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With global warming, heat stress has been recognized as a significant factor limiting grapevine development and fruit quality. MicroRNAs (miRNAs) are a class of small non-coding RNAs known to play crucial regulatory roles in stress resistance. Hence, there is an immediate requirement to cultivate and identify grapevine varieties that are resistant to heat and explore miRNA-mediated heat stress defense mechanisms. In this study, we assessed the thermal resistance of 38 grape germplasm resources and identified a series of miRNAs involved in heat stress resistance. The CK (25°C) and HS (45°C) groups of “Shenyue” cuttings of grapes were used as experimental materials for next-generation sequencing and construct libraries of small RNAs. A total of 177 known and 20 novel miRNAs were detected in the libraries. Differential expression analysis identified 65 differentially expressed miRNAs (DEMs) using the DE-Seq procedure. Furthermore, RT-qPCR validation confirmed complementary expression profiles of eight DEMs and their target genes between the HS and CK groups. Heterologous transformation further identified the function of Vvi-miR3633a downregulated under heat stress in Arabidopsis. In the heterologous expression lines, the survival rate was reduced by high temperature treatment indicating the ability of Vvi-miR3633a to regulate heat resistance. Assessing the heat resistance of grape species and the expression patterns of miRNA in response to high temperatures may reveal the molecular processes of heat resistance regulation mediated by miRNA in grapes under heat stress.

The grapevine, a globally significant fruit and an essential fruit tree species in China, is vulnerable to the adverse effects of high temperatures. Understanding the roles of microRNA and transcription factors in plant development and stress resistance is crucial for mitigating the impact of high temperature on grape growth and yield. This study investigates the response of miRNA to high-temperature stress in grape leaves. The expression level of Vvi-miR3633a was found to be inhibited under heat treatment in both Thompson seedless and Shen yue varieties, while its potential target genes (Vv-Atg36 and Vv-GA3ox2) were induced. Through transgenic overexpression experiments, it was demonstrated that Vvi-miR3633a plays a role in thermal response by affecting the expression of target genes. Furthermore, under heat stress conditions, overexpression of Vvi-miR3633a in grape callus decreased heat resistance compared to the control group (CK). The study also revealed that the target genes of Vvi-miR3633a regulate the expression of oxidase synthesis genes VvSOD and VvCAT, leading to reduced oxidase synthesis which may compromise the oxidation system. Additionally, the expression level of heat shock proteins in the transgenic lines was changed compared to the control (CK). Overall, this research provides valuable insights into understanding the molecular mechanisms involved in different crossing/breeding programs to produce heat-resistant grape varieties. Such varieties can be appropriate to propagate in warm climate areas with high temperature conditions.

Abstract Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Abstract Thermal characteristic is one of the key performances of dry‐type on‐board traction transformer (D‐OBTT), which directly affects the operation safety of the new generation electric multiple units. However, due to the particularity of train‐induced wind cooling mode of D‐OBTT, the existing efficient thermal modelling methods cannot be used under fluctuating air velocity and load. A time‐saving transient thermal model for D‐OBTT is proposed. First, the framework of the transient thermal network model (TTNM) is proposed considering the coexistence of non‐fully and fully developed state of the train‐induced wind and the addition heat flow in the solid domain. Then, a novel formula for calculating the length of non‐fully developed section considering the geometric dimensions and heat flux density is proposed based on computational fluid dynamics (CFD) parametric sweeps for the first time. The accuracy of TTNM is validated by a D‐OBTT experimental setup, and the time consumption is significantly reduced compared with CFD.

Background and objectiveGlioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome.MethodsWe proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity.ResultsWSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes.ConclusionsThis study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

The core loss calculation is essential for the design and performance evaluation of high-frequency transformers. It is related to the dimensions, temperature rises performance, and operating efficiency of transformer designs. Some scholars have examined the correlation between the characteristics of the core and losses, such as the core air gap length and the core structure; some investigations have also analyzed the effects of harmonics, distortion flux, and other factors on core losses. However, in reality, the core operating environment of high-frequency transformers is very complex, and achieving the required accuracy of loss model calculations is difficult. This paper discussed the insufficiency of the classical Bertotti loss separation model in estimating core loss under non-sinusoidal excitation of high-frequency transformers. Based on the derivation and modification of the classical loss model, the magnetic performance test platform of the nanocrystalline core material was established. In order to obtain a higher-order correction calculation method for the core loss of high-frequency transformers under trapezoidal wave excitation, the experimentally measured loss curves of nanocrystalline materials were further corrected. Finally, the accuracy of the correction model was verified by changing the loss results by varying the trapezoidal wave rise time constant.

Mesenchymal stem cells (MSCs) have potential role in organ regeneration therapy. Previous work indicating that MSCs confer protection against liver disease. Here, we aimed to determine the potential application in liver regeneration of human placenta-derived MSCs extracellular vesicles (hPMSCs-EVs) via experimental hepatectomy. hPMSCs-EVs were administered intravenously 24 h before 70% partial hepatectomy, the specific composition of hPMSCs-EVs was identified by sequencing and validated by the quantitative polymerase chain reaction, including circ-RBM23. The role of circ-RBM23 in L02 cell was evaluated and it was found that circ-RBM23 knockdown inhibited L02 cell proliferation both in vitro and in vivo. The competing endogenous RNA function of circ-RBM23 was evaluated by the RNA immunoprecipitation assay and found that circ-RBM23 shares miRNA response elements with RRM2. Overexpressed circ-RBM23 bound competitively to miR-139-5p, preventing the miRNA-mediated degradation of RRM2, activating the expression of eIF4G and AKT/mTOR, and facilitating liver regeneration. These results indicate that hPMSCs-EVs prevent hepatic dysfunction and improve liver regeneration in vivo and hepatocytes proliferation in vitro, potentially via circ-RBM23 delivery.

A previous genome-wide association study (GWAS) reported several novel loci for nephrolithiasis in British and Japanese population, some of which were predicted to influence CaSR signaling. In this study, we aimed to evaluate the association of these loci with calcium nephrolithiasis in Chinese Han population. We performed a case-control association analysis involving 691 patients with calcium nephrolithiasis and 1008 control subjects. We were able to genotype a total of 17 single-nucleotide polymorphisms (SNPs), which were previously reported to be significantly associated with nephrolithiasis in GWAS. rs578595 at WDR72 was significantly associated with calcium nephrolithiasis in Chinese Han population (p < 0.001, OR = 0.617). Moreover, rs12654812 at SLC34A1 (p = 0.0427, OR = 1.170), rs12539707 at HIBADH (p = 0.0179, OR = 0.734), rs1037271 at DGKH (p = 0.0096, OR = 0.828) and rs12626330 at CLDN14 (p = 0.0080, OR = 1.213) indicated suggestive associations with calcium nephrolithiasis. Our results elucidated the significance of genetic variation at WDR72, DGKH, CLDN14, SLC34A1, and HIBADH in Chinese patients with nephrolithiasis. Since polymorphisms of WDR72, DGKH, and CLDN14 are predicted to influence in CaSR signaling, our results emphasized the role of abnormal calcium homeostasis in calcium nephrolithiasis.

Abstract Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor—a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.

The fan is one of the key components of the power transformer cooling system. The operating condition of fans determines transformers’ internal temperature rise and long-term reliability. However, at present, the fans’ condition monitoring only includes switch status (online) and regular maintenance (offline), online direct monitoring of the fans’ operating condition is lacking due to economic costs. In view of the above-mentioned problem, this paper proposes a transformer fan early fault detection method based on the oil exponent, which is monitored by the existing transformer top-oil temperature data, thereby detecting the abnormality of the fans. In this method, the oil exponent was chosen as the characteristic criterion. First, to obtain the range of oil exponent in different cooling modes, a set of physical models describing global oil flow and its interaction with air was established based on fluid dynamics and heat transfer principle. Then, regarding the constantly changing top-oil temperature, ambient temperature and load current, an oil exponent tracking algorithm using particle swarm optimization (PSO) was proposed within an improved IEC dynamic thermal model. The operation data from an oil-immersed transformer with a rated capacity of 120-MVA and rated voltage of 220-kV was selected to verify the above methods under two different scenarios.

Objective. This study aimed to determine if variations in the expression profiles of CA 19-9 and carcinoembryonic antigen (CEA) within the reference range could serve as possible biomarkers for postoperative CRC recurrence. Method. This retrospective cohort investigation enrolled 2,596 cases of CRC that received curative surgery. Serum CEA/CA 19-9 were measured through chemiluminescence immunoassay (CLIA). Results. During follow-up (median follow-up = 5.2 years), in total, 837 patients experienced recurrence. The fully adjusted hazard ratios (HRs) were significantly higher, ≥1 standard deviation (±SD), in patients with upregulated CEA/CA 19-9 levels (HRCEA=7.06; HRCA 19−9=3.98) than in those with downregulated CEA/CA 19-9 levels. The likelihood of recurrence remained consistently greater in cases of elevated CEA/CA 19-9 levels during sensitivity analyses. Conclusions. The findings of this analysis showed that variations in CEA/CA 19-9 expression profiles within the reference range impact CRC recurrence.

In a tunnel fire, smoke flow is often divided into two regions: the near-field and the far-field. The former is a three-dimensional radial flow region close to the fire source and the latter is a one-dimensional steady flow region generally formed a certain distance away from the fire. Although the efficiency of the smoke exhaust system is influenced by the region, limited research has been done to determine the demarcation point between the two regions. In this study, a total of 27 tunnel fire computer simulations were conducted to examine the effect of heat release rate (HRR) and the tunnel's cross-sectional dimensions on the location of the demarcation point. Rather than relying on the tunnel's height, which has been commonly used in previous tunnel fire studies to determine smoke flow characteristics, a hydraulic diameter of the tunnel's cross-section was employed in this study. An improved correlation for the location of the demarcation point is proposed by comparing a theoretical dimensionless model to numerical simulation results.

With the development and progress of information technology, especially V2X technology, the research focus of intelligent vehicles gradually shifted from single-vehicle control to multi-vehicle control, and the cooperative control system of intelligent connected vehicles became an important topic of development. In order to track the research progress of intelligent connected vehicle cooperative driving systems in recent years, this paper discusses the current research of intelligent connected vehicle cooperative driving systems with vehicles, infrastructure, and test sites, and analyzes the current development status, development trend, and development limitations of each object. Based on the analysis results of relevant references of the cooperative control algorithm, this paper expounds on vehicle collaborative queue control, vehicle collaborative decision making, and vehicle collaborative positioning. In the case of taking the infrastructure as the object, this paper expounds the communication security, communication delay, and communication optimization algorithm of the vehicle terminal and the road terminal of intelligent connected vehicles. In the case of taking the test site as the object, this paper expounds the development process and research status of the real vehicle road test platform, virtual test platform, test method, and evaluation mechanism, and analyzes the problems existing in the intelligent connected vehicle test environment. Finally, the future development trend and limitations of intelligent networked vehicle collaborative control system are discussed. This paper summarizes the intelligent connected car collaborative control system, and puts forward the next problems to be solved and the direction of further exploration. The research results can provide a reference for the cooperative driving of intelligent vehicles.

Oil-immersed insulation paper (OIP) bushing is one of the most important equipment in power transmission and distribution systems. Moisture is one of the most serious factors that affect the insulation status of OIP bushing. In this paper, the OIP bushing was assumed to be in a stable and simplicity condition, and then the transient moisture distribution of capacitor core and its effects on the electric field were studied. First, by dissecting a 110 kV OIP bushing, the specific sizes for modelling were obtained. Afterwards, a moisture diffusion model for OIP bushing was established based on COMSOL Multiphysics software, and it was also verified by moisture diffusion experiment. Then, the moisture distribution for different conditions were obtained and analyzed. Finally, a model for the electric field of OIP bushing was established, and then the effects of moisture on the electric field were studied.

Studying the moisture diffusion in non-oil-immersed insulation paper is helpful to optimize the drying process and improve the drying efficiency of oil-immersed equipment. Moisture diffusion factor (MDF) is the key parameter to describe the moisture diffusion in non-oil-immersed insulation paper. Thermal aging affects the moisture absorption capacity of insulation paper obviously, thus, this paper intends to modify the empirical expression of MDF by considering the effects of thermal aging. The transient moisture contents of non-oil-immersed insulation paper with different thicknesses were measured at 40 °C and 60 °C, respectively. Then, the experimental values of MDF were extracted, and the empirical expression of MDF was modified by considering the effects of thermal aging. Finally, the modified expression of MDF was verified. The following conclusion can be obtained: 1) the equilibrium time constant of non-oil-immersed insulation paper increases with thermal aging; 2) the moisture absorption rate of non-oil-immersed insulation paper decreases with thermal aging, and; 3) the modified expression of MDF is reasonable and effective.

To study the effect of hyperbranched polyester with different kinds of terminal groups on the thermomechanical and dielectric properties of silica–epoxy resin composite, a molecular dynamics simulation method was utilized. Pure epoxy resin and four groups of silica–epoxy resin composites were established, where the silica surface was hydrogenated, grafted with silane coupling agents, and grafted with hyperbranched polyester with terminal carboxyl and terminal hydroxyl, respectively. Then the thermal conductivity, glass transition temperature, elastic modulus, dielectric constant, free volume fraction, mean square displacement, hydrogen bonds, and binding energy of the five models were calculated. The results showed that the hyperbranched polyester significantly improved the thermomechanical and dielectric properties of the silica–epoxy composites compared with other surface treatments, and the terminal groups had an obvious effect on the enhancement effect. Among them, epoxy composite modified by the hyperbranched polyester with terminal carboxy exhibited the best thermomechanical properties and lowest dielectric constant. Our analysis of the microstructure found that the two systems grafted with hyperbranched polyester had a smaller free volume fraction (FFV) and mean square displacement (MSD), and the larger number of hydrogen bonds and greater binding energy, indicating that weaker strength of molecular segments motion and stronger interfacial bonding between silica and epoxy resin matrix were the reasons for the enhancement of the thermomechanical and dielectric properties.

OBJECTIVES:To (i) investigate alterations in homotopic functional connectivity (hfc) in concussed patients relative to healthy controls (HC) and to (ii) interrogate whether hfc in concussed patients normalized during the recovery process. The relationship between symptom recovery and change in hfc was assessed using post-hoc analyses. METHODS:This study included 15 concussed patients (mean age = 39.1, SD = 10.1; sex: 13 females, 2 males) and 15 HC (mean age = 39.1, SD = 11.7; sex: 13 females, 2 males). Hfc patterns were interrogated using resting-state magnetic resonance imaging (rs-MRI) for 29 a priori selected pain-processing regions. Concussed patients underwent imaging at two time-points; at 1-month post-concussion (mean time following concussion: 28 days, SD = 9.5) and again at 5-months post-concussion (mean time following concussion: 121 days, SD = 13). At both time-points, symptoms associated with concussion were assessed using the Sports Concussion Assessment Tool (SCAT-3). RESULTS:Concussed patients had significantly weaker hfc in the following six regions 1-month post-concussion compared to HC: middle cingulate, posterior insula, middle occipital, spinal trigeminal nucleus, precentral and the pulvinar. There were no regions of significantly stronger hfc in concussed patients relative to HC. Longitudinally, patients showed significant symptom recovery 5-months post-concussion and had significant strengthening of hfc patterns in seven homotopic ROIs: middle cingulate, posterior insula, middle occipital, secondary somatosensory area, spinal trigeminal nucleus, precentral, and the pulvinar. Post-hoc analyses indicated a significant negative correlation between somatosensory functional connectivity strengthening and symptom severity. CONCLUSION:At 1-month post-concussion, patients had significantly weaker hfc in a number of pain-processing regions relative to HC. However, over a period of 5-months, region-pair connectivity showed significant recovery and normalization. Those patients with more successful symptom recovery at 5-months post-concussion had more functional somatosensory strengthening, suggesting an association between functional strengthening and post-concussion symptom recovery.

BACKGROUND:The current classification of traumatic brain injury (TBI) into "mild", "moderate", or "severe" does not adequately account for the patient heterogeneity that still exists within each of these categories. The objective of this study was to identify "sub-groups" of mild TBI (mTBI) patients based on data available at the time of the initial post-TBI patient evaluation and to determine if the sub-grouping correlates with patient outcomes at 90 and 180 days post-TBI. METHODS:Data from patients in the TRACK-TBI Pilot dataset who had a Glasgow Coma Scale (GCS) score of 13 to 15 at arrival to the Emergency Department and a closed head injury were included. Considering 53 clinical variables that are typically available during the initial evaluation of the patient with mild TBI, sparse heirarchial clustering with cluster quality assessment was used to identify the optimal number of patient sub-groups. Patient sub-groups were then compared for ten outcomes measured at 90 or 180 days post-TBI. RESULTS:Amongst the 485 patients with mTBI, optimal clustering was based on the inclusion of 12 clinical variables that divided the patients into 5 mild TBI sub-groups. Clinical variables driving the sub-clustering included: gender, employment status, marital status, TBI due to falling, brain CT scan result, systolic blood pressure, diastolic blood pressure, administration of IV fluids in the Emergency Department, alcohol use, tobacco use, history of neurologic disease, and history of psychiatric disease. These 5 mild TBI sub-groups differed in their 90 day and 180 day outcomes within several domains including global outcomes, persistence of TBI-related symptoms, and neuropsychological impairment. CONCLUSIONS:Sub-groups of patients with mTBI can be identified according to clinical variables that are relatively easy to obtain at the time of initial patient evaluation. A patient's sub-group assignment is associated with multidimensional patient outcomes at 90 and 180 days. These findings support the notion that there are clinically meaningful subgroups of patients amongst those currently classified as having mTBI.