Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease.

Clinicians have long been interested in understanding the molecular basis of diabetic kidney disease (DKD)and its potential treatment targets. Its pathophysiology involves protein phosphorylation, one of the most recognizable post-transcriptional modifications, that can take part in many cellular functions and control different metabolic processes. In order to recognize the molecular and protein changes of DKD kidney, this study applied Tandem liquid chromatography-mass spectrometry (LC-MS/MS) and Next-Generation Sequencing, along with Tandem Mass Tags (TMT) labeling techniques to evaluate the mRNA, protein and modified phosphorylation sites between DKD mice and model ones. Based on Gene Ontology (GO) and KEGG pathway analyses of transcriptome and proteome, The molecular changes of DKD include accumulation of extracellular matrix, abnormally activated inflammatory microenvironment, oxidative stress and lipid metabolism disorders, leading to glomerulosclerosis and tubulointerstitial fibrosis. Oxidative stress has been emphasized as an important factor in DKD and progression to ESKD, which is directly related to podocyte injury, albuminuria and renal tubulointerstitial fibrosis. A histological study of phosphorylation further revealed that kinases were crucial. Three groups of studies have found that RAS signaling pathway, RAP1 signaling pathway, AMPK signaling pathway, PPAR signaling pathway and HIF-1 signaling pathway were crucial for the pathogenesis of DKD. Through this approach, it was discovered that targeting specific molecules, proteins, kinases and critical pathways could be a promising approach for treating DKD.

Rapid and Precise Differentiation and Authentication of Agricultural Products via Deep Learning-Assisted Multiplex SERS Fingerprinting.

Accurate and rapid differentiation and authentication of agricultural products based on their origin and quality are crucial to ensuring food safety and quality control. However, similar chemical compositions and complex matrices often hinder precise identification, particularly for adulterated samples. Herein, we propose a novel method combining multiplex surface-enhanced Raman scattering (SERS) fingerprinting with a one-dimensional convolutional neural network (1D-CNN), which enables the effective differentiation of the category, origin, and grade of agricultural products. This strategy leverages three different SERS-active nanoparticles as multiplex sensors, each tailored to selectively amplify the signals of preferentially adsorbed chemicals within the sample. By strategically combining SERS spectra from different NPs, a 'SERS super-fingerprint' is constructed, offering a more comprehensive representation of the characteristic information on agricultural products. Subsequently, utilizing a custom-designed 1D-CNN model for feature extraction from the 'super-fingerprint' significantly enhances the predictive accuracy for agricultural products. This strategy successfully identified various agricultural products and simulated adulterated samples with exceptional accuracy, reaching 97.7% and 94.8%, respectively. Notably, the entire identification process, encompassing sample preparation, SERS measurement, and deep learning analysis, takes only 35 min. This development of deep learning-assisted multiplex SERS fingerprinting establishes a rapid and reliable method for the identification and authentication of agricultural products.

Inhibition of tumor migration and invasion by fenofibrate via suppressing epithelial-mesenchymal transition in breast cancers.

The recurrence and metastasis in breast cancer within 3 years after the chemotherapies or surgery leads to poor prognosis with approximately 1-year overall survival. Large-scale scanning research studies have shown that taking lipid-lowering drugs may assist to reduce the risk of death from many cancers, since cholesterol in lipid rafts are essential for maintain integral membrane structure and functional signaling regulation. In this study, we examined five lipid-lowering drugs: swertiamarin, gemfibrozil, clofibrate, bezafibrate, and fenofibrate in triple-negative breast cancer, which is the most migration-prone subtype. Using human and murine triple-negative breast cancer cell lines (Hs 578 t and 4 T1), we found that fenofibrate displays the highest potential in inhibiting the colony formation, wound healing, and transwell migration. We further discovered that fenofibrate reduces the activity of pro-metastatic enzymes, matrix metalloproteinases (MMP)-9 and MMP-2. In addition, epithelial markers including E-cadherin and Zonula occludens-1 are increased, whereas mesenchymal markers including Snail, Twist and α-smooth muscle actin are attenuated. Furthermore, we found that fenofibrate downregulates ubiquitin-dependent GDF-15 degradation, which leads to enhanced GDF-15 expression that inhibits cell migration. Besides, nuclear translocation of FOXO1 is also upregulated by fenofibrate, which may responsible for GDF-15 expression. In summary, fenofibrate with anti-cancer ability hinders TNBC from migration and invasion, and may be beneficial to repurposing use of fenofibrate.

Characterization of alternative splicing events and prognostic signatures in gastric cancer.

BACKGROUND: Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation. METHODS: The expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted. RESULTS: In total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups. CONCLUSIONS: In this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment.

Macrophage RAGE deficiency prevents myocardial fibrosis by repressing autophagy-mediated macrophage alternative activation.

Myocardial fibrosis (MF) is the characteristic pathological feature of various cardiovascular diseases that lead to heart failure (HF) or even fatal outcomes. Alternatively, activated macrophages are involved in the development of fibrosis and tissue remodeling. Although the receptor for advanced glycation end products (RAGE) is involved in MF, its potential role in regulating macrophage function in cardiac fibrosis has not been fully investigated. We aimed to determine the role of macrophage RAGE in transverse aortic constriction (TAC)-induced MF. In this study, we found that RAGE expression was markedly increased in the infiltrated alternatively activated macrophages within mice hearts after TAC. RAGE knockout mice showed less infiltration of alternatively activated macrophages and attenuated cardiac hypertrophy and fibrosis compared to the wild-type mice. Our data suggest that mice with macrophage-specific genetic deletion of RAGE were protected from interstitial fibrosis and cardiac dysfunction when subjected to pressure overload, which led to a decreased proportion of alternatively activated macrophages in heart tissues. Our in vitro experiments demonstrated that RAGE deficiency inhibited the differentiation into alternatively activated macrophages by suppressing autophagy activation. In the co-culture system, in vitro polarization of RAW264.7 macrophages toward an alternatively activated phenotype stimulated the expression of α-smooth muscle actin and collagen in cardiac fibroblasts. However, the knockdown of RAGE and inhibition of autophagy in macrophages showed reduced fibroblast-to-myofibroblast transition (FMT). Collectively, our results suggest that RAGE plays an important role in the recruitment and activation of alternatively activated macrophages by regulating autophagy, which contributes to MF. Thus, blockage of RAGE signaling may be an attractive therapeutic target for the treatment of hypertensive heart disease.

Protective effects of paeonol against cognitive impairment in lung diseases.

Pulmonary inflammation may lead to neuroinflammation resulting in neurological dysfunction, and it is associated with a variety of acute and chronic lung diseases. Paeonol is a herbal phenolic compound with anti-inflammatory and anti-oxidative properties. The aim of this study is to understand the beneficial effects of paeonol on cognitive impairment, pulmonary inflammation and its underlying mechanisms. Pulmonary inflammation-associated cognitive deficit was observed in TNFα-stimulated mice, and paeonol mitigated the cognitive impairment by reducing the expressions of interleukin (IL)-1ß, IL-6, and NOD-like receptor family pyrin domain-containing 3 (NLRP3) in hippocampus. Moreover, elevated plasma miR-34c-5p in lung-inflamed mice was also reduced by paeonol. Pulmonary inflammation induced by intratracheal instillation of TNFα in mice resulted in immune cells infiltration in bronchoalveolar lavage fluid, pulmonary edema, and acute fibrosis, and these inflammatory responses were alleviated by paeonol orally. In MH-S alveolar macrophages, tumor necrosis factor (TNF) α- and phorbol myristate acetate (PMA)-induced inflammasome activation was ameliorated by paeonol. In addition, the expressions of antioxidants were elevated by paeonol, and reactive oxygen species production was reduced. In this study, paeonol demonstrates protective effects against cognitive deficits and pulmonary inflammation by exerting anti-inflammatory and anti-oxidative properties, suggesting a powerful benefit as a potential therapeutic agent.

Ancient DNA and multimethod dating confirm the late arrival of anatomically modern humans in southern China.

The expansion of anatomically modern humans (AMHs) from Africa around 65,000 to 45,000 y ago (ca. 65 to 45 ka) led to the establishment of present-day non-African populations. Some paleoanthropologists have argued that fossil discoveries from Huanglong, Zhiren, Luna, and Fuyan caves in southern China indicate one or more prior dispersals, perhaps as early as ca. 120 ka. We investigated the age of the human remains from three of these localities and two additional early AMH sites (Yangjiapo and Sanyou caves, Hubei) by combining ancient DNA (aDNA) analysis with a multimethod geological dating strategy. Although U-Th dating of capping flowstones suggested they lie within the range ca. 168 to 70 ka, analyses of aDNA and direct AMS 14C dating on human teeth from Fuyan and Yangjiapo caves showed they derive from the Holocene. OSL dating of sediments and AMS 14C analysis of mammal teeth and charcoal also demonstrated major discrepancies from the flowstone ages; the difference between them being an order of magnitude or more at most of these localities. Our work highlights the surprisingly complex depositional history recorded at these subtropical caves which involved one or more episodes of erosion and redeposition or intrusion as recently as the late Holocene. In light of our findings, the first appearance datum for AMHs in southern China should probably lie within the timeframe set by molecular data of ca. 50 to 45 ka.

A comprehensive study of Chuanwang Xiaoyan capsule based on characterization of chemical constituents in vitro and in vivo using ultra-high-performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry and pharmacokinetic study of multiple components in rats using ultra-high-performance liquid chromatography-triple quadrupole-tandem mass spectrometry.

Chuanwang Xiaoyan (CWXY) capsule is primarily used to treat a variety of acute and chronic inflammations, including acute and chronic pharyngitis and tonsillitis. However, a systematic study of its chemical constituents is still not available. This study evaluated the chemical constituents in vitro and metabolite profiles in vivo of CWXY using ultra-high-performance liquid chromatography (UHPLC) coupled with Q-Exactive Orbitrap mass spectrometry, and the pharmacokinetic behaviors of the nine main components in rats were detected using ultra-high-performance liquid chromatography-triple quadrupole-mass spectrometry (UPLC-QQQ-MS/MS). A total of 92 chemical constituents in CWXY were preliminarily identified in vitro. After oral administration to rats, 56 prototype components and 128 metabolites of CWXY were detected in the biological samples of rat plasma, urine, bile, and feces. Of these prototype components and metabolites, seven new compounds, namely M15, M16, M25, M30, M31, M71, and M128, were detected for the first time. The quantitation method of nine components in rat plasma was developed using a pharmacokinetic study. To the best of our knowledge, this study was the first to investigate the pharmacokinetic behavior of triumbelletin.

SeMet alleviates AFB1-induced oxidative stress and apoptosis in rabbit kidney by regulating Nrf2//Keap1/NQO1 and PI3K/AKT signaling pathways.

The purpose of this study was to explore the protective effect of SeMet on renal injury induced by AFB1 in rabbits and its molecular mechanism. Forty rabbits of 35 days old were randomly divided into control group, AFB1 group (0.3 mg AFB1/kg b.w), 0.2 mg/kg Se + AFB1 group (0.3 mg AFB1/kg b.w + 0.2 mg SeMet/kg feed) and 0.4 mg/kg Se + AFB1 group (0.3 mg AFB1/kg b.w + 0.4 mg SeMet/kg feed). The SeMet treatment group was fed different doses of SeMet diets every day for 21 days. On the 17-21 day, the AFB1 treatment group, the 0.2 mg/kg Se + AFB1 group and the 0.4 mg/kg Se + AFB1 group were administered 0.3 mg AFB1 /kg b.w by gavage (dissolved in 0.5 ml olive oil) respectively. The results showed that AFB1 poisoning resulted in the changes of renal structure, the increase of renal coefficient and serum biochemical indexes, the ascent of ROS and MDA levels, the descent of antioxidant enzyme activity, and the significant down-regulation of Nrf2, HO-1 and NQO1. Besides, AFB1 poisoning increased the number of renal apoptotic cells, rised the levels of PTEN, Bax, Caspase-3 and Caspase-9, and decreased the levels of PI3K, AKT, p-AKT and Bcl-2. In summary, SeMet was added to alleviate the oxidative stress injury and apoptosis of kidney induced by AFB1, and the effect of 0.2 mg/kg Se + AFB1 is better than 0.4 mg/kg Se + AFB1.

Molecular MR Imaging of Renal Fibrogenesis in Mice.

BACKGROUND: In most CKDs, lysyl oxidase oxidation of collagen forms allysine side chains, which then form stable crosslinks. We hypothesized that MRI with the allysine-targeted probe Gd-oxyamine (OA) could be used to measure this process and noninvasively detect renal fibrosis. METHODS: Two mouse models were used: hereditary nephritis in Col4a3-deficient mice (Alport model) and a glomerulonephritis model, nephrotoxic nephritis (NTN). MRI measured the difference in kidney relaxation rate, ΔR1, after intravenous Gd-OA administration. Renal tissue was collected for biochemical and histological analysis. RESULTS: ΔR1 was increased in the renal cortex of NTN mice and in both the cortex and the medulla of Alport mice. Ex vivo tissue analyses showed increased collagen and Gd-OA levels in fibrotic renal tissues and a high correlation between tissue collagen and ΔR1. CONCLUSIONS: Magnetic resonance imaging using Gd-OA is potentially a valuable tool for detecting and staging renal fibrogenesis.

High-Efficiency Photo-Fenton-like Catalyst of FeOOH/g-C3N4 for the Degradation of PNP: Characterization, Catalytic Performance and Mechanism Exploration.

The composite photocatalyst FeOOH/g-C3N4 was prepared through thermal polycondensation and co-precipitation methods, followed by XRD, SEM and UV-vis characterization. The stability of FeOOH/g-C3N4 was explored by the recycling test. The active species in the reaction system were investigated by the capture experiment. The results indicated that the optimal preparation condition for g-C3N4 involved calcination at 600 °C for 4 h. XRD analysis revealed that g-C3N4 exhibits a high-purity phase, and Fe in FeOOH/g-C3N4 exists in a highly dispersed amorphous state. SEM analysis showed that FeOOH/g-C3N4 has a rough surface with an irregular layered structure. Element composition analysis confirmed that the content of elements in the prepared catalyst is consistent with the theoretical calculation. FeOOH/g-C3N4 possesses the largest specific surface area of 143.2 m2/g and a suitable pore distribution. UV-vis DRS analysis showed that the absorption intensity of FeOOH/g-C3N4 is stronger than that of g-C3N4. When the catalyst dosage was 1.0 g/L, the H2O2 dosage was 4 mmol/L, the PNP initial concentration was 10 mg/L and the initial pH value was 5, the PNP removal could reach 92% in 120 min. Even after 5 cycles, the efficiency of PNP removal by FeOOH/g-C3N4 remains nearly 80%. The capture experiment indicated that both •OH and •O2- play roles in the photocatalytic degradation of PNP, with •OH being more significant. These findings affirm that FeOOH has been successfully incorporated into g-C3N4, resulting in a conspicuous catalytic effect on the degradation of PNP in the visible light-assisted Fenton-like reaction.

Developmental validation of a high-resolution panel genotyping 639 Y-chromosome SNP and InDel markers and its evolutionary features in Chinese populations.

Uniparental-inherited haploid genetic marker of Y-chromosome single nucleotide polymorphisms (Y-SNP) have the power to provide a deep understanding of the human evolutionary past, forensic pedigree, and bio-geographical ancestry information. Several international cross-continental or regional Y-panels instead of Y-whole sequencing have recently been developed to promote Y-tools in forensic practice. However, panels based on next-generation sequencing (NGS) explicitly developed for Chinese populations are insufficient to represent the Chinese Y-chromosome genetic diversity and complex population structures, especially for Chinese-predominant haplogroup O. We developed and validated a 639-plex panel including 633 Y-SNPs and 6 Y-Insertion/deletions, which covered 573 Y haplogroups on the Y-DNA haplogroup tree. In this panel, subgroups from haplogroup O accounted for 64.4% of total inferable haplogroups. We reported the sequencing metrics of 354 libraries sequenced with this panel, with the average sequencing depth among 226 individuals being 3,741×. We illuminated the high level of concordance, accuracy, reproducibility, and specificity of the 639-plex panel and found that 610 loci were genotyped with as little as 0.03 ng of genomic DNA in the sensitivity test. 94.05% of the 639 loci were detectable in male-female mixed DNA samples with a mix ratio of 1:500. Nearly all of the loci were genotyped correctly when no more than 25 ng/µL tannic acid, 20 ng/µL humic acid, or 37.5 µM hematin was added to the amplification mixture. More than 80% of genotypes were obtained from degraded DNA samples with a degradation index of 11.76. Individuals from the same pedigree shared identical genotypes in 11 male pedigrees. Finally, we presented the complex evolutionary history of 183 northern Chinese Hans and six other Chinese populations, and found multiple founding lineages that contributed to the northern Han Chinese gene pool. The 639-plex panel proved an efficient tool for Chinese paternal studies and forensic applications.

The formation of proto-austronesians: insights from a revised phylogeography of the paternal founder lineage.

OBJECTIVES: Previous studies suggested that the Y-chromosome haplogroups O2-N6-B451-AM01756 and O1a-M119 are two founder lineages of proto-Austronesians at about five thousand years ago. The objective of this study was to investigate the formation of proto-Austronesians from the perspective of the paternal gene pool. MATERIALS AND METHODS: In this study, we developed a highly evised phylogenetic tree with age estimates for haplogroup O2-N6 and early branches of O1a-M119 (M110, F1036, and F819). In addition, we also explored the geographical distribution of eight sub-branches of O2-N6 and O1a-M119, and spatial autocorrelation analysis was conducted for each sub-branch. RESULTS: The paternal lineage combination of proto-Austronesians is a small subset of a diverse gene pool of populations from the mainland of East Asia. The distribution map and results of the spatial autocorrelation analysis suggested that the eastern coastal region of northern China is likely the source of lineage O2-N6 while the coastal region of southeastern China is likely the diffusion center of early branches of O1a-M119. We developed an evolutionary diagram for Austronesians and their ancestors in the past 18,000 years. DISCUSSION: We proposed that the millet farming community in North China is the common ancestor group of the Austronesians and the Han people, while the diverse ancient people in the southeast coastal areas of East Asia form the common ancestor group of the Austronesians and the East Asian mainland population. The demographic history of multiple ancestral groups of the most recent common ancestor group itself in the more ancient period is helpful to understand the deep roots of the genetic components and cultural traditions of Austronesians.

Coordinated regulation of plant defense and autoimmunity by paired trihelix transcription factors ASR3/AITF1 in Arabidopsis.

Plants perceive pathogens and induce robust transcriptional reprogramming to rapidly achieve immunity. The mechanisms of how immune-related genes are transcriptionally regulated remain largely unknown. Previously, the trihelix transcriptional factor ARABIDOPSIS SH4-RELATED 3 (ASR3) was shown to negatively regulate pattern-triggered immunity (PTI) in Arabidopsis thaliana. Here, we identified another trihelix family member ASR3-Interacting Transcriptional Factor 1 (AITF1) as an interacting protein of ASR3. ASR3-Interacting Transcriptional Factor 1 and ASR3 form heterogenous and homogenous dimers in planta. Both aitf1 and asr3 single mutants exhibited increased resistance against the bacterial pathogen Pseudomonas syringae, but the double mutant showed reduced resistance, suggesting AITF1 and ASR3 interdependently regulate immune gene expression and resistance. Overexpression of AITF1 triggered autoimmunity dependently on its DNA-binding ability and the presence of ASR3. Notably, autoimmunity caused by overexpression of AITF1 was dependent on a TIR-NBS-LRR (TNL) protein suppressor of AITF1-induced autoimmunity 1 (SAA1), as well as enhanced disease susceptibility 1 (EDS1), the central regulator of TNL signaling. ASR3-Interacting Transcriptional Factor 1 and ASR3 directly activated SAA1 expression through binding to the GT-boxes in SAA1 promoter. Collectively, our results revealed a mechanism of trihelix transcription factor complex in regulating immune gene expression, thereby modulating plant disease resistance and autoimmunity.

Prevalence of bovine coronavirus in cattle in China: A systematic review and meta-analysis.

Bovine coronavirus (BCoV) is one of the important pathogens that cause calf diarrhea (CD), winter dysentery (WD), and the bovine respiratory disease complex (BRDC), and spreads worldwide. An infection of BCoV in cattle can lead to death of young animals, stunted growth, reduced milk production, and milk quality, thus bringing serious economic losses to the bovine industry. Therefore, it is necessary to prevent and control the spread of BCoV. Here, a systematic review and meta-analysis was conducted to assess the prevalence of BCoV in cattle in China before 2022. A total of 57 articles regarding the prevalence of BCoV in cattle in China were collected from five databases (PubMed, ScienceDirect, CNKI, VIP, and Wan Fang). Based on the inclusion criteria, a total of 15,838 samples were included, and 6,136 were positive cases. The overall prevalence of BCoV was 30.8%, with the highest prevalence rate (60.5%) identified in South China and the lowest prevalence (15.6%) identified in Central China. We also analyzed other subgroup information, included sampling years, sample sources, detection methods, breeding methods, age, type of cattle, presence of diarrhea, and geographic and climatic factors. The results indicated that BCoV was widely prevalent in China. Among all subgroups, the sample sources, detection methods, breeding methods, and presence or absence of diarrheal might be potential risk factors responsible for BCoV prevalence. It is recommended to strengthen the detection of BCoV in cattle, in order to effectively control the spread of BCoV.

Meta-analysis of the prevalence of Giardia duodenalis in sheep and goats in China.

Giardia duodenum (G. duodenalis) can cause giardiasis and infect a variety of hosts. So far, there have been no detailed data regarding the positive rate of G. duodenalis in sheep and goats in China. Here, a systematic literature review was carried out to investigate the epidemiology of G. duodenalis in sheep and goats in China. To perform the meta-analysis, the databases CNKI, VIP, WanFang, PubMed, Web of science and ScienceDirect were employed for screening studies related to the prevalence of G. duodenalis in sheep and goats in China. The total prevalence of G. duodenalis in sheep and goats was estimated to be 7.00% (95% CI: 4.00-10.00). In the age subgroup, the prevalence of G. duodenalis in sheep and goats of >12 months (11.29%; 95% CI: 8.08-14.97) was higher than that in sheep and goats of ≤12 months (7.57%; 95% CI: 3.95-12.24). An analysis based on seasons showed that the prevalence of G. duodenalis in sheep and goats was higher in summer (11.90%; 95% CI: 0.50-35.05) than that in other seasons. The prevalence of G. duodenalis in sheep and goats after 2016 was 8.57% (95% CI: 5.34-11.79), which was higher than others. The highest prevalence of G. duodenalis in sheep and goats was 13.06% (95% CI: 6.26-19.86) recorded in Southwestern China. The prevalence of Giardia infection in sheep (7.28%; 95% CI: 2.30-14.73) was higher than that in goats (5.43%; 95% CI: 2.73-8.98). The NOAA's National Center for Environmental Information (https://gis.ncdc.noaa.gov/maps/ncei/cdo/monthly) was used to extract relevant geoclimatic data (latitude, longitude, elevation, temperature, precipitation, humidity, and climate). By analyzing the data of each subgroup, it was shown that region, genetype, and climate were potential risk factors for giardiasis prevalence in sheep and goats. Based on the analysis of common factors and geographical factors, it is recommended to strengthen effective management measures (e.g. ventilation and disinfection in warm and humid areas) and formulate relevant policies according to local conditions. Breeders should strengthen the detection of G. duodenalis in sheep and goats, customize corresponding control measures according to the diet and living habits of sheep and goats, and strengthen the protection of sheep and lamb calves, so as to reduce the incidence rate and reduce the economic loss of China's animal husbandry.

Vaccination in children with congenital heart disease: an observational study in a Beijing hospital.

INTRODUCTION: Underimmunization of CHD children is a public health concern in China. This study aimed to analyze the vaccination status of CHD children to provide additional evidence on optimal vaccination strategies and to make suggestions to promote appropriate vaccination services for these children. METHODS: This cross-sectional study evaluated 155 CHD children who received at least one vaccine at Peking University First Hospital. Vaccine-specific immunization rates were calculated. A telephone questionnaire survey was conducted that covered the following: the prognosis, reasons for delayed vaccinations and getting vaccination in the hospital. All statistical analyses were performed using the SPSS version 22 software. RESULTS: The left-to-right shunt group involved 138 children, while the other type CHD group involved 17. The vaccination rate was the highest for MPSV-AC (87.1%) and the lowest for DTaP (40.1%). The most frequent reason for vaccination in the hospital was refusal from community health centers (61.5%). No participant reported vaccine-related adverse effects. CONCLUSIONS: The age-appropriate vaccine-specific immunization rates in CHD children are low, with the lowest for DTaP. Refusal of community health centers was the primary reason. Our findings support that clinically stable CHD children may be safely vaccinated on a schedule similar to that of ordinary children in China. IMPACT: From our investigation, we found that the age-appropriate vaccine-specific immunization rates in children with CHD in China are low, with the lowest for diphtheria and tetanus toxoid and acellular pertussis. Refusal of community health centers to vaccinate was the primary reason for the low rates. We believe our study provides additional evidence on optimal vaccination strategies for children with CHD and it can be used to develop strategies to promote appropriate vaccination services for these children.

Representation of time-varying and time-invariant EMR data and its application in modeling outcome prediction for heart failure patients.

OBJECTIVE: To represent a patient record with both time-invariant and time-varying features as a single vector using an end-to-end deep learning model, and further to predict the kidney failure (KF) status and mortality of heart failure (HF) patients. MATERIALS AND METHODS: The time-invariant EMR data included demographic information and comorbidities, and the time-varying EMR data were lab tests. We used a Transformer encoder module to represent the time-invariant data, and refined a long short-term memory (LSTM) with a Transformer encoder attached to the top to represent the time-varying data, taking the original measured values and their corresponding embedding vectors, masking vectors, and two types of time intervals as inputs. The proposed representations of patients with time-invariant and time-varying data were used to predict KF status (949 out of 5268 HF patients diagnosed with KF) and mortality (463 in-hospital deaths) for HF patients. Comparative experiments were conducted between the proposed model and some representative machine learning models. Ablation experiments were also performed around the time-varying data representation, including replacing the refined LSTM with the standard LSTM, GRU-D and T-LSTM, respectively, and removing the Transformer encoder and the time-varying data representation module, respectively. The visualization of the attention weights of the time-invariant and time-varying features was used to clinically interpret the predictive performance. We used the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), and the F1-score to evaluate the predictive performance of the models. RESULTS: The proposed model achieved superior performance, with average AUROCs, AUPRCs and F1-scores of 0.960, 0.610 and 0.759 for KF prediction and 0.937, 0.353 and 0.537 for mortality prediction, respectively. Predictive performance improved with the addition of time-varying data from longer time periods. The proposed model outperformed the comparison and ablation references in both prediction tasks. CONCLUSIONS: Both time-invariant and time-varying EMR data of patients could be efficiently represented by the proposed unified deep learning model, which shows higher performance in clinical prediction tasks. The way to use time-varying data in the current study is hopeful to be used in other kinds of time-varying data and other clinical tasks.

Identification of PDK4 as Hub Gene for Diabetic Nephropathy Using Co-Expression Network Analysis.

INTRODUCTION: Diabetic nephropathy (DN) is related to type 1 and type 2 diabetes. They are the leading cause of end-stage renal disease, but the underling specific pathogenesis of DN is not yet clear. Our study was conducted to explore how DN changed the transcriptome profiles in the kidney. METHODS: The gene expression profile of microdissected glomeruli of 41 type 2 DN patients and 20 healthy controls were included. The sample dataset GSE96804 was obtained from the GEO database. Differentially expressed genes (DEGs) were analyzed in R with the limma package and the important modules were found by weighted gene co-expression network analysis (WGCNA) clustering. The modules were then analyzed based on Gene Ontology (GO) gene set enrichment analysis, and the hub genes were found out. We next validated the hub gene, PDK4, in a cell model of DN. We also constructed the PDK4-related PPI network to investigate the correlation between PDK4 expression and other genes. RESULTS: Heatmap and volcano map were drawn to illustrate the mRNA expression profile of 1,204 DEGs in both samples of DN patients and the control group. Using WGCNA, we selected the blue module in which genes showed the strongest correlation with the phenotype and the smallest p value. We also identified PDK4 as a hub gene. PDK4 expression was upregulated in human diabetic kidney tissue. Moreover, PDK4 was speculated to play a role in glomerular basement membrane development and kidney development according to the enrichment of functions and signaling pathways. Furthermore, PDK4 and two key genes GSTA2 and G6PC protein expression were verified highly expressed in the cell model of DN. CONCLUSION: During the pathogenesis of DN, many genes may change expression in a coordinated manner. The discovery of PDK4 as key gene using WGCNA is of great significance for the development of new treatment strategies to block the development of DN.

Association between meteorological factors and COVID-19 transmission in low- and middle-income countries: A time-stratified case-crossover study.

BACKGROUND: Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs). OBJECTIVE: To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs. METHODS: We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model. RESULTS: There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI): 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI: 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites. CONCLUSION: Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.