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Abstract Biallelic mutations of the chromatin regulator SMARCAL1 cause Schimke Immunoosseous Dysplasia (SIOD), characterized by severe growth defects and premature mortality. Atherosclerosis and hyperlipidemia are common among SIOD patients, yet their onset and progression are poorly understood. Using an integrative approach involving proteomics, mouse models, and population genetics, we investigated SMARCAL1’s role. We found that SmarcAL1 interacts with angiopoietin-like 3 (Angptl3), a key regulator of lipoprotein metabolism. In vitro and in vivo analyses demonstrate SmarcAL1’s vital role in maintaining cellular lipid homeostasis. The observed translocation of SmarcAL1 to cytoplasmic peroxisomes suggests a potential regulatory role in lipid metabolism through gene expression. SmarcAL1 gene inactivation reduces the expression of key genes in cellular lipid catabolism. Population genetics investigations highlight significant associations between SMARCAL1 genetic variations and body mass index, along with lipid-related traits. This study underscores SMARCAL1’s pivotal role in cellular lipid metabolism, likely contributing to the observed lipid phenotypes in SIOD patients.

Abstract Background The ovary is an important reproductive organ in mammals, and its development directly affects the sexual maturity and reproductive capacity of individuals. MicroRNAs (miRNAs) are recognized as regulators of reproductive physiological processes in various animals and have been shown to regulate ovarian development through typical targeting and translational repression. However, little is known about the regulatory role of miRNAs in ovarian tissue development during sexual maturity in goats. To comprehensively profile the different physiological stages of sexual maturation in goats, we performed small-RNA sequencing of ovarian tissue samples collected at four specific time points (1 day after birth (D1), 2 months old (M2), 4 months old (M4), and 6 months old (M6)). In addition, we used ELISAs to measure serum levels of reproductive hormones to study their temporal changes. Results The results showed that serum levels of gonadotropin-releasing hormone, follicle-stimulating hormone, luteinizing hormone, oestradiol, progesterone, oxytocin, and prolactin were lower in goats at the D1 stage than at the other three developmental stages (P 1, FDR

The accurate characterization of soil structure is fundamental to groundwater science, environmental ecology, and Earth systems science. To address the challenge of quantifying the high spatial variability of large-scale soil structures, this study used a laser particle size analyzer to measure the distribution of soil particle size in 207 samples from ten profiles across the Daqing and Ziya River basins in the North China Plain. The quantified soil structure, expressed as soil fractal dimension D, was derived using monofractal theory. Various spatial analysis techniques, including Moran’s I index, correlation analysis heat maps, the Kolmogorov–Smirnov one-sample test, and geostatistical semivariogram function, were jointly applied to investigate the spatial variability of soil structural fractals across different depths in the piedmont plain–coastal areas of the two river basins. The results indicate the following: (1) Quantitative analysis confirms that under the influence of piedmont alluvial and fluvial dynamics, soil D values homogenize from the piedmont to the coastal areas, with decreasing particle size differences closer to the coast. However, the spatial variability of the soil structural fractals in the Ziya River Basin was greater than that in the Daqing River Basin. (2) The combined effects of climate change, regional differences, and human activity led to greater spatial variability in the soil structural fractals in the Ziya River Basin than in the Daqing River Basin. The correlation between D values and burial depth was strongest in the Xianxian profile (−0.78), whereas the spatial correlation was strongest in the Hengshui and Dacheng profiles (−0.47). (3) The greatest spatial variability in soil D values occurred at depths of 1–2 m, with a coefficient of variation of 23.595%, which was significantly higher than those at depths of 0–1 (14.569%) and 2–3 m (16.284%).

Verticillium wilt, caused by Verticillium dahliae, is a soil-borne disease affecting eggplant. Wild eggplant, recognized as an excellent disease-resistant resource against verticillium wilt, plays a pivotal role in grafting and breeding for disease resistance. However, the underlying resistance mechanisms of wild eggplant remain poorly understood. This study compared two wild eggplant varieties, LC-2 (high resistance) and LC-7 (sensitive) at the phenotypic, transcriptomic, and metabolomic levels to determine the molecular basis of their resistance to verticillium wilt. These two varieties exhibit substantial phenotypic differences in petal color, leaf spines, and fruit traits. Following inoculation with V. dahliae, LC-2 demonstrated significantly higher activities of polyphenol oxidase, superoxide dismutase, peroxidase, phenylalanine ammonia lyase, β-1,3 glucanase, and chitinase than did LC-7. RNA sequencing revealed 4,017 differentially expressed genes (DEGs), with a significant portion implicated in processes associated with disease resistance and growth. These processes encompassed defense responses, cell wall biogenesis, developmental processes, and biosynthesis of spermidine, cinnamic acid, and cutin. A gene co-expression analysis identified 13 transcription factors as hub genes in modules related to plant defense response. Some genes exhibited distinct expression patterns between LC-2 and LC-7, suggesting their crucial roles in responding to infection. Further, metabolome analysis identified 549 differentially accumulated metabolites (DAMs) between LC-2 and LC-7, primarily consisting of compounds such as flavonoids, phenolic acids, lipids, and other metabolites. Integrated transcriptome and metabolome analyses revealed the association of 35 gene–metabolite pairs in modules related to the plant defense response, highlighting the interconnected processes underlying the plant defense response. These findings characterize the molecular basis of LC-2 resistance to verticillium wilt and thus have potential value for future breeding of wilt-resistant eggplant varieties.

GATA proteins are transcription factors of zinc finger proteins, which play an important role in plant growth development and abiotic stress. However, there have been no identification or systematic studies of the GATA gene family in eggplant. In this study, 28 SmGATA genes were identified in the genome database of eggplant, which could be divided into four subgroups. Plant development, hormones, and stress-related cis-acting elements were identified in promoter regions of the SmGATA gene family. RT-qPCR indicated that 4 SmGATA genes displayed upregulated expressions during fruit developmental stage, whereas 2 SmGATA genes were down-regulated expression patterns. It was also demonstrated that SmGATA genes may be involved in light signals to regulate fruit anthocyanin biosynthesis. Furthermore, the expression patterns of SmGATA genes under ABA, GA and MeJA treatments showed that the SmGATAs were involved in the process of fruit ripening. Notably, SmGATA4 and SmGATA23 were highly correlated with the expression of anthocyanin biosynthesis genes, light-responsive genes, and genes that function in multiple hormone signaling pathways and the proteins they encoded were localized in the nucleus. All these results showed GATA genes likely play a major role in regulating fruit anthocyanin biosynthesis by integrating the light, ABA, GA and MeJA signaling pathways and provided references for further research on fruit quality in eggplant.

Development of a micromodel that recapitulates multiple mechanical properties to mimic the complex mechanical microenvironment is crucial for cell‐based research. Herein, a microsystem combining structure of hydrogel matrix and acoustic streaming (AS) to mimic the cellular microenvironment is proposed, which can realize multiplex cellular mechanical cues, including matrix stiffness, fluid shear stress (FSS) generated by AS, and matrix roughness. The results demonstrate that the cell spreading area enlarges with the increase of matrix stiffness, and cell spreading is encouraged by integrin β1 cluster to polymerize actin when combines the hydrogel matrix with FSS. In addition, FSS has the influence on the roughness of the hydrogel, which further affects the cell morphology and mechanical properties, inducing mesenchymal stem cells (MSCs) differentiation into astrocytes rapidly. Meanwhile, cell migration is also enhanced by FSS stimulation, particularly, undifferentiated cells at 22 kPa hydrogel have the fastest migration speed, and change the movement model from contact inhibition to contact stimulation migration. Especially, matrix roughness and stiffness dominantly control of cell spreading and differentiation, whereas FSS affects cell migration. In conclusion, the microsystem in this work shows superior performance in regulating the spreading, differentiation, and migration of MSCs, which provides a new tool for cell‐microenvironment study.

Many clinical management strategies have been proposed to deal with diabetic foot ulcers. However, the occurrence and recurrence of foot ulcers remain the major problems for diabetics. This study aims to identify, visualize, and characterize the meta-analyses on diabetic foot ulcer research. Articles published online were retrieved from the Web of Science core collection database using a search query incorporating MeSH terms and topics related to diabetic foot ulcers and meta-analysis. The publications were then analyzed for basic characteristics, including publication year, countries, topics covered, references, and keywords discussed in the articles. Data visualization was performed using CiteSpace. 334 meta-analyses and systematic reviews on diabetic foot ulcers were identified. The number of publications has experienced rapid growth in recent years (nearly 6-fold since 2016). The United States, China, Netherlands, England, and Australia had a strong collaboration in the contribution of publication. 7 primary topics were summarized from the top 100 highly cited publications: #1 Interventions (proportion: 59%), #2 Risk factors and Prevention (22%), #3 Epidemiology analysis (6%), #4 Cost-effectiveness of interventions (5%), #5 Long-term prognosis (3%), #6 Quality of life analysis (3%), and #7 Economic burden analysis (2%). Footwear and offloading interventions, multidisciplinary care, hyperbaric oxygen, platelet-rich plasma, and negative pressure wound therapies are highly regarded in terms of intervention. Diabetic foot osteomyelitis, peripheral diabetic neuropathy, chronic limb-threatening ischemia, and infections are the main comorbidities. In recent years, offloading interventions, debridement, telemedicine, long-term prognosis, and economic burden analyses have gradually received attention. Individualized treatment, multidisciplinary collaboration, quality of life considerations, and economic burden analyses are the long-term concerns.

Rationale and objectivesTo construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value.Materials and methodsWe selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated.ResultsAge, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology.ConclusionThe random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

Soil salinization has significant deleterious impacts on arable lands and crop productivity worldwide. Plant growth–promoting rhizobacteria (PGPR) have the capability to establish mutualistic associations with plants, resulting in the increase of plant growth under abiotic stress. PGPR strain RL-WG26 was previously isolated from the rhizosphere of rice Sea Rice 86 (SR86). In this study, by genome-based average nucleotide identity (ANI) calculation, RL-WG26 was re-identified as Pseudomonas promysalinigenes here instead of Pseudomonas putida. SR86 seedlings inoculated with RL-WG26 possessed significant increases in plant biomass (fresh weight and dry weight), root surface area and length, and chlorophyll content under either normal or saline conditions, when compared with those without RL-WG26 inoculation. Ion content analysis demonstrated that seedlings inoculated with RL-WG26 contained lower Na+ and Cl– accumulation but higher K+ and Ca2+ uptake under saline condition, which finally alleviated the salt ion toxic in the RL-WG26 inoculated seedlings, when compared with those without RL-WG26 inoculation. In addition, SR86 seedlings inoculated with RL-WG26 also exhibited higher antioxidant activity and higher concentration of osmoregulation factor proline than those without RL-WG26 inoculation. At last, genomic analysis of strain RL-WG26 identified several genes and gene clusters encoding 1-aminocyclopropane-1-carboxylic acid (ACC)-deaminase, the tryptophan-dependent indole-3-acetic acid (IAA) synthesis pathway, and the synthesis of betaine. Taken together, PGPR strain RL-WG26 could enhance the growth and salt stress tolerance in SR86 seedlings through various pathways, which provide a foundation for deciphering the molecular mechanisms of strain RL-WG26-mediated plant salt tolerance and promote the application of this strain.

Abstract Lichens are of great ecological importance but mechanisms regulating lichen symbiosis are not clear. Umbilicaria muhlenbergii is a lichen-forming fungus amenable to molecular manipulations and dimorphic. Here, we established conditions conducive to symbiotic interactions and lichen differentiation and showed the importance of UMP1 MAP kinase in lichen development. In the initial biofilm-like symbiotic complexes, algal cells were interwoven with pseudohyphae covered with extracellular matrix. After longer incubation, fungal-algal complexes further differentiated into primitive lichen thalli with a melanized cortex-like and pseudoparenchyma-like tissues containing photoactive algal cells. Mutants deleted of UMP1 were blocked in pseudohyphal growth and development of biofilm-like complexes and primitive lichens. Invasion of dividing mother cells that contributes to algal layer organization in lichens was not observed in the ump1 mutant. Overall, these results showed regulatory roles of UMP1 in symbiotic interactions and lichen development and suitability of U. muhlenbergii as a model for studying lichen symbiosis.

Abstract In order to effectively use of phages as antimicrobial agents for controlling multidrug-resistant E. coli, it is important to understand phage biology. The isolation and research of novel bacteriophages are urgently needed for food safety and animal health. Phage is considered as a novel alternative antibacterial agents and a new way of prevent, control and treat pathogens. In this paper, we isolated and characterized a novel lytic phage from chicken samples, named vB_EscP_vE20 (in brief vE20). We identified vE20 as belonging to the Podoviridae family through morphological and phylogenetic analysis. It had lytic activities against 24 out of 51 different serotypes of clinical E. coli strains, interestingly it also can lyse Salmonella species, such as Salmonella Enteritidis (S. Enteritidis) and Samonella Typhimurium (S. Typhimurium). One step growth curve showed that the latent period and lysis period was 10 min and 60 min, respectively. The burst size of vE20 was about 60 PFU/cell. The phage vE20 survived in a wide range of temperatures (30–60 °C) and pH (3–11). The whole genome size of phage vE20 is 77,938 bps, which is double stranded DNA. There are 121 Open reading frame (ORFs) in total, and the GC-content is 42.17%, without virulence-associated, antibiotic and lysogeny related genes. Phage vE20 has high bactericidal activity in killing E. coli EXG20-1 in cultures containing 4 × 109 cfu/mL in several MOIs culture. The results revealed the promising potential of phage vE20 as attractive candidates for the control of E. coli infections. Graphical Abstract

Abstract Background The immunity of patients with lung cancer decreases after treatment; thus, they are easily infected with pathogenic bacteria that causes pulmonary infections. Understanding the distribution characteristics of pathogenic bacteria in pulmonary infection in patients with lung cancer after treatment can provide a basis to effectively prevent infection and rationally use antibacterial drugs. However, no meta-analyses have assessed the distribution characteristics of pathogenic bacteria in mainland China. Therefore, our meta-analysis aimed to investigate the pathogen distribution in pulmonary infection in Chinese patients with lung cancer. Methods A literature search was conducted to study the pathogen distribution in pulmonary infection in Chinese patients with lung cancer between January 1, 2020 and December 31, 2022, using English and Chinese databases. The relevant data were extracted. The meta-analysis was performed using a random-effects model ( I2 > 50%) with 95% confidence intervals for forest plots. Data were processed using RevMan 5.3. Results Fifteen studies (2,683 strains in 2,129 patients with pulmonary infection were cultured) met the evaluation criteria. The results showed that Gram-negative bacteria had the highest detection rate (63%), followed by Gram-positive bacteria (23%), and fungi (12%). Among the Gram-negative bacteria detected, the distribution of the main pathogenic bacteria was Klebsiella pneumonia (17%), Pseudomonas aeruginosa (14%), Escherichia coli (13%), Acinetobacter baumannii (7%), Enterobacter cloacae (4%), and Hemophilus influenza (4%). Moreover, the prevalence of pulmonary infections after chemotherapy (53%) was significantly higher than that after surgery (10%), P

Abstract Orientation estimation is one of the core problems in several computer vision tasks. Recently deep learning techniques combined with the Bingham distribution have attracted considerable interest towards this problem when considering ambiguities and rotational symmetries of objects. However, existing works suffer from two issues. First, the computational overhead for calculating the normalisation constant of the Bingham distribution is relatively high. Second, the choice of loss functions is uncertain. In light of these problems, we present an online deep Bingham network to estimate the orientation of objects. We sharply reduce the computational overhead of the normalisation constant by directly applying a numerical integration formula. Additionally, we are the first to give theorems on the convexity and Lipschitz continuity of the Bingham distribution's negative log‐likelihood, which formally indicates that it is a proper choice of the loss function. We test our method on three public datasets, namely the UPNA, the T‐LESS and Pascal3D+, showing that our method outperforms the state‐of‐the‐art in terms of orientation accuracy and time efficiency, which can reduce the runtime by more than 6 h compared to the offline methods. The ablation experiments further demonstrate the effectiveness and robustness of our model.

Abstract Sentence-level sentiment analysis (SLSA) aims to identify the overall sentiment polarity conveyed in a given sentence. The state-of-the-art performance of SLSA has been achieved by deep learning models. However, depending on the i.i.d (independent and identically distributed) assumption, the performance of these deep learning models may fall short in real scenarios, where the distributions of training and target data are almost certainly different to some extent. In this paper, we propose a supervised solution based on the non-i.i.d paradigm of gradual machine learning (GML) for SLSA. It begins with some labeled observations, and gradually labels target instances in the order of increasing hardness by iterative knowledge conveyance. It leverages labeled samples for supervised deep feature extraction, and constructs a factor graph based on the extracted features to enable gradual knowledge conveyance. Specifically, it employs a polarity classifier to detect polarity similarity between close neighbors in an embedding space, and a separate binary semantic network to extract implicit polarity relations between arbitrary instances. Our extensive experiments on benchmark datasets show that the proposed approach achieves the state-of-the-art performance on all benchmark datasets. Our work clearly demonstrates that by leveraging DNN for feature extraction, GML can easily outperform the pure DNN solutions.

Abstract Background Zoonotic diseases pose a significant threat to public health. Chlamydia, as an intracellular pathogen, can colonize the intestinal tract of humans and animals, changing the gut microbiota. However, only a few studies have evaluated alterations in the gut microbiota of horses infected with Chlamydia. Therefore, this study aimed to investigate gut microbiota and serum biochemical indicators in horses with Chlamydial infection (IG) and healthy horses (HG). Fecal and blood samples were collected from 16 horses (IG: 10; HG: 6) before morning feeding for the determination of gut microbiota and serum biochemical parameters. Results The results showed that total globulin (GLB), alanine aminotransferase (ALT), and creatine kinase (CK) levels were significantly increased in IG compared with HG. Notably, the gut microbial diversity increased in IG compared with HG. Furthermore, Moraxellaceae and Akkermanisa abundance decreased in IG, while Streptococcus, Treponema, Prevotella, and Paraprevotella abundances (13 genera of bacterial species) increased. Compared with HG, carbohydrate metabolism increased in IG while amino acid metabolism decreased. In addition, the abundance of 18 genera of bacteria was associated with the level of five serum biochemical indicators. Conclusions In summary, this study elucidated the influence of Chlamydia infection in horses on the gut microbiota, unraveling consequential alterations in its composition and metabolic profile. Therefore, this study improves the understanding of Chlamydia-induced intestinal infections.

The morphological adjustments of euhalophytes are well-known to be influenced by the soil-soluble salt variation; however, whether and how these changes in morphological traits alter the biomass allocation pattern remains unclear, especially under different NaCl levels. Therefore, an allometric analysis was applied to investigate the biomass allocation pattern and morphological plasticity, and the carbon (C), nitrogen (N), and phosphorus (P) stoichiometric characteristics of the euhalophyte Suaeda Salsa (S. salsa) at the four soil-soluble salt levels of no salt (NS), light salt (LS), moderate salt (MS), and heavy salt (HS). The results showed that soil-soluble salts significantly change the biomass allocation to the stems and leaves (p < 0.05). With the growth of S. salsa, the NS treatment produced a downward leaf mass ratio (LMR) and upward stem mass ratio (SMR); this finding was completely different from that for the salt treatments. When S. salsa was harvested on the 100th day, the HS treatment had the highest LMR (61%) and the lowest SMR (31%), while the NS treatment was the opposite, with an LMR of 44% and an SMR of 50%. Meanwhile, the soil-soluble salt reshaped the morphological characteristics of S. salsa (e.g., root length, plant height, basal stem diameter, and leaf succulence). Combined with the stoichiometric characteristics, N uptake restriction under salt stress is a vital reason for inhibited stem growth. Although the NS treatment had the highest biomass (48.65 g root box−1), the LS treatment had the highest salt absorption (3.73 g root box−1). In conclusion, S. salsa can change its biomass allocation pattern through morphological adjustments to adapt to different saline–alkali habitats. Moreover, it has an optimal biological desalting effect in lightly saline soil dominated by NaCl.

This paper concerns with the existence of radial solutions of the biharmonic elliptic equation ▵2u=f(|x|,u,|∇u|,▵u) in an annular domain Ω={x∈RN:r1<|x|

Selenium (Se) is crucial for both plants and humans, with plants acting as the main source for human Se intake. In plants, moderate Se enhances growth and increases stress resistance, whereas excessive Se leads to toxicity. The physiological mechanisms by which Se influences rice seedlings’ growth are poorly understood and require additional research. In order to study the effects of selenium stress on rice seedlings, plant phenotype analysis, root scanning, metal ion content determination, physiological response index determination, hormone level determination, quantitative PCR (qPCR), and other methods were used. Our findings indicated that sodium selenite had dual effects on rice seedling growth under hydroponic conditions. At low concentrations, Se treatment promotes rice seedling growth by enhancing biomass, root length, and antioxidant capacity. Conversely, high concentrations of sodium selenite impair and damage rice, as evidenced by leaf yellowing, reduced chlorophyll content, decreased biomass, and stunted growth. Elevated Se levels also significantly affect antioxidase activities and the levels of proline, malondialdehyde, metal ions, and various phytohormones and selenium metabolism, ion transport, and antioxidant genes in rice. The adverse effects of high Se concentrations may directly disrupt protein synthesis or indirectly induce oxidative stress by altering the absorption and synthesis of other compounds. This study aims to elucidate the physiological responses of rice to Se toxicity stress and lay the groundwork for the development of Se-enriched rice varieties.

Abstract Vitamin B6 is an essential nutrient with extensive applications in the medicine, food, animal feed, and cosmetics industries. Pyridoxine (PN), the most common commercial form of vitamin B6, is currently chemically synthesized using expensive and toxic chemicals. However, the low catalytic efficiencies of natural enzymes and the tight regulation of the metabolic pathway have hindered PN production by the microbial fermentation process. Here, we report an engineered Escherichia coli strain for PN production. Parallel pathway engineering is performed to decouple PN production and cell growth. Further, protein engineering is rationally designed including the inefficient enzymes PdxA, PdxJ, and the initial enzymes Epd and Dxs. By the iterative multimodule optimization strategy, the final strain produces 1.4 g/L of PN with productivity of 29.16 mg/L/h by fed-batch fermentation. The strategies reported here will be useful for developing microbial strains for the production of vitamins and other bioproducts having inherently low metabolic fluxes.

Objective: To establish a preparation method of Atractylodes macrocephala Koidz polysaccharide (AMP) sulfate with anti-hyperplasia of mammary. Methods: AMP were sulfated by sulfated method, and the optimal conditions for the sulfated modification were determined by response surface methodology. The structures of AMP and SAMP were initially analyzed by infrared spectroscopy (IR) and High-Performance Gel Chromatography (HPGPC). The anti-oxidative activity in vitro of polysaccharide was investigated by testing the DPPH, ABTS+, OH free radical scavenging ability of AMP and SAMP. Rat model of mammary gland hyperplasia was established by intramuscular injection of estradiol benzoate and progesterone. The rats weight and breast diameter were recorded and the pathological organization form of mammary gland of rats were observed. Results: The optimum preparation conditions were as follows: Ratio of conditions of volume ratio of sulfuric acid and n-butanol 2:1, reaction temperature −4 ℃, reaction time 21 min. The degree of substitution of SAMP was 0.59±0.00391. The HPGPC results showed the relative molecular weights for AMP and SAMP were 2719 and 33524 Da, respectively. The IR spectra showed that SAMP had characteristic absorption peaks of S=O and C-O-S appeared near 833 and 1226 cm−1, indicating that the sulfated was successful. When the sample concentration was 0.5 mg/mL, the DPPH, ABTS+, OH free radical scavenging activities of SAMP were 54.91% , 38.21%, and 42.23%, respectively. Compared with the model group, the diameter of the nipples of the rats in the SAMP group decreased (P

Abstract Background N-terminal probrain natriuretic peptide (NT-pro-BNP) and BNP are well-known markers for the diagnosis and prognostic of heart failure. Until now, it was not clear whether BNP levels are influenced by events occurring within Obstructive sleep apnea–hypopnea syndrome (OSAHS) with continuous positive airway pressure (CPAP). Methods A thorough search in PubMed, EMBASE, Google Scholar, and Web of Science databases up to October 24, 2022, and a meta-analysis aimed to explore further accurate estimates of the effects of BNP on OSAHS after CPAP treatment to assess the strength of the evidence. Results The forest plot outcome indicated that CPAP therapy did not change the BNP level in patients with OSAHS, with a weighted mean difference (WMD) of -0.47 (95% CI: -1.67 to 2.62; P = 0.53] based on the random effect model because of high significant heterogeneity (I 2 = 80%) among the studies. Subgroup analysis also explored the changes in BNP levels in patients with OSAHS. Begg’s test (P = 0.835) and Egger’s test (P = 0.245) suggested significant negative publication bias. Conclusion Our meta-analysis suggests that CPAP therapy does not change the BNP level in patients with OSAHS; therefore, it is not accurate to use BNP level as an index to evaluate heart function in patients with OSAHS, but more related research should be conducted.

Abstract Empagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, is a highly effective and well-tolerated antidiabetic drug. In addition to hypoglycemic effects, empagliflozin has many other effects, such as being hypotensive and cardioprotective. It also has anti-inflammatory and antioxidative stress effects in diabetic nephropathy. Several studies have shown that empagliflozin has anticancer effects. SGLT2 is expressed in a variety of cancer cell lines. The SGLT2 inhibitor empagliflozin has significant inhibitory effects on certain types of tumor cells, such as inhibition of proliferation, migration and induction of apoptosis. In conclusion, empagliflozin has promising applications in cancer therapy as a drug for the treatment of diabetes and heart failure. This article provides a brief review of the anticancer effects of empagliflozin.

Abstract A high‐efficiency power management unit (PMU) with wide dynamic range for radio frequency (RF) energy harvesting system is proposed in this paper. A digital zero current switching (ZCS) and a digital maximum power point tracking (MPPT) circuits are adopted. A sub‐threshold current reference circuit and a subthreshold voltage detection circuit are proposed to reduce the power consumption of always‐on control circuits and improve the conversion efficiency at low input power. A dual‐oscillator is designed to extend the frequency range and widen the input power range with optimized power consumption under low‐end band and high‐end band, respectively. Switch size and on‐time are adjusted according to the input power, which optimizes the conversion efficiency in a wide power range. Proposed PMU is implemented in a standard 180 nm CMOS process. The post‐layout simulation results show that proposed PMU can achieve cold‐start at the input voltage of 280 mV, the power consumption to maintain the PMU is only 9.6 nW. The input power range of the PMU is 11 nW–677 μW. When the input power is 50 nW, a power conversion efficiency (PCE) of 65% is achieved, and the peak PCE can reach 93% at 23.5 μW.

Background: The global increase in an aging population has led to more common age-related health challenges, particularly multimorbidity and frailty, but there is a significant gap. Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (1999–2018). The association between age and frailty was assessed using a restricted cubic spline (RCS) model, while weighted adjusted multivariable logistic regression evaluated the effect of diseases to frailty. And in machine learning process, feature selection for the frailty prediction model involved three algorithms. The model's performance was optimized using nested cross-validation and tested with various algorithms including decision tree, Logistic Regression, k-Nearest Neighbor, Random Forest, Recursive Partitioning and Regression Trees, and eXtreme Gradient Boosting (XGBoost). We used areas under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AU-PRC) to evaluate six algorithms, select the optimal model, and test the discrimination and consistency of the optimal model. Results: The study included 46,187 participants, with 6,009 cases of frailty. RCS analysis showed a non-linear association between age and frailty, with a turning point at 49 years. Key impacting variables identified are Anemia, Arthritis, Diabetes Mellitus, Coronary Heart Disease, and Hypertension. In the machine learning process, we selected the optimal data set by feature selection, including 13 variables. Through nested cross-validation, a total of 31,900 models were built using 6 algorithms. And the XGBoost model showed the highest performance (AUC = 0.8828 and AU-PRC = 0.624), and clear proficiency in both discrimination and calibration. Conclusions: We found 49 years maintain the balance of physiological reserve and external aggression. In addition, chronic diseases are trigger factor of frailty, while acute diseases are contributing factor that exacerbates the body's rapid decline. Last, the XGBoost frailty prediction model, with its simplicity, high performance and high clinical value holds potential for clinical application.

[This corrects the article DOI: 10.1371/journal.pone.0083132.].

BackgroundThe role of microsatellite instability (MSI) and prognosis for stage II–III colorectal cancer (CRC) has been described, but the role of MSI in stage I and IV CRC is controversial.MethodsA total of 2,540 CRC patients were collected from Huzhou Central Hospital, China, from January 2006 to 2016, and 783 cases were excluded. This retrospective study illustrates the correlation between MMR status and prognosis for 1,757 CRC patients as well as the correlation between MSI and prognosis for CRC patients. Two groups were classified as MSI-H and MSI-L&MSS. If the expression of one or more mismatch repair (MMR) proteins was negative, it was considered as microsatellite instability high expression (MSI-H), whereas positive expression was considered as microsatellite instability low expression and microsatellite stability (MSI-L&MSS), as assessed by correlation analyses. Overall and disease-free survival were analyzed using the Kaplan–Meier method. Univariable and multivariable analyses were conducted using Cox regression.ResultsPreoperative serum S-CEA, positive lymph, tumor size, pathologic tumor (Pt) status, node (N) stage, differentiation, chemotherapy, and the 8th Edition of the American Joint Committee on Cancer (AJCC-8) were significantly correlated with MSI (P=0.028, 0.037, 0.019, 0.007, 0.002, 0.05).ConclusionMSI-H was associated with a good prognosis for stages II to IV, whereas stage I did not show any significant correlation. Moreover, MSI expression was an independent prognostic factor.

Powdered infant formula (PIF) is prone to Cronobacter sakazakii (C. sakazakii) contamination, which can result in infections that endanger the lives of newborns and infants. Slightly acidic electrolytic water (SAEW) has shown antibacterial effects on a variety of foodborne pathogens and has a wide applicability in the food industry. Here, the antibacterial activity of SAEW against C. sakazakii and its use as a disinfectant on contact surfaces with high infection transmission risk were investigated. The inactivation of SAEW on C. sakazakii was positively correlated to the SAEW concentration and treatment time. The antibacterial effect of SAEW was achieved by decreasing the intracellular adenosine triphosphate (ATP), K+, protein, and DNA contents of C. sakazakii, reducing the intracellular pH (pHin) and destroying the cell morphology, which led to inactivation of C. sakazakii ultimately. To test the applicability of this study, the results showed that approximately 103 CFU/cm2 of C. sakazakii were successfully inactivated on stainless steel and rubber surfaces after a 30 mg/L SAEW treatment for 20 s. These results indicate the antibacterial mechanism and potential application of SAEW against C. sakazakii, as well as a new strategy for the prevention and control of C. sakazakii on stainless steel and rubber surfaces.

Pressure buildup testing can be used to analyze fracture network characteristics and conduct quantitative interpretation of relevant parameters for shale gas wells, thus providing bases for assessing the well productivity and formulating proper development strategies. This study establishes a new well test interpretation model for fractured horizontal wells based on seepage mechanisms of shale reservoirs and proposes a method for identifying fracturing patterns based on the characteristic slopes of pressure buildup curves and curve combination patterns. The pressure buildup curve patterns are identified to represent three types of shale reservoirs in the Sichuan Basin, namely the moderately deep shale reservoirs with high pressure, deep shale reservoirs with ultra-high pressure, and moderately deep shale reservoirs with normal pressure. Based on this, the relationship between the typical pressure buildup curve patterns and the fracture network types are put forward. Fracturing effects of three types of shale gas reservoir are compared and analyzed. The results show that typical flow patterns of shale reservoirs include bilinear flow in primary and secondary fractures, linear flow in secondary fractures, bilinear flow in secondary fractures and matrix, and linear flow in matrix. The fracture network characteristics can be determined using the characteristic slopes of pressure buildup curves and curve combinations. The linear flow in early secondary fractures is increasingly distinct with an increase in primary fracture conductivity. Moreover, the bilinear flow in secondary fractures and matrix and the subsequent linear flow in the matrix occur as the propping and density of secondary fractures increase. The increase in the burial depth, in-situ stress, and stress difference corresponds to a decrease in the propping of primary fractures that expand along different directions in the shale gas wells in the Sichuan Basin. Four pressure buildup curve patterns exist in the Sichuan Basin and its periphery. The pattern of pressure buildup curves of shale reservoirs in the Yongchuan area can be described as 1/2 → 1/4, indicating limited stimulated reservoir volume, poorly propped secondary fractures, and the forming of primary fractures that extend only to certain directions. The pressure buildup curves of shale reservoirs in the main block of the Fuling area show a pattern of 1/4 → 1/2 or 1/2, indicating greater stimulated reservoir volume, well propped secondary fractures, and the forming of complex fracture networks. The pattern of pressure buildup curves of shale reservoirs in the Pingqiao area is 1/2 → 1/4 → 1/2, indicating a fracturing effect somewhere between that of the Fuling and Yongchuan areas. For reservoirs with normal pressure, it is difficult to determine fracture network characteristics from pressure buildup curves due to insufficient formation energy and limited liquid drainage.

Soil salinization threatening natural and agricultural production challenges global food security. Halophytes are of great interest in soil desalinization in recent years; yet, there is a lack of a comprehensive quantitative overview of biotic and abiotic factors for halophytes’ desalinization performance across global scales. Here, a meta-analysis was conducted using 400 observations from 53 peer-reviewed studies to assess desalinization by halophytes in relation to 27 variables. Results showed that soil salinity was significantly decreased in halophytes field on average by 37.7% compared to control on a global scale (p < 0.05). Desalinization performance was better in cold and hot regions than in temperate regions, in dry regions than in wet regions, in alkaline saline soils than in neutral saline soils, and in conditions with low sand content than high sand content. Under aboveground harvest treatment, desalinization increased with the years of cultivation, while no trends were detected under no harvest treatment, indicating the importance of aboveground accumulation. Desalinization was not related to soil CaCO3 content but was accompanied by soil structure improvement, nutrition enrichment, and microbe propagation, implying other root-microbe-soil interactions rather than CaCO3 dissolution play important roles. Shoot biomass could be used as an indicator of the desalinization performance, and the performance would not be decreased due to the high uptake selectivity for K+ over Na+. Notably, desalinization was similar in the pot experiments and field experiments, but pot experiments would magnify the contribution of aboveground salt accumulation to desalinization. Our findings can help to expand the applicability and efficiency of halophytes for sustainable agricultural development in saline soils.

Summary: Cytidine deaminases as DNA mutators play important roles in immunity and genome stability. Here, we present a high-throughput protocol for deamination of long single-stranded (ss) DNA or oligo pools containing complex sequences. We describe steps for the preparation of both enzyme (activation-induced deaminase, AID) and ssDNA substrates, the deamination reaction, uracil-friendly amplification, and data analysis. This assay can be used to determine the intrinsic mutation profile of a single antibody gene or a pool of selected regions on genomic DNA.For complete details on the use and execution of this protocol, please refer to Wang et al. (2023).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Aqueous Zn-ion batteries have attracted increasing research interest; however, the development of these batteries has been hindered by several challenges, including dendrite growth, Zn corrosion, cathode material degradation, limited temperature adaptability and electrochemical stability window, which are associated with water activity and the solvation structure of electrolytes. Here we report that water activity is suppressed by increasing the electron density of the water protons through interactions with highly polar dimethylacetamide and trimethyl phosphate molecules. Meanwhile, the Zn corrosion in the hybrid electrolyte is mitigated, and the electrochemical stability window and the operating temperature of the electrolyte are extended. The dimethylacetamide alters the surface energy of Zn, guiding the (002) plane dominated deposition of Zn. Molecular dynamics simulation evidences Zn2+ ions are solvated with fewer water molecules, resulting in lower lattice strain in the NaV3O8·1.5H2O cathode during the insertion of hydrated Zn2+ ions, boosting the lifespan of Zn|| NaV3O8·1.5H2O cell to 3000 cycles.

Highlights History and benefits of zinc ion hybrid capacitors are introduced. Carbon materials with different dimensions are developed for the cathodes. Relationship between carbon structures and capacitive performances are discussed. Current collectors and separators are firstly showcased and summarized.

Sulfur (S) deficiency is becoming increasingly prevalent, posing a serious threat to crop yield and quality. The incorporation of S fertilizers into macronutrient fertilizers such as ammonium phosphate represents a straightforward and economically efficient approach to alleviating S deficiency, strengthening S supply, and improving crop yield. However, limited research has been conducted to assess the effect of monoammonium phosphate (MAP) and diammonium phosphate (DAP) with different S additions on agronomic outcomes. In this study, ammonium sulfate and elemental S with S set at 3%, 6%, 9%, and 12% (ensuring a 1:1 ratio of SO4−S to elemental S) were granulated with MAP and DAP, respectively. Maize was used as the test crop to evaluate its yield, nutrient uptake, and apparent sulfur recovery. The results showed that S-fortified MAP treatment increased crop yield and S uptake by an average of 9.3% and 10.6%, respectively. A significant difference in crop yield and S uptake was observed when the S addition in MAP exceeded 9% S. Nevertheless, no statistical difference was found among the DAP-based treatments in calcareous soil. There was a strong relationship between S applied in fertilizers and S uptake by crops for MAP-based treatments. However, the apparent sulfur recovery drastically dropped from 44.2% to 7.19% with the increased addition level of S for MAP-based fertilizers. The results of this study indicate that the addition of S to MAP could be a simple, low-cost, and effective approach with great potential to promote S fertilizer application, minimize soil S deficiency, and improve crop yield in calcareous soil.

Construction and demolition waste (C&DW) recycling products have drawn worldwide attention over the past few decades. There is a general agreement among researchers that C&DW recycling is an important means for curbing the deterioration of the environment. Previous papers mainly focused on the decision-making behavior of dual stakeholders or tripartite stakeholders, as well as the lack of cooperation among multiple stakeholders. This study explored a dynamic evolutionary game model with three different parameter conditions to research the decision-making behaviors and stable strategies of the multi-stakeholders involved in the C&DW recycling product industry, including government departments and some enterprises. This research also investigated how the government’s supervision costs, penalties applied to enterprises, and resource taxes affect the dynamic evolution process of C&DW recycling. This research conducted numerical simulations using Python to analyze stakeholders’ behavioral evolutionarily stable strategy (ESS) and the sensitivity to main factors in each stage of the C&DW recycling process to accelerate the development of construction waste resource utilization. Based on the results of the evolutionary game, this paper proposed that the roles of multi-stakeholders are different at different stages of industry development, and that supervision costs, penalties, and resource tax have their own impacts on the C&DW recycling product industry. The paper suggests a range of discussions and simulation studies to highlight the significance of the government’s refined and moderate adjustments to the regulatory incentive system and the level of government regulation and involvement at different stages of the process. These adjustments are aimed at promoting the sustainable recycling and utilization of construction and demolition waste (C&DW) products within some countries’ construction industry.

Crop growth parameters are the basis for evaluation of crop growth status and crop yield. The aim of this study was to develop a more accurate estimation model for corn growth parameters combined with multispectral vegetation indexes (VIopt) and the differential radar information (DRI) derived from SAR data. Targeting the estimation of corn plant height (H) and the BBCH (Biologische Bundesanstalt, Bundessortenamt and CHemical industry) phenological parameters, this study compared the estimation accuracies of various multispectral vegetation indexes (VIopt) and the corresponding VIDRI (vegetation index corrected by DRI) indexes in inverting the corn growth parameters. (1) When comparing the estimation accuracies of four multispectral vegetation indexes (NDVI, NDVIre1, NDVIre2, and S2REP), NDVI showed the lowest estimation accuracy, with a normalized root mean square error (nRMSE) of 20.84% for the plant height, while S2REP showed the highest estimation accuracy (nRMSE = 16.05%). In addition, NDVIre2 (nRMSE = 16.18%) and S2REP (16.05%) exhibited a higher accuracy than NDVIre1 (nRMSE = 19.27%). Similarly, for BBCH, the nRMSEs of the four indexes were 24.17%, 22.49%, 17.04% and 16.60%, respectively. This confirmed that the multispectral vegetation indexes based on the red-edge bands were more sensitive to the growth parameters, especially for the Sentinel-2 red-edge 2 band. (2) The constructed VIDRI indexes were more beneficial than the VIopt indexes in enhancing the estimation accuracy of corn growth parameters. Specifically, the nRMSEs of the four VIDRI indexes (NDVIDRI, NDVIre1DRI, NDVIre2DRI, and S2REPDRI) decreased to 19.64%, 18.11%, 15.00%, and 14.64% for plant height, and to 23.24%, 21.58%, 15.79%, and 15.91% for BBCH, indicating that even in cases of high vegetation coverage, the introduction of SAR DRI features can further improve the estimation accuracy of growth parameters. Our findings also demonstrated that the NDVIre2DRI and S2REPDRI indexes constructed using red-edge 2 band information of Sentinel-2 and SAR DRI features had more advantages in improving the estimation accuracy of corn growth parameters.

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types.

The scheduling of tower crane operations is a complex process. Overlapping areas between tower cranes often lead to increased collision possibilities, resulting in additional tower crane operation complexity. Single objectives related to time or economic aspects were always considered in dealing with this issue, which neglected other objectives and the relationships between different objectives. Therefore, this article proposes a novel method for the schedule of prefabricated component lifting tasks on the construction site, integrating the multi-objective optimization model with the decision-making method with the aim of minimizing energy consumption costs and minimizing the amplitude of the costs among multiple tower cranes. A non-dominated sorting genetic algorithm-III (NSGA-III) written in Python is used as the multi-objective optimization algorithm—which considers the selection of tasks for each tower crane and the order of lifting for each tower crane and technique for order preference by similarity to an ideal solution (TOPSIS), and is applied as the decision-making method for ranking the Pareto front. Then, a green construction production and education integration training building construction project located in Jinan, China is used as the case study to verify that the method is practical and reasonable. The results show that conflicts can be effectively avoided, energy consumption costs reduced, and equipment utilization increased by rationally distributing lifting tasks among multiple overlapping tower cranes. And among the top 11 solutions, the lifting tasks and priorities for tower crane 1 are close to the same. In contrast, the task lifting for tower crane 2 was assigned based on the balance of the energy consumption costs of the two tower cranes. The discovery of this article is helpful to eliminate collisions, interference, and frequent start and stop of several tower cranes, so as to realize the safe, stable, and efficient operation of the construction site.

Developing effective strategies for the flexible control of fluid is vital for microfluidic electrochemical biosensing. In this study, a gigahertz (GHz) acoustic streaming (AS) based sonoelectrochemical system was developed to realize an on-chip surface modification and sensitive hydrogen peroxide (H2O2) detection from living cells. The flexible and controlled fluid surrounding the electrochemical chip was optimized theoretically and applied in the sonoelectrochemical deposition of Au nanoparticles (AuNPs) first. Under the steady and fast flow stimulus of AS, AuNPs could be synthesized with a smaller and evener size distribution than the normal condition, allowing AuNPs to show an excellent peroxidase-like activity. Moreover, the AS also accelerated the mass transport of target molecules and improved the catalytic rate, leading to the enhancement of H2O2 detection, with an extremely low detection limit of 32 nM and a high sensitivity of 4.34 μA/ (mM·mm2). Finally, this system was successfully applied in tracking H2O2 release from different cell lines to distinguish the cancer cells from normal cells. This study innovatively integrated the surface modification and molecules detection process on a chip, and also proposed a simple but sensitive platform for microfluidic biosensing application.

Phenylethanoid glycosides derived from Cistanche deserticola (PhGs) are plant-derived natural medicinal compounds that occur in many medicinal plants. This study aims to investigate whether PhGs treatment improves the stroke and its potential mechanisms. Adult male C57BL/6 J mice were administrated PhGs once daily for 7 days after MCAO surgery. The neurological score, and catwalk were evaluated on Day 1, 3 and 7 after ischemic stroke. Furthermore, triphenyl-2,3,5-tetrazoliumchloride (TTC) and hematoxylin-eosin (H&E) staining were used for evaluating the infarct volume and neuronal restoration. The effects of PhGs on NSCs proliferation were investigated in vitro and in vivo. Western blot was used to detect the proteins of Wnt/β-catenin signaling pathway. This study found that PhGs effectively improved the neurological functions in ischemic stroke mice. TTC and H&E staining demonstrated that PhGs not only reduced infarct volume, but also improved neuronal restoration. The immunohistochemistry and 5-Ethynyl-2-deoxyuridine (EdU) incorporation assays revealed that PhGs promoted the proliferation of neural stem cells (NSCs) in subventricular zone (SVZ). In addition, transcriptome analysis of NSCs showed that the Wnt/β-catenin signaling pathway was involved in the PhGs induced NSCs proliferation. Importantly, the related proteins in the Wnt/β-catenin signaling pathway were changed after PhGs treatment, including β-catenin, Wnt3a, GSK-3β, c-Myc. PhGs treatment improved the stroke through enhancing endogenous NSCs proliferation via activating Wnt/β-catenin signaling pathway. Due to its effect on the proliferation of NSCs, PhGs are a potential adjuvant therapeutic drug for post-stroke treatment.

Emerging evidence suggests that the Impostor Phenomenon (IP) among doctoral students is a serious problem worldwide academic. Although previous studies demonstrate that IP can endanger doctoral students’ academic advancement and psychological well-being, limited studies systematically and comprehensively explore the IP among those population. Thus, the fundamental goal of this study is to conduct a scoping review of IP among doctoral students so as to clarify the reality of their situation. Systematic searches were conducted using 5 databases: Springer, Google Scholar, Web of Science, PubMed, and JSTOR for empirical studies published from 1978 to 2023. Two reviewers independently carried out the literature search, study selection, data extraction and assessment of study; disagreements were resolved by a third reviewer. Thirty empirical studies covering four specific domains were include in current research, including the characteristics of IP among doctoral students, factors contributing to IP among doctoral students, correlation of IP with doctoral students’ mental illness, and measurement of IP. The findings of this study may provide insight to improving the comprehension of IP among doctoral students and establishing the groundwork for future research in this field.

Abstract Background Post-stroke depression (PSD) can be conceptualized as a complex network where PSD symptoms (PSDS) interact with each other. The neural mechanism of PSD and interactions among PSDS remain to be elucidated. This study aimed to investigate the neuroanatomical substrates of, as well as the interactions between, individual PSDS to better understand the pathogenesis of early-onset PSD. Methods A total of 861 first-ever stroke patients admitted within 7 days poststroke were consecutively recruited from three independent hospitals in China. Sociodemographic, clinical and neuroimaging data were collected upon admission. PSDS assessment with Hamilton Depression Rating Scale was performed at 2 weeks after stroke. Thirteen PSDS were included to develop a psychopathological network in which central symptoms (i.e. symptoms most strongly correlated with other PSDS) were identified. Voxel-based lesion-symptom mapping (VLSM) was performed to uncover the lesion locations associated with overall PSDS severity and severities of individual PSDS, in order to test the hypothesis that strategic lesion locations for central symptoms could significantly contribute to higher overall PSDS severity. Results Depressed mood, Psychiatric anxiety and Loss of interest in work and activities were identified as central PSDS at the early stage of stroke in our relatively stable PSDS network. Lesions in bilateral (especially the right) basal ganglia and capsular regions were found significantly associated with higher overall PSDS severity. Most of the above regions were also correlated with higher severities of 3 central PSDS. The other 10 PSDS could not be mapped to any certain brain region. Conclusions There are stable interactions among early-onset PSDS with Depressed mood, Psychiatric anxiety and Loss of interest as central symptoms. The strategic lesion locations for central symptoms may indirectly induce other PSDS via the symptom network, resulting in higher overall PSDS severity. Trial registration URL: http://www.chictr.org.cn/enIndex.aspx ; Unique identifier: ChiCTR-ROC-17013993.

Highlights 1. The optimum Fe:C (1:10) and dosage (10 g L−1) of the IMEPB were obtained. 2. The NRE and NRR increased by 11% and the Candidatus Brocadia increased by 20% in the anammox with adding IMEPB. 3. A novel biochar-based strategy was established for the anammox reinforcement.

Abstract Background Sarcopenia is common in patients with Parkinson's disease (PD), showing mitochondrial oxidative stress in skeletal muscle. The aggregation of α‐synuclein (α‐Syn) to induce oxidative stress is a key pathogenic process of PD; nevertheless, we know little about its potential role in regulating peripheral nerves and the function of the muscles they innervate. Methods To investigate the role of α‐Syn aggregation on neuromuscular system, we used the Thy1 promoter to overexpress human α‐Syn transgenic mice (mThy1‐hSNCA). hα‐Syn expression was evaluated by western blot, and its localization was determined by confocal microscopy. The impact of α‐Syn aggregation on the structure and function of skeletal muscle mitochondria and neuromuscular junctions (NMJs), as well as muscle mass and function were characterized by flow cytometry, transmission electron microscopy, Seahorse XF24 metabolic assay, and AAV9 in vivo injection. We assessed the regenerative effect of mitochondrial‐targeted superoxide dismutase (Mito‐TEMPO) after skeletal muscle injury in mThy1‐hSNCA mice. Results Overexpressed hα‐Syn protein localized in motor neuron axons and NMJs in muscle and formed aggregates. α‐Syn aggregation increased the number of abnormal mitochondrial in the intramuscular axons and NMJs by over 60% (P

It is generally thought that complement activation in human membranous nephropathy (MN) occurs predominantly via the lectin or alternative pathway. Here, the authors show that the classical pathway is the dominant form of complement activation in MN and a pathogenic driver of the disease.

Abstract Background Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors. Methods This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis. Results This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p