Multiple-view 3D digital image correlation based on pseudo-overlapped imaging.

The restriction of the field of view (FOV) enlargement and spatial resolution increase during optical monitoring was investigated. Traditional optical instruments usually have a fixed FOV in one test; thus, they have low accuracy for small samples under large motions/deformations. To improve the spatial resolution in a relatively large FOV of an optical instrument, a multiple-view 3D digital image correlation (3D-DIC) method based on pseudo-overlapped imaging is proposed. Using a set of optical components, pseudo-overlapped imaging can image two FOVs with the same camera, which converts one pair of cameras to four virtual cameras. Each virtual camera has the same whole pixels. Therefore, compared with the conventional 3D-DIC system, the proposed method simultaneously enlarges FOVs and increases spatial resolutions by two times. The efficiency, accuracy, and feasibility of the technique were validated through experiments.

Lysosomal cation channel TRPML1 suppression sensitizes acute myeloid leukemia cells to chemotherapeutics by inhibiting autophagy.

Despite the implementation of novel therapeutic regimens and extensive research efforts, chemoresistance remains a formidable challenge in the treatment of acute myeloid leukemia (AML). Notably, the involvement of lysosomes in chemoresistance has sparked interest in developing lysosome-targeted therapies to sensitize tumor cells to currently approved chemotherapy or as innovative pharmacological approaches. Moreover, as ion channels on the lysosomal membrane are critical regulators of lysosomal function, they present potential as novel targets for enhancing chemosensitivity. Here, we discovered that the expression of a lysosomal cation channel, namely transient receptor potential mucolipin 1 (TRPML1), was elevated in AML cells. Inhibiting TRPML1 individually does not impact the proliferation and apoptosis of AML cells. Importantly, inhibition of TRPML1 demonstrated the potential to modulate the sensitivity of AML cells to chemotherapeutic agents. Exploration of the underlying mechanisms revealed that suppression of TRPML1 impaired autophagy while concurrently increasing the production of reactive oxygen species (ROS) and ROS-mediated lipid peroxidation (Lipid-ROS) in AML cells. Finally, the knockdown of TRPML1 significantly reduced OCI-AML3 tumor growth following chemotherapy in a mouse model of human leukemia. In summary, targeting TRPML1 represents a promising approach for combination therapy aimed at enhancing chemosensitivity in treating AML.

Associations of E-proteinoid 3 receptor genetic polymorphisms with salt sensitivity, longitudinal blood pressure changes, and hypertension incidence in Chinese adults.

The E-proteinoid 3 receptor (PTGER3), a member of the prostaglandin E2 (PGE2) subtype receptor, belongs to the G-protein-coupled superfamily of receptors. Animal studies have demonstrated its involvement in salt sensitivity by regulating sodium reabsorption. This study aimed to investigate the association between genetic variants of PTGER3 and salt sensitivity, longitudinal blood pressure (BP) changes, and the incidence of hypertension in Chinese adults. A chronic salt intake intervention was conducted involving 514 adults from 124 families in the 2004 Baoji Salt-Sensitivity Study Cohort in northern China. These participants followed a 3-day regular baseline diet, followed by a 7-day low-salt diet (3.0 g/d) and a 7-day high-salt diet (18 g/d), and were subsequently followed for 14 years. The findings revealed a significant relationship between the single nucleotide polymorphism (SNP) rs17482751 of PTGER3 and diastolic blood pressure (DBP) response to high salt intervention. Additionally, SNPs rs11209733, rs3765894, and rs2268062 were significantly associated with longitudinal changes in systolic blood pressure (SBP), DBP, and mean arterial pressure (MAP) during the 14-year follow-up period. SNP rs6424414 was significantly associated with longitudinal changes in DBP over 14 years. Finally, SNP rs17482751 showed a significant correlation with the incidence of hypertension over 14 years. These results emphasize the significant role of PTGER3 gene polymorphism in salt sensitivity, longitudinal BP changes, and the development of hypertension in the Chinese population.

Development of xanthan gum intelligent oil-in-water ink and its application in pork freshness preservation.

To optimize the stability of oil-based inks and ensure their wide application in freshness indication, new natural indicator inks were prepared using a stable oil-in-water structure. This study selected natural Lycium ruthenicum anthocyanin as the dye and glucose as the pigment carrier. Soybean oil was introduced as a linker and xanthan gum as a thickener, and an oil-in-water ink with the function of freshness indication was successfully developed. In ensuring the safety of ink labels for use on food packaging, particular attention is paid to the origin and properties of the materials used. All ingredients are of food-grade or bio-friendly provenance, thereby ensuring the safety of the product when in direct contact with food. We measured the viscosity, particle size and fineness of the ink for micro characterization and evaluated its macro printing performance by its printing effect on A4 paper. According to the experimental results, when the water-oil ratio of the ink is 10:5, the average particle size of the emulsion system is 822.83 nm, and the fineness reaches 5 µm. These values are relatively low, which indicates that the stability of the ink system is high at this time, and the ink shows excellent rheological and printing characteristics. With this water-to-oil ratio, the ink can show the best results when printed on A4 paper, clearly displaying image details. In addition, in fresh pork applications, inks with a 10: 5 water-to-oil ratio provide an accurate and highly sensitive indication of the freshness of pork. When the freshness of the pork changes, the ink color responds promptly. This high sensitivity makes the ink ideal for use as a food freshness indication tool, providing consumers with an intuitive and reliable reference for pork freshness. As a further innovation, combining this ink-printed label with a WeChat app not only allows consumers to know the freshness of the food in real-time but also tracks the supply chain information of the food, providing a more comprehensive application prospect for freshness-indicating products.

Nonlinear association between atherogenic index of plasma and type 2 diabetes mellitus in overweight and obesity patients: evidence from Chinese medical examination data.

BACKGROUND: The atherogenic index of plasma (AIP) is closely associated with the onset of diabetes, with obesity being a significant risk factor for type 2 diabetes mellitus (T2DM). However, the association between the AIP and T2DM in overweight and obese populations has been infrequently studied. Therefore, this study aimed to explore this association in overweight and obese individuals with T2DM. METHODS: This cross-sectional analysis utilized data from 40,633 participants with a body mass index (BMI) ≥ 24 kg/m2 who were screened from January 2018 to December 2023 at Henan Provincial People's Hospital. Participants were categorized into groups of overweight and obese individuals with and without diabetes according to the T2DM criteria. The AIP, our dependent variable, was calculated using the formula log10 [(TG mol/L)/HDL-C (mol/L)]. We investigated the association between the AIP and T2DM in overweight and obese individuals using multivariate logistic regression, subgroup analysis, generalized additive models, smoothed curve fitting, and threshold effect analysis. Additionally, mediation analysis evaluated the role of inflammatory cells in AIP-related T2DM. RESULTS: Overweight and obese patients with T2DM exhibited higher AIP levels than those without diabetes. After adjusting for confounders, our results indicated a significant association between the AIP and the risk of T2DM in overweight and obese individuals (odds ratio (OR) = 5.17, 95% confidence interval (CI) 4.69-5.69). Notably, participants with a high baseline AIP (Q4 group) had a significantly greater risk of T2DM than those in the Q1 group, with an OR of 3.18 (95% CI 2.94-3.45). Subgroup analysis revealed that the association between the AIP and T2DM decreased with increasing age (interaction P < 0.001). In overweight and obese populations, the association between AIP and T2DM risk displayed a J-shaped nonlinear pattern, with AIP > - 0.07 indicating a significant increase in T2DM risk. Various inflammatory cells, including neutrophils, leukocytes, and monocytes, mediated 4.66%, 4.16%, and 1.93% of the associations, respectively. CONCLUSION: In overweight and obese individuals, the AIP was independently associated with T2DM, exhibiting a nonlinear association. Additionally, the association between the AIP and T2DM decreased with advancing age. Multiple types of inflammatory cells mediate this association.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis.

Objective: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy. Methods: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features. Results: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients. Conclusion: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

RiskFormer: Exploring the temporal associations between multi-type aberrant driving events and crash occurrence.

With the development of driving behavior monitoring technologies, commercial transportation enterprises have leveraged aberrant driving event detection results for evaluating crash risk and triggering proactive interventions. The state-of-the-art applications were established based upon instant associations between events and crash occurrence, which assumed crash risk surged with aberrant events. Consequently, the generated crash risk monitoring results merely contain discrete abrupt changes, failing to depict the time-varying trend of crash risk and posing challenges for interventions. Given the multiple types of aberrant events and their various temporal combinations, the key to depict crash risk time-varying trend is the analysis of multi-type events' temporal coupling influence. Existing studies employed event frequency to model combined influence, lacking the capability to differentiate the temporal sequential characteristics of events. Hence, there is an urgent need to further explore multi-type events' temporal coupling influence on crash risk. In this study, the temporal associations between multi-type aberrant driving events and crash occurrence are explored. Specifically, a contrastive learning method, fusing prior domain knowledge and empirical data, was proposed to analyze the single event temporal influence on crash risk. After that, a novel Crash Risk Evaluation Transformer (RiskFormer) was developed. In the RiskFormer, a unified encoding method for different events, as well as a self-attention mechanism, were established to learn multi-type events' temporal coupling influence. Empirical data from online ride-hailing services were employed, and the modeling results unveiled three distinct time-varying patterns of crash risk, including decay, increasing, and increasing-decay pattern. Additionally, RiskFormer exhibited remarkable crash risk evaluation performance, demonstrating a 12.8% improvement in the Area Under Curve (AUC) score compared to the conventional instant-association-based model. Furthermore, the practical utility of RiskFormer was illustrated through a crash risk monitoring sample case. Finally, applications of the proposed methods and their further investigations have been discussed.

Non-O blood types are associated with a greater risk of large artery atherosclerosis stroke and dysregulation of cholesterol metabolism: an observational study.

BACKGROUND: Previous research on ABO blood types and stroke has been controversial, predominantly suggesting heightened risk of stroke in non-O blood types. Nonetheless, investigations into the correlation and underlying mechanisms between ABO blood groups and stroke subtypes, especially within Chinese cohorts, remain limited. METHODS: The ABO blood types of 9,542 ischaemic stroke (IS) patients were inferred using two ABO gene loci (c.261G > del; c.802G > A). The healthy population was derived from the 1000 Genomes Project. Patients were classified by the causative classification system (CCS). Volcano plot and gene ontology (GO) analysis were employed to explore protein differential expression among blood types. Additionally, HT29 and SW480 cell lines with downregulated ABO expression were generated to evaluate its impact on cholesterol uptake and efflux. RESULTS: A greater proportion of stroke patients had non-O blood types (70.46%) than did healthy individuals (61.54%). Notable differences in blood type distributions were observed among stroke subtypes, with non-O blood type patients mainly classified as having large artery atherosclerosis (LAA). Clinical baseline characteristics, such as the low-density lipoprotein cholesterol level, activated partial thromboplastin time and thrombin time, varied significantly among blood types. A volcano plot revealed 17 upregulated and 42 downregulated proteins in the O blood type. GO term analysis indicated that downregulated proteins were primarily associated with lipid metabolism pathways. In vitro experiments revealed that reducing ABO gene expression decreased cholesterol uptake and increased cholesterol efflux. CONCLUSIONS: This study revealed that the non-O blood type increased the risk of LAA stroke through cholesterol metabolism.

A data-driven intravoxel mean diffusivities distribution approach for molecular classifications and MIB-1 prediction of gliomas.

BACKGROUND: Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes. PURPOSE: We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas. METHODS: An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR ∈ [ 30 , 300 ] $ \in [ {30,\ 300} ]$ . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years ± $ \pm $ 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions ( f n , n = 1 - 6 ${{f}_n},\ n = 1 -6$ ) and diffusivities of the maximum peaks ( D p e a k ${{D}_{peak}}$ ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation. RESULTS: The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis). f 3 , f 4 , D p e a k ${{f}_3},\ {{f}_4},{{D}_{peak}}$ showed a positive and negative correlation with MIB-1 respectively ( r = 0.568 , r = - 0.521 , r = - 0.654 $r = 0.568,\ r = - 0.521,\ r = - 0.654$ , all p < 0.001 $p < 0.001$ ). The AUC of D p e a k ${{D}_{peak}}$ for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model ( f 1 + f 3 ${{f}_1} + {{f}_3}$ ) was 0.873 (95% CI, 0.802-0.944). CONCLUSION: The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.

Occurrence and risk factors for post-stroke delirium: A systematic review and meta-analysis.

OBJECTIVES: Delirium is a significant health concern in acute stroke patients. We aim to systematically summarize existing evidence to conduct a meta-analysis to quantify the occurrence and risk factors for delirium after acute stroke. METHOD: PubMed, EMBASE and MEDLINE were searched from inception to Feb. 2023 for prospective observational studies that reported the incidence or prevalence of post-stroke delirium and/or evaluated potential risk factors. The search strategy was created using controlled vocabulary terms and text words for stroke and delirium. We performed a meta-analysis of the estimates for occurrence and risk factors using random-effects models. Meta-regression and subgroup meta-analyses were conducted to explore the sources of heterogeneity. Study quality and quality of evidence were assessed using the customized Newcastle-Ottawa Scale and GRADE, respectively. RESULTS: Forty-nine studies that enrolled 12383 patients were included. The pooled occurrence rate of post-stroke delirium was 24.4 % (95 %CI, 20.4 %-28.9 %, I2=96.2 %). The pooled occurrence of hyperactive, hypoactive, and mixed delirium was 8.5 %, 5.7 % and 5.0 %, respectively. Study location, delirium assessment method and stroke type independently affected the heterogeneity of the pooled estimate of delirium. Statistically significant risk factors were older age, low education level, cigarette smoking, alcohol drinking, atrial fibrillation, lower ADL level, higher pre-stroke mRS score, premorbid cognitive impairment or dementia, aphasia, total anterior circulation impairment, higher National Institute of Health Stroke Scale score and infection. CONCLUSIONS: Delirium affected 1 in 4 acute stroke patients, although reported rates may depend on assessment method and stroke type. Timely prevention, recognition and intervention require prioritizing patients with dominant risk factors.

The joint association of lipoprotein(a) and Lp-PLA2 with the risk of stroke recurrence.

BACKGROUND AND PURPOSE: Currently little is known about the joint association of lipoprotein (a) [Lp(a)] and Lipoprotein-associated phospholipase A2 (Lp-PLA2) with stroke recurrence. METHODS: In this prospective multicenter cohort study, 10,675 consecutive acute ischemic stroke (IS) and transient ischemic attack patients (TIA) with Lp(a) and Lp-PLA2 were enrolled. The association of stroke recurrence within 1 year with Lp(a) and Lp-PLA2 was assessed using Cox proportional hazards models and Kaplan-Meier curves. The interaction between Lp(a) and Lp-PLA2 with stroke recurrence was evaluated by multiplicative and additive scales. RESULTS: A significant joint association of Lp(a) and Lp-PLA2 with the risk of stroke recurrence was observed. Multivariate cox regression analysis demonstrated that the combination of elevated Lp(a) (≥ 50 mg/dL) and Lp-PLA2 (≥175.1 ng/ml) was independently associated with the risk of stroke recurrence (adjusted hazard ratio: 1.42; 95 % CI: 1.15-1.76). Both significant multiplicative [(exp(ß3):1.63, 95 % CI: 1.17-2.29, P = 0.004] and additive interaction (RERI:0.55, 95 % CI: 0.20-0.90, P = 0.002; AP: 0.39, 95 %CI, 0.24-0.53) were observed between Lp(a) and Lp-PLA2. CONCLUSIONS: Our results indicated that Lp(a) and Lp-PLA2 have a joint association with the risk of stroke recurrence in IS/TIA patients. Patients with concomitant presence of elevated Lp(a) and Lp-PLA2 have greater risk of stroke recurrence.

Modern perspectives of heavy metals alleviation from oil contaminated soil: A review.

Heavy metal poisoning of soil from oil spills causes serious environmental problems worldwide. Various causes and effects of heavy metal pollution in the soil environment are discussed in this article. In addition, this study explores new approaches to cleaning up soil that has been contaminated with heavy metals as a result of oil spills. Furthermore, it provides a thorough analysis of recent developments in remediation methods, such as novel nano-based approaches, chemical amendments, bioremediation, and phytoremediation. The objective of this review is to provide a comprehensive overview of the removal of heavy metals from oil-contaminated soils. This review emphasizes on the integration of various approaches and the development of hybrid approaches that combine various remediation techniques in a synergistic way to improve sustainability and efficacy. The study places a strong emphasis on each remediation strategy that can be applied in the real-world circumstances while critically evaluating its effectiveness, drawbacks, and environmental repercussions. Additionally, it discusses the processes that reduce heavy metal toxicity and improve soil health, taking into account elements like interactions between plants and microbes, bioavailability, and pollutant uptake pathways. Furthermore, the current study suggests that more research and development is needed in this area, particularly to overcome current barriers, improve our understanding of underlying mechanisms, and investigate cutting-edge ideas that have the potential to completely transform the heavy metal clean up industry.

Suppressing the virulence factors of Candida auris with baicalein through multifaceted mechanisms.

Candida auris, a rapidly spreading multi-drug-resistant fungus, is causing lethal infections under certain conditions globally. Baicalin (BE), an active ingredient extracted from the dried root of Scutellaria baicalensis Georgi, exhibits antifungal activity. However, studies have shown the distinctive advantages of Traditional Chinese medicine in combating fungal infections, while the effect of BE, an active ingredient extracted from the dried roots of Scutellaria baicalensis Georgi, on C. auris, remains unknown. Therefore, this study aims to evaluate the potential of BE as an antifungal agent against the emerging multidrug-resistant C. auris. Various assays and models, including microbroth dilution, time growth curve analysis, spot assays, adhesion tests, flocculation test, cell surface hydrophobicity assay, hydrolase activity assays, XTT assay, violet crystal assay, scanning electron microscope (SEM), confocal laser scanning microscope (CLSM), flow cytometry, Live/dead fluorescent staining, reactive oxygen species (ROS), cell wall assay, aggregation assay, porcine skin model, Galleria mellonella larvae (G. mellonella larvae) infection model, and reverse transcription-quantitative polymerase chain reaction (RT-PCR) were utilized to investigate how baicalein suppresses C. auris through possible multifaceted mechanisms. The findings indicate that BE strongly inhibited C. auris growth, adhesion, and biofilm formation. It also effectively reduced drug resistance and aggregation by disrupting the cell membrane and cell wall while reducing colonization and invasion of the host. Transcriptome analysis showed significant modulation in gene expression related to different virulence factors post-BE treatment. In conclusion, BE exhibits significant effectiveness against C. auris, suggesting its potential as a viable treatment option due to its multifaceted suppression mechanisms.

The cumulative analgesic effect of repeated electroacupuncture is modulated by Adora3 in the SCDH of mice with neuropathic pain.

BACKGROUND: Existing remedial approaches for relieving neuropathic pain (NPP) are challenging and open the way for alternative therapeutic measures such as electroacupuncture (EA). The mechanism underlying the antinociceptive effects of repeated EA sessions, particularly concerning the regulation of the Adora3 receptor and its associated enzymes, has remained elusive. METHODS: This study used a mouse model of spared nerve injury (SNI) to explore the cumulative analgesic effects of repeated EA at ST36 (Zusanli) and its impact on Adora3 regulation in the spinal cord dorsal horn (SCDH). Forty-eight male mice underwent SNI surgery for induction of neuropathic pain and were randomly assigned to the SNI, SNI + 2EA, SNI + 4EA, and SNI + 7EA groups. Spinal cord (L4-L6) was sampled for immunofluorescence, adenosine (ADO) detection and for molecular investigations following repeated EA treatment. RESULTS: Following spared nerve injury (SNI), there was a significant decrease in mechanical withdrawal thresholds (PWTs) and thermal nociceptive withdrawal latency (TWL) in the ipsilateral hind paw on the third day post-surgery, while the contralateral hind paw PWTs showed no significant changes. On subsequent EA treatments, the SNI + EA groups led to a significant increase in pain thresholds (p < 0.05). Repeated EA sessions in SNI mice upregulated Adenosine A3 (Adora3) and cluster of differentiation-73 (CD73) expression while downregulating adenosine deaminase (ADA) and enhancing neuronal instigation in the SCDH. Colocalization analysis of Neun-treated cells revealed increased Adora3 expression, particularly in the SNI + 7EA group. CONCLUSIONS: In conclusion, cumulative electroacupuncture treatment reduced neuropathic pain by regulating Adora3 and CD73 expression, inhibiting ADA and most likely increasing neuronal activation in the SCDH. This study offers a promising therapeutic option for managing neuropathic pain, paving the way for further research.

Integrating high-throughput phenotyping and genome-wide association studies for enhanced drought resistance and yield prediction in wheat.

Drought, especially terminal drought, severely limits wheat growth and yield. Understanding the complex mechanisms behind the drought response in wheat is essential for developing drought-resistant varieties. This study aimed to dissect the genetic architecture and high-yielding wheat ideotypes under terminal drought. An automated high-throughput phenotyping platform was used to examine 28 392 image-based digital traits (i-traits) under different drought conditions during the flowering stage of a natural wheat population. Of the i-traits examined, 17 073 were identified as drought-related. A genome-wide association study (GWAS) identified 5320 drought-related significant single-nucleotide polymorphisms (SNPs) and 27 SNP clusters. A notable hotspot region controlling wheat drought tolerance was discovered, in which TaPP2C6 was shown to be an important negative regulator of the drought response. The tapp2c6 knockout lines exhibited enhanced drought resistance without a yield penalty. A haplotype analysis revealed a favored allele of TaPP2C6 that was significantly correlated with drought resistance, affirming its potential value in wheat breeding programs. We developed an advanced prediction model for wheat yield and drought resistance using 24 i-traits analyzed by machine learning. In summary, this study provides comprehensive insights into the high-yielding ideotype and an approach for the rapid breeding of drought-resistant wheat.

Large-Kernel Attention for 3D Medical Image Segmentation.

Automated segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT) scans using deep learning methods can aid in diagnosing and treating cancer. However, organs often overlap and are complexly connected, characterized by extensive anatomical variation and low contrast. In addition, the diversity of tumor shape, location, and appearance, coupled with the dominance of background voxels, makes accurate 3D medical image segmentation difficult. In this paper, a novel 3D large-kernel (LK) attention module is proposed to address these problems to achieve accurate multi-organ segmentation and tumor segmentation. The advantages of biologically inspired self-attention and convolution are combined in the proposed LK attention module, including local contextual information, long-range dependencies, and channel adaptation. The module also decomposes the LK convolution to optimize the computational cost and can be easily incorporated into CNNs such as U-Net. Comprehensive ablation experiments demonstrated the feasibility of convolutional decomposition and explored the most efficient and effective network design. Among them, the best Mid-type 3D LK attention-based U-Net network was evaluated on CT-ORG and BraTS 2020 datasets, achieving state-of-the-art segmentation performance when compared to avant-garde CNN and Transformer-based methods for medical image segmentation. The performance improvement due to the proposed 3D LK attention module was statistically validated.

High-performing cross-dataset machine learning reveals robust microbiota alteration in secondary apical periodontitis.

Multiple research groups have consistently underscored the intricate interplay between the microbiome and apical periodontitis. However, the presence of variability in experimental design and quantitative assessment have added a layer of complexity, making it challenging to comprehensively assess the relationship. Through an unbiased methodological refinement analysis, we re-analyzed 4 microbiota studies including 120 apical samples from infected teeth (with/without root canal treatment), healthy teeth, using meta-analysis and machine learning. With high-performing machine-learning models, we discover disease signatures of related species and enriched metabolic pathways, expanded understanding of apical periodontitis with potential therapeutic implications. Our approach employs uniform computational tools across datasets to leverage statistical power and define a reproducible signal potentially linked to the development of secondary apical periodontitis (SAP).

A neutral invertase controls cell division besides hydrolysis of sucrose for nutrition during germination and seed setting in rice.

Sucrose is the transport form of carbohydrate in plants serving as signal molecule besides nutrition, but the signaling is elusive. Here, neutral invertase 8 (OsNIN8) mutated at G461R into OsNIN8m, which increased its charge and hydrophobicity, decreased hydrolysis of sucrose to 13% and firmer binding to sucrose than the wildtype. This caused downstream metabolites and energy accumulation forming overnutrition. Paradoxically, division of subinitials in longitudinal cell lineages was only about 15 times but more than 100 times in wildtype, resulting in short radicle. Further, mutation of OsNIN8 into deficiency of hydrolysis but maintenance of sucrose binding allowed cell division until ran out of energy showing the association but not hydrolysis gave the signal. Chemically, sucrose binding to OsNIN8 was exothermic but to OsNIN8m was endothermic. Therefore, OsNIN8m lost the signal function owing to change of thermodynamic state. So, OsNIN8 sensed sucrose for cell division besides hydrolyzed sucrose.

Influence of hypocalcemia on the prognosis of patients with multiple trauma.

BACKGROUND: Hypocalcemia is highly common in hospitalized patients, especially in those with trauma, On the other hand, abnormal calcium metabolism is an important metabolic challenge; however, it is often neglected and untreated, and certain factors may induce serious neurological and cardiovascular complications. AIM: To retrospectively analyze the impact of hypocalcemia on the prognosis of patients with multiple traumas. METHODS: The study was conducted from January 2020 to December 2021. Ninety-nine patients with multiple injuries were treated at the critical care medicine department of Fuyang People's Hospital. The selected indicators included sex, age, and blood calcium and hematocrit levels. Many indicators were observed, including within 24 h of hospitalization, and the prognosis was collected after 28 d. Based on the blood calcium levels, the patients were divided into the following two groups: Normocalcemia and hypocalcemia. Of the 99 patients included, 81 had normocalcemia, and 18 had hypocalcemia. Separate experiments were conducted for these two groups. RESULTS: There was an association between serum calcium levels and the prognosis of patients with polytrauma. CONCLUSION: Clinically, the prognosis of patients with multiple traumas can be preliminarily evaluated based on serum calcium levels.

Dysregulated Wnt/ß-catenin signaling confers resistance to cuproptosis in cancer cells.

Cuproptosis is characterized by the aggregation of lipoylated enzymes of the tricarboxylic acid cycle and subsequent loss of iron-sulfur cluster proteins as a unique copper-dependent form of regulated cell death. As dysregulation of copper homeostasis can induce cuproptosis, there is emerging interest in exploiting cuproptosis for cancer therapy. However, the molecular drivers of cancer cell evasion of cuproptosis were previously undefined. Here, we found that cuproptosis activates the Wnt/ß-catenin pathway. Mechanistically, copper binds PDK1 and promotes its interaction with AKT, resulting in activation of the Wnt/ß-catenin pathway and cancer stem cell (CSC) properties. Notably, aberrant activation of Wnt/ß-catenin signaling conferred resistance of CSCs to cuproptosis. Further studies showed the ß-catenin/TCF4 transcriptional complex directly binds the ATP7B promoter, inducing its expression. ATP7B effluxes copper ions, reducing intracellular copper and inhibiting cuproptosis. Knockdown of TCF4 or pharmacological Wnt/ß-catenin blockade increased the sensitivity of CSCs to elesclomol-Cu-induced cuproptosis. These findings reveal a link between copper homeostasis regulated by the Wnt/ß-catenin pathway and cuproptosis sensitivity, and suggest a precision medicine strategy for cancer treatment through selective cuproptosis induction.