An open auscultation dataset for machine learning-based respiratory diagnosis studies.

Machine learning enabled auscultating diagnosis can provide promising solutions especially for prescreening purposes. The bottleneck for its potential success is that high-quality datasets for training are still scarce. An open auscultation dataset that consists of samples and annotations from patients and healthy individuals is established in this work for the respiratory diagnosis studies with machine learning, which is of both scientific importance and practical potential. A machine learning approach is examined to showcase the use of this new dataset for lung sound classifications with different diseases. The open dataset is available to the public online.

Automated segmentation of liver and hepatic vessels on portal venous phase computed tomography images using a deep learning algorithm.

BACKGROUND: CT-image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time-consuming process and inter-observer variations of manual segmentation have limited wider application in clinical practice. PURPOSE: Our study aimed to propose an automated deep learning (DL) segmentation algorithm for liver and hepatic vessels on portal venous phase CT images. METHODS: This retrospective study was performed to develop a coarse-to-fine DL-based algorithm that was trained, validated, and tested using private 413, 52, and 50 portal venous phase CT images, respectively. Additionally, the performance of the DL algorithm was extensively evaluated and compared with manual segmentation using an independent clinical dataset of preoperative contrast-enhanced CT images from 44 patients with hepatic focal lesions. The accuracy of DL-based segmentation was quantitatively evaluated using the Dice Similarity Coefficient (DSC) and complementary metrics [Normalized Surface Dice (NSD) and Hausdorff distance_95 (HD95) for liver segmentation, Recall and Precision for hepatic vessel segmentation]. The processing time for DL and manual segmentation was also compared. RESULTS: Our DL algorithm achieved accurate liver segmentation with DSC of 0.98, NSD of 0.92, and HD95 of 1.52 mm. DL-segmentation of hepatic veins, portal veins, and inferior vena cava attained DSC of 0.86, 0.89, and 0.94, respectively. Compared with the manual approach, the DL algorithm significantly outperformed with better segmentation results for both liver and hepatic vessels, with higher accuracy of liver and hepatic vessel segmentation (all p < 0.001) in independent 44 clinical data. In addition, the DL method significantly reduced the manual processing time of clinical postprocessing (p < 0.001). CONCLUSIONS: The proposed DL algorithm potentially enabled accurate and rapid segmentation for liver and hepatic vessels using portal venous phase contrast CT images.

The bidirectional relationship between activities of daily living and frailty during short-and long-term follow-up period among the middle-aged and older population: findings from the Chinese nationwide cohort study.

Objective: Frailty and activities of daily living (ADL) disability are common conditions among older population. Studies on the bidirectional relationship between frailty and ADL are limited. The current study examined the cross-sectional and longitudinal associations between frailty and ADL in middle-aged and older Chinese individuals. Methods: The data was collected through the China Health and Retirement Longitudinal Study (CHARLS), conducted in 2011, 2013, and 2015, encompassing 17,284 individuals aged ≥45 years. We excluded individuals without follow-up data. 2,631 participants finished the baseline survey. The definition of ADL disability encompasses difficulty in engaging in either basic activities of daily living (BADL) or instrumental activities of daily living (IADL). Frailty was assessed according to the Fried criteria. Logistic regression was utilized to examine odds ratios (ORs) and 95% confidence intervals (CIs) for assessing the cross-sectional relationships between ADL with frailty at baseline. The prediction effects were explored using Cox proportional hazards analysis, testing hazard ratios (HRs) and 95%CIs. Results: In cross-sectional analysis, BADL [OR = 6.660 (4.519-9.815)], IADL [OR = 5.950 (4.490-7.866)], and ADL [OR = 5.658 (4.278-7.483)] exhibited significant associations with frailty; frailty demonstrated significant associations with BADL [OR = 6.741 (4.574-9.933)], IADL [OR = 6.042 (4.555-8.016)] and ADL [OR = 5.735 (4.333-7.591)]. In longitudinal analysis, IADL and ADL were significantly associated with frailty in participants without baseline frailty in the short-term period [IADL: HR = 1.971 (1.150-3.379), ADL: HR = 1.920 (1.146-3.215)], IADL exhibited a significant association with frailty in the long-term period [HR = 2.056 (1.085-3.895)]. There was no significant link observed between frailty and an elevated risk of disability onset in BADL, IADL and ADL during the short-term period. When considering the long-term perspective, frailty exhibited a significant association with an elevated risk of disability onset in BADL [HR= 1.820 (1.126-2.939)] and IADL [HR = 1.724 (1.103-2.694)]. Conclusion: In middle-aged and older adults, ADL and IADL disability predicted frailty after 2-year follow-up, IADL disability predicted frailty after 4-year follow-up. Moreover, frailty did not predict BADL, IADL and ADL disability after 2-year follow-up. However, frailty predicted BADL and IADL disability after 4-year follow-up.

Radiological Features for Predicting the Status of CD8-Positive Lymphocytes in HER2 Positive Breast Cancer.

Background: The level of tumor-infiltrating lymphocytes (TILs) in human epidermal growth factor receptor type 2 (HER2)-positive breast cancer (BC) is positively correlated with pathological complete response. Aims: To investigate the relationship between ultrasound (US) and magnetic resonance imaging (MRI) features and the level of CD8-positive TILs (CD8+-TILs) in patients with HER2-positive BC. Study Design: Retrospective cohort study. Methods: This retrospective study included 155 consecutive women with HER2-positive BC. Patients were divided into two groups: CD8+-TILlow (< 35%) and CD8+-TILhigh (≥ 35%) groups. US and MRI features were evaluated using the BI-RADS lexicon, and the apparent diffusion coefficient (ADC) value was calculated using RadiAnt software. Univariate and multivariate analyses revealed the optimal US and MRI features for predicting CD8+-TIL levels. Receiver operating characteristic analysis and the Delong test were used to compare the diagnostic performance of US and MRI features. Furthermore, implementing a nomogram will increase clinical utility. Results: Univariate analysis of US features showed significant differences in shape, orientation, and posterior echo between the two groups; however, there were no significant differences in margins, internal echo, and microcalcification. Multifactorial analysis revealed that shape, orientation, and posterior echo were independent risk factors, with odds ratios of 11.62, 2.70, and 0.16, respectively. In terms of MRI features, ADC was an independent predictor of CD8+-TIL levels. These three US features and the ADC performed well, with area under the curve (AUC) values of 0.802 and 0.705, respectively. The combination of US and ADC values had higher predictive efficacy (AUC = 0.888) than either US or ADC alone (p = 0.009, US_ADC vs. US; p < 0.001, US_ADC vs. ADC). Conclusion: US features (shape, orientation, and posterior echo) and ADC value may be a valuable tool for estimating CD8+-TIL levels in HER2-positive BC. The nomogram may help clinicians in making decisions.

ICT diffusion and financial development: Comparing high, middle, and low-income countries.

Given the importance of ICT diffusion in the development of the financial sector, this analysis is an effort to analyze the transmission channels between the two in high-income and middle and low-income economies over 2001-2019. We have used three variables, including the ICT index, individuals using the internet, and mobile subscribers, to represent ICT and three indices, including the financial development index, financial institution index, and financial market index, to make our results reliable and robust. We utilized a GMM method for conducting the empirical analysis. Generally, our results imply that ICT diffusion positively impacts financial development in high-income economies and negatively impacts middle and low-income economies. Our findings suggest that middle- and low-income-economy policymakers should follow the footprint of the high-income economies and increase the role of ICT in the financial sector for its development.

Maintenance treatment of immunotherapy after microwave ablation plus drug-eluting bead bronchial arterial chemoembolization for advanced non-small cell lung cancer: a retrospective single-center cohort study.

Background: The combination therapy of immunotherapy and drug-eluting bead bronchial artery chemoembolization (DEB-BACE) or microwave ablation (MWA) has been attempted as an effective and safe approach for advanced non-small cell lung cancer (NSCLC). However, the outcomes of immunotherapy plus multiple interventional techniques for advanced NSCLC remain unclear. This retrospective study thus aimed to investigate the effectiveness and safety of the maintenance treatment of programmed cell death protein 1 (PD-1) blockade after MWA plus DEB-BACE for advanced NSCLC. Methods: This retrospective cohort study consists of 95 patients with advanced NSCLC who were treated with DEB-BACE between April 2017 and October 2022 and who were allocated to three groups: group A (MWA + DEB-BACE + PD-1 blockade; n=15), group B (MWA + DEB-BACE; n=25), and group C (DEB-BACE alone; n=55). The adverse events (AEs) were compared between the three groups. The outcomes were compared via Kaplan-Meier methods, including median progression-free survival (PFS) and overall survival (OS). Survival analyses were performed via the univariate and multivariate analyses to investigate the prognostic predictors. Results: The overall incidence of AEs in the groups A-C was 53.3% (8/15), 36.0% (9/25), and 32.7% (18/55), respectively, which did not represent a significant difference (P=0.42). No severe AEs (SAEs) occurred. Group A, compared with group B and group C, had a significantly longer estimated median PFS (33.0 vs. 7.0 vs. 3.0 months; P<0.001) and OS (33.0 vs. 13.0 vs. 6.0 months; P=0.002). PD-1 blockade (P=0.006), tumor number (P=0.01), and DEB-BACE/bronchial artery infusion (BAI) chemotherapy cycles (P=0.04) were identified as the predictors of PFS, while the predictors of OS were PD-1 blockade (P<0.001), number of metastases (P<0.001), tumor diameter (P<0.001), and DEB-BACE/BAI cycles (P=0.02). Conclusions: Compared with that of advanced NSCLC treated with MWA plus DEB-BACE or DEB-BACE alone, the maintenance treatment of immunotherapy after MWA plus DEB-BACE might provide a superior prognosis without increasing the risk of AEs.

Clinical Characteristics and Pathogen Spectrum of Male Genital Fungal Infections in Nanchang Area, South China.

The cutaneous fungal infections in male genitalia are relatively rare, and often present with various atypical clinical symptoms. It was mainly reported in a small number of case reports, while data with large number of patients were rarely reported. In this study, we reported 79 male patients with cutaneous fungal infections on scrotum or penis. The fungal infections were confirmed by microscopic examination directly and fungus culture. Clinical characteristics and predisposing factors were also collected. Of these 79 patients, 72 has lesions on scrotum, 5 on penis and 2 on both scrotum and penis. Trichophyton (T.) rubrum is the most common pathogen, found in 50 (67.6%) patients, which presented diverse clinical manifestation such as majorly erythematous, dry diffused scaly lesions without a clear border, slightly powdery and scutular scalings. Candida (C.) albicans is the secondly common pathogen, found in 21 (28.4%) patients, which also presented diverse lesions such as erythematous with dry whitish scaly lesions and erythematous erosion. The predisposing factors mainly included concomitant fungal infections on sites other than genitalia, especially inguinal region (tinea cruris), application of corticosteroid and high moisture. In conclusion, cutaneous fungal infections in male genitalia could be caused by different fungi, showed atypical or mild clinical appearances in most cases and might be a fungus reservoir, emphasizing the necessity to timely perform the fungi examinations and corresponding therapy.

Pure ZrO2 Ferroelectric Thin Film for Nonvolatile Memory and Neural Network Computing.

The recent discovery of ferroelectricity in pure ZrO2 has drawn much attention, but the information storage and processing performances of ferroelectric ZrO2-based nonvolatile devices remain open for further exploration. Here, a ZrO2 (∼8 nm)-based ferroelectric capacitor using RuO2 oxide electrodes is fabricated, and the ferroelectric orthorhombic phase evolution under electric field cycling is studied. A ferroelectric remnant polarization (2Pr) of >30 µC/cm2, leakage current density of ∼2.79 × 10-8 A/cm2 at 1 MV/cm, and estimated polarization retention of >10 years are achieved. When the ferroelectric capacitor is connected with a transistor, a memory window of ∼0.8 V and eight distinct states can be obtained in such a ferroelectric field-effect transistor (FeFET). Through the conductance manipulation of the FeFET, a high object image recognition accuracy of ∼93.32% is achieved on the basis of the CIFAR-10 dataset in the convolutional neural network (CNN) simulation, which is close to the result of ∼94.20% obtained by floating-point-based CNN software. These results demonstrate the potential of ferroelectric ZrO2 devices for nonvolatile memory and artificial neural network computing.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer.

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

HRU-Net: A high-resolution convolutional neural network for esophageal cancer radiotherapy target segmentation.

BACKGROUND AND OBJECTIVE: The effective segmentation of esophageal squamous carcinoma lesions in CT scans is significant for auxiliary diagnosis and treatment. However, accurate lesion segmentation is still a challenging task due to the irregular form of the esophagus and small size, the inconsistency of spatio-temporal structure, and low contrast of esophagus and its peripheral tissues in medical images. The objective of this study is to improve the segmentation effect of esophageal squamous cell carcinoma lesions. METHODS: It is critical for a segmentation network to effectively extract 3D discriminative features to distinguish esophageal cancers from some visually closed adjacent esophageal tissues and organs. In this work, an efficient HRU-Net architecture (High-Resolution U-Net) was exploited for esophageal cancer and esophageal carcinoma segmentation in CT slices. Based on the idea of localization first and segmentation later, the HRU-Net locates the esophageal region before segmentation. In addition, an Resolution Fusion Module (RFM) was designed to integrate the information of adjacent resolution feature maps to obtain strong semantic information, as well as preserve the high-resolution features. RESULTS: Compared with the other five typical methods, the devised HRU-Net is capable of generating superior segmentation results. CONCLUSIONS: Our proposed HRU-NET improves the accuracy of segmentation for squamous esophageal cancer. Compared to other models, our model performs the best. The designed method may improve the efficiency of clinical diagnosis of esophageal squamous cell carcinoma lesions.

A core scientific problem in the treatment of central nervous system diseases: newborn neurons.

It has long been asserted that failure to recover from central nervous system diseases is due to the system's intricate structure and the regenerative incapacity of adult neurons. Yet over recent decades, numerous studies have established that endogenous neurogenesis occurs in the adult central nervous system, including humans'. This has challenged the long-held scientific consensus that the number of adult neurons remains constant, and that new central nervous system neurons cannot be created or renewed. Herein, we present a comprehensive overview of the alterations and regulatory mechanisms of endogenous neurogenesis following central nervous system injury, and describe novel treatment strategies that target endogenous neurogenesis and newborn neurons in the treatment of central nervous system injury. Central nervous system injury frequently results in alterations of endogenous neurogenesis, encompassing the activation, proliferation, ectopic migration, differentiation, and functional integration of endogenous neural stem cells. Because of the unfavorable local microenvironment, most activated neural stem cells differentiate into glial cells rather than neurons. Consequently, the injury-induced endogenous neurogenesis response is inadequate for repairing impaired neural function. Scientists have attempted to enhance endogenous neurogenesis using various strategies, including using neurotrophic factors, bioactive materials, and cell reprogramming techniques. Used alone or in combination, these therapeutic strategies can promote targeted migration of neural stem cells to an injured area, ensure their survival and differentiation into mature functional neurons, and facilitate their integration into the neural circuit. Thus can integration replenish lost neurons after central nervous system injury, by improving the local microenvironment. By regulating each phase of endogenous neurogenesis, endogenous neural stem cells can be harnessed to promote effective regeneration of newborn neurons. This offers a novel approach for treating central nervous system injury.

Sub-features orthogonal decoupling: Detecting bone wall absence via a small number of abnormal examples for temporal CT images.

The absence of bone wall located in the jugular bulb and sigmoid sinus of the temporal bone is one of the important reasons for pulsatile tinnitus. Automatic and accurate detection of these abnormal singes in CT slices has important theoretical significance and clinical value. Due to the shortage of abnormal samples, imbalanced samples, small inter-class differences, and low interpretability, existing deep-learning methods are greatly challenged. In this paper, we proposed a sub-features orthogonal decoupling model, which can effectively disentangle the representation features into class-specific sub-features and class-independent sub-features in a latent space. The former contains the discriminative information, while, the latter preserves information for image reconstruction. In addition, the proposed method can generate image samples using category conversion by combining the different class-specific sub-features and the class-independent sub-features, achieving corresponding mapping between deep features and images of specific classes. The proposed model improves the interpretability of the deep model and provides image synthesis methods for downstream tasks. The effectiveness of the method was verified in the detection of bone wall absence in the temporal bone jugular bulb and sigmoid sinus.

Comprehensive effects of salinity, dissolved organic carbon and copper on mortality, osmotic regulation and bioaccumulation of copper in Oryzias melastigma.

Cu, as an essential and toxic element, has gained widespread attention. Both salinity and dissolved organic carbon (DOC) are known to influence Cu toxicity in marine organisms. However, the intricate interplay between these factors and their specific influence on Cu toxicity remains ambiguous. So, this study conducted toxicity tests of Cu on Oryzias melastigma. The experiments involved three salinity levels (10, 20, and 30 ppt) and three DOC levels (0, 1, and 5 mg/L) to comprehensively investigate the underlying mechanisms of toxicity. The complex toxic effects were analyzed by mortality, NKA activity, net Na+ flux and Cu bioaccumulation in O. melastigma. The results indicate that Cu toxicity is notably influenced by both DOC and salinity. Interestingly, the discernible variation in Cu toxicity across different DOC levels diminishes as salinity levels increase. The presence of DOC enhances the impact of salinity on Cu toxicity, especially at higher Cu concentrations. Additionally, Visual MINTEQ was utilized to elucidate the chemical composition of Cu, revealing that DOC had a significant impact on Cu forms. Furthermore, we observed that fluctuations in salinity lead to the inhibition of Na+/K+-ATPase (NKA) activity, subsequently hindering the inflow of Na+. The effects of salinity and DOC on the bioaccumulation of copper were not significant. The influence of salinity on Cu toxicity is mainly through its effect on the osmotic regulation and biophysiology of O. melastigma. Additionally, DOC plays a crucial role in the different forms of Cu. Moreover, DOC-Cu complexes can be utilized by organisms. This study contributes to understanding the mechanism of copper's biological toxicity in intricate marine environments and serves as a valuable reference for developing marine water quality criteria for Cu.

Comprehensive assessment of copper's effect on marine organisms under ocean acidification and warming in the 21st century.

Copper (Cu) has sparked widespread global concern as one of the most hazardous metals to aquatic animals. Ocean acidification (OA) and warming (OW) are expected to alter copper's bioavailability based on pH and temperature-sensitive effects; research on their effects on copper on marine organisms is still in its infancy. Therefore, under representative concentration pathways (RCP) 2.6, 4.5, and 8.5, we used the multiple linear regression-water quality criteria (MLR-WQC) method to assess the effects of OA and OW on the ecological risk posed by copper in the Ocean of East China (OEC), which includes the Bohai Sea, Yellow Sea, and East China Sea. The results showed that there was a positive correlation between temperature and copper toxicity, while there was a negative correlation between pH and copper toxicity. The short-term water quality criteria (WQC) values were 1.53, 1.41, 1.30 and 1.13 µg·L-1, while the long-term WQC values were 0.58, 0.48, 0.40 and 0.29 µg·L-1 for 2020, 2099-RCP2.6, 2099-RCP4.5 and 2099-RCP8.5, respectively. Cu in the OEC poses a moderate ecological risk. Under the current copper exposure situation, strict intervention (RCP2.6) only increases the ecological risk of copper exposure by 20 %, and no intervention (RCP8.5) will increase the ecological risk of copper exposure by nearly double. The results indicate that intervention on carbon emissions can slow down the rate at which OA and OW worsen the damage copper poses to marine creatures. This study can provide valuable information for a comprehensive understanding of the combined impacts of climate change and copper on marine organisms.

Recent advances in drug delivery of celastrol for enhancing efficiency and reducing the toxicity.

Celastrol is a quinone methyl triterpenoid monomeric ingredient extracted from the root of Tripterygium wilfordii. Celastrol shows potential pharmacological activities in various diseases, which include inflammatory, obesity, cancer, and bacterial diseases. However, the application prospect of celastrol is largely limited by its low bioavailability, poor water solubility, and undesired off-target cytotoxicity. To address these problems, a number of drug delivery methods and technologies have been reported to enhance the efficiency and reduce the toxicity of celastrol. We classified the current drug delivery technologies into two parts. The direct chemical modification includes nucleic acid aptamer-celastrol conjugate, nucleic acid aptamer-dendrimer-celastrol conjugate, and glucolipid-celastrol conjugate. The indirect modification includes dendrimers, polymers, albumins, and vesicular carriers. The current technologies can covalently bond or encapsulate celastrol, which improves its selectivity. Here, we present a review that focalizes the recent advances of drug delivery strategies in enhancing the efficiency and reducing the toxicity of celastrol.

WDFF-Net: Weighted Dual-branch Feature Fusion Network for Polyp Segmentation with Object-aware Attention Mechanism.

Colon polyps in colonoscopy images exhibit significant differences in color, size, shape, appearance, and location, posing significant challenges to accurate polyp segmentation. In this paper, a Weighted Dual-branch Feature Fusion Network is proposed for Polyp Segmentation, named WDFF-Net, which adopts HarDNet68 as the backbone network. Firstly, a dual-branch feature fusion network architecture is constructed, which includes a shared feature extractor and two feature fusion branches, i.e. Progressive Feature Fusion (PFF) branch and Scale-aware Feature Fusion (SFF) branch. The branches fuse the deep features of multiple layers for different purposes and with different fusion ways. The PFF branch is to address the under-segmentation or over-segmentation problems of flat polyps with low-edge contrast by iteratively fusing the features from low, medium, and high layers. The SFF branch is to tackle the the problem of drastic variations in polyp size and shape, especially the missed segmentation problem for small polyps. These two branches are complementary and play different roles, in improving segmentation accuracy. Secondly, an Object-aware Attention Mechanism (OAM) is proposed to enhance the features of the target regions and suppress those of the background regions, to interfere with the segmentation performance. Thirdly, a weighted dual-branch the segmentation loss function is specifically designed, which dynamically assigns the weight factors of the loss functions for two branches to optimize their collaborative training. Experimental results on five public colon polyp datasets demonstrate that, the proposed WDFF-Net can achieve a superior segmentation performance with lower model complexity and faster inference speed, while maintaining good generalization ability.

Generation of skyrmions by combining thermal and spin-orbit torque: breaking half skyrmions into skyrmions.

Skyrmions, swirling spin textures with topologically protected stability and low critical driven-current density, can be generated from the stripe domain with current pulses, bringing them closer to practical applications in racetrack memory. However, the mechanism of this topological transition from the stripe domain to the skyrmion remains unclear because the transition process occurs at a nanosecond timescale, giving rise to difficulties in observing this process using imaging tools. In this study, we controlled the domain wall - skyrmion transition by combining Joule heating with spin-orbit torque (SOT) and experimentally observed the details of this process, by which we confirmed the mechanism: the spatial variation of the topological charge density induces half skyrmions branching from the stripe domains, and these half skyrmions overcome the surface tension and break away from the stripe domain, resulting in the generation of skyrmions. The details were observed by employing Joule heating to overcome the pinning effect and manipulating the strength of the SOT to induce the branching and breaking of half skyrmions. These findings offer new insights into skyrmion generation and serve as an important step towards the development of highly efficient devices for processing and computing based on skyrmionics.

A study of clinical and serological correlation of early myocardial injury in elderly patients infected with the Omicron variant.

Introduction: Myocardial injury in elderly Omicron variant patients is a leading cause of severe disease and death. This study focuses on elucidating the clinical characteristics and potential risk factors associated with myocardial injury in elderly patients infected with the Omicron variant. Methods: Myocardial injury was defined based on elevated cardiac troponin concentrations exceeding the 99th percentile upper reference limit. Among 772 elderly Omicron-infected patients, categorized into myocardial injury (n = 263) and non-myocardial injury (n = 509) groups. The stratified log-rank statistic was used to compare the probability of patients developing intensive care. Receiver operating characteristic curves were used to determine the best cut-off values of clinical and laboratory data for predicting myocardial injury. Univariate and multivariate logistic regression was adopted to analyze the risk factors for myocardial injury. Results: The occurrence of myocardial injury in Omicron variant-infected geriatric patients was up to 34.07% and these patients may have a higher rate of requiring intensive care (P < 0.05). By comparing myocardial injury patients with non-myocardial injury patients, notable differences were observed in age, pre-existing medical conditions (e.g., hypertension, coronary heart disease, cerebrovascular disease, arrhythmia, chronic kidney disease, and heart failure), and various laboratory biomarkers, including cycle threshold-ORF1ab gene (Ct-ORF1ab), cycle threshold-N gene (Ct-N), white blood cell count, neutrophil (NEUT) count, NEUT%, lymphocyte (LYM) count, LYM%, and D-dimer, interleukin-6, procalcitonin, C-reactive protein, serum amyloid A, total protein, lactate dehydrogenase, aspartate aminotransferase, glomerular filtration rate, blood urea nitrogen, and serum creatinine (sCr) levels (P < 0.05). Furthermore, in the multivariable logistic regression, we identified potential risk factors for myocardial injury in Omicron variant-infected elderly patients, including advanced age, pre-existing coronary artery disease, interleukin-6 > 22.69 pg/ml, procalcitonin > 0.0435 ng/ml, D-dimer > 0.615 mg/L, and sCr > 81.30 µmol/L. Conclusion: This study revealed the clinical characteristics and potential risk factors associated with myocardial injury that enable early diagnosis of myocardial injury in Omicron variant-infected elderly patients, providing important reference indicators for early diagnosis and timely clinical intervention.

Identification of the toxin components of Rhizoctonia solani AG1-IA and its destructive effect on plant cell membrane structure.

Rice sheath blight is a fungal disease caused mainly by Rhizoctonia solani AG1-IA. Toxins are a major pathogenic factor of R. solani, and some studies have reported their toxin components; however, there is no unified conclusion. In this study, we reported the toxin components and their targets that play a role in R. solani AG1-IA. First, toxins produced by R. solani AG1-IA were examined. Several important phytotoxins, including benzoic acid (BZA), 5-hydroxymethyl-2-furanic aid (HFA), and catechol (CAT), were identified by comparative analysis of secondary metabolites from AG1-IA, AG1-IB, and healthy rice. Follow-up studies have shown that the toxin components of this fungus can rapidly disintegrate the biofilm structure while maintaining the content of host plant membrane components, thereby affecting the organelles, which may also explain the lack of varieties highly resistant to sheath blight.