Search Results (5,308)

Background: Peri-implantitis, a condition characterized by inflammation and progressive bone loss around dental implants, presents a significant challenge in contemporary dentistry. Conventional non-surgical treatments often fail to fully eliminate bacterial biofilms, particularly on complex implant surfaces. Laser therapies have emerged as potential adjuncts due to their antimicrobial and bio-modulatory properties. However, their microbiological effectiveness and suitability for individualized patient treatment planning remain unclear. Objective: Τhis study aims to systematically assess and synthesize the microbiological effects of various laser-assisted non-surgical treatments for peri-implantitis compared to conventional mechanical debridement. Methods: This systematic review and meta-analysis followed PRISMA guidelines and was registered in PROSPERO (CRD420251035354). Randomized controlled trials (RCTs) evaluating microbiological changes following laser-assisted non-surgical treatment of peri-implantitis, with a minimum follow-up of one month, were identified through searches in multiple databases and registries up to February 2025. The ncluded studies used lasers such as diode, Er: YAG, and photodynamic therapy (PDT) either alone or as adjuncts to mechanical debridement. Outcomes of interest included bacterial counts. Risk of bias was assessed using the RoB2 tool, and certainty of evidence was evaluated via GRADE. Quantitative synthesis used random-effects meta-analysis, with standardized mean differences (SMDs) calculated. Results: Eight RCTs involving 266 patients and 335 implants were included in the systematic review. Quantitative synthesis of three pathogens (counts of Fusobacterium nucleatum, P. gingivalis, T. denticola) across three studies displayed no statistically significant differences between laser and control groups at 3 and 6 months (p > 0.05 for all comparisons). When examining individual study findings, PDT, particularly in patients with diabetes or acute abscess, showed short-term reductions in red complex bacteria (e.g., Porphyromonas gingivalis and Treponema denticola). In contrast, diode and Er: YAG lasers demonstrated inconsistent or transient effects. The quality of evidence was rated as very low according to GRADE. Conclusions: Laser-assisted therapies, especially PDT, may provide targeted microbiological benefit in selected patient groups, supporting their adjunctive use within personalized treatment planning rather than as replacements for mechanical debridement, which remains the gold standard. Further high-quality RCTs incorporating well-defined patient risk profiles, such as systemic conditions and behavioral factors, and precision treatment algorithms are needed. Full article

Predicting energy consumption in battery electric vehicles (BEVs) is a complex task due to the large number of influencing factors and their interdependencies. Nevertheless, reliable energy consumption estimation is essential to reduce range anxiety, facilitate route planning, manage charging infrastructure, and support more effective travel decisions that lower operational risks in transportation, thereby fostering wider BEV adoption. In this context, the present study examines the existing literature on methodologies for predicting BEV energy consumption through a systematic literature review (SLR) following the Denyer and Tranfield protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The analysis covers modelling approaches, computational tools, model accuracy metrics, variable topology, sampling frequency and analysis period, modelling scale, and data sources. In addition, this review incorporates a structured assessment of the methodological quality of the included studies and a systematic evaluation of risk of bias, enabling a critical appraisal of the reliability and generalisability of reported findings. A comprehensive classification of modelling methodologies and variables is proposed, providing an integrative reference framework for future research. Overall, this study addresses existing research gaps, identifies current methodological limitations, and outlines directions for future work on BEV energy consumption prediction. Full article

Background: Recalcitrant plantar fasciitis (RPF) is a common cause of chronic heel pain, resistant to conservative treatment in up to 10% of cases. A biomechanical association exists between isolated gastrocnemius contracture and increased tension on the plantar fascia. In this context, gastrocnemius recession (GR) has emerged as a surgical intervention aimed at reducing fascial strain and improving functional outcomes. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines and registered with PROSPERO (CRD420251028862). Randomized controlled trials evaluating the efficacy of GR in patients with RPF were included. Searches were performed in PubMed, Cochrane Library, and Web of Science. Risk of bias was assessed using the RoB 2 tool, and the certainty of evidence was evaluated using the GRADE approach. Primary outcomes included foot function (AOFAS), pain (VAS), and ankle dorsiflexion range (FDTPA). Results: Five studies encompassing 150 patients were included. Meta-analysis revealed statistically significant improvements in foot function (AOFAS, standardized mean difference [SMD] = 0.81; 95% CI: 0.26–1.36), pain reduction (VAS, SMD = −1.17; 95% CI: −1.99 to −0.36), and ankle dorsiflexion (FDTPA, SMD = 0.74; 95% CI: 0.26–1.22). GR demonstrated advantages over plantar fasciotomy in terms of postoperative recovery and preservation of fascial structure. No major complications were reported, and some studies documented sustained benefits up to six years postoperatively. Moderate to high heterogeneity was observed, largely due to variations in surgical technique and follow-up durations. Conclusions: Gastrocnemius recession is a safe and effective surgical option for treating RPF, particularly in patients with isolated gastrocnemius contracture and failure of conservative therapies. It significantly improves foot function, reduces pain, and enhances ankle mobility, with durable long-term outcomes. Trial Registration: This systematic review is registered with PROSPERO (CRD420251028862). Full article

Background: Postoperative bone healing can be impaired by systemic factors and surgical trauma, leading to delayed recovery. Photobiomodulation therapy (PBMT) has been proposed as a non-invasive method to enhance osteogenesis, but variability in protocols and outcomes limits its clinical use. Aim: To systematically review and synthesize evidence from randomized controlled trials (RCTs) evaluating PBMT’s effectiveness in promoting postoperative osteogenesis. Methods: A systematic search of PubMed, Embase, Scopus, and Cochrane Library was conducted following the PRISMA 2020 guidelines. Only RCTs comparing PBMT with sham treatment or standard care were included. Data on laser parameters, surgical indications, and outcomes such as bone regeneration, healing time, and implant stability were extracted. The risk of bias of the included randomized studies was evaluated using the Cochrane Risk of Bias 2 (RoB version 2) tool. Results: Twelve RCTs were included. PBMT consistently improved early soft tissue healing and reduced postoperative inflammation and edema. Some studies showed accelerated bone maturation, especially in grafted sockets and distraction osteogenesis, while others reported no significant long-term effects on implant stability or chronic lesion healing. Heterogeneity in laser parameters limited comparability. Conclusions: PBMT is a safe adjunct that reliably enhances early postoperative healing and may promote bone remodeling in selected cases. Standardized protocols and larger, high-quality RCTs are needed to confirm long-term benefits and optimize treatment parameters. Full article

Background/Objectives: Aortic-arch calcification (AAC) is a robust predictor of cardiovascular events often overlooked on routine chest radiographs (CXR). This systematic review aimed to evaluate the diagnostic accuracy of artificial intelligence (AI) models for detecting AAC on CXR and assess their potential for clinical implementation. Methods: The review followed PRISMA 2020 guidelines (PROSPERO: CRD420251208627). A search of Embase, PubMed, Scopus, and Web of Science was conducted (Jan 2020–Oct 2025) for studies evaluating AI models detecting AAC in adults. Bias was assessed using QUADAS-2. Due to methodological heterogeneity, a narrative synthesis was performed instead of a meta-analysis. Results: Out of 115 records, three retrospective studies (2022–2024) utilizing CNNs across ~2.7 million images were included. Models demonstrated high diagnostic discrimination (AUROC 0.81–0.99), though performance estimates were often attenuated in external cohorts. Pronounced sensitivity–specificity trade-offs occurred: one model achieved 95.9% recall, while another exhibited near-perfect specificity (0.99) despite markedly low sensitivity (0.22). Although the risk of bias was predominantly low, the overall GRADE certainty remained low due to methodological heterogeneity and the absence of cross-sectional imaging reference standards. Conclusions: Deep learning-based models reliably detect AAC on routine CXR, offering a scalable tool for opportunistic cardiovascular risk stratification. However, significant heterogeneity in model architectures and validation strategies currently limits broad comparability. Future research requires standardized annotation protocols and external validation to ensure clinical generalizability. Full article

Objectives: This systematic review aims to evaluate the effectiveness of autologous Plasma Rich in Growth Factors (PRGF) in enhancing post-extraction socket healing by synthesizing evidence from randomized controlled trials and assessing outcomes related to bone regeneration, soft-tissue healing, and postoperative discomfort. Methods: A comprehensive search was conducted in MEDLINE, Embase, Cochrane Library, Scopus, Web of Science, and CINAHL, using a fully reproducible Boolean search strategy. Non-English studies were screened but excluded only when a reliable translation was not feasible. Only randomized controlled trials (RCTs) involving PRGF application in human extraction sockets were included. Risk of bias was assessed using the Cochrane RoB2 tool. A meta-analysis could not be performed due to substantial heterogeneity in PRGF preparation protocols, follow-up duration, and outcome measurements. Results: Seven RCTs met the eligibility criteria. Four studies demonstrated significantly improved healing outcomes in the PRGF group compared with controls, whereas two studies reported comparable results. Pain reduction was consistently observed in PRGF-treated sockets in studies that reported standardized postoperative analgesic protocols. Mineralized tissue formation favored PRGF in high-quality trials. Considerable heterogeneity was identified in PRGF centrifugation parameters, outcome tools, and evaluation timelines. Conclusions: Evidence from current RCTs supports PRGF as an effective and well-established adjunct for enhancing early post-extraction healing. The novelty of this review lies in its updated methodological rigor, corrected risk-of-bias analysis, standardized data handling, and clarification of long-standing gaps in reporting PRGF preparation variability. Future trials with standardized PRGF protocols and long-term follow-up are needed to improve comparability and strengthen clinical recommendations. Full article

Background/Objectives: Premalignant laryngeal lesions carry a variable risk of malignant transformation to squamous cell carcinoma. Identifying reliable biomarkers that predict malignant transformation could improve patient management and surveillance strategies. The objective of this work is to perform a systematic review of the literature on biomarkers that predict malignant transformation of premalignant laryngeal lesions. Methods: We conducted a systematic review following PRISMA 2020 guidelines. The PubMed, Scopus and Embase databases, and Google Scholar were searched for studies published between January 2011 and November 2025. Studies investigating biomarkers that predict malignant transformation of histopathologically confirmed premalignant laryngeal lesions were included. Risk of bias was assessed using the ROBINS-I tool. Results: From 166 initially identified records, 11 studies met the inclusion criteria, including 730 patients. These studies investigated diverse biomarker categories such as protein markers (cortactin, FAK, NANOG, SOX2, CSPG4), immune markers (tumor-infiltrating lymphocytes, immune gene signatures), microRNAs (miR-183-5p, miR-155-5p, miR-106b-3p), and genetic markers (chromosomal instability, PIK3CA amplification and mutations, FGFR3 mutations). Five studies provided adequate follow-up data on transformation outcomes. Most studies showed a moderate to serious risk of bias primarily due to limited confounder control and incomplete reporting. Conclusions: While several promising biomarker candidates have been identified, the evidence base remains limited due to small sample sizes, heterogeneous methodologies, and inadequate follow-up data. Cortactin/FAK protein expression and immune signatures are the most promising but require validation in larger, well-designed prospective cohorts. Full article

Background/Objectives: Multidisciplinary outcome studies are carried out to evaluate long-term treatment in patients with cleft lip and palate. Speech function as one of the key outcomes of the treatment is examined by means of an auditory-perceptual analysis. For scientific and global studies it is essential to reduce the risk of bias as much as possible. The aim of the present study was the examination of auditory-perceptive analyses on the basis of an outcome study. Reliability was evaluated. Methods: Twenty patients were examined to evaluate their speech function. The speech sample was obtained via the online tool Zoom™. The speech sample consisted of single words (picture supported), a version of the German “Great Ormond Street Speech Assessment” (GOS.SP.ASS) sentences and spontaneous speech. The analysis was carried out by three experienced examiners, all using the German version of the Universal Reporting Parameters at two different times. The intrarater and interrater reliability were calculated. Results: Twenty participants with unilateral cleft and palate and a minimum age of 18 years (ø 20.1) were enrolled in the analysis of the speech function. None of the participants had undergone a secondary operation due to velopharyngeal incompetence. The examination happened at a point in time before an osteotomy might be needed. The multidisciplinary treatment of the 20 participants regarding their speech function was successful. There were only marginal abnormalities. The listeners showed a very good intrarater and moderate interrater reliability (ICC/Fleiss’ kappa). An overall percentual agreement of 88.3% was achieved. Conclusions: These positive results cannot be compared with outcome studies on a national or international level, since the construction of the speech sample as well as the structure and the implementation of the auditing process reveal considerable deficiencies in methodological rigor. The small number of examiners and patients as well as the patients’ minor residual impairments influence the significance of the statistical calculation by kappa and ICC. The auditory-perceptual analysis should be validated for German-speaking countries. Full article

Large language models (LLMs) and other foundation models are rapidly being woven into enterprise analytics workflows, where they assist with data exploration, forecasting, decision support, and automation. These systems can feel like powerful new teammates: creative, scalable, and tireless. Yet they also introduce distinctive risks related to opacity, brittleness, bias, and misalignment with organizational goals. Existing work on AI ethics, alignment, and governance provides valuable principles and technical safeguards, but enterprises still lack practical frameworks that connect these ideas to the specific metrics, controls, and workflows by which analytics teams design, deploy, and monitor LLM-powered systems. This paper proposes a conceptual governance framework for enterprise AI and analytics that is explicitly centered on LLMs embedded in analytics pipelines. The framework adopts a three-layered perspective—model and data alignment, system and workflow alignment, and ecosystem and governance alignment—that links technical properties of models to enterprise analytics practices, performance indicators, and oversight mechanisms. In practical terms, the framework shows how model and workflow choices translate into concrete metrics and inform real deployment, monitoring, and scaling decisions for LLM-powered analytics. We also illustrate how this framework can guide the design of controls for metrics, monitoring, human-in-the-loop structures, and incident response in LLM-driven analytics. The paper concludes with implications for analytics leaders and governance teams seeking to operationalize responsible, scalable use of LLMs in enterprise settings. Full article

Surface deformation induced by the extraction of natural resources constitutes a non-stationary spatiotemporal process. Modeling surface deformation time series obtained through Interferometric Synthetic Aperture Radar (InSAR) technology using deep learning methods is crucial for disaster prevention and mitigation. However, the complexity of model hyperparameter configuration and the lack of interpretability in the resulting predictions constrain its engineering applications. To enhance the reliability of model outputs and their decision-making value for engineering applications, this study presents a workflow that combines a Tree-structured Parzen Estimator (TPE)-based Bayesian optimization approach with ensemble inference. Using the Rhineland coalfield in Germany as a case study, we systematically evaluated six deep learning architectures in conjunction with various spatiotemporal coding strategies. Pairwise comparisons were conducted using a Welch t-test to evaluate the performance differences across each architecture under two parameter-tuning approaches. The Benjamini–Hochberg method was applied to control the false discovery rate (FDR) at 0.05 for multiple comparisons. The results indicate that TPE-optimized models demonstrate significantly improved performance compared to their manually tuned counterparts, with the ResNet+Transformer architecture yielding the most favorable outcomes. A comprehensive analysis of the spatial residuals further revealed that TPE optimization not only enhances average accuracy, but also mitigates the model’s prediction bias in fault zones and mineralize areas by improving the spatial distribution structure of errors. Based on this optimal architecture, we combined the ten highest-performing models from the optimization stage to generate a quantile-based susceptibility map, using the ensemble median as the central predictor. Uncertainty was quantified from three complementary perspectives: ensemble spread, class ambiguity, and classification confidence. Our analysis revealed spatial collinearity between physical uncertainty and absolute residuals. This suggests that uncertainty is more closely related to the physical complexity of geological discontinuities and human-disturbed zones, rather than statistical noise. In the analysis of super-threshold probability, the threshold sensitivity exhibited by the mining area reflects the widespread yet moderate impact of mining activities. By contrast, the fault zone continues to exhibit distinct high-probability zones, even under extreme thresholds. It suggests that fault-controlled deformation is more physically intense and poses a greater risk of disaster than mining activities. Finally, we propose an engineering decision strategy that combines uncertainty and residual spatial patterns. This approach transforms statistical diagnostics into actionable, tiered control measures, thereby increasing the practical value of susceptibility mapping in the planning of natural resource extraction. Full article

Traditional surgical techniques are based on the manual application of force using mallets and osteotomes, which often result in uncontrolled impact forces, procedural inconsistencies, and patient discomfort. Magnetic mallets (MMs), magnetodynamic devices, provide a controlled application of force using electromagnetism, aiming to achieve greater precision, reduced operating time, and improved surgical outcomes. The aim of the present systematic review was to evaluate the effectiveness of MMs compared to conventional surgical techniques in oral and implant surgery. The focused question was as follows: “Do magnetic mallets improve clinical outcomes in oral and implant surgery compared to traditional instruments?” Only clinical studies comparing the use of MMs with traditional techniques in oral surgery were included. The following databases were searched up to 27 November 2025: Pubmed, Scopus, Web of Science. For quality assessment, the Cochrane Risk of Bias 2 (RoB 2) tool was applied for randomized controlled trials (RCTs), while the Newcastle–Ottawa Scale (NOS) was used for non-randomized studies. Data were screened and synthesized by two reviewers. The systematic review was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. In total, 347 studies were initially found and 6 matched the inclusion criteria and were included in the review, for a total of 282 patients. Five RCTs were included, as well as one retrospective study. The studies investigated were as follows: implant site preparation (two studies with a total of 86 patients), sinus lift and contextual implant insertion (three studies, total: 102 patients), dental extraction (two studies, total: 70 patients), and split-crest (one study with 46 patients). The outcomes suggest that MMs may serve as a potential alternative to traditional techniques, exhibiting promising although preliminary outcomes. The studies included reported a lower incidence of benign paroxysmal positional vertigo with the use of MMs compared to hand osteotomes. Regarding quality assessment, RCTs raised some concerns, while the retrospective study had a moderate risk of bias. Despite the promising results, the paucity of high-quality controlled trials limits definitive conclusions on the superiority of MM over conventional techniques. Further well-designed comparative trials are needed to confirm the clinical benefits, optimize protocols across different indications, and evaluate MMs’ potential role in the management of critical bone conditions and complex surgery. Full article

Background/Objectives: Sexual dysfunction (SD) and broader sexual health problems are common after neurological disorders, yet interventional evidence is fragmented across conditions and outcomes. This umbrella review mapped and appraised systematic review-level evidence on interventions targeting SD and sexual health in neurological populations and qualified conclusions using certainty of evidence. Methods: PubMed, Web of Science, Cochrane Library, Embase, PsycINFO, EBSCOhost, and Scopus were searched from inception to 27 November 2025. Two reviewers screened records, extracted data, assessed review quality with AMSTAR 2, and rated certainty across intervention–outcome pairings using a GRADE-informed approach that integrated review confidence and primary-study risk-of-bias as reported by the source reviews. Results: Twenty-six systematic reviews were included. Overall confidence was frequently limited (17/26 critically low and 6/26 low), with only a small subset rated moderate or higher. Evidence was most coherent for phosphodiesterase type 5 (PDE5) inhibitors improving erectile function in men with spinal cord injury, whereas most other interventions and outcomes were supported by low or very low certainty. Women were represented in 16/26 reviews, yet validated female sexual function outcomes were synthesized in 6/26 reviews and relationship/couple outcomes in 3/26; furthermore, 10/26 reviews restricted inclusion to men, and no review synthesized pediatric intervention trials. Conclusions: Evidence supports PDE5 inhibitors for improving erectile function in men with spinal cord injury, while evidence for other interventions and sexual health domains remains limited. Methodological limitations highlight the need for more inclusive trials, broader standardized outcomes, and longer follow-up within neurorehabilitation pathways. Full article

Anthropogenic pressures in the Amazon Basin are reshaping human–animal–environment interactions and increasing zoonotic disease risk. Within this One Health context, domestic dogs and cats are underrecognized contributors to pathogen circulation at the human–wildlife interface. We conducted a PRISMA-compliant systematic review of zoonotic pathogens reported in companion animals across Amazonian territories in nine countries, including literature published between 2000 and 2025 in four languages. Zoonotic pathogens showed a heterogeneous yet widespread distribution, with parasitic infections, particularly Leishmania spp., Toxoplasma gondii, and vector-borne protozoa, being the most frequently reported. A pronounced geographic bias was evident, with studies concentrated in Brazil and selected areas of the western Amazon, while large portions of the Basin remain understudied. Methodological limitations included reliance on cross-sectional designs and heterogeneous diagnostic approaches, often based solely on serology. These findings highlight the need to strengthen One Health-oriented governance frameworks that integrate animal health surveillance into environmental and public health policies. Priority actions include expanding surveillance to underrepresented regions, harmonizing diagnostic protocols, investing in regional laboratory capacity, and promoting community-based monitoring. Strengthened cross-sectoral and transboundary coordination is essential to reduce zoonotic risk and support evidence-based disease prevention in Amazonian ecosystems. Full article

Background: Cardiometabolic risk (CMR), including obesity, dyslipidemia, hypertension, and impaired glucose regulation, disproportionately affects Hispanic/Latinx adults in the United States (U.S.). Although plant-forward dietary patterns are established as cardioprotective, less is known about how dietary patterns within Hispanic/Latinx subgroups relate to CMR. Methods: A narrative review was conducted of observational studies among U.S. Hispanic/Latinx adults (≥18 years) examining defined dietary patterns (a priori, a posteriori, or hybrid) in relation to CMR outcomes (e.g., BMI, waist circumference, blood pressure, glucose, lipids). Risk of bias was assessed using an adapted version of the Newcastle–Ottawa Scale. Results: Ten studies met the inclusion criteria, including Seventh-day Adventist Latinx, Puerto Rican adults, Mexican American adults, Hispanic women, and a national Hispanic cohort. Plant-forward dietary patterns were associated with lower BMI and waist circumference, lower triglycerides and fasting glucose, and higher HDL-C. In contrast, energy-dense patterns characterized by refined grains, added sugars, processed meats, fried foods, solid fats, and sugar-sweetened beverages were associated with greater adiposity, poorer lipid profiles, and higher blood pressure. Traditional rice-and-beans–based patterns observed in Puerto Rican and Mexican American groups were associated with central adiposity and higher metabolic syndrome prevalence, despite modestly higher intakes of fruits, vegetables, and fiber. Study quality ranged from good (n = 4) to very good (n = 6). Conclusions: Across Hispanic/Latinx subgroups, plant-forward dietary patterns were associated with favorable cardiometabolic profiles, whereas refined and animal-based patterns aligned with higher CMR. Given the predominance of cross-sectional evidence, these findings should be interpreted as associative rather than causal. Culturally grounded dietary counseling, along with additional longitudinal and intervention studies, is needed to support cardiometabolic health in these populations. Full article

This study addresses the issues of sparse observations from buoys in the tropical Indian Ocean and systematic biases in reanalysis products by proposing a daily-mean wind speed reconstruction framework that integrates multi-source meteorological fields. This study also considers the impact of different source domains on model pre-training, with the goal of providing reliable data support for wind energy assessment. The model was pre-trained using data from the Americas and tropical Pacific buoys as the source domain and then fine-tuned on Indian Ocean buoys as the target domain. Using annual leave-one-out cross-validation, we evaluated the model’s performance against uncorrected ERA5 and CCMP data while comparing three deep reconstruction models. The results demonstrate that deep models significantly reduce reanalysis bias: the RMSE decreases from approximately 1.00 m/s to 0.88 m/s, while R² improves by approximately 8.9% and 7.1% compared to ERA5/CCMP, respectively. The Branch CNN–Transformer outperforms standalone LSTM or CNN models in overall accuracy and interpretability, with transfer learning yielding directional gains for specific wind conditions in complex topography and monsoon zones. The 20-year wind energy data reconstructed using this model indicates wind energy densities 60–150 W/m² higher than in the reanalysis data in open high-wind zones such as the southern Arabian Sea and the Somali coast. This study not only provides a pathway for constructing high-precision wind speed databases for tropical Indian Ocean wind resource assessment but also offers precise quantitative support for delineating priority development zones for offshore wind farms and mitigating near-shore engineering risks. Full article