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PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗

PubMed2026

Cross-species variant-to-function analyses implicate MEIS1 in conferring sleep abnormalities and impaired cerebellar development.

Genome-wide association studies (GWAS) have identified numerous loci for insomnia, yet functional validation of effector genes remains limited because most risk variants lie in noncoding regions, and the true causal gene is not known. Here, we use prior human cell-based variant-to-gene mapping to nominate six insomnia effector genes and test them in zebrafish, a tractable diurnal vertebrate model well suited for sleep phenotyping. Our CRISPR-based behavioral screening identifies the MEIS1 ortholog, meis1b, as a regulator of sleep maintenance, with crispants displaying impaired nighttime-specific sleep maintenance and increased sleep latency. Comparative chromatin analyses reveal conserved regulatory architecture spanning the human insomnia-associated locus and selectively implicate meis1b, whereas the duplicated ohnolog meis1a was dispensable. Developmental profiling further shows that meis1b is expressed in cerebellar granule progenitors, paralleling human MEIS1 expression, and that its disruption impairs cerebellar development. Together, these findings establish zebrafish as an efficient vertebrate platform for functional interrogation of GWAS candidates and support an evolutionarily conserved cerebellar role for MEIS1 in sleep maintenance.

Animals↗

PubMed2026

Non-linear predictive modeling and comprehensive meta-analysis of rectal temperature in Santa Inês sheep: a systematic review of thermal challenges and biometerological trends.

A systematic and bibliometric review, combined with a meta-analysis, was used to adjust an equation for estimating the physiological responses of Santa Inês sheep subjected to different thermal challenges. The systematic review compiled data on physiological responses and the thermal environment, which were then used in the meta-analysis to adjust regression models. The bibliometric analysis mapped the relationships among studies, highlighting their usefulness in interpreting research findings and biases. Addressing prior methodological critiques, the core of this study involves replacing the linear approach with a non-linear segmented regression model to accurately define the Thermal Neutral Zone (TNZ). The Segmented Regression Model was crucial, establishing the upper limit of the Thermal Neutral Zone (TNZ) at an air temperature (tair) of 34.64 °C, where trectal begins to increase abruptly. The model, while identifying a biologically significant breakpoint, exhibited a moderate Multiple R-squared of 0.3529, highlighting the high heterogeneity and methodological variability in the current Santa Inês literature. This non-linear approach offers a biologically superior tool for identifying the onset of thermal distress.

Animals↗

PubMed2026

Ramu stunt virus genome reveals previously unreported segments and nucleocapsid domain duplication in Mechlorovirus.

Ramu stunt virus (RmSV), a member of the genus Mechlorovirus within the family Phenuiviridae, was previously described as a six-segmented RNA virus infecting sugarcane. In this study, we re-examined type material and additional isolates using high-throughput sequencing and RT-PCR validation, revealing that RmSV possesses a nine-segmented genome, making it the largest reported in the Phenuiviridae. This expanded architecture includes duplicated RNA segments (RNA 2a and RNA 2b) encoding nucleocapsid-like proteins and two novel segments (RNA 7 and RNA 8). Comparative analysis showed that RNA 2a and 2b share about 84% amino acid identity, while RNA 5 encodes a third nucleocapsid homolog, indicating unprecedented domain redundancy. Structural modeling confirmed that all three nucleocapsid proteins maintain a conserved fold despite low sequence identity, with electrostatic mapping suggesting differential RNA-binding potential. Additionally, RNA 6 encodes a hypothetical protein structurally similar to the rice stripe virus disease-specific S-protein, implicating a role in symptom development. Transcript abundance analysis revealed RNA 6 as the most highly expressed segment across isolates. These findings revise the genomic composition of RmSV, highlight mechanisms of genome plasticity and adaptive evolution in plant-infecting bunyaviruses, and underscore practical implications for diagnostic assay design, resistance breeding, and biosecurity surveillance.

Genome, Viral↗

PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Use of indocyanine green fluorescence versus patent blue V dye for sentinel lymph node biopsy in early breast cancer, a randomized controlled trial.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard for axillary staging in early breast cancer. While the combination of radioisotope and blue dye (e.g., patent blue V, PBV) remains the standard, it has limitations including logistics, variable identification rate (IR), and allergic potential. Indocyanine green (ICG) fluorescence is a promising alternative, but high-quality comparative evidence is needed. METHODS: This was a single-center, prospective, randomized controlled trial. Forty patients with early-stage, node-negative breast cancer were allocated to SLNB using either ICG (n = 20) or PBV (n = 20). All patients subsequently underwent completion level I-II axillary lymph node dissection (ALND) as the pathological reference standard for diagnostic performance assessment. Primary outcome was sentinel lymph node (SLN) IR. Secondary outcomes included detection time, number of SLNs retrieved, false-negative rate (FNR), and safety. RESULTS: Baseline characteristics were comparable between groups. The SLN IR was significantly higher with ICG (100% [20/20]) than with PBV (75% [15/20], p = 0.047). ICG was associated with a significantly shorter median detection time (14.5 vs. 24.0 min, p < 0.001) and retrieved more SLNs (mean: 3.6 vs. 2.4, p = 0.002). Most critically, ICG demonstrated 100% sensitivity, specificity, negative predictive value (NPV), and overall diagnostic accuracy, with a 0% FNR. In contrast, PBV achieved a sensitivity of 75%, an overall diagnostic accuracy of 90%, and an FNR of 25%. No ICG-related adverse events occurred. PBV caused skin discoloration in 75% of patients and one (5%) allergic reaction. CONCLUSION: ICG fluorescence achieved a higher SLN IR, shorter detection time, higher sensitivity, lower FNR, and fewer tracer-related adverse events than PBV as a single tracer for SLNB in patients with early-stage breast cancer. These findings suggest that ICG is a promising standalone tracer when radioisotope mapping is unavailable. Larger multicenter studies are required before widespread adoption can be recommended.

Humans↗

PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans↗

PubMed2026

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085 mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes↗

PubMed2026

Smartphone apps for obesity management: A systematic review using self-determination theory.

BACKGROUND: While bariatric surgery and pharmacotherapy are effective treatments for obesity, ongoing supportive care remains a challenge. Smartphone applications (apps) may assist with symptom management, but their effectiveness and practical use in obesity treatment is unclear. This review evaluated the effectiveness, acceptability, and feasibility of these apps in supporting individuals following obesity treatment. To better understand how these apps may promote sustained engagement and behaviour change, their design was analysed using Self-Determination Theory (SDT). METHODS: A systematic search was conducted across MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, SCOPUS, and CENTRAL databases. Eligible studies included randomised and non-randomised interventions involving adults (≥18 years) with obesity (BMI ≥ 30 kg/m2) who had undergone bariatric surgery or pharmacotherapy. Interventions had to include an app designed to support post-treatment symptom management. Findings were synthesised narratively, and app features were mapped to SDT constructs of autonomy, competence, and relatedness. RESULTS: Five studies (three RCTs, two cohort studies) involving 1,133 participants were included (female: 78 %; median age: 47.63 years). Most apps targeted post-bariatric surgery care; only one focused on pharmacotherapy. Common features included tracking, reminders, and education, supporting autonomy and competence. Relatedness features such as communication and peer support were least represented. Two studies reported improvements in weight-related outcomes and one in medication adherence. Effects on quality of life, self-efficacy, and healthcare utilisation were not significant. Patient satisfaction was reported in one study, with 95 % expressing positive feedback, though formal assessments of feasibility and acceptability were limited. CONCLUSION: Smartphone apps show potential to support obesity management, particularly after bariatric surgery. While some evidence suggests benefits for weight loss and adherence outcomes, the limited studies and variability of reporting prevent conclusive observations in other outcomes. Future app development should integrate behavioural theory to address psychological needs, nutritional risks and promote holistic self-management beyond weight control.

Female↗

PubMed2026

Long-term consequences of childhood sexual abuse: An umbrella review of diagnostic meta-analyses.

BACKGROUND: Childhood sexual abuse (CSA) is a public health issue with an estimated worldwide prevalence of 12.7%, potentially leading to a host of lifelong and significant mental, physical, and behavioral health. The aim of this study was to comprehensively map the long-term consequences of childhood sexual abuse on physical, psychiatric, and behavioral health outcomes. METHODS: An umbrella review of meta-analyses of observational studies, registered on PROSPERO, was conducted to examine the diverse repercussions of childhood sexual abuse on adult health. Three bibliographic databases (PsycINFO, PubMed and Scopus) were searched from the inception of the respective databases to November 1st, 2022. Thirty-eight meta-analyses representing about 20 million individuals were analyzed, revealing a range of long-lasting consequences associated with CSA. RESULTS: Among physical pathologies, cervical cancer and functional neurological syndromes emerged as the most prominent, exhibiting significantly elevated odds ratios (ORs) of 4.18 IC95% and 3.30 IC95%, respectively. Sleep disorders and borderline personality disorders were the most prevalent mental health disorders associated with CSA, with respective ORs of 16.17 IC95% and 5.96 IC95%. Early sexual initiation (OR=3.59 IC95%, sexual assault (OR=3.36 IC95%, and prostitution (OR=3.24 IC95%) emerged as the most common behavioral consequences. Notably, no significant differences in the consequences of CSA were observed between men and women, except for reproductive health outcomes. DISCUSSION: When faced with certain pathologies, clinicians should consider and discuss sexual abuse with their patients. The consequences of abuse have a multifactorial origin, which is a weakness, as are the problems of defining abuse. The strength of our study is that it lists the consequences published in high-quality studies. CONCLUSION: This umbrella review provides compelling evidence of the profound and far-reaching impact of childhood sexual abuse on a broad spectrum of physical, mental, and behavioral health issues.

Humans↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Single-cell transcriptomics reveals heterogeneous stress responses and Mg2+-mediated survival mechanisms in Lactobacillus delbrueckii subsp. bulgaricus during freeze-drying and storage.

Maintaining the viability of lactic acid bacteria during dehydration and subsequent storage remains a significant challenge. Here, we employed single-cell RNA sequencing to reveal the heterogeneous stress responses of Lactobacillus delbrueckii subsp. bulgaricus, identifying seven distinct transcriptional clusters across the liquid culture, freeze-drying, and storage phases. The dominant clusters in the freeze-drying and storage were not completely consistent, showing significant functional differentiation. Genomic stability may be important for survival during freeze-drying and storage, while intracellular energy homeostasis appears important for viability during storage. The magnesium transporter mgtB was highly expressed in clusters tolerant to freeze-drying and storage, suggesting a critical role for Mg2+ homeostasis. Further experimental validation confirmed that Mg2+ treatment significantly bolstered stress resistance, increasing immediate post-freeze-drying survival by over 2-fold (up to 92.90%) and post-storage survival by over 5-fold (up to 5.98%). Proteomic data indicated that Mg2+ supplementation correlated with the maintenance of several biological functions potentially relevant to bacterial survival during freeze-drying and storage, including DNA repair, translation, and central carbon metabolism. These findings provide a map of microbial stress resistance through population heterogeneity and offer a potential strategy that may be adapted for enhancing the stability of other industrial lactic acid bacteria products.

Freeze Drying↗

PubMed2026

Metatranscriptomic analysis of viral sequences associated with Culex nigripalpus at an Alabama aquaculture site.

Mosquitoes associated with aquaculture habitats can harbor diverse viruses, yet the viromes of many locally abundant species remain poorly characterized. At an aquaculture-associated site in Auburn, Alabama, we surveyed mosquito populations and found Culex nigripalpus to be the dominant species collected. To characterize viruses associated with this mosquito, we performed RNA-seq on pooled female Cx. nigripalpus and compared complementary bioinformatic workflows for viral detection and genome recovery. One workflow removed host-associated reads by mapping to the closest available mosquito reference genome prior to assembly, whereas a second workflow used fully de novo assembly and viral database annotation. Additional protein-level filtering, cross-workflow comparison, and comparison of Trinity and rnaSPAdes assemblies were used to prioritize well-supported viral candidates. Across the original analyses, 16 submitted accessions corresponding to 12 collapsed virus/name groups were recovered, including Merida virus, Hubei mosquito virus 5, Zhejiang mosquito virus, Hubei virga-like virus 3, Rinkaby virus, Elemess virus, Qingnian mosquito virus, Serbia narna-like virus 2, XiangYun narna-levi-like virus 8, Ecclesville picorna-like virus, and baculovirus-like fragments. Several candidates were supported across multiple workflows, while others were recovered only under specific analytical conditions, indicating that candidate recovery was influenced by assembly and filtering choices. Selected viral contigs were independently supported by RT-PCR amplification. Overall, these results provide a first characterization of viral sequences associated with Cx. nigripalpus from an Alabama aquaculture-associated site and show that comparison across assembly and filtering strategies helped prioritize the most consistently supported viral candidates.

Animals↗

PubMed2026

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans↗

PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗

PubMed2025

Parent-Child Communication after Parental Exposure to Potentially Traumatic Events: A Systematic Review.

Intergenerational traumatization poses a risk for the well-being of children whose parents have been exposed to potentially traumatic events (PTEs). Previous research has implied that parent-child communication may significantly contribute to the transmission of trauma across generations, but findings remain limited and inconclusive, particularly regarding the mechanisms and factors that could underlie this process. Therefore, the present paper performed a mixed methods systematic literature review to methodically map how PTE-exposed parents communicate with their children-both in general and about parental PTEs-and how such communication may contribute to trauma transmission. Five electronic databases were accessed to conduct keyword-led searches, yielding a final inclusion of 31 peer-reviewed, empirical studies that investigated parent-child communication among PTE-exposed parents and/or their nonexposed children. Parental PTE exposure was found to have a negative impact on general parent-child communication, often due to the presence of parental anger, irritability, and withdrawal. Conversations about parental PTEs showed substantial diversity in their frequency, content and style, with strategies of partial/modulated disclosure appearing most common. How parents approached PTE communication frequently stemmed from a desire to keep their children safe and unburdened by their previous experiences. Finally, both general communication and PTE communication were implied to contribute to trauma transmission, revealing a significant impact of parent-child communication on child functioning, identity, and well-being. Based on these key findings, the authors discuss meaningful implications for future research (i.e., prospective directions, addressing methodological concerns) and formulate suggestions for clinicians and policymakers surrounding the treatment of PTE-exposed parents and their offspring.

Humans↗

PubMed2026

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗