搜索结果：Evaluation review

The environmental challenges posed by heavy metal contamination in sludge leachate are becoming increasingly severe, necessitating the development of highly efficient remediation technologies. Among various treatment approaches, magnetic adsorbents have garnered significant attention as a promising solution due to their outstanding adsorption performance, convenient magnetic separation characteristics, and potential for regeneration. This paper systematically reviews the latest research progress on magnetic adsorbents designed for the complex system of sludge leachate, covering synthesis methods, surface functionalization, adsorption mechanisms, and performance evaluation. Key synthesis strategies are analyzed, including magnetic core preparation, inorganic coating, carbon composites, organic polymer grafting, functional molecule impregnation, and metal-organic framework (MOF) composites. The mechanisms by which these strategies influence material adsorption capacity, selectivity, and stability are elucidated. Despite significant achievements in laboratory studies, practical applications still face challenges such as large-scale synthesis, regeneration efficiency, cyclic stability, and adaptability to complex water bodies. Future research should focus on green synthetic pathways to advance the industrial application of structurally functional magnetic composite materials, providing systematic solutions from material design to process optimization for the sustainable remediation of heavy metal contamination in sludge leachate.

Chronic pain remains a critical clinical issue worldwide, with adverse effects on the quality of life of oncology patients. Meanwhile, the overuse of opioids to treat or alleviate chronic cancer pain has contributed to a global opioid crisis. The increasing accessibility of high-quality clinical datasets and computational frameworks has promoted the use of machine learning (ML) techniques in clinical practice to manage opioid consumption. This review investigates the current bibliography referring to the role of applied ML techniques in opioid administration in patients with chronic cancer pain. The objective of the current scoping review, according to population, intervention, comparison, and outcome (PICO) standards, was to evaluate the effectiveness of ML techniques in monitoring opioid consumption in patients with chronic cancer pain. This review includes scientific journal papers published from 2010 to 2024 that use healthcare data from patients with chronic cancer pain, apply machine learning techniques, and may address the potential consequences of the misuse of opioids. A systematic literature search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed in PubMed and Google Scholar databases. Data extracted include the study's goal, dataset used, cohort selected, types of ML models created, model evaluation metrics, and the details of the ML tools and techniques used to create the models. After conducting the screening process, 50 articles were identified, but only four focused specifically on or included data of patients with chronic cancer pain where ML techniques were applied. The four included studies showed high performance (area under the curve {AUC}: >0.8) in predicting opioid adherence, misuse, and long-term use. Although generalizability remains limited due to small sample sizes and a lack of external validation, it sets distinct limits in applying these methods in clinical use. After a thorough review of recent literature, ML models demonstrated promising accuracy in predicting opioid adherence, misuse, and long-term use among patients with chronic cancer pain. However, these findings are based on studies with limited sample sizes and a lack of external validation, which restricts their generalizability. Future research should focus specifically on populations with chronic cancer pain and expand predictive models to incorporate a combination of clinical, psychosocial, biometric, and genomic data. This approach may enable more accurate, personalized, and safer opioid management in oncology care.

There is a need to better understand traditional, complementary, and integrative medicine (TCIM) and health literacy (HL) as intersecting fields of research, and to identify the impact of HL on TCIM use and practices. This is best achieved through validated instruments that measure TCIM-specific HL. This critical, systematic review aimed to identify the use and features of validated instruments for measuring HL in the general adult population using TCIM, and the degree to which those elements measure TCIM-specific HL. Evaluation of the methodological rigor of instrument testing and grade determination was undertaken using the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) checklist and an adapted version of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-COSMIN manual for the systematic review of patient-reported outcome measures. A total of 21 validated HL instruments, identified from 29 studies, were included in the review. Ten instruments were specific or partially specific to TCIM. Most instruments assessed two or more HL domains (n = 14), including five that assessed all four domains of the integrated conceptual model of HL. Approximately one quarter of all instruments received an overall assessment rating of "very good" quality (n = 5), with majority of instruments rating as either "doubtful" (n = 9) or "inadequate" (n = 7) quality. The examination of HL in relation to TCIM use and users will clearly benefit the TCIM research field and the wider health research community. Focused efforts to develop validated TCIM-specific HL instruments will ensure TCIM use and users are not excluded from HL scholarship and advancements.

Cardiometabolic diseases, encompassing obesity, insulin resistance, type 2 diabetes (T2D), metabolic dysfunction-associated steatotic liver disease (MASLD), hypertension, and atherosclerotic cardiovascular disease (ASCVD), represent a vast continuum driven by multi-organ network dysregulation. Clinical risk assessment remains dominated by late-stage measures (e.g., fasting glucose, HbA1c, standard lipids). While these assessments predominate the literature and clinical trial endpoints, each incompletely capture early mechanistic risk, inter-individual heterogeneity, and differential response to interventions. Multiomics (genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, microbiomics, and extracellular vesicle/exosome cargo profiling) expands the biomarker landscape but introduces translational barriers: high dimensionality, cohort heterogeneity, limited causal inference, and insufficient validation pipelines. AI-driven systems biology platforms can support cardiometabolic biomarker discovery and therapeutic translation by enabling systems-level biological inference across heterogeneous datasets, prioritizing mechanism and traceability over purely correlation-based models. GATC Health's Operon™ platform is described as a proprietary, AI-driven internal scientific computing platform designed to support therapeutic discovery and development decision-making across the pharmaceutical lifecycle, including evaluation of drug efficacy, safety, off-target effects, pharmacokinetics (PK), pharmacodynamics (PD), and overall development risk. Operon evolved from earlier generations of GATC Health's internal multiomic modeling systems (formerly referred to as the Multiomics Advanced Technology, MAT) and incorporates expanded data types, orchestration layers, validation workflows, and productization frameworks. Operon is operated by GATC scientists and generates structured, productized outputs (e.g., formal assessments, analyses, and decision frameworks) that are reviewed by experts. Operon methodologies have undergone internal validation and independent academic evaluation under blinded conditions, with reported classification performance (true positive rate 86% and true negative rate 91%) in controlled evaluation settings; these performance metrics should not be interpreted as guarantees of clinical success. This review provides a T2D-centered cardiometabolic biomarker landscape with cardiovascular extension and outlines how Operon-enabled multiomic integration and scenario-based simulation can support early screening, endotype stratification, mechanistic interpretation, and precision intervention design, including AI-guided polypharmacology strategies.

Visual impairment affects approximately 2.2 billion people worldwide and has significant impacts on various aspects of life, including physical, social, economic, and emotional domains. Assessing the quality of life of these individuals is essential for identifying their needs and guiding health promotion strategies. However, no studies were found that systematically cataloged the instruments used for this evaluation specifically for people with visual impairment. This study aims to systematically map the scientific evidence regarding the instruments used to assess quality of life in individuals with visual impairment at any health care level. The population, concept, and context framework guided the development of the research question: What instruments are available in the scientific literature to assess the quality of life of people with visual impairment across health care levels? Data will be collected from major databases and gray literature, with duplicates managed in Mendeley and screening conducted independently by 2 reviewers using Rayyan. Full texts will be assessed based on eligibility criteria, and data will be synthesized in Microsoft Excel and reported using a flowchart and narrative summary, following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. This protocol was registered on the Open Science Framework platform on July 28, 2025. The results of this study will be disseminated through publication in a peer-reviewed scientific journal. It is expected that the findings will provide valuable support for the development and advancement of a broader research project. Identifying and evaluating instruments used to assess the quality of life in individuals with visual impairment are crucial to ensure the use of reliable and scientifically sound tools. This process not only advances scientific knowledge but also informs public health policies aimed at promoting equity, inclusion, and improved living conditions for this population.

To review the recommended imaging modalities for pre-transplant evaluation in patients with sickle cell disease (SCD) undergoing allogeneic hematopoietic stem cell transplantation (HSCT). This was a narrative review focusing on key imaging techniques employed to assess organ damage and stratify risks prior to HSCT in patients with SCD, including transcranial Doppler (TCD) ultrasonography, brain magnetic resonance imaging (MRI) with magnetic resonance angiography (MRA), MRI for osteonecrosis evaluation, and MRI-based hepatic iron quantification. TCD, including blind Doppler and TCD imaging (TCDI), plays a critical role in detecting in-creased cerebral blood flow velocities associated with stroke risk. Brain MRI/MRA is essential for identifying silent cerebral infarcts and intracranial vasculopathy, even in patients with normal TCDI velocities. Bone MRI allows early detection of osteonecrosis, which is frequently asymptomatic in SCD. Liver MRI, using R2 relaxometry and T2*-weighting, provides accurate quantification of hepatic iron overload, an important risk factor for transplant-related complications. Cardiac MRI, chest computed tomography, and liver ultrasound are also recommended to help stratify pre-HSCT risk and identify organ damage. A structured imaging protocol is essential for pre-HSCT assessment in SCD. Radiologists play a pivotal role in identifying subclinical organ damage and providing information critical to transplant candidacy and perioperative management. Revisar as modalidades de imagem recomendadas na avaliação pré-transplante de pacientes com doença falciforme (DF) submetidos ao transplante alogênico de célulastronco hematopoéticas (TCTH), destacando seus as-pectos técnicos e relevância clínica. Tratase de uma revisão narrativa com foco nas principais técnicas de imagem empregadas para avaliar danos orgânicos e estratificar riscos antes do TCTH em pacientes com doença falciforme (DF), incluindo a ultrassonografia com Doppler transcraniano (DTC), a ressonância magnética (RM) cerebral associada à angiografia por ressonância magnética (ARM), a RM para avaliação de osteonecrose e a quantificação da sobrecarga de ferro hepático por RM. O DTC, tanto na forma cega quanto com imagem (DTCI), é fundamental na detecção de velocidades elevadas do fluxo cerebral associadas ao risco de acidente vascular cerebral. A RM cerebral e a ARM permitem identificar infartos cerebrais silenciosos e vasculopatia intracraniana, mesmo em pacientes com DTCI normal. A RM óssea possibilita a detecção precoce de osteonecrose, frequentemente assintomática. A RM hepática, por meio de sequências T2* ou relaxometria R2, fornece quantificação precisa e não invasiva da sobrecarga de ferro hepático, fator relevante para complicações relacionadas ao transplante. Um protocolo estruturado de imagem é essencial na avaliação pré-TCTH de pacientes com DF, sendo o radiologista peça-chave na identificação de danos subclínicos e no suporte à decisão clínica.

In some of the existing literature, obesity is associated with increased complications in those who undergo lower limb arthroplasty. We conducted a systematic review and meta-analysis to assess if pre-arthroplasty weight loss mitigates increased post-operative risks. This systematic review and meta-analysis was registered on PROSPERO (CRD42023431110). Key terms were utilized to search PubMed, EMBASE, Ovid, Web of Science, Google Scholar, and Europe PMC. Peer-reviewed articles published between January 1, 2010, and December 31, 2024, were screened. Studies that reported specific outcomes (superficial wound infection, deep wound infection, pulmonary embolus [PE], deep vein thrombosis [DVT], and revision surgery) in an intervention group (patients with a BMI > 30 kg/m2 who underwent pre-arthroplasty weight loss) and a control group (patients who underwent arthroplasty without preceding weight loss) 90 days post-arthroplasty were selected and data were extracted from studies meeting these inclusion criteria. Data were analyzed using a random effects model. Twenty-one articles were included in the meta-analysis. In people with obesity, pre-arthroplasty weight loss was associated with an increased risk of revision surgery in the first 90 days following lower limb arthroplasty (OR 1.37 [1.01-1.84], p = 0.04). Weight loss did not alter the risk of post-operative DVT, PE, superficial wound infections, and deep wound infections. Our results demonstrate that pre-arthroplasty weight loss does not improve short-term post-operative outcomes in people with obesity. Large, well-designed prospective studies should be performed to provide robust data for the development of evidence-based guidelines for lower limb arthroplasty in people living with obesity.

The exponential growth of genomic and proteomic data has made computational protein-protein interaction (PPI) prediction indispensable, driving the need for a comprehensive and method-aware evaluation of supervised learning approaches. PPIs are fundamental to understanding cellular processes and disease mechanisms, yet experimental identification remains slow, costly, and difficult to scale. This survey systematically investigates ten supervised learning models-Extreme Learning Machine (ELM), Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), Deep Neural Networks (DNNs), Naïve Bayes, Probabilistic Decision Tree, Support Vector Machine (SVM), Least Squares SVM (LS-SVM), K-Nearest Neighbor (KNN), and Weighted K-Nearest Neighbor (WKNN)-through a tri-layered framework that integrates Comparative Quantitative Analysis, Comparative Observational Analysis, and Experimental Evaluations. Beyond conventional accuracy summaries, this work provides critical commentary tied to real-world use, analyzing where techniques succeed or fail in practice-for instance, when instance-based methods bottleneck during inference, when kernel choices influence SVM variance, or when deep architectures trade accuracy for computational cost. The survey also offers concrete deployment guidance, such as calibration insights for WKNN versus KNN under varying feature noise or dataset curation quality, delivering operational perspectives that typical surveys omit. Comparative Quantitative Analysis consolidates metrics such as accuracy, F1-score, and computational time from the existing literature, while Comparative Observational Analysis evaluates interpretability, scalability, dataset suitability, and efficiency. Complementing these, Experimental Evaluations conducted by the authors empirically validate model performance on benchmark datasets. Together, these layers provide a unified and evidence-backed perspective on algorithmic strengths, weaknesses, and practical applicability. Findings show that GNNs and DNNs achieve the highest predictive accuracy due to their ability to capture structural and topological relationships, whereas ELM and Naïve Bayes offer superior efficiency. SVM and LS-SVM maintain robust stability under noisy conditions, and CNNs are well-suited for sequence-based prediction tasks. By combining empirical validation, critical insights, and deployment-focused recommendations, this survey delivers decision-grade guidance that bridges theoretical understanding with real-world implementation, thus clarifying the trade-offs among accuracy, efficiency, and scalability in PPI detection research.

Group antenatal care (GANC) is an alternative to traditional individual antenatal care (IANC), which combines health assessment, interactive learning, and community building in group sessions. GANC has been associated with positive health outcomes. To scale up GANC, more evidence is needed on the financial implications of its initial implementation and (long-term) cost-effectiveness. This study aims to review and synthesise the available evidence on the economics of GANC. We searched for observational and experimental studies assessing the cost aspects of implementing and running GANC with or without comparison with IANC. We searched PubMed, EMBASE, and Ovid Emcare up to 22 August 2024 using keywords and controlled vocabulary without restriction by year of publication. CASP Economic Evaluation Checklist. Narrative synthesis. A limited number of studies (n = 9) addressing the costs and/or benefits of GANC were eligible to be included in the review. These studies varied considerably in setting, design, quality, type of cost data, cost categories included and perspective used. Evidence on the costs of GANC is sparse. Future studies of the lifetime costs and health outcomes of GANC compared with IANC are needed to gain insight into the cost implications and cost-effectiveness of GANC and to scale up its implementation. PROSPERO 2023 CRD42023454379.

Aim: This literature review presents the biological evaluation of light-curing 3D printing materials containing methacrylic and acrylic resin in dentistry. The sample was 42 articles published between 2008 and 2025, available on PubMed, Scopus, Cochrane, and Google Scholar. The articles were analyzed following the assessment requirements of ISO 10993-2018 (Endpoint) regarding the biological evaluation of each Medical Device. The first selection criterion of the articles was based on the PRISMA schema, concerned with the application of these materials in various fields of dentistry used in 3D printing (e.g., material for crowns and bridges, night, and surgical guide, orthodontic, and denture base). The second criterion included the composition of materials (e.g., catalysts, methacrylic resins, and stabilizers) and the post-curing process. Results: The topics discussed in the literature included: (a) estrogenic interactions, sensitization, and the zebra fish model to determine acute toxicity; (b) the main post-processes affecting biocompatibility, i.e., alcohol washing and polymerization in light ovens; and (c) the modification of 3D resins using various types of nanomaterials. Conclusions: 3D resins can be used safely in dentistry to make various types of restorations, provided that the polymerization, washing with alcohol and post-polymerization in a light oven follow the manufacturer's specifications.

Splenic artery aneurysm (SAA) rupture is a deceptive cause of sudden unexpected death presenting significant medicolegal challenges. This retrospective case series and comprehensive literature review analyzes the clinicopathological features of six nontraumatic fatal SAA ruptures. Clinical presentations were predominantly nonspecific, resulting in diagnostic delays and medicolegal inquiries in two cases. A size-rupture paradox was observed, as fatal hemorrhage occurred across a wide diameter spectrum (3-12 cm), proving that small aneurysms also carry lethal potential. The literature review elucidates the multifactorial etiopathogenesis of SAA, encompassing genetic, hormonal, hemodynamic, and inflammatory factors. Furthermore, the clinical trajectory of delayed fatality is explained by the double-rupture phenomenon, which creates a deceptive lucid interval. Histochemical evaluation utilizing Elastic Verhoeff-Van Gieson (EVG) staining was pivotal, demonstrating severe internal elastic lamina loss to confirm spontaneous degenerative rupture and exclude trauma. Consequently, meticulous celiac trunk dissection and routine EVG histochemistry must be integrated into forensic autopsy protocols evaluating unexplained hemoperitoneum to accurately determine the cause of death and address liability disputes.

Phenylketonuria (PKU) is an autosomal recessive disorder characterised by an inborn error of phenylalanine (Phe) metabolism. Such errors are attributed to pathogenic gene variants causing phenylalanine hydroxylase (PAH) deficiency, impairing the hydroxylation of phenylalanine to tyrosine in the Phe metabolic pathway. This defect leads to plasma Phe concentrations above the normal range. If untreated, hyperphenylalaninemia can adversely affect brain function, leading to severe intellectual disability and seizures. Since 1969, the newborn dried blood spot test has remained the main method of early screening and diagnosis for PKU. The primary therapeutic management is a lifelong phenylalanine-restricted diet with the aim of decreasing plasma Phe levels. The recommended diet consists of avoiding high-protein foods such as meat, fish, eggs and nuts, and can be supplemented with high-protein medical formulas which are low in phenylalanine. Pharmacological interventions such as sapropterin, sepiapterin and pegvaliase can also be used as treatment adjuncts in patients with PKU. Currently, small-molecule inhibitors reducing renal phenylalanine reabsorption are being explored as a potential therapeutic intervention. Furthermore, novel gene-editing techniques are under evaluation as potential curative strategies, with preclinical studies showing promising results in correcting pathogenic phenylalanine hydroxylase variants. This non-systematic review synthesises current literature on the management of PKU, with a focus on dietary interventions and recommendations.

The implementation of photon-counting (PCD) CT has led to substantial technologic improvements over conventional energy-integrated detector (EID) CT. These advances include better spatial and contrast resolution, intrinsic spectral information, and potential for reductions in radiation doses and contrast media volumes. Since the clinical introduction of PCD CT, numerous studies have been performed to investigate the advantages and potential impact brought by this new technology for various clinical scenarios with respect to cardiothoracic imaging. For example, PCD CT offers improved visualization of pulmonary and cardiac anatomy and allows dose reduction in the assessment of pulmonary vasculature, nodules, emphysema, and interstitial lung diseases. PCD CT also improves visualization of coronary plaque and stents, provides more accurate assessment of coronary stenoses, and facilitates myocardial tissue characterization. The faster data acquisition enabled by PCD CT additionally aids cardiothoracic evaluation in pediatric and/or dyspneic patients. This AJR Expert Panel Narrative Review explores these state-of-the art cardiothoracic applications of PCD CT considering supporting evidence, technical features, protocols, and areas of greatest potential clinical benefit. Ongoing implementation challenges and remaining research priorities that warrant attention to support the integration of PCD CT into standard cardiothoracic imaging practice are highlighted.

Background/Objectives: Dietary antioxidants are frequently utilized by breast cancer (BC) patients to mitigate treatment-related toxicities and enhance quality of life. However, their clinical efficacy remains highly controversial due to conflicting epidemiological and clinical data. This review aims to critically evaluate the molecular mechanisms, clinical outcomes, and translational challenges of antioxidant supplementation in BC management. Methods: A comprehensive evaluation of current literature-encompassing observational cohorts, randomized controlled trials, and mechanistic in vitro/in vivo models-was conducted. The analysis focused on the pharmacological interactions of diverse bioactive compounds (polyphenols, vitamins, carotenoids) with BC progression and standard antineoplastic regimens. Results: Current evidence demonstrates a paradoxical, double-edged role of antioxidants in oncology. While specific interventions (e.g., Coenzyme Q10, melatonin) effectively ameliorate treatment-induced toxicities without compromising therapeutic efficacy, the concurrent administration of antioxidants during cytotoxic chemotherapy can inadvertently neutralize essential reactive oxygen species (ROS), correlating with increased disease recurrence and mortality. Furthermore, clinical translation is severely hindered by the intrinsic hydrophobicity of natural compounds, the lack of whole-food matrix standardization, and dose-dependent hepatotoxicity. Emerging targeted delivery systems, such as lipid nanoformulations, show significant potential in overcoming these pharmacokinetic barriers. Conclusions: The therapeutic viability of antioxidant supplementation in BC is not universal; it is heavily dictated by intrinsic tumor biology, specific treatment modalities, and chronopharmacology. These findings underscore a critical biological imperative to transition from generalized dietary guidelines toward a rigorous paradigm of precision nutritional oncology, strictly avoiding concurrent antioxidant supplementation during active oxidative therapies.

The objective is to assess the effectiveness and safety of combining PD-1 inhibitors with CTLA-4 inhibitors for melanoma treatment, drawing on current meta-analysis findings and evaluating the supporting evidence. We used medical subject words and free text words (such as "PD-1 inhibitor", "CTLA-4 inhibitor", "melanoma") as search keywords to search the literature in six literature databases from the establishment of the database to 11 April 2025. Using the PICO (Participant, Intervention, Control, and Outcome) framework, we identified 27 unique associations between combination treatment efficacy outcomes and 70 unique associations between adverse event outcomes, which were re-evaluated using a random effects model. A total of 10 meta-analysis were included, including 36 randomized controlled trials and two retrospective studies. According to the evaluation meta-analysis of AMSTAR 2 (A MeaSurement Tool to Assess Systematic Reviews, version 2), all 10 meta-analysis were of very low quality. The association of outcome indicators was re-analyzed based on the random effects model, of which 26 associations showed high efficacy of combination therapy and 66 associations showed poor safety of combination therapy. In conclusion, a PD-1 inhibitor combined with a CTLA-4 inhibitor is a very effective method for the treatment of melanoma, but the incidence of various types of adverse reactions is high, and the evidence is not reliable. Therefore, future studies need higher quality evidence.

Stillbirth is a major contributor to perinatal mortality. Placental examination is central to stillbirth evaluation. Published evidence is heterogeneous in lesion taxonomy, sampling approaches, comparator selection, and confounder control. We conducted a systematic review following PRISMA guidelines. We searched PubMed, Embase, and Scopus and screened reference lists to identify comparative observational studies. These studies evaluated placental histopathology in stillbirth compared with live birth or other clearly defined nonstillbirth comparator groups. We included studies that estimated stillbirth associations and those providing comparative insights into lesion reporting. Data were extracted on study design, stillbirth definition, comparator characteristics, placental sampling and reporting methods, lesion definitions, and reported association measures. Risk of bias was assessed using the Newcastle-Ottawa Scale. Due to substantial clinical and methodological heterogeneity, findings were synthesized narratively with structured tabulation. Across included studies, stillbirth was consistently associated with multidomain placental pathology. This was most prominent for vascular malperfusion and obstructive or hemorrhagic injury. Recurrent signals were also observed for villous maturation and hypoxia pattern abnormalities. Inflammatory lesions frequently co-occurred with vascular findings. These results support placental vascular pathology, villous developmental abnormalities, and inflammation as recurring domains linked to stillbirth. The findings underscore the need for more standardized definitions, sampling, and reporting. Standardization is needed to improve comparability and clinical interpretability.

Although the prognostic utility of the prognostic nutritional index (PNI) in breast cancer (BC) treated with neoadjuvant chemotherapy (NACT) has been widely reported, the available evidence remains inconsistent. Therefore, this meta-analysis systematically evaluated the predictive value of pre-NACT PNI for clinical outcomes in patients with BC. PubMed, Embase, Web of Science, and the Cochrane Library were queried comprehensively through November 2025 to identify reports evaluating the association of pre-NACT PNI with overall survival (OS), disease-free survival (DFS), and pathological complete response (pCR) in individuals with BC. Eligible studies were selected according to the PICOS framework. Hazard ratios (HRs) and odds ratios (ORs), along with 95% confidence intervals (CIs), were retrieved. Effect estimates were synthesized using fixed-or random-effects models as indicated, and robustness was tested by subgroup analyses, sensitivity analyses, and evaluation of publication bias. Nine studies comprising 3,718 patients were included. A high pre-treatment PNI was significantly associated with better OS (HR&#xa0;=&#xa0;0.36, 95% CI 0.25-0.52; p < 0.001) and increased odds of achieving pCR (OR&#xa0;=&#xa0;1.90, 95% CI 1.21-2.98; p = 0.005). A favorable association was also observed for DFS (HR&#xa0;=&#xa0;0.52, 95% CI 0.31-0.87; p = 0.01); however, this finding should be interpreted with caution because substantial heterogeneity was present and the estimate showed limited stability in leave-one-out sensitivity analyses. Subgroup analyses indicated that sample size, age, PNI cut-off value, and geographic region might modify the predictive performance of PNI for DFS and pCR. A high pre-NACT PNI was significantly associated with longer OS and a higher likelihood of pCR in patients with BC receiving NACT. A favorable association with DFS was also observed, but this finding should be interpreted cautiously because of substantial heterogeneity and limited robustness. PNI may serve as a simple and practical marker for clinical risk stratification, although further prospective validation is warranted. https://www.crd.york.ac.uk/prospero/, identifier CRD420251268856.

Stroke is the main cause of long-term disability, burdening people and healthcare systems. In stroke patients, modified Constraint-Induced Movement Therapy (mCIMT) may improve lower extremity function. Protocol variability complicates efficacy evaluation. For stroke patients' lower extremity rehabilitation, examine mCIMT safety and effectiveness and identify important protocol components for motor recovery augmentation. An extensive PubMed, Web of Science, Scopus, and PEDro search found clinical studies on mCIMT for lower extremity mobility impairments in adult stroke patients published between January 1, 2000, and November 30, 2023. Constraints, doses, transfer packages, and outcome measures analyzed heterogeneity and study classifications appraised quality. 36 trials with 931 stroke victims were examined. Heterogeneity prevented clear results on the best mCIMT methods. Studies show that mCIMT improves motor function, functional mobility, balance, lower limb strength, weight-bearing, and walking ability with minor side effects. Physical restraint devices may be unsafe and painful. For safety, behavioral limitations are advised. Instead of training length, task repetitions are a better indication of training intensity and can decrease training time. Transfer packages help transfer training gains to daily activities and preserve long-term effects, as shown by better real-world walking habits and functional mobility during follow-up. mCIMT is safe and effective for stroke lower extremity rehabilitation. Behavioral limitations, a specified dose of task repetitions, and patient-specific transfer packages are recommended for mCIMT. Standardizing methods and finding appropriate component combinations to overcome heterogeneity and improve clinical applicability and patient outcomes require further study.

Primary Ovarian Insufficiency (POI) is a highly heterogeneous condition characterized by the cessation of ovarian function before age 40. While genetic factors play a substantial role, the contribution of structural variants remains incompletely mapped. We conducted a systematic review and in silico genomic re-analysis of published copy number variations (CNVs) in individuals with POI. Following PRISMA guidelines, we aggregated 382 CNVs from 25 studies, standardized genomic coordinates, and filtered variants against population databases. Pathogenicity was re-evaluated using ACMG/ClinGen guidelines, yielding 42 pathogenic/likely pathogenic variants and 25 large CNVs (>3.5 Mb). Consistent with previous findings, the X chromosome exhibited the highest CNV burden, emphasizing its central role in structural genomic instability and POI pathogenesis. Beyond canonical POI-associated genes, gene ontology and GTEx expression profiling identified several biologically plausible, highly ovary-expressed candidate genes within disrupted loci-notably ATF3, GAS5, PPP4R1, and PRKAA1. Despite their established roles in cellular stress responses, DNA repair, and meiotic progression, these genes remain absent from most commercial POI diagnostic panels. This comprehensive re-analysis highlights the complex structural genomic landscape of POI and suggests that expanding current clinical testing panels to include these under-recognized genes could improve diagnostic yields for genetically unexplained cases.