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PubMed2026

Flap Versus Tunneling for Horizontal Ridge Augmentation With FDBA and i-PRF: A Randomized Controlled Clinical Trial.

AIM: This study evaluated the efficacy of conventional flap and tunneling techniques for horizontal alveolar ridge augmentation using freeze-dried bone allograft (FDBA) particles combined with injectable platelet-rich fibrin (i-PRF). MATERIALS AND METHODS: Forty-five patients were randomly allocated to one of three groups (n = 15 each): conventional flap (CF), tunneling with membrane (TM), or tunneling without membrane (TnM). Preoperative ridge width was measured via cone beam computed tomography (CBCT). All augmentation procedures incorporated FDBA and i-PRF; an absorbable collagen membrane was applied in the CF and TM groups. Follow-up assessments, including CBCT imaging and histomorphometric analysis, were conducted 6 months postoperatively. For normally distributed data, ANOVA with Tukey's post hoc test and paired samples t-test were applied. Non-normally distributed data were analyzed using Kruskal-Wallis, Mann-Whitney U, and Wilcoxon signed-rank tests. RESULTS: Statistical analysis was performed on 43 patients. All groups demonstrated an increase in ridge width after 6 months. At the 2 mm level, the mean width gain was 1.28 mm (95% CI: 0.17 to 2.40) in the TM group, 2.85 mm (95% CI: 1.80 to 3.89) in the TnM group, and 1.95 mm (95% CI: 1.07 to 2.83) in the CF group. However, statistical analysis revealed no significant intergroup variation (p > 0.05). Histomorphometric assessments similarly demonstrated comparable outcomes across all groups, with no statistically significant differences observed (p > 0.05). CONCLUSION: Within the limitations of this study, the tunneling technique, regardless of membrane use, appears to be a clinically viable alternative to the conventional flap method for horizontal alveolar ridge augmentation. However, further studies with longer follow-up periods are required to substantiate these findings. TRIAL REGISTRATION: irct.behdasht.gov.ir identifier: IRCT 20101204005305N21.

Humans↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

The radiographic effect of cage subsidence on neuroforamina after anterior cervical discectomy and fusion.

STUDY DESIGN: Retrospective Cohort Study. OBJECTIVE: The objective of this study is to investigate the effect of cage subsidence on neuroforaminal area after anterior cervical discectomy and fusion (ACDF) utilizing computed tomography (CT). SUMMARY OF BACKGROUND DATA: Restoration of disc height via implantation of an interbody device provides an indirect decompression of the cervical neuroforamina. Interbody cage subsidence is a potential postoperative occurrence, but the effect of this on neuroforaminal area has yet to be characterized. METHODS: A retrospective review was conducted of patients who underwent one- to four-levels of ACDF utilizing an interbody device with anterior plating. Cage subsidence, neuroforaminal area, height and width were measured on CT scans preoperatively and at least 6 months postoperatively. Levels with a cumulative sum of cranial and caudal subsidence greater than 4 mm were classified as severely subsided, while levels with cumulative subsidence less than 4 mm were classified as non-severely subsided. RESULTS: A total of 83 patients (151 levels) were included in this retrospective analysis. Average endplate subsidence was 3.2 ± 1.9 mm. Non-severely subsided levels demonstrated a greater perioperative increase in neuroforaminal area (7.9 vs 2.1 mm2, p < 0.001), neuroforaminal height (1.1 vs 0.4 mm, p < 0.001) and neuroforaminal width (0.7 vs 0.1 mm, p < 0.001) compared to severely subsided levels. Interbody subsidence significantly predicted a decreased change in neuroforaminal height, width and area (p < 0.001). Severe subsidence was associated with an increased rate of pseudarthrosis, but similar reoperation rates and recurrent neurologic deficits between the two groups. CONCLUSIONS: Severe subsidence of interbody cages after an ACDF was associated with a decreased perioperative change in neuroforaminal dimensions. This decrease in the size of the neuroforamen may reduce the effect of indirect decompression of the nerve root.

Humans↗

PubMed2026

Imaging techniques for assessing the hand in systemic sclerosis: a systematic review.

BACKGROUND: Systemic sclerosis (SSc) is a rare autoimmune connective tissue disease frequently associated with hand involvement, leading to significant functional impairment. Imaging techniques provide unique opportunities to visualize and quantify structural and functional abnormalities of the hand, supporting diagnosis, monitoring, and treatment evaluation. This systematic review summarizes the imaging techniques used in SSc. METHODS: A systematic search of PubMed and Embase was conducted. Eligible studies included original research articles in English that applied or evaluated imaging techniques of the hands in SSc, published after 2000. Ultrasound and nailfold capillaroscopy were excluded, given their established use. Screening was performed independently by two authors. Findings were synthesized by clinical manifestations, study quality was assessed using the QUADAS-2 tool. RESULTS: Sixty-one studies met the inclusion criteria. In total, 25 distinct imaging techniques were identified, enabling assessment of various hand structures, including vascular involvement, inflammation, fibrosis, calcifications, erosions, and bone marrow edema. Vascular imaging was most extensively studied, particularly in the context of Raynaud's phenomenon and digital ischemia, with multiple techniques demonstrating impaired perfusion and altered thermoregulatory responses. MRI consistently detected subclinical inflammatory and erosive changes of joints and soft tissues,. CT-based techniques provided detailed assessment of calcinosis cutis, while optical and photoacoustic methods showed promise for quantifying skin fibrosis. CONCLUSION: Imaging techniques provide valuable, complementary insights into hand involvement in SSc, often revealing subclinical disease. Despite promising results, limited standardization and longitudinal validation currently restrict clinical implementation. Future studies should focus on harmonizing protocols and validating against clinically meaningful outcomes.

Humans↗

PubMed2026

The prevalence of isthmic and degenerative lumbar spondylolisthesis: an analysis of 1376 patients.

INTRODUCTION: Typically, spondylolisthesis is an asymptomatic spinal condition that is often captured accidently in radiographic studies. The limited studies reviewing incidence primarily used lateral radiographs, which lack the granularity of advanced imaging. In response, computed tomography (CT) has been recommended to enhance the accuracy of spondylolisthesis diagnosis (degenerative versus isthmic). In the present study, we sought to determine the prevalence of isthmic and degenerative spondylolisthesis using CT imaging. METHODS: We conducted a retrospective study of 1,680 patients who underwent abdominal/pelvic CT scans at a single level-1 trauma center from January 1, 2017, to January 31, 2017. RESULTS: A total of 1,680 CT scans were screened, of which 1,376 patient scans met the inclusion criteria of having undergone complete imaging (axial and sagittal images). The average age of the study population was 57.1 (standard deviation, 18.7) years; 51.1% were female, and 83.2% were Caucasian. The prevalence of isthmic spondylolisthesis was 5.4% (n = 71): 3.6% of cases were at the L5-S1 level, 2.1% were at the L4-L5 level, and 0.6% were at the L3-L4 level. The female-to-male ratio was 0.73:1. The prevalence of degenerative spondylolisthesis was higher at 21.5% (n = 285), and the level most commonly affected was L4-L5 (11.8%), followed by L5-S1 (9.7%) and L3-L4 (4.6%). The female-to-male ratio was 1.3:1. There was a higher prevalence of degenerative spondylolisthesis in women at L4-L5 (51.2% vs. 35.6%; P < 0.001). CONCLUSION: We found that degenerative spondylolisthesis was more prevalent, occurring primarily in older women, between the L4-L5 vertebrae. On the other hand, isthmic spondylolisthesis more commonly occurred within male patients between the L5-S1 vertebrae. Our study is one of the first to recognize a high rate of degenerative spondylolisthesis within the L5-S1 region, highlighting the utility of CT scan to visualize spinal translation. LEVEL OF EVIDENCE: IV.

Humans↗

PubMed2026

A conserved distal-tail helical extension defines a tailspike attachment architecture in Gram-negative siphophages.

Rapid growth of bacteriophage genome collections has outpaced functional annotation of tail-tip proteins, limiting comparative analysis of host-recognition structures. Starting from a shared distal-tail gene organization in the Salmonella phages 9NA and Jersey, I developed a morphogenetic bioinformatic framework integrating gene synteny, sequence comparison, profile hidden Markov model (HMM) screening, structural evidence, structure-aware searching, and AlphaFold modeling. Comparison with the experimentally characterized lambda and Sf11 tail assemblies identified a predominantly alpha-helical C-terminal extension of the distal-tail (DT) protein associated with tailspike attachment, termed the distal-tail helical extension (DT-helix). Screening 541,986 proteins from 5167 complete NCBI RefSeq tailed-phage genomes, followed by evidence-based evaluation of sequence, genomic context, and structural architecture, identified 165 curated DT-helical-extension-associated phages. Their DT proteins segregated into six sequence groups. In the four principal multi-member groups, cognate tailspikes showed group-specific conservation in proximal N-terminal regions but substantially greater downstream diversity, consistent with sequence constraint at the DT-tailspike attachment boundary. A complementary ProstT5/Foldseek search supported the established groups but revealed no convincing additional highly divergent family. Together with the experimentally characterized Sf11 attachment interface, these findings define a recurrent morphogenetic architecture linking conserved distal-tail scaffolds to more variable receptor-binding proteins across siphophages infecting Gram-negative bacteria. Although universal exchangeability is not established, the identified scaffold-receptor-binding boundaries provide a framework for molecular characterization and rational phage engineering. Accession-level information for the 165 curated phages is available through PhageTailDB.

Viral Tail Proteins↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

The impact of absolute change in tibiofemoral morphology on patient reported outcome measures post total knee arthroplasty.

BACKGROUND: Reconstructing knee morphology and alignment is important for outcomes post total knee arthroplasty (TKA). Personalised alignment strategies are proposed to improve outcomes by replicating native alignment. However, how change in morphology affects patient outcomes is unclear. This study aimed to investigate the relationship between absolute change in morphological measures post-TKA and patient reported outcome measures (PROMs). METHOD: An observational analysis of a randomised clinical trial was conducted. Participants received preoperative and postoperative CT scans and completed PROMs at six-months post-TKA. Absolute change in hip-knee-ankle angle, medial proximal tibial angle, lateral distal femoral angle, non-weightbearing joint line convergence angle, tibial and femoral rotation, and posterior tibial slope (PTS) were calculated. PROMs included visual analogue scales of pain and satisfaction (0-100), Oxford Knee Score, Forgotten Joint Score, and the Kujala Score. Regression and principal component (PCA) analyses investigated relationships between PROMs and change in morphology. RESULTS: Sixty-one participants were included for analysis (61% women, age 66.9 ± 9.1 [mean ± SD] years, BMI 32.8 ± 6.8 kg/m2). The PCA demonstrated coronal, axial, and sagittal plane measures were interdependent, with over 65% of variability driven by change in tibial rotation (PC1) and the PTS (PC2). The regression analysis showed no relationships between morphological change and PROMs postoperatively. CONCLUSION: Tibiofemoral morphology was interrelated across coronal, axial, and sagittal planes. However, this study suggests absolute morphological change had minimal impact upon PROMs at six-months post-TKA. Future research should clearly distinguish between osteoarthritic versus prearthritic alignment and consider the influence of soft-tissue releases upon PROMs.

Humans↗

PubMed2026

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-κB, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans↗

PubMed2026

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Stage shift, histological differentiation, and survival patterns of lung squamous cell carcinoma versus adenocarcinoma in low-dose CT screening.

BACKGROUND: Whether LDCT-associated stage shift translates into similar survival patterns across lung cancer histologies remains uncertain. We compared stage shift, histological differentiation, tumor characteristics, and survival between lung squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD) in the National Lung Screening Trial. METHODS: Among participants diagnosed with LUSC or LUAD, stage distribution and histological differentiation were compared between LDCT and chest X-ray (CXR) arms. Survival among diagnosed cases was measured from randomization. Multivariable models tested screening arm-by-histology interactions. Screen-detected LDCT tumors were compared by histology. RESULTS: During 6.5 years of median follow-up, 498 LUAD and 249 LUSC cases were diagnosed in the LDCT arm, and 374 and 212, respectively, were diagnosed in the CXR arm. LDCT was associated with higher odds of stage I disease for LUAD (adjusted odds ratio [aOR], 2.48; 95% CI 1.88-3.28) and LUSC (aOR, 1.71; 95% CI 1.17-2.48), without significant interaction (P = 0.116). LDCT was associated with lower hazard of lung cancer-specific death among diagnosed LUAD cases (adjusted hazard ratio [aHR], 0.54; 95% CI 0.43-0.66), but not among diagnosed LUSC cases (aHR, 1.04; 95% CI 0.78-1.39; P for interaction<0.001). LUSC had lower screening sensitivity, more frequent detection in annual screening rounds, greater prediagnostic tumor size increase, and fewer well-differentiated stage I tumors than LUAD. CONCLUSION: LDCT was associated with stage shift for both subtypes, but favorable survival patterns among diagnosed cases were mainly observed for LUAD. Lower screening sensitivity, greater prediagnostic tumor size increase, and poorer histological differentiation may help explain why stage shift did not translate into similar survival patterns for LUSC. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00047385.

Humans↗

PubMed2026

Safety and efficacy of distal versus conventional radial artery cannulation for invasive blood pressure monitoring: a systematic review and meta-analysis.

To compare the safety and effectiveness of distal radial artery (DRA) versus conventional radial artery (CRA) catheterization for invasive arterial blood pressure monitoring. This meta-analysis followed PRISMA guidelines. Randomized controlled trials published up to December 30, 2025 were systematically searched in PubMed, Embase, Web of Science, the Cochrane Library, CINAHL, CNKI, Wanfang, VIP, and SinoMed. Two reviewers independently screened studies, extracted data, and assessed risk of bias. Meta-analyses were conducted using Review Manager 5.4 and Stata 18.0, and evidence quality was evaluated with the GRADE system. 12 randomized controlled trials (RCTs) involving 1,790 participants were included. For the primary outcomes, compared with CRA, DRA was associated with lower incidences of haematoma (RR = 0.42, 95% CI: 0.24-0.73), catheter blockage (RR = 0.33, 95% CI: 0.14-0.81), and bleeding (RR = 0.25, 95% CI: 0.11-0.59), but a longer catheter insertion time (MD = 26.89, 95% CI: 5.28-48.50). For the secondary outcomes, DRA was associated with a shorter haemostasis time and reduced waveform instability, with no significant differences in first-attempt success rate or pain scores. Subgroup analysis showed a higher first-attempt success rate in patients aged ≤ 65 years (RR = 1.14, 95% CI: 1.02-1.28). DRA catheterization for invasive arterial blood pressure monitoring appears to be associated with fewer complications and more stable arterial waveform acquisition than CRA catheterization, despite a longer insertion time. DRA may represent a feasible alternative in surgical and intensive care settings; however, further high-quality studies are needed to confirm its long-term safety and generalizability.

Humans↗

PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Ablative radiotherapy in castration-resistant prostate cancer.

OBJECTIVE: To prove the oncological benefit of ablative radiotherapy in patients with up to five metastases from castration-resistant prostate cancer (CRPC) a single-centre randomised trial was initiated. PATIENTS AND METHODS: This monocentric, randomised, phase II clinical trial enrolled patients with up to five prostate-specific membrane antigen-positive bone or lymph node metastases developing prostate-specific antigen (PSA) progression during androgen deprivation (ADT) or ADT and androgen-receptor targeted therapy. Participants were randomised (2:1) to receive metastasis-directed therapy (MDT) or observation (OBS) without changing systemic therapy. The primary endpoint was the proportion of patients having PSA progression within 1 year, with statistical analyses conducted using intention-to-treat principles. Here, results of a planned interim analysis of the primary endpoint are reported. RESULTS: A total of 30 patients (12 in the observation arm and 18 in the MDT arm) were enrolled, PSA progression within 1 year occurred in 44% of the MDT group vs 75% in the OBS group (P = 0.14, not significant). The median time to PSA progression was significantly longer in the MDT arm (12.4 months) compared to the OBS arm (2.9 months, P = 0.03). The pre-defined criteria to discontinue the study were not met. Limitations include the single-centre design and small sample size at interim analysis. CONCLUSION: This pre-planned interim analysis of the primary endpoint did not meet the discontinuation criteria of the study protocol, suggesting that MDT in oligometastatic CRPC may extend the time to PSA progression without immediate change of systemic therapy. The continuation of the study in a multicentre setting is planned (Institutional funding by the TU Dresden, ClinicalTrials.gov identifier: NCT04141709).

Humans↗