High casein concentration induces diarrhea through mTOR signal pathway inhibition in post-weaning piglets.

Weaning is one of the most challenging periods in a pig's life, during which piglets suffer from nutrition and other issues. Post-weaning diarrhea is one of the major health problems in the pig industry, leading to high morbidity and mortality rates. Previous studies have demonstrated that both the source and concentration of proteins are closely associated with post-weaning diarrhea in piglets. This study was conducted to prevent and control post-weaning diarrhea by selecting different dietary protein concentrations. To eliminate interference from other protein sources, casein was used as the only protein source in this study. Fourteen piglets (weighing 8.43 ± 0.3 kg, weaned on the 28th day) were randomly assigned to two dietary protein groups: a low-protein group (LP, containing 17% casein) and a high-protein group (HP, containing 30% casein). The experiment lasted 2 weeks, during which all piglets had ad libitum access to food and water. Diarrhea was scored on a scale from 1 to 3 (where 1 indicates normal stools and 3 indicates watery diarrhea), and growth performance measurements were recorded daily. The results showed that the piglets in the HP group had persistent diarrhea during the whole study, whereas no diarrhea was observed among piglets in the control group. The body weights and feed intake were significantly lower in piglets in the HP group compared to those in the LP group (p < 0.05). The gastrointestinal pH was significantly higher in piglets in the HP group than those in the LP group (p < 0.05). The intestinal tract microorganisms of the piglets in both groups were significantly affected by the protein concentration of the diet. A diet with high casein concentration significantly reduced the microbiota diversity. Compared to the LP group, the 30% casein diet decreased the abundance of Firmicutes, Bacteroidetes, and Actinobacteria at the phylum level and the relative abundance of Ruminococcus at the genus level. Diarrhea-related mRNA abundances were analyzed by the real-time polymerase chain reaction (PCR) in the intestine of piglets, and the results showed that the HP concentration markedly decreased the expression of solute carriers (SLC, p < 0.05). The mammalian target of rapamycin-mTOR signaling pathway (p < 0.01) was activated in the HP group. In conclusion, a high-protein diet induced post-weaning diarrhea, decreased growth performance, increased gastrointestinal pH, and reduced expression of solute carrier proteins. However, the relationship between high dietary casein feed and post-weaning diarrhea remains unclear and needs to be explored further.

Nanomedicines with Versatile GSH-Responsive Linkers for Cancer Theranostics.

Glutathione (GSH)-responsive nanomedicines have generated significant interest in biochemistry, oncology, and material sciences due to their diverse applications, including chemical and biological sensors, diagnostics, and drug delivery systems. The effectiveness of these smart GSH-responsive nanomedicines depends critically on the choice of GSH-responsive linkers. Despite their crucial role, comprehensive reviews of GSH-responsive linkers are scarce, revealing a gap in the current literature. This review addresses this gap by systematically summarizing various GSH-responsive linkers and exploring their potential applications in cancer treatment. We provide an overview of the mechanisms of action of these linkers and their bioapplications, evaluating their advantages and limitations. The insights presented aim to guide the development of advanced GSH-responsive agents for cancer diagnosis and therapy.

Unraveling the key role of chromatin structure in cancer development through epigenetic landscape characterization of oral cancer.

Epigenetic alterations, such as those in chromatin structure and DNA methylation, have been extensively studied in a number of tumor types. But oral cancer, particularly oral adenocarcinoma, has received far less attention. Here, we combined laser-capture microdissection and muti-omics mini-bulk sequencing to systematically characterize the epigenetic landscape of oral cancer, including chromatin architecture, DNA methylation, H3K27me3 modification, and gene expression. In carcinogenesis, tumor cells exhibit reorganized chromatin spatial structures, including compromised compartment structures and altered gene-gene interaction networks. Notably, some structural alterations are observed in phenotypically non-malignant paracancerous but not in normal cells. We developed transformer models to identify the cancer propensity of individual genome loci, thereby determining the carcinogenic status of each sample. Insights into cancer epigenetic landscapes provide evidence that chromatin reorganization is an important hallmark of oral cancer progression, which is also linked with genomic alterations and DNA methylation reprogramming. In particular, regions of frequent copy number alternations in cancer cells are associated with strong spatial insulation in both cancer and normal samples. Aberrant methylation reprogramming in oral squamous cell carcinomas is closely related to chromatin structure and H3K27me3 signals, which are further influenced by intrinsic sequence properties. Our findings indicate that structural changes are both significant and conserved in two distinct types of oral cancer, closely linked to transcriptomic alterations and cancer development. Notably, the structural changes remain markedly evident in oral adenocarcinoma despite the considerably lower incidence of genomic copy number alterations and lesser extent of methylation alterations compared to squamous cell carcinoma. We expect that the comprehensive analysis of epigenetic reprogramming of different types and subtypes of primary oral tumors can provide additional guidance to the design of novel detection and therapy for oral cancer.

Unlocking the multifaceted molecular functions and diverse disease implications of lactylation.

In recent years, a significant breakthrough has emerged in biology, the identification of lactylation, a novel post-translational process. This intriguing modification is not limited to a specific class of proteins but occurs across a diverse range, including histones, signalling molecules, enzymes, and substrates. It can exert a broad regulatory role in various diseases, ranging from developmental anomalies and neurodegenerative disorders to inflammation and cancer. Thus, it presents exciting opportunities for exploring innovative treatment approaches. As a result, there has been a recent surge of research interest, leading to a deeper understanding of the molecular mechanisms and regulatory functions underlying lactylation within physiological and pathological processes. Here, we review the detection and molecular mechanisms of lactylation, from biological functions to disease effects, providing a systematic overview of the mechanisms and functions of this post-translational modification.

Differences in the landscape of colonized microorganisms in different oral potentially malignant disorders and squamous cell carcinoma: a multi-group comparative study.

BACKGROUND: The role of microbes in diseases, especially cancer, has garnered significant attention. However, research on the oral microbiota in oral potentially malignant disorders (OPMDs) remains limited. Our study investigates microbial communities in OPMDs. MATERIALS AND METHODS: Oral biopsies from19 oral leukoplakia (OLK) patients, 19 proliferative verrucous leukoplakia (PVL) patients, 19 oral lichen planus (OLP) patients, and 19 oral lichenoid lesions (OLL) patients were obtained. 15 SCC specimens were also collected from PVL patients. Healthy individuals served as controls, and DNA was extracted from their paraffin-embedded tissues. 2bRAD-M sequencing generated taxonomic profiles. Alpha and beta diversity analyses, along with Linear Discriminant Analysis effect size analysis, were conducted. RESULTS: Our results showed the microbial richness and diversity were significantly different among groups, with PVL-SCC resembling controls, while OLK exhibited the highest richness. Each disease group displayed unique microbial compositions, with distinct dominant bacterial species. Noteworthy alterations during PVL-SCC progression included a decline in Fusobacterium periodonticum and an elevation in Prevotella oris. CONCLUSIONS: Different disease groups exhibited distinct dominant bacterial species and microbial compositions. These findings offer promise in elucidating the underlying mechanisms of this disease.

Identification of genomic alteration and prognosis using pathomics-based artificial intelligence in oral leukoplakia and head and neck squamous cell carcinoma: A multicenter experimental study.

BACKGROUND: Loss of chromosome 9p is an important biomarker in the malignant transformation of oral leukoplakia (OLK) to head and neck squamous cell carcinoma (HNSCC), and is associated with the prognosis of HNSCC patients. However, various challenges have prevented 9p loss from being assessed in clinical practice. The objective of this study was to develop a pathomics-based artificial intelligence (AI) model for the rapid and cost-effective prediction of 9p loss (9PLP). MATERIALS AND METHODS: 333 OLK cases were retrospectively collected with hematoxylin and eosin (H&E)-stained whole slide images and genomic alteration data from multicenter cohorts to develop the genomic alteration prediction AI model. They were divided into a training dataset (n=217), a validation dataset (n=93), and an external testing dataset (n=23). The latest Transformer method and XGBoost algorithm were combined to develop the 9PLP model. The AI model was further applied and validated in two multicenter HNSCC datasets (n=42, n=365, respectively). Moreover, the combination of 9PLP with clinicopathological parameters was used to develop a nomogram model for assessing HNSCC patient prognosis. RESULTS: 9PLP could predict chromosome 9p loss rapidly and effectively using both OLK and HNSCC images, with the area under the curve achieving 0.890 and 0.825, respectively. Furthermore, the predictive model showed high accuracy in HNSCC patient prognosis assessment (the area under the curve was 0.739 for 1-year prediction, 0.705 for 3-year prediction, and 0.691 for 5-year prediction). CONCLUSION: To the best of our knowledge, this study developed the first genomic alteration prediction deep learning model in OLK and HNSCC. This novel AI model could predict 9p loss and assess patient prognosis by identifying pathomics features in H&E-stained images with good performance. In the future, the 9PLP model may potentially contribute to better clinical management of OLK and HNSCC.

Hot Deformation Behavior and Microstructure Evolution of a Graphene/Copper Composite.

Graphene/copper composites are promising in electronic and energy fields due to their superior conductivity, but microstructure control during thermal mechanical processing (TMP) remains a crucial issue for the manufacturing of high-performance graphene/copper composites. In this study, the hot deformation behavior of graphene/copper composites was investigated by isothermal compression tests at deformation temperatures of 700~850 °C and strain rates of 0.01~10 s-1, and a constitutive equation based on the Arrhenius model and hot processing map was established. Results demonstrate that the deformation mechanism of the graphene/copper composites mainly involves dynamic recrystallization (DRX), and such DRX-mediated deformation behavior can be accurately described by the established Arrhenius model. In addition, it was found that the strain rate has a stronger impact on the DRX grain size than the deformation temperature. The optimum deformation temperature and strain rate were determined to be 800 °C and 1 s-1, respectively, with which a uniform microstructure with fine grains can be obtained.

Mast Cell Infiltration and Subtype Promote Malignant Transformation of Oral Precancer and Progression of Oral Cancer.

The role of mast cell (MC), a common myeloid-derived immune cell, in the development of oral squamous cell carcinoma (OSCC) is unclear. The aim of this study was to investigate MC infiltration in oral precancer and oral cancer. The evaluation of immune cell infiltration and its association with prognosis in OSCC used RNA sequencing and multiple public datasets. Multiplex immunofluorescence was used to explore the infiltration of MC in the microenvironment of OSCC and oral precancer and the interaction with CD8+ cells. The role of MC in OSCC progression was verified by in vivo experiments. The resting MC infiltration was mainly present in oral precancer, whereas activated MC infiltration was significantly higher in OSCC. Activated MC was associated with malignant transformation of oral precancer and poor prognosis of OSCC. In vivo studies showed that MC promoted the growth of OSCC. The infiltration of activated MC was negatively correlated with the infiltration of CD8+ T cells. The subtype of MC containing tryptase without chymase (MCT) was significantly higher in OSCC compared with oral precancer and was associated with poor survival. Furthermore, spatial distance analysis revealed a greater distance between MCT and CD8+ cells, which was also linked to poor prognosis in OSCC. Cox regression analysis showed that MCT could be a potential diagnostic and prognostic biomarker. This study provides new insights into the role of MC in the immune microenvironment of OSCC. It might enhance the immunotherapeutic efficacy of OSCC by developing targeted therapies against MC. SIGNIFICANCE: In this study, we investigated the role of mast cells (MC) in oral precancer and oral cancer and demonstrated that MCs are involved in oral cancer progression and may serve as a potential diagnostic and prognostic marker. It might improve the immunotherapeutic efficacy through developing targeted therapies against MCs.

A comprehensive survey of the application of swarm intelligent optimization algorithm in photovoltaic energy storage systems.

With the rapid development of renewable energy, photovoltaic energy storage systems (PV-ESS) play an important role in improving energy efficiency, ensuring grid stability and promoting energy transition. As an important part of the micro-grid system, the energy storage system can realize the stable operation of the micro-grid system through the design optimization and scheduling optimization of the photovoltaic energy storage system. The structure and characteristics of photovoltaic energy storage system are summarized. From the perspective of photovoltaic energy storage system, the optimization objectives and constraints are discussed, and the current main optimization algorithms for energy storage systems are compared and evaluated. The challenges and future development of energy storage systems are briefly described, and the research results of energy storage system optimization methods are summarized. This paper summarizes the application of swarm intelligence optimization algorithm in photovoltaic energy storage systems, including algorithm principles, optimization goals, practical application cases, challenges and future development directions, providing new ideas for better promotion and application of new energy photovoltaic energy storage systems and valuable reference.

Determination of Volatile Halogenated Hydrocarbons in Drinking and Environmental Waters by Headspace Gas Chromatography.

Volatile halogenated hydrocarbons (VHHs) are annually produced and released into the environment, posing a threat to public health. In this study, a simple, rapid, sensitive and automated method based on headspace and gas chromatography (GC) with electron-capture detection was described for the determination of VHHs in different concentration levels in water samples. The proposed headspace GC method was initially optimized, and the optimum experimental conditions found were 10-mL water sample containing 20% w/v sodium chloride placed in a 20-mL vial and stirred at 60°C for 35 min, and then 14 VHHs were well separated on DB-35 MS capillary column with a split ratio of 12.5: 1. The limits of detection were in the low µg/L level, ranging between 0.01 and 0.6 µg/L. Finally optimized method was applied for determination 14 VHHs in drinking and environmental waters. The total mean concentrations of VHHs were 34.962, 26.183, 3.228 and 647.344 µg/L in tap water, purified water with 1-year-old filter element, seawater and effluents, respectively. However, no VHHs was detected in purified water with a new filter element. The main composition is different among different water matrix, which may be attributed to their different sources.

The prevalence, diagnostic accuracy and genotype-phenotype correlation of GNAS mutations in fibrous dysplasia: a meta-analysis.

Background: There is inconsistent evidence regarding the accuracy of GNAS mutations identification for the diagnosis of FD/MAS. This study was performed to estimate the prevalence and diagnostic accuracy of GNAS mutations detection and to preliminarily investigate the genotype-phenotype correlation in FD patients. Methods: Five electronic databases were searched from 1995 to 2024 using search terms related to GNAS and fibrous dysplasia. Observational studies of FD patients undergoing GNAS mutation detection in FD were included. Results: A total of 878 FD patients were included. The pooled prevalence of GNAS mutations in FD based on the random effects model was 74% (95% CI = 64%-83%). Regarding diagnostic accuracy, a sensitivity of 0.83 (95% CI, 0.65-0.96), specificity of 0.99 (95% CI, 0.98-1.00) and the area under the receiver operating characteristic curve of 98.38% were found. Additionally, meta-analysis and Fisher's test showed the GNAS mutation types were significantly associated with FD types (OR = 3.51, 95% CI = 1.05 to 11.72; p < 0.05). Conclusion: A high detection rate of GNAS mutations occurred in FD, and its detection is reliable for diagnosing FD. Additionally, GNAS mutation type was types were significantly associated with FD type. Systematic Review Registration: Identifier CRD42024553469.

Different effects of acute and chronic oxidative stress on the intestinal flora and gut-liver axis in weaned piglets.

Introduction: Oxidative stress plays a pivotal role in modulating the balance of intestinal flora and the gut-liver axis, while also serving as a key determinant of the growth potential of weaned piglets. However, few studies have subdivided and compared acute and chronic oxidative stress. Methods: In this study, an intestinal model of acute oxidative stress in weaned piglets using paraquat (PQ) and a chronic oxidative stress model using D-galactosa in weaned piglets were conducted. And we further systematically compare their effects. Results: Both acute and chronic oxidative stress models impaired intestinal barrier function and liver function. Chronic stress caused by D-galactose can result in severe redox dysregulation, while acute stress caused by paraquat can lead to inflammation and liver damage. Additionally, the components involved in the CAR pathway were expressed differently. Chronic or acute oxidative stress can reduce the diversity and composition of intestinal flora. In the PQ group, the richness of Mogibacterium and Denitratisoma improved, but in the D-gal group, the richness of Catenisphaera and Syntrophococcus increased. Discussion: Not only does this research deepen our understanding of the effects of acute and chronic oxidative stress on intestinal functions, but it also characterizes characteristic changes in the gut flora, potentially identifying novel therapeutic targets and opening new avenues for future research.

High-Performance Tin Oxide Thin-Film Transistors Realized by Codoping and Their Application in Logic Circuits.

Tin oxide is a promising channel material, offering the advantages of being low-cost and environmentally friendly and having a wide band gap. However, despite the high electron mobility of SnO2 in bulk, the corresponding thin-film transistors (TFTs) generally exhibit moderate performance, hindering their widespread application. Herein, we proposed a codoping strategy to improve both the electrical property and the stability of SnO2 TFTs. A comparative analysis between doped and undoped SnO2 was conducted. It is observed that taking advantage of the difference in ionic radii between two dopants (indium and gallium) and the tin ions in the host lattice can effectively reduce impurity-induced strain. Additionally, we investigated the effect of codoping content on SnO2 TFTs. The optimal codoped SnO2 (TIGO) TFTs demonstrate high performance, featuring a field-effect mobility of 15.9 cm2/V·s, a threshold voltage of 0.2 V, a subthreshold swing of 0.5 V/decade, and an on-to-off current ratio of 2.2 × 107. Furthermore, the devices show high stability under both positive and negative bias stress conditions with a small threshold voltage shift of 1.8 and -1.2 V, respectively. Utilizing the TIGO TFTs, we successfully constructed a resistor-loaded unipolar inverter with a high gain of 10.76. This study highlights the potential of codoped SnO2 TFTs for advanced applications in electronic devices.

Adaptive Weighted Data Fusion for Line Structured Light and Photometric Stereo Measurement System.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

Rapid Determination of Tetracyclines in Drinking and Environmental Waters Using Fully Automatic Solid-Phase Extraction with Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry.

The abuse and irrational use of tetracyclines (TCs) in human medicine and animal husbandry has become a serious concern, affecting the ecological environment and human health. The aim of this study was to develop a sensitive and selective method using fully automatic solid-phase extraction coupled with ultra-performance liquid chromatography-tandem mass spectrometry for the determination of twelve TCs in water. Four isotope-labeled internal standards for TCs were used to correct matrix effects. Several parameters affecting extraction efficiency were systematically optimized, and the optimum experimental conditions found were 1.0 L water sample with 0.5 g/L Na2EDTA (pH 3.0) extracted and enriched by CNW HLB cartridge and eluted by 4 mL of acetone:methanol (v/v, 1:1). The enrichment factors were up to 798-1059 but only requiring about 60 min per six samples. Under the optimized conditions, the linearity of the method ranged from 0.2 to 100 µg/L for 12 TCs, the detection limits were as low as 0.01-0.15 ng/L, and the recoveries were in the range of 70%-118%, with relative standard deviations less than 15%. The developed method can be successfully utilized for the determination of 12 TCs in pure water, tap water, river water, and mariculture seawater. In summary, three and six TCs were detected in river water and mariculture seawater, respectively, with total concentrations of 0.074-0.520 ng/L (mean 0.248 ng/L) and 0.792-58.369 ng/L (12.629 ng/L), respectively. Tetracycline (TC) and oxytetracycline (OTC) were the dominant TCs in river water, while doxytetracycline (DXC) and OTC were dominant in mariculture seawater.

EPR-Net: constructing a non-equilibrium potential landscape via a variational force projection formulation.

We present EPR-Net, a novel and effective deep learning approach that tackles a crucial challenge in biophysics: constructing potential landscapes for high-dimensional non-equilibrium steady-state systems. EPR-Net leverages a nice mathematical fact that the desired negative potential gradient is simply the orthogonal projection of the driving force of the underlying dynamics in a weighted inner-product space. Remarkably, our loss function has an intimate connection with the steady entropy production rate (EPR), enabling simultaneous landscape construction and EPR estimation. We introduce an enhanced learning strategy for systems with small noise, and extend our framework to include dimensionality reduction and the state-dependent diffusion coefficient case in a unified fashion. Comparative evaluations on benchmark problems demonstrate the superior accuracy, effectiveness and robustness of EPR-Net compared to existing methods. We apply our approach to challenging biophysical problems, such as an eight-dimensional (8D) limit cycle and a 52D multi-stability problem, which provide accurate solutions and interesting insights on constructed landscapes. With its versatility and power, EPR-Net offers a promising solution for diverse landscape construction problems in biophysics.

Clinicopathological characteristics and diagnostic accuracy of BRAF mutations in ameloblastoma: A Bayesian network analysis.

OBJECTIVE: This Bayesian network meta-analysis was performed to analyze the associations between clinicopathological characteristics and BRAF mutations in ameloblastoma (AM) patients and to evaluate the diagnostic accuracy. MATERIALS AND METHODS: Four electronic databases were searched from 2010 to 2024. The search terms used were specific to BRAF and AM. Observational studies or randomized controlled trials were considered eligible. The incidence of BRAF mutation and corresponding clinicopathological features in AM patients were subjected to Bayesian network analyses and diagnostic accuracy evaluation. RESULTS: A total of 937 AM patients from 20 studies were included. The pooled prevalence of BRAF mutations in AM patients was 72%. According to the Bayesian network analysis, BRAF mutations are more likely to occur in younger (odds ratio [OR], 2.3; credible interval [CrI]: 1.2-4.5), mandible site (OR, 3.6; 95% CrI: 2.7-5.2), and unicystic (OR, 1.6; 95% CrI: 1.1-2.4) AM patients. Similarly, higher diagnostic accuracy was found in the younger, mandible, and unicystic AM groups. CONCLUSIONS: The incidence, risk, and diagnostic accuracy of BRAF mutation in AM were greater in younger patients, those with mandible involvement, and those with unicystic AM than in patients with other clinicopathological features. In addition, there was a strong concordance in the diagnostic accuracy between molecular tests and immunohistochemical analysis.

Effects of fermented sweet potato residue on nutrient digestibility, meat quality, and intestinal microbes in broilers.

This study aimed to investigate the effects of different proportions of dietary fermented sweet potato residue (FSPR) supplementation as a substitute for corn on the nutrient digestibility, meat quality, and intestinal microbes of yellow-feathered broilers. Experiment 1 (force-feeding) evaluated the nutrient composition and digestibility of mixtures with different proportions of sweet potato residue (70%, 80%, 90%, and 100%) before and after fermentation. In Experiment 2 (metabolic growth), a total of 420 one-day-old yellow-feathered broilers were randomly allocated to 4 groups and fed corn-soybean meal-based diets with 0, 5%, 8%, and 10% FSPR as a substitute for corn. The force-feeding and metabolic growth experiments were performed for 9 and 70 d, respectively. The treatment of 70% sweet potato residue (after fermentation) had the highest levels of crude protein, ether extract, and crude fiber and improved the digestibility of crude protein and amino acids (P < 0.05). Although dietary FSPR supplementation at different levels had no significant effect on growth performance and intestinal morphology, it improved slaughter rate, half-chamber rate, full clearance rate, and meat color, as well as reduced cooking loss in the breast and thigh muscles (P < 0.05). Dietary supplementation with 8% and 10% FSPR increased the serum immunoglobulin M and immunoglobulin G levels in broilers (P < 0.05). Furthermore, 10% FSPR increased the Shannon index and Ruminococcaceae_UCG-014, Ruminococcaceae_UCG-010 and Romboutsia abundances and decreased Sutterella and Megamonas abundances (P < 0.05). Spearman's correlation analysis showed that meat color was positively correlated with Ruminococcaceae_UCG-014 (P < 0.05) and negatively correlated with Megamonas (P < 0.05). Collectively, 70% sweet potato residue (after fermentation) had the best nutritional value and nutrient digestibility. Dietary supplementation with 8% to 10% FSPR as a substitute for corn can improve the slaughter performance, meat quality, and intestinal microbe profiles of broilers. Our findings suggest that FSPR has the potential to be used as a substitute for corn-soybean meals to improve the meat quality and intestinal health of broilers.

CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.

OBJECTIVE: In this study, our aim was to develop and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery. MATERIALS AND METHODS: We enrolled 220 patients with confirmed FD or OF. We extracted radiomic features from nonenhanced CT images. Following dimensionality reduction and feature selection, we constructed radiomic models using logistic regression, support vector machine, random forest, light gradient boosting machine, and eXtreme gradient boosting. We then identified the best radiomic model using receiver operating characteristic (ROC) curve analysis. After combining radiomics features with clinical features, we developed a comprehensive model. ROC curve and decision curve analysis (DCA) demonstrated the models' robustness and clinical value. RESULTS: We extracted 1834 radiomic features from CT images, reduced them to eight valuable features, and achieved high predictive efficiency, with area under curves (AUC) exceeding 0.95 for all the models. Ultimately, our combined model, which integrates radiomic and clinical data, displayed superior discriminatory ability (AUC: training cohort 0.970; test cohort 0.967). DCA highlighted its optimal clinical efficacy. CONCLUSION: Our combined model effectively differentiates between FD and OF, offering a noninvasive and efficient approach to clinical decision-making.

Spatial transition tensor of single cells.

Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics associated with multiple cell states and transition paths. Here we present spatial transition tensor (STT), a method that uses messenger RNA splicing and spatial transcriptomes through a multiscale dynamical model to characterize multistability in space. By learning a four-dimensional transition tensor and spatial-constrained random walk, STT reconstructs cell-state-specific dynamics and spatial state transitions via both short-time local tensor streamlines between cells and long-time transition paths among attractors. Benchmarking and applications of STT on several transcriptome datasets via multiple technologies on epithelial-mesenchymal transitions, blood development, spatially resolved mouse brain and chicken heart development, indicate STT's capability in recovering cell-state-specific dynamics and their associated genes not seen using existing methods. Overall, STT provides a consistent multiscale description of single-cell transcriptome data across multiple spatiotemporal scales.