Search Results (1,614)

Background/Objectives: While artificial intelligence (AI) is rapidly transforming education, its specific effectiveness for students with learning disabilities (LD) requires rigorous evaluation. This systematic review aims to assess the efficacy of AI-based educational interventions for students with LD, with a specific focus on the methodological quality and risk of bias of the available evidence. Methods: A systematic search was conducted across seven major databases (Google Scholar, ScienceDirect, APA PsycInfo, ERIC, Scopus, PubMed) for experimental studies published between 2022 and 2025. This review followed PRISMA guidelines, using the PICOS framework for inclusion criteria. A formal risk of bias assessment was performed using the ROBINS-I and JBI critical appraisal tools. Results: Eleven studies (representing 10 independent experiments), encompassing 3033 participants, met the inclusion criteria. The most studied disabilities were dyslexia (six studies) and other specific learning disorders (three studies). Personalized/adaptive learning systems and game-based learning were the most common AI interventions. All 11 studies reported positive outcomes. However, the risk of bias assessment revealed significant methodological limitations: no studies were rated as having a low risk of bias, with most presenting a moderate (70%) to high/serious (30%) risk. Despite these limitations, quantitative results from the stronger studies showed large effect sizes, such as in arithmetic fluency (d = 1.63) and reading comprehension (d = −1.66). Conclusions: AI-based interventions demonstrate significant potential for supporting students with learning disabilities, with unanimously positive reported outcomes. However, this conclusion must be tempered by the considerable risk of bias and methodological weaknesses prevalent in the current literature. The limited and potentially biased evidence base warrants cautious interpretation. Future research must prioritize high-quality randomized controlled trials (RCTs) and longitudinal assessments to establish a definitive evidence base and investigate long-term effects, including the risk of cognitive offloading. Full article

In recent years, cross-domain few-shot learning (CDFSL) has demonstrated remarkable performance in hyperspectral image classification (HSIC), partially alleviating the distribution shift problem. However, most domain adaptation methods rely on similarity metrics to establish cross-domain class matching, making it difficult to simultaneously account for intra-class sample size variations and inherent inter-class differences. To address this problem, existing studies have introduced a class weighting mechanism within the prototype network framework, determining class weights by calculating inter-sample similarity through distance metrics. However, this method suffers from a dual limitation: susceptibility to noise interference and insufficient capacity to capture global class variations, which may lead to distorted weight allocation and consequently result in alignment bias. To solve these issues, we propose a novel class-discrepancy dynamic weighting-based cross-domain FSL (CDDW-CFSL) framework. It integrates three key components: (1) the class-weighted domain adaptation (CWDA) method dynamically measures cross-domain distribution shifts using global class mean discrepancies. It employs discrepancy-sensitive weighting to strengthen the alignment of critical categories, enabling accurate domain adaptation while maintaining feature topology; (2) the class mean refinement (CMR) method incorporates class covariance distance to compute distribution discrepancies between support set samples and class prototypes, enabling the precise capture of cross-domain feature internal structures; (3) a novel multi-dimensional feature extractor that captures both local spatial details and continuous spectral characteristics simultaneously, facilitating deep cross-dimensional feature fusion. The results in three publicly available HSIC datasets show the effectiveness of the CDDW-CFSL. Full article

Background and Objectives: The relationship between ABO or Rh blood groups and susceptibility to Chikungunya virus (CHIKV) infection remains unclear. This systematic review and meta-analysis aimed to synthesize available evidence on this association. Materials and Methods: Studies reporting ABO and/or Rh blood groups and CHIKV infection were searched through PubMed, Scopus, EMBASE, MEDLINE, Ovid, ProQuest, and Google Scholar up to 8 July 2025. A random-effects meta-analysis was conducted to calculate pooled odds ratios (Ors) with 95% CIs. Heterogeneity was assessed using I² statistics. Subgroup analyses were performed based on study design and study quality. Sensitivity analysis was conducted using a leave-one-out method. Publication bias was evaluated via funnel plots and Egger’s test. Results: Seven studies, including 24,828 participants, were included. No significant associations were observed between blood groups A, B, AB, or Rh(D) and CHIKV infection. However, blood group O was significantly associated with an increased risk of CHIKV infection (OR: 1.52, 95% CI: 1.01–2.29, p = 0.043, I² = 95.38%) compared to non-O blood groups. Subgroup analyses showed stable results. Nevertheless, the sensitivity analysis indicated that certain studies had a greater influence on the overall results. In addition, significant publication bias was also detected. Conclusions: Current evidence indicates that blood group O is significantly associated with an increased susceptibility to CHIKV infection. In contrast, no consistent associations were observed for other ABO or Rh blood groups. Due to substantial heterogeneity and methodological limitations, these findings should be interpreted with caution. Further well-designed, large-scale studies with standardized diagnostics are needed to clarify these associations and underlying mechanisms. Full article

Accurate estimation of erupted lava volumes is essential for understanding volcanic processes, interpreting eruptive cycles, and assessing volcanic hazards. Traditional methods based on Mid-Infrared (MIR) satellite imagery require clear-sky conditions during eruptions and are prone to sensor saturation, limiting data availability. Here, we present an alternative approach based on the post-eruptive Thermal InfraRed (TIR) signal, using the recently proposed VRP_TIR method to quantify radiative energy loss during lava flow cooling. We identify thermally anomalous pixels in VIIRS I5 scenes (11.45 µm, 375 m resolution) using the TIRVolcH algorithm, this allowing the detection of subtle thermal anomalies throughout the cooling phase, and retrieve lava flow area by fitting theoretical cooling curves to observed VRP_TIR time series. Collating a dataset of 191 mafic eruptions that occurred between 2010 and 2025 at (i) Etna and Stromboli (Italy); (ii) Piton de la Fournaise (France); (iii) Bárðarbunga, Fagradalsfjall, and Sundhnúkagígar (Iceland); (iv) Kīlauea and Mauna Loa (United States); (v) Wolf, Fernandina, and Sierra Negra (Ecuador); (vi) Nyamuragira and Nyiragongo (DRC); (vii) Fogo (Cape Verde); and (viii) La Palma (Spain), we derive a new power-law equation describing mafic lava flow thickening as a function of time across five orders of magnitude (from 0.02 Mm³ to 5.5 km³). Finally, from knowledge of areas and episode durations, we estimate erupted volumes. The method is validated against 68 eruptions with known volumes, yielding high agreement (R² = 0.947; ρ = 0.96; MAPE = 28.60%), a negligible bias (MPE = −0.85%), and uncertainties within ±50%. Application to the February-March 2025 Etna eruption further corroborates the robustness of our workflow, from which we estimate a bulk erupted volume of 4.23 ± 2.12 × 10⁶ m³, in close agreement with preliminary estimates from independent data. Beyond volume estimation, we show that VRP_TIR cooling curves follow a consistent decay pattern that aligns with established theoretical thermal models, indicating a stable conductive regime during the cooling stage. This scale-invariant pattern suggests that crustal insulation and heat transfer across a solidifying boundary govern the thermal evolution of cooling basaltic flows. Full article

Background: MRI-based radiomics has emerged as a promising approach to enhance the non-invasive, presurgical assessment of lymph node staging in rectal cancer (RC). However, its clinical implementation remains limited due to methodological variability in published studies. We conducted a systematic review and meta-analysis to synthesize the diagnostic performance of MRI-based radiomics models for predicting pathological nodal status (pN) in RC. Methods: A systematic literature search was conducted in PubMed, Web of Science, and Scopus for studies published until 31 December 2024. Eligible studies applied MRI-based radiomics for pN prediction in RC patients. We excluded other imaging sources and models combining radiomics and other data (e.g., clinical). All models with available outcome metrics were included in data analysis. Data extraction and quality assessment (QUADAS-2) were performed independently by two reviewers. Random-effects meta-analyses including hierarchical summary receiver operating characteristic (HSROC) and restricted maximum likelihood estimator (REML) analyses were conducted to pool sensitivity, specificity, area under the curve (AUC), and diagnostic odds ratios (DORs). Sensitivity analyses and publication bias evaluation were also performed. Results: Sixteen studies (n = 3157 patients) were included. The HSROC showed pooled sensitivity, specificity, and AUC values of 0.68 (95% CI, 0.63–0.72), 0.73 (95% CI, 0.68–0.78), and 0.70 (95% CI, 0.65–0.75), respectively. The mean pooled AUC and DOR obtained by REML were 0.78 (95% CI, 0.75–0.80) and 6.03 (95% CI, 4.65–7.82). Funnel plot asymmetry and Egger’s test (p = 0.025) indicated potential publication bias. Conclusions: Overall, MRI-based radiomics models demonstrated moderate accuracy in predicting pN status in RC, with some studies reporting outstanding results. However, heterogeneity in relevant methodological approaches such as the source of MRI sequences or machine learning methods applied along with possible publication bias call for further standardization and preclude their translation to clinical practice. Full article

Objective: This cross-sectional content analysis aimed to investigate how oil pulling is portrayed on YouTube Shorts, focusing on the types of speakers, claims made, and alignment with scientific evidence. The study further explored how the content may influence viewer perception, health behaviors, and the potential spread of misinformation. Methods: On 28 January 2025, a systematic search of YouTube Shorts was performed using the term “oil pulling” in incognito mode to reduce algorithmic bias. English language videos with at least 1000 views were included through purposive sampling. A total of 47 Shorts met the inclusion criteria. Data were extracted using a structured coding framework that recorded speaker type (e.g., dentist, hygienist, influencer), engagement metrics, stated benefits, oil type and regimen, the use of disclaimers or citations, and stance toward oil pulling rated on a 5-point Likert scale. Speaker background and nationality were determined through publicly available channel descriptions or linked websites, with user identities anonymized and ethical approval deemed unnecessary due to the use of publicly available content. In total, 47 videos met the inclusion criteria. Results: Of the 47 YouTube Shorts that met the inclusion criteria, most were posted by influencers rather than dental professionals. These videos predominantly encouraged oil pulling, often recommending coconut oil for 10–15 min daily and citing benefits such as reduced halitosis and improved gum health. However, a smaller subset advanced more extreme claims, including reversing cavities and remineralizing enamel. Notably, US-licensed dentists and dental hygienists tended to discourage or express skepticism toward oil pulling, assigning lower Likert scores (1 or 2) to influencers and alternative health practitioners (often 4 or 5). Conclusions: YouTube Shorts largely promote oil pulling through anecdotal and testimonial-driven content, often diverging from evidence-based dental recommendations. The findings reveal a disconnect between professional dental guidance and popular social media narratives. While some benefits like halitosis reduction may have limited support, exaggerated or misleading claims may result in improper oral hygiene practices. Greater engagement from dental professionals and improved health communication strategies are needed to counteract misinformation and reinforce oil pulling’s role, if any, as an adjunct—not a replacement—for standard oral care. Future studies should explore viewer interpretation, behavioral influence, and cross-platform content patterns to better understand the impact of short-form health videos. Full article

Poor sleep quality and insomnia are increasingly linked to chronic inflammation and obesity-related metabolic dysfunction. Aerobic exercise is a promising non-pharmacological approach for enhancing sleep quality and reducing systemic inflammation; Therefore, we aim to systematically evaluate and quantify the effects of aerobic exercise interventions on subjective sleep quality, insomnia severity, and circulating markers (IL-6 and TNF-α) in adults. A systematic search was conducted in institutional databases (UNAM, UACJ) and PubMed to identify randomized controlled trials (RCTs) examining the effects of exercise on sleep and inflammation. Risk of bias was assessed using the Cochrane RoB2 tool. Meta-analyses were performed using RevMan 5.4 with random-effects models to estimate pooled mean differences (MD) and standardized mean differences (SMD), with 95% confidence intervals. Anaerobic protocols were excluded from the meta-analysis due to the insufficient availability of data. : Eleven RCTs met the inclusion criteria. Aerobic exercise showed a significant pooled effect on sleep outcomes (MD = −2.51; 95% CI: −4.80 to −0.23; p = 0.03). However, subgroup analyses for Pittsburgh Sleep Quality Index (PSQI) (MD = −2.27; p = 0.15) and Insomnia Severity Index (ISI) (MD = −2.98; p = 0.16) were not statistically significant. Two studies on IL-6 reported a non-significant reduction (SMD = −0.17; p = 0.66), with moderate heterogeneity. TNF-α results were also non-significant (SMD = 0.60; p = 0.29) with substantial variability. Our results showed that aerobic exercise may modestly improve sleep outcomes; however, current evidence does not support its effectiveness in reducing levels of IL-6 or TNF-α. Further well-controlled trials are needed to clarify its immunometabolic effects, particularly in populations with obesity or metabolic disorders. Full article

Chlorophyll-a (Chla) and suspended particulate matter (SPM) are key indicators of water quality, playing critical roles in understanding marine biogeochemical processes and ecosystem health. Although satellite data from the Chinese Ocean Color and Temperature Scanner (COCTS) onboard the Haiyang-1C/D satellites is freely available, there has been limited validation of its standard Chla and SPM products. This study is a first step to address this gap by evaluating COCTS-derived Chla and SPM products against in situ measurements in French coastal waters. The matchup analysis showed robust performance for the Chla product, with a median symmetric accuracy (MSA) of 50.46% over a dynamic range of 0.13–4.31 mg·m⁻³ (n = 24, Bias = 41.11%, Slope = 0.93). In contrast, the SPM product showed significant limitations, particularly in turbid waters, despite a reasonable performance in the matchup exercise, with an MSA of 45.86% within a range of 0.18–10.52 g·m⁻³ (n = 23, Bias = −14.59%, Slope = 2.29). A comparison with another SPM model and Moderate Resolution Imaging Spectroradiometer (MODIS) products showed that the COCTS standard algorithm tends to overestimate SPM and suggests that the issue does not originate from the input radiometric data. This study provides the first regional assessment of COCTS Chla and SPM products in European coastal waters. The findings highlight the need for algorithm refinement to improve the reliability of COCTS SPM products, while the Chla product demonstrates suitability for water quality monitoring in low to moderate Chla concentrations. Future studies should focus on the validation of COCTS ocean color products in more diverse waters. Full article

Drug-induced nephrotoxicity is a common and serious problem in clinical practice. We conducted a systematic review of studies reporting nephrotoxicity events associated with antibiotics approved since 2018. The agents assessed included aztreonam/avibactam, cefepime/enmetazobactam, cefiderocol, ceftobiprole, contezolid, gepotidacin, imipenem/cilastatin/relebactam, lascufloxacin, lefamulin, levonadifloxacin, plazomicin, and sulbactam/durlobactam. Literature searches were conducted in PubMed, Scopus, Web of Science, and major pharmacovigilance databases (Vigibase, FAERS, EudraVigilance, EMA, FDA, NMPA, PMDA, and CDSCO) in May 2025, along with reference citation tracking. Studies were included if they reported safety or adverse event data. The risk of bias was assessed using validated tools in accordance with the study design. Out of 2105 potentially relevant records, 74 studies met inclusion criteria, comprising 52 clinical trials, 17 observational studies, 1 registry-based study, 3 case series, and 1 case report. Nephrotoxicity was rarely reported for any of the newly approved antibiotics. No renal adverse events were found in the available studies for aztreonam/avibactam, levonadifloxacin, and contezolid. Most studies were of moderate to high quality; two were classified as low quality. However, nephrotoxicity was inconsistently assessed, with variable definitions and methodologies used. Although current data suggest a low frequency of nephrotoxicity, limitations in study design and reporting preclude firm conclusions. There is a need for post-marketing studies to better characterize renal safety. Clinicians should remain vigilant and continue to monitor for and report renal-related adverse events. Full article

In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of $3\times {10}^{16}$ 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach. Full article

Background: Endometrial cancer (EC) is the most common gynecological malignancy, increasingly affecting premenopausal women. While hysterectomy is the standard treatment, it eliminates reproductive potential, highlighting the need for effective fertility-sparing alternatives. Current ESHRE/ESGO/ESGE guidelines recommend progestin-based therapies, often with hysteroscopic resection. However, these are based on limited pharmacological options and moderate to low-quality evidence. Novel and combination therapies have shown promise but remain absent from current clinical guidelines. This review aims to evaluate the efficacy and safety of fertility-preserving treatments for early-stage EC, emphasizing the need to update current strategies based on emerging data. Methods: A systematic review and meta-analysis will follow PRISMA guidelines and the Cochrane Handbook. Eligible studies, including randomized and non-randomized designs, will assess fertility-preserving treatments for early-stage EC. Data will be extracted on complete response, recurrence, and long-term fertility outcomes. The GRADE system will assess evidence certainty. Risk of bias will be evaluated using RoB 2 for RCTs and ROBINS-I for non-randomized studies. Meta-analysis will be performed if sufficient data are available. Conclusions: This review will provide a comprehensive analysis of fertility-sparing treatments for early-stage EC, support personalized strategies, identify evidence gaps, and guide future research. Trial registration—Prospero: CRD420251032161. Full article

Background/Objectives: The main purpose of the present scoping review was to map and explore the efficacy of computer-controlled intraosseous anesthesia (CCIA) in comparison with conventional dental anesthesia in pediatric dental patients. Secondarily, this study aimed to compare the acceptance and preference factors between CCIA and conventional dental anesthesia in children. Given the limited and heterogeneous nature of the available literature, this review aimed to identify gaps and scope the extent of research conducted in this area, providing a foundation for future, more targeted studies. Methods: The search was conducted in 19 electronic databases, and the appropriate studies were identified according to PRISMA-ScR guidelines. Only split-mouth randomized controlled clinical trials that reported on the clinical outcomes of CCIA in children were included. Two reviewers worked independently on the screening and selection of the studies. The same two reviewers carried out the data extraction and the risk of bias assessment, using the Cochrane risk of bias tool. Due to the exploratory nature, this review focused on mapping the characteristics, outcomes, and research trends rather than synthesizing effect sizes. Results: Out of 841 papers, 2 randomized clinical trials were ultimately included in the scoping review. The outcomes were categorized as primary (including results that answered the focus question) and secondary (relating to additional quality characteristics). Regarding the primary outcomes, in both studies, intraosseous anesthesia was efficacious in achieving the adequate level of anesthesia. One of the secondary outcomes was the acceptance and preference of CCIA in comparison with conventional dental anesthesia in children. The limited number and the high risk of bias in existing studies highlight the necessity for more comprehensive and high-quality research. Conclusions: The selected studies support the assertion that CCIA is a promising technique since it results in less pain perception and is preferred by patients compared to conventional local anesthesia. However, the existing literature is limited and at high risk of bias. Thus, further targeted investigations are needed to evaluate and yield more definitive results regarding the superiority of CCIA. Full article

Background and objectives: The interest in studying the relationship between bruxism and sleep apnea has increased over the past decade, given its prevalence and its implications for both oral and overall health. Bruxism occurs in a significant portion of the population, with an overall incidence ranging between 8 and 31%. Obstructive sleep apnea affects 4–6% of middle-aged men and 2–4% of middle-aged women, and it is associated with diminished quality of life, hypertension, increased cardiovascular risks, traffic accidents, and a higher mortality rate. Although a possible association has been suggested, the causal relationship remains unclear. This review aimed to systematically evaluate the available evidence on the association between SB and OSA, focusing on potential shared risk factors and underlying mechanisms. Methods: An electronic literature search was conducted in PubMed, Scopus, Web of Science, and the Cochrane Library for studies published between 2020 and 2025. Inclusion criteria encompassed observational studies and clinical trials involving adults with SB and/or OSA. Risk of bias was assessed using ROBINS-I, and the certainty of evidence was evaluated using GRADE. The review protocol was not registered. Results: A total of 11 studies met the inclusion criteria. The prevalence of SB was consistently higher in individuals with OSA compared to the general population. Several studies suggest a potential link through autonomic arousals and neurotransmitter dysregulation. However, inconsistencies in diagnostic criteria and moderate methodological quality limited the strength of the findings. Conclusions: There is a notable prevalence of bruxism in patients with OSA, suggesting possible shared pathophysiological mechanisms; however, it is necessary to standardize diagnostic criteria and conduct larger, more standardized studies to clarify the relationship. No funding was received, and the authors declare no conflicts of interest. Full article

Background: The gold standard for diagnosing primary central nervous system lymphoma (PCNSL) is brain biopsy, an invasive procedure with significant risks. The role of cerebrospinal fluid (CSF) examination, limited to cytology and flow cytometry in current practice, is acknowledged as a less invasive diagnostic method. We aimed to summarize available data concerning the efficacy and actual use of current standard CSF diagnostics in the diagnosis of PCNSL. Methods: A systematic review and meta-analysis of 144 studies (n = 9493 patients) was conducted, assessing detection rates of cytology and flow cytometry and the proportion of diagnoses based on CSF analysis. The QUADAS-2 tool was used to evaluate study quality and bias. Results: Meta-analysis showed an 18% pooled detection rate for positive CSF results, with 17% for cytology and 20% for flow cytometry. Only 8% of diagnoses were made using CSF analysis. Most studies had a high risk of bias. Conclusions: Despite its established role in guidelines, CSF analysis remains underutilized for diagnosing PCNSL, with room to improve its clinical impact. Novel techniques, such as chemokines and circulating tumor DNA (cfDNA) analysis, hold promise to unlock the untapped potential of CSF diagnostics, offering significant advancements in non-invasive PCNSL diagnosis. Full article

This research aims to understand the evolving role of academic libraries, focusing on student perceptions of current services and their vision for the future. Data was collected using a survey at a midwestern research university in the United States. The survey contained both quantitative and qualitative questions. The objective of the survey was to understand the current utilization of library services and students’ future visions for academic libraries. Qualitative and quantitative analysis techniques were utilized as part of the study. Thematic analysis was employed as part of the qualitative analysis, while descriptive and inferential analysis techniques were utilized in the quantitative analysis. The findings reveal that many students use libraries for traditional functions such as studying and accessing resources. There is also an inclination toward digitalization due to convenience, accessibility, and environmental sustainability; however, print materials remain relevant as well. Another finding was a lack of awareness among some students regarding available library services, indicating a need for better marketing and communication strategies. Students envision future libraries as technology-driven spaces integrating artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and innovative collaborative environments. Ethical considerations surrounding AI, including privacy, bias, and transparency, are crucial factors that must be addressed. Some of the actionable recommendations include integrating ethical AI, implementing digital literacy initiatives, conducting ongoing usability and user experience (UX) research within the library, and fostering cross-functional collaboration to enhance library services and student learning. Full article