Arrays of Bowl-Shaped Janus Particle Film with Structured Colors.

Structural colors generated via total internal reflection (TIR) using nanostructure-free micro-concave shapes have garnered increasing attention. However, the application of large micro-concave structures for structural coloration remains limited. Herein, a flexibly tunable structural color film fabricated by casting polydimethylsiloxane (PDMS) on an array of large poly(glycidyl methacrylate) (PGMA) bowl-shaped particles is reported. The resultant film exhibits tunable red to green structural colors with changing observation angles. Moreover, the color can be further tailored by altering the shape of the film itself. The incorporation of the PDMS layer not only facilitates a shift in the locus of TIR from the bottom surface to the top concave surface of the particles, thereby enabling the generation of structural color, but also confers enhanced flexibility to the film. Further decoration with silver nanoparticles imparts antimicrobial properties, yielding a novel antimicrobial coating material with structural colors. The simple and cost-effective strategy for the production of structural color films provides potential applications in antimicrobial coatings, enabling accessible and customizable structural coloration using big-size micro-concave particles.

Excessive accumulation of epicardial adipose tissue promotes microvascular obstruction formation after myocardial ischemia/reperfusion through modulating macrophages polarization.

BACKGROUND: Owing to its unique location and multifaceted metabolic functions, epicardial adipose tissue (EAT) is gradually emerging as a new metabolic target for coronary artery disease risk stratification. Microvascular obstruction (MVO) has been recognized as an independent risk factor for unfavorable prognosis in acute myocardial infarction patients. However, the concrete role of EAT in the pathogenesis of MVO formation in individuals with ST-segment elevation myocardial infarction (STEMI) remains unclear. The objective of the study is to evaluate the correlation between EAT accumulation and MVO formation measured by cardiac magnetic resonance (CMR) in STEMI patients and clarify the underlying mechanisms involved in this relationship. METHODS: Firstly, we utilized CMR technique to explore the association of EAT distribution and quantity with MVO formation in patients with STEMI. Then we utilized a mouse model with EAT depletion to explore how EAT affected MVO formation under the circumstances of myocardial ischemia/reperfusion (I/R) injury. We further investigated the immunomodulatory effect of EAT on macrophages through co-culture experiments. Finally, we searched for new therapeutic strategies targeting EAT to prevent MVO formation. RESULTS: The increase of left atrioventricular EAT mass index was independently associated with MVO formation. We also found that increased circulating levels of DPP4 and high DPP4 activity seemed to be associated with EAT increase. EAT accumulation acted as a pro-inflammatory mediator boosting the transition of macrophages towards inflammatory phenotype in myocardial I/R injury through secreting inflammatory EVs. Furthermore, our study declared the potential therapeutic effects of GLP-1 receptor agonist and GLP-1/GLP-2 receptor dual agonist for MVO prevention were at least partially ascribed to its impact on EAT modulation. CONCLUSIONS: Our work for the first time demonstrated that excessive accumulation of EAT promoted MVO formation by promoting the polarization state of cardiac macrophages towards an inflammatory phenotype. Furthermore, this study identified a very promising therapeutic strategy, GLP-1/GLP-2 receptor dual agonist, targeting EAT for MVO prevention following myocardial I/R injury.

Prospective cohort study evaluating efficacy and safety of efgartigimod in Chinese generalized myasthenia gravis patients.

Background: Despite the efficacy of efgartigimod demonstrated in ADAPT phase 3 trial, data specifically derived from Chinese participants are not available. Therefore, we aimed to evaluate the efficacy and safety of efgartigimod in Chinese patients with generalized myasthenia gravis (gMG). Methods: This is a prospective cohort study conducted in 8 hospitals across China. gMG patients received weekly intravenous infusions of efgartigimod (10 mg/kg) under a named patient program (NPP). The present study is an 8-week study, consisting of 4 consecutive doses of efgartigimod administered over 3 weeks (one cycle), followed by a 5-week follow-up period to assess the tolerability of efgartigimod's therapeutic effects. The primary outcome was the mean change in MG activities of daily living (MG-ADL) total score from baseline to 4 weeks. MG-ADL responder was defined as a ≥ 2-point improvement that persisted for 4 weeks, starting by week 4. Safety evaluations encompassed the monitoring of adverse events (AE) and serious AE (SAE) throughout the study. Results: Between 5 July 2022 and 25 August 2023, a total of 14 gMG patients were included. The mean age was 57.7 years, with a mean MG-ADL score of 10.86 ± 3.32. At week 4, MG-ADL scores showed a mean reduction of 6 points, reaching a maximum decline of 13 points. Among the patients, 85.7% (12/14) achieved MG-ADL responder status after one cycle of treatment. The most significant reduction in quantitative MG (QMG) scores also occurred at week 4, with a mean decrease of 7 points. Notably, the improvements in MG-ADL and QMG scores persisted until week 8. During treatment and follow-up period, only two mild neck rashes occurred and resolved promptly. No infections or SAE were reported. Discussion: A single cycle of efgartigimod treatment demonstrates effectiveness and the tolerability through week 8, with no new safety signals observed in Chinese gMG patients.

An Overview of Infectious and Non-Infectious Causes of Pregnancy Losses in Equine.

Equine breeding plays an essential role in the local economic development of many countries, and it has experienced rapid growth in China in recent years. However, the equine industry, particularly large-scale donkey farms, faces a significant challenge with pregnancy losses. Unfortunately, there is a lack of systematic research on abortion during equine breeding. Several causes, both infectious and non-infectious, of pregnancy losses have been documented in equines. The infectious causes are viruses, bacteria, parasites, and fungi. Non-infectious causes may include long transportation, ingestion of mycotoxins, hormonal disturbances, twinning, placentitis, umbilical length and torsion, etc. In current review, we discuss the transmission routes, diagnostic methods, and control measures for these infectious agents. Early detection of the cause and appropriate management are crucial in preventing pregnancy loss in equine practice. This review aims to provide a comprehensive understanding of the potential causes of abortion in equines, including infectious agents and non-infectious factors. It emphasizes the importance of continued research and effective control measures to address this significant challenge in the equine industry.

The effect of preeclampsia on long-term kidney function among pregnant women with chronic kidney disease.

BACKGROUND AND HYPOTHESIS: The association between superimposed preeclampsia and an elevated risk of long-term kidney function decline or end-stage kidney disease (ESKD) in patients with chronic kidney disease (CKD) has not been determined. This study aimed to analyze the association between preeclampsia and kidney function deterioration in CKD patients. METHODS: This was a retrospective cohort study that included the clinical information of 103 pregnant CKD patients with preeclampsia and 103 matched CKD patients without preeclampsia who were followed-up for a minimum of 1 year after their first pregnancy from January 1, 2009, to May 31, 2022. Robust Cox regression analysis was also conducted to evaluate the effects of preeclampsia on long-term kidney function decline or ESKD in CKD patients. K-M curves were used to compare renal survival within different subgroups via the log-rank test. RESULTS: During the follow-up period, 44 (42.72%) CKD patients with preeclampsia and 20 (19.42%) without preeclampsia had an estimated glomerular filtration rate (eGFR) decrease >30% or developed ESKD. Compared with CKD patients without preeclampsia, the eGFR decreased more significantly in patients with preeclampsia [98.43 (79.48, 116.47) to 81.32 (41.20, 102.97) mL/min/1.73 m2 vs. 99.43 (79.00, 118.50) to 89.44 (63.69, 105.30) mL/min/1.73 m2; P=0.034]. The rate of eGFR decrease was more pronounced in patients with preeclampsia (17.38% vs. 10.05%, p<0.05). Multivariate analysis revealed that early-onset preeclampsia (preeclampsia that developed before 34 weeks of gestation) (HR=2.61, 95% CI=1.32-5.16, P=0.006) and late-onset preeclampsia (HR=2.54, 95% CI=1.34-4.83, P=0.004) were both risk factors for an eGFR decrease >30% or ESKD. CONCLUSION: Preeclampsia was associated with a greater risk of long-term kidney function decline or ESKD among CKD patients, especially in patients with early-onset preeclampsia.

A biomechanics and energetics dataset of neurotypical adults walking with and without kinematic constraints.

Numerous studies have explored the biomechanics and energetics of human walking, offering valuable insights into how we walk. However, prior studies focused on changing external factors (e.g., walking speed) and examined group averages and trends rather than individual adaptations in the presence of internal constraints (e.g., injury-related muscle weakness). To address this gap, this paper presents an open dataset of human walking biomechanics and energetics collected from 21 neurotypical young adults. To investigate the effects of internal constraints (reduced joint range of motion), the participants are both the control group (free walking) and the intervention group (constrained walking - left knee fully extended using a passive orthosis). Each subject walked on a dual-belt treadmill at three speeds (0.4, 0.8, and 1.1 m/s) and five step frequencies ( - 10% to 20% of their preferred frequency) for a total of 30 test conditions. The dataset includes raw and segmented data featuring ground reaction forces, joint motion, muscle activity, and metabolic data. Additionally, a sample code is provided for basic data manipulation and visualisation.

Temporal Dynamic Synchronous Functional Brain Network for Schizophrenia Classification and Lateralization Analysis.

Available evidence suggests that dynamic functional connectivity can capture time-varying abnormalities in brain activity in resting-state cerebral functional magnetic resonance imaging (rs-fMRI) data and has a natural advantage in uncovering mechanisms of abnormal brain activity in schizophrenia (SZ) patients. Hence, an advanced dynamic brain network analysis model called the temporal brain category graph convolutional network (Temporal-BCGCN) was employed. Firstly, a unique dynamic brain network analysis module, DSF-BrainNet, was designed to construct dynamic synchronization features. Subsequently, a revolutionary graph convolution method, TemporalConv, was proposed based on the synchronous temporal properties of features. Finally, the first modular test tool for abnormal hemispherical lateralization in deep learning based on rs-fMRI data, named CategoryPool, was proposed. This study was validated on COBRE and UCLA datasets and achieved 83.62% and 89.71% average accuracies, respectively, outperforming the baseline model and other state-of-the-art methods. The ablation results also demonstrate the advantages of TemporalConv over the traditional edge feature graph convolution approach and the improvement of CategoryPool over the classical graph pooling approach. Interestingly, this study showed that the lower-order perceptual system and higher-order network regions in the left hemisphere are more severely dysfunctional than in the right hemisphere in SZ, reaffirmings the importance of the left medial superior frontal gyrus in SZ. Our code was available at: https://github.com/swfen/Temporal-BCGCN.

Introducing and Validating the Cranial-Dorsal-Hip Angle (∠CDH): A Method for Accurate Fetal Position Assessment in the First Trimester and Future AI Applications.

Purpose To introduce the cranial-dorsal-hip angle (∠CDH) as a novel quantitative tool for assessing fetal position in the first trimester and to validate its feasibility for future AI applications. Materials and Methods 2520 first-trimester fetal NT exams with 2582 CRL images (January-August 2022) were analyzed at a tertiary hospital as the pilot group. Additionally, 1418 cases with 1450 fetal CRL images (September-December 2022) were examined for validation. Three expert sonographers defined a standard for fetal positions. ∠CDH measurements, conducted by two ultrasound technicians, were validated for consistency using Bland-Altman plots and the intra-class correlation coefficient (ICC). This method allowed for categorizing fetal positions as hyperflexion, neutral, and hyperextension based on ∠CDH. Comparative accuracy was assessed against Ioannou, Wanyonyi, and Roux methods using the weighted Kappa coefficient (k value). Results The pilot group comprised 2186 fetal CRL images, and the validation group included 1193 images. Measurement consistency was high (ICCs of 0.993; P<0.001). The established 95% reference range for ∠CDH in the neutral fetal position was 118.3° to 137.8°. The ∠CDH method demonstrated superior accuracy over the Ioannou, Wanyonyi, and Roux methods in both groups, with accuracy rates of 94.5% (k values: 0.874, 95%CI: 0.852-0.896) in the pilot group, and 92.6% (k values: 0.838, 95%CI: 0.806-0.871) in the validation group. Conclusion The ∠CDH method has been validated as a highly reproducible and accurate technique for first-trimester fetal position assessment. This sets the stage for its potential future integration into intelligent assessment models.

Identification of disulfidptosis-associated genes and characterization of immune cell infiltration in thyroid carcinoma.

OBJECTIVE: The primary objective of this study is to conduct a comprehensive screening and analysis of differentially expressed genes related to disulfidoptosis (DEDRGs) in thyroid carcinoma (THCA). This entails delving into the intricate characterization of immune cell infiltration within the THCA context and subsequently formulating and validating a novel prognostic model. METHOD: To achieve our objectives, we first delineated two distinct subtypes of disulfidoptosis-related genes (DRGs) via consensus clustering methodology. Subsequently, employing the limma R package, we identified the DEDRGs critical for our investigation. These DEDRGs underwent meticulous validation across various databases, alongside an in-depth analysis of gene regulation. Employing functional enrichment techniques, we explored the potential molecular mechanisms underlying disulfidoptosis in THCA. Furthermore, we scrutinized the immune landscape within the two identified subtypes utilizing CIBERSORT and ESTIMATE algorithms. The construction of the prognostic model for THCA entailed intricate methodologies including univariate, multivariate Cox regression, and LASSO regression algorithms. The validity and efficacy of our prognostic model were corroborated through Kaplan-Meier survival curves and ROC curves. Additionally, a nomogram was meticulously formulated to facilitate the prediction of patient prognosis. To fortify our findings, we conducted a comprehensive Bayesian co-localization analysis coupled with rigorous in vitro experimentation, aimed at unequivocally establishing the validity of the identified DEDRGs. RESULT: Our analyses unveiled Cluster C1, characterized by elevated expression levels of DEDRGs, as harboring a favorable prognosis accompanied by abundant immune cell infiltration. Correlation analyses underscored predominantly positive associations among the DEDRGs, further affirming their significance in THCA. Differential expression patterns of DEDRGs between tumor samples and normal tissues were evident across the GEPIA and HPA databases. Insights from the TIMER database underscored a robust correlation between DEDRGs and immune cell infiltration. KEGG analysis elucidated the enrichment of DEDRGs primarily in pivotal pathways including MAPK, PPAR signaling pathway, and Proteoglycans in cancer. Furthermore, analyses using CIBERSORT and ESTIMATE algorithms shed light on the crucial role played by DEDRGs in shaping the immune microenvironment. The prognostic model, anchored by five genes intricately associated with THCA prognosis, exhibited commendable predictive accuracy and was intricately linked to the tumor immune microenvironment. Notably, patients categorized with low-risk scores stood to potentially benefit more from immunotherapy. The validation of DEDRGs unequivocally underscores the protective role of INF2 in THCA. CONCLUSION: In summary, our study delineates two discernible subtypes intricately associated with DRGs, revealing profound disparities in immune infiltration and survival prognosis within the THCA milieu. The implications of our findings extend to potential treatment strategies for THCA patients, which could entail targeted interventions directed towards DEDRGs and prognostic genes, thereby influencing disulfidptosis and the immune microenvironment. Moreover, the robust predictive capability demonstrated by our prognostic model, based on the five genes (ANGPTL7, FIRRE, ODAPH, PROKR1, SFRP5), underscores its potential clinical utility in guiding personalized therapeutic approaches for THCA patients.

Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach.

OBJECTIVES: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis-associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients. METHODS: GWAS data was analyzed for genetic association between AKI and sepsis. Then, we systematically applied three distinct machine learning algorithms (LASSO, SVM-RFE, RF) to rigorously identify and validate signature genes of SA-AKI, assessing their diagnostic and prognostic value through ROC curves and survival analysis. The study also examined the functional and immunological aspects of these genes, potential drug targets, and ceRNA networks. A mouse model of sepsis was created to test the reliability of these signature genes. RESULTS: LDSC confirmed a positive genetic correlation between AKI and sepsis, although no significant shared loci were found. Bidirectional MR analysis indicated mutual increased risks of AKI and sepsis. Then, 311 key genes common to sepsis and AKI were identified, with 42 significantly linked to sepsis prognosis. Six genes, selected through LASSO, SVM-RFE, and RF algorithms, showed excellent predictive performance for sepsis, AKI, and SA-AKI. The models demonstrated near-perfect AUCs in both training and testing datasets, and a perfect AUC in a sepsis mouse model. Significant differences in immune cells, immune-related pathways, HLA, and checkpoint genes were found between high- and low-risk groups. The study identified 62 potential drug treatments for sepsis and AKI and constructed a ceRNA network. CONCLUSIONS: The identified signature genes hold potential clinical applications, including prognostic evaluation and targeted therapeutic strategies for sepsis and AKI. However, further research is needed to confirm these findings.

Injectable alginate-based zwitterionic hydrogels promoting endometrial repair and restoring fertility.

The development of novel therapeutic approaches to facilitate endometrial repair and regeneration while preventing adhesion recurrence is a crucial research objective aimed at enhancing clinical outcomes for women with intrauterine adhesions (IUA). In this study, we introduced an injectable Alg-GMA/PTSB zwitterionic hydrogel, characterized by excellent biocompatibility, anti-protein adsorption properties, and biodegradability. In a rat model, the hydrogel significantly promoted the regeneration and angiogenesis of damaged endometrial tissue, leading to improved recovery of epithelial cells, glands, proliferation, and vascularization. Furthermore, it exhibited the ability to suppress cellular apoptosis and collagen deposition, thereby mitigating fibrosis. Additionally, the hydrogel restored the expression of estrogen/progesterone receptors and endometrial receptivity markers, contributing to enhanced embryo implantation and fertility. These findings underscore the potential of the hydrogel as a promising therapeutic strategy for addressing endometrial injury, reducing fibrosis, restoring fertility, and ultimately improving outcomes for women with IUA.

Identification of microtubule-associated biomarker using machine learning methods in osteonecrosis of the femoral head and osteosarcoma.

Background: This study aims to explore the microtubule-associated gene signatures and molecular processes shared by osteonecrosis of the femoral head (ONFH) and osteosarcoma (OS). Methods: Datasets from the TARGET and GEO databases were subjected to bioinformatics analysis, including the functional enrichment analysis of genes shared by ONFH and OS. Prognostic genes were identified using univariate and multivariate Cox regression analyses to develop a risk score model for predicting overall survival and immune characteristics. Furthermore, LASSO and SVM-RFE algorithms identified biomarkers for ONFH, which were validated in OS. Function prediction, ceRNA network analysis, and gene-drug interaction network construction were subsequently conducted. Biomarker expression was then validated on clinical samples by using qPCR. Results: A total of 14 microtubule-associated disease genes were detected in ONFH and OS. Subsequently, risk score model based on four genes was then created, revealing that patients with low-risk exhibited superior survival outcomes compared with those with high-risk. Notably, ONFH with low-risk profiles may manifest an antitumor immune microenvironment. Moreover, by utilizing LASSO and SVM-RFE algorithms, four diagnostic biomarkers were pinpointed, enabling effective discrimination between patients with ONFH and healthy individuals as well as between OS and normal tissues. Additionally, 21 drugs targeting these biomarkers were predicted, and a comprehensive ceRNA network comprising four mRNAs, 71 miRNAs, and 98 lncRNAs was established. The validation of biomarker expression in clinical samples through qPCR affirmed consistency with the results of bioinformatics analysis. Conclusion: Microtubule-associated genes may play pivotal roles in OS and ONFH. Additionally, a prognostic model was constructed, and four genes were identified as potential biomarkers and therapeutic targets for both diseases.

Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.

BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in literature include incomplete reporting of model performance, inadequate alignment of model formulation with implementation use-case, and insufficient explainability hindering trust and adoption in clinical settings. Hence, we aim to develop an explainable machine learning EHR-based model that prompts palliative care processes by predicting for 365-day mortality risk among patients with advanced cancer within an outpatient setting. METHODS: Our cohort consisted of 5,926 adults diagnosed with Stage 3 or 4 solid organ cancer between July 1, 2017, and June 30, 2020 and receiving ambulatory cancer care within a tertiary center. The classification problem was modelled using Extreme Gradient Boosting (XGBoost) and aligned to our envisioned use-case: "Given a prediction point that corresponds to an outpatient cancer encounter, predict for mortality within 365-days from prediction point, using EHR data up to 365-days prior." The model was trained with 75% of the dataset (n = 39,416 outpatient encounters) and validated on a 25% hold-out dataset (n = 13,122 outpatient encounters). To explain model outputs, we used Shapley Additive Explanations (SHAP) values. Clinical characteristics, laboratory tests and treatment data were used to train the model. Performance was evaluated using area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC), while model calibration was assessed using the Brier score. RESULTS: In total, 17,149 of the 52,538 prediction points (32.6%) had a mortality event within the 365-day prediction window. The model demonstrated an AUROC of 0.861 (95% CI 0.856-0.867) and AUPRC of 0.771. The Brier score was 0.147, indicating slight overestimations of mortality risk. Explanatory diagrams utilizing SHAP values allowed visualization of feature impacts on predictions at both the global and individual levels. CONCLUSION: Our machine learning model demonstrated good discrimination and precision-recall in predicting 365-day mortality risk among individuals with advanced cancer. It has the potential to provide personalized mortality predictions and facilitate earlier integration of palliative care.

Opportunistic atrial fibrillation screening in primary care in Ireland: results of a pilot screening programme.

BACKGROUND: Atrial fibrillation (AF), a common, frequently asymptomatic cardiac arrhythmia, is a major risk factor for stroke. Identification of AF enables effective preventive treatment to be offered, potentially reducing stroke risk by up to two-thirds. There is international consensus that opportunistic AF screening is valuable though uncertainty remains about the optimum screening location and method. Primary care has been identified as a potential location for AF screening using one-lead ECG devices. METHODS: A pilot AF screening programme is in primary care in the south of Ireland. General practitioners (GPs) were recruited from Cork and Kerry. GPs invited patients ≥65 years to undergo AF screening. The screening comprised a one-lead ECG device, Kardia Mobile, blood pressure check and ascertainment of smoking status. Possible AF on one-lead ECG was confirmed with a 12-lead ECG. GPs also recorded information including medical history, current medication and onward referral. The Keele Decision Support tool was used to assess patients for oral anticoagulation (OAC). RESULTS: 3555 eligible patients, attending 52 GPs across 34 GP practices, agreed to undergo screening. 1720 (48%) were female, 1780 (50%) were hypertensive and 285 (8%) were current smokers. On the one-lead ECG, 3282 (92%) were in normal sinus rhythm, 101 (3%) had possible AF and among 124 (4%) the one-lead ECG was unreadable or unclassified. Of the 101 patients with possible AF, 45 (45%) had AF confirmed with 12-lead ECG, an incidence rate of AF of 1.3%. Among the 45 confirmed AF cases, 27 (60%) were commenced on OAC therapy by their GP. CONCLUSION: These findings suggest that AF screening in primary care may prove useful for early detection of AF cases that can be assessed for treatment. One-lead ECG devices may be useful in the detection of paroxysmal AF in this population and setting. Current OAC of AF may be suboptimal.

Comparative effectiveness of myocardial patches and intramyocardial injections in treating myocardial infarction with a MitoQ/hydrogel system.

In cardiac tissue engineering, myocardial surface patches and hydrogel intramyocardial injections represent the two primary hydrogel-based strategies for myocardial infarction (MI) treatment. However, the comparative effectiveness of these two treatments remains uncertain. Therefore, this study aimed to compare the effects of the two treatment modalities by designing a simple and reproducible hydrogel cross-linked with γ-PGA and 4-arm-PEG-SG. To improve mitochondrial damage in cardiomyocytes (CMs) during early MI, we incorporated the mitochondria-targeting antioxidant MitoQ into the hydrogel network. The hydrogel exhibited excellent biodegradability, biocompatibility, adhesion, and injectability in vitro. The hydrogel was utilized for rat MI treatment through both patch adhesion and intramyocardial injections. In vivo results demonstrated that the slow release of MitoQ peptide from the hydrogel hindered ROS production in CM, alleviated mitochondrial damage, and enhanced CM activity within 7 days, effectively inhibiting MI progression. Both hydrogel intramyocardial injections and patches exhibited positive therapeutic effects, with intramyocardial injections demonstrating superior efficacy in terms of cardiac function and structure in equivalent treatment cycles. In conclusion, we developed a MitoQ/hydrogel system that is easily prepared and can serve as both a myocardial patch and an intramyocardial injection for MI treatment, showing significant potential for clinical applications.

OsLCD3 interacts with OsSAMS1 to regulate grain size via ethylene/polyamine homeostasis control.

A fundamental question in developmental biology is how to regulate grain size to improve crop yields. Despite this, little is still known about the genetics and molecular mechanisms regulating grain size in crops. Here, we provide evidence that a putative protein kinase-like (OsLCD3) interacts with the S-adenosyl-L-methionine synthetase 1 (OsSAMS1) and determines the size and weight of grains. OsLCD3 mutation (lcd3) significantly increased grain size and weight by promoting cell expansion in spikelet hull, whereas its overexpression caused negative effects, suggesting that grain size was negatively regulated by OsLCD3. Importantly, lcd3 and OsSAMS1 overexpression (SAM1OE) led to large and heavy grains, with increased ethylene and decreased polyamines production. Based on genetic analyses, it appears that OsLCD3 and OsSAMS1 control rice grain size in part by ethylene/polyamine homeostasis. The results of this study provide a genetic and molecular understanding of how the OsLCD3-OsSAMS1 regulatory module regulates grain size, suggesting that ethylene/polyamine homeostasis is an appropriate target for improving grain size and weight.

Changes in planta K nutrient content altered the interaction pattern between Nicotiana benthamiana and Alternaria longipes.

Potassium (K) fertilisation has frequently been shown to enhance plant resistance against pathogens, though the mechanisms remain elusive. This study investigates the interaction dynamics between Nicotiana benthamiana and the pathogen Alternaria longipes under different planta K levels. On the host side, adding K activated the expressions of three NLR (nucleotide-binding domain and leucine-rich repeat-containing proteins) resistance genes, including NbRPM1, NbR1B23 and NbNBS12. Silencing these NLRs attenuated resistance in high-K (HK, 40.8 g/kg) plant, whereas their overexpression strengthened resistance in low-K (LK, 23.9 g/kg) plant. Typically, these NLRs mainly strengthened plant resistance via promoting the expression of pathogenesis-related genes (PRs), ROS burst and synthesis of antifungal metabolites in HK plant. On the pathogen side, the expression of effectors HKCSP1, HKCSP2 and LKCSP were shown to be related to planta K content. A. longipes mainly expressed effectors HKCSP1 and HKCSP2 in HK plant to interfere host resistance. HKCSP1 physically interacted with NbRPM1 to promote the degradation of NbRPM1, then attenuated related resistance in HK N. benthamiana. Meanwhile, HKCSP2 directly interacted with NbPR5 to suppress resistance in HK plant. In LK plant, A. longipes mainly deployed LKCSP that interacted with NbR1B23 to interfere reduce resistance in N. benthamiana. Overall, our research insights that both pathogen and host mobilise distinct strategies to outcompete each other during interactions in different K nutrient environments.

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing.

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcriptome sequencing and bulk RNA-seq. Using single-cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage-related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH-associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment.

Therapeutic effects of orexin-A in sepsis-associated encephalopathy in mice.

BACKGROUND: Sepsis-associated encephalopathy (SAE) causes acute and long-term cognitive deficits. However, information on the prevention and treatment of cognitive dysfunction after sepsis is limited. The neuropeptide orexin-A (OXA) has been shown to play a protective role against neurological diseases by modulating the inflammatory response through the activation of OXR1 and OXR2 receptors. However, the role of OXA in mediating the neuroprotective effects of SAE has not yet been reported. METHODS: A mouse model of SAE was induced using cecal ligation perforation (CLP) and treated via intranasal administration of exogenous OXA after surgery. Mouse survival, in addition to cognitive and anxiety behaviors, were assessed. Changes in neurons, cerebral edema, blood-brain barrier (BBB) permeability, and brain ultrastructure were monitored. Levels of pro-inflammatory factors (IL-1ß, TNF-α) and microglial activation were also measured. The underlying molecular mechanisms were investigated by proteomics analysis and western blotting. RESULTS: Intranasal OXA treatment reduced mortality, ameliorated cognitive and emotional deficits, and attenuated cerebral edema, BBB disruption, and ultrastructural brain damage in mice. In addition, OXA significantly reduced the expression of the pro-inflammatory factors IL-1ß and TNF-α, and inhibited microglial activation. In addition, OXA downregulated the expression of the Rras and RAS proteins, and reduced the phosphorylation of P-38 and JNK, thus inhibiting activation of the MAPK pathway. JNJ-10,397,049 (an OXR2 blocker) reversed the effect of OXA, whereas SB-334,867 (an OXR1 blocker) did not. CONCLUSION: This study demonstrated that the intranasal administration of moderate amounts of OXA protects the BBB and inhibits the activation of the OXR2/RAS/MAPK pathway to attenuate the outcome of SAE, suggesting that OXA may be a promising therapeutic approach for the management of SAE.

Evaluating the surgical trainee ergonomic experience during minimally invasive abdominal surgery (ESTEEMA study).

Minimally invasive abdominal surgery (MAS) can exert a physical cost. Surgical trainees spend years assisting minimally-invasive surgeries, increasing the risk of workplace injury. This prospective questionnaire-based cohort study was conducted amongst general surgery residents in Singapore. Residents assisting major MAS surgery were invited to complete anonymous online survey forms after surgery. The Phase 1 survey assessed physical discomfort scores and risk factors. Intraoperative measures to improve ergonomics were administered and evaluated in Phase 2. During Phase 1 (October 2021 to April 2022), physical discomfort was reported in at least one body part in 82.6% (n = 38) of respondents. Over a third of respondents reported severe discomfort in at least one body part (n = 17, 37.0%). Extremes of height, training seniority, longer surgical duration and operative complexity were significant risk factors for greater physical discomfort. In Phase 2 (October 2022 to February 2023), the overall rate of physical symptoms and severe discomfort improved to 81.3% (n = 52) and 34.4% (n = 22) respectively. The ergonomic measure most found useful was having separate television monitors for the primary surgeon and assistants, followed by intraoperative feedback on television monitor angle or position. Close to 20% of survey respondents felt that surgeon education was likely to improve physical discomfort.