvements of 7.5% and 7.9% over the topological-only and semantic-only channels, respectively, underscoring the synergistic value of integrating multiple graph perspectives. Collectively, these results indicate that TFMPHGNN effectively captures complex sentiment-emotion interdependencies and offers a robust, interpretable framework for fine-grained sentiment understanding.

PMID:41904902 | DOI:10.1016/j.neunet.2026.108885

Comput Biol Chem. 2026 Mar 24;123:109027. doi: 10.1016/j.compbiolchem.2026.109027. Online ahead of print.

ABSTRACT

Chemical graph theory has provided a rigorous framework to represent molecular structure with graphs and hence, topological indices could be derived in a systematic way and bear enough predictive power. In fact, these indices are critical in the studies of Quantitative Structure Property Relationship (QSPR), as they relate molecular structure to measurable physicochemical properties. Present research focuses on pharmaceuticals for Urinary Tract Infections (UTIs) and aims to outline the power of topological indices in modelling the physicochemical properties of the commonly used 10 UTIs drugs. Topological indices are first calculated, and then quadratic and cubic polynomial regression models were formulated and compared. Models are evaluated based on statistical criteria to decide on the best-fitted predictive model. Since there is a limited number of observations, Leave-One-Out Cross-Validation (LOOCV) was conducted to confirm the reliability/robustness of the model. Additionally, drugs have been ranked using Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approaches based on combined values of their structural and property descriptors. The results show that the quadratic regression was validated as the optimal model and consistent SAW and TOPSIS rankings. This paper also showcases the relevance of topological descriptors in QSPR based drug analysis.

PMID:41904899 | DOI:10.1016/j.compbiolchem.2026.109027

Int Dent J. 2026 Mar 27;76(3):109530. doi: 10.1016/j.identj.2026.109530. Online ahead of print.

ABSTRACT

OBJECTIVE: The successful completion of orthodontic treatment largely depends on the accuracy of bracket placement. This study aimed to compare the impact of virtual simulation and traditional training on bonding, while also exploring student feedback regarding their learning journey.

METHODS: Twenty dental interns with no experience in orthodontics were randomly assigned either to a traditional training group (Group A) or a virtual simulation training group (Group B). Following their respective trainings, students placed orthodontic brackets on head-simulator models. Three-dimensional bracket deviations (mesiodistal, vertical, and buccolingual) from an ideal reference were quantified using the Geomagic Studio software. Participants’ motivation and satisfaction were also assessed with the ARCS (Attention, Relevance, Confidence, Satisfaction) motivation and learning experience satisfaction questionnaires. Due to the non-normal distribution of the data, the Mann-Whitney U test was used to compare differences between two groups.

RESULTS: The virtual simulation group had less deviation in bracket positioning in the mesiodistal and buccolingual directions than the traditional training group (P < .05). There was no statistically significant difference in the vertical directions (P > .05). Furthermore, the virtual simulation group scored higher in all questionnaire domains, although most of the differences were not statistically significant.

CONCLUSION: Within the limitations of this pilot study, differences in selected aspects of the accuracy of bracket positioning were found to be associated with virtual simulation training. The findings suggest that virtual simulation provides learning outcomes comparable to those of traditional training without compromising technical accuracy from an educational perspective. Adoption of this technology is a great addition to modern dental educational curricula. However, more research with larger sample sizes is necessary. With the pilot nature of the study and limited statistical power, the results must be treated with caution.

PMID:41904887 | DOI:10.1016/j.identj.2026.109530