Survival nomogram and risk classification system for patients with adrenocortical carcinoma: a study based on the SEER database and external validation in China.

Background: Adrenocortical carcinoma (ACC) is an extremely rare and highly invasive malignant tumor. However, there is currently no reliable method to predict the prognosis of ACC. Our objective is to construct a nomogram and a risk classification system to predict the 1-year, 3-year, and 5-year overall survival (OS) of ACC. Methods: We retrieved clinicopathological data of patients diagnosed with ACC in The Surveillance, Epidemiology, and End Results (SEER) database and divided them into training and validation cohorts with a 7:3 ratio. Simultaneously, we collected an external validation cohort from The First Affiliated Hospital of Naval Medical University (Shanghai, China). Univariate and multivariate Cox analyses were performed to identify relevant risk factors, which were then combined to develop a correlation nomogram. The predictive performance of the nomogram was evaluated using the concordance index (C-index), receiver-operating characteristic curve (ROC), and calibration curves. Decision curve analysis (DCA) was applied to assess the clinical utility of the nomogram. In addition, Kaplan-Meier survival curves were generated to demonstrate the variation in OS between groups. Results: The final nomogram consisted of five factors: age, T, N, M, and history of chemotherapy. Our prognostic model demonstrated significant discriminative ability, with C-index and the area under the receiver operating characteristic (AUC) values exceeding 0.70. Additionally, DCA validated the clinical utility of the nomogram. In the entire cohort, the median OS for patients in the low- and high-risk groups was 70 and 10 months, respectively. Conclusions: A nomogram and a corresponding risk classification system were developed in order to predict the OS of patients diagnosed with ACC. These tools have the potential to provide valuable support for patient counseling and assist in the decision-making process related to treatment options.

Comparative analysis of stripe rust resistance in seedling stage and Yr gene incidence in spring and winter wheat from Xinjiang, China.

Background: Stripe rust, caused by the fungus Puccinia striiformis f.sp. tritici (Pst), poses a significant threat to global wheat production. Objectives: This study aims to analyze the distribution of stripe rust resistance genes, characterize resistance phenotypes at the seedling stage of 137 spring and 149 winter wheat varieties in Xinjiang, China, and discern differences in resistance between spring and winter wheat varieties. Design: We used various Pst races (CYR23, CYR29, CYR31, CYR32, CYR33, CYR34) to characterize seedling resistance of spring and winter wheat varieties and to correlate resistance to the presence of wheat resistance genes (Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr41, Yr80, Yr81) using molecular markers. Results: Among spring wheat varieties, 62, 60, 42, 26, 51, and 24 varieties exhibited resistance to CYR23, CYR29, CYR31, CYR32, CYR33, and CYR34, respectively, with four varieties resistant to all varieties. Among winter wheat varieties, 66, 32, 69, 26, 83, 40 varieties demonstrated resistance to CYR23, CYR29, CYR31, CYR32, CYR33, and CYR34, respectively, with four varieties resistant to all varieties. Molecular testing revealed that, in spring wheat, 2, 17, 21, 61, 10, 0, 10, 79, and 32 varieties carried Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr41, Yr80, and Yr81 genes, respectively. In winter wheat, 40, 20, 7, 143, 15, 1, 6, 38, and 54 varieties carried Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr41, Yr80, and Yr81 genes, respectively. Notably, winter wheat exhibited a significantly higher resistance frequency than spring wheat, particularly in the incidence of Yr9, Yr10, Yr17, Yr18, and multi-gene combinations. Conclusion: In summary, this study provides information on seedling stage resistance to stripe rust 286 Xinjiang wheat varieties, elucidates the distribution of resistance genes in this population, and offers a mechanistic basis for breeding durable resistance in wheat. varieties from Xinjiang.

Drug Analysis of Voriconazole Combined with Granulocyte Colony Stimulating Factor.

BACKGROUND: The aim of the study was to improve the clinical cognition of leukemia-like reaction caused by voriconazole and granulocyte colony-stimulating factor and to avoid misdiagnosis or delayed diagnosis. METHODS: A case of drug analysis of Voriconazole combined with granulocyte colony stimulating factor was retrospectively analyzed and related literature was reviewed. RESULTS: Blood routine of the patient on July 29: WBC 13.48 x 109/L, neutrophil 85.3%, lymphocyte 13.4%, hemoglobin 111 g/L, platelet 285 x 109/L. Vancomycin was given to prevent intracranial infection. Lumbar puncture was performed on July 30, cerebrospinal fluid was sent for routine and biochemical examination, leukocytes were 0.15 x 109/L, monocytes 45%, polynuclear cells 55%, protein 1.172 g/L, Acinetobacter baumannii and Candida clorbicus were detected in sputum culture, vancomycin and meropenem static sites were given to prevent intracranial secondary infection. Fungi were detected in urine culture, and voriconazole was given to prevent fungal infection. Blood routine: White blood cell 0.61 x 109/L, neutrophil 23%, lymphocyte 73.8%, red blood cell 2.65 x 1012/L, hemoglobin 77 g/L, platelet 17 x 109/L, bone marrow was extracted after medication. Bone marrow images show poor myelodysplasia, with granulocytes dominated by protoearly cells. Subsequent flow cytometry, chromosomal karyotype, and fusion gene analysis were performed to exclude the possibility of leukemia. Flow cytometry showed that the proportion of myeloid primordial cells was not high, the granulocytes were mainly at the early and young stage, no abnormal phenotype was observed in erythrocytes, monocytes and NK cells, no obvious mature B lymphocytes were observed, and the ratio of CD4+/CD8+ was decreased. Karyotype results showed that there was no mitotic phase. The results of fusion gene analysis showed that the fusion gene was negative or lower than the detection sensitivity. Voliconazole was stopped first, and granulocyte colony stimulating factor was stopped 3 days later. Two weeks later, blood and bone marrow images basically recovered, white blood cell 7.88 x 109/L, neutrophil 46.3%, lymphocyte 48.2%, hemoglobin 126 g/L, platelet 142 x 109/L, bone marrow hyperplasia active. The proportion of three series is roughly normal. CONCLUSIONS: The reason for the occurrence of leukemia-like reaction in this patient was considered to be related to voriconazole and granulocyte colony stimulating factor, cessation of voriconazole and granulocyte colony stimulating factor, and recovery of blood and bone marrow images. In the clinical use of voriconazole and granulocyte colony stimulating factor, close attention should be paid to the drug interaction and individualized medication should be carried out to ensure the safety of medication.

A LAMP-based hydrogen ion selective electrochemical sensor for highly sensitive detection of Mycoplasma pneumoniae.

A concise and rapid detection method for Mycoplasma pneumoniae is urgently required due to its severe impact on human health. To meet such a need, this study proposed and constructed an innovative point-of-care testing (POCT) platform that consists of a hydrogen ion-selective loop-mediated isothermal amplification (H+-LAMP) sensor and an electrochemical detection device. The H+-LAMP sensor successfully integrated the working and reference electrodes and converted the H+ generated during the LAMP process into an electrochemical signal. High sensitivity and stability for pathogen detection were also achieved by treating the working electrode with an electrodeposited polyaniline solid contact layer and by using an ion-selective membrane. As a result, the sensor shows a sensitivity of 68.26 mV per pH, a response time of less than 2 s, and a potential drift of less than 5 mV within one hour, which well meets the urgent need. The results also demonstrated that the detection limit for Mycoplasma pneumoniae was lowered to 1 copy per µL, the nucleic acid extraction and detection process could be completed in 30 minutes, and the impact of interfering ions on the sensor was negligible. Validation with 20 clinical samples yielded satisfactory results. More importantly, the storage lifespan of such an electrochemical sensor is over seven days, which is a great advantage for on-site pathogen detection. Therefore, the hydrogen ion-selective sensor constructed in this investigation is particularly suitable as a core component for instant pathogen detection platforms.

When DNA-damage responses meet innate and adaptive immunity.

When cells proliferate, stress on DNA replication or exposure to endogenous or external insults frequently results in DNA damage. DNA-Damage Response (DDR) networks are complex signaling pathways used by multicellular organisms to prevent DNA damage. Depending on the type of broken DNA, the various pathways, Base-Excision Repair (BER), Nucleotide Excision Repair (NER), Mismatch Repair (MMR), Homologous Recombination (HR), Non-Homologous End-Joining (NHEJ), Interstrand Crosslink (ICL) repair, and other direct repair pathways, can be activated separately or in combination to repair DNA damage. To preserve homeostasis, innate and adaptive immune responses are effective defenses against endogenous mutation or invasion by external pathogens. It is interesting to note that new research keeps showing how closely DDR components and the immune system are related. DDR and immunological response are linked by immune effectors such as the cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) pathway. These effectors act as sensors of DNA damage-caused immune response. Furthermore, DDR components themselves function in immune responses to trigger the generation of inflammatory cytokines in a cascade or even trigger programmed cell death. Defective DDR components are known to disrupt genomic stability and compromise immunological responses, aggravating immune imbalance and leading to serious diseases such as cancer and autoimmune disorders. This study examines the most recent developments in the interaction between DDR elements and immunological responses. The DDR network's immune modulators' dual roles may offer new perspectives on treating infectious disorders linked to DNA damage, including cancer, and on the development of target immunotherapy.

Oxygen Vacancies-Induced Antifouling Photoelectrochemical Aptasensor for Highly Sensitive and Selective Determination of α-Fetoprotein.

Accurate measurement of cancer markers in urine is a convenient method for tumor monitoring. However, the concentration of cancer markers in urine is so low that it is difficult to achieve their measurement. Photoelectrochemical (PEC) sensors are a promising technology to realize the detection of trace cancer markers due to their high sensitivity. Currently, the interference of nonspecific biomolecules in urine is the main reason affecting the high sensitivity and selectivity of PEC sensors in detecting cancer markers. In this work, a strategy of oxygen vacancy (OV) modulation is proposed to construct a fouling-resistant PEC aptamer sensing platform for the detection of α-fetoprotein (AFP), a liver cancer marker. The introduction of OVs induces the formation of intermediate localized states in the photoelectric material, which not only facilitates the separation of photogenerated carriers but also leads to the redshift of the light absorption edge. More importantly, OVs with positive electrical properties can be employed to modify the antifouling layer (C-PEG) with negatively charged groups through an electrostatic interaction. The synergistic effect of OVs, antifouling layer, and aptamer resulted in a TiO2/OVs/C-PEG-based PEC sensor achieves a wide linear range from 1 pg/mL to 100 ng/mL and a low detection limit of 0.3 pg/mL for AFP. In addition, the sensor successfully realized the determination of AFP in urine samples and accurately differentiated between normal people and liver cancer patients in the early and advanced stages. This project is of great significance in advancing the application of photoelectrochemical bioanalytical technology to achieve the detection of cancer markers in urine by investigating the construction of an OVs-regulated fouling-resistant sensing interface.

Gut microbiota-dependent phenylacetylglutamine in cardiovascular disease: current knowledge and new insights.

Phenylacetylglutamine (PAGln) is an amino acid derivate that comes from the amino acid phenylalanine. There are increasing studies showing that the level of PAGln is associated with the risk of different cardiovascular diseases. In this review, we discussed the metabolic pathway of PAGln production and the quantitative measurement methods of PAGln. We summarized the epidemiological evidence to show the role of PAGln in diagnostic and prognostic value in several cardiovascular diseases, such as heart failure, coronary heart disease/atherosclerosis, and cardiac arrhythmia. The underlying mechanism of PAGln is now considered to be related to the thrombotic potential of platelets via adrenergic receptors. Besides, other possible mechanisms such as inflammatory response and oxidative stress could also be induced by PAGln. Moreover, since PAGln is produced across different organs including the intestine, liver, and kidney, the cross-talk among multiple organs focused on the function of this uremic toxic metabolite. Finally, the prognostic value of PAGln compared to the classical biomarker was discussed and we also highlighted important gaps in knowledge and areas requiring future investigation of PAGln in cardiovascular diseases.

Multi-Omics Analysis Reveals the Role of Changes in Platelet Activation Pathways in the Survival Outcome of Patients with Esophageal Squamous Cell Carcinoma.

Objective: The objective of this study was to integrate metabolomics and transcriptomics data to identify key diagnostic and prognostic markers for esophageal squamous cell carcinoma (ESCC). Plasma samples were collected from 85 ESCC patients at different stages and 50 healthy volunteers for non-targeted metabolomic analysis. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for non-targeted metabolomic analysis. Subsequently, we integrated the metabolomic data with transcriptomic data from the Gene Expression Omnibus (GEO) and prognosis data from The Cancer Genome Atlas Program (TCGA) to perform pathway analysis. Our focus was on pathways that involve both metabolites and upstream genes, as they often exhibit higher accuracy. Results: Through the integration of metabolomics and transcriptomics, we identified significant alterations in the platelet activation pathway in ESCC. This pathway involves the participation of both metabolites and genes, making it a more accurate reflection of pathological changes associated with the disease. Notably, metabolite arachidonic acid (AA) and chemokine receptor type 2(CXCR2) were significantly downregulated in ESCC, while genes collagen type I alpha 1(COL1A1), collagen type I alpha 2(COL1A2), collagen type III alpha 1(COL3A1), type 3 inositol 1,4,5-trisphosphate receptor (ITPR3), and insulin-like growth factor II mRNA binding protein 3(IGF2BP3) were significantly upregulated, indicating the presence of tumor-induced platelet activation in ESCC. Further analysis of prognosis data revealed that high expression of COL1A1, IGF2BP3, and ITPR3 was associated with a favorable prognosis for ESCC, while high CXCR2 expression was linked to an adverse prognosis. In addition, we combined COL1A1, ITPR3, IGF2BP3, CXCR2, and AA to form a diagnostic biomarker panel. The receiver operating characteristic curve (ROC) demonstrated excellent diagnostic capability (AUC=0.987). Conclusion: Our study underscores the significant role of platelet activation pathways and related genes in the diagnosis and prognosis of ESCC patients. These findings offer promising insights for improving the clinical management of ESCC.

Adverse drug reaction signal detection methods in spontaneous reporting system: A systematic review.

BACKGROUND: A series of signal detection methods have been developed to detect adverse drug reaction (ADR) signals in spontaneous reporting system. However, different signal detection methods yield quite different signal detection results, and we do not know which method has the best detection performance. How to choose the most suitable signal detection method is an urgent problem to be solved. In this study, we systematically reviewed the characteristics and application scopes of current signal detection methods, with the goal of providing references for the optimization selection of signal detection methods in spontaneous reporting system. METHODS: We searched six databases from inception to January 2023. The search strategy targeted literatures regarding signal detection methods in spontaneous reporting system. We used thematic analysis approach to summarize the advantages, disadvantages, and application scope of each signal detection method. RESULTS: A total of 93 literatures were included, including 27 reviews and 66 methodological studies. Moreover, 31 signal detection methods were identified in these literatures. Each signal detection method has its inherent advantages and disadvantages, resulting in different application scopes of these methods. CONCLUSION: Our systematic review finds that there are variabilities in the advantages, disadvantages, and application scopes of different signal detection methods. This finding indicates that the most suitable signal detection method varies across different drug safety scenarios. Moreover, when selecting signal detection method in a particular drug safety scenario, the following factors need to be considered: purpose of research, database size, drug characteristics, adverse event characteristics, and characteristics of the relations between drugs and adverse events.

A prognostic prediction model for ovarian cancer using a cross-modal view correlation discovery network.

Ovarian cancer is a tumor with different clinicopathological and molecular features, and the vast majority of patients have local or extensive spread at the time of diagnosis. Early diagnosis and prognostic prediction of patients can contribute to the understanding of the underlying pathogenesis of ovarian cancer and the improvement of therapeutic outcomes. The occurrence of ovarian cancer is influenced by multiple complex mechanisms, including the genome, transcriptome and proteome. Different types of omics analysis help predict the survival rate of ovarian cancer patients. Multi-omics data of ovarian cancer exhibit high-dimensional heterogeneity, and existing methods for integrating multi-omics data have not taken into account the variability and inter-correlation between different omics data. In this paper, we propose a deep learning model, MDCADON, which utilizes multi-omics data and cross-modal view correlation discovery network. We introduce random forest into LASSO regression for feature selection on mRNA expression, DNA methylation, miRNA expression and copy number variation (CNV), aiming to select important features highly correlated with ovarian cancer prognosis. A multi-modal deep neural network is used to comprehensively learn feature representations of each omics data and clinical data, and cross-modal view correlation discovery network is employed to construct the multi-omics discovery tensor, exploring the inter-relationships between different omics data. The experimental results demonstrate that MDCADON is superior to the existing methods in predicting ovarian cancer prognosis, which enables survival analysis for patients and facilitates the determination of follow-up treatment plans. Finally, we perform Gene Ontology (GO) term analysis and biological pathway analysis on the genes identified by MDCADON, revealing the underlying mechanisms of ovarian cancer and providing certain support for guiding ovarian cancer treatments.

Significance of Cuproptosis-related genes in immunological characterization, diagnosis and clusters classification in Parkinson's disease.

Parkinson's disease (PD) is a progressive neurological disorder that affects millions of people throughout the world. Cuproptosis is a newly discovered form of programmed cell death linked to several neurological disorders. Nevertheless, the precise mechanisms of Cuproptosis-related genes (CRGs) in PD remain unknown. This study investigated immune infiltration and CRG expression profiling in patients with Parkinson's disease and healthy controls. Subsequently, we construct a predictive model based on 5 significant CRGs. The performance of the predictive model was validated by nomograms and external datasets. Additionally, we classified PD patients into two clusters based on CRGs and three gene clusters based on differentially expressed genes (DEG) of CRGs clusters. We further evaluated immunological characterization between the different clusters and created the CRGs scores to quantify CRGs patterns. Finally, we investigate the prediction of CRGs drugs and the ceRNA network, providing new insights into the pathogenesis and management of PD.

Genome-Wide Characterization of Berberine Bridge Enzyme Gene Family in Wheat (Triticum aestivum L.) and the Positive Regulatory Role of TaBBE64 in Response to Wheat Stripe Rust.

Berberine bridge enzymes (BBEs), functioning as carbonate oxidases, enhance disease resistance in Arabidopsis and tobacco. However, the understanding of BBEs' role in monocots against pathogens remains limited. This study identified 81 TaBBEs with FAD_binding_4 and BBE domains. Phylogenetic analysis revealed a separation of the BBE gene family between monocots and dicots. Notably, RNA-seq showed TaBBE64's significant induction by both pathogen-associated molecular pattern treatment and Puccinia striiformis f. sp. tritici (Pst) infection at early stages. Subcellular localization revealed TaBBE64 at the cytoplasmic membrane. Knocking down TaBBE64 compromised wheat's Pst resistance, reducing reactive oxygen species and promoting fungal growth, confirming its positive role. Molecular docking and enzyme activity assays confirmed TaBBE64's glucose oxidation to produce H2O2. Since Pst relies on living wheat cells for carbohydrate absorption, TaBBE64's promotion of glucose oxidation limits fungal growth and resists pathogen infection. This study sheds light on BBEs' role in wheat resistance against biotrophic fungi.

Wine aroma modification by Hanseniaspora uvarum: A multiple-step strategy for screening potential mixed starters.

Hanseniaspora uvarum is a prevalent yeast species in vineyards. However, its application in grape wine fermentation remains limited. This study used culture-dependent and -independent approaches to investigate the dynamics of H. uvarum during the spontaneous fermentation of Cabernet Sauvignon grapes. The results revealed that H. uvarum constituted 77.49 % of the non-Saccharomyces yeast population during fermentation. An indigenous strain, QTX-C10, was isolated from the 148 H. uvarum strains using a multistep screening strategy. The 1:1 co-inoculation of QTX-C10 with Saccharomyces cerevisiae proved to be an optimal strategy for mixed fermentation, resulting in a 48.54 %-59.55 % increase in ethyl esters in Cabernet Sauvignon wine and a 96.94 %-110.92 % increase in Chardonnay wine. Furthermore, this approach reduced the acetic acid levels by 12.50 %-17.07 % for Cabernet Sauvignon wine and 10.81 %-17.78 % for Chardonnay wine. Additionally, increased ethyl ester content may enhance the tropical fruit flavor of Cabernet Sauvignon wines.

Global burden and inequality of autism spectrum disorders: Based on data from the 2019 Global Burden of Disease study.

It is unclear whether the health equity of autism spectrum disorders (ASDs) has changed in different years, regions, and gender. The aims of this study were to provide a comprehensive description of the ASDs burden and provide evidence for improvement in health policies regarding ASDs inequality. This study is a population-based cross-sectional study based on the Global Burden of Disease datasets 1990-2019. We collected detailed information on ASDs between 1990 and 2019 in 204 countries worldwide, derived from the Global Burden of Disease study in 2019. Burden was calculated in terms of the incidence, prevalence and years lived with disability (YLDs). Concentration curves and concentration indices were used to summarize the degree of income-related inequality in the burden of ASDs. The overall age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized YLDs rate (ASYR) of ASDs was 9.3 (95 %UI 7.7-11.1), 369.4 (95 %UI 305.9-441.2), 56.3 (95 %UI 36.8-81.5) per 100,000 people, respectively. The ASIR, ASPR and ASYR of ASDs affected three times as many males as females. The changing trends of age-standardized rates of ASDs showed that the ASIR of ASDs a slow growing trend globally. However, the ASPR and ASYR of ASDs showed a slow decreasing trend globally. All the concentration curves were below the line of equality and statistically significant. There was no significant difference in the age-standardized rate for different years in socio-demographic index-related inequality happened over 29 years (p > 0.05). The global burden of ASDs has remained higher in males and pro-rich, the income-related inequality tended not to change between 1990 and 2019.

Association between testosterone and cancers risk in women: a two-sample Mendelian randomization study.

OBJECTIVE: Previous observational studies have explored the correlation between testosterone and cancer risk. However, the causal association between testosterone and various cancer types in women remains inconclusive. The objective of this Mendelian randomization study is to evaluate the causal links between total testosterone (TT) and bioavailable testosterone (BT) with cancer risk in females. METHODS: Initially, a rigorous quality control process was employed to identify suitable instrumental single nucleotide polymorphisms (SNPs) associated with the exposure under investigation that exhibited a significant association. The genetic causal relationship between female testosterone levels and the risk of developing cancers was examined through a two-sample Mendelian randomization. Various analytical methods, including inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode, were applied in the investigation. Key findings were primarily based on the results obtained via IVW (random effects), and sensitivity analyses were conducted to assess the reliability of the obtained results. Furthermore, maximum likelihood, penalized weighted median, and IVW (fixed effects) methods were utilized to further validate the robustness of the results. RESULTS: Based on the results of IVW analysis, our study indicated a positive causal relationship between BT and breast cancer (OR = 1.1407, 95%CI: 1.0627-1.2244, P = 0.0015) and endometrial cancer (OR = 1.4610, 95%CI: 1.2695-1.6813, P = 1.22E-06). Moreover, our findings also showed a positive causal association between TT and breast cancer (OR = 1.1764, 95%CI: 1.0846-1.2761, P = 0.0005), cervical cancer(OR = 1.0020, 95%CI: 1.0007-1.0032, P = 0.0077), and endometrial cancer(OR = 1.4124, 95%CI: 1.2083-1.6511, P = 0.0001). Additionally, our results demonstrated a negative causal relationship between BT and ovarian cancer (OR = 0.8649, 95%CI: 0.7750-0.9653, P = 0.0320). However, no causal relationship was found between BT, TT and other types of cancer (corrected P > 0.05). CONCLUSIONS: This study elucidates the role of testosterone on the development of breast cancer, endometrial cancer, ovarian cancer, and cervical cancer. It also hints at a potential but fragile link between testosterone and bladder cancer, as well as thyroid cancer. Nonetheless, it's worth noting that no statistically significant relationship between testosterone and various other types of cancer in females was identified.

The Long-Term Impacts of COVID-19 on Physical and Psychological Health - Beijing Municipality, China, December 2022-April 2023.

What is already known about this topic?: Reports detailing the clinical presentation of coronavirus disease 2019 (COVID-19) are extensive in China. However, data remains limited regarding the long-term effects of the 2022 outbreak on the community and healthcare workers (HCWs). What is added by this report?: In the follow-up study conducted with 1,069 community members and 3,309 HCWs infected with COVID-19, we observed that five months post-outbreak, 39.2% of community members and 28.7% of HCWs reported experiencing at least one symptom. The symptoms most frequently reported included fatigue or muscle weakness, insomnia, cognitive dysfunction, hair loss, joint or muscle pain, and persistent cough. HCWs tended to experience fewer long-term physical consequences and their symptoms had an expedited recovery time compared to the community members. Nevertheless, HCWs displayed a higher prevalence of moderate to severe depression and anxiety. What are the implications for public health practice?: The establishment of a public healthcare system dedicated to continual monitoring, prevention, and clinical treatment of persistent COVID-19 symptoms is imperative.

Identification of Puccinia striiformis races from the spring wheat crop in Xinjiang, China.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a foliar disease that affects both winter and spring wheat crops in Xinjiang, China, which is linked to Central Asia. Race identification of Pst from spring wheat in Xinjiang was not done before. In this study, a total of 216 isolates were recovered from stripe rust samples of spring wheat in the region in 2021 and multiplied using the susceptible cultivar Mingxian 169. These isolates were tested on the Chinese set of 19 wheat differential lines for identifying Pst races. A total of 46 races were identified. Races Suwon-11-1, Suwon11-12, and CYR32 had high frequencies in the spring wheat region. The frequencies of virulence factors on differentials "Fulhard" and "Early Premium" were high (>95%), whereas the virulence factor to differential "Triticum spelta var. Album" (Yr5) was not detected, while virulence to other differentials showed variable frequency within different counties. The predominant races in winter wheat in the same season were also detected from spring wheat cultivars, indicating Pst spreading from winter wheat to spring wheat crops. Deploying resistance genes in spring and winter wheat cultivars is critical for control stripe rust.

Eco Polymeric Materials and Natural Polymer.

With the increasing concern regarding the undesirable environmental and socioeconomic consequences of petrochemicals and limited fossil resources, biomass, bio-based polymers, and other renewable natural resources have increasingly become alternatives for the production of functional materials [...].

Liver injury in children: signal analysis of suspected drugs based on the food and drug administration adverse event reporting system.

BACKGROUND: Evidence of drug-induced liver injury is abundant in adults but is lacking in children. Our aim was to identify suspected drug signals associated with pediatric liver injury. METHODS: Hepatic adverse events (HAEs) among children reported in the Food and Drug Administration Adverse Event Reporting System were analyzed. A descriptive analysis was performed to summarize pediatric HAEs, and a disproportionality analysis was conducted by evaluating reporting odds ratios (RORs) and proportional reporting ratios to detect suspected drugs. RESULTS: Here, 14,143 pediatric cases were reported, specifically 49.6% in males, 45.1% in females, and 5.2% unknown. Most patients (68.8%) were 6-18 years old. Hospitalization ranked first among definite outcomes (7,207 cases, 37.2%). In total, 264 disproportionate drug signals were identified. The top 10 drugs by the number of reports were paracetamol (1,365; ROR, 3.6; 95% confidence interval (CI), 3.4-3.8), methotrexate (878; ROR, 2.5; 95% CI, 2.3-2.7), vincristine (649; ROR, 3.0; 95% CI, 2.8-3.3), valproic acid (511; ROR, 3.2; 95% CI, 2.9-3.6), cyclophosphamide (490; ROR, 2.4; 95% CI, 2.2-2.6), tacrolimus (427; ROR, 2.4; 95% CI, 2.2-2.7), prednisone (416; ROR, 2.1; 95% CI, 1.9-2.3), prednisolone (401; ROR, 2.3; 95% CI, 2.1-2.5), etoposide (378; ROR, 2.3; 95% CI, 2.1-2.6), and cytarabine (344; ROR, 2.8; 95% CI, 2.5-3.2). After excluding validated hepatotoxic drugs, six were newly detected, specifically acetylcysteine, thiopental, temazepam, nefopam, primaquine, and pyrimethamine. CONCLUSIONS: The hepatotoxic risk associated with 264 signals needs to be noted in practice. The causality of hepatotoxicity and mechanism among new signals should be verified with preclinical and clinical studies.

K-N Bridge-Mediated charge separation in hollow g-C3N4 Frameworks: A bifunctional photocatalysts towards efficient H2 and H2O2 production.

The development of bifunctional photocatalysts for enhancing hydrogen (H2) and hydrogen peroxide (H2O2) production from water is essential in addressing environmental and energy issues. However, the practical implementation of photocatalytic technology is still constrained by the inadequate separation of photo-generated charge carriers. Herein, potassium (K) atoms are introduced into the interlayers of graphitic carbon nitride (g-C3N4) with a hollow hexagonal structure (K-TCN) and are coordinated with N atoms in adjacent layers. The presence of K-N coordination serves as a layer bridge, facilitating the separation of charge carriers. The hollow hexagonal structure reduces the distance over which photogenerated electrons migrate to the surface, thereby enhancing the reaction kinetics. Consequently, the optimized K-TCN exhibits a dramatically improved photocatalytic H2 (941.6 µmol g-1h-1 with platinum (Pt) as the cocatalyst) and H2O2 (347.6 µmol g-1h-1) generation as compared to hollow g-C3N4 (TCN) and bulk g-C3N4 nanosheet (CN) without K-N bridge under visible light irradiation. The unique design holds promising potential for developing highly efficient bifunctional photocatalysts towards producing renewable fuels and value-added chemicals.