Tag: statistics

Pharm Res. 2026 Jul 1. doi: 10.1007/s11095-026-04130-3. Online ahead of print.

ABSTRACT

PURPOSE: Glioblastoma(GBM) is highly aggressive and therapeutically refractory brain malignancy. Despite maximal intervention, patient prognosis remains dismal. A major obstacle in its management is the limited permeation of therapeutic agents across the blood-brain barrier(BBB), further intensified by resistance to standard chemotherapy such as temozolomide(TMZ). Proteolysis-targeting chimeras(PROTACs), offer new opportunities by enabling selective degradation of oncogenic proteins. A1874, a heterobifunctional molecule, has demonstrated potent, selective degradation of oncogenic driver-BRD4 in pancreatic, breast, and colon cancer. BRD4 drives GBM cell proliferation, survival, and resistance to therapy; therefore, we investigated the therapeutic potential of A1874 in brain cancer.

METHODS: Herein, we developed brain-targeted self-nanoemulsifying drug delivery system, termed PRONano, designed to enhance the targeted delivery of A1874. The system is functionalized with Palmitoyl-DL-carnitine chloride(PC) to facilitate transport across the BBB. Physicochemical characterization was performed to assess particle size. In-vitro cytotoxicity, qualitative and quantitative cellular uptake was analyzed. Mechanistic validation was conducted using western blot and qPCR, while 3D spheroid assay was employed to assess efficacy in tumor-mimicking microenvironment.

RESULTS: PRONano exhibited nanoscale particle size and significantly enhanced intracellular uptake of A1874. Formulation exhibited enhanced cytotoxicity in temozolomide-sensitive and resistant GBM cells. Effective BRD4 protein degradation was identified in the Western blot. PRONano significantly inhibited 3-D spheroid tumor growth suggesting better penetration and efficacy in tumor-like microenvironment.

CONCLUSIONS: PRONano is brain-targeted, rationally designed nanoformulation which can overcome major A1874 delivery constraints. This strategy augmented PROTAC delivery and therapeutic potential in GBM, supporting future preclinical development.

PMID:42387117 | DOI:10.1007/s11095-026-04130-3

Sci Rep. 2026 Jul 1. doi: 10.1038/s41598-026-59706-1. Online ahead of print.

ABSTRACT

Accurate day-ahead cooling load forecasting is a time series forecasting problem that is essential for optimizing the scheduling and energy efficiency of chilled water plants (CWPs). While previous studies have explored different forecasting models and input features, the combined effects of key factors such as historical context length (including regressor lags), sampling resolution, and exogenous inputs remain insufficiently examined for real industrial data. This study examines, under varying regressors and data granularity, the amount of historical context that provides stable and reliable forecasts with low computational cost. The experimental results show that (i) weekly scale look-back windows (LBW) provide an optimal balance between accuracy and computational cost for day-ahead horizons, (ii) hourly inputs often match or exceed finer-resolution accuracy and reveal distinct compute scaling: deep-learning (DL) models remain comparatively efficient as resolution increases, whereas the machine learning (ML) model, XGBoost, grows steeply, (iii) incorporating weather and calendar features enhances prediction accuracy around weekends and holidays. The DL model NHiTS, when integrating exogenous features and a 7-day LBW, improves forecasting accuracy by 50.8%, outperforming all other deep learning, machine learning, and statistical forecasting models by achieving a MASE of 1.88, compared to 3.82 for the baseline. These findings provide practical insights for smart-building and industrial applications, guiding practitioners such as building-energy engineers and facility managers in selecting optimal historical data lengths and parameter combinations to improve forecasting accuracy.

PMID:42387106 | DOI:10.1038/s41598-026-59706-1

Mol Psychiatry. 2026 Jul 1. doi: 10.1038/s41380-026-03730-0. Online ahead of print.

ABSTRACT

Depression arises from dynamic interactions among genetic predisposition, brain alterations, and environmental stressors. Despite genome-wide association studies (GWAS) identifying risk loci, the mechanisms translating genetic variation into brain changes remain elusive. Imaging-derived phenotypes (IDPs) were the intermediate traits linking genetic architecture to neural circuit dysfunction. Here, we collected large-scale GWAS summary statistics of depression and IDPs across European (EUR; N = 1,293,933 and 33,224, respectively) and East Asian (EAS; N = 82,874 and 7058, respectively). In the multiple-trait analysis between depression and IDPs, we clarified their genetic correlation through MTAG, identified the pleiotropic single nucleotide variants (SNVs) and genes with functional insight, and established the causal relationship through Mendelian randomization via TwoSampleMR in EUR and EAS ancestry, respectively. To discern the heterogeneous genetic drivers, we selected independent SNVs from the multiple-trait analyses to perform unsupervised clustering. Six clusters delineated distinct biological pathways for metabolic regulation, neurotransmitter dynamics, and neuroimmune interactions, with tissue/cell type specificity through MAGMA. Finally, we dissected relationships between depression and polygenic risk score, IDPs, and modifiable lifestyle factors, and introduced a machine learning framework to refine risk stratification (N = 16,166). Our study advanced the understanding of the multiscale etiology of depression while providing dynamic depression risk stratification for precision prevention.

PMID:42387104 | DOI:10.1038/s41380-026-03730-0

Mol Psychiatry. 2026 Jul 1. doi: 10.1038/s41380-026-03735-9. Online ahead of print.

ABSTRACT

Epidemiological and clinical observations linking schizophrenia (SCZ) to increased dementia risk, together with the occurrence of psychosis in Alzheimer’s disease and related dementias (ADRD), suggest that shared genetic liabilities may contribute to their co-occurrence. Leveraging large-scale genome-wide association study summary statistics for SCZ (53,386 cases and 77,258 controls) and ADRD (111,326 cases and 677,663 controls), we systematically investigated their shared genetic architecture and potential biological mechanisms. We identified three significant local genetic correlations (P < 2.0 × 10⁻⁵) and cross-trait polygenic enrichment between SCZ and ADRD, with 39 genomic loci jointly associated at conjunctional false discovery rate (conjFDR) < 0.05. Fifteen high-confidence genes (CNIH4, CD302, PCGF3, TFR2, EPHX2, SNX32, EFEMP2, CTSW, ASPHD1, TAOK2, INO80E, DOC2A, MAPK3, KANSL1, and XPNPEP3) were consistently prioritized across positional, expression quantitative trait locus, and chromatin-interaction mapping. Tissue- and cell-type enrichment analyses highlighted cerebellar tissues and ependymal-cell-related signals, while pathway analyses implicated synaptic signaling, axonal growth, and presynaptic structural organization. At the locus level, colocalization and transcriptome-wide association analyses converged on 16p11.2, prioritizing INO80E, YPEL3, SLX1B, and TMEM219. Developmental trajectory modeling further revealed region- and stage-specific expression divergence of prioritized 16p11.2 genes, with prominent differences spanning childhood and adulthood. Brain-wide association analysis linked the 16p11.2 lead variant rs9932702 to cortical gray-white contrast (β = -0.062, P = 7.5 × 10⁻¹⁵), a neuroimaging phenotype related to gray-white boundary microstructure and myelination. Finally, bidirectional Mendelian randomization supported a modest directional association between genetic liability to SCZ and increased ADRD risk, but not the reverse direction. Collectively, these findings provide convergent genetic, regulatory, transcriptomic, developmental, and imaging evidence for partial shared liability between SCZ and ADRD, highlighting 16p11.2 and biological processes related to neurodevelopment, synaptic and axonal organization, myelination-related microstructure, and later-life brain vulnerability.

PMID:42387103 | DOI:10.1038/s41380-026-03735-9

Drugs R D. 2026 Jul 1. doi: 10.1007/s40268-026-00547-8. Online ahead of print.

ABSTRACT

BACKGROUND: Gabapentin is effective for treating post-herpetic neuralgia and neuropathic pain by stabilizing nerve activity through blocking calcium channels and reducing neurotransmitter release. Gabapentin is available in immediate-release (IR) and extended-release (ER) formulations. A comparative bioavailability study was conducted between Gabapentin ER 600 mg tablets once-daily (OD) (Gabantin^® GRS) [Test (T)] (manufactured by Sun Pharmaceuticals Industries Limited), and Gabapentin Tablets 600 mg OD (Gralise^®) [Reference (R)] (distributed by Almatica Pharma LLC) in healthy human male adults under fed conditions.

METHODS: In this open-label, balanced, randomized, crossover study each subject received a 600 mg single dose of either T or R in Period 1, followed by crossover treatment in Period 2, with a washout period of 12 days in-between. Pharmacokinetic parameters, including C_max, AUC_0-t, and AUC_0₋∞, were assessed. Safety was monitored through treatment-emergent adverse events (AEs).

RESULTS: All 24 enrolled subjects completed the study. The test formulation demonstrated comparable pharmacokinetic profile to the reference product, meeting the criteria for bioequivalence within acceptable limits (0.80-1.25). The percentage ratio for T vs R product was 0.9171 (90% confidence interval [CI] 0.826-1.0183) for AUC_0-t, 0.9191 (90%CI 0.8279-1.0203) for AUC_0-∞ and 0.9135 (90%CI 0.8324-1.0026) for C_max. Plasma concentration-time profiles were similar. One AE of fever was reported after administration of T; no serious adverse event was reported.

CONCLUSIONS: Gabantin^® GRS 600 Tablet ER OD of Sun Pharma had a similar pharmacokinetic profile and was bioequivalent to Gralise^® in healthy subjects under fed conditions with good safety and tolerability profiles.

PMID:42387089 | DOI:10.1007/s40268-026-00547-8

Drugs Aging. 2026 Jul 1. doi: 10.1007/s40266-026-01306-9. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Propofol is widely used in clinical anesthesia, but its cardiorespiratory depressive effects may limit its safety in older patients. With the growing number of older adults requiring anesthesia, ciprofol has attracted interest because of its higher potency and relatively mild hemodynamic impact. This meta-analysis evaluated the efficacy and safety of ciprofol compared with propofol in older patients undergoing general anesthesia or painless endoscopy.

METHODS: We conducted a comprehensive search of PubMed, Embase, the Cochrane Library, and Web of Science up to 7 November, 2025, to identify eligible studies. All statistical analyses were performed using RevMan 5.4 and R version 4.5.1.

RESULTS: A total of 12 randomized controlled trials involving 2027 older participants were included. For safety outcomes, ciprofol significantly reduced the incidence of hypotension (risk ratio = 0.76, 95% confidence interval 0.68-0.84; p < 0.00001) and injection pain (risk ratio = 0.16, 95% confidence interval 0.09-0.26; p < 0.00001) compared with propofol. No significant differences were observed between the two agents in the incidence of bradycardia, hypoxemia, and postoperative nausea and vomiting. Regarding efficacy outcomes, ciprofol was associated with a longer time to loss of consciousness compared with propofol (mean difference = 4.67 seconds, 95% confidence interval 0.65-8.70; p = 0.02), while no significant differences were observed in anesthesia success rate, procedure completion rate, and awakening time.

CONCLUSIONS: Based on the currently available evidence from randomized trials conducted in China, ciprofol showed comparable efficacy to propofol and was associated with lower incidences of hypotension and injection pain in older patients. These findings may still be informative for anesthetic management in broader settings, although further validation is needed.

CLINICAL TRIAL REGISTRATION: PROSPERO registration number: CRD420251179366.

PMID:42387086 | DOI:10.1007/s40266-026-01306-9

Cell Death Differ. 2026 Jul 1. doi: 10.1038/s41418-026-01795-6. Online ahead of print.

ABSTRACT

Receptor-interacting protein kinase 1 (RIPK1) is a key stress sensor regulating cell death, inflammation, and tumorigenesis, yet how RIPK1 becomes activated remains unclear. Here, we identify serine/threonine kinase 38 (STK38) as a novel direct RIPK1 activator. STK38 binds to RIPK1, integrates into RIPK1-containing death complexes, and accelerates RIPK1-dependent cell death. STK38 deletion suppresses RIPK1-mediated necroptosis and apoptosis. Moreover, TNF-α stimulation triggers MEKK2-dependent STK38 activation, which in turn phosphorylates RIPK1 at serine 309, a residue conserved only in higher primates. This phosphorylation at S309 disrupts RIPK1’s interaction with its inhibitory kinase MK2, thereby suppressing S320 phosphorylation and facilitating RIPK1 activation. Furthermore, colorectal cancer sample analysis revealed a positive correlation among STK38 expression, RIPK1 activation status, and favourable patient outcomes. Consistently, STK38 deficiency confers resistance to RIPK1-dependent cell death and facilitates tumour progression in a xenograft model. Our findings identify STK38 as an activator of RIPK1 and uncover a novel regulatory mechanism of RIPK1-mediated cell death in humans.

PMID:42387067 | DOI:10.1038/s41418-026-01795-6

Sci Rep. 2026 Jul 1. doi: 10.1038/s41598-026-60196-4. Online ahead of print.

ABSTRACT

Large audio archives contain rich and diverse sonic material, yet they are seldom usable as controllable media in interactive contexts such as installations, live performance and adaptive sound environments. This paper presents a framework for interactive latent audio synthesis and technically continuous sound-space traversal and synthesis within a structured latent manifold rather than unconstrained audio generation. The framework first uses pretrained audio encoders, including AudioMAE, CLAP and related models, to organize a curated 120,000-clip AudioSet subset into a structured audio embedding space. A variational autoencoder then learns a smooth latent representation, which is further refined by a latent diffusion model to improve latent validity and traversal continuity. The refined latent codes are rendered into controllable waveforms through a DDSP-based synthesis stage, while Ambisonic spatialization provides Ambisonic spatial rendering coupled to traversal parameters. Gesture is used only at inference time as a control layer for traversal and spatial modulation, rather than as a training condition for the generator. The framework is evaluated against VAE-only and diffusion-only baselines using latent-structure analysis, interpolation behavior, synthesis quality and runtime performance. Results show that the proposed hybrid model achieves a CLAP similarity of 0.82, a mean F0 error of 245.3 Hz, a spectral convergence of 0.132 and an interactive latency of approximately 35 ms. These findings provide technical and proxy-based evidence for latent continuity, synthesis stability and real-time traversal feasibility. These findings provide technical and proxy-based evidence for latent continuity, synthesis stability and real-time traversal feasibility, while the human-centered pilot evaluation provides initial user-level evidence for perceived traversal smoothness, controllability, responsiveness and creative usefulness. Because the pilot evaluation is small-scale, these user-facing findings should be interpreted as preliminary rather than as statistically generalizable validation.

PMID:42387044 | DOI:10.1038/s41598-026-60196-4

J Therm Biol. 2026 Jun 29;140:104529. doi: 10.1016/j.jtherbio.2026.104529. Online ahead of print.

ABSTRACT

OBJECTIVES: Topical menthol is increasingly used as a perceptual cooling strategy during exercise, yet its ergogenic potential and underlying mechanisms remain unclear. Unlike previous route-mixed meta-analyses, this systematic review and three-level meta-analysis specifically examined the effects of acute topical menthol application on exercise performance alongside perceptual and physiological responses.

DESIGN: Meta-analysis.

METHODS: Six databases were searched from inception to March 2026. Randomized or controlled trials examining acute topical menthol application during exercise were included. Risk of bias was assessed using RoB-2. Three-level meta-analyses accounted for dependence among multiple outcomes. Prespecified moderators included sex, training status, environmental condition, application method, application site, and exercise modality. Sensitivity analyses addressed outliers and influential cases.

RESULTS: Sixteen studies involving 191 participants were included. Topical menthol produced a small but significant improvement in exercise performance (g = 0.27, p = 0.02). Thermal sensation (g = -0.74) and perceived exertion (g = -0.35) were reduced, with a small improvement in thermal comfort (g = 0.34), whereas core body temperature was unchanged. Performance benefits were most evident in aerobic endurance tasks, following rub-on application methods, and under temperate conditions, whereas effects in hot environments (≥30 °C) were smaller and not statistically significant. Several subgroup findings were sensitive to influential observations and should be interpreted cautiously.

CONCLUSIONS: Acute topical menthol may provide a small ergogenic benefit primarily through perceptual cooling rather than physiological heat strain. Effects appear context dependent and most relevant for endurance exercise. Further well-controlled studies are needed to clarify optimal application strategies and environmental conditions.

PMID:42385298 | DOI:10.1016/j.jtherbio.2026.104529

Public Health. 2026 Jul 1;258:106404. doi: 10.1016/j.puhe.2026.106404. Online ahead of print.

ABSTRACT

OBJECTIVE: The primary health challenges currently facing the United States (U.S.) and many other countries around the world are largely due to patients with chronic conditions, which act either independently or synergistically. The current study assesses the ability of the Ecological Framework of Population Health to predict U.S. county-level prevalences of eight common chronic conditions.

STUDY DESIGN: Analytic analysis of population-level surveillance data METHODS: This study utilizes several U.S. county-level datasets representing over 30 predictive variables of the ecological framework, a model that includes measures of culture, politics, policy, socioeconomics, lifestyle behaviors, and both chronic condition risk factors and diagnoses. A non-linear artificial intelligence statistical approach was used to assess the ability of these variables (i.e., features) to predict the prevalence of eight leading chronic conditions at the U.S. county-level.

RESULTS: Artificial intelligence models demonstrated good to excellent performances in the independent test set (0.73 < R² < 0.96) in predicting U.S. county-level prevalence of chronic conditions. Findings indicate that upstream domains (culture, politics, policy and environment) explain substantial variance in the prevalence of chronic conditions before downstream domains (behavior and risk) are introduced.

CONCLUSIONS: Despite a significant amount of attention given to the health challenges associated with chronic conditions, little progress has been made in reversing trends. The findings presented here propose a new approach to this complex issue that focuses on the forcing factors that lie upstream from health behaviors to improve downstream health outcomes.

PMID:42385291 | DOI:10.1016/j.puhe.2026.106404