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PubMed2026

Harnessing Endogenous Plasticity Rather than Reprogramming of Mature Cells Will Advance Regenerative Medicine, Cancer Treatment and Rejuvenation.

The successful culture of human embryonic stem (hES) cells from inner cell mass cells of blastocyst stage 'spare' embryos in 1998, followed by induced pluripotent stem (iPS) cells in 2006, which allowed somatic cells to be reprogrammed to pluripotency using the Yamanaka factors, transformed regenerative biology and inspired extensive global efforts towards developing pluripotent stem cell-based applications. However, hES and iPS cells, as well as organoids generated from them, largely retain fetal-like characteristics, which limits their relevance for clinical translation. Concurrently, the prevailing assumption published in leading journals that adult tissues lack endogenous stem cells has led to the belief that mature cells dedifferentiate and reprogram during in vivo regeneration upon chronic injury, and that the appearance of embryonic/fetal markers in diabetes, heart failure, cancer, and many other chronic disease states reflects dedifferentiation of mature cells. We suggest that the prevailing concepts of dedifferentiation and reprogramming, both in vitro and in vivo, require careful re-evaluation. Adult somatic cells possibly do not truly dedifferentiate, neither in vitro nor in vivo. Instead, tissue-resident, pluripotent, very small embryonic-like stem cells (VSELs) in multiple organs account for the observed biology. In vitro "reprogramming" responses to Yamanaka factors likely reflect selective activation and expansion of VSELs/early progenitors rather than the dedifferentiation/ reprogramming of mature adult somatic cells. Likewise, the embryonic/fetal-like signatures reported in multiple disease states including cancer reflect expansion of immature tissue-specific progenitors that arise from VSELs but fail to differentiate normally due to a damaged microenvironment in vivo. Therapeutic strategies involving transplantation of MSCs, MUSE cells, or their secreted exosomes improve disease outcomes, possibly by restoring the damaged niche that supports functional tissue repair by VSELs. Although direct evidence to support this is lacking at present, recognising the central role of VSELs/progenitors and their niche in maintaining tissue homeostasis in vivo could resolve existing roadblocks and guide more effective endogenous regenerative therapies for diseased tissues and age-related dysfunctions.

Humans↗

PubMed2026

Performance of Photon-counting CT for Assessing Pretreatment Breast Cancer: Comparison with Mammography, MRI, and 18F-FDG PET/CT.

Background Photon-counting CT (PCCT) offers improved spatial resolution, contrast to noise ratio, and dose efficiency, but its clinical utility remains incompletely defined for breast cancer. Purpose To evaluate the feasibility of PCCT for pretreatment breast cancer assessment through comparisons with MRI, full-field digital mammography (FFDM), and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT. Materials and Methods In this prospective study (March-May 2025), female participants with breast lesions categorized as Breast Imaging Reporting and Data System 4C or higher at US or FFDM underwent breast MRI and multiphasic contrast-enhanced PCCT. 18F-FDG PET/CT was performed in a subset with locally advanced disease. Four radiologists independently evaluated lesion morphologic characteristics, additional findings, and clinical TNM stage. Agreement was analyzed using intraclass correlation coefficients (ICCs) and κ statistics. The diagnostic performance for additional lesions and nodal metastasis was compared with the reference standard (pathologic examination). Results Among 126 participants (mean age, 58.1 years ± 12.3 [SD]), interreader agreement across PCCT, MRI, and FFDM was good to excellent. PCCT agreed with MRI for lesion characterization (κ = 0.57-0.96) and clinical T categorization (κ = 0.86-0.88), with highest agreement with pathologic size (ICC, 0.70-0.81). For 46 pathologically confirmed additional lesions, PCCT was more sensitive than FFDM (difference, 44% [95% CI: 19, 66]) and similar to MRI (difference, 7% [95% CI: -5, 21]). Additionally, 44% (95% CI: 27, 52) of microcalcifications were missed at PCCT versus FFDM. For pathologically confirmed nodal metastasis, PCCT was more sensitive (difference, 10% [95% CI: 1, 20]) and accurate (difference, 6% [95% CI: 1, 11]) than MRI. For clinical N category, PCCT agreed with PET/CT (κ = 0.82 [95% CI: 0.62, 0.96]; n = 19). Two distant metastases identified at PCCT were consistent with 18F-FDG PET/CT and pathologic findings. Conclusion PCCT demonstrated similar performance to MRI for lesion characterization and detection of additional lesions, with better performance for nodal metastasis evaluation; however, detection of microcalcifications was limited. © RSNA, 2026 Supplemental material is available for this article.

Humans↗

PubMed2026

Can host genetics transform the sustainable control of tropical theileriosis? Insights from the Tick-Theileria interface.

Tropical theileriosis, caused by the tick-transmitted apicomplexan parasite Theileria annulata, remains a major constraint on cattle production across North Africa, the Mediterranean basin, the Middle East and South Asia. Current control depends on acaricides, the theilericidal drug buparvaquone and live attenuated schizont vaccines, but acaricide resistance, buparvaquone-resistance mutations and the logistical demands of vaccination are eroding the sustainability of these tools. Host genetics offers a complementary and durable alternative. Indigenous Bos indicus breeds are consistently more resistant to ticks and tolerate T. annulata infection better than exotic Bos taurus cattle, and this advantage has a measurable heritable component. Unlike previous reviews, which treat tick resistance, T. annulata immunobiology and livestock genomic selection as separate subjects, we integrate all three and assess host genetics specifically against the failure modes of current control. We review the tick, parasite and host interface, the evidence for natural resistance, and the genetic and immunological mechanisms involved, including signal-regulatory protein, bovine major histocompatibility complex class II and inflammatory pathway genes. We then assess whether genomic selection, multi-omics, machine learning and gene editing can translate these mechanisms into resistant cattle, and we weigh the biological, economic and infrastructural barriers to implementation. The evidence indicates that host genetics will not replace existing control but could reduce reliance on acaricides and chemotherapy. That contribution remains prospective rather than demonstrated: no resistance marker for T. annulata has yet been validated, prediction accuracies are moderate and transfer poorly between breeds, and no endemic production system has implemented selection for resistance.

Animals↗

PubMed2026

Effects of erector spinae plane block on postoperative pain in patients undergoing implant-based breast reconstruction for breast cancer: a randomized controlled trial.

BACKGROUND: Implant-based breast reconstruction after mastectomy causes acute pain. OBJECTIVE: To determine whether a single-shot T5 erector spinae plane block (ESPB) reduces postoperative pain. DESIGN: Single-center, RCT with allocation concealment; blinded assessors and statisticians. SETTING: Tertiary cancer center in China. PATIENTS: 100 adults scheduled for radical mastectomy with implant reconstruction were randomized (1:1); follow-up complete. INTERVENTION: Before induction, ESPB was given under ultrasound guidance at T5 with 30 mL of 0.375% ropivacaine plus dexmedetomidine 1 μg/kg; controls received no block. Standardized general anesthesia and postoperative PCA for both groups. MAIN OUTCOME MEASURES: Resting NRS at 6 h (MCID=1). Secondary outcomes were opioid consumption, quality of recovery, and PONV. RESULTS: ESPB did not significantly reduce resting pain at 6 h at the median (τ =0.50; adjusted difference -0.9; p = 0.08). At the upper tail, pain intensity was lower (τ = 0.75; -1.8; p <0.01). Repeated measures provided additional time-point information, improving estimation precision and test sensitivity. ESPB get lower pain scores at 6, 12, and 24 hours (all p <0.01). But, the 95% CI includes the MCID, the clinical benefit remains uncertain. Opioid use decreased at 24 h (-13.5 mg; p <0.01) and 48 h (-6.6 mg; p <0.01). Quality of recovery improved at 24 h (difference 5 points; p <0.01), but not later. No differences were observed in intraoperative hemodynamics or PONV. CONCLUSIONS: Single-shot T5 ESPB with perineural dexmedetomidine may reduce postoperative pain and opioid requirements and improve early recovery. Further large trials are warranted. Clinical relevance remains to be confirmed. TRIAL REGISTRATION: ClinicalTrials.gov NCT06143020.

Humans↗

PubMed2025

Systematic meta-analysis of the toxicities and side effects of the targeted drug lenvatinib.

BACKGROUND: Lenvatinib, an effective targeted drug for various cancers, has clinical medication safety concerns due to its toxicities and side effects. OBJECTIVE: This study evaluated lenvatinib-induced any adverse events (any AEs) and nine aspects: vascular toxicities related to the circulatory system (vascular toxicities, blood system, and heart), toxicities of the skin and its appendages (skin/subcutaneous tissue and taste system), toxicities of the respiratory system (respiratory, thoracic, and mediastinal and respiratory tract), toxicities of the nervous system (nervous system and general), toxicities of the digestive system (gastrointestinal and liver), toxicities of the urinary system, toxicities of the endocrine and metabolic system (endocrine and metabolism/nutrition), toxicities of the musculoskeletal system, and other severe toxicities. Toxicities and side effects were stratified by severity into any and ≥3 grades for analysis. PATIENTS/MATERIALS AND METHODS: Multiple databases were searched for lenvatinib cancer clinical studies (cohort studies and randomized controlled trials) from inception to December 31, 2024; toxicity and side effect data were extracted and analyzed. RESULTS: Nine high-quality studies were included, showing that lenvatinib is effective in cancers but has notable toxicities. Taking hypertension as an example, for any grade, the risk ratio (RR) was 2.34 with a 95% confidence interval (CI) of [2.09, 2.62], a Z-value of 14.74, and a P-value <0.00001; for grade ≥3, the RR was 2.60 with a 95% CI of [2.21, 3.06], a Z-value of 11.44, and a P-value <0.00001. CONCLUSION: Lenvatinib is effective for cancer but toxic, and this study supports its rational clinical use.

Humans↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Microbial allies in a cotton pest: A descriptive account of associated microbiota dynamics in Dysdercus cingulatus across development.

BACKGROUND: Hemipteran insects harbour several symbiotic partners, mainly bacteria, which play pivotal roles for hosts like dietary provision, support overall physiology, xenobiotic degradation and manipulate/regulate behaviour. Most of these symbionts usually reside and operate from the digestive tracts of the animals. Cotton is one of the major cash crops in India and Dysdercus cingulatus (D. cingulatus) though a secondary pest, is causing significant destruction of cotton bolls, poor lint quality and reduce oil content of seeds. Premature opening of cotton bolls often leads to bacterial and fungal infections, thus resulting in extensive economic loss worldwide. D. cingulatus is a hemimetabolous insect that comprises of developmental stages like egg, nymph (5 instar stages), and adult. The present work explored the ontogeny specific diversity in the associated microbiota and predicted their probable functional inputs in D. cingulatus. RESULTS: The data obtained using 16S rRNA gene sequencing (NovaSeq 6000) revealed presence of members of Proteobacteria (65.83%), Firmicutes (24%), Actinobacteria (10%) phyla throughout the ontogeny of D. cingulatus. Highest alpha diversity of these symbiotic bacteria was recorded in the third instar nymphs in contrast to rest of the developmental stages. Among all the observed genera, Stenotrophomonas, Hungatella and Glutamicibacter were predominant from egg to adult stages. MicFunPred, a tool used for predicting the probable functional inputs of these symbionts, hinted at their probable stage specific contribution in crucial biochemical pathways such as polyketide biosynthesis, ascorbate/aldarate metabolism, pentose phosphate and glyoxylate cycles, steroid hormone and peptidoglycan biosynthesis, and glycolysis/pyruvate metabolism. CONCLUSIONS: The primary investigations on the ontogenetic composition and diversity of associated microbiota, suggest dynamic shifts in D. cingulatus, concurrent with their probable functions/roles in the host development and metabolism. To the best of our knowledge, this is the first report on symbiotic microbiota variation across the developmental stages of D. cingulatus that provides preliminary descriptive observations that may guide future functional and experimental investigations into microbiota-based pest management.

Animals↗

PubMed2026

Safety and efficacy of Meridian sinew tuina (MST) for post-surgical upper limb lymphedema: a systematic review and meta-analysis.

BACKGROUND: Complex Decongestive Therapy (CDT) is the non-operative standard for breast cancer-related lymphedema (BCRL), but many patients experience persistent subcutaneous stiffness, pain, and restricted mobility. This study systematically reviews the safety and clinical efficacy of Meridian Sinew Tuina (MST) protocols for BCRL. METHODS: Global and regional databases (PubMed, Cochrane Library, Embase, Web of Science, CNKI, Wanfang, VIP) were searched from inception to January 15, 2026, with alerts monitored through April 30, 2026. Randomised controlled trials (RCTs) evaluating MST (deep tissue mobilisation along the six-hand meridian sinew [Jingjin] lines via plucking, kneading, and pressing) were included. Two reviewers independently extracted data, evaluated risk of bias using Cochrane RoB 2, and assessed evidence certainty via GRADE using a random-effects model. RESULTS: Fifteen RCTs were included. For the primary anthropometric outcome, MST significantly reduced upper limb circumference compared to controls (SMD = 1.59; 95% CI: 1.44 to 1.74; Z = 20.81; p < 0.0001; I2=0.0%; N = 924; GRADE: Moderate certainty). The Clinical Response Efficacy Rate (≥ 30% swelling reduction and symptom relief) favoured MST (RR = 1.69; 95% CI: 1.54 to 1.87; Z = 10.62; p < 0.0001; I2=0.0%; N = 1,114; GRADE: Moderate certainty). Trial Sequential Analysis confirmed sample size sufficiency. For secondary outcomes (N = 924; GRADE: Low to Very Low certainty due to performance bias and clinical heterogeneity), MST showed favourable 3-month improvements in DASH functional scores (SMD = -1.81; 95% CI: -2.11 to -1.51; I2=45.1%), pain intensity (SMD = -2.44; 95% CI: -2.93 to -1.95; I2=50.4%), and quality of life (SMD = 1.04; 95% CI: 0.79 to 1.29; I2=0.0%). No serious adverse events occurred. CONCLUSIONS: MST protocols are associated with favourable short- and mid-term reductions in upper limb swelling. However, confidence is tempered by unblinded performance bias and control group variations. MST cannot be unconditionally recommended for standalone implementation but represents a promising, optional supportive adjunctive intervention within oncological rehabilitation.

Humans↗

PubMed2026

Artificial intelligence in genitourinary oncology: publication trends and systematic review.

OBJECTIVE: To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication. METHODS: We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non-English papers, non-human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool. RESULTS: Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective/prospective methods, and four RCTs. Studies most commonly addressed prostate (n = 923), renal (n = 274), and urothelial (n = 194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified - one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI-based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions. CONCLUSIONS: Artificial intelligence research in GU oncology has grown, although high-level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.

Humans↗

PubMed2026

A novel neoadjuvant immunotherapy confers improved overall survival in oral cancer patients with low tumor PD-L1 expression The IT-MATTERS Clinical trial - Prognostic role of tumor PD-L1 expression.

OBJECTIVE: Five-year overall survival (OS) remains < 50% for patients with resectable, locally advanced (LA) primary oral squamous cell carcinoma (OSCC) and soft palate, receiving current standard of care (SOC). The aim of our study was to examine neoadjuvant Leukocyte Interleukin Injection (LI) with CIZ (intravenous low dose cyclophosphamide, indomethacin and zinc multivitamins) effect on OS, in low-risk (LR) OSCC patients. PATIENTS AND METHODS: In a randomized, controlled Phase 3 trial, treatment-naïve locally advanced patients, with stage III/IVa OSCC and soft-palate cancer, had surgical tumor samples assessed for pre-defined thresholds of PD-L1 tumor proportion score (TPS). OS was analyzed using proportional hazard models for LI + CIZ + SOC vs SOC, in the intention-to-treat (ITT) population. RESULTS: OS was superior in low risk (LR) patients receiving LI + CIZ + SOC compared to SOC; OS advantage hazard ratio (HR) 0.64, p = 0.0569 (without selecting for N0, PD-L1 TPS < 10%), and the Kaplan-Meier (K-M) lifetable achieved significance (log rank p = 0.0340) favoring LI + CIZ + SOC vs SOC. Applying the selection criteria (cN0 and TPS < 10%) to ITT, OS reached HR 0.34p = 0.0012, Kaplan-Meier log rank p = 0.0015. The ITT LR cohort (cN0 and TPS < 10%) achieved a HR 0.26 (p = 0.0023), Kaplan-Meier log rank p = 0.0013, supported by progression free survival (PFS) HR 0.43, p = 0.0178, Kaplan-Meier log rank p = 0.0431, with 32% absolute survival advantage over control at 60 months. CONCLUSIONS: Significant OS prolongation was observed in ITT population for LI + CIZ + SOC vs SOC, in LR and in ITT LR cN0, PD-L1TPS < 10% cohort having locally advanced squamous cell carcinoma tumors in oral cavity/soft-palate. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT01265849; EudraCT (Identifier: 2010-019952-35).

Humans↗

PubMed2026

Corneal Epithelial Alterations Associated With Cyclin-Dependent Kinase 4/6 Inhibitor Therapy in Hormone Receptor-Positive Breast Cancer.

IMPORTANCE: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors are standard therapy for hormone receptor-positive (HR+), HER2-negative breast cancer. By blocking the G1/S cell-cycle transition, these agents may impair renewal of the corneal epithelium. No controlled study has systematically evaluated corneal epithelial changes in patients receiving CDK4/6 inhibitors. OBJECTIVE: To determine whether CDK4/6 inhibitor-based therapy is associated with cornealepithelial alterations independent of aromatase inhibitor exposure and tear film dysfunction. DESIGN, SETTING, AND PARTICIPANTS: Retrospective comparative cross-sectional study at a tertiary ophthalmology center. A total of 132 women were enrolled: 45 receiving a CDK4/6 inhibitor plus an aromatase inhibitor (CDKAI group), 44 receiving aromatase inhibitor monotherapy (AI group), and 43 age-matched postmenopausal controls without systemic oncologic therapy. EXPOSURES: CDK4/6 inhibitor (ribociclib, palbociclib, or abemaciclib) combined with an aromatase inhibitor; aromatase inhibitor alone; or no systemic oncologic therapy. MAIN OUTCOMES AND MEASURES: Prevalence and severity of punctate epitheliopathy and vortex keratopathy, assessed by a masked ophthalmologist. Secondary outcomes included Schirmer I test, tear film break-up time, and Ocular Surface Disease Index (OSDI). RESULTS: PE was present in 44.4% of eyes in the CDKAI group vs 4.7% in the AI group and 2.3% in controls (χ² = 34.31; P < .001). All moderate (13.3%) and severe/complicated (8.9%) PE cases occurred exclusively in the CDKAI group. Vortex keratopathy was observed in 13.3% of CDKAI patients and in none of the other groups (P = .025). Schirmer values, tear film break-up time, and OSDI scores did not differ among groups (all P > .05). Within the CDKAI group, PE was not associated with treatment duration (P = .963) or tear film parameters. CONCLUSIONS AND RELEVANCE: In this comparative study, CDK4/6 inhibitor-based therapy was associated with significantly higher prevalence and severity of PE and vortex keratopathy, independent of aromatase inhibitor exposure and in the absence of measurable tear film dysfunction. These findings suggest a direct cytostatic effect on the corneal epithelium. Symptom scores were low, although OSDI interpretation was limited by incomplete responses. Proactive corneal surface evaluation with fluorescein staining may be warranted during CDK4/6 inhibitor treatment.

Humans↗

PubMed2026

Novel Germline ELP1 Splice-Acceptor Variant in NF1-Negative Optic Pathway Glioma: Expanding the Clinical Spectrum Associated With ELP1 Variation.

We report a 7-year-old boy with NF1-negative optic pathway glioma harboring a novel germline ELP1 splice-acceptor variant (NM_003640.5:c.2205-2A>G) identified by whole-exome sequencing. The variant was likely pathogenic (ACMG/AMP: PVS1, PM2) and inherited from an asymptomatic father, consistent with incomplete penetrance, expanding the limited evidence linking germline ELP1 variation to gliomas.

Humans↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗

PubMed2026

A Sentiment-Based Comparison of AI- and Physician-Generated Empathic Statements in Palliative Care.

CONTEXT: Empathic communication promotes trust in patient-provider relationships. As healthcare integrates artificial intelligence (AI) into patient communication, we have yet to understand how these models' communication compares to that of physicians. OBJECTIVES: Our primary objectives were to examine patient preferences for AI-generated vs. palliative care physician-generated empathic statements addressing fear and anxiety around cancer treatment, and to analyze associations between linguistic features and patient preferences. METHODS: We conducted a secondary analysis of the PALL-AI trial, a randomized controlled survey comparing cancer patients' preferences of AI- to physician-generated empathic statements. Physicians and AI were provided the same prompt with a maximum sentence length. Patient preferences for each statement were measured in blinded surveys. We analyzed sentiment of the statements using the Valence Aware Dictionary and Sentiment Reasoner (VADER) and the National Research Council Canada (NRC) Emotion Lexicon. We evaluated associations between sentiment scores and patient preferences using Spearman's correlation coefficients. RESULTS: A total of 105 patients completed blinded surveys, preferring the AI-generated statement 72.4% of the time. VADER sentiment analysis showed all three AI statements displayed positive sentiment, while all three physician statements displayed negative sentiment. Controlling for statement length, AI statements used twice as many positive words as human statements. However, they contained a similar number of negative words. Of the eight NRC emotions, "trust" and "joy" demonstrated the strongest correlations with patient preference. CONCLUSION: Patients preferred AI-generated statements around cancer care over those from palliative care physicians when standardized for prompt and statement length. Analysis shows AI-generated statements contain more positive language which may be the factor driving patient preference toward AI.

Humans↗

PubMed2026

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics↗

PubMed2026

Corrigendum to "The impact of diverse ancestry on polygenic risk score-based prediction models for psychiatric and neurodevelopmental disorders" [Psychiatry Research 2026 Oct:364:117322].

Explore the source record for details and available documents.

Published Erratum↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗

PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗