To provide a practical and descriptive comparison of contemporary clinical planning software for guided implant surgery, focusing on digital workflow feasibility, user experience, system requirements, cost models, and the availability of prosthetic component libraries, based on real‑world expert use. Seven implant planning software platforms (DentiqGuide, BlueSkyPlan, CoDiagnostix, Implant Studio, R2Gate, ExoPlan, and RealGuide) were evaluated by experienced clinicians using two predefined clinical scenarios representing moderate and high planning complexity. User interface (UI) friendliness was assessed using a Likert scale, and planning time was recorded according to standardized task definitions. Hardware requirements, pricing models, available functionalities, and workflow completeness were compared. All quantitative outcomes were analysed descriptively. Descriptive values of UI scores ranged from 5.3 to 10, while planning times ranged from 10 to 67 minutes depending on workflow completeness and task availability. Based on a predefined complete workflow (CW), only DentiqGuide and BlueSkyPlan enabled completion of all planning steps within a single clinical software environment, whereas other platforms required additional modules or external tools. System requirements and cost structures differed substantially, including license‑based and pay‑per‑use models. Semi‑automated functions, such as wax‑up-guided implant positioning, were available in several platforms. However, none provided fully automated planning. A consistent limitation across all evaluated software was restricted availability of prosthetic components within integrated libraries. Within the limits of this descriptive, expert‑based evaluation, the findings should be interpreted as exploratory and hypothesis‑generating rather than as comparative performance rankings. However, current clinical implant planning software may demonstrate substantial variability in workflow integration, usability and cost structure, and a common limitation in the availability of prosthetic component libraries. These findings highlight a persistent gap in achieving fully prosthetically driven digital workflows in clinical planning environments. The present findings reflect expert-dependent interaction with individual software platforms and were not validated using inter-rater reliability assessment. Therefore, the reported outcomes should not be interpreted as standardized or directly comparable measures of usability or workflow performance. Understanding practical digital workflow limitations, particularly restricted prosthetic component libraries, may support clinicians in selecting implant planning software that aligns with their experience level, case complexity, and clinical setting, while emphasizing the need for careful verification of prosthetic feasibility during digital treatment planning.
A major problem with reviewing the statistical methodology in published medical articles is that extracting the necessary details from large sample sets is time-consuming. This paper demonstrates how a novel automated procedure can extract information about statistical reporting from literature. To illustrate this, we searched the PubMed Central database for original research articles published in 2021 and 2023 to identify the statistical software packages used for data analysis. A key element in terms of transparency and reproducibility is the reporting of the software used for statistical analysis. A freely available Shiny App was created with the help of generative artificial intelligence, and it was used to retrieve automatically information from randomly selected samples of articles indexed in PubMed Central. We analyzed a large sample of articles (n = 1740) to determine the reporting of statistical software for nine study designs. We found that, across different study types, proprietary software such as IBM SPSS Statistics still dominates. Despite multiple calls for greater use of open-source research software, these programs are not used as frequently. In addition, a surprising number of articles did not report the software used. Furthermore, this is the first application of the recent Vibe Coding concept to statistical research methods.
Computational methods are central to the life sciences. The rapid growth and diversification of software tools and databases make it difficult to find, compare, and reuse methods for a given task. bio.tools is a community-driven registry designed to improve the visibility of research software and allow researchers to simplify access to the software ecosystem through structured, interoperable, and accessible metadata. Tools are annotated using the EDAM ontology and additional controlled vocabularies, enabling users to search and filter by scientific topics, operations, input/output data types, and data formats. bio.tools supports interactive exploration via rich tool landing pages and provides programmatic access through a documented API for search, retrieval, and registry statistics. The registry has expanded to almost 33,000 annotated tools through the combined contributions of thousands of community members and semi-automated literature mining that keep the registry up to date. Recent improvements to the registry include machine-assisted scoring to prioritise curator review, and consolidation of both its standards stack and software architecture. bio.tools has also become a foundational upstream metadata source that is reused by other services in the ELIXIR Research Software Ecosystem and beyond, to support synchronisation, cross-linking, and additional downstream services. bio.tools is freely available at https://bio.tools.
To present a feasible workflow for artificial intelligence (AI)-assisted software engineering in dentistry as a technical innovation report. The use of this workflow is illustrated through three self-developed open-source dental applications. Four AI-assisted development approaches were employed: chat-based interfaces of large language models, command-line interface tools, integrated development environments with AI assistance, and agent-based architectures. The dental software applications were created by a single clinician without formal programming training. Three applications were created: (1) VirtualEndo Converter, a Blender add-on for automated CBCT derived STL conversion for augmented/virtual reality (AR/VR), (2) MeshComparisonTool, a 3D Slicer extension for quantitative 3D morphology comparisons, and (3) DentalEmergencyTrainer, an application for simulating dental trauma emergency calls. All the applications are publicly available under the MIT license on GitHub. This report demonstrates that AI-assisted software development can enable dental practitioners without formal programming training to create functional prototypes of applications for research, education, and potentially clinical support. However, the reproducibility of this approach remains to be established, as the three tools were developed by a single clinician, and their clinical deployment would require thorough validation, security auditing, and regulatory assessment. AI-assisted development can help dental practitioners prototype tools that address unmet needs in clinical workflows, research, and education, but clinical use requires cautious separation from validated medical software. Before deployment, such tools require defined intended use, safety evaluation, data-protection safeguards, maintenance plans, and regulatory assessment.
Shaking table testing is a crucial method for evaluating the seismic performance of structures; however, the resulting data are typically characterized by massive volumes, high sampling rates, and complex multi-channel arrays. Traditional manual processing methods relying on commercial spreadsheet software (e.g., Excel, Origin) present significant limitations regarding processing efficiency, mathematical transparency, and result reproducibility. To address these methodological gaps, this paper proposes a novel, fully automated data processing and analysis framework tailored for high-density structural dynamic testing using an open-source Python toolchain. Unlike conventional "black-box' commercial software, this method provides a transparent, end-to-end pipeline-from automated raw multi-channel data alignment and signal pre-processing to advanced time-frequency domain analysis and standardized visualization. The framework's efficacy is validated using a shaking table test of a 1:2 scaled village masonry structure. The extracted experimental results clearly indicate that the masonry structure exhibits a significant low-pass filtering effect on high-frequency inputs (5-15 Hz), with response energy concentrated within the natural frequency range of 2-4 Hz. Furthermore, the pipeline integrates an automated structural health evaluation module; by comparing the Power Spectral Density (PSD) of white noise sweeps before and after seismic inputs, the method successfully and rapidly identified that while the structure exhibited displacement amplification under the 0.2 g operating condition, no significant stiffness degradation occurred. Ultimately, this study contributes a scalable, reproducible, and highly efficient methodological blueprint for big data analysis in structural seismic evaluation.
Photogrammetry technique may provide a promising approach compared to conventional techniques for multiple implants. However, the accuracy of photogrammetric technique for implant-supported fixed complete dentures in clinical scenarios remains unclear. This study aimed to evaluate the accuracy of photogrammetric technique in horizontal impressions for implant-supported fixed complete dentures compared to conventional impression technique in edentulous jaws. Between March and December 2023, twenty edentulous arches (10 maxillary and 10 mandibular), each consisting of four to eight dental implants, were selected. For the photogrammetric technique, specialized scan bodies were placed on dental implants, followed by a digital scan using a photogrammetric camera. An intraoral scanner was then applied to obtain the information of soft tissue, which was subsequently aligned with photogrammetric data in the software using a best-fit algorithm. After one month, half of the participants were selected to repeat the procedure to assess the precision of photogrammetric technique. For conventional impressions, a two-step technique was employed. The initial impression was first completed using polyvinyl siloxane impression material to create a model. After pouring dental stone, several impression posts were attached to analogs, and a perforated custom tray was subsequently fabricated to facilitate the open-tray splinted final impressions. The final impressions, made with polyvinyl siloxane impression material, were subsequently poured with dental stone and scanned using a laboratory scanner. The deviations in distances and angles between photogrammetric technique and conventional impression were measured in the software. Distance deviations were recorded as the main outcome, while angular deviations were calculated as the secondary outcome. Deviations between photogrammetric technique versus conventional impression technique were compared using the Wilcoxon test. The significance level was set at 0.05. The overall deviation in distance was 34.46 ± 24.65 mm for the maxilla and 49.80 ± 39.09 mm for the mandible. In terms of angular parameters, deviation was 0.36 ± 0.28 degrees for the maxilla and 0.44 ± 0.33 degrees for the mandible. The results of the Wilcoxon test indicated no significant differences in distance and angles between photogrammetric technique and conventional impression technique, demonstrating the acceptable trueness of the photogrammetric technique for implant-supported fixed complete dentures (P < 0.05). Additionally, no significant difference was found between two measurements using the photogrammetry technique over a one-month interval, indicating the promising precision of the technique (P < 0.05). The photogrammetric technique could serve as a promising alternative for implant-supported fixed complete dentures in edentulous patients, demonstrating acceptable trueness and precision in the clinical environment.
Accurate surgical case duration estimation (CDE) is critical for operating room efficiency, staffing, resource allocation, and patient safety. Traditional approaches-historical case averages, surgeon estimates, and variable use of electronic scheduling tools-frequently produce substantial under- or overestimation, leading to workflow disruption, overtime, and reduced access. This study developed and evaluated a machine learning (ML)-based CDE model and conducted a parallel human-factor analysis to identify contributors to scheduling variability at a high-volume tertiary cancer center. The authors curated 40,656 surgical cases across 22 service lines (2016-2024) and trained a gradient-boosted tree model (termed "ORchestra") using patient-, procedure-, and surgeon-specific features. Model performance was compared with existing scheduling practices, including originally scheduled duration, historical averages, and Epic's CDE tool under both user-adjusted and vendor-recommended configurations. Evaluation metrics included mean absolute error (MAE magnitude), mean signed error (MSE bias), and the proportion of cases scheduled within ± 30 min of actual duration (f30min) or within ± 10% of actual duration (f10%). Human-factor investigations assessed variation in scheduling behavior, definitions of case duration, and choice of software parameters. A silent-trial deployment examined real-world feasibility. Baseline scheduling practices demonstrated substantial systematic underscheduling bias (MSE = -31 min), wide variability across service lines, and low accuracy: overall MAE = 35.3 min, f30min = 0.52, and f10% = 0.09. Standardizing workflow elements-specifically, consistent inclusion of prep/wrap time and use of vendor-recommended Epic settings-substantially improved performance (MAE = 20.1 min, f30min = 0.81, and f10% = 0.37). The ORchestra ML model further reduced error (MAE = 19.8 min), eliminated systematic bias (+1.2 min), and decreased overscheduling outliers, with the largest gains observed in high-variability services. Notably, workflow standardization alone approached ML-level accuracy for many procedures, highlighting human-factor variability as a dominant source of error. ML-based CDE improves predictive accuracy and reduces disruptive scheduling outliers; however, real-world performance depends equally on standardized workflows, consistent software configuration, and unified operational definitions. This study demonstrates that successful deployment requires not only technical optimization but also organizational alignment, governance, and disciplined practice change. Integrating predictive tools into perioperative operations provides measurable benefit but must be paired with structured workflow redesign to ensure reliability, safety, and sustainable impact.
X-chromosome short tandem repeats (X-STRs) are valuable for resolving complex kinship cases. Most population databases are based on the ArgusX12 kit (Qiagen), using PCR and capillary electrophoresis (CE) to identify length-based (LB) alleles, and are formatted for FamlinkX software. However, haplotype diversity is often underrepresented by population studies, compelling database updates ( https://famlink.se/fx_databases.html ). The ForenSeq DNA Signature Prep kit (Verogen) uses massive parallel sequencing (MPS) to analyze 7 X-STRs and report sequence-based (SB) alleles, for which population databases are currently unavailable. Because these 7 markers are a subset of the ArgusX12 panel, existing LB-based databases can support kinship interpretation of MPS-derived data. We therefore updated a Mexican population database for 12 X-STRs and generated a corresponding 7-marker subset with FamlinkX-compatible files. Using 500 haplotypes from the Investigator Argus X-12 kit QS (Qiagen), we estimated forensic parameters and evaluated the impact of the updated database by calculating likelihood ratios (LRs) in four representative kinship scenarios. The updated database (n = 1433) increased LRs by an average of 55% compared to the previous version (n = 933). These results support improved forensic interpretation in Mexican and Latin American populations lacking comprehensive national X-STR databases based on ArgusX12 and ForenSeq DNA Signature kits.
Intra-abdominal infections are a common complication of colorectal cancer surgery. Postoperative abdominal infections can cause systemic inflammatory response syndrome, which seriously affects the prognosis of patients. With the widespread application of antibiotics, the detection rate of drug-resistant bacteria has increased annually, resulting in increased pressure on antibiotic treatment selection. To improve the prognosis of postoperative patients with colorectal cancer, it is important to actively search for risk factors leading to postoperative abdominal infection and formulate effective intervention measures according to these risk factors. A comprehensive search was conducted using several databases, including China National Knowledge Infrastructure, Wanfang Data, VIP, CBM, PubMed, Embase, and OVID, until September 2025. Case-control studies focusing on postoperative abdominal infections in colorectal cancer were conducted, and a meta-analysis was performed using the RevMan 5.4 software. A total of 21 case-control studies were included, and 42 risk factors for infection were identified. The results indicated that significant differences (P < .05) existed between the postoperative abdominal infection and non-infection groups concerning various factors, including diabetes mellitus, hypertension, cardiovascular disease, hypoproteinemia, tumor-node-metastasis stage I, tumor location, and several perioperative variables: operation time exceeding 150 minutes, hospital stay of 30 days or more, drainage tube indentation lasting over 10 days, serum albumin levels, preoperative hemoglobin levels, incision length > 15 cm, blood loss exceeding 300 mL, laparoscopic surgery, postoperative fistula, preoperative intestinal obstruction, anemia, anastomotic fistula, combined organ resection, preoperative ASA score, perioperative blood transfusion, and reoperation. Given the multitude of identified risk factors for postoperative abdominal infections in colorectal cancer, medical institutions should prioritize the prevention and control of hospital infections. This includes developing targeted strategies based on identified risk factors, careful assessment of surgical indications for colorectal cancer patients during clinical diagnosis and treatment, strict adherence to surgical protocols, and enhancing organ function support for patients post-surgery to reduce the incidence of postoperative abdominal infections.
Acute pancreatitis (AP) concurrent with acute kidney injury (AKI) remarkably elevates the risk of adverse outcomes in affected individuals. Abnormal serum magnesium concentrations have been linked to AKI development across diverse patient populations; however, the prognostic significance of serum magnesium levels at multiple time points (60 days, 90 days, 180 days, and 365 days) remains inadequately explored in AP patients with AKI admitted to the intensive care unit (ICU). This study aimed to assess the dynamic prognostic value of serum magnesium at the aforementioned key time points, clarify its clinical utility for risk stratification in this specific cohort, and investigate prognostic disparities among patients stratified by gender, as well as the presence or absence of diabetes mellitus, congestive heart failure, and pre-existing kidney disease. Study data were extracted from the MIMIC-IV database, which was made publicly available in October 2024. Adult patients (≥ 18 years) diagnosed with AP, who had an ICU length of stay (LOS) exceeding 24 h and complete mortality data, were enrolled. Exclusion criteria included missing serum magnesium measurements, ICU LOS < 24 h, incomplete clinical records, and aberrant survival data. Finally, 492 data samples meeting the inclusion criteria were enrolled in the present study. Serum magnesium levels were stratified into three grades using X-tile software, with stratification thresholds determined based on 60-day survival outcomes. Clinical data were retrieved using SQL and PostgreSQL. Intergroup comparisons were performed using statistical methods including the Wilcoxon rank-sum test, chi-square test, and t-test. Survival analyses were conducted to evaluate the association between serum magnesium levels and prognosis. Univariate Cox regression models were used to initially assess the relationship, and multivariate Cox regression models were constructed to adjust for confounding factors based on key patient characteristics. Among the 492 enrolled patients, males accounted for 53.25%. No statistically significant differences were noted in gender distribution or age across the three groups stratified by serum magnesium levels (P > 0.05). The hypermagnesemia group had the longest median ICU length of stay (LOS) (145 h, interquartile range [IQR]: 62-274 h), with intergroup differences approaching statistical significance (H = 5.112, P = 0.078). The incidence rates of sepsis and hypertension increased significantly with elevated serum magnesium levels (sepsis: χ² = 11.496, P = 0.003; hypertension: χ² = 6.065, P = 0.048). Additionally, the utilization rate of continuous renal replacement therapy (CRRT) in the hypermagnesemia group (20.75%) was significantly higher than that in the hypomagnesemia group (9.15%) and normomagnesemia group (11.48%) (χ² = 6.302, P = 0.043). In the hypermagnesemia group, serum creatinine, potassium, sodium, and chloride levels were significantly elevated, while serum calcium levels were markedly decreased (all P < 0.05). Disease severity scores, including the Sequential Organ Failure Assessment (SOFA) score, Simplified Acute Physiology Score II (SAPS II), and Logistic Organ Dysfunction System (LODS) score, were significantly higher in the hypermagnesemia group compared to the other two groups (all P < 0.05). Regarding prognostic outcomes, the hypermagnesemia group had the shortest median survival times at 60, 180, and 365 days, with statistically significant intergroup differences (H-values: 6.75, 6.033, 9.235; all P < 0.049). Its 365-day mortality rate (37.74%) was more than twice that of the hypomagnesemia group (18.61%). Kaplan-Meier analysis revealed that the hypermagnesemia group had significantly lower survival rates at all time points compared to the hypomagnesemia group (log-rank test, P < 0.05). Multivariate Cox regression analysis indicated that the risk of death gradually increased with rising serum magnesium levels, and hypermagnesemia was associated with a 54% higher risk of 365-day mortality (HR = 1.54, 95% CI: 0.54-4.43). Restricted cubic spline (RCS) analysis demonstrated a significant increase in mortality risk when serum magnesium levels exceeded 1.9 mg/dL. Subgroup analysis confirmed that the association between serum magnesium levels and prognosis was consistent across different subgroups. Furthermore, during the 365-day follow-up, the hypermagnesemia-related mortality risk was significantly elevated in obese patients and those with sepsis (P < 0.05). Elevated serum magnesium levels upon ICU admission are closely correlated with increased risks of adverse events and medium- and long-term mortality in patients with acute pancreatitis complicated by acute kidney injury, and can serve as a valuable early clinical indicator for evaluating disease severity and predicting patient prognosis. Abnormally elevated serum magnesium levels effectively reflect the status of severe concomitant organ dysfunction and possess favorable clinical value for disease assessment and prognostic prediction. The stratified cut-off values of serum magnesium established in this study can be applied to early clinical risk stratification and early warning for such patients. Routine dynamic monitoring of serum magnesium is recommended to facilitate early clinical evaluation and risk assessment. Furthermore, it provides a reliable reference for subsequent mechanistic investigations and prospective clinical trials to explore targeted interventions for improving patient outcomes.
To systematically evaluate structural and functional alterations of the subbasal corneal nerve plexus (SBCNP) in adults with migraine using in vivo confocal microscopy (IVCM) and corneal sensitivity testing, and to explore differences according to migraine subtype. PubMed, Embase, Ovid, LILACS, VHL, and MedRxiv were searched through May 24, 2025, for studies assessing IVCM or corneal sensitivity in adults with migraine. Eligible designs included case-control and cross-sectional studies. Outcomes included corneal total branch density (CTBD), nerve fiber density (NFD), nerve fiber length (NFL), nerve branch density (NBD), tortuosity coefficient (TC), and corneal sensitivity. Risk of bias was assessed using tools designed for each study type, and Certainty of evidence was graded using the GRADE framework adapted to observational studies. Due to substantial methodological heterogeneity across studies, including differences in IVCM acquisition protocols, image analysis software, and mathematical definitions of nerve parameters, findings were synthesized narratively. The protocol was registered in PROSPERO (CRD420251105525). Eight studies, including 370 participants with migraine, met eligibility criteria. Most studies evaluating chronic migraine populations reported lower CTBD, NFD, and NFL compared with healthy controls, although findings remained heterogeneous across studies. Studies of episodic migraine showed contradictory findings, including preserved nerve parameters or isolated increases in TC. Two studies using different neurophysiological approaches to measure corneal sensitivity suggested altered peripheral and central trigeminal sensory processing in migraine individuals. Available evidence suggests that chronic migraine may be associated with structural alterations of the SBCNP, whereas episodic migraine demonstrates more variable findings, including possible increases in nerve tortuosity. Functional studies suggest altered peripheral and central trigeminal sensory processing in migraine.
Sulfamethoxazole (SMX), an emerging contaminant frequently detected in water, poses a risk to drinking water safety and ecosystem health. Piezoelectric catalysis offers a light- and oxidant-free approach to contaminant removal, but its application is limited by rapid charge recombination and insufficient understanding of interfacial charge dynamics. Here, we construct a Bi2MoO6/BaTiO3 (BMO/BTO) heterojunction that leverages an interfacial electric field induced by the work function difference to enhance charge separation under ultrasonic stimulation. The optimized catalyst exhibits efficient and competitive piezocatalytic performance under the present reaction conditions, achieving a 97.74% removal rate of SMX within 60 min. It maintains stable activity over six cycles and demonstrates excellent degradation capabilities for various emerging pollutants (including tetracycline, bisphenol A, 1-naphthol, and acetaminophen). Radical trapping and EPR confirm ·O2- and ·OH as the primary reactive species. By integrating experiments, DFT calculations and transformation pathway analysis, we reveal that the interfacial electric field promotes charge redistribution, suppresses carrier recombination, and drives SMX transformation. Combined with the results of software simulation predictions and toxicity tests on Escherichia coli and Chlorella, these findings further indicate that the overall toxicity of treated SMX has been reduced compared to untreated SMX. This study designed a piezoelectric heterojunction material for pollutant degradation, with the aim of achieving efficient degradation and toxicity reduction of emerging pollutants.
Fibroblast activation protein alpha (FAP) is a pan-tumor target highly expressed on cancer-associated fibroblasts. We developed 4AH29, a single-domain antibody binding FAP, and investigated the biodistribution of [131I]I-GMIB-4AH29 and [111In]In-DOTA-4AH29 in Göttingen minipigs. Following radiopharmaceutical administration, blood activity profile was determined by gamma-counter and biodistribution kinetics were determined using SPECT/CT imaging, respectively. The data obtained with [111In]In-DOTA-4AH29 were used as a surrogate for its 177Lu- and 225Ac-labeled analogues and extrapolation to human absorbed dose was calculated for all analogues. Radiolabeled 4AH29 showed good tolerability within the studied time frame. It displayed fast blood clearance driven by renal excretion. Kidney clearance dynamics of [131I]I-GMIB-4AH29 and [111In]In-DOTA-4AH29 were distinct, likely driven by the different radiolabeling chemistry for halogen or metal conjugation. However, the contrasting patterns did not translate into relevant differences in mean residence time (MRT), nor was there a significant difference in bone marrow or liver MRTs when comparing halogen and metal-radiolabeled 4AH29. Extrapolated human absorbed doses for [131I]I-GMIB-4AH29 and [177Lu]Lu-DOTA-4AH29 were compared given their similar particle decay and comparable physical half-lives. In kidneys, [131I]I-GMIB-4AH29 led to an extrapolated human absorbed dose of 8.23E-01 mGy/MBq, whereas [177Lu]Lu-DOTA-4AH29 reached 5.86E-01 mGy/MBq. Consequently, the maximum tolerable administered activities were 28 and 39 GBq, respectively, to reach the renal absorbed dose limit of 23 Gy as determined by external beam radiation therapy (EBRT). In red marrow, the equivalent dose for [131I]I-GMIB-4AH29 was 3.8E-02 mGy/MBq and 1.36E-02 mGy/MBq with [177Lu]Lu-DOTA-4AH29. Thus, 53 GBq and 148 GBq can be administered, respectively, before reaching the EBRT set absorbed dose threshold of 2 Gy. 4AH29 radiolabeled with 131I or 111In is well tolerated in Göttingen minipigs within the studied time frame. Extrapolated dosimetry of radiolabeled 4AH29 using OLINDA software indicates that its administration within a clinically relevant range is possible without exceeding toxicity limits in critical organs.
This study aimed to review the self-care status of heart failure patients through the European Heart Failure Self-Care Behavior Scale. Eligible studies were retrieved by searching in PubMed, Web of Science, and Embase. The studies' title, abstract, and full text were screened and selected by two researchers independently. The data were analyzed using the Comprehensive Meta-Analysis software and a random effects model. A total of 7819 studies screened and 31 articles were included finally. The mean scores of selfcare in studies using the 12-item questionnaire were estimated to be 32.91 Å} 1.29 (95% CI: 30.38-35.44), in studies using the 9-item questionnaire it was 25.54 Å} 1.45 (95% CI: 22.68-28.40), in studies using the 9-item questionnaire with standardized score (0-100), it was 62.28 Å} 5.2 (95% CI: 52.08-72.47). The findings demonstrate that the level of self-care in heart failure patients is not satisfactory. Due to the high heterogeneity of the studies, the findings should be interpreted with caution. Cite this article as: Negarandeh, R., Hoseini-Esfidarjani, S.S., & Aghajanloo, A. (2025). Self-care behaviors in heart failure patients using the European Heart Failure Self- Care Behavior Scale: systematic review and meta-analysis. Florence Nightingale Journal of Nursing, 34, 0121, doi:10.5152/FNJN.2026.25121.
Radiance is a Monte Carlo-based treatment planning software integrated into the Intrabeam system for 50-kVp X-rays intraoperative radiotherapy (IORT). This study evaluates Radiance accuracy in calculating absorbed dose in IORT of the breast including the effect of tissue heterogeneities. Dose distributions from IORT were calculated in 88 virtual phantoms of different tissue-equivalent materials. Dose was calculated independently using the penEasy code for the PENELOPE Monte Carlo engine and compared to Radiance. Depth dose curves (DDCs) were compared through gamma analysis using 5%/0.5 mm and 3%/0.5 mm criteria. When comparing Radiance vs penEasy all passing rates were above 95%. Notable differences from dose to water emerged for some tissues: cortical bone absorbed about four times more than water, while adipose tissue received about 45% less. These variations were affected by atomic number more than density. Radiance results show strong agreement with penEasy simulations. Furthermore, it was observed that IORT absorbed doses can fluctuate by ± 50% due to heterogeneities surrounding the applicator. This highlights that the prescribed dose and the absorbed dose in the applicator surface do not necessarily coincide in non-water tissues, emphasizing the critical need to account for specific tissue characteristics during treatment planning.
Vibration-controlled transient elastography (VCTE)-based liver stiffness measurement (LSM) is widely used for non-invasive assessment of liver fibrosis and portal hypertension in chronic liver disease. In daily practice, LSM values are often interpreted using etiology-specific fibrosis cut-offs embedded in device software. However, an increasing proportion of patients now present with mixed liver disease etiologies, particularly combinations of metabolic-associated steatotic liver disease (MASLD) with viral or alcohol-related liver disease. In such patients, applying singleetiology cut-offs may lead to misclassification of fibrosis stage and portal hypertension risk. We highlight the limitations of this approach and argue that LSM should be interpreted within a broader clinical context, integrating platelet count, biochemical markers, and validated risk-stratification algorithms rather than relying solely on fibrosis staging tables.
In recent decades, thousands of research articles on neurodegenerative diseases (NDs) have been published. Retinoic acid and its analogues play crucial roles in biological processes such as cell proliferation, differentiation, and apoptosis through their interaction with retinoic acid receptors (RARs). While the involvement of RARs in NDs has attracted increasing interest, a further understanding of the current state and future trajectories of RARs research within this field needs to be explored. This study aims to provide a systematic overview through bibliometric and visual analysis. Original research and review articles concerning RARs in NDs were systematically retrieved from 3 databases: Web of Science Core Collection, Scopus, and PubMed. Subsequent statistical analysis and graphical representation of data on country, institution, authorship, journal, and key terms were conducted using advanced software like VOSviewer, CiteSpace, and the bibliometric toolbox within the R programming language. A total of 1094 articles were included in the analysis, with the United States leading in both publication output (n = 254) and total citations (TC = 17,102), followed by China and Germany. The United States also demonstrated the highest total link strength (90), indicating its central role in international collaborations. The University of California System was the most prolific institution. Keyword analysis revealed core research themes including "retinoic acid," "neurodegeneration," "neuroinflammation," "oxidative stress," and "neuronal differentiation," with recent shifts toward mechanisms involving microglia, the blood-brain barrier, and translational models. Research on RARs in NDs represents a dynamically growing and interdisciplinary field. The USA has contributed most substantially to the literature, underscoring the importance of international and institutional collaboration. Current and emerging research hotspots focus on intracellular calcium, cancer, tau protein, and inflammation, highlighting pathways with therapeutic potential. Future studies should further elucidate molecular mechanisms, integrate advanced technologies such as single-cell sequencing, and accelerate the translation of RAR-related findings into clinical applications.
The European ready meals market is growing, with increased demand for convenient, minimally processed foods. Refrigerated processed foods of extended durability (REPFEDs) rely on mild heat treatments and chilled storage, which may allow survival of non-proteolytic Clostridium botulinum, a pathogen capable of producing botulinum neurotoxin at low temperatures. The objective of this study was to investigate combinations of mild heat-treatment conditions (below 90°C for 10 min) and mild acidic conditions (pH above 5) which may prevent the outgrowth, namely the inhibition, of non-proteolytic C. botulinum in chilled foods. This study used a probabilistic model integrating literature data, previous predictive models, realistic domestic storage conditions of chilled temperatures and time of consumption. The model was implemented in R software with variability and uncertainty separated. Results indicated that a heat treatment of 85 °C for 18 min led to a time before outgrowth of 104 days (95% uncertainty interval: 76-156 days). In this specific process and formulation condition, the probability of inhibition for a product having a Use-by-Date of 28 days was estimated at 0.06% (95% uncertainty interval 0.00% - 0.4%). That corresponded to a level of inhibition of 3.2 log (1/0.0006) CFU/g. Similarly, a heat-treatment of 84°C for 10 min combined with a pH of 6.4, or, a heat-treatment of 87°C for 10 min at pH 6.6 enabled to reach 3 log CFU/g of spore outgrowth inhibition. These findings help to design safe REPFEDs under mild thermal treatment and pH, considering realistic domestic storage conditions. The study illustrates also the added value of modelling approach to capitalize on existing literature information.
Based on the local context in China, this study systematically reviews and explores the prevalence of social frailty among community-dwelling older adults in China and its potential influencing factors. A systematic search was conducted in databases including CNKI, VIP, Wanfang Data, the Chinese Biomedical Literature Database, PubMed, the Cochrane Library, Web of Science, and Embase, covering the period from the inception of each database to November 9, 2025. Two researchers independently performed the systematic literature search, data extraction, and article quality assessment. Meta-analysis was conducted using Stata 15.1 software, incorporating cross-sectional and cohort studies; a random-effects model was used to calculate the pooled prevalence of social frailty and pre-frailty; odds ratios (OR) and 95% confidence intervals (CI) were used to assess associated influencing factors; the I2statistic was used to assess heterogeneity, and subgroup analysis and meta-regression were performed. An initial search identified 5,488 articles; after screening, a total of 24 studies (n = 242,591) were ultimately included. The random-effects model showed that the pooled prevalence of social frailty among community-dwelling older adults in China was 25.0% (95% CI: 19.4%-31.0%, I2 = 99.47%, P < 0.001),and the prevalence of pre-social frailty was 42.0% (95% CI: 37.6%-46.3%, I2 = 94.80%, P < 0.001). Gender (female), advanced age (≥ 85 years), depression, physical frailty, housing satisfaction, marital status, and physical frailty were significantly associated with the risk of social frailty (OR: 1.36-4.15). Pre-social frailty and social frailty are common health challenges faced by community-dwelling older adults in China. Recent data indicate that the prevalence of these conditions remains high; although the prevalence is the very high heterogeneity and should be interpreted with caution, it nevertheless underscores the necessity and urgency of implementing effective interventions. Early identification and intervention for individuals at risk of social frailty are of critical importance for advancing the Healthy China strategy and achieving the goals of active aging. CRD420251246136.
Warming eye masks, provide relief from symptoms of dry eye associated with meibomian gland disease along with other related eye conditions such as blepharitis, hordeolum and meibomian cysts. Certain eye mask designs use head straps to potentially improve mask retention on the face and heat transfer to the eyelids. Straps may increase pressure on the eye, the chance of tissue damage from direct heating, or pose a vision hazard for the user if they move around with the mask in place. This study investigated whether the presence of a strap clinically influences the performance of such eye masks. The surface temperature decline of a Blepha EyeBag® eye mask (Théa Pharmaceuticals Limited,UK) placed on the facial area of a composite manikin head was measured with a thermographer following heating in a domestic microwave for 30, 45 and 60 s at a 800mw settings. Thermographic images were analyzed based on scale intensity using ImageJ software, and variations in facial temperature were plotted. Using a strap significantly (F = 40.451, p < 0.001) decreased the temperature of the manikin upper eyelid by on average 1.4 ± 1.9 °C and lower eyelid by 2.5 ± 2.2 °C. The upper and lower eyelids heated to a similar temperature (on average 31.1 ± 5.1 °C vs 31.2 ± 5.4 °C, respectively; F = 0.064, p = 0.805), with temperate systematically increasing with Blepha EyeBag® heating time (F = 74.027, p < 0.001). The temperature dropped with time following heating (F = 56.483, p < 0.001) in a similar manner with and without the strap in place F = 1.949, p = 0.221). The temperature transference to the eyelid surfaces was higher without the strap (on average by 1.9 ± 2.2 °C) possibly because the mask could conform to the contours of the face better when it wasn't pulled tight.