Angong Niuhuang Wan ameliorates LPS-induced cerebrovascular edema by inhibiting blood‒brain barrier leakage and promoting the membrane expression of AQP4.

Introduction: Angong Niuhuang Wan (AGNHW), developed during the Qing dynasty (18th century) for the treatment of consciousness disturbances caused by severe infections, has been used to treat brain edema caused by ischemia‒reperfusion. However, it remains unclear whether AGNHW can ameliorate vascular-origin brain edema caused by lipopolysaccharides (LPS). This study explored the ameliorative effects of AGNHW on LPS-induced cerebrovascular edema in mice, as well as the potential underlying mechanisms. Methods: A cerebrovascular edema model was established in male C57BL/6N mice by two intraperitoneal injections of LPS (15 mg/kg), at 0 and 24 h. AGNHW was administered by gavage at doses of 0.2275 g/kg, 0.455 g/kg, and 0.91 g/kg, 2 h after LPS administration. In control mice, normal saline (NS) or AGNHW (0.455 g/kg) was administered by gavage 2 h after intraperitoneal injection of NS. The survival rate, cerebral water content, cerebral venous FITC-dextran leakage, Evans blue extravasation, and expression of vascular endothelial cadherin (VE-cadherin), zonula occludens-1 (ZO-1), claudin-5, phosphorylated caveolin-1 (CAV-1), and cytomembrane and cytoplasmic aquaporin 1 (AQP1) and aquaporin 4 (AQP4) were evaluated. The cerebral tissue phosphoproteome, blood levels of AGNHW metabolites, and the relationships between these blood metabolites and differentially phosphorylated proteins were analyzed. Results: AGNHW inhibited the LPS-induced decrease in survival rate, increase in cerebral water content, decrease in VE-Cadherin expression and increase in phosphorylated CAV-1 (P-CAV-1). AGNHW treatment increased the expression of AQP4 on astrocyte membrane after LPS injection. AGNHW also inhibited the LPS-induced increases in the phosphorylation of 21 proteins, including protein kinase C-α (PKC-α) and mitogen-activated protein kinase 1 (MAPK1), in the cerebral tissue. Eleven AGNHW metabolites were detected in the blood. These metabolites might exert therapeutic effects by regulating PKC-α and MAPK1. Conclusion: AGNHW can ameliorate cerebrovascular edema caused by LPS. This effect is associated with the inhibition of VE-Cadherin reduction and CAV-1 phosphorylation, as well as the upregulation of AQP4 expression on the astrocyte membrane, following LPS injection.

[Effects of Sophora japonica extract on alveolar bone mass in ovariectomized osteoporosis mice].

PURPOSE: To investigate the effect of Sophora japonica extract on alveolar bone mass in ovariectomized osteoporosis mice. METHODS: Six-week-old female non-pregnant wild-type C57BL/6J mice were randomly divided into sham operation group, ovariectomy(OVX) group and OVX+Sophora japonica extract group. Ovaries of the mice in the OVX group and the OVX+Sophora japonica extract group were removed, and the mice in the OVX+Sophora japonica extract group were treated by Sophora japonica extract at a dose of 150 mg/kg, three times a week for 4 weeks; while mice of the other two groups were given an equal volume of normal saline at the same time. Body weight was measured 3 times a week, and the micro-parameters of alveolar bone were detected by Micro-CT after 4 weeks. The data were analyzed by GraphPad Prism 9 software. RESULTS: Compared with the sham-operated group, the trabecular bone parameters of the alveolar bone in the OVX group were significantly decreased 1 month after operation (P＜0.05). One month after intervention with Sophora japonica extract, alveolar bone mineral density (BMD), trabecular number (Tb.N) and trabecular separation(Tb.Sp) in OVX mice was significantly rescued, with no significant difference compared to the sham surgery group(P＞0.05); but bone volume fraction(BV/TV) and trabecular thickness (Tb.Th) had not completely recovered to the levels of the sham-operated group(P＜0.05). CONCLUSIONS: Sophora japonica extract can effectively increase the alveolar bone mass reduced by estrogen deficiency and may be used as one of the potential drugs for the treatment of menopausal alveolar bone osteoporosis.

Improving Global Generalization and Local Personalization for Federated Learning.

Federated learning aims to facilitate collaborative training among multiple clients with data heterogeneity in a privacy-preserving manner, which either generates the generalized model or develops personalized models. However, existing methods typically struggle to balance both directions, as optimizing one often leads to failure in another. To address the problem, this article presents a method named personalized federated learning via cross silo prototypical calibration (pFedCSPC) to enhance the consistency of knowledge of clients by calibrating features from heterogeneous spaces, which contributes to enhancing the collaboration effectiveness between clients. Specifically, pFedCSPC employs an adaptive aggregation method to offer personalized initial models to each client, enabling rapid adaptation to personalized tasks. Subsequently, pFedCSPC learns class representation patterns on clients by clustering, averages the representations within each cluster to form local prototypes, and aggregates them on the server to generate global prototypes. Meanwhile, pFedCSPC leverages global prototypes as knowledge to guide the learning of local representation, which is beneficial for mitigating the data imbalanced problem and preventing overfitting. Moreover, pFedCSPC has designed a cross-silo prototypical calibration (CSPC) module, which utilizes contrastive learning techniques to map heterogeneous features from different sources into a unified space. This can enhance the generalization ability of the global model. Experiments were conducted on four datasets in terms of performance comparison, ablation study, in-depth analysis, and case study, and the results verified that pFedCSPC achieves improvements in both global generalization and local personalization performance via calibrating cross-source features and strengthening collaboration effectiveness, respectively.

Polymer Fiber Rigid Network with High Glass Transition Temperature Reinforces Stability of Organic Photovoltaics.

Organic photovoltaics (OPVs) need to overcome limitations such as insufficient thermal stability to be commercialized. The reported approaches to improve stability either rely on the development of new materials or on tailoring the donor/acceptor morphology, however, exhibiting limited applicability. Therefore, it is timely to develop an easy method to enhance thermal stability without having to develop new donor/acceptor materials or donor-acceptor compatibilizers, or by introducing another third component. Herein, a unique approach is presented, based on constructing a polymer fiber rigid network with a high glass transition temperature (Tg) to impede the movement of acceptor and donor molecules, to immobilize the active layer morphology, and thereby to improve thermal stability. A high-Tg one-dimensional aramid nanofiber (ANF) is utilized for network construction. Inverted OPVs with ANF network yield superior thermal stability compared to the ANF-free counterpart. The ANF network-incorporated active layer demonstrates significantly more stable morphology than the ANF-free counterpart, thereby leaving fundamental processes such as charge separation, transport, and collection, determining the device efficiency, largely unaltered. This strategy is also successfully applied to other photovoltaic systems. The strategy of incorporating a polymer fiber rigid network with high Tg offers a distinct perspective addressing the challenge of thermal instability with simplicity and universality.

Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling.

Engineering natural microbiomes for biotechnological applications remains challenging, as metabolic interactions within microbiomes are largely unknown, and practical principles and tools for microbiome engineering are still lacking. Here, we present a combinatory top-down and bottom-up framework to engineer natural microbiomes for the construction of function-enhanced synthetic microbiomes. We show that application of herbicide and herbicide-degrader inoculation drives a convergent succession of different natural microbiomes toward functional microbiomes (e.g., enhanced bioremediation of herbicide-contaminated soils). We develop a metabolic modeling pipeline, SuperCC, that can be used to document metabolic interactions within microbiomes and to simulate the performances of different microbiomes. Using SuperCC, we construct bioremediation-enhanced synthetic microbiomes based on 18 keystone species identified from natural microbiomes. Our results highlight the importance of metabolic interactions in shaping microbiome functions and provide practical guidance for engineering natural microbiomes.

Structure information analysis and relative content determination of protein and chitin from yellow mealworm larvae using Raman spectroscopy.

Insect protein extract is one of the high-quality protein sources and is frequently viewed as a potential nutrition alternative. However, a more precise method for protein measurement is still needed due to protein overestimation by the Kjeldahl method due to the presence of a large amount of chitin in insects. Therefore, we demonstrated the monitoring of chitin and protein extracted from yellow mealworm larvae through the information on molecular vibration obtained using Raman spectroscopy and infrared (IR) spectroscopy. The NH vibration at 3475 cm-1 is the characteristic peak of chitin in defatted product observed in the Raman spectra. The nitrogen-to-protein conversion factor in protein extracted from larvae by the Raman method was determined based on the NH vibration and found to be 5.66 ± 0.01. We also compared these experimental data to theoretical Raman and IR spectra and determined the possible reasons for why nitrogen elements in chitin affect the determination of protein content. The method of sequentially removing fat and protein could provide more accurate quantification of protein and chitin. Raman spectroscopy is feasible for various types of insects with high chitin content. Compared with the Kjeldahl method, the Raman method is a faster and more accurate measurement method. Moreover, it provides the content of impurities, purity, and structural information.

High sensitivity humidity sensor based on the U-shaped tapered no-core fiber coated with MXene.

Ti3C2Tx MXene is an emerging two-dimensional material that has good potential in relative humidity (RH) measurement because of its unique layer structure, strong hydrophilic nature, and large specific surface area. Here, a high-performance RH sensor integrating Ti3C2TX MXene nanosheets and U-shaped tapered no-core fiber (UTNCF) is proposed. The sensing principle is based on mode interference. The change of ambient RH leads to the change of the refractive index (RI) of Ti3C2Tx MXene, which eventually leads to the shift of the transmission spectrum of the sensing probe. The average sensitivity is 1.11 nm/%RH in the RH range of 45% to 80%, and the response time is 25 ms. The proposed micro-nano fiber RH sensor has the advantages of high sensitivity, fast response, good repeatability, and stability. In addition, the proposed sensor has a broad application prospect in human respiratory monitoring, industrial and agricultural production, and environmental monitoring.

Construction of the pulmonary bio-adhesive delivery system of nintedanib nanocrystalline for effective treatment of pulmonary fibrosis.

Pulmonary fibrosis (PF) is a chronic, progressive, and fatal lung disease with a high mortality rate. Nintedanib, as a multi-tyrosine kinase inhibitor, is widely used as the first line drug for PF patients. However, only nintedanib oral formulations are used currently in clinic and show a low drug selectivity, significant first-pass effect and low bioavailability with 4.7%, thus limiting the clinical outcome of nintedanib. In this study, nintedanib was prepared in the form of nintedanib nanocrystalline (Nib-NC) and then encapsulated with hyaluronic acid (HA) to construct a nanocrystalline-in-adhesive delivery system Nib-NC@HA with high drug loading efficacy and pulmonary bio-adhesive properties, which could avoid the first-pass effects, increase the bioavailability and reduce the systemic side effects of nintedanib. After inhalation administration of Nib-NC@HA, due to the bio-adhesive properties of HA, Nib-NC@HA could prolong the retention time of drug in the lungs and inhibit the expression of inflammation associated factors such as IL-6, IL-1ß and TNF-α in lung tissue, reduce the release of pro-fibrotic growth factor, and improve the lung function, thus showing enhanced anti-fibrotic effect than Nib-NC. The results suggested that Nib-NC@HA is an efficient and optimal targeted bio-adhesive delivery system for the lungs to treat pulmonary fibrosis.

Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke.

Background and objectives: Upwards of 50% of acute ischemic stroke (AIS) survivors endure varying degrees of disability, with a recurrence rate of 17.7%. Thus, the prediction of outcomes in AIS may be useful for treatment decisions. This study aimed to determine the applicability of a machine learning approach for forecasting early outcomes in AIS patients. Methods: A total of 659 patients with new-onset AIS admitted to the Department of Neurology of both the First and Second Affiliated Hospitals of Bengbu Medical University from January 2020 to October 2022 included in the study. The patient' demographic information, medical history, Trial of Org 10,172 in Acute Stroke Treatment (TOAST), National Institute of Health Stroke Scale (NIHSS) and laboratory indicators at 24 h of admission data were collected. The Modified Rankine Scale (mRS) was used to assess the 3-mouth outcome of participants' prognosis. We constructed nine machine learning models based on 18 parameters and compared their accuracies for outcome variables. Results: Feature selection through the Least Absolute Shrinkage and Selection Operator cross-validation (Lasso CV) method identified the most critical predictors for early prognosis in AIS patients as white blood cell (WBC), homocysteine (HCY), D-Dimer, baseline NIHSS, fibrinogen degradation product (FDP), and glucose (GLU). Among the nine machine learning models evaluated, the Random Forest model exhibited superior performance in the test set, achieving an Area Under the Curve (AUC) of 0.852, an accuracy rate of 0.818, a sensitivity of 0.654, a specificity of 0.945, and a recall rate of 0.900. Conclusion: These findings indicate that RF models utilizing general clinical and laboratory data from the initial 24 h of admission can effectively predict the early prognosis of AIS patients.

A novel missense mutation of CCDC34 causes male infertility with oligoasthenoteratozoospermia in a consanguineous Pakistani family.

ABSTRACT: Male infertility is a worldwide health issue, affecting 8%-12% of the global population. Oligoasthenoteratozoospermia (OAT) represents a severe type of male infertility, characterized by reduced sperm count and motility and an increased frequency of sperm with aberrant morphology. Using whole-exome sequencing, this study identified a novel missense mutation (c.848C>A, p.A283E) in the coiled-coil domain-containing 34 gene (CCDC34) in a consanguineous Pakistani family. This rare mutation was predicted to be deleterious and to affect the protein stability. Hematoxylin and eosin staining of spermatozoa from the patient with OAT revealed multiple morphological abnormalities of the flagella and transmission electron microscopy indicated axonemal ultrastructural defects with a lack of outer dynein arms. These findings indicated that CCDC34 plays a role in maintaining the axonemal ultrastructure and the assembly or stability of the outer dynein arms, thus expanding the phenotypic spectrum of CCDC34 missense mutations.

TP-GCL: graph contrastive learning from the tensor perspective.

Graph Neural Networks (GNNs) have demonstrated significant potential as powerful tools for handling graph data in various fields. However, traditional GNNs often encounter limitations in information capture and generalization when dealing with complex and high-order graph structures. Concurrently, the sparse labeling phenomenon in graph data poses challenges in practical applications. To address these issues, we propose a novel graph contrastive learning method, TP-GCL, based on a tensor perspective. The objective is to overcome the limitations of traditional GNNs in modeling complex structures and addressing the issue of sparse labels. Firstly, we transform ordinary graphs into hypergraphs through clique expansion and employ high-order adjacency tensors to represent hypergraphs, aiming to comprehensively capture their complex structural information. Secondly, we introduce a contrastive learning framework, using the original graph as the anchor, to further explore the differences and similarities between the anchor graph and the tensorized hypergraph. This process effectively extracts crucial structural features from graph data. Experimental results demonstrate that TP-GCL achieves significant performance improvements compared to baseline methods across multiple public datasets, particularly showcasing enhanced generalization capabilities and effectiveness in handling complex graph structures and sparse labeled data.

Hypertension and cardiac damage in pheochromocytoma and paraganglioma patients: a large-scale single-center cohort study.

BACKGROUND: Hypertension (HT) is one of the most common manifestations in patients with catecholamine-secreting neuroendocrine tumors. Although the cardiovascular manifestations of these tumors have been described, there have been no large-scale investigations of the profile of HT and changes in cardiac structure and function that occur in patients with pheochromocytomas and paragangliomas (PPGL). MATERIALS AND METHODS: In this study, we investigated the prevalence of HT and left ventricular remodeling (LVR) in a cohort of 598 patients who underwent surgery for PPGL at our center between January 2001 and April 2022. Information on demographics, reason for hospitalization, medical history, biochemical parameters, findings on echocardiography, and tumor characteristics were recorded. The LVR index was compared according to whether or not there was a history of HT. RESULTS: The average age was 47.07 ± 15.07 years, and 277 (46.32%) of the patients were male. A history of HT was found in 423 (70.74%) of the 598 patients. Paraganglioma was significantly more common in the group with HT (26.00% vs. 17.71%, P = 0.030) and significantly less likely to be found incidentally during a health check-up in this group (22.93% vs. 59.43%, P < 0.001). Among 365 patients with complete echocardiography data, left ventricular mass index (86.58 ± 26.70 vs. 75.80 ± 17.26, P < 0.001) and relative wall thickness (0.43 ± 0. 08 vs. 0.41 ± 0.06, P = 0.012) were significantly higher in patients with PPGL and a history of HT. The proportions with left ventricular hypertrophy (LVH) (19.40% vs. 8.25%, P = 0.011) and LVR (53.73% vs. 39.18%, P = 0.014) were also higher when there was a history of HT. After adjusting for age, gender, body mass index, alcohol consumption, smoking status, diabetes, stroke, creatinine level, tumor location, and tumor size, a history of HT was significantly correlated with LVH (odds ratio 2.71, 95% confidence interval 1.18-6.19; P = 0.018) and LVR (odds ratio 1.83, 95% confidence interval 1.11-3.03; P = 0.018). CONCLUSION: HT is common in patients with PPGL (70.74% in this cohort). PPGL without a history of HT is more likely to be found incidentally (59.43% in our cohort). HT is associated with LVR in PPGL patients with complete echocardiography data. These patients should be observed carefully for cardiac damage, especially those with a history of HT.

Efficacy of a mouthwash containing ε-poly-L-lysine, funme peptides and domiphen in reducing halitosis and supragingival plaque: a randomized clinical trial.

OBJECTIVE: To evaluate the antibacterial effectiveness of a combination of ε-poly-L-lysine (ε-PL), funme peptide (FP) as well as domiphen against oral pathogens, and assess the efficacy of a BOP® mouthwash supplemented with this combination in reducing halitosis and supragingival plaque in a clinical trial. MATERIALS AND METHODS: The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the compound against Fusobacterium nucleatum, Porphyromonas gingivalis, Streptococcus mutans, and Aggregatibacter actinomycetemcomitans were determined by the gradient dilution method. Subsequently, the CCK-8 assay was used to detect the toxicity of mouthwash on human gingival fibroblastst, and the effectiveness in reducing halitosis and supragingival plaque of the mouthwash supplemented with the combination was analyzed by a randomized, double-blind, parallel-controlled clinical trial. RESULTS: The combination exhibited significant inhibitory effects on tested oral pathogens with the MIC < 1.56% (v/v) and the MBC < 3.13% (v/v), and the mouthwash containing this combination did not inhibit the viability of human gingival fibroblasts at the test concentrations. The clinical trial showed that the test group displayed notably lower volatile sulfur compounds (VSCs) at 0, 10, 24 h, and 7 d post-mouthwash (P < 0.05), compared with the baseline. After 7 days, the VSC levels of the and control groups were reduced by 50.27% and 32.12%, respectively, and notably cutting severe halitosis by 57.03% in the test group. Additionally, the Plaque Index (PLI) of the test and control group decreased by 54.55% and 8.38%, respectively, and there was a significant difference in PLI between the two groups after 7 days (P < 0.01). CONCLUSIONS: The combination of ε-PL, FP and domiphen demonstrated potent inhibitory and bactericidal effects against the tested oral pathogens, and the newly formulated mouthwash added with the combination exhibited anti-dental plaque and anti-halitosis properties in a clinical trial and was safe. TRIAL REGISTRATION: The randomized controlled clinical trial was registered on Chinese Clinical Trial Registry (No. ChiCTR2300073816, Date: 21/07/2023).

Recent Advances in the Inhibition of Membrane Lipid Peroxidation by Food-Borne Plant Polyphenols via the Nrf2/GPx4 Pathway.

Lipid peroxidation (LP) leads to changes in the fluidity and permeability of cell membranes, affecting normal cellular function and potentially triggering apoptosis or necrosis. This process is closely correlated with the onset of many diseases. Evidence suggests that the phenolic hydroxyl groups in food-borne plant polyphenols (FPPs) make them effective antioxidants capable of preventing diseases triggered by cell membrane LP. Proper dietary intake of FPPs can attenuate cellular oxidative stress, especially damage to cell membrane phospholipids, by activating the Nrf2/GPx4 pathway. Nuclear factor E2-related factor 2 (Nrf2) is an oxidative stress antagonist. The signaling pathway regulated by Nrf2 is a defense transduction pathway of the organism against external stimuli such as reactive oxygen species and exogenous chemicals. Glutathione peroxidase 4 (GPx4), under the regulation of Nrf2, is the only enzyme that reduces cell membrane lipid peroxides with specificity, thus playing a pivotal role in regulating cellular ferroptosis and counteracting oxidative stress. This study explored the Nrf2/GPx4 pathway mechanism, antioxidant activity of FPPs, and mechanism of LP. It also highlighted the bioprotective properties of FPPs against LP and its associated mechanisms, including (i) activation of the Nrf2/GPx4 pathway, with GPx4 potentially serving as a central target protein, (ii) regulation of antioxidant enzyme activities, leading to a reduction in the production of ROS and other peroxides, and (iii) antioxidant effects on LP and downstream phospholipid structure. In conclusion, FPPs play a crucial role as natural antioxidants in preventing LP. However, further in-depth analysis of FPPs coregulation of multiple signaling pathways is required, and the combined effects of these mechanisms need further evaluation in experimental models. Human trials could provide valuable insights into new directions for research and application.

Analysis of endophytic bacterial diversity in seeds of different genotypes of cotton and the suppression of Verticillium wilt pathogen infection by a synthetic microbial community.

BACKGROUND: In agricultural production, fungal diseases significantly impact the yield and quality of cotton (Gossypium spp.) with Verticillium wilt posing a particularly severe threat. RESULTS: This study is focused on investigating the effectiveness of endophytic microbial communities present in the seeds of disease-resistant cotton genotypes in the control of cotton Verticillium wilt. The technique of 16S ribosomal RNA (16S rRNA) amplicon sequencing identified a significant enrichment of the Bacillus genus in the resistant genotype Xinluzao 78, which differed from the endophytic bacterial community structure in the susceptible genotype Xinluzao 63. Specific enriched strains were isolated and screened from the seeds of Xinluzao 78 to further explore the biological functions of seed endophytes. A synthetic microbial community (SynCom) was constructed using the broken-rod model, and seeds of the susceptible genotype Xinluzao 63 in this community that had been soaked with the SynCom were found to significantly control the occurrence of Verticillium wilt and regulate the growth of cotton plants. Antibiotic screening techniques were used to preliminarily identify the colonization of strains in the community. These techniques revealed that the strains can colonize plant tissues and occupy ecological niches in cotton tissues through a priority effect, which prevents infection by pathogens. CONCLUSION: This study highlights the key role of seed endophytes in driving plant disease defense and provides a theoretical basis for the future application of SynComs in agriculture.

Se site targeted-two circles antioxidant in GPx4-like catalytic peroxide degradation by polyphenols (-)-epigallocatechin gallate and genistein using SERS.

A Se site targeted-two circles antioxidant of polyphenols EGCG and genistein in glutathione peroxidase 4 (GPx4)-like catalytic peroxide H2O2 and cumene hydroperoxide degradation was demonstrated by surface-enhanced Raman scattering (SERS). Se atom's active center is presenting a 'low-oxidation' and a 'high-oxidation' catalytic cycle. The former is oxidized to selenenic acid (SeO-) with a Raman bond at 619/ 610 cm-1 assigned to the νO - Se by the hydroperoxide substrate at 544/ 551 cm-1 assigned to ωHSeC decreased. Under oxidative stress, the enzyme shifted to 'high-oxidation' catalytic cycle, in which GPx4 shuttles between R-SeO- and R-SeOO- with a Raman intensity of bond at 840/ 860 cm-1 assigned to νO[bond, double bond]Se. EGCG could act as a reducing agent both in H2O2 and Cu-OOH degradation, while, genistein can only reduce Cu-OOH, because it binds more readily to the selenium site in GPx4 than EGCG with a closer proximity, therefore may affect its simultaneous binding to coenzymes.

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study.

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

C-Phycocyanin improves the quality of goat oocytes after in vitro maturation and vitrification.

In vitro maturation (IVM) and cryopreservation of goat oocytes are important for establishing a valuable genetic bank for domesticated female animals and improving livestock reproductive efficiency. C-Phycocyanin (PC) is a Spirulina extract with antioxidant, antiinflammatory, and radical scavenging properties. However, whether PC has positive effect on goat oocytes IVM or developmental competence after vitrification is still unknown. In this study, we found that first polar body extrusion (n = 293), cumulus expansion index (n = 269), and parthenogenetic blastocyst formation (n = 281) were facilitated by adding 30 µg/mL PC to the oocyte maturation medium when compared with the control groups and that supplemented with 3, 10, 100 or 300 µg/mL PC (P < 0.05). Although PC supplementation did not affect spindle formation or chromosome alignment (n = 115), it facilitated or improved cortical granules migration (n = 46, P < 0.05), mitochondria distribution (n = 39, P < 0.05), and mitochondrial membrane potential (n = 46, P < 10-4). Meanwhile, supplementation with 30 µg/mL PC in the maturation medium could significantly inhibit the reactive oxygen species accumulation (n = 65, P < 10-4), and cell apoptosis (n = 42, P < 0.05). In addition, PC increased the oocyte mRNA levels of GPX4 (P < 0.01), and decreased the mRNA and protein levels of BAX (P < 0.01). Next, we investigated the effect of PC supplementation in the vitrification solution on oocyte cryopreservation. When compared with the those equilibrate in the vitrification solution without PC, recovered oocytes in the 30 µg/mL PC group showed higher ratios of normal morphology (n = 85, P < 0.05), survival (n = 85, P < 0.05), first polar body extrusion (n = 62, P < 0.05), and parthenogenetic blastocyst formation (n = 107, P < 0.05). Meanwhile, PC supplementation of the vitrification solution increased oocyte mitochondrial membrane potential (n = 53, P < 0.05), decreased the reactive oxygen species accumulation (n = 73, P < 0.05), promoted mitochondria distribution (n = 58, P < 0.05), and inhibited apoptosis (n = 46, P < 10-3). Collectively, our findings suggest that PC improves goat oocyte IVM and vitrification by reducing oxidative stress and early apoptosis, which providing a novel strategy for livestock gamete preservation and utilization.

Selective Orbital Coupling: An Adsorption Mechanism in Single-Atom Catalysis.

Quantitative understanding of the chemisorption on single-atom catalysts (SACs) by their electronic properties is crucial for the catalyst design. However, the physical mechanism is still under debate. Here, the CO catalytic oxidation on single transition metal (i.e., Sc, Ti, V, Cr, Mn, Fe, Co, Ni) dopants is used as a theoretical model to explore the correlations between the characteristics of electronic structures and the chemisorption on SACs. For these metal dopants, their atomic d orbitals form several nondegenerate and localized electronic states that are found to be selectively coupled with the π* orbital of the adsorbed O2, which we defined as selective orbital coupling. Based on the selective orbital coupling, we find that the alignment between the selected d state and the π* state determines the bond strength, regardless of the electron occupation number of the selected d states; the electron transfer to form M-O bonding can be provided by the support. Such electron transfer can be related with the electronic metal-support interaction. We attribute the origin of the chemisorption mechanism to the coexistence of the localized orbital of the single transition metal and the continuous energy band of the Au support. Finally, we illustrate how this mechanism dominates the variation trend of the reaction barriers. Our results unravel a fundamental adsorption mechanism in SAC systems.