Bleomycin-induced flagellate-like skin pigmentation in a 15-year-old girl: a case report and review.

We present a detailed report of a case of flagellar-like skin pigmentation observed in a 15-year-old female patient diagnosed with ovarian yolk sac tumor following administration of a chemotherapy regimen containing bleomycin. After three cycles of chemotherapy, the patient exhibited characteristic painless, non-pruritic linear hyperpigmentation on her trunk and back. This case underscores the significance of paying attention to bleomycin-associated dermal toxicity, emphasizing the need for its early detection and management to alleviate the patient's psychological and physical distress.

Advancing precision photothermal therapy by integrating armored gold nanostars with real-time photoacoustic thermometry and imaging.

Nanoparticle-mediated photothermal therapy (PTT) is a promising strategy for cancer treatment; however, nanoparticle instability and lack of precise imaging tools for real-time temperature monitoring during therapy and nanoparticle tracking have hindered investigations in animal models. To address these critical issues, we present a theranostic platform that seamlessly integrates armored core-gold nanostar (AC-GNS)-mediated PTT with full-view photoacoustic computed tomography (PACT), enabling nanoparticle tracking and real-time imaging-guided PTT in deep tissues. The AC-GNS platform delivered exceptional photostability and thermal resilience beyond those of conventional nanoparticles while serving as a high-performance contrast agent for PACT and a photothermal transducer for PTT.

Broadband imaging spectrometer based on conical diffraction for extreme ultraviolet source.

We demonstrate what we believe to be a novel design of an imaging spectrometer tailored for extreme ultraviolet (EUV) sources, employing uniformly spaced planar gratings. For what appears to be the first time, our approach adopts a grating-toroid-grating configuration for spectral measurements femtosecond high-harmonic EUV lasers. This spectrometer performs superior in point-to-point imaging modes and the resulting experimental setup is very simple.

Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive exPlanations.

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a prevalent and progressive liver disorder closely linked to obesity and metabolic dysregulation. Traditional anthropometric measures such as body mass index (BMI) are limited in their ability to capture fat distribution and associated risk. This study aimed to develop and validate machine learning (ML) models for predicting MAFLD using detailed body composition metrics and to explore the relative contributions of adipose tissue features through explainable ML techniques.

A robust and effective framework for 3D scene reconstruction and high-quality rendering in nasal endoscopy surgery.

In nasal endoscopic surgery, the narrow nasal cavity restricts the surgical field of view and the manipulation of surgical instruments. Therefore, precise real-time intraoperative navigation, which can provide precise 3D information, plays a crucial role in avoiding critical areas with dense blood vessels and nerves. Although significant progress has been made in endoscopic 3D reconstruction methods, their application in nasal scenarios still faces numerous challenges.

Short term prediction of photovoltaic power with time embedding temporal convolutional networks.

The incorporation of both spatial and temporal characteristics is vital for improving the predictive accuracy of photovoltaic (PV) power generation forecasting. However, in multivariate time series forecasting, an excessive number of features and traditional decomposition methods often lead to information redundancy and data leakage, resulting in prediction bias. To address these limitations, this study introduces the Time-Embedding Temporal Convolutional Network (ETCN), providing an innovative solution.

LL-MAROCO: A Large Language Model-Assisted Robotic System for Oral and Craniomaxillofacial Osteotomy.

Oral and craniomaxillofacial bone deformities necessitate treatment through osteotomy. Robot-assisted osteotomy appears promising in oral and craniomaxillofacial surgery, but it lacks sufficient intelligence and comprehensive integration of navigation tracking with surgical planning. This study aims to develop an intelligent surgical robot, based on the large language model ChatGPT-4, to enable autonomous planning for oral and craniomaxillofacial osteotomies.

Intrinsic Antibacterial Urushiol-Based Benzoxazine Polymer Coating for Marine Antifouling Applications.

Marine antifouling coatings that rely on the release of antifouling agents are the most prevalent and effective strategy for combating fouling. However, the environmental concerns arising from the widespread discharge of these agents into marine ecosystems cannot be overlooked. An innovative and promising alternative involves incorporating antimicrobial groups into polymers to create coatings endowed with intrinsic antimicrobial properties.

Safety and efficacy of rechallenge with immune checkpoint inhibitors and anlotinib in advanced non-small cell lung cancer without targetable driver mutations: a retrospective analysis.

Objective: This study assessed the safety and efficacy of rechallenging patients in advanced non-small cell lung cancer (NSCLC) without targetable driver mutations using a combination of immune checkpoint inhibitors (ICIs) and anlotinib following progression after prior immunotherapy.

Methods: A retrospective analysis was performed on 14 patients who received rechallenge with ICIs combined with anlotinib at the First Affiliated Hospital of Guangzhou University of Chinese Medicine. China, between March 2020 and June 2024.

IDNet: A Diffusion Model-Enhanced Framework for Accurate Cranio-Maxillofacial Bone Defect Repair.

Cranio-maxillofacial bone defect repair poses significant challenges in oral and maxillofacial surgery due to the complex anatomy of the region and its substantial impact on patients' physiological function, aesthetic appearance, and quality of life. Inaccurate reconstruction can result in serious complications, including functional impairment and psychological trauma. Traditional methods have notable limitations for complex defects, underscoring the need for advanced computational approaches to achieve high-precision personalized reconstruction.

Comparison and Analysis of the Drug-Resistance Mechanism of Osimertinib- and Almonertinib-Resistant Cell Lines.

Non-small-cell lung cancer remains the leading cause of cancer-related deaths globally, and epidermal growth factor receptor mutations have been identified as crucial drivers of the disease. Encouragingly, epidermal growth factor receptor tyrosine kinase inhibitors have demonstrated promising clinical outcomes. Nonetheless, the emergence of resistance to third-generation EGFR-TKIs like osimertinib and almonertinib is an inevitable challenge.

Enhanced denitrification under saline Conditions: Glycine betaine as a key osmoprotectant.

Biological denitrification is significantly inhibited by salinity, which adversely affects microbial activity and reduces efficiency. This study aimed to evaluate the impact of salinity on denitrification performance and assess the potential of glycine betaine (GB) as an osmotic pressure regulator and protective agent. Results indicated that under the optimal conditions, including an influent nitrate concentration of 51.

RelVid: Relational Learning with Vision-Language Models for Weakly Video Anomaly Detection.

Weakly supervised video anomaly detection aims to identify abnormal events in video sequences without requiring frame-level supervision, which is a challenging task in computer vision. Traditional methods typically rely on low-level visual features with weak supervision from a single backbone branch, which often struggles to capture the distinctive characteristics of different categories. This limitation reduces their adaptability to real-world scenarios.

Age-related differences in primary central nervous system lymphomas based on the SEER database.

Objective: The aim of this study was to compare prognostic factors and survival outcomes in patients with primary central nervous system lymphoma (PCNSL).

Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried for patients diagnosed with PCNSL between 2000 and 2019.

Results: Between 2000 and 2019, a total of 5,812 patients were diagnosed with PCNSL, of whom 2,175 (37%) were ≤ 60 years old and 3,637 (63%) were >60 years old.

NaMA-Mamba: Foundation model for generalizable nasal disease detection using masked autoencoder with Mamba on endoscopic images.

Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In this work, the challenge is addressed through two key innovations, the creation of the first large-scale pre-training dataset of nasal endoscopic images, and the development of a novel self-learning AI system specifically designed for nasal endoscopy, named NaMA-Mamba.

Siloxane-Mediated Schiff Base Bio-Based Curing Agent: Achieving Epoxy Vitrimer with Excellent Mechanical Properties, Low Dielectric Constant and Rapid Degradation Characteristics.

Epoxy resin is indispensable in various applications due to its outstanding properties. However, its limited recyclability and associated environmental issues pose significant challenges for sustainable development. To address this issue, integrating recyclable Schiff base groups into epoxy resin systems to construct epoxy vitrimer with dynamic properties has become a promising strategy.

Updated Bayesian network meta-analysis on the efficacy and safety of PD-1 versus PD-L1 inhibitors in first-line treatment with chemotherapy for extensive-stage small-cell lung cancer.

Objective: To compare the efficacy and safety of programmed cell death 1 inhibitors plus chemotherapy (PD-1 + Chemo) and programmed cell death ligand 1 inhibitors plus chemotherapy (PD-L1 + Chemo) for the treatment of extensive-stage small-cell lung cancer (ES-SCLC).

Methods: We performed a meta-analysis of relevant data using R software, considering overall survival (OS), progression-free survival (PFS), and grade ≥ 3 treatment-related adverse events (TRAES).

Results: PD-1 + Chemo (OS: hazard ratio [HR] 0.

SeLa-MIL: Developing an instance-level classifier via weakly-supervised self-training for whole slide image classification.

Background And Objective: Pathology image classification is crucial in clinical cancer diagnosis and computer-aided diagnosis. Whole Slide Image (WSI) classification is often framed as a multiple instance learning (MIL) problem due to the high cost of detailed patch-level annotations. Existing MIL methods primarily focus on bag-level classification, often overlooking critical instance-level information, which results in suboptimal outcomes.

Novel non-HDLc/HDLc ratio for predicting MASLD: a cross-sectional study in a Chinese health screening population.

Background: Previous studies have shown a positive correlation between the non-high-density lipoprotein cholesterol/high-density lipoprotein cholesterol(non-HDLc/HDLc ratio) and metabolism-associated steatohepatitis (MASLD), suggesting it is a superior predictor of MASLD.The aim of this study is to assess the predictive value of the non-HDLc/HDLc ratio for MASLD.

Methods: In this study, we retrospectively analyzed data from 4,498 adult patients at the Health Management Centre of Guangdong Provincial Hospital of Integrative Medicine, regardless of gender, and the diagnostic criteria for MASLD were derived from guidelines.

Waist-to-hip ratio and nonalcoholic fatty liver disease: a clinical observational and Mendelian randomization analysis.

Background: Obesity often coincides with non-alcoholic fatty liver disease (NAFLD), yet a significant portion of NAFLD patients exhibit normal body mass index (BMI) but have abdominal obesity. Recognizing this discrepancy, we aimed to delve deeper into this phenomenon through observational studies coupled with two-sample Mendelian randomization (MR) analysis, with waist-to-hip ratio (WHR) serving as the indicator for abdominal obesity. Our objective was to ascertain whether WHR correlates with an increased risk of NAFLD development.

Effect of Different Concentrations of Chlorhexidine on Anti-Plaque in Oral Care Practice: A Systematic Review and Network Meta-Analysis.

Objectives: The aim of this network meta-analysis was to compare the anti-plaque effects and adverse effects of different concentrations of chlorhexidine (CHX).

Methods: PubMed, OVID Embase and the Cochrane Library were searched from inception to October 2023 for randomised controlled trials (RCTs) of different concentrations of CHX in healthy populations. Random-effects network meta-analyses were performed to summarise the evidence, and the Grading of Recommendations Assessment, Development and Evaluation framework was used to rate the certainty of evidence.

Efficacy of respiratory support therapies during pulmonary rehabilitation exercise training in chronic obstructive pulmonary disease patients: a systematic review and network meta-analysis.

Background: Exercise training is fundamental in pulmonary rehabilitation (PR), but patients with chronic obstructive pulmonary disease (COPD) often struggle with exercise intolerance. Respiratory support during exercise in COPD patients may be a beneficial adjunct therapy. In this study, the effect of different respiratory support therapy during pulmonary rehabilitation exercise training in COPD patients was assessed through a network meta-analysis.