Nevin Manimala

Sci Rep. 2025 Sep 5;15(1):28716. doi: 10.1038/s41598-025-11890-2.

ABSTRACT

The processing-transportation composite robots, with their dual functions of processing and transportation, as well as comprehensive robot-machine interactions, have been widely and efficiently applied in the manufacturing industry, leading to a continuous increase in energy consumption. Hence, this work focuses on investigating robot-machine integrated energy-efficient scheduling in flexible job shop environments. To address the new problem, an innovative mixed-integer linear programming model and a novel dual-self-learning co-evolutionary algorithm are proposed, aimed at minimizing the total energy consumption and makespan. In the proposed algorithm, a three-dimensional vector is first used to comprehensively express the solution, and then a greedy decoding strategy is designed to reduce the idle time and energy consumption simultaneously. A hybrid initialization method with adaptive random selection and chaos mapping is developed to ensure the diversity and high quality of the initial solutions. A dual-self-learning mechanism, including a self-learning evolutionary mechanism and a self-learning cooperation mechanism, is designed to select suitable evolutionary operators and enhance interactions between populations, respectively. Finally, multiple sets of experiments are conducted to demonstrate the effectiveness of the proposed mathematical model, improved components and algorithm through numerical, statistical, and differential analyses.

PMID:40913072 | DOI:10.1038/s41598-025-11890-2

Br J Cancer. 2025 Sep 5. doi: 10.1038/s41416-025-03169-0. Online ahead of print.

ABSTRACT

BACKGROUND: Locally advanced nasopharyngeal carcinoma (LA-NPC) has a heterogeneous prognosis, with approximately one-fourth of patients experiencing poor outcomes. Studies have explored the application of induction chemoimmunotherapy followed by chemoradiotherapy, but its efficacy was controversial.

METHODS: The protocol was registered in the Prospective Register of Systematic Reviews (PROSPERO, CRD42024619387). The primary outcome measures were objective response rate (ORR), complete response rate (CRR), and the incidence of treatment-related adverse events (TRAEs). Meta-analysis was performed using Cochrane Collaboration Review Manager 5.4.1 and Meta-Analyst Beta 3.13 statistical software.

RESULTS: The meta-analysis involving 1680 patients with LA-NPC from 7 studies showed that the induction chemoimmunotherapy group had significantly better ORR (odds ratio[OR] = 2.03, 95% confidence interval [CI]:1.44-2.86, P < 0.01), and CRR (OR = 2.61, 95% CI:1.55-4.38, P < 0.01) than the induction chemotherapy group. The pooled ORR and CRR of induction chemoimmunotherapy were 92.7% (95% CI: 90.7-94.7%) and 24.3% (95% CI: 15.2-33.6%), respectively. There was no significant difference of TRAEs between induction chemotherapy group and induction chemoimmunotherapy group (OR = 1.13; 95% CI: 0.92-1.39, P = 0.23).

CONCLUSIONS: Induction chemoimmunotherapy could be a promising induction treatment option for LA-NPC patients, improving ORR and CRR with an acceptable safety profile. However, due to limitations in this meta-analysis, further large-scale, well-designed clinical trials are required to validate these results and optimise treatment strategies.

PMID:40913058 | DOI:10.1038/s41416-025-03169-0

Sci Rep. 2025 Sep 5;15(1):32368. doi: 10.1038/s41598-025-16070-w.

ABSTRACT

In radiomics, feature selection methods are primarily used to eliminate redundant features and identify relevant ones. Feature projection methods, such as principal component analysis (PCA), are often avoided due to concerns that recombining features may compromise interpretability. However, since most radiomic features lack inherent semantic meaning, prioritizing interpretability over predictive performance may not be justified. This study investigates whether feature projection methods can improve predictive performance compared to feature selection, as measured by the area under the receiver operating characteristic curve (AUC), the area under the precision-recall curve (AUPRC), and the F1, F0.5 and F2 scores. Models were trained on a large collection of 50 binary classification radiomic datasets derived from CT and MRI of various organs and representing different clinical outcomes. Evaluation was performed using nested, stratified 5-fold cross-validation with 10 repeats. Nine feature projection methods, including PCA, Kernel PCA, and Non-Negative Matrix Factorization (NMF), were compared to nine selection methods, such as Minimum Redundancy Maximum Relevance (MRMRe), Extremely Randomized Trees (ET), and LASSO, using four classifiers. The results showed that selection methods, particularly ET, MRMRe, Boruta, and LASSO, achieved the highest overall performance. Importantly, performance varied considerably across datasets, and some projection methods, such as NMF, occasionally outperformed all selection methods on individual datasets, indicating their potential utility. However, the average difference between selection methods and projection methods across all datasets was negligible and statistically insignificant, suggesting that both perform similarly based solely on methodological considerations. These findings support the notion that, in a typical radiomics study, selection methods should remain the primary approach but also emphasize the importance of considering projection methods in order to achieve the highest performance.

PMID:40913054 | DOI:10.1038/s41598-025-16070-w

ESMO Open. 2025 Sep 4;10(9):105573. doi: 10.1016/j.esmoop.2025.105573. Online ahead of print.

ABSTRACT

BACKGROUND: Antibody-drug conjugates (ADCs) combine targeted monoclonal antibodies with cytotoxic payloads and are an emerging modality in systemic cancer therapy. Thirteen ADCs are Food and Drug Administration approved, with many more in development. However, design and use remain challenging, with issues including on/off-target toxicity, resistance from prior exposure to payload classes, and optimal target/payload selection.

PATIENTS AND METHODS: This pooled analysis included patients treated on 19 clinical trials (9 phase I, 10 phase II/III) of 14 novel ADCs at Sarah Cannon Research Institute, London (2012-2025). Patients who received one or more doses of the study drug were analyzed. Descriptive statistics and Cox regression were used to evaluate demographics, tumor characteristics, toxicity and outcomes, overall and in subgroups.

RESULTS: A total of 163 patients [median age 61 years (range 31-82 years); 46.8% male] were included. Most had breast (n = 53, 32.5%) or gynecological cancers (n = 36, 22.1%), with a median of 4 prior treatments (range 1-20). Payloads included alkylating agents (n = 3), microtubule inhibitors (n = 8), and topoisomerase inhibitors (n = 3). Four ADCs targeted an oncogene (HER2); others targeted tumor-associated antigens (TAAs). Treatment-emergent adverse events (TEAEs) occurred in 84% (grade 3-4 in 29%). Rates of any-grade colitis, interstitial lung disease (ILD), neuropathy, ocular toxicity, and hepatotoxicity were 2.4%, 6.0%, 25.1%, 18.0% and 22.8%, respectively. Most toxicities emerged within 6 weeks, except colitis (median 18.2 weeks), ILD (13.1 weeks), neuropathy (11.6 weeks) and thrombocytopenia (23.2 weeks). No significant difference in grade ≥3 AEs was seen across payload classes (P = 0.50), although HER2 targeting was associated with higher rates (P = 0.04). Overall objective response rate was 16%, higher with topoisomerase payloads (43%), HER2 targeting (49% versus 6% for TAAs), in breast cancer (39%), and at recommended phase II dosing (25%).

CONCLUSIONS: ADCs show activity across tumor types, with greater efficacy when targeting oncogenes. Toxicities are frequent and often early. Anticipating timing of toxicities is key to effective clinical management.

PMID:40912047 | DOI:10.1016/j.esmoop.2025.105573

J Clin Neurosci. 2025 Sep 3;141:111603. doi: 10.1016/j.jocn.2025.111603. Online ahead of print.

ABSTRACT

BACKGROUND: Meningiomas exhibit considerable phenotypic variation within each WHO grade, thus additional markers are needed to identify prognostically relevant subgroups and optimize long-term management. Among biomarkers, genetic signatures correlate with prognoses. High Ki-67 proliferation indices and TERT promotor mutations and loss of CDKNA are known prognostic markers. Yet, such markers were mainly established by correlative analyses between biomarker expression and retrospective clinical data.

METHODS: Our group has reported on expression of a panel of markers in 176 meningiomas from 170 meningioma patients who underwent surgery from 2005 to 2008 in a previous publication. The markers were growth hormone receptor, insulin-like growth factor 1 receptor, progesterone receptor (PR), CD34, androgen receptor, epidermal growth factor receptor E30, caspase 3, and vascular endothelial growth factor (VEGF). Of the 176 meningiomas, 159 were classified as WHO grade 1, 16 were WHO grade 2 and one was WHO grade 3. We have now surveyed outcome after >10 years. We analyzed possible correlations between marker expression and clinical data such as recurrence, tumor location and patient death.

RESULTS: 27 of 155 WHO grade 1 and 5 of 15 WHO grade 2 meningiomas recurred. No statistically significant correlations between marker expression and recurrence were observed. The 10-year mortality was 10,8% and 53,4% for WHO grade 1 and 2, respectively, with 47 % and 50 % being disease specific for meningioma. A statistically significant negative correlation was observed between PR expression and death related to the tumor (50 % PR expression vs. 89 % in those not dying from the tumor; p = 0.001). Additionally, Ki-67 values showed to be higher in tumors of patients dying from the tumor (8 % vs. 4 %, p = 0.001). A statistically significant relationship was observed between PR and central/skull base (70 % expression in central/skull base vs. 39 % in other locations, p = 0,0002).

CONCLUSIONS: During 10-year follow-up, tumor recurrence was an important cause of death, accounting for approximately half of follow-up mortality despite the benign grading of meningiomas. This ambitious, prospective observational study failed to identify expression of GHr, Igf1r, CD34, EGFR, caspase 3 and VEGF as clinically relevant biomarkers.

PMID:40912009 | DOI:10.1016/j.jocn.2025.111603

Eur J Radiol. 2025 Sep 1;192:112401. doi: 10.1016/j.ejrad.2025.112401. Online ahead of print.

ABSTRACT

OBJECTIVES: Preoperatively identifying patients with unresectable hepatocellular carcinoma (uHCC) who are likely to achieve an objective response to the treatment regimen of transarterial chemoembolization (TACE) plus lenvatinib and programmed death-1 inhibitors (TLP) remains challenging. We aimed to develop and validate a predictive model for tumor response to TLP treatment in patients with uHCC.

MATERIALS AND METHODS: Patients with uHCC who received TLP treatment were divided into training (n = 107), internal validation (n = 46), and external validation (n = 52) cohorts. A nomogram model was developed based on the clinical variables of the training cohort using multivariate logistic regression. The performance of this nomogram model was evaluated using the area under the curve (AUC) and calibration curves, and its performance was compared with that of other predictive models.

RESULTS: The Eastern Cooperative Oncology Group performance status, albumin-bilirubin grade, platelet-to-lymphocyte ratio, tumor distribution, and total bilirubin were identified as independent predictors of objective response. These variables were incorporated to develop the EAPTT model. The AUCs of the EAPTT model were 0.84, 0.90, and 0.85 in the training, internal validation, and external validation cohorts, respectively-statistical analysis via the DeLong test showed that these AUCs were significantly higher than those of the other seven predictive models. Stratification of patients into objective responders and non-responders via the EAPTT model revealed statistically significant progression-free survival and overall survival differences between the two groups.

CONCLUSION: The EAPTT model may enable precise stratification of the efficacy of patients with uHCC receiving TLP treatment, serving to assist in identifying the optimal candidates.

PMID:40911988 | DOI:10.1016/j.ejrad.2025.112401

Eur J Radiol. 2025 Aug 29;192:112398. doi: 10.1016/j.ejrad.2025.112398. Online ahead of print.

ABSTRACT

PURPOSE: Osteoarthritis of the trapeziometacarpal joint is very common, especially in females, and is closely associated with ligamentous laxity and joint subluxation. The dorsoradial ligament (DRL) remains largely unexplored in ultrasound studies despite its clinical relevance. This study aimed to identify the central fascicle of the DRL anatomically and ultrasonographically and to establish a standardized ultrasound examination protocol.

METHODS: This observational cross-sectional validation study was conducted in two phases. First, anatomical dissections were performed on five cadaveric specimens to define anatomical landmarks and guide the development of an ultrasound protocol. In the second phase, bilateral ultrasound examinations were performed on the thumbs of 26 healthy participants (n = 52) to assess ligament morphology and establish normative measurements.

RESULTS: The DRL was successfully identified in all cases, and ultrasound imaging allowed for the reproducible visualization of its central fascicle. The mean joint distance was 0.36 ± 0.13 cm, and the mean ligament area was 0.20 ± 0.08 cm². Significant differences were observed between the sexes, with males having statistically higher distances (p < 0.05) than females from the tubercle of the trapezium to the skin and from the tubercle of the trapezium to the upper edge of the first metacarpal. However, no significant correlations were found with age, and no significant asymmetries were found between both sides.

CONCLUSION: The DRL can be reliably assessed by ultrasound and provides clinically relevant parameters to assess ligament morphology. The standardized protocol developed provides a valuable tool for detecting ligamentous insufficiency and capsuloligamentous changes. These findings contribute to understanding the anatomy and function of the DRL and provide a basis for future research into its role in joint stability and osteoarthritic progression.

PMID:40911987 | DOI:10.1016/j.ejrad.2025.112398

Healthc (Amst). 2025 Sep 4;13(2):100767. doi: 10.1016/j.hjdsi.2025.100767. Online ahead of print.

NO ABSTRACT

PMID:40911956 | DOI:10.1016/j.hjdsi.2025.100767

Oral Oncol. 2025 Sep 4;169:107670. doi: 10.1016/j.oraloncology.2025.107670. Online ahead of print.

ABSTRACT

OBJECTIVE: Oral squamous cell carcinoma (OSCC) with bone invasion are staged as pT4a, potentially upstaging smaller tumors. This study aimed to evaluate the oncological benefit of postoperative radiotherapy (PORT) in pT4aN0 OSCC with respect to tumor size and without other risk factors.

METHODS: This retrospective matched cohort study included pT4aN0 OSCC patients with bone invasion treated surgically (R0) between 2010 and 2022. Each case was 1:1 matched to a pT1-3 N0 OSCC patient based on tumor size, but without bone invasion. The primary endpoint was overall survival (OS), secondary endpoints included the recurrence-free survival and outcome predictors.

RESULTS: A total of 156 patients were analyzed (78 per group). There were no statistically significant differences in 3-year OS between both groups in general (78.2%, 95%CI: 68.6-87.8 vs. 80.0%, 95%CI: 68.4-91.6). After stratification for pT2 criteria, there was also no significant difference between both groups if PORT was omitted (63.9%, 95%CI: 44.2-92.4 vs. 70.5%, 95%CI: 55.0-90.0). Multivariate analysis identified age and poor differentiation (grade III) as significant predictors of worse OS, while PORT showed no independent survival benefit.

CONCLUSION: In small OSCC staged pT4a due to bone invasion and lacking other risk factors, PORT demonstrated no statistically significant improvement in OS when matched for tumor size. Further prospective trials and larger cohorts are warranted to confirm these findings.

PMID:40911948 | DOI:10.1016/j.oraloncology.2025.107670

Curr Pharm Teach Learn. 2025 Sep 4;17(12):102467. doi: 10.1016/j.cptl.2025.102467. Online ahead of print.

ABSTRACT

OBJECTIVE: To develop and evaluate the effectiveness of a two-step training pilot program in the Doctor of Pharmacy curriculum to prepare students to utilize medical language interpreters during patient interactions.

METHODS: The Advanced Communications and Counseling Skills course was a two-step program developed to train professional year two (P2) student pharmacists to effectively utilize interpreters during patient encounters. Training included completion of virtual modules and in-person standardized patient encounters where the use of an interpreter was required to counsel. Students then demonstrated the communication skills acquired at a health fair for patients that spoke a language other than English. Student perspective, comfort, and confidence of using interpreter services were measured and compared pre and post program implementation. Patient satisfaction with P2 communication skills were also assessed.

RESULTS: A total of 23 P2 students completed the program. Overall, summary statistics indicate trends for student improvement in all areas, with students’ confidence in using an interpreter improved. All students were satisfied with the training modules (100.0 %) and the majority felt prepared in using an interpreter (94.4 %). Patients were very satisfied (76.5 %) or satisfied (23.5 %) with the students’ ability to utilize an interpreter during the patient encounter at the health fair.

CONCLUSION: The Two-Step program provides students with training on how to utilize interpreters. Students are receptive to participating in the course and satisfied with the communication skills acquired. Embedding this course in the pharmacy curriculum could increase student confidence and have a positive impact on patient communication experience.

PMID:40911947 | DOI:10.1016/j.cptl.2025.102467