Emission characteristics, environmental impacts and health risk assessment of volatile organic compounds from the typical chemical industry in China.

To study the volatile organic compounds (VOCs) emission characteristics of industrial enterprises in China, 6 typical chemical industries in Yuncheng City were selected as research objects, including the modern coal chemical industry (MCC), pharmaceutical industry (PM), pesticide industry (PE), coking industry (CO) and organic chemical industry (OC). The chemical composition of 91 VOCs was quantitatively analyzed. The results showed that the emission concentration of VOCs in the chemical industry ranged from 1.16 to 155.59 mg/m3. Alkanes were the main emission components of MCC (62.0%), PE (55.1%), and OC (58.5%). Alkenes (46.5%) were important components of PM, followed by alkanes (23.8%) and oxygenated volatile organic compounds (OVOCs) (21.2%). Halocarbons (8.6%-71.1%), OVOCs (9.7%-37.6%) and alkanes (11.2%-27.0%) were characteristic components of CO. The largest contributor to OFP was alkenes (0.6%-81.7%), followed by alkanes (9.3%-45.9%), and the lowest one was alkyne (0%-0.5%). Aromatics (66.9%-85.4%) were the largest contributing components to SOA generation, followed by alkanes (2.6%-28.5%), and the lowest one was alkenes (0%-4.1%). Ethylene and BTEX were the key active species in various chemical industries. The human health risk assessment showed workers long-term exposed to the air in the chemical industrial zone had a high cancer and non-cancer risk during work, and BTEX and dichloromethane were the largest contributors.

Paclitaxel-Induced Hepatotoxicity in Ovarian Cancer Patients: A Case Report.

Paclitaxel plus carboplatin is the most common regimen for the treatment of ovarian cancer. While generally effective, these chemotherapy agents can cause adverse events such as myelotoxicity, nausea, vomiting, and rarely, hepatotoxicity. Paclitaxel is associated with mild elevations in serum aminotransferase levels, but significant hepatotoxicity is uncommon, particularly in patients without prior liver disease. We present a patient with ovarian cancer who developed significant elevation of serum aminotransferases up to 12 times the upper limit of normal after the first cycle of paclitaxel plus carboplatin chemotherapy. Extensive evaluations excluded other potential causes of liver injury and the diagnosis of paclitaxel-induced liver injury was confirmed. The patient was treated with liver protective medications and a reduced dose of paclitaxel (135 mg/m2) for subsequent cycles. Her liver function tests stabilized within 2 to 3 times the upper limit of normal, allowing continuation of chemotherapy and achieving a favorable outcome.

A CT-based radiomics model for predicting lymph node metastasis in hepatic alveolar echinococcosis patients to support lymph node dissection.

BACKGROUND: Hepatic alveolar echinococcosis (AE) is a severe zoonotic parasitic disease, and accurate preoperative prediction of lymph node (LN) metastasis in AE patients is crucial for disease management, but it remains an unresolved challenge. The aim of this study was to establish a radiomics model for the preoperative prediction of LN metastasis in hepatic AE patients. METHODS: A total of 100 hepatic AE patients who underwent hepatectomy and hepatoduodenal ligament LN dissection at Qinghai Provincial People's Hospital between January 2016 and August 2023 were included in the study. The patients were randomly divided into a training set and a validation set at an 8:2 ratio. Radiomic features were extracted from three-dimensional images of the hepatoduodenal ligament LNs delineated on arterial phase computed tomography (CT) scans of hepatic AE patients. Least absolute shrinkage and selection operator (LASSO) regression was applied for data dimensionality reduction and feature selection. Multivariate logistic regression analysis was performed to develop a prediction model, and the predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: A total of 7 radiomics features associated with LN status were selected using LASSO regression. The classification performances of the training set and validation set were consistent, with area under the operating characteristic curve (AUC) values of 0.928 and 0.890, respectively. The model also demonstrated good stability in subsequent validation. CONCLUSION: In this study, we established and evaluated a radiomics-based prediction model for LN metastasis in patients with hepatic AE using CT imaging. Our findings may provide a valuable reference for clinicians to determine the occurrence of LN metastasis in hepatic AE patients preoperatively, and help guide the implementation of individualized surgical plans to improve patient prognosis.

White Organic Light-Emitting Diodes with External Quantum Efficiency of 20.77% at 10000 cd m-2 and Ultra-High Color Stability by Controlling Exciton Distribution.

Although brightness and efficiency have been continually improved, the inability to achieve superior efficiency, color stability, and low-efficiency roll-off simultaneously in white organic light-emitting diodes (OLEDs) remains a knotty problem restricting the commercial application. In this paper, emission balance for two different horizontal orientation emitting molecules is maintained by using hole transport materials and bipolar host materials to control carriers' recombination and exciton diffusion. Impressively, the obtained devices exhibit extremely stable white emission with small chromaticity coordinates variation of (0.0023, 0.0078) over a wide brightness range from 1000 to 50000 cd m-2. Meanwhile, the optimal white OLED realizes the power efficiency, current efficiency, and external quantum efficiency up to 70.68 lm W-1, 85.53 cd A-1, and 24.33%, respectively at the practical brightness of 1000 cd m-2. Owing to reduced heterogeneous interfaces and broadening recombination region, this device exhibits a high EQE over 20% under high luminance of 10000 cd m-2, demonstrating slight efficiency roll-off. The operating mechanism of the device is analyzed by versatile experimental and theoretical evidences, which concludes precise manipulation of charges and excitons is the key points to achieve these excellent performances. This work provides an effective strategy for the design of high-performance white OLEDs.

Cloud computing load prediction method based on CNN-BiLSTM model under low-carbon background.

With the establishment of the "double carbon" goal, various industries are actively exploring ways to reduce carbon emissions. Cloud data centers, represented by cloud computing, often have the problem of mismatch between load requests and resource supply, resulting in excessive carbon emissions. Based on this, this paper proposes a complete method for cloud computing carbon emission prediction. Firstly, the convolutional neural network and bidirectional long-term and short-term memory neural network (CNN-BiLSTM) combined model are used to predict the cloud computing load. The real-time prediction power is obtained by real-time prediction load of cloud computing, and then the carbon emission prediction is obtained by power calculation. Develop a dynamic server carbon emission prediction model, so that the server carbon emission can change with the change of CPU utilization, so as to achieve the purpose of low carbon emission reduction. In this paper, Google cluster data is used to predict the load. The experimental results show that the CNN-BiLSTM combined model has good prediction effect. Compared with the multi-layer feed forward neural network model (BP), long short-term memory network model (LSTM ), bidirectional long short-term memory network model (BiLSTM), modal decomposition and convolution long time series neural network model (CEEMDAN-ConvLSTM), the MSE index decreased by 52 % , 50 % , 34 % and 45 % respectively.

Crystallinity Control and Strain Release in Wide-Bandgap Perovskite Film via Seed-Induced Growth for Efficient Photovoltaics.

The seed method stands out as a straightforward and efficient approach for fabricating high-performance perovskite solar cells (PSCs). In this study, we propose the utilization of an antisolvent as an additive to induce crystal seeding, thereby facilitating the growth of wide-bandgap perovskite grains. Specifically, we introduce three commonly used antisolvents─ethyl acetate (EA), isopropanol (IPA), and chlorobenzene (CB)─directly into the perovskite precursor solution to generate perovskite seeds, which serve to promote subsequent nucleation. This antisolvent-crystal seeding method (ACSM) results in increased grain sizes, reduced film defects, and overall improved film quality. Consequently, the power conversion efficiencies (PCEs) of 1.647 eV PSCs with EA, IPA, and CB additives are recorded at 19.86%, 20.61%, and 20.45%, respectively, surpassing that of the reference device with a PCE of 18.83%. Furthermore, the stability of the PSCs prepared through ACSM is notably enhanced. Notably, PSCs optimized with IPA retain 75% of the original PCE after being stored in ambient air conditions (25 °C, RH ∼ 15%) for 30 days, better than the CB-added (64%) and the EA-added devices (53%), while the reference devices only retain 31% of the initial PCE. Moreover, even after continuous thermal annealing at 50 °C for 200 h, IPA-assisted devices demonstrate the best stability, followed by those with CB and EA, with the reference exhibiting the poorest stability.

Advanced electrochemical membrane technologies for near-complete resource recovery and zero-discharge of urine: Performance optimization and evaluation.

The depletion of nutrient sources in fertilizers demands a paradigm shift in the treatment of nutrient-rich wastewater, such as urine, to enable efficient resource recovery and high-value conversion. This study presented an integrated bipolar membrane electrodialysis (BMED) and hollow fiber membrane (HFM) system for near-complete resource recovery and zero-discharge from urine treatment. Computational simulations and experimental validations demonstrated that a higher voltage (20 V) significantly enhanced energy utilization, while an optimal flow rate of 0.4 L/min effectively mitigated the negative effects of concentration polarization and electro-osmosis on system performance. Within 40 min, the process separated 90.13% of the salts in urine, with an energy consumption of only 8.45 kWh/kgbase. Utilizing a multi-chamber structure for selective separation, the system achieved recovery efficiencies of 89% for nitrogen, 96% for phosphorus, and 95% for potassium from fresh urine, converting them into high-value products such as 85 mM acid, 69.5 mM base, and liquid fertilizer. According to techno-economic analysis, the cost of treating urine using this system at the lab-scale was $6.29/kg of products (including acid, base, and (NH4)2SO4), which was significantly lower than the $20.44/kg cost for the precipitation method to produce struvite. Excluding fixed costs, a net profit of $18.24/m3 was achieved through the recovery of valuable products from urine using this system. The pilot-scale assessment showed that the net benefit amounts to $19.90/m3 of urine, demonstrating significant economic feasibility. This study presents an effective approach for the near-complete resource recovery and zero-discharge treatment of urine, offering a practical solution for sustainable nutrient recycling and wastewater management.

Prognostic effect of the TyG index on patients with severe aortic stenosis following transcatheter aortic valve replacement: a retrospective cohort study.

BACKGROUND: The triglyceride glucose (TyG) index, as a reliable marker of insulin resistance, is associated with the incidence and poor prognosis of various cardiovascular diseases. However, the relationship between the TyG index and clinical outcomes in patients with severe aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR) remains unclear. METHODS: This study consecutively enrolled 1569 patients with AS underwent TAVR at West China Hospital of Sichuan University between April 2014 and August 2023. The outcomes of interest included all-cause mortality, cardiovascular mortality, and major adverse cardiovascular events (MACE). Multivariate adjusted Cox regression and restricted cubic splines (RCS) regression analyses were used to assess the associations between the TyG index and the clinical outcomes. The incremental prognostic value of the TyG index was further assessed by the time-dependent Harrell's C-index, integrated discrimination improvement (IDI) and the net reclassification improvement (NRI). RESULTS: During a median follow-up of 1.09 years, there were 146, 70, and 196 patients experienced all-cause death, cardiovascular death, and MACE, respectively. After fully adjusting for confounders, a per-unit increase of TyG index was associated with a 441% (adjusted HR: 5.41, 95% CI: 4.01-7.32), 385% (adjusted HR: 4.85, 95% CI: 3.16-7.43), and 347% (adjusted HR: 4.47, 95% CI: 3.42-5.85) higher risk of all-cause mortality, cardiovascular mortality and MACE, respectively. The RCS regression analyses revealed a linear association between TyG index and endpoints (all P for non-linearity > 0.05) with 8.40 as the optimal binary cutoff point. Furthermore, adding TyG index to the basic risk model provided a significant incremental value in predicting poor prognosis (Time-dependent Harrell's C-index increased for all the endpoints; All-cause mortality, IDI: 0.11, P < 0.001; NRI: 0.32, P < 0.001; Cardiovascular mortality, IDI: 0.043, P < 0.001; NRI: 0.37, P < 0.001; MACE, IDI: 0.092, P < 0.001; NRI: 0.32, P < 0.001). CONCLUSIONS: In patients with severe AS receiving TAVR, there was a positive linear relationship between TyG index and poor prognosis, with 8.4 as the optimal bivariate cutoff value. Our findings suggest TyG index holds potential value for risk stratification and guiding therapeutic decisions in patients after TAVR.

Copper/ruthenium relay catalysis enables 1,6-double chiral inductions with stereodivergence.

The dual catalysis strategy is an efficient and powerful tool to fulfill the stereodivergent synthesis of stereoisomeric products from the same set of starting materials. Great attention has been given to the construction of chiral compounds with two contiguous stereocenters. However, the synthesis of two remote noncontiguous stereocenters is more challenging and is less developed, despite the high demand for synthetic tactics. We herein developed an unprecedented example of the stereodivergent preparation of synthetically useful and biologically important chiral ζ-hydroxy amino ester derivatives containing remote 1,6-noncontiguous stereocenters and a unique ß,γ-unsaturation moiety. This cascade dehydrogenation/1,6-Michael addition/hydrogenation protocol between readily-available ketoimine esters and racemic branched dienyl carbinols was rationally realized with bimetallic copper/ruthenium relay catalysis. The key features of the process were atom economy, step economy, and redox-neutrality. All four stereoisomers of chiral ζ-hydroxy amino ester derivatives were easily achieved by the orthogonal permutations of a chiral copper catalyst and chiral ruthenium catalyst. Importantly, a much more challenging stereodivergent synthesis of all eight stereoisomers of chiral peptide products containing three remote stereocenters was accomplished with excellent results through the cooperation of two chiral catalyst pairs and substrate enantiomers.

Non-linear association between air pollutants and secondary sensitive skin in acne patients.

BACKGROUND: There is a growing number of patients suffering from sensitive skin secondary to acne, but its prevalence and influencing factors are not yet well-understood. OBJECTIVE: The aim of this study is to investigate the nonlinear relationship between air pollutants and secondary sensitive skin in acne patients. METHODS: A cross-sectional study comprising 4325 acne outpatients in China was carried out between September 2021 and December 2022, employing a simple random sampling approach. Air pollutants data was derived from the nearest air quality monitoring station corresponding to the subjects' residential locations. Furthermore, socio-economic characteristics, biological attributes, and lifestyle data of patients were acquired via questionnaire surveys. The data were subsequently analyzed utilizing the XGBoost machine learning model. RESULTS: A nonlinear relationship has been observed between secondary sensitive skin in acne patients and various factors, including particulate matter (PM2.5), inhalable particulate matter (PM10), ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), the severity of depression, different levels of exercise intensity, acne grading, frequency of sunscreen application, gender, and age. CONCLUSION: The occurrence of secondary sensitive skin in acne patients be mitigated through the implementation of measures such as the control of air pollutant emissions, regulation of negative emotions, and improvement of personal lifestyle.

Modulating secondary growth of perovskite grains through residual solvent evaporation.

Over the past decade, perovskite solar cells (PSCs) have attracted enormous attention due to their high performance. One key to fabricating high-quality perovskite films lies in controlling the volatilization rate of residual solvents during the annealing process. This study systematically investigates how different protective substrates affect the volatilization rate of residual solvent in perovskite films. By adjusting the direction and rate of evaporation, the supersaturation time of the solution was precisely controlled, leading to effective recrystallization of the grains. Concurrently, the annealing time was optimized to enhance film quality further. This optimization aimed to increase crystallinity, reduce defects, and thereby minimize non-radiative recombination centers. Implementing these methodologies, particularly the use of filter paper as a protective substrate during a 2-minute annealing process, significantly improved the fill factor (FF) and open-circuit voltage (VOC) of the PSCs. This led to a remarkable 5.26% improvement in power conversion efficiency (PCE) compared to control devices. The strategies employed in this work demonstrate significant potential in improving PSC film quality. This approach not only advances our understanding of film formation dynamics but also provides a practical guideline for future PSC fabrication.

A unique Ca2+-inhibited C-type lectin in shrimp Fenneropenaeuschinensis.

C-type lectins (CTLs) are glycan-binding pattern recognition receptors (PRRs) that can bind to carbohydrates on pathogen surfaces, triggering immune responses in shrimp innate immunity. In this study, a unique Ca2+-inhibited CTL named FcLec was identified and characterized in Chinese shrimp Fenneropenaeus chinensis. The full-length cDNA sequence of FcLec was 976 bp (GenBank accession number KU361826), with a 615 bp open reading frame (ORF) encoding 204 amino acids. FcLec possesses a C-type lectin-like domain (CTLD) containing four conserved cysteines (Cys105, Cys174, Cys192, and Cys200) and two sugar-binding site structures (QPD and LNP). The tertiary structure of FcLec deduced revealed three α-helices and eight ß-pleated sheets. The mRNA expression levels of FcLec in hemocytes and the hepatopancreas were markedly elevated after stimulation with Vibrio anguillarum and white spot syndrome virus (WSSV). The recombinant FcLec protein exhibited Ca2+-independent hemagglutination and bacterial agglutination, but these activities were observed only in the presence of EDTA to chelate metal ions. These findings suggest that FcLec plays important and functionally distinct roles in the shrimp's innate immune response to bacteria and viruses, enriching the current understanding of the relationship between CTL activity and Ca2+ in invertebrates.

Phosphorus release and distribution in sediment resuspension systems under disturbing conditions.

The resuspension of phosphorus (P) in sediments has the most significant contribution to the overlying water. The PP release characterization during resuspension was investigated. The results indicated that the P in suspensions had more release risk compared to the sediments. The particulate P (PP) concentration (0.54 mg L-1) under high-intensity rotational speed (250 rad min-1) was about five times higher than others (0.11 mg L-1). The sorption parameters of zero equilibrium P concentration (EPC0F) and soluble reactive P (SRP) were significantly correlated with each other (p < 0.01, r = 0.73). Suspended solids expressed stronger P source than sediments. The values of EPC0F was highly significantly correlated with the sorption coefficient (KF) and native adsorbed P (NAP) (p < 0.01). The mean values of NAP were 0.0612 mg g-1 and 0.0604 mg g-1 in the Prophase and Metaphase, respectively, and 0.0586 mg g-1 at Anaphase. The values of P sorption index (PSI) ranged from 0.4359 to 0.6862 L g-1, with mean values of 0.5350 L g-1 (Prophase), 0.6061 L g-1 (Metaphase), and 0.4967 L g-1 (Anaphase). The degree of P saturation (DPS) decreased in the order of Anaphase (2.73%) > Prophase (2.53%) > Metaphase (2.12%). The release risk index of P (ERI) decreased in the order of Anaphase (5.47%) > Prophase (4.72%) > Metaphase (3.59%), with a range of 2.12%-8.56%. To fast and slow scale, the results of NaOH-P (V1<0, V2>0) contribution indicated that the persistent disturbance promoted the release of adsorbed dissolved PP from NaOH-P in suspended sediment to the overlying water. The contribution of HCl-P (V2 > 0) was positive in the Anaphase of the slow scale, and HCl-P was a PP source in the frequently disturbing conditions.

Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.

PURPOSE: To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC). METHODS: The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit. RESULTS: 166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000-1.000) in the training set and 0.927 (95%CI: 0.837-0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837-0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908. CONCLUSION: This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.

Development and validation of HPV-associated and HPV-independent penile squamous cell carcinoma prognostic nomogram.

OBJECTIVE: The aim of this study was to introduce HPV-associated and HPV-independent histologic classifications to analyze prognostic factors and develop a prognostic nomogram for patients with penile squamous cell carcinoma (PSCC). METHODS: Data of 1502 PSCC patients between 2010 and 2020 were accessed from the SEER database, and the patients were randomly divided into a training set and a validation set. Independent risk factors for PSCC patients prognosis were analyzed by using univariate and multivariate COX proportional hazards regression, and was used for the construction of the nomogram, and the predictive performance of the model was evaluated by C-index, calibration curve and ROC curve. Kaplan-Meier analysis was applied to explore the impact of HPV-related factors on patient survival, while propensity score matching (PSM) and inverse probability treatment weighting (IPTW) techniques were used to balance other confounding factors like individual clinical and pathological factors, and to evaluate the differences in overall survival (OS) and cause-specific survival (CSS) between subgroups. RESULT: The results indicated that histologic type, Grade classification, T/M stage, surgical methods and chemotherapy were independent risk factors affecting OS and CSS in PSCC patients. In addition, age and marital status were significantly associated with OS, while lymph node metastasis was an independent prognostic factor for CSS, the validation results of the model showed that the nomogram had a superior predictive performance compared with the American Joint Committee on Cancer staging system. In addition, subgroup analyses prior to and after IPTW and PSM adjustments showed that HPV-associated group had better OS and CSS than HPV-independent group. CONCLUSION: Our study developed and validated a nomogram using a novel histologic classification and achieved satisfactory results, which can better help clinicians to predict the prognosis of penile squamous cell carcinoma patients.

Construction of a diagnostic model based on random forest and artificial neural network for peri-implantitis.

OBJECTIVES: This study aimed to reveal critical genes regulating peri-implantitis during its development and construct a diagnostic model by using random forest (RF) and artificial neural network (ANN). METHODS: GSE-33774, GSE106090, and GSE57631 datasets were obtained from the GEO database. The GSE33774 and GSE106090 datasets were analyzed for differential expression and functional enrichment. The protein-protein interaction networks (PPI) and RF screened vital genes. A diagnostic model for peri-implantitis was established using ANN and validated on the GSE33774 and GSE57631 datasets. A transcription factor-gene interaction network and a transcription factor-micro-RNA (miRNA) regulatory network were also established. RESULTS: A total of 124 differentially expressed genes (DEGs) involved in the regulation of peri-implantitis were screened. Enrichment analysis showed that DEGs were mainly associated with immune receptor activity and cytokine receptor activity and were mainly involved in processes such as leukocyte and neutrophil migration. The PPI and RF screened six essential genes, namely, CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8. The receiver operating characteristic curve (ROC) indicated that the ANN model had an excellent diagnostic performance. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 may be a key miRNA. CONCLUSIONS: The diagnostic model of peri-implantitis constructed by RF and ANN has high confidence, and CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8 are potential diagnostic markers. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 plays a vital role as a critical miRNA.

Mechanism of Astragalus mongholicus Bunge ameliorating cerebral ischemia-reperfusion injury: Based on network pharmacology analysis and experimental verification.

ETHNOPHARMACOLOGICAL RELEVANCE: Astragalus mongholicus Bunge (AMB) is a herb with wide application in traditional Chinese medicine, exerting a wealth of pharmacological effects. AMB has been proven to have an evident therapeutic effect on ischemic cerebrovascular diseases, including cerebral ischemia-reperfusion injury (CIRI). However, the specific mechanism underlying AMB in CIRI remains unclear. AIM OF THE STUDY: This study aimed to investigate the potential role of AMB in CIRI through a comprehensive approach of network pharmacology and in vivo experimental research. METHODS: The intersection genes of drugs and diseases were obtained through analysis of the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and Gene Expression Omnibus (GEO) database. The protein-protein interaction (PPI) network was created through the string website. Meanwhile, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out using R studio, and thereafter the key genes were screened. Then, the molecular docking prediction was made between the main active ingredients and target genes, and hub genes with high binding energy were obtained. In addition, molecular dynamic (MD) simulation was used to validate the result of molecular docking. Based on the results of network pharmacology, we used animal experiments to verify the predicted hub genes. First, the rat middle cerebral artery occlusion and reperfusion (MACO/R) model was established and the effective dose of AMB in CIRI was determined by behavioral detection and 2,3,5-Triphenyltetrazolium chloride (TTC) staining. Then the target proteins corresponding to the hub genes were measured by Western blot. Moreover, the level of neuronal death was measured using hematoxylin and eosin (HE) and Nissl staining. RESULTS: Based on the analysis of the TCMSP database and GEO database, a total of 62 intersection target genes of diseases and drugs were obtained. The KEGG enrichment analysis showed that the therapeutic effect of AMB on CIRI might be realized through the advanced glycation endproduct-the receptor of advanced glycation endproduct (AGE-RAGE) signaling pathway in diabetic complications, nuclear factor kappa-B (NF-κB) signaling pathway and other pathways. Molecular docking results showed that the active ingredients of AMB had good binding potential with hub genes that included Prkcb, Ikbkb, Gsk3b, Fos and Rela. Animal experiments showed that AWE (60 g/kg) could alleviate CIRI by regulating the phosphorylation of PKCß, IKKß, GSK3ß, c-Fos and NF-κB p65 proteins. CONCLUSION: AMB exerts multi-target and multi-pathway effects against CIRI, and the underlying mechanism may be related to anti-apoptosis, anti-inflammation, anti-oxidative stress and inhibiting calcium overload.

Natural Killer Cells Do Not Attenuate a Mouse-Adapted SARS-CoV-2-Induced Disease in Rag2-/- Mice.

This study investigates the roles of T, B, and Natural Killer (NK) cells in the pathogenesis of severe COVID-19, utilizing mouse-adapted SARS-CoV-2-MA30 (MA30). To evaluate this MA30 mouse model, we characterized MA30-infected C57BL/6 mice (B6) and compared them with SARS-CoV-2-WA1 (an original SARS-CoV-2 strain) infected K18-human ACE2 (K18-hACE2) mice. We found that the infected B6 mice developed severe peribronchial inflammation and rapid severe pulmonary edema, but less lung interstitial inflammation than the infected K18-hACE2 mice. These pathological findings recapitulate some pathological changes seen in severe COVID-19 patients. Using this MA30-infected mouse model, we further demonstrate that T and/or B cells are essential in mounting an effective immune response against SARS-CoV-2. This was evident as Rag2-/- showed heightened vulnerability to infection and inhibited viral clearance. Conversely, the depletion of NK cells did not significantly alter the disease course in Rag2-/- mice, underscoring the minimal role of NK cells in the acute phase of MA30-induced disease. Together, our results indicate that T and/or B cells, but not NK cells, mitigate MA30-induced disease in mice and the infected mouse model can be used for dissecting the pathogenesis and immunology of severe COVID-19.

Vaccine-elicited IL-1R signaling results in Th17 TRM-mediated immunity.

Lung tissue resident memory (TRM) cells are thought to play crucial roles in lung host defense. We have recently shown that immunization with the adjuvant LTA1 (derived from the A1 domain of E. coli heat labile toxin) admixed with OmpX from K. pneumoniae can elicit antigen specific lung Th17 TRM cells that provide serotype independent immunity to members of the Enterobacteriaceae family. However, the upstream requirements to generate these cells are unclear. Single-cell RNA-seq showed that vaccine-elicited Th17 TRM cells expressed high levels of IL-1R1, suggesting that IL-1 family members may be critical to generate these cells. Using a combination of genetic and antibody neutralization approaches, we show that Th17 TRM cells can be generated independent of caspase-1 but are compromised when IL-1α is neutralized. Moreover IL-1α could serve as a molecular adjuvant to generate lung Th17 TRM cells independent of LTA1. Taken together, these data suggest that IL-1α plays a major role in vaccine-mediated lung Th17 TRM generation.