Search Results (45,761)

Background: Vertebral fractures are the most common osteoporotic fractures and are frequently underdiagnosed. Although prior fragility fractures increase the risk of subsequent fractures, the magnitude and distribution of extremity fracture risk following vertebral fractures remain incompletely defined. Objective: The objective of this study is to evaluate the risk of subsequent extremity fractures following vertebral fractures in adults aged ≥ 50 years and to characterize fracture patterns and timing. Methods: A systematic review was conducted using three databases (PubMed, OVID, and Scopus) covering studies published between January 2005 and December 2025. Studies reporting subsequent extremity fractures after an index vertebral fracture in adults aged ≥ 50 years were included. Data extraction included patient demographics, fracture characteristics, treatment variables, and incidence of subsequent fractures. Results: Eight studies were included in the qualitative (narrative) synthesis, comprising a total of 488,770 patients with an index vertebral fracture. The reported incidence of subsequent extremity fractures ranged from 1.4% to 12.4%, with a crude aggregated incidence of 6.90% (33,605 patients). Hip fractures accounted for 73.3% of extremity fractures, followed by forearm/wrist (11.8%), humerus (10.3%), and ankle fractures (3.26%). Most subsequent extremity fractures occurred within 1–3 years after the index vertebral fracture. Additionally, 23,542 patients (4.82%) experienced subsequent vertebral fractures. Rates of dual-energy X-ray absorptiometry utilization and pharmacologic treatment ranged from 5% to 34.5%. Conclusions: Vertebral fractures in adults aged ≥ 50 years are strong predictors of subsequent extremity fractures, particularly hip fractures, with risk concentrated in the early post-fracture period. These findings support the concept of a systemic fracture cascade and emphasize the need for early detection and structured secondary prevention strategies. Full article

Background and Objectives: Coronavirus disease 2019 (COVID-19) is characterized by excessive inflammatory responses, including the so-called cytokine storm, which contributes substantially to morbidity and mortality in hospitalized patients. The vagus nerve, through the cholinergic anti-inflammatory pathway, represents a theoretically attractive therapeutic target for modulating systemic inflammation. Vagus nerve stimulation (VNS) has emerged as a potential adjunctive treatment for COVID-19, with several randomized controlled trials (RCTs) investigating its efficacy on inflammatory biomarkers and clinical outcomes. The quality of this evidence base has not been rigorously evaluated. This systematic review critically appraises all available RCT evidence for VNS in hospitalized COVID-19 patients. Materials and Methods: We systematically searched PubMed, Scopus, Cochrane (CENTRAL), and Web of Science from database inception to January 2026, for RCTs evaluating any form of VNS (invasive, non-invasive, cervical, or auricular) in hospitalized patients with confirmed acute COVID-19. Two reviewers independently screened titles, abstracts, and full texts according to pre-specified eligibility criteria. Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool, with assessments initially performed using multiple artificial intelligence tools and subsequently validated by the authors in accordance with PRISMA 2020 guidelines. Given substantial heterogeneity and high risk of bias, narrative synthesis was performed rather than meta-analysis. Also, GRADE assessment was performed. Results: From 437 records identified, six RCTs comprising 221 patients met the inclusion criteria. Five trials (83%) were rated as high risk of bias, primarily due to inadequate blinding, substantial baseline imbalances, significant missing data and extensive multiple testing without statistical correction. The single double-blind trial with a credible sham control (Rangon et al.) found null results across all outcomes, including clinical progression, ICU transfer, and mortality, while the five “high” risk-of-bias trials generally reported positive findings on various inflammatory markers and clinical outcomes. One trial (Corrêa et al.) measured heart rate variability as a direct indicator of vagal activation and found no change despite claiming anti-inflammatory effects, contradicting the proposed mechanism of action. Significant cognitive findings from an interim analysis (Uehara et al., n = 21) disappeared in the larger completed trial (Corrêa et al., n = 52), providing empirical demonstration of false positive findings in small, underpowered studies. Conclusions: Currently available evidence supporting the use of VNS for acute COVID-19 remains scarce; however, the physiological rationale remains sound, although the absence of reliable target engagement markers in the included studies limits confidence in this treatment method. Large-scale, double-blind, sham-controlled trials are required before VNS can be firmly recommended for COVID-19 management. Full article

Despite the widespread adoption of BIM, information exchange across disciplines remains hindered by heterogeneous structures at the tabular data level, particularly when integrating data across multiple discipline-specific models. Manual mapping, rigid templates, or one-off programming scripts are labor-intensive and difficult to scale, limiting automated querying, cross-model aggregation, and schedule-level analytics. This study proposes a lightweight, workflow-driven approach for semantic normalization and cross-model integration of BIM schedule data, with optional script-supported workflow configuration used only to assist the configuration of deterministic, rule-guided mapping logic, rather than serving as a core analytical method. By introducing a customizable subcategory layer, the workflow enables fine-grained semantic alignment and efficient normalization across diverse schedule datasets, implemented through lightweight Python scripting and rule-guided semantic matching used solely as a supporting mechanism for deterministic field mapping. Using structural, architectural, and HVAC models, we demonstrate a stepwise process including data cleaning, hierarchical classification, consistency checking, batch analytics, and automated computation of cross-model metrics such as opening-to-wall ratios. Sample-based validation confirms the workflow’s reliability, achieving semantic mapping agreement rates above 95% and reducing manual processing time by more than 85%. The workflow is readily extensible to other disciplines and modeling conventions, supporting high-throughput data integration for tasks such as design coordination, semantic alignment, RFI reduction, accelerated design reviews, and data-driven decision making. Overall, rather than introducing a new algorithm, the contribution of this work lies in formalizing a reusable, schedule-level workflow abstraction that enables consistent semantic alignment and automated cross-model aggregation without relying on rigid ontologies or training-intensive learning-based models. Any optional tooling used during workflow configuration is auxiliary and does not constitute a standalone learning-based method requiring model training or performance benchmarking. This provides a reusable methodological foundation for scalable, schedule-level BIM data integration and cross-model analytics. Full article

Background: Global immunization programs continue to rely on needle-based injections despite persistent concerns regarding sharps disposal, accidental injuries, and the technical skill required for accurate intradermal administration. Needle-free jet injectors (NFJIs) are an alternative delivery method in which narrow, high-velocity liquid jets penetrate the skin without a needle. Contemporary designs, ranging from single-use disposable-syringe injectors to digitally controlled electromechanical devices, address historical safety issues and meet current WHO and FDA device expectations. Methods: Evidence from engineering analyses, preclinical modeling, and clinical trials was reviewed to characterize how jet velocity, nozzle structure, and formulation rheology influence skin penetration and drug dispersion. Published vaccine studies were examined for antibody responses, seroconversion, and reactogenicity compared with needle–syringe injection. Field vaccination campaign data from national campaigns and operational reports were evaluated to describe implementation steps, acceptability, and implementation constraints. Results: Published studies evaluating vaccines, including inactivated influenza, hepatitis B, typhoid, rabies, and measles, report antibody titers and seroconversion rates after NFJI administration that are comparable to those achieved with conventional intramuscular or intradermal needle injection. Needle-free delivery was associated with operational advantages in several immunization programs, including reduced sharps waste and improved vaccination rate during high-volume immunization campaigns. Local and systemic reactogenicity follows expected patterns, with slightly higher injection-site responses in some NFJI studies. Imaging and mechanical data confirm that jet performance depends on nozzle geometry and controlled pressure pulses. At the same time, formulation stability remains a critical determinant of successful jet-based vaccine administration, particularly for protein antigens, adjuvanted formulations, and emerging mRNA vaccines that may experience transient shear stress during high-velocity injection. Evidence from vaccination campaigns further indicates that needle-free jet injectors reduce sharps waste, simplify vaccine handling and administration procedures, and support rapid vaccine delivery in large-scale immunization programs. Conclusions: Needle-free jet injectors are a practical alternative to traditional needle-based injections for some vaccines. Their main benefits include enabling intradermal dose-sparing strategies, reducing reliance on sharps disposal methods, and enabling the efficient vaccination of large groups without compromising immunogenicity. Future research should define the physicochemical stability limits of biologic formulations subjected to jet injection and evaluate digitally controlled injectors capable of precise pressure modulation and adjustable delivery parameters. In addition, needle-free jet injection eliminates needle penetration and sharps handling, which may reduce needle-associated anxiety and improve vaccine acceptability among individuals with needle aversion. Full article

COVID-19 is increasingly recognized as a multisystemic disease with significant neurocognitive consequences. However, its specific impact on spatial memory, a cognitive domain essential for daily navigation and functional independence, remains insufficiently explored. This narrative review provides a critical synthesis of current evidence regarding spatial and visuospatial memory alterations across acute and post-acute phases, and post COVID-19 condition (PCC). Clinical findings, conventional and emerging assessment tools ranging from static tasks to immersive virtual reality environments, as well as potential neurobiological mechanisms, were considered. Results suggested that spatial memory is frequently compromised after COVID-19 disease, with deficits being most pronounced at longer retention intervals and within navigational contexts. Neuroimaging and biomarker data further reveal selective vulnerability in the medial temporal lobe, characterized by hippocampal atrophy, hypoperfusion, and disrupted functional connectivity. Importantly, traditional neuropsychological tools may underestimate these impairments due to limited ecological validity. Therefore, implementing multimodal assessment frameworks that integrate navigational paradigms is essential to enhance diagnostic sensitivity and facilitate the development of targeted rehabilitation strategies for PCC patients. Full article

Accurate energy forecasting is essential for maintaining power system reliability, integrating renewable generation, and ensuring market stability. Although machine learning has improved forecasting accuracy, its operational deployment depends on Machine Learning Operations (MLOps) platforms that automate and scale the entire lifecycle of energy data pipelines. However, the capabilities of existing MLOps platforms for energy forecasting have not been systematically compared. This study adopts a PRISMA-informed review process to identify relevant end-to-end MLOps platforms for energy forecasting and then maps their documented capabilities using an established energy forecasting pipeline lifecycle as the reference structure. A total of 256 records were screened across vendor documentation, open-source repositories, and academic literature, of which 13 MLOps platforms were selected for comparative capability analysis. Platform capabilities are organised and presented across an end-to-end lifecycle covering project setup and governance, data ingestion and management, model development and experimentation, deployment and serving, and monitoring and feedback. Commercial platforms such as Amazon SageMaker and Google Vertex AI generally provide stronger end-to-end integration and production readiness, while open-source platforms such as Kubeflow and ClearML offer modular flexibility that typically requires additional integration effort to achieve end-to-end operation. The mapping identifies four priority areas where platform support remains limited, namely (i) governance workflow automation, (ii) automated data quality validation, (iii) feature management, and (iv) deployment and monitoring support under nonstationary conditions. These findings indicate that platform selection for energy forecasting should be treated as a lifecycle capability decision, balancing end-to-end integration, operational assurance, and long-term flexibility. Full article

Background/Objectives: This study evaluates the efficacy of hypoglossal nerve stimulation as an alternative intervention for pediatric patients with obstructive sleep apnea (OSA) unresponsive to standard therapies and examines the uniformity of therapeutic outcomes across different patient cohorts. Methods: An extensive systematic search was performed across four principal databases (PubMed, EMBASE, Cochrane Library, and Web of Science) utilizing keywords associated with pediatric OSA and hypoglossal nerve stimulation, encompassing studies up to July 2025 that provided objective polysomnographic metrics (e.g., apnea-hypopnea index [AHI] values) to enable the quantitative assessment of pre- and post-intervention effects in children. The primary outcome measured was the ratio of means (ROM), determined from pre–post data in single-group studies, with summary estimates obtained using the fixed-effects model. Results: The systematic review included nine eligible studies with a total of 140 pediatric subjects, the majority of whom were adolescents with Down syndrome. AHI meta-analysis outcomes indicated a marked improvement in OSA severity, yielding an overall ROM of 0.57 [95% confidence interval: 0.49–0.65]. The therapeutic benefit demonstrated a high degree of uniformity across cohorts, as indicated by minimal statistical heterogeneity (I² = 16%, p = 0.30). Funnel plot assessment showed no statistically significant evidence of systematic publication bias. Conclusions: Current evidence suggests that hypoglossal nerve stimulation therapy is a safe, effective, and valuable alternative for pediatric OSA patients who do not respond to conventional therapies. Full article

Objectives: To map and synthesize the available evidence regarding the use of manual therapy, core stability training, and Pilates Method exercises in the rehabilitation of musculoskeletal conditions in adult dancers. Methods: A scoping review was conducted in accordance with the PRISMA-ScR guidelines. A systematic search across six electronic databases (PubMed, Scopus, Web of Science, SPORTDiscus, CINAHL, and PEDro) was performed. Study eligibility was strictly guided by the Population–Concept–Context (PCC) framework. Two independent reviewers screened the literature and extracted data. Results: A total of 16 studies met the inclusion criteria, encompassing randomized controlled trials, intervention studies, and case-level reports or series. Interventions primarily addressed chronic ankle instability, low back pain, and post-surgical rehabilitation. Results indicate that while individualized manual therapy and Pilates Method protocols are widely utilized in dance medicine, high-level evidence remains limited. Conclusions: Integrated rehabilitation approaches combining manual therapy with motor control exercises (such as the Pilates Method and core training) appear to have potential utility in supporting the safe return of dancers to performance. However, the current literature is heavily reliant on observational and case-driven evidence, highlighting the need for robust clinical trials to establish standardized, dance-specific rehabilitation guidelines. Full article

The use of effect size estimates to complement visual analysis has become increasingly emphasized in single-case research design (SCRD) studies in special education. This review examined trends in SCRD publication and ES reporting practices across three major special education journals (i.e., Journal of Special Education, Exceptional Children, and Remedial and Special Education) from 2001 to 2025. A total of 1969 articles were screened, yielding 194 SCRD intervention studies and 124 SCRD systematic reviews/meta-analyses. Results indicated a sustained increase in the publication of SCRD studies over time, accompanied by a marked rise in ES reporting. Overall, 42.27% (n = 82) of SCRD intervention studies and 55.65% (n = 69) of SCRD systematic reviews reported at least one effect size estimate, with the highest rates observed in the most recent publication period (2001–2025). Across both intervention studies and systematic reviews, Percentage of Nonoverlapping Data and Tau-U were the most frequently reported ES metrics, although reliance on Percentage of Nonoverlapping Data declined over time while use of Tau-U increased. Findings highlight evolving effect size reporting practices and have implications for evidence synthesis and methodological standards in special education research. Full article

The rapid increase in companion animal ownership has intensified the demand for innovative tools that support animal health and overall welfare. In recent years, artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has emerged as a promising approach in veterinary medicine. However, its application beyond clinical diagnostics, especially in behaviour and personality assessment, remains fragmented and insufficiently integrated into routine practice. This systematic review aims to synthesise current knowledge on AI-based applications in companion animal care, with a focus on behavioural monitoring, personality prediction, and welfare-related challenges. Following PRISMA guidelines, a structured literature search was conducted in the Scopus and PubMed databases from 2020 to 2025. In addition, grey literature sources were searched to capture relevant non-peer-reviewed data. A total of 115 studies met the inclusion criteria and were included in the analysis. Eligibility criteria included studies applying AI methods (machine learning or deep learning) to companion animals (dogs, cats, and exotic pets), while studies on humans, farm animals, or without AI methods were excluded. Due to the heterogeneity of included studies, no formal risk of bias assessment was performed, and results were synthesised narratively. The findings indicate that AI applications are most advanced in diagnostic imaging and clinical decision support, where data availability and methodological maturity are highest. In contrast, AI-based approaches for behaviour and personality prediction remain limited, particularly in cats and exotic companion animals, largely due to small, heterogeneous datasets, potential bias, and a lack of external validation. Emerging technologies such as wearable sensors, computer vision, and multimodal data integration demonstrate substantial potential for continuous behavioural monitoring and early detection of welfare-related issues in real household environments. Nevertheless, significant challenges persist, including data heterogeneity, limited model explainability, ethical considerations, and the absence of regulatory frameworks specifically addressing AI-based veterinary applications. Overall, this review highlights a substantial gap between the technical potential of AI and its current readiness for widespread application in companion animal behaviour and welfare assessment. Future research should prioritise large-scale and standardised data collection, cross-species validation, and interdisciplinary collaboration to ensure that AI-driven tools effectively support veterinary decision-making, animal welfare, and the well-being of owners. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic, multisystemic disorder characterized by severe, persistent fatigue not alleviated by rest and worsened by minimal exertion, often accompanied by post-exertional malaise (PEM), unrefreshing sleep, cognitive dysfunction, and autonomic disturbances. Despite decades of research, its pathophysiology remains incompletely understood, and skeletal muscle involvement has only recently gained attention. This review aims to provide a historical and pathophysiological synthesis of ME/CFS, emphasizing the pivotal role of skeletal muscle in the onset and persistence of symptoms, and to integrate molecular, cellular, and pathophysiological evidence into a coherent explanatory framework. This is a narrative review of published literature (1990–2025) with critical integration of clinical, biochemical, and experimental data on oxidative stress, mitochondrial dysfunction, Excitation–Contraction (E-C coupling) dysregulation, and muscle secretome alterations in ME/CFS also in relation to post-viral syndromes (e.g., Long COVID). Evidence consistently points to mitochondrial oxidative stress, redox imbalance, impaired Ca²⁺ handling, and altered signaling pathways in skeletal muscle of patients with ME/CFS. Historical milestones show an evolution from psychogenic interpretations toward recognition of ME/CFS as a biological disorder with neuromuscular and metabolic underpinnings. ME/CFS can be interpreted as a skeletal muscle–metabolic disorder characterized by oxidative distress, mitochondrial dysfunction, and impaired energy regulation, leading to the clinical picture of exercise intolerance and post-exertional malaise. Integrating basic and clinical research through a translational approach provides the foundation for new diagnostic tools, targeted therapies, and biomarkers. Full article

Background/Objectives: Psoriatic disease is a systemic inflammatory condition associated with increased cardiometabolic risk, but the impact of contemporary systemic therapies and narrowband ultraviolet B (NB-UVB) phototherapy on vascular and systemic inflammatory markers remains incompletely characterized. We aimed to systematically synthesize prospective evidence on treatment-associated changes in vascular inflammation and systemic inflammatory biomarkers in adults with moderate-to-severe psoriatic disease. Specifically, we evaluated changes assessed by 18F-FDG PET/CT imaging and circulating biomarkers following biologic therapies or NB-UVB phototherapy. Methods: We systematically searched MEDLINE, Embase, Web of Science, Scopus, and CENTRAL from inception to 31 January 2026 for prospective interventional and observational studies in adults with psoriasis or psoriatic arthritis treated with biologic agents targeting TNF-α, IL-12/23, IL-17, or IL-23, or with NB-UVB phototherapy. Eligible studies were required to report serial assessments of vascular inflammation by 18F-FDG PET/CT (typically aortic target-to-background ratio) and/or systemic inflammatory markers (high-sensitivity C-reactive protein, interleukin-6, TNF-α, GlycA, or hematologic indices such as the neutrophil-to-lymphocyte ratio) over at least 8 weeks of follow-up. We imposed no language restrictions and included only full-text, peer-reviewed prospective studies. Risk of bias was evaluated using RoB 2 for randomized trials and ROBINS-I for nonrandomized studies. Random-effects meta-analyses were prespecified for outcomes reported by at least two clinically comparable studies; however, because of substantial heterogeneity in reporting and methodology, effect estimates were summarized using a structured narrative synthesis. Results: Thirteen prospective studies (n ≈ 900 adults, published 2015–2025) met inclusion criteria, including four studies with serial 18F-FDG PET/CT imaging and one additional PET/CT study providing baseline observational data on vascular inflammation, as well as eight biomarker-focused prospective cohorts. Across randomized mechanistic trials and observational studies, biologic therapies reduced aortic target-to-background ratio by approximately 6–12% over 12–24 weeks (e.g., mean change from 2.42 to 2.18 with TNF-α inhibition and from 2.51 to 2.20 with IL-17 blockade), and no study reported worsening of PET-derived vascular indices under effective systemic treatment. Biologic and other systemic therapies produced concordant reductions in hs-CRP (typically by 30–50%), IL-6, TNF-α, GlycA, and blood-count-derived indices including neutrophil-to-lymphocyte ratio, with biomarker improvements frequently paralleling reductions in cutaneous disease activity and cardiometabolic risk markers. Two NB-UVB cohorts demonstrated significant hs-CRP reductions of roughly 20–30% and modulation of vitamin D-related inflammatory proteins, suggesting systemic anti-inflammatory effects, although these changes appeared less pronounced than with biologic therapy and were not accompanied by vascular imaging. Conclusions: Contemporary systemic psoriasis therapies, particularly biologic agents targeting the IL-23/Th17 axis and TNF-α, are associated with consistent reductions in aortic vascular inflammation and broad improvements in systemic inflammatory biomarkers, whereas NB-UVB phototherapy confers more modest but measurable systemic anti-inflammatory effects, although the current evidence does not allow differentiation between individual biologic classes in terms of magnitude of effect. Although reductions in vascular and systemic inflammatory markers were observed across therapies targeting TNF-α, IL-12/23, IL-17, and IL-23, the small number of mechanistic imaging studies and absence of head-to-head comparisons do not allow robust differentiation between biologic classes or support a uniform class effect. The convergence of imaging and biomarker data reinforces psoriasis as a clinically relevant model of inflammation-driven atherosclerosis and supports the concept that effective control of psoriatic inflammation may contribute to cardiovascular risk modification, highlighting the need for integrated cardiovascular risk assessment in routine care. However, the imaging evidence base remains limited to four small mechanistic PET/CT studies with relatively short follow-up, which constrains the strength and generalizability of conclusions regarding vascular inflammation. Larger, adequately powered, event-driven prospective trials with standardized imaging and biomarker endpoints are needed to determine whether these vascular and systemic anti-inflammatory effects translate into reduced cardiovascular events in psoriatic disease; because of methodological and reporting heterogeneity across the 13 included studies, these conclusions are based on a structured narrative synthesis rather than a formal quantitative meta-analysis. PROSPERO registration number: CRD420261296646. Full article

Decarbonising the building sector is an energy policy priority due to its major contribution to global energy consumption and related emissions. Accurate energy modelling is crucial, with significant scientific advancements being made in the last decade. As data gathering is a primary bottleneck, the potential of Geographic Information Systems and Remote Sensing for streamlining data acquisition and integrating data sources has gained specific interest. This study aims to identify prevailing trends in scales, inputs, and outputs of energy modelling, focusing on Remote Sensing and Geographic Information Systems applications. A structured literature review was conducted, encompassing screening, textual analysis, and findings synthesis to identify key research trends. The results highlight a predominance of the neighbourhood scale (54%) and the reliance on building geometries as principal input (91% of studies). Remote Sensing, used in 36% of cases, is employed for defining geometric (41%) and non-geometric (45%) attributes, while 17% of studies leverage it to determine climatic variables. EnergyPlus remains the most widespread simulation engine (37%), frequently coupled with construction archetypes (50% of cases) to address data gaps. The increasing integration of these technologies in energy modelling is expected to diversify the number of inputs, ultimately enhancing output accuracy, scalability, and generalisability. Full article

Objective: The aim of this systematic review was to evaluate the skeletal stability, predictability, and safety of using autogenous iliac crest bone grafts (ICBG) during large maxillary advancement performed with Le Fort I osteotomy. Methods: A systematic literature search was performed in November 2025 using PubMed, Scopus, Embase, Web of Science, and WorldCat databases. Clinical studies reporting large maxillary advancement performed with Le Fort I osteotomy and incorporating ICBG were included. Study selection followed PRISMA guidelines. Data extraction focused on the magnitude of maxillary advancement, surgical protocols, stabilization methods, skeletal stability, relapse patterns, graft integration, implant-related outcomes, and complications. Methodological quality was assessed using the Mixed-Methods Appraisal Tool (MMAT). Results: The review included clinical studies predominantly consisting of case reports, case series, and retrospective cohort studies. ICBG were consistently used in complex clinical scenarios, such as severe maxillary atrophy, hypoplasia, and congenital craniofacial deformities. Large maxillary advancements were generally associated with favorable postoperative skeletal stability, with most relapse occurring during the early healing phase and minimal changes observed during long-term follow-up when rigid fixation and adequate graft integration were achieved. Interpositional grafting facilitated predictable advancement by bridging extensive osteotomy gaps. Donor-site morbidity related to iliac crest harvesting was typically mild and transient. Implant-related outcomes, reported as secondary findings, were generally favorable when implants were placed after an adequate healing period. Conclusions: Despite predominantly observational evidence, ICBG during large maxillary advancement with Le Fort I osteotomy appears to offer predictable advancement, acceptable skeletal stability, and a favorable safety profile, warranting further prospective investigation. Full article

Mescaline, the primary bioactive alkaloid found in Peyote and San Pedro cactus, has been used in traditional medicine for centuries and is now attracting renewed interest for clinical applications. The purpose of this systematic review was to search the literature for studies reporting the use of mescaline to address the gap in our understanding of mescaline use and its impact. References were exported from PubMed, Scopus, Embase, and Cochrane. Included studies contained patient data pertaining to mescaline, primary sources for beliefs on the use of mescaline as traditional medicine, and a range of psychiatric conditions. Excluded studies included unpublished studies, animal studies, and studies without English full-texts available. Of 2770 imported references, 66 met the inclusion criteria, with only 10 being found suitable for analysis. Studies reported therapeutic effects such as improvements in depression scales, well-being, nicotine dependence, alcohol use, and obsessions. Bayesian analysis found that certain effects were frequently reported, such as hypertension, headache, nausea, and vomiting. The existing literature on mescaline is limited and of highly variable quality, preventing definitive conclusions regarding the prevalence of psychological and somatic effects from mescaline and mescaline-containing ethnobotanicals. Additional research is needed to determine the safety profile of mescaline. Given the prevalence of Peyote use in the Native American Church, the collaboration of the Native American Church and regional hospitals/poison centers is recommended to create a registry to allow for standardized and clinically applicable data collection on the effects of mescaline in prevalent populations. Full article