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The reconstruction of neural function and recovery of chronic damage following traumatic brain injury (TBI) remain significant clinical challenges. Exosomes derived from neural stem cells (NSCs) offer various benefits in TBI treatment. Numerous studies confirmed that appropriate preconditioning methods enhanced the targeted efficacy of exosome therapy. Interferon-gamma (IFN-γ) possesses immunomodulatory capabilities and is widely involved in neurological disorders. In this study, IFN-γ was employed for preconditioning NSCs to enhance the efficacy of exosome (IFN-Exo, IE) for TBI. miRNA sequencing revealed the potential of IFN-Exo in promoting neural differentiation and modulating inflammatory responses. Through low-temperature 3D printing, IFN-Exo was combined with collagen/chitosan (3D-CC-IE) to preserve the biological activity of the exosome. The delivery of exosomes via biomaterial scaffolds benefited the retention and therapeutic potential of exosomes, ensuring that they could exert long-term effects at the injury site. The 3D-CC-IE scaffold exhibited excellent biocompatibility and mechanical properties. Subsequently, 3D-CC-IE scaffold significantly improved impaired motor and cognitive functions after TBI in rat. Histological results showed that 3D-CC-IE scaffold markedly facilitated the reconstruction of damaged neural tissue and promoted endogenous neurogenesis. Further mechanistic validation suggested that IFN-Exo alleviated neuroinflammation by modulating the MAPK/mTOR signaling pathway. In summary, the results of this study indicated that 3D-CC-IE scaffold engaged in long-term pathophysiological processes, fostering neural function recovery after TBI, offering a promising regenerative therapy avenue.

Research and policy often focus on reducing attrition from educational trajectories leading to careers in science, technology, engineering, and mathematics (STEM), but many students change career plans "within" STEM. This study examined how changing career plans within STEM fields was associated with psychological indicators of career readiness. We conducted a large online survey of undergraduate students (N = 1,727) across 42 courses covering every major STEM discipline at a large U.S. research-intensive public university. Students reported about their career plans, whether plans had changed, motivation for those career plans, and satisfaction with and certainty of persisting with those plans. A trained team of coders classified whether students reported having STEM career plans at the time of the survey and at the beginning of college. Students who said they had changed career plans within STEM fields during college also reported lower motivation for their new career plans, satisfaction with those plans, and certainty of persisting in them, compared to students who retained consistent STEM career plans. With few exceptions, these associations held across students' gender, race, year in school, and STEM field of study. Within-STEM career plan changes were very common, reported by 55% of fourth-year STEM students. Women reported changing career plans within STEM fields more often than men. Results suggest that changing career plans within STEM is an important phenomenon to consider in preparing a qualified and diverse STEM workforce. Students who change career plans within STEM fields may need additional supports for their career motivation and satisfaction compared to students who do not change plans.

The ash content of rubber was determined by thermogravimetric analysis (TGA) and the effects of sample amount, sample representativeness, heating rate, combustion temperature and combustion atmosphere on the test results were studied and the repeatability and reproducibility of the method were determined. The results showed that the optimal conditions of TGA were sample mass between 10 mg and 20 mg, heating rate of 20 ℃/min or 30 ℃/min, combustion temperature for raw rubber and compounded rubber (or vulcanized rubber) of 550 ℃ and 650 ℃, respectively. The repeatability and reproducibility of TGA were all good. When ash mass fraction of 4 types of different rubbers were from 0.29% to 5.12%, the repeatability within laboratory was from 0.110% to 0.303%, and the reproducibility between laboratories was from 0.283% to 0.676%.

Edible plant oils are widely used in cooking, cosmetics, health supplement capsules, and other industries, due to their various health-promoting effects. There is increasing evidence that edible plant oils can modulate gut microbiota during their health-promoting effects in animal experiments and cohort or clinical studies. However, the information concerning the gut microbiota modulation of edible plant oils during their health-promoting effects is scattered. In this article, the research progress on gut microbiota modulation of edible plant oils (especially camellia oil, olive oil, and flaxseed oil) is summarized. Meanwhile, a summary on correlations between modulated gut microbiota and changed biochemical indexes is provided. The alterations of edible plant oils on gut microbiota-derived metabolites and the correlations between altered metabolites and modulated gut microbiota as well as changed biochemical indexes are reviewed. Furthermore, the prospects for gut microbiota modulation of edible plant oils during their health-promoting effects are put forward. Existing literature has shown that edible plant oils could modulate gut microbiota during their health-promoting effects, and some differential gut microbiota biomarkers were gained. Some similarities and differences existed while the oils exhibited health-promoting actions. Dosage and treatment time have influences on gut microbiota modulation of edible plant oils. Different edible plant oils exhibited different behaviors in modulating gut microbiota, and edible plant oils were mostly different in modulating gut microbiota compared to edible animal oils. Moreover, the modulated gut microbiota was significantly correlated with the changed biochemical indexes. Furthermore, edible plant oils altered SCFAs and other gut microbiota-derived metabolites. The altered metabolites were obviously correlated with the modulated gut microbiota and changed biochemical indexes. This review is helpful to the future research and application of edible plant oils in health-promoting effects from the perspective of gut microbiota.

Physical simulation serves as a crucial method for understanding the mechanisms of underground oil and gas migration and accumulation. To gain a deeper understanding of gas migration mechanisms in tight reservoirs under deep geological conditions, experimental models and boundary conditions were designed using the tight sandstone gas reservoirs of the Upper Paleozoic Shanxi Formation in the Yan'an Gas Field as a case study. Based on ultra-low permeability rock multiphase flow nuclear magnetic resonance online simulation experiments, the study investigated the critical pressure and dynamic conditions governing gas migration in tight sandstone, while also analyzing the factors influencing gas migration and accumulation. Different types of sandstones from the Shanxi Formation were selected, including quartz clean sandstone, quartz-rich low-plasticity particle detrital quartz sandstone, plastic particle-rich detrital sandstone, and tuffaceous matrix-rich quartz sandstone samples, representing reservoir rock facies with different porosity and permeability distributions. Experiments with constant low injection flow rates, different flow velocities (flow rates), and different pressure differences were conducted. The findings indicate that the critical charging pressure of tight sandstone reservoirs is primarily influenced by rock facies and permeability. Dominant rock facies with higher permeability exhibit lower critical charging pressures. For instance, the critical injection pressure of pure quartz sandstone gas typically falls below 1.2 MPa, while it generally remains below 1.5 MPa even for plastic-rich granular lithic sandstones and tuff-rich hybridquartz sandstones with inferior physical properties. Furthermore, there exists no absolute lower limit for the gas charging physical properties of tight sandstone. However, the charging efficiency and gas saturation of tight sandstone are positively correlated with reservoir physical properties, particularly permeability. The more developed the dominant rock facies and the higher the permeability, the higher the charging efficiency and gas saturation.

The resistance to intergranular corrosion (IGC) is crucial for 7xxx series high-strength aluminum alloy. The grain boundary characteristics and nanoscale intergranular precipitates are the most significant factors affecting the IGC performance of alloys. Exploring the influences of the two factors on the mechanism and kinetics of corrosion is a fundamental issue for IGC processes. In this paper, the multi-phase field model for electrochemical corrosion is employed to study the IGC processes. The effects of grain size, GB overpotential, and the status of nano-precipitates on the mechanism and kinetics of IGC are systematically and quantitatively investigated. Polycrystalline alloys with the averaged grain sizes in micrometer and nanoscale show typical IGC (GB network propagation) regime and massive corrosion regime respectively. The IGC tendency of micrometer-sized grains increases with the average grain size, while that of nanoscale grains exhibits the opposite trend due to different corrosion mechanisms. For the IGC in the presence of nano-precipitates, our simulations quantify that the orientation, size, and distribution of precipitates could substantially affect the corrosion rate. Nanoscale precipitates exhibit completely different corrosion regimes in the process of IGC, with trenching and penetrating corrosion patterns depending on the overpotential. The multi-phase field model lays a foundation for revealing the corrosion mechanism as well as designing new corrosion resistant materials.

Abstract The success of deep learning in various applications depends on task-specific architecture design choices, including the types, hyperparameters, and number of layers. In computational biology, there is no consensus on the optimal architecture design, and decisions are often made using insights from more well-established fields such as computer vision. These may not consider the domain-specific characteristics of genome sequences, potentially limiting performance. Here, we present GenomeNet-Architect, a neural architecture design framework that automatically optimizes deep learning models for genome sequence data. It optimizes the overall layout of the architecture, with a search space specifically designed for genomics. Additionally, it optimizes hyperparameters of individual layers and the model training procedure. On a viral classification task, GenomeNet-Architect reduced the read-level misclassification rate by 19%, with 67% faster inference and 83% fewer parameters, and achieved similar contig-level accuracy with ~100 times fewer parameters compared to the best-performing deep learning baselines.

Abstract Interstitial lung disease (ILD) can lead to lung cancer, which brings great challenges to differential diagnosis and comprehensive treatment. However, the clinical features of lung-dominant connective tissue disease (LD-CTD) related ILD combined with lung cancer has not been validated. We report the case of an 80-year-old woman with LD-CTD treated regularly with nintedanib who presented progressive dyspnoea and hypoxemia after recurrent viral infections. Her chest computed tomography (CT) showed aggravated interstitial fibrosis in both lower lungs with moderate right pleural effusion. Clinicians should be alert to lung cancer in patients who are experiencing poor responsiveness to treatment or acute progression of ILD. The available literatures about the differential diagnosis of clinical manifestations, imaging, treatment and prognosis of LD-CTD are reviewed and discussed in this study.

Purpose: To investigate the relationship between ocular fundus abnormalities and cytokines in patients with severe viral pneumonia, aiming to provide targeted diagnostic recommendations. Methods: We assessed critically ill patients with severe viral pneumonia and categorized them into the survivor (17 patients, 33 eyes) and deceased (30 patients, 58 eyes) groups. Spearman's correlation analysis was used to assess associations between cytokine levels and fundus abnormalities. Results: In the deceased group, the vascular fractal dimension (FD) and vessel density (VD) were lower and negatively correlated with interleukin 2 (IL-2), IL-8, IL-10, interferon (IFN)-α, IFN-γ, IL-1β, IL-12, and IL-6 but positively correlated with IL-5. In the survivor group, arterial dilatation and reduced curvature were positively correlated with IL-6 and negatively correlated with IL-2 and IL-12; moreover, venous abnormalities were negatively correlated with IL-5, IL-10, and tumor necrosis factor (TNF)-α. In the deceased group, venous abnormalities were positively correlated with IL-10 and negatively correlated with IL-5, IL-1β, and TNF-α. The cup-to-disc ratio (CDR) was lower in the deceased group, with a significant reduction in rim width (RW), especially in the superior region. In the survivor group, the CDR was negatively correlated with IL-10, while in the deceased group, it was positively correlated with IL-6. RW was positively correlated with IL-1β, IL-5, and IL-10 in the survivor group and with IL-10, IL-12, and IL-17 in the deceased group. Conclusion: Fundus vascular abnormalities and optic disc edema are associated with cytokine levels in patients with severe viral pneumonia, with significant differences between survivors and deceased patients.

Background: Machine learning (ML) analysis of retinal nerve fiber layer (RNFL) thickness and vessel density (VD) alterations in the macular region and optic disc may provide a new diagnostic method for lupus nephritis (LN). This study aimed to assess these alterations in LN patients using optical coherence tomography angiography (OCTA). Methods: A retrospective analysis was conducted on 81 systemic lupus erythematosus (SLE) patients without retinopathy, divided into two groups: LN (41 patients) and non-LN (39 patients). OCTA imaging was performed on all participants. Independent risk factors were identified through univariate and multivariate analyses, followed by the development of a random forest (RF) diagnostic model. Results: A total of 37 RNFL and VD variables from the macular region and 23 from the optic disc were analyzed. Through elastic net regression, 16 significant factors were identified. Further multivariate logistic regression selected 8 critical factors, which were used to construct the RF model. The RF model achieved an area under the curve (AUC) of 0.950 (95 % CI: 0.882 to 1.000), accuracy of 0.903 (95 % CI: 0.743 to 0.980), sensitivity of 0.867, specificity of 0.938, a positive predictive value (PPV) of 0.929, and a negative predictive value (NPV) of 0.882. Conclusion: This study highlights the potential of ML-based OCTA data in diagnosing LN. Key diagnostic factors included perimeter (PERIM), superficial capillary plexus vessel density (SVD) - parafoveal (para)-temporal (T), SVD-perifoveal (peri)-inferior (I), RNFL-Fovea, RNFL-Peri, RNFL-Peri-T, capillary-whole-image, and peripapillary RNFL (PRNFL)- inferonasal (IN).

Background: Self-efficacy, or the beliefs learners hold about what they can do, develops largely from how learners perceive and interpret four main sources of information: mastery experiences, vicarious experiences, social persuasions and physiological and affective states. Although the relationship between these sources and self-efficacy is well-established, less is known about the factors that may influence how early adolescent learners perceive and interpret information from these sources. Aims: The purpose of this study was to investigate how the predisposition of perfectionism might predict how learners perceive efficacy-relevant information in the domain of math. Methods: Using a correlational design, this study considered whether perfectionism was associated with how middle school students (N = 1683) perceive information from the four hypothesized sources of self-efficacy. Participants completed a paper-based survey at two time points. Perfectionism was measured at Time 1. Self-efficacy and its sources were measured at Time 2. Structural equation modelling techniques were used to examine the relationship between factors. Results and Conclusions: Students who held themselves to high standards (i.e., greater self-oriented perfectionism) reported higher levels of mastery experiences, vicarious experiences, social messages and self-efficacy. Conversely, students who felt external pressure to be perfect (i.e., socially prescribed perfectionism) reported lower levels of mastery experiences, vicarious experiences and self-efficacy, as well as higher levels of negative physiological and affective states. The relationship between perfectionism and self-efficacy was partially mediated by students' perceptions of mastery. This study extends the current literature on the sources of math self-efficacy in early adolescence by showing how a predisposition like perfectionism is associated with how adolescent learners perceive and interpret efficacy-relevant information.

IntroductionGrape is of high economic value. Colletotrichum viniferum, a pathogen causing grape ripe rot and leaf spot, threatens grape production and quality.MethodsThis study investigates the interplay between C. viniferum by Cytological study and transcriptome sequencing.ResultsDifferent grapevine germplasms, V. vinifera cv. Thompson Seedless (TS), V. labrusca accession Beaumont (B) and V. piasezkii Liuba-8 (LB-8) were classified as highly sensitive, moderate resistant and resistant to C. viniferum, respectively. Cytological study analysis reveals distinct differences between susceptible and resistant grapes post-inoculation, including faster pathogen development, longer germination tubes, normal appressoria of C. viniferum and absence of white secretions in the susceptible host grapevine. To understand the pathogenic mechanisms of C. viniferum, transcriptome sequencing was performed on the susceptible grapevine “TS” identifying 236 differentially expressed C. viniferum genes. These included 56 effectors, 36 carbohydrate genes, 5 P450 genes, and 10 genes involved in secondary metabolism. Fungal effectors are known as pivotal pathogenic factors that modulate plant immunity and affect disease development. Agrobacterium-mediated transient transformation in Nicotiana benthamiana screened 10 effectors (CvA13877, CvA01508, CvA05621, CvA00229, CvA07043, CvA05569, CvA12648, CvA02698, CvA14071 and CvA10999) that inhibited INF1 (infestans 1, P. infestans PAMP elicitor) induced cell death and 2 effectors (CvA02641 and CvA11478) that induced cell death. Additionally, transcriptome analysis of “TS” in response to C. viniferum identified differentially expressed grape genes related to plant hormone signaling (TGA, PR1, ETR, and ERF1/2), resveratrol biosynthesis genes (STS), phenylpropanoid biosynthesis genes (PAL and COMT), photosynthetic antenna proteins (Lhca and Lhcb), transcription factors (WRKY, NAC, MYB, ERF, GATA, bHLH and SBP), ROS (reactive oxygen species) clearance genes (CAT, GSH, POD and SOD), and disease-related genes (LRR, RPS2 and GST).DiscussionThis study highlights the potential functional diversity of C. viniferum effectors. Our findings lay a foundation for further research of infection mechanisms in Colletotrichum and identification of disease response targets in grape.

Sugar beet (Beta vulgaris L.) is one of the most important sugar crops, accounting for nearly 30% of the world’s annual sugar production. And it is mainly distributed in the northwestern, northern, and northeastern regions of China. However, Cercospora leaf spot (CLS) is the most serious and destructive foliar disease during the cultivation of sugar beet. In plants, the bZIP gene family is one of important family of transcription factors that regulate many biological processes, including cell and tissue differentiation, pathogen defense, light response, and abiotic stress signaling. Although the bZIP gene family has been mentioned in previous studies as playing a crucial role in plant defense against diseases, there has been no comprehensive study or functional analysis of the bZIP gene family in sugar beet with respect to biotic stresses. In this study, we performed a genome-wide analysis of bZIP family genes (BvbZIPs) in sugar beet to investigate their phylogenetic relationships, gene structure and chromosomal localization. At the same time, we observed the stomatal and cell ultrastructure of sugar beet leaf surface during the period of infestation by Cercospora beticola Sacc (C. beticola). And identified the genes with significant differential expression in the bZIP gene family of sugar beet by qRT-PCR. Finally we determined the concentrations of SA and JA and verified the associated genes by qRT-PCR. The results showed that 48 genes were identified and gene expression analysis indicated that 6 BvbZIPs were significantly differential expressed in C. beticola infection. It is speculated that these BvbZIPs are candidate genes for regulating the response of sugar beet to CLS infection. Meanwhile, the observation stomata of sugar beet leaves infected with C. beticola revealed that there were also differences in the surface stomata of the leaves at different periods of infection. In addition, we further confirmed that the protein encoded by the SA signaling pathway-related gene BVRB_9g222570 in high-resistant varieties was PR1, which is closely related to systemic acquired resistance. One of the protein interaction modes of JA signal transduction pathway is the response of MYC2 transcription factor caused by JAZ protein degradation, and there is a molecular interaction between JA signal transduction pathway and auxin. Despite previous reports on abiotic stresses in sugar beet, this study provides very useful information for further research on the role of the sugar beet bZIP gene family in sugar beet through experiments. The above research findings can promote the development of sugar beet disease resistance breeding.

The evaluation of the pore structure in dolomite, particularly with regard to pore heterogeneity, geometry, and connectivity, is crucial for oil and gas field production and reservoir prediction. The subsalt dolomite reservoir in the Ordovician strata of the Ordos Basin has shown promising exploration results and is anticipated to have a high hydrocarbon potential. However, there has been limited research on the pore structure and primary controlling factors of the Ordovician Majiagou reservoir in the south-central Ordos Basin. Therefore, we conducted a comprehensive analysis of the pore structure and fractal characteristics using routine petrophysical measurements, thin-section analysis, and high-pressure mercury injection (HPMI) data. We also discussed the relationship between fractal dimension, reservoir physical properties, and pore structure, along with exploring the origin of potentially prolific reservoirs. Our observations from the thin section identified four main pore types: intercrystalline pores, intercrystalline dissolved pores, dissolved pores, and micro-fractures. The data from HPMI revealed that the average pore–throat radii range from 0.009 μm to 0.015 μm with porosity ranging from 0.4% to 5.26%, and permeability ranging from 0.011 mD to 0.059 mD. They were further categorized into three reservoir types: dissolved pore type, intra-crystalline (dissolved) pore type, and micro-porous type. The fractal dimension was calculated based on HPMI data, and the reservoir’s fractal characteristics were divided into two segments. The dissolved pore type was identified as the potentially prolific reservoir due to its larger pore size and volume, moderate permeability, and homogeneity on pore structure. Additionally, the fractal dimension is negatively correlated with porosity and permeability and positively correlated with sorting coefficient and skewness, suggesting that fractal dimensions are valuable for evaluating reservoir quality and quantitatively characterizing pore networks.

Accumulating evidence has highlighted the influence of the gut microbiota on lung immunity. We examined the effects of changes in intestinal microecology on the development of Chronic Obstructive Pulmonary Disease (COPD) and identified microbial biomarkers for acute exacerbations of COPD (AECOPD). Fecal samples were collected from 30 patients with stable COPD, 30 patients with AECOPD, and 10 healthy individuals. Fecal microbiological profiles were analyzed using 16S rRNA gene sequencing. The results showed a distinct difference in the bacterial community composition between the AECOPD, COPD, and healthy control groups. The COPD and AECOPD groups had higher levels of Firmicutes but lower levels of Bacteroidetes compared to the healthy control group at the phylum level. At the genus level, there was an increased abundance of Lachnoclostridium, Alistipes, Streptococcus, and Prevotella in COPD and AECOPD patients. Increasing levels of Lachnoclostridium and Prevotella may indicate an acute exacerbation of COPD. This study identified specific microbial biomarkers associated with AECOPD and characterized the composition of gut microbiota in patients with AECOPD.