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Positive conversion of latent tuberculosis screening in patients with inflammatory bowel disease on antitumor necrosis factor alpha drugs: a systematic review and meta-analysis.

Inflammatory bowel disease (IBD) patients undergoing antitumor necrosis factor-alpha (anti-TNF) therapy are at increased risk of developing tuberculosis (TB), making screening before anti-TNF initiation mandatory. Repeated screening during treatment is not yet recommended because of a lack of studies to support this practice. We aimed to determine the proportion of patients who develop latent TB during anti-TNF therapy. We systematically searched studies from MEDLINE, Embase, and Lilacs, and performed a single-arm meta-analysis investigating the positive conversion rate in IBD patients under anti-TNF therapy with previous negative TB screening. We calculated the combined proportion with 95% confidence interval, using the random-effects model. A P value less than 0.05 was considered statistically significant for subgroup differences. We included 13 studies from nine countries with 1153 patients. The overall positive conversion rate was 9.20%. Portugal had 18.01% of positive conversion, Spain 4.51%, and the USA 1.11%. Tests for subgroup differences were statistically significant for subgroup analysis by country and consistency of test used (performig same test as baseline). Subgroup analyses by continent, study design, or specific test (tuberculin skin test or interferon-gamma release assay) showed no statistical difference. Meta-regression analysis showed a significant positive association between positive conversion and TB incidence. In conclusion, IBD patients on anti-TNF therapy can have a positive conversion rate of 9.20%. Higher conversion rates were seen in European and Asian studies compared with those in the Americas (particularly the USA). TB prevention strategies should, therefore, be individualized and based on geographic location and risk factors.

Humans

Hot vs cold knife for endoscopic ablation of posterior urethral valves: a systematic review by the EAU-YAU paediatric urology working group.

INTRODUCTION: Posterior urethral valves (PUV) are the most frequent cause of congenital lower urinary tract obstruction in males. Despite early surgical ablation, up to 22% of patients develop chronic kidney disease and 11% progress to end-stage renal disease. Multiple endoscopic modalities have been described for valve ablation but the optimal technique remains uncertain. This systematic review aims to determine whether cold or hot knife ablation provides superior effectiveness for primary endoscopic treatment of PUV in a single surgical session. MATERIAL AND METHODS: A systematic search of PubMed and Embase databases was conducted to identify studies comparing cold and hot knife techniques for endoscopic ablation of PUV in children, covering all publications up to December 2025. The review was performed in accordance with PRISMA 2020 guidelines and was prospectively registered in PROSPERO (ID CRD420251180556). Original studies including patients <18 years who underwent primary valve ablation with postoperative cystoscopy or VCUG and &#x2265;6 months of follow-up were included. Quality assessment was done using RoB 2.0 for randomized trials and MINORS for observational studies. RESULTS: A total of 1581 studies were identified, of which 26 met the inclusion criteria, comprising one randomized controlled trial, five prospective, and 20 retrospective studies constituting a sum of 1725 paediatric patients. The overall methodological quality of included studies was moderate, with marked heterogeneity in design, follow-up duration, and outcome reporting, limiting direct comparisons across series. Thus statistical analysis was not possible. Of these, 829 (48.1%) underwent cold valve ablation and 896 (51.9%) underwent hot ablation techniques. Within the cold group, most patients were treated with a cold knife (80.2%), followed by balloon dilatation (7%), the Mohan valvotome (6.5%), cold hook (5%), and, rarely, a modified venous valvulotome (1.3%). Among hot techniques, 32.8% of procedures were performed by electro-fulguration with a resectoscope, 29.4% using a Bugbee electrode, 23.8% with a hook electrode and 14% with laser-based systems. Follow-up ranged from 6 months to 22 years across studies. Single-session success rates for valve ablation ranged from 22% to 100% in the cold resection group and from 71.4% to 100% in the hot resection group. Reintervention for residual valves was reported in 0%-78% of cold cases and in 0%-28.6% of hot resections. Urethral stricture rates ranged from 0% to 11.1% after cold incision and from 0% to 23.8% after hot techniques. Reporting of postoperative outcomes such as urinary tract infection, incontinence, bladder dysfunction, vesicoureteral reflux (VUR) resolution, hydronephrosis improvement, and renal function varied widely among studies and was assessed using different methodologies. CONCLUSIONS: Both cold and hot ablation techniques for PUV achieved high single-session success rates and low complication rates. Cold resection appeared slightly safer, although this finding should be interpreted cautiously given the heterogeneity and observational nature of the available data.

Humans

Assessing the accuracy and efficiency of an electronic platform for managing childhood illnesses in rural China: A cluster randomized controlled trial.

OBJECTIVES: The Integrated Management of Childhood Illness (IMCI) faces challenges in capacity building and quality control. This trial aims to assess an electronic IMCI (eIMCI) platform in improving the effectiveness and efficiency in disease classification and management by community health workers (CHWs). DESIGN: Cluster randomized controlled trial. SETTING: Rural western China. PARTICIPANTS: 24 CHWs and 72 ill children aged 2 months to 5 years (3 children per CHW). CHWs were randomly assigned to intervention or control groups. INTERVENTIONS: The intervention CHWs received online training and performed disease management using the eIMCI platform featuring integrated training modules and decision-support tools. The control group received traditional face-to-face training and used paper-based IMCI protocols. MAIN OUTCOME MEASURES: Proportion of children correctly diagnosed or classified by CHWs, as determined by a pediatric specialist. Relative risk (RR) between groups was estimated using Poisson Generalized Linear Mixed Models incorporating a random intercept for CHW to account for clustering of children within individual CHWs and adjusting for key covariates at both the CHW and child levels. RESULTS: The intervention group (13 CHWs, 39 children) had a higher rate of correct classification (64.1%) compared to the control group (11 CHWs, 33 children) (39.4%, P&#x2009;=&#x2009;.056). Multivariable regression analysis confirmed this (RR&#x2009;=&#x2009;2.1, 95% CI: 1.5-3.1; P&#x2009;<&#x2009;.001). No significant difference was found in correct treatment rates (38.5% vs. 27.3%, P&#x2009;=&#x2009;.316). Online training reduced time and costs by approximately 80%, though with a slight decrease in post-training evaluation scores. CONCLUSIONS: The eIMCI platform shows potential in enhancing IMCI implementation and significantly reducing the training burden in resource-limited settings. Trial registration: Chinese Clinical Trial Registry: ChiCTR2100042533, https://www.chictr.org.cn/showproj.html?proj=119995.

Humans

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one&#x2011;carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals

Metabolomic and structural signatures of pigmented and non-pigmented Himalayan rice landraces.

BACKGROUND: This study investigated the anti-oxidant properties, starch composition, pasting behavior, structural properties, textural properties and non-targeted metabolomic profiles of pigmented and non-pigmented rice landraces as potential next-generation functional food ingredients. RESULTS: Pigmented rice demonstrated 1.34 times more anti-oxidant activity as compared to non-pigmented rice. Pigmented landraces showcased superior nutritional and functional attributes, including higher total dietary fiber and starch content. Fourier-transform infrared (FTIR) analysis revealed distinct molecular signatures with enhanced peak transmittance, while X-ray diffraction (XRD) indicated greater crystallinity ranging from 36-44.3% in pigmented rice compared with 30-40% in non-pigmented rice, suggesting improved digestibility and processing versatility. Pigmented rice recorded less amylose content hence tended to possess increased adhesiveness values whereas non-pigmented rice revealed greater amylose content hence was coupled with greater hardness values. Field-emission scanning electron microscopy (FE-SEM) images revealed that pigmented rice had densely packed and polygonal starch granules whereas non-pigmented rice had loosely packed starch granules with intergranular voids. Untargeted gas chromatography-mass spectrometry (GC-MS) profiling identified 84 metabolites, including unique compounds such as 3,3-dimethylbutanol and ethanoic acid, along with shared metabolites such as sucrose and linoleic acid, highlighting notable biochemical diversity. Multivariate statistical analyses using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping further differentiated the metabolomic landscapes, with variable importance in the projection (VIP) scores identifying key bioactive contributors. CONCLUSION: Pigmented rice landraces exhibited significant functional and nutritional advantages, making them promising candidates for functional food development and nutritional improvement programs. These findings support their potential role in advancing sustainable and health-oriented food systems. &#xa9; 2026 Society of Chemical Industry.

Oryza

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans

Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases.

PURPOSE: To evaluate whether a cornea-specialized large language model (LLM) enhanced with retrieval-augmented generation (RAG) improves clinicians' diagnostic and management accuracy in complex corneal cases compared to a general-purpose GPT-4o model and unaided clinician performance. METHODS: This prospective, randomized, masked evaluation study involved three cornea trainees who each independently reviewed 39 real-world corneal cases under three experimental conditions: unaided, GPT-4o-assisted, and assisted by a cornea-specialized GPT-4o model. The cornea-specialized model was constructed by embedding over 200 publicly available Wikipedia articles into GPT-4o's RAG framework. Participants provided open-ended diagnoses and selected the next-step management options (multiple choice). They were allowed up to three GPT-4o queries per case, and the AI-assisted arms were randomized to minimize bias. Accuracy for both tasks was compared against expert reference standards using McNemar's test. RESULTS: Diagnostic accuracy was 48.7%, 20.5%, and 38.5% unaided, improving to 69.2%, 46.2%, and 59.0% with general GPT-4o (p<0.04). The cornea-specialized GPT-4o further improved accuracy to 71.8%, 48.7%, and 74.4%, with improvements over unaided performance for all clinicians (p<0.01). For next-step decisions, unaided accuracy was 76.9%, 87.2%, and 59.0%. With the specialized model, Ophthalmologist 3 improved to 71.8% (p<0.05), Ophthalmologist 1 remained high at 82.1%, and Ophthalmologist 2 declined to 64.1% (p<0.05). CONCLUSIONS: A cornea-specialized LLM enhanced with RAG improved diagnostic accuracy in complex corneal cases, particularly among clinicians with lower baseline performance. Effects on management accuracy were inconsistent. Future studies should explore the use of open-ended management tasks and examine whether smaller, curated retrieval corpora yield better model performance.

Humans

Maternal disease control and pregnancy outcomes with anti-CD20 therapy versus natalizumab in multiple sclerosis: a systematic review.

BACKGROUND: Management of multiple sclerosis (MS) during pregnancy requires balancing maternal disease control with fetal safety. Among high-efficacy disease-modifying therapies, anti-CD20 monoclonal antibodies and natalizumab are commonly used in women with active disease, yet their comparative effectiveness and safety during pregnancy remain incompletely defined. This systematic review evaluated maternal disease activity and pregnancy-related outcomes associated with anti-CD20 exposure compared with natalizumab in pregnant women with MS. METHODS: PubMed/MEDLINE, Web of Science, Scopus, and the Cochrane Library were searched from inception through February 2026. Eligible studies included pregnant women with MS exposed to anti-CD20 before or during pregnancy and reporting maternal disease activity compared to natalizumab. RESULTS: Seven studies were included, comprising six observational cohort studies and one pharmacovigilance disproportionality analysis. Across studies, anti-CD20 exposure was consistently associated with lower relapse activity than natalizumab, particularly in the postpartum period. Anti-CD20 strategies were also associated with markedly lower postpartum MRI activity and more favorable disability-related outcomes where reported. Meta-analysis of three studies demonstrated a significant reduction in postpartum MRI activity with anti-CD20 therapy compared with natalizumab (RR 0.06, 95% CI 0.02-0.24; I&#xb2; = 0%). No clear increase in major congenital anomalies was identified, although some data suggested higher odds of small for gestational age and maternal antibiotic use with anti-CD20 exposure. CONCLUSIONS: Anti-CD20 therapy was associated with lower maternal disease activity than natalizumab during pregnancy, especially for relapse prevention and postpartum MRI suppression. However, evidence regarding fetal and neonatal safety remains limited, warranting cautious individualized treatment decisions and further comparative research.

Humans

Dissemination of blaKPC-3-harbouring Klebsiella pneumoniae across ST48 and ST628 in multiple healthcare facilities in the Republic of Korea.

Klebsiella pneumoniae carbapenemase-3 (KPC-3) remains rare in South Korea, where KPC-2 is the dominant carbapenemase, making the repeated detection of a concentrated blaKPC-3 signal over five years notable. We performed genomic analyses of blaKPC-3-harbouring K. pneumoniae from a regional healthcare network. Two chromosomally distinct lineages with concordant capsule loci (ST628/KL15 and ST48/KL62) presented multidrug-resistant phenotypes, and the virulence-associated loci were confined to ST48. Single-nucleotide polymorphism (SNP) analyses revealed near-clonal relatedness within lineages, with 0-38 pairwise SNPs among ST628 isolates and 8 SNPs between the two ST48 isolates. Core-genome multilocus sequence typing (cgMLST) supported this structure, as ST628 isolates were assigned to complex type 19149 with 0-7 allelic differences, and ST48 isolates were assigned to complex type 19150 with 5 allelic differences. These patterns support vertical spread via clonal expansion across multiple facilities. Despite substantial chromosomal separation, most isolates carried the same IncFII(K) plasmid backbone and blaKPC-3, and they were nearly indistinguishable from a plasmid previously reported in South Korea. One isolate carried blaKPC-3 on a distinct multireplicon IncFIB(K)/IncFII(K) plasmid, indicating that the signal was not confined to a single plasmid backbone. In both plasmids, blaKPC-3 was embedded within Tn4401b. These findings indicate that a rare blaKPC-3 genotype can persist regionally through sustained clonal dissemination and that cross-lineage linkage is compatible with past horizontal transfer involving a conserved plasmid. These findings underscore the need for subtype-resolved, regionally coordinated genomic surveillance in connected healthcare networks to detect uncommon carbapenemase variants early.

Klebsiella pneumoniae

Treatment preference for once-weekly versus once-daily DPP-4 inhibitors in patients with type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND/OBJECTIVE: Although once-weekly and once-daily DPP-4 inhibitors have gained widespread market recognition, patient preference differences remain a key focus. This meta-analysis compares treatment preferences for once-weekly versus once-daily DPP-4 inhibitors in T2DM, offering evidence to guide clinical decisions and healthcare policies. METHODS: PubMed, OVID, EBSCO, Web of Science, CNKI, Wanfang, and clinical trial registries were searched up to June 30, 2025. After screening literature against predefined criteria, a systematic review was conducted to compare the effects of once-weekly and once-daily DPP-4 inhibitors on the treatment preferences of patients with T2DM. RESULTS: 8 RCTs with 1,575 participants were analyzed. No significant difference in medication adherence and DTSQ total score between the once-weekly and once-daily groups (p > 0.05). HbA1c percentage (MD = -0.21, 95% CI [-0.42, -0.01], p < 0.05) decreased significantly with once-weekly dosing, while GA and FPG showed no change (p > 0.05), this suggests greater improvement in HbA1c percentage levels following a switch to once-weekly DPP-4 inhibitors. Once-weekly DPP-4 inhibitors showed higher musculoskeletal/connective tissue disorder risk (RR = 2.63; 95% CI [1.18, 5.83]), but no significant differences in other adverse events (p > 0.05). No significant differences in treatment burden between both groups (p > 0.05). CONCLUSION: No statistically significant association between treatment preferences for once-weekly versus once-daily DPP-4 inhibitors among T2DM patients and medication adherence, treatment satisfaction, glycemic level changes, safety, or treatment burden for these two dosing regimens. Further research is needed to elucidate the influence of physician prescribing behavior on these preferences.

Humans

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics

The impact of routine traffic encounters that include procedural justice on police perceptions.

OBJECTIVES: Despite procedural justice in police-citizen interactions being widely studied, there is limited research regarding police perceptions of these interactions. This study addresses this by exploring police perceptions of two different types of random breath test (RBT) - standard and procedurally just - in an experimental trial. Officers were asked to report on whether they believe that their RBT interaction with drivers and riders changed behaviour, developed more positive perceptions of police and resulted in slower travel. Additionally, they were asked if they thought that the RBT interaction took too long. METHODS: This study was a six month randomised control trial with two operational conditions: a control condition with a standard (n&#xa0;=&#xa0;18&#xa0;days) and an experimental condition with a procedurally just (n&#xa0;=&#xa0;17&#xa0;days) RBT. Police officers completed post-operation surveys (n&#xa0;=&#xa0;80). RESULTS: Police officers incorporating the principles of procedural justice into RBT had limited impact on officer perceptions. However, those officers who were more open to innovation believed that the interaction would result in more positive perceptions of police. Police officers who believed that their RBTs with motorcycle riders would make a difference perceived that the riders would both change their behaviour and travel more slowly after the interaction. There were no differences in perceived interaction length by police officers across both conditions. CONCLUSIONS: This study has shown that police officer openness to innovation has an important role to play in police officers having more positive perceptions regarding the outcomes of RBT interactions. As such police organisations should undertake activities, such as training, to improve innovation. The lack of perceived differences in RBT length between standard and procedurally just interactions suggests that these enhanced interactions can be implemented without concerns that police officers believe that they 'take too long'.

Humans

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.

This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.

Neoplasms

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans

Identifying biomarkers of accelerated ageing in cancer patients from routine clinical data.

INTRODUCTION: Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Therefore, biological age can differ from chronological age; biomarkers are needed to stratify interventions to minimise accelerated ageing. METHODS: PhenoAge was calculated from routine blood test results of patients attending a Geriatric Oncology clinic. PhenoAgeAccel was the residual from a regression of PhenoAge against age. RESULTS: Data were available for 173 patients (62% male). Mean PhenoAge was higher than age (84.3 (12.6) vs 76.2 (7.24), p&#x202f;<&#x202f;0.001), though the two were correlated (r&#x202f;=&#x202f;0.579, p&#x202f;<&#x202f;0.001). Unlike age, PhenoAge and PhenoAgeAccel were associated with one-year mortality (PhenoAge OR=1.083, 95% CI: 1.038-1.136; PhenoAgeAccel OR=1.096, 95% CI: 1.047-1.155). PhenoAge correlated with Clinical Frailty Score and Timed Up and Go (CFS: Rs=0.31, p&#x202f;<&#x202f;0.001; TUG: Rs=0.25, p&#x202f;<&#x202f;0.005); there were no correlations with age. PhenoAgeAccel correlated with the number of CGA interventions made (Rs=0.17, p&#x202f;<&#x202f;0.05), unlike age and PhenoAge. Patients with diabetes mellitus had a higher PhenoAgeAccel compared to those without (3.40 vs -1.71, p&#x202f;=&#x202f;0.002). In patients receiving systemic anti-cancer treatment, patients with PhenoAgeAccel calculated pre-treatment had less age acceleration than those with PhenoAgeAccel calculated post-treatment, both overall (2.18 vs -2.87; p&#x202f;=&#x202f;0.048) and in matched samples (n&#x202f;=&#x202f;21, 7.76 vs -2.87, p&#x202f;<&#x202f;0.001). CONCLUSIONS: PhenoAgeAccel is a greater predictor of risk than chronological age in older people with cancer. This makes it a promising biomarker to stratify patients for holistic geriatric assessment, dose reductions, or future geroprotective measures which could be integrated within electronic healthcare record systems.

Humans

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans