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.
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.
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.
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.
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.
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.
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.
This report uses data from the 2024 National Health Interview Survey (NHIS) to examine the use of prescription medication for mental health and the receipt of counseling or therapy from a mental health professional in the past 12 months among U.S. adults, by selected characteristics. Analyses were conducted using data from the 2024 NHIS. Point estimates and corresponding confidence intervals were calculated using SAS-callable SUDAAN software to account for the survey's complex sample design. Differences between percentages were evaluated using two-sided significance tests at the 0.05 level. A total of 19.3% of adults took medication for their mental health and 14.0% received counseling or therapy from a mental health professional in the past 12 months during 2024. Women were more likely than men to have received either treatment. Adults ages 30-44 were more likely to have taken medication than those ages 65-74 and 75 and older. Adults 75 and older were least likely to have received counseling or therapy. Adults with family incomes less than 100% of the federal poverty level (FPL) were more likely to have taken medication and as likely to have received counseling or therapy than adults with incomes greater than 400% FPL. Adults living in nonmetropolitan areas were most likely to have taken medication and least likely to have received counseling or therapy for their mental health.
The Bonwill triangle, defined by the mandibular incisor (MI) point and the center of right (CR) and left (CL) condyles, which provide a crucial reference for determining craniofacial symmetry and occlusion. Although three-dimensional imaging has enhanced the precision of triangle measurement, few studies have evaluated Bonwill triangle geometry in patients who have undergone orthognathic surgery (OGS). The present study assessed Bonwill triangle geometry in a Taiwanese population by comparing individuals who underwent OGS and those who did not and by analyzing the effects of sex and age on mandibular asymmetry. Cone-beam computed tomography images from 109 adults (54 in the OGS group and 55 in the non-OGS group) were retrospectively analyzed. Three side lengths of the Bonwill triangle (mandibular incisor point to left condyle (MI-CL), mandibular incisor point to right condyle (MI-CR), and right condyle to left condyle (CR-CL)) were measured using Mimics software. Group comparisons and subgroup analyses by sex and age were conducted using independent and paired t tests and Pearson correlation analysis. The OGS group exhibited greater asymmetry in the bilateral side lengths than the non-OGS group did (3.41 ± 2.35 mm vs. 1.69 ± 1.02 mm, p < 0.001), particularly the men in the group (p < 0.001). Additionally, only the men in the OGS group exhibited a negative correlation between age and bilateral side length (r = - 0.480, p = 0.034). CR-CL length did not differ significantly between the OGS and non-OGS groups. The Bonwill triangle can support preoperative mandibular asymmetryassessments. Candidates for OGS, especially men, exhibit greater skeletal asymmetry than non-OGS candidates do, underscoring a need for individualized planning. Future studies evaluating surgical type and long-term outcomes can enhance the clinical applications of the Bonwill triangle in pre-OGS assessments. This retrospective study was approved by the Institutional Review Board of China Medical University Hospital, Taichung, Taiwan (CMUH 114REC2019).
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.
To investigate the predictors of anatomical response in patients with diabetic macular edema (DME) following anti-vascular endothelial growth factor (anti-VEGF) therapy and establish a nomogram model for predicting the probability of anatomical response. This study enrolled 200 DME patients treated with anti-VEGF regimen. Based on the reduction rate of central macular thickness (CMT) following treatment, patients were classified into an anatomical weak responder group (CMT reduction < 20%) and an anatomical responder group (CMT reduction ≥ 20%). Baseline clinical data and OCT biomarkers were analyzed with multivariate logistic regression. A nomogram model was constructed by using R software. Bootstrapping was used for model validation, receiver operating characteristic (ROC) curve and calibration curve were used for evaluating the discrimination and calibration of prediction model, and decision analysis curve (DCA) was used for evaluating the practicality of model. Predictors for anatomical response in DME patients are serum creatinine (Scr), CMT, photoreceptor outer segment length (PROSL), and cystoid macular edema (CME) presence as independent variables. The nomogram prediction model based on the above four predictors had good representativeness (Bootstrap method: precision: 0.820), differentiation [the area under curve (AUC) value: 0.819], and the DCA analysis showed that the prediction model, whose threshold probability was in the range of 0 to 1, had clinical practical value. The anatomical response to anti-VEGF treatment for DME is independently associated with baseline Scr, CMT, PROSL, and the presence of CME.
Transgenic crops undergo rigorous safety assessments prior to commercialization, with molecular characterization serving as a critical component of regulatory review. This process establishes the identity, copy number, sequence integrity, absence of unintended foreign DNA, and insert stability across breeding generations. While whole-genome sequencing (WGS) has emerged as a powerful alternative to Southern blotting, the lack of accessible interpretation frameworks can be an entry barrier to those who wish to understand this modernized experimental setup. We developed an analytical workflow based on mapped-read signatures to characterize T-DNA (transfer DNA) insertions using short-read WGS data. Simulated Illumina paired-end datasets representing diverse transformation outcomes were generated and analyzed to define five informative read classes, which when observed mapped to a reference transformation construct provide distinct signatures indicating transformation outcomes. These signatures were applied to identify insertion boundaries, copy number, structural anomalies, and potential contamination. Mapped-read signatures can reliably distinguish single-copy inserts, multiple insertions, backbone co-integrations, and structural rearrangements, aided by coverage profiles and mate-pair orientations. We present representative examples and a practical interpretation to guide practitioners new to WGS-based molecular characterization and regulators assessing these data. This framework standardizes interpretation of short-read paired-end WGS data for molecular characterization without prescribing specific software. The platform-agnostic approach ensures broad applicability while enhancing transparency in regulatory assessments.
Body composition is emerging as a prognostic biomarker in cancer and may be associated with treatment tolerance, side-effects, and health-related quality of life (HRQoL). It can be measured from imaging routinely acquired during patient care. We evaluated whether body composition metrics were associated with radiotherapy-related side-effects and HRQoL in patients with prostate or lung cancer using a prospective multicentre dataset. Radiotherapy planning computed tomography (CT) scans, patient and disease characteristics, and clinician- and patient-reported side-effects up to 24 months post-treatment were obtained from the REQUITE study. Skeletal muscle and intramuscular adipose tissue were segmented at the L3 and T12 vertebrae for prostate and lung patients respectively using in-house software. Standardised total average toxicity scores captured composite acute and late clinician- and patient-reported side-effects and HRQoL. Gradient boosted machine models were developed for all endpoints with and without body composition variables. Predictor importance rankings and model performance (root mean squared error (RMSE)) were assessed. 279 lung and 848 prostate patients were available for analysis. Body composition variables were ranked in the top five most important variables for 9 of 12 endpoints. Body composition variables were ranked higher than body mass index for 9 of 12 endpoints. Adding body composition variables was associated with statistically significant (p < 0.01) but small reductions in apparent/in-sample RMSE across endpoints. Body composition variables were frequently ranked among important predictors of radiotherapy-related side-effects and HRQoL, but their incremental improvement in apparent model fit was small. These findings suggest that CT-derived body composition may warrant further investigation as an exploratory imaging biomarker, but external validation and demonstration of clinically meaningful incremental value are required before clinical implementation.
Men who have sex with men (MSM) have an elevated risk of adverse outcomes associated with cannabis use. Many studies have been conducted globally; however, there is a lack of research regarding the existing status and factors associated with cannabis use among MSM in Nepal. Therefore, this study aimed to examine the characteristics and factors associated with cannabis use among MSM in Nepal. A cross-sectional respondent driven survey was conducted among MSM in Kathmandu Valley, Nepal between October and December 2022. Overall proportions were weighted in respondent driven sampling analyst software, and 95% confidence intervals (CIs) were calculated. Bivariate and multivariable logistic regression analyses were used to evaluate independent correlates of cannabis use in the last 6 months. Among 250 participants, 27.3% of them used cannabis at least once in their lifetime, and 15.6% had used it within the last 6 months. Older MSM were less likely to have used cannabis (adjusted odds ratio [aOR]: 0.8, 95% CI: 0.7-0.9). Participants who were single (aOR: 21.5; 95% CI: 2.6-175.6), detained at least once by the police (aOR: 11.4; 95% CI: 2.2-58.4), and smoked tobacco daily (aOR: 4.6; 95% CI: 1.2-17.9) had higher odds of cannabis use. Participants who had seen a doctor in the last 6 months (aOR: 0.2; 95% CI: 0.1-0.6) and had trusted healthcare provider (aOR: 0.1; 95% CI: 0.01-0.2) were less likely to use cannabis. Given the known negative health effects of cannabis use such as increased risk of HIV transmission, polydrug use, and heightened sexual health risks, special attention should be directed toward MSM who are young, single, and daily smokers. Participants who had seen a doctor in the last 6 months and had trusted healthcare provider were less likely to use cannabis. This highlights the importance of connecting individuals to regular healthcare services and building trust with providers.
This study aimed to examine the training needs for competency development of novice nurse educators using the Nursing Professional Development (NPD) practice model, with the purpose of providing evidence to inform training program development. A descriptive qualitative approach was applied in accordance with the NPD practice model. Between April and May 2025, 29 nurse educators from a grade A tertiary teaching hospital were recruited using purposive sampling. Participants were organized into four focus groups and engaged in semi-structured interviews. Data were analyzed using directed content analysis with the assistance of NVivo 12.0 software. The training needs of novice nurse educators were classified into three dimensions based on the NPD model. Within the input dimension, adaptation to teaching environments and analysis of learner needs were identified as key requirements for improving role clarity. Within the process dimension, there was a strong demand for systematic instruction in teaching theory, curriculum design, and resource development, as well as structured mentorship and communication mechanisms to address challenges related to role overload and limited visibility of outcomes. Within the output dimension, self-innovation and targeted empowerment were identified as necessary to advance team development and transform teaching practice, thereby promoting the integration of organizational culture and professional values. Competency development training for novice nurse educators should align with the seven core role standards of the NPD model and be supported through appropriate pedagogical strategies. This requires the restructuring of resources during the input phase, implementation of multidimensional empowerment during the process phase, and the establishment of scientific evaluation systems during the output phase. These measures support the progression of novice nurse educators into competent NPD practitioners and enhance the overall quality of talent cultivation.
The present study aims to examine the language impairments observed across various stages of Alzheimer's Disease (AD) in Turkish-speaking individuals. The study involved 24 participants diagnosed with AD (12 women, 12 men; mean age = 82.00 ± 6.75) and a control group of 24 healthy adults (12 women, 12 men; mean age = 80.71 ± 8.61). All participants completed the Test Your Memory-Turkish (TYM-TR) and the Aphasia Language Assessment Test (ADD). Data analysis was conducted using SPSS 24 software with descriptive statistics, Spearman's correlation coefficient, and the Mann-Whitney U test. Participants with AD scored lower on the TYM-TR and ADD than healthy participants. A strong positive correlation was observed between scores on the TYM-TR and ADD tests in both participant groups. The test scores decreased as AD stages progressed. This study provides a framework for SLTs to identify AD stages and tailor language interventions accordingly.
Chronic pain is a severe burden affecting 20% of the population worldwide. To develop novel analgesics, in vivo preclinical assessment of the pain threshold is inevitable. Investigation of the nociception in rodents is still challenging, since most of the currently available methods are manually operated. So, the results highly depend on the experience of the examiner and can be significantly biased by subjective human factors. To improve this translational research paradigm, advanced tools are needed in this field. Therefore, the aim of the present study was to develop a new generation automated pain assessment device. In collaboration with Z-Elektronika Ltd., Pécs, Hungary we have designed and validated high-precision automated dynamic plantar aesthesiometer (ADPA) that is suitable for the assessment of mechanonociceptive threshold in rats and mice. It utilizes artificial intelligence (AI) to automatically recognize the animals investigated. The system's software controls the mechanical stimulation of the hindpaws with simultaneous video recording of the nocifensive reaction and analysis of the pain thresholds. The main advantage of ADPA is the automated, computer-controlled induction and evaluation of the pain threshold, increasing the quality, comparability, reproducibility, and objectivity of the results. This device may significantly enhance the accuracy of pain assessment in animal models and contribute to improved preclinical pain research.
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.
Deaths due to lightning strikes are rare but of great forensic importance because of their sudden and fatal nature. This study aimed to evaluate the demographic characteristics, scene findings, and autopsy results of fatal lightning strike cases examined in Kars and Ardahan provinces. This retrospective study included 13 cases of death by lightning strike, identified from 847 autopsies performed in 2 climatically similar provinces between 2019 and 2025 via the National Judicial Network Project (UYAP) database. The research evaluates the victims' demographic data, incident location characteristics, and macroscopic autopsy findings, alongside negative toxicological and histopathological examination results. The data were analyzed using the SPSS software, utilizing descriptive statistical methods such as frequency, percentage distribution, and mean values. Between 2019 and 2025, 1.53% (n = 13) of forensic autopsies in Kars and Ardahan were attributed to lightning strikes, with all cases involving male victims and a mean age of 31.3 years. The majority of cases were shepherds (69.2%), and deaths occurred most frequently in rural pastures during the spring and summer months, particularly in May and June. While all cases exhibited first- and second-degree burns and singed body hair, characteristic Lichtenberg figures were detected in 46.1% of the victims alongside various internal hemorrhages in some instances. Crime scene investigations provided critical diagnostic evidence, including the presence of deceased livestock near the victims and partially burned or torn personal belongings. Lightning-related deaths show a strong association with seasonal, occupational, and environmental factors. Scene investigation and the recognition of Lichtenberg figures play a crucial role in the forensic diagnosis of lightning strike fatalities. Cite this article as: Sancı A, Karaalp E, Baltacı AS, Vural T. Evaluation of lightning strike fatalities: a retrospective autopsy study from 2 centers in eastern Türkiye. Eurasian J Med. 2026, 58(4), 1359, doi: 10.5152/eurasianjmed.2026.261359.
Advanced lower extremity lymphedema is difficult to manage and can lead to significant functional impairment and diminished quality of life. Extirpative (also known as excisional and debulking) surgical procedures offer meaningful volume reduction for patients with advanced disease refractory to conservative management. The objective of this systematic review was to identify the clinical and imaging criteria used to determine candidacy for excisional surgery (i.e. Charles and modified Homan procedures) in adults with lower extremity lymphedema and to report the surgical outcomes observed across the included studies. A systematic search of PubMed, Embase and Cochrane Library was conducted by an expert medical librarian. The search yielded 3,916 articles. Inclusion criteria involved randomized controlled trials, cohort studies, and case series that reported on excisional surgical procedures for adults with lower extremity lymphedema and described clinical or imaging criteria for surgical candidacy. Studies that did not involve lower extremity lymphedema patients were excluded. Screening, full text review, and data extraction were performed using Covidence software with standardized data extraction templates. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines. Five studies were included in this systematic review. There was a total of 933 patients across all studies. The five included studies were one systematic review, three retrospective cohorts or case series, and one small case series. Five clinical criteria for surgical candidacy were identified in this review: failure of conservative management, advanced clinical staging (ISL III or equivalent), functional impairment, skin changes, and recurrent infections. No imaging was used to determine surgical candidacy for excisional surgery alone in lower extremity lymphedema. The quality of life was not formally measured with validated instruments in any study. This systematic review reveals a fundamental absence of validated, evidence-based selection criteria for extirpative surgery in lower extremity lymphedema. The current selection process is entirely surgeon-dependent, institution-specific, and non-standardized. This represents a critical barrier to the development of clinical guidelines and equitable patient care. No existing evidence supports the superiority of any particular set of selection criteria over another.