Category: Nevin Manimala

J Robot Surg. 2025 Oct 2;19(1):653. doi: 10.1007/s11701-025-02839-8.

ABSTRACT

Gastric cancer requires surgical resection for cure, with robot-assisted minimally invasive gastrectomy (RAMIG) emerging as an alternative to open gastrectomy (OG). Comparative data on postoperative pain and recovery remain limited. This study aimed to compare RAMIG versus OG in patients with resectable gastric cancer, focusing on postoperative opioid consumption, pain intensity, and recovery parameters. In this retrospective cohort study, 138 patients with resectable gastric cancer underwent either RAMIG (n = 39) or OG (n = 99) between May 2021 and August 2023. Primary endpoints were pain intensity (Numerical Rating Scale (NRS)) and opioid consumption. Secondary endpoints comprised intensive/intermediate care (ICU/IMC) and hospital stays, blood loss, severe complications, and operative duration. Statistical analysis used SPSS version 29.0 with Mann-Whitney U and Fisher’s exact tests (p < 0.05). RAMIG showed reduced opioid consumption (p = 0.002) and lower NRS scores during mobilization on days 5 and 7 (p = 0.011; p = 0.002) and at rest on day 7 (p = 0.005). The RAMIG group experienced significantly shortened ICU/IMC stays (p < 0.001), reduced hospitalization duration (p < 0.001), and decreased intraoperative blood loss, although operative duration was prolonged. RAMIG demonstrates favorable outcomes regarding opioid requirements, pain management, ICU/IMC and hospital stays, and blood loss compared to OG, despite longer operative duration. These findings support RAMIG as an effective approach enabling accelerated recovery in patient-centered care, though prospective randomized validation studies are warranted. Trial registration: DRKS00036368, retrospectively registered 11th of March 2025.

PMID:41037210 | DOI:10.1007/s11701-025-02839-8

J Mol Neurosci. 2025 Oct 2;75(4):132. doi: 10.1007/s12031-025-02412-w.

ABSTRACT

This study aims to develop and evaluate deep neural network (DNN) models for accurately predicting the recurrence risk of glioblastoma multiforme (GBM) to enhance individualized treatment strategies and improve patient outcomes. This study implemented DNN architectures optimized using a hybrid differential evolution neural network (HDE-NN) framework to forecast GBM recurrence risk, particularly in patients at advanced disease stages. The models were trained and validated on a multimodal dataset comprising genomic profiles, imaging-derived metrics, and longitudinal clinical records from 780 GBM patients. Data were sourced from The Cancer Genome Atlas (TCGA) and institutional repositories. Performance was benchmarked against conventional machine learning models, including support vector machines (SVM), random forests (RF), and standard DNNs. The models were implemented in Python. The proposed HDE-optimized DNN achieved an accuracy of 94%, precision of 92%, recall of 90%, F1 score of 91%, and an AUC-ROC of 0.96. These metrics significantly outperformed baseline models, with improvements of 6-12% across evaluation criteria. Confidence intervals (95%) were computed via tenfold cross-validation, confirming statistical robustness. This research introduces a high-performance and generalizable deep learning framework for GBM recurrence prediction. By incorporating multi-source clinical and genomic data, the model demonstrates superior predictive capacity over traditional methods. These findings support the integration of AI-driven tools into GBM care workflows to improve prognosis assessment and personalize therapeutic interventions.

PMID:41037206 | DOI:10.1007/s12031-025-02412-w

Brain Inform. 2025 Oct 2;12(1):25. doi: 10.1186/s40708-025-00274-x.

ABSTRACT

Understanding how demographic factors influence visual attention is crucial for the development of adaptive and user-centered web interfaces. This paper presents a gender-aware saliency prediction system based on fine-tuned deep learning models and demographic-specific gaze behavior. We introduce the WIC640 dataset, which includes 640 web page screenshots categorized by content type and country of origin, along with eye-tracking data from 85 participants across four age groups and both genders. To investigate gender-related differences in visual saliency, we fine-tuned TranSalNet, a Transformer-based saliency prediction model, on the WIC640 dataset. Our experiments reveal distinct gaze behavior patterns between male and female users. The female-trained model achieved a correlation coefficient (CC) of 0.7786, normalized scanpath saliency (NSS) of 2.4224, and Kullback-Leibler divergence (KLD) of 0.5447; the male-trained model showed slightly lower performance (CC = 0.7582, NSS = 2.3508, KLD = 0.5986). Interestingly, the general model trained on the complete dataset outperformed both gender-specific models, highlighting the importance of inclusive training data. Statistical analysis revealed significant gender-related differences in 9 out of 12 saliency features and a trend of reduced fixation dispersion with increasing age. While this study does not yet incorporate temporal gaze modeling, the results suggest practical benefits for intelligent systems aiming to personalize user experiences based on demographic features. The WIC640 dataset is publicly available and offers a valuable resource for future research on adaptive AI systems, visual attention modeling, and demographic-aware interface design.

PMID:41037184 | DOI:10.1186/s40708-025-00274-x

J Robot Surg. 2025 Oct 2;19(1):657. doi: 10.1007/s11701-025-02851-y.

ABSTRACT

AIMS: Robotic surgery continues to expand rapidly in elective settings; however, its role in emergency care is limited to date. This study aims to evaluate the safety and feasibility of the adoption of robotic emergency general surgery (EGS) within a high-volume centre.

METHODS: Robotic EGS cases performed between 2020 and 2024 at a large UK university hospital were identified and matched 1:3 to non-robotic cases based on operation type, age, gender, and pathology. Data on demographics, operative details, and operative and clinical outcomes were collected. Groups were compared using appropriate statistical tests.

RESULTS: A total of 369 patients were included, with 95 (25.7%) in the robotic and 274 (74.3%) in the non-robotic (open/laparoscopic) EGS group. There were no differences between groups for demographics, procedures, or pathology. No statistically significant differences were observed in major complications (10.5% vs 9.1%, p = 0.688), conversion to open surgery (1.1% vs 3.9%, p = 0.174), post-operative length of stay (4 vs 3 days, p = 0.814), and 6-month mortality (0.0% vs 2.9%, p = 0.092) between robotic and non-robotic groups. Adjusted analyses showed no association between surgical approach and differences in operative time, major complications, or post-operative stay.

CONCLUSION: The introduction of robotic emergency general surgery is safe and feasible with comparable short-term clinical outcomes to non-robotic approaches. Further research is needed to explore the impact of an established robotic EGS programme on long-term clinical, patient, and surgeon-reported outcomes.

PMID:41037147 | DOI:10.1007/s11701-025-02851-y

Saudi Pharm J. 2025 Oct 2;33(5):36. doi: 10.1007/s44446-025-00036-0.

ABSTRACT

In Saudi Arabia, the regulation of community pharmacies currently falls under the Ministry of Health (MOH). There is a need to shift the regulatory framework of community pharmacies to be under the Saudi Food and Drug Authority (SFDA) to align with global standards. However, there is limited knowledge about the perceptions of pharmacists regarding the current regulatory framework in community pharmacies in the Kingdom of Saudi Arabia (KSA).

OBJECTIVES: This study aims to assess pharmacists’ knowledge, perceptions, and preferences regarding the current regulatory framework of community pharmacies and feasibility of transitioning regulatory oversight to SFDA.

METHODOLOGY: A cross-sectional survey design was used to assess the regulation of community pharmacies in Saudi Arabia. The sample consisted of 139 pharmacists from various sectors, selected through random sampling. A structured questionnaire focusing on regulation, awareness, and perceptions was distributed online. The questionnaire’s validity and reliability were ensured through expert review. Descriptive statistics in SPSS were used for data analysis.

RESULTS: The survey findings revealed a diverse representation across the pharmaceutical sector. Hospital pharmacists formed the largest group (37.4%, n = 52), followed by regulatory field workers from the Ministry of Health (21.6%, n = 30) and SFDA (20.1%, n = 28), pharmaceutical industry professionals (11.5%, n = 16), and community pharmacists (9.4%, n = 13). Most participants (51.8%, n = 72) had 1-5 years of experience, while 31.7% (n = 44) had 6-10 years, and 16.5% (n = 23) had more than 10 years of experience. Regarding current regulatory oversight, the majority (82.7%, n = 115) reported being under MOH regulation, with 12.2% (n = 17) under SFDA oversight. The study revealed high awareness of current regulations (77.0%, n = 107), though most participants (62.6%, n = 87) expressed dissatisfaction with the current regulatory framework. Notably, 77.0% (n = 107) preferred SFDA as the future regulator, and 80.6% (n = 112) believed SFDA would perform better in regulating the sector. Most participants demonstrated strong agreement with proposed regulatory changes, with 78.4% (n = 109) agreeing to P1 and 79.1% (n = 110) to P4 statements regarding regulatory reform.

CONCLUSION: The study reveals strong sector-wide preference among pharmaceutical professionals for transitioning community pharmacy regulation to SFDA, driven by dissatisfaction with current MOH oversight. This consensus across all professional categories and experience levels indicates practitioners’ expectations that SFDA regulation would enhance pharmaceutical service quality and regulatory effectiveness in Saudi Arabia.

PMID:41037140 | DOI:10.1007/s44446-025-00036-0

Cancer Causes Control. 2025 Oct 2. doi: 10.1007/s10552-025-02075-3. Online ahead of print.

ABSTRACT

PURPOSE: Childhood and adolescence may represent critical time windows for shaping future breast cancer risk. The association between early-life diet and breast cancer risk has been investigated, but few studies have examined the relation between adolescent diet and benign breast disease (BBD), an established breast cancer risk factor.

METHODS: Among 11,422 female Growing Up Today Study participants followed from 1996 to 2016 who completed food frequency questionnaires, we investigated the associations between adherence to three dietary patterns (Alternative Healthy Eating Index [AHEI], the Empirical Dietary Inflammatory Pattern [EDIP], and the Empirical Dietary Index for Hyperinsulinemia [EDIH]) at ages 10 and 14 years and self-reported BBD diagnosis. Cox proportional hazards models were used to estimates hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS: Over 20 years of follow-up, 554 BBD cases were ascertained, with 259 biopsy-confirmed cases. Non-significant inverse associations were observed between greater adherence to the AHEI at age 10 and BBD risk (HR for fourth vs. first quartile = 0.74; 95% CI = 0.50-1.10; p_trend = 0.09), and between AHEI at age 14 and biopsy-confirmed BBD (HR for fourth vs. first quartile = 0.70; 95% CI = 0.48-1.03; p_trend = 0.10). Non-significant positive associations were observed between adherence to the EDIH at age 10 and (HR for fourth vs. first quartile = 1.49; 95% CI = 0.91-2.43; p_trend = 0.09) age 14 (HR for fourth vs. first quartile = 1.33; 95% CI = 0.97-1.82; p_trend = 0.09) and BBD risk. No associations were observed for EDIP. In secondary analyses, the association between EDIH at age 10 and BBD became statistically significant after accounting for change in dietary pattern quartile from age 10 to 14 (HR for fourth vs. first quartile = 2.14; 95% CI = 1.04-4.41). Adjustment for adult diet also strengthened associations between EDIH at age 10 and BBD risk (HR = 1.94; 95% CI = 1.12-3.37; p_trend = 0.007), and showed a significant inverse trend for AHEI (p_trend = 0.04).

CONCLUSION: These findings may suggest that greater early-life adherence to a healthier dietary pattern (AHEI) is associated with lower BBD risk, while consuming a more insulinemic dietary pattern (EDIH) may be associated with increased risk. Associations for EDIH at age 10 were statistically significant in secondary analyses accounting for dietary change and adult diet. Further research is needed to confirm these findings and clarify potential mechanisms.

PMID:41037133 | DOI:10.1007/s10552-025-02075-3

Diabetologia. 2025 Oct 2. doi: 10.1007/s00125-025-06563-8. Online ahead of print.

ABSTRACT

AIMS/HYPOTHESIS: Type 1 diabetes is characterised by the destruction of pancreatic beta cells. Genetic factors account for approximately 50% of the total risk, with variants in the HLA region contributing to half of this genetic risk. Research has historically focused on populations of European ancestry. We developed HLA-focused type 1 diabetes genetic risk scores (T1D GRS_HLA) using SNPs or HLA alleles from four ancestry groups (admixed African [AFR; T1D GRS_HLA-AFR], admixed American [AMR; T1D GRS_HLA-AMR], European [EUR; T1D GRS_HLA-EUR] and Finnish [FIN; T1D GRS_HLA-FIN]). We also developed an across-ancestry GRS (ALL; T1D GRS_HLA-ALL). We assessed the performance of the GRS in each population to determine the transferability of constructed scores.

METHODS: A total of 41,689 samples and 13,695 SNPs in the HLA region were genotyped, with HLA alleles imputed using the HLA-TAPAS multi-ethnic reference panel. Conditionally independent SNPs and HLA alleles associated with type 1 diabetes were identified in each population group to construct T1D GRS_HLA models. Generated T1D GRS_HLA models were used to predict HLA-focused type 1 diabetes genetic risk across four ancestry groups. The performance of each T1D GRS_HLA model was assessed using receiver operating characteristic (ROC) AUCs, and compared statistically.

RESULTS: Each T1D GRS_HLA model included a different number of conditionally independent HLA-region SNPs (AFR, n=5; AMR, n=3; EUR, n=38; FIN, n=6; ALL, n=36) and HLA alleles (AFR, n=6; AMR, n=5; EUR, n=40; FIN, n=8; ALL, n=41). The ROC AUC values for the T1D GRS_HLA from SNPs or HLA alleles were similar, and ranged from 0.73 (T1D GRS_{HLA-allele-AMR} applied to FIN) to 0.88 (T1D GRS_{HLA-allele-EUR} applied to EUR). The ROC AUC using the combined set of conditionally independent SNPs (T1D GRS_HLA-SNP-ALL) or HLA alleles (T1D GRS_{HLA-allele-ALL}) performed uniformly well across all ancestry groups, with values ranging from 0.82 to 0.88 for SNPs and 0.80 to 0.87 for HLA alleles.

CONCLUSIONS/INTERPRETATION: T1D GRS_HLA models derived from SNPs performed equivalently to those derived from HLA alleles across ancestries. In addition, T1D GRS_HLA-SNP-ALL and GRS_{HLA-allele-ALL} models had consistently high ROC AUC values when applied across ancestry groups. Larger studies in more diverse populations are needed to better assess the transferability of T1D GRS_HLA across ancestries.

PMID:41037100 | DOI:10.1007/s00125-025-06563-8

Eur J Appl Physiol. 2025 Oct 2. doi: 10.1007/s00421-025-06008-5. Online ahead of print.

ABSTRACT

AIM: This pilot study aimed to systematically evaluate exercise-induced electrocardiographic (ECG) responses in professional firefighters and to explore the association between premature ventricular complexes (PVCs) and myocardial ischemia in this high-risk occupational group.

METHOD: This pilot cross-sectional study enrolled 21 male firefighters (mean age 43.4 ± 7.18 years) from a single municipal fire department. Participants underwent comprehensive cardiovascular assessment including anthropometric measurements, biochemical analyses (lipid profile, testosterone), submaximal exercise testing (Bruce protocol), and 24-h Holter ECG monitoring. Statistical analyses included Mann-Whitney U tests and effect size calculations.

RESULTS: No exercise-induced ST-segment changes indicative of myocardial ischemia were observed. However, PVCs were detected in 33% of participants (7/21), with exercise testing revealing 18 simple and 2 multiform PVCs, while Holter monitoring recorded 25 simple and 1 multiform PVC. PVC-positive firefighters were significantly older (median 49 vs. 40 years, p = 0.019, r = 0.514). Mean exercise capacity was 12.45 METs, with 81% achieving moderate fitness levels. Post-exercise heart rate recovery (HRR1: 24 ± 11.5 bpm; HRR2: 35.4 ± 11.5 bpm) showed normal patterns.

CONCLUSION: The findings of this pilot study indicate the need for larger-scale investigations, supported by advanced diagnostic modalities, to clarify the clinical relevance of exercise-induced premature ventricular complexes (PVCs) in firefighters. Although no ischemic changes were observed, the presence of subclinical coronary artery disease cannot be definitively excluded. These results provide a meaningful preliminary foundation for developing targeted screening approaches to improve early cardiovascular risk detection in high-physical-demand occupational groups.

PMID:41037097 | DOI:10.1007/s00421-025-06008-5

Odontology. 2025 Oct 2. doi: 10.1007/s10266-025-01222-1. Online ahead of print.

ABSTRACT

The aim of this study was to evaluate changes in tooth color and the bond strength of resin to enamel and dentin after exposure to electronic cigarette (e-cigarette) vapor in an in vitro vaping model, as well as to analyze the chemical composition of the materials present in the vapor. A device with a vacuum pump simulated vaping. Eighty dental slabs (40 dentin and 40 enamel) and were randomly divided into two groups. Half received e-cigarette exposure, and the other remained without vaping (control). Color changes were measured using a spectrophotometer (CIELAB). Composite cylinders were built on substrates using etch-and-rinse or self-etch strategies and subjected to loading tests. Gas chromatography-mass spectrometry (GC-MS) analyzed the organic compound of the e-liquid, while inductively coupled plasma mass spectrometry (ICP-MS) assessed the metal content. Statistical analysis was conducted using MANOVA and ANOVA (α = 0.05), and CIEDE2000 formula. E-cigarette exposure darkened (L*) and yellowed (b*) enamel and dentin. Bond strength in dentin decreased for both adhesion strategies, and in enamel using the etch-and-rinse adhesive. GC-MS identified 72 different volatile compounds, whereas ICP-MS detected 26 distinct metals. Among metals, eight exceeded the WHO (World Health Organization) tolerance limits. E-cigarette exposure altered the color of substrates and reduced resin bond strength in dentin for both adhesives, and in enamel restored with the etch-and-rinse technique. E-liquid had toxic organic compounds and metals. Exposure to e-cigarette can cause tooth discoloration and weaken bonding to dental tissues. Toxic volatile organic and metallic compounds present in vapor can adversely affect oral health.

PMID:41037091 | DOI:10.1007/s10266-025-01222-1

Eur Radiol. 2025 Oct 2. doi: 10.1007/s00330-025-12034-w. Online ahead of print.

ABSTRACT

OBJECTIVES: To construct a combined nomogram using CT enhancement ratio-based habitat imaging and radiological features in predicting the main component of combined hepatocellular carcinoma‑cholangiocarcinoma (cHCC-CCA), and to assess its ability for stratifying the prognosis.

MATERIALS AND METHODS: Patients with pathologically diagnosed cHCC-CCA who underwent contrast-enhanced CT examinations were retrospectively included and randomized into the training and validation cohorts. Tumors were grouped into high hepatocellular carcinoma (HCC) component (high-HCC%) and low-HCC component (low-HCC%) according to pathology. Voxels of tumor from early enhancement ratio and late enhancement ratio maps were clustered into different habitats through the k-means algorithm. The volume fractions of different habitats were quantified. Logistic regression analyses were utilized to identify independent predictors for high-HCC%, construct prediction models, and visualize them as a nomogram. The predictive performance was assessed by receiver operating characteristic analysis. Survival analysis was conducted using the Kaplan-Meier method.

RESULTS: 165 patients were finally included, and 78 (47.27%) patients were grouped as high-HCC%. Four tumor habitats were determined. The fraction of habitat 1 (f₁) was significantly higher, while the fraction of habitat 4 (f₄) was significantly lower in the high-HCC% group than in the low-HCC% group. Tumor capsule, corona enhancement, delayed enhancement, f₁, and f₄ were used to construct the combined nomogram with AUCs of 0.927 and 0.923 in training and validation cohorts, respectively. The combined nomogram predicted-high-HCC% exhibited better prognoses than the predicted-low-HCC% groups in terms of recurrence-free survival and overall survival.

CONCLUSION: Enhancement-based CT habitat imaging exhibited potential for predicting the main component cHCC-CCA, and provided a tool for prognosis stratification.

KEY POINTS: Question The component of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) significantly affected the prognosis, but there is no effective method for predicting the main component of cHCC-CCA. Findings The combined nomogram integrated habitat parameters and radiological features can predict the main component of cHCC-CCA and help stratify the prognosis after hepatectomy. Clinical relevance The habitat-based combined nomogram offers an effective tool for personalized and appropriate treatment in cHCC-CCA patients.

PMID:41037071 | DOI:10.1007/s00330-025-12034-w