Search Results (36,640)

Background: Depression that is resistant to two or more adequate treatment trials—treatment-resistant depression (TRD)—is a prevalent clinical challenge. Although psychotherapies have been recommended by clinical guidelines as an alternative or adjunctive treatment strategy, the effectiveness of psychotherapy in individuals with TRD has not yet been evaluated through meta-analytic methods, primarily due to a limited number of trials. This highlights the necessity of personalized research targeting this specific population. This systematic review and meta-analysis aimed to summarize the evidence on psychotherapy in treating TRD. Methods: A systematic search was conducted following the Guidelines from Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles were included if they quantitatively examined the efficacy of psychotherapy on depression symptoms in individuals diagnosed with depression who had not responded to at least two prior treatments (i.e., pharmacotherapy and/or psychotherapy). Results: A total of 12 studies were included. The quality of evidence was evaluated as being globally moderate. When pooling all psychotherapies, a small-to-moderate, but significant, effect on depressive symptoms was observed compared to the control group (SMD = −0.49, CI = −0.63; −0.34). The observed effect remained unchanged after removing the outlier (SMD = −0.47, CI = −0.62; −0.32). When examining depressive symptoms by type of psychotherapy, Mindfulness-Based Cognitive Therapy (SMD = −0.51, CI = −0.76; −0.25), Cognitive Behavioral Therapy (SMD = −0.53, CI = −0.92; −0.14), and Cognitive Therapy (SMD = −0.51, CI = −1.01; −0.01) showed a moderately significant effect on depressive symptoms compared to the control group. Conclusions: Although this potentially represents the first meta-analysis in this area, the number of studies specifically addressing this complex population remains limited, and the existing literature is still in its early stages. Research focusing on TRD is notably sparse compared to the broader body of work on depression without treatment resistance. Consequently, it was not possible to conduct meta-analyses by type of psychotherapy across all treatment modalities and by type of control group. Due to several study limitations, there is currently limited evidence available about the effectiveness of psychotherapy for TRD, and further trials are needed. Beyond the treatments usually offered for depression, it is possible that TRD requires a personalized medicine approach. Full article

Potentially toxic elements, such as chromium (Cr) and zinc (Zn), play essential roles in humans and animals. However, the harmful effects of excessive exposure to these elements through food remain unknown. In this sense, this study aimed to evaluate the anthropogenic contamination of chromium and zinc in aquatic biota and seafood consumers. Based on the PRISMA protocol, 67 articles were selected for this systematic review. The main results point to a wide distribution of these elements, which have familiar emission sources in the aquatic environment, especially in highly industrialized regions. Significant concentrations of both have been reported in different fish species, which sometimes represent a non-carcinogenic risk to consumer health and a carcinogenic risk related to Cr exposure. New studies should be encouraged to fill gaps, such as the characterization of the toxicity of these essential elements through fish consumption, determination of limit concentrations updated by international regulatory institutions, especially for zinc, studies on the influence of abiotic factors on the toxicity and bioavailability of elements in the environment, and those that evaluate the bioaccessibility of these elements in a simulated digestion system when in high concentrations. Full article

Plant genetics and chemotaxonomic analysis are considered key parameters in understanding evolution, plant diversity and adaptation. Korean Peninsula has a unique biogeographical landscape that supports various aromatic plant species, each with considerable ecological, ethnobotanical, and pharmacological significance. This review aims to provide a comprehensive overview of the chemotaxonomic traits, biological activities, phylogenetic relationships and potential applications of Korean aromatic plants, highlighting their significance in more accurate identification. Chemotaxonomic investigations employing techniques such as gas chromatography mass spectrometry, high-performance liquid chromatography, and nuclear magnetic resonance spectroscopy have enabled the identification of essential oils and specialized metabolites that serve as valuable taxonomic and diagnostic markers. These chemical traits play essential roles in species delimitation and in clarifying interspecific variation. The biological activities of selected taxa are reviewed, with emphasis on antimicrobial, antioxidant, anti-inflammatory, and cytotoxic effects, supported by bioassay-guided fractionation and compound isolation. In parallel, recent advances in phylogenetic reconstruction employing DNA barcoding, internal transcribed spacer regions, and chloroplast genes such as rbcL and matK are examined for their role in clarifying taxonomic uncertainties and inferring evolutionary lineages. Overall, the search period was from year 2001 to 2025 and total of 268 records were included in the study. By integrating phytochemical profiling, pharmacological evidence, and molecular systematics, this review highlights the multifaceted significance of Korean endemic aromatic plants. The conclusion highlights the importance of multidisciplinary approaches including metabolomics and phylogenomics in advancing our understanding of species diversity, evolutionary adaptation, and potential applications. Future research directions are proposed to support conservation efforts. Full article

Background/Objectives: The present study aimed to evaluate the oral health and patient satisfaction of flexible and non-metal clasp dentures (NMCD) compared to removable partial dentures (RPD) using a systematic review. Methods: The PICOS framework of this review was as follows: Do rehabilitations involving flexible dentures or NMCD have a similar success rate to those using RPD? Thus, the PICOS approach involves the following topics: (P) Population/Problem: partial edentulous adult patients; (I) Intervention: patients rehabilitated with flexible dentures or NMCD; (C) Comparison: patients rehabilitated with standard RPD; (O) Outcome: clinical parameters such as oral health, masticatory function, and patient satisfaction; and (S) Study Type: clinical trials and observational studies (cohort, case–control, and cross-sectional). No language restrictions were applied to the studies. The search strategy consisted of the following keywords in different databases: ((flexible) OR (nonmetal) OR (non-metal) OR (thermoplastic)) AND (denture). Only clinical trials and observational studies (cohort, case–control, and cross-sectional studies) from the last 15 years were included, and no language restrictions were applied. Studies that did not describe the denture material were excluded. Results: Of the 2197 potentially relevant records, 14 studies were included in the present review. Two studies reported retrospective results, while twelve reported a prospective evaluation. Considering the thermoplastic materials, five studies evaluated polyester, five polyamides, three polyacetals, and only one study evaluated polyetheretherketone (PEEK). Flexible dentures and NMCD demonstrated similar periodontal status and bone levels on abutment teeth to RPD after up to 12 months. Flexible dentures exhibited a higher degree of redness of the mucosa after 12 months. One study showed a lower maximum bite force for flexible dentures compared to RPD. No study has performed a clinical evaluation of mastication and chewing ability. Conclusions: Despite increased short-term patient satisfaction for flexible dentures and NMCD, there is weak evidence to support a similar clinical performance of flexible dentures and NMCD to RPD. Full article

Systematic reviews are a cornerstone of evidence-based research, providing comprehensive summaries of existing studies to answer specific research questions. This article offers a detailed guide to conducting high-quality systematic reviews in biology, health and social sciences. It outlines key steps, including developing and registering a protocol, designing comprehensive search strategies, and selecting studies through a screening process. The article emphasizes the importance of accurate data extraction and the use of validated tools to assess the risk of bias across different study designs. Both meta-analysis (quantitative approach) and narrative synthesis (qualitative approach) are discussed in detail. The guide also highlights the use of frameworks, such as GRADE, to assess the certainty of evidence and provides recommendations for clear and transparent reporting in line with the PRISMA 2020 guidelines. This paper aims to adapt and translate evidence-based review principles, commonly applied in clinical research, into the context of biological sciences. By highlighting domain-specific methodologies, challenges, and resources, we provide tailored guidance for researchers in ecology, molecular biology, evolutionary biology, and related fields in order to conduct transparent and reproducible evidence syntheses. Full article

Background: Emotional abuse is both prevalent and underrecognized particularly in culturally complex settings like India. Adolescents, being in a critical developmental phase, are especially vulnerable to the long-lasting psychological effects of emotional abuse. This qualitative literature review aims to synthesize findings from primary studies that explore the lived experiences of emotional abuse among Indian adolescents and identify emerging patterns across sociocultural contexts. Method: Electronic databases, including DOAJ, Google Scholar, ProQuest, JSTOR, Pubmed, PsycNet, and SCOPUS, were searched for peer-reviewed articles published in English up to March 2025. Inclusion criteria comprised qualitative or mixed-methods research focusing on emotional abuse among adolescents aged 12–20 in Indian contexts. The Critical Appraisal Skills Programme (CASP) was used for quality assessment. Results: Five major thematic domains were identified across the included studies: (1) Family as a primary site of emotional abuse; (2) Gendered experiences of abuse; (3) Cultural normalization and silence; (4) Psychological and emotional consequences; and (5) Coping and resilience among adolescents. These themes reflect shared experiences of emotional abuse shaped by cultural, familial, and gender-based expectations. Conclusions: This review highlights the urgent need for increased awareness and culturally sensitive interventions addressing emotional abuse in Indian adolescents. The findings suggest that parents, educators, and policymakers must recognize emotionally harmful behaviors and implement prevention-oriented strategies, particularly through non-violent communication and adolescent mental health support frameworks. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

Previous reviews have examined specific facets of Geographic Information Systems (GIS) in transportation planning, such as transit-focused applications and open source geospatial tools. However, this study offers the first systematic, PRISMA-guided longitudinal evaluation of GIS integration in transportation planning, spanning thematic domains, data models, methodologies, and outcomes from 2004 to 2024. This study addresses this gap through a longitudinal analysis of GIS-based transportation research from 2004 to 2024, adhering to PRISMA guidelines. By conducting a mixed-methods analysis of 241 peer-reviewed articles, this study delineates major trends, such as increased emphasis on sustainability, equity, stakeholder involvement, and the incorporation of advanced technologies. Prominent domains include land use–transportation coordination, accessibility, artificial intelligence, real-time monitoring, and policy evaluation. Expanded data sources, such as real-time sensor feeds and 3D models, alongside sophisticated modeling techniques, enable evidence-based, multifaceted decision-making. However, challenges like data limitations, ethical concerns, and the need for specialized expertise persist, particularly in developing regions. Future geospatial innovations should prioritize the responsible adoption of emerging technologies, inclusive capacity building, and environmental justice to foster equitable and efficient transportation systems. This review highlights GIS’s evolution from a supplementary tool to a cornerstone of data-driven, sustainable urban mobility planning, offering insights for researchers, practitioners, and policymakers to advance transportation strategies that align with equity and sustainability goals. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Management for pheasant shooting is a widespread land use in the UK, with potential implications for forest and hedgerow habitats. This study evaluates whether sites managed for pheasant shooting differ ecologically from similar sites not used for shooting. A systematic evidence evaluation of comparative studies was combined with a spatial analysis using remote sensing data (2010–2024). The literature review identified only 32 studies meeting strict criteria for comparability, revealing inconsistent and often weak evidence, with few studies reporting detailed forest management or statistically robust outcomes. While some studies noted increased or decreased biodiversity associated with pheasant shooting, the evidence base was generally of low quality. Remote sensing assessed forest structural and spectral diversity, intactness, and hedgerow density across 1131 pheasant-managed and 1131 matched control sites. Biodiversity data for birds, plants, and butterflies were sourced from GBIF records. Structural diversity and hedgerow density were significantly higher on pheasant-managed sites, while no significant differences were found in forest spectral diversity, intactness, or biodiversity indicators. Pheasant management may shape certain habitat features but has limited demonstrable effects on overall biodiversity. Further field-based, controlled studies are required to understand causal mechanisms and inform ecologically sustainable shooting practices. Full article

Background/Objectives: Mucosal vaccines, delivered intranasally or via inhalation, are being studied for respiratory infectious diseases like COVID-19 and influenza. These vaccines aim to provide non-invasive administration and strong immune responses at infection sites, making them a promising area of research. This systematic review and meta-analysis assessed their immunogenicity, safety, and protective efficacy. Methods: The study design was a systematic review and meta-analysis, searching PubMed and Cochrane databases up to May 30, 2025. Inclusion criteria followed the PICOS framework, focusing on mucosal vaccines for COVID-19, influenza, RSV, pertussis, and tuberculosis. Results: A total of 65 studies with 229,614 participants were included in the final analysis. Mucosal COVID-19 vaccines elicited higher neutralizing antibodies compared to intramuscular vaccines (SMD = 2.48, 95% CI: 2.17–2.78 for wild-type; SMD = 1.95, 95% CI: 1.32–2.58 for Omicron), with varying efficacy by route (inhaled VE = 47%, 95% CI: 22–74%; intranasal vaccine VE = 17%, 95% CI: 0–31%). Mucosal influenza vaccines protected children well (VE = 62%, 95% CI: 30–46%, I² = 17.1%), but seroconversion rates were lower than those of intramuscular vaccines. RSV and pertussis vaccines had high seroconversion rates (73% and 52%, respectively). Tuberculosis vaccines were reviewed systemically, exhibiting robust cellular immunogenicity. Safety was comparable to intramuscular vaccines or placebo, with no publication bias detected. Conclusions: Current evidence suggests mucosal vaccines are immunogenic, safe, and protective, particularly for respiratory diseases. This review provides insights for future research and vaccination strategies, though limitations include varying efficacy by route and study heterogeneity. Full article

Background and Objective: Insulinoma-associated protein 1 (INSM1) is a novel immunohistochemical marker with potential utility in identifying neuroendocrine differentiation in lung cancer. Unlike conventional neuroendocrine (NE) markers, INSM1 can potentially serve as a standalone diagnostic biomarker. This study presents the first meta-analysis assessing the diagnostic accuracy of using INSM1 to distinguish LCNEC and SCLC from other lung cancer subtypes, addressing the variability across individual studies. Methods: A systematic review and meta-analysis were conducted to comprehensively evaluate the diagnostic performance of INSM1 in the pathological classification of lung cancer. The online databases PubMed, Web of Science, and Embase were systematically searched for data collection. Studies reporting the sensitivity and specificity of INSM1 in diagnosing LCNEC and SCLC were included. Pooled estimates were calculated using two models: the NSCLC model, which distinguishes LCNEC from other non-small cell lung cancers (NSCLCs), and the lung cancer model, which differentiates both LCNEC and SCLC from non-neuroendocrine (non-NE) lung cancer. Results: Fourteen studies comprising 3,218 specimens were included in this systematic review and meta-analysis. In the NSCLC model, INSM1 demonstrated a pooled sensitivity of 0.67 (95% CI: 0.61–0.73) and specificity of 0.97 (95% CI: 0.96–0.98), with an area under the curve (AUC) of 0.943. In the lung cancer model, the pooled sensitivity and specificity were 0.86 (95% CI: 0.84–0.88) and 0.97 (95% CI: 0.96–0.98), respectively, with an AUC of 0.974. Conclusions: INSM1 demonstrated excellent diagnostic accuracy and consistently high specificity for pulmonary neuroendocrine carcinomas, supporting its utility as a reliable standalone immunohistochemical marker with the potential to replace conventional NE markers in the pathological diagnosis of LCNEC and SCLC. Full article

Prescriptive Maintenance (PsM) transforms industrial asset management by enabling autonomous decisions through simultaneous failure anticipation and optimal maintenance recommendations. Yet, despite increasing research interest, the conceptual clarity, technological maturity, and practical deployment of PsM remains fragmented. Here, we conduct a comprehensive and application-oriented Systematic Literature Review of studies published between 2013–2024. We identify key enablers—artificial intelligence and machine learning, horizontal and vertical integration, and deep reinforcement learning—that map the functional space of PsM across industrial sectors. The results from our multivariate meta-synthesis uncover three main thematic research clusters, ranging from decision-automation of technical (multi)component-level systems to strategic and organisational-support strategies. Notably, while predictive models are widely adopted, the translation of these capabilities to PsM remains limited. Primary reasons include semantic interoperability, real-time optimisation, and deployment scalability. As a response, a structured research agenda is proposed to emphasise hybrid architectures, context-aware prescription mechanisms, and alignment with Industry 5.0 principles of human-centricity, resilience, and sustainability. The review establishes a critical foundation for future advances in intelligent, explainable, and action-oriented maintenance systems. Full article

Carbon dots (CDs) have attracted much attention as new types of luminescent carbon nanomaterials in recent years because of their tunable fluorescence, good biocompatibility, high stability, and low cost. In this review, the classification of CDs is overviewed based on their differences in structure. Subsequently, the latest research progress of CDs in fluorescence sensing is systematically summarized and various sensing principles are elucidated in detail, including fluorescence resonance energy transfer, aggregation-induced emission, aggregation-caused quenching, electron transfer, and the inner filter effect. Finally, the challenges and future direction of CD fluorescent probes are discussed in detail. The purpose of this review is to stimulate the design of advanced CD fluorescent probes and achieve the accurate and reliable measurement of analytes in complex samples. Full article

Introduction: Asthma is a chronic respiratory disease affecting approximately 5 million children in the US, but little is known about whether asthma alters children’s attention and memory functions. Most studies on this topic focus on psychiatric and QoL outcomes rather than cognitive functions, leaving a gap in the literature. We aimed to conduct a systematic review and meta-analysis to evaluate the attention deficit and memory function outcomes in children with bronchial asthma. Methods: A systematic search was conducted in PubMed, Web of Science, and Cochrane Library from inception to 28 February 2025 for studies evaluating attention deficit and memory function in children with bronchial asthma. Outcomes of interest included attention deficit and memory function. Statistical analysis was performed with R 4.3.1. Heterogeneity was accessed using the I² statistics and Cochrane Q test. The standardized mean difference (SMD) with restricted maximum-likelihood estimator random-effects method was computed for all outcomes. Results: A total of seven studies were included in the final meta-analysis, comprising 104,975 patients, of whom 10,200 (9.7%) had bronchial asthma (mean age ± 8.98 years, mean 45% females). In the pooled analysis, children with asthma had a worsened attention deficit compared to the healthy group (SMD 0.29; 95% CI [0.07; 0.51]; p = 0.01; I² = 92%). However, no statistically significant difference was found in memory function between groups (SMD −0.24; 95% CI [−1.81; 1.33]; p = 0.77; I² = 96%). Conclusions: Children with asthma showed significantly higher attention deficit scores compared to healthy children. No statistically significant differences were observed in memory function between the groups. These findings may have implications for early cognitive screening in pediatric asthma management. Full article