Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications. Bayesian Modeling: Uses R-INLA to predict soil geochemistry across large spatial extents. Covariate Integration: Incorporates environmental variables to increase predictive accuracy. Raster Generation: Produces continuous geospatial layers of element and mineral distributions of the conterminous United States for a variety of applications.

Chronic kidney disease (CKD) has emerged as a critical public health challenge worldwide, and organ donor shortages underscore the urgent need for alternative therapeutic strategies. Advances in stem cell technologies have enabled the generation of kidney organoids, providing innovative platforms to model renal development, investigate disease mechanisms, support drug discovery, and explore applications in regenerative medicine. Yet, limitations such as immature tissue architecture, insufficient vascularisation, and unaddressed safety concerns still hinder their translation into regenerative medicine. In this review, we summarise the fundamentals of kidney development, current differentiation approaches, and the signalling and epigenetic mechanisms underlying organoid lineage specification. We further highlight the roles of bioengineering innovations and single-cell transcriptomics in establishing evaluation frameworks and enhancing structural complexity. We finally emphasise that existing optimisation frameworks, primarily focused on improving differentiation efficiency and enforcing relatively restricted lineage specification, may prove inadequate for bridging the gap to clinical translation. Instead, the most promising paradigm shift involves the convergence of bioengineering modulation and high-resolution functional assessment to facilitate the synchronised advancement of organoid complexity and physiological utility.

Wine origin mislabelling undermines geographical indication (GI) protection and market confidence, calling for robust, data-driven authentication tools adapted to arid continental viticulture. Here, we established an integrated element-isotope fingerprinting and chemometric data-fusion framework to discriminate the region of origin of Xinjiang wines. A total of 473 wines from the 2021 vintage were collected across seven sub-regions (Changji, Hami, Heshuo, Kuerle, Shihezi, Wujiaqu, and Yanqi). Twenty-seven elements were quantified by ICP-MS, and δ13C (ethanol) and δ18O (water) were measured by IRMS. After z-score standardisation, PCA revealed partial clustering. At the same time, OPLS-DA improved separation and highlighted Li, Na, K, Sr, several trace/transition elements (e.g., Cu, V, Mn, and As) and δ18O as the main discriminants (VIP > 1). Correlation analysis indicated that climatic aridity, particularly evaporation, temperature and sunshine duration, was a key driver of isotopic enrichment and elemental differentiation. Supervised classification further demonstrated strong predictive performance, with Random Forest achieving the highest accuracy (92 % in 10-fold cross-validation), followed by ANN (88 %), SVM (86 %) and recursive partitioning (79 %). Overall, integrating multi-element and stable-isotope signatures with data-fusion modelling provides a reproducible and accurate approach for terroir differentiation and region-of-origin authentication of Xinjiang wines, supporting GI enforcement in arid viticultural regions.

This study investigated the physicochemical and nutritional changes in mahi-mahi (Coryphaena hippurus) dorsal epaxial muscle during a 42-day dry-aging period (3°C, 83% RH, 0.8 m/s laminar airflow). While dry-aging is well-established to enhance tenderness in slaughter animals' meat, its application to seafood, particularly species with high polyunsaturated fatty acid (PUFA) content, remains scientifically underexplored due to risks of oxidative degradation. Fresh specimens were processed within 2 hours post-capture and analyzed at 0, 15, 27, and 42 days. Moisture decreased from 76.9% to 61.5%, while protein content increased from 20.9% to 35.4% due to concentration and proteolysis. Lipid oxidation of thiobarbituric acid reactive substances increased at 0.56mg MDA/kg by day 27, indicating substantial degradation of PUFAs. Hardness initially decreased by 76% at day 15, and then partially recovered due to protein aggregation and moisture loss. Color parameters shifted toward darker (L decrease) and greenish (a decrease) tones, reflecting myoglobin oxidation. The fatty acid exhibited early lipolysis (increased oleic acid C18:1 ω-9) followed by oxidative degradation. Nutritional indices (atherogenic index, thrombogenic index, hypocholesterolemic/hypercholesterolemic fatty acid ratio) improved up to day 27, decreasing thereafter. These findings suggested that dry-aging mahi-mahi for 27 days optimized quality by balancing texture development with acceptable oxidative stability, providing a scientific basis for premium dry-aged seafood products. PRACTICAL APPLICATIONS: The study demonstrated that mahi-mahi can be commercially dry-aged for 5-27 days (3°C and 83% RH) to enhance texture. This process concentrated proteins and developed desirable sensory attributes through controlled enzymatic activity and moisture loss while maintaining nutritional quality before oxidative rancidity increased. By adopting this method, seafood producers could offer a premium, value-added product aligned with culinary additive-free trends, such as novel foods. Routine monitoring of lipid oxidation and moisture loss was recommended to ensure consistent quality. This research provided a scientifically validated approach for product diversification and market differentiation within the seafood industry.

MRI-based deep learning and radiomics for preoperative prediction of P53abn endometrial cancer: A multicenter study.

Dosimetric study of dose de-escalation using MRI-guidance for Pd-103 low-dose-rate brachytherapy in prostate cancer.

Acute febrile illnesses are frequently attributed to malaria in endemic countries, despite the circulation of arboviruses whose vectors share the same breeding environments. This study assessed the molecular prevalence of arboviral and arboviral-malaria co-infections and associated epidemiological and hematological characteristics among febrile children in Libreville, Gabon. Plasma samples from 151 febrile children attending a malaria sentinel surveillance site between September and October 2022 were retrospectively analyzed. Samples were screened by pan-DENV, CHIKV and ZIKV RT-qPCR for arboviruses diagnosis. DENV-positive samples underwent additional molecular characterization, including serotype-specific RT-PCR and pan-flavivirus PCR targeting the NS5 region. Malaria was diagnosed by microscopy, and demographic and hematological data were recorded. DENV RNA was detected in 18.5% of patients, with serotype identification confirming DENV-1 and DENV-3 circulation and suggesting possible DENV-4. No CHIKV or ZIKV infections were detected. Malaria prevalence was 56.9%, and 9.3% had dengue-malaria co-infection. Dengue predominated in children <5 years, whereas those aged 5-10 years had higher odds of malaria (OR: 2.61 IC95%: [1.07-7.02]; p=0.03) and co-infection (OR:16.28 IC95% [1.85-79.40]; p=0.002). DENV infections occurred mainly in urban/peri‑urban areas , while malaria was associated with rural residence (p=0.03). Severe anemia was most common in malaria (p=0.02), and thrombocytopenia was most marked in co-infected patients (p < 0.01). These findings confirm active DENV circulation and malaria-dengue co-endemicity in Libreville, highlighting the need to strengthen differential diagnostic approaches and surveillance strategies for febrile illnesses in urban Gabon.

Species-dependent colony size variation of environmental Enterococcus on sodium azide-containing selective agar.

ABSTRACT This paper introduces a new framework for the control of networked control systems (NCSs) consisting of a continuous‐time plant, a discrete‐time controller, and a wireless network with delays, via the differential linear matrix inequality (DLMI)‐based approach. We first derive a hybrid linear system (HLS) representation of NCSs by defining two flow dynamic equations before and after the sampling instants and one jump equation at the sampling instants. Based on the HLS representation, we derive a DLMI‐based necessary and sufficient condition for the exponential stability of NCSs with known constant delays. This also allows us to establish a controller ensuring that the NCS is exponentially stable and the resulting ‐gain is less than a pre‐given . The relevant arguments are further extended to a more involved problem of NCSs with time‐varying unknown delays. In other words, we obtain some DLMI‐based conditions characterizing the exponential stability and a controller synthesis for suppressing the ‐gain of such networked systems. Finally, numerical examples are provided to validate the effectiveness of the proposed DLMI‐based arguments.

To retrospectively investigate the clinical characteristics and etiological spectrum of infantile cholestasis, with an emphasis on evolving diagnostic approaches. Clinical data of 326 infants diagnosed with infantile cholestasis at the Children's Hospital Affiliated to Shandong University from January 2020 to December 2025 were retrospectively analyzed. Etiological distribution was systematically examined. Serum bile acid profiling was performed for suspected bile acid synthesis defects, and genetic sequencing for unexplained or suspected genetic cholestasis. Among 326 infants with infantile cholestasis, 56.7% presented with light- or clay-colored stools, 62.9% had hepatomegaly, and 8.3% had comorbidities. The etiological spectrum included biliary tract anomalies [50.6%, including 161 biliary atresia (BA)], genetic metabolic liver diseases (9.8%, n = 32), infectious causes (7.4%), drug-related causes (3.4%), idiopathic cholestasis (6.7%), other rare causes (0.9%), and undetermined etiology (21.2%). No significant differences in sex or age were observed between the genetic metabolic group (n = 32) and BA group (n = 161) (both P > 0.05). After excluding 165 surgical cases, genetic testing was performed in 55 of 161 remaining infants (34.2%), with pathogenic or likely pathogenic variants identified in 33 (60.0% detection rate) across 14 genes (e.g., JAG1, SLC25A13, ABCC2). In an exploratory subgroup analysis (genetic metabolic, n = 16; BA, n = 20), the BA subgroup showed significantly higher levels of matrix metalloproteinase-7 (MMP-7), direct bilirubin, and GGT (P = 0.002 for GGT), with no other significant differences between the two subgroups. The etiology of infantile cholestasis is complex and highly heterogeneous. Genetic testing improves the diagnostic yield of inherited metabolic liver diseases. Serum bile acid profiling provides metabolomic signatures for etiological differentiation. Conventional liver function tests combined with serum MMP-7 represent a simple, reliable, noninvasive approach for early differentiation of biliary atresia.

Abstract Reconstructing the trajectories of charged particles in high-energy collisions requires high precision to ensure reliable event reconstruction and accurate downstream physics analyses. In particular, both precise hit selection and transverse momentum estimation are essential to improve the overall resolution of reconstructed physics observables. Enhanced momentum resolution also enables more efficient trigger threshold settings, leading to more effective data selection within the given data acquisition constraints. In this paper, we introduce a novel endto-end tracking approach that employs the differentiable programming paradigm to incorporate physics priors directly into a machine learning model. This results in an optimized pipeline capable of simultaneously reconstructing tracks and accurately determining their transverse momenta. The model combines a graph attention network with differentiable clustering and fitting routines, and is trained using a composite loss that, due to its differentiable design, allows physical constraints to be back-propagated effectively through both the neural network and the fitting procedures. This proof of concept shows that introducing differentiable connections within the reconstruction process improves overall performance compared to an equivalent factorized and more standard-like approach, highlighting the potential of integrating physics information through differentiable programming.

Alzheimer’s disease (AD) develops as a progressive dementia condition through the step-by-step breakdown of nerve cells. Neurodegeneration in this context primarily results from metal ions, including copper, iron, zinc, and aluminum, building up in the system. The aggregation of amyloid-beta (Aβ) peptides and oxidative stress generation stem from metal ion involvement acting as defining characteristics of Alzheimer’s disease pathology. We developed a comprehensive mathematical model based on 24 coupled ordinary differential equations (ODEs) to represent the interactions between metal ions, Aβ peptides, reactive oxygen species (ROS), antioxidant defenses, and tau protein phosphorylation. The mathematical model monitors how metal ion concentrations change over time and examines their competitive binding effects, which trigger a series of reactions, resulting in oxidative stress and subsequent tau protein damage. The model uses analytical and numerical mathematical methods to expose nonlinear behaviors and threshold effects while offering mechanistic insights into the course of disease development. This model functions as a quantitative framework for assessing how therapeutic interventions that target metal dyshomeostasis and oxidative stress can potentially affect outcomes.

Life tables are essential tools to describe insect biology and to understand population responses to environmental factors. Two main approaches are used to represent life tables data: the differential approach provides the distribution of the stage-development times, from which statistics can be computed, and supports the development of biodemographic models; the integral approach provides the stage-frequency matrices and offers a global view of the biological life cycle. However, the two representations are not equivalent, and it is not possible to switch from the one to the other if the original raw data are no longer available. As stage-frequency matrices are available for many species, this study introduces a novel method to estimate the statistics coming from the differential life tables representation, such as the mean development time and its standard deviation, using frequency matrices when raw data are not available. The approach combines constrained least-squares optimization with stage-impulse response models to infer the distribution of the development time from stage-frequency data. The method was validated using datasets of Corcyra cephalonica and Drosophila suzukii, for which individual life history data was available. The results show that the estimated distributions of the development times and their statistics are in accordance with validation data, especially for early developmental stages. This method provides a valuable methodology for estimating the distribution of the stage-development times using stage-frequency matrices when raw data is inaccessible or when individual rearing is impractical.

This protocol describes a sequential differential centrifugation approach to enrich lipid droplets (LDs) of different sizes from bovine mammary epithelial cells (BMECs) and mammary tissues, enabling size-resolved analysis beyond conventional bulk LD isolation methods. As dynamic regulatory hubs of intracellular lipid metabolism, LDs serve critical functions by storing neutral lipids (such as triglycerides and cholesteryl esters) and coordinating their synthesis, hydrolysis, and transport. They play a central role in maintaining energy homeostasis, supporting membrane biogenesis, and facilitating cellular signal transduction. LD extraction is essential for investigating the regulatory mechanisms of lipid metabolism. Studying mammary gland lipid metabolism has significant implications for infant development, human health, agricultural economics, and fundamental cell biology. Therefore, we describe a differential centrifugation method for extracting LDs from BMECs and mammary gland tissue. In contrast to conventional bulk LD isolation approaches, this protocol enables size-based enrichment of LD subpopulations by sequentially adjusting centrifugal forces. The integrity and relative enrichment of LD fractions are preliminarily evaluated using BODIPY493/503 staining, providing a practical and reproducible approach for downstream analyses of lipid metabolism and LD-associated processes.

Prospective memory anchors upcoming activities in future time and space either cued externally (event-based prospective memory) or internally (time-based prospective memory). It is key to remain autonomous and can be enhanced using incentives. To examine the neuronal underpinnings of prospective memory and any performance improvement, we randomly assigned 58 healthy older participants (60-75 years old, 36 women) to time-based and focal event-based prospective memory tasks using 7T-fMRI, with or without incentives. Event-based and time-based prospective memory differ in their functional neuroanatomy. The focal event-based task required activity important for the perception of relevant changes in the environment and for adapting the focus of attention to then respond swiftly. The time-based task, in contrast, involved regions supporting cognitive control or serving as a multimodal information buffer. Incentives had no effect in time-based prospective memory but recruited brain regions important for attention thus improving cue recognition in event-based prospective memory. This highlights the differences between these two prospective memory types and the need for differential approaches depending on the type of memory demand.

A vital question in neuroscience is whether and how efficiently cellular models may be differentiated into functional neuronal cells in culture. Despite the frequent use of the human neuroblastoma cell line SH-SY5Y, differentiation protocols vary extensively, with the most common being differentiation via the addition of retinoic acid and brain-derived neurotrophic factor. However, due to the lack of a reliable evaluation method, their adequacy as synaptic models remains unclear. Here, we investigate whether SH-SY5Y cells constitute a functional model for synaptic studies by phenotypically and ultrastructurally analyzing synaptogenesis in SH-SY5Y cells subjected to different differentiation protocols. Electron microscopy (EM) techniques, including conventional EM, cryo-EM, and cryo-electron tomography, were systematically applied to characterize synaptogenesis in SH-SY5Y cells. Further characterization was performed using immunostaining and functional assays, such as live exocytosis assays and whole-cell patch-clamp electrophysiology. Despite exhibiting some presynaptic-like features, differentiated SH-SY5Y cells do not form morphologically or functionally complete synapses under the conditions tested. Immunostaining results were consistent with previous findings, showing synaptic markers. However, functional investigations did not detect synaptic activity. High-throughput EM analyses revealed an absence of synaptic structures in these cells. Additionally, an alternative differentiation approach incorporating additional neurotrophic factors promoted the formation of presynaptic-like compartments containing synaptic vesicle-like vesicles (SVLVs). In contrast to typical synaptic vesicles, these SVLVs exhibited a pleomorphic size distribution and lacked connectors. These findings underscore the need for cautious interpretation of results derived from SH-SY5Y cells when investigating molecular synaptic architecture or function, as well as neurodegenerative diseases.

Interval differential equation approach for inventory systems with green and price-dependent nonlinear demand

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have potential applications in treating cardiovascular disease but are currently limited in their clinical translation. This can be attributed in large part to the complex molecular and cellular interactions that underly cardiac differentiation, with current differentiation approaches yielding heterogeneous outcomes due to inadequate understanding and control of these interactions. We hypothesize that clonal lineage-dependent responses to differentiation contribute to these heterogeneous outcomes, and as such cardiac differentiations can be improved by tracking and controlling for hiPSC clonal heterogeneity, a variable often overlooked in current differentiation approaches. "Fate priming", wherein clonal lineage identity determines differentiation fate, has been demonstrated in other stem cell differentiation pathways. We investigated fate priming in hiPSC cardiac differentiation using the ClonMapper cell barcoding platform to label, track, and isolate distinct hiPSC lineages from the same cell line. We show that certain hiPSC lineages preferentially differentiate into hiPSC-CMs or non-CMs. After isolating lineages with apparent fate priming, we found significant differences in cardiac differentiation outcomes between these single-clone populations and heterogeneous, multi-clone hiPSC populations. These findings indicate that lineage identity influences hiPSC cardiac differentiation outcomes.

The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and prognosis. However, current clinical practice relies on multi-step staining and labelling processes that are time-intensive and costly, requiring highly specialised expertise. In this study, we propose a label-free methodology that facilitates autofluorescence imaging of unstained NSCLC samples and deep learning (DL) techniques to distinguish between non-cancerous tissue, adenocarcinoma (AC), squamous cell carcinoma (SqCC), and other subtypes (OS). We conducted DL-based classification and generated virtual immunohistochemical (IHC) stains, including thyroid transcription factor-1 (TTF-1) for AC and p40 for SqCC. We evaluated these methods using two types of autofluorescence imaging: intensity imaging and lifetime imaging. The results demonstrate the exceptional ability of this approach for NSCLC subtype differentiation, achieving an area under the curve above 0.981 and 0.996 for binary- and multi-class classification. Furthermore, this approach produces clinical-grade virtual IHC staining, which was blind-evaluated by three experienced thoracic pathologists. Our label-free NSCLC subtyping approach enables rapid and accurate diagnosis without the need for conventional tissue processing and staining. Both strategies can significantly accelerate diagnostic workflows and support efficient lung cancer diagnosis, without compromising clinical decision-making.

Pareto improving taxes with non-separable externalities: A differentiable approach