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Abstract Aims Cardiac arrhythmia is a rising public health issue. The aim of this study was to determine the associations of atrial fibrillation (AF) and heart block with cardiovascular disease (CVD) incidence and all-cause mortality. Methods and results We included 141,362 participants (mean age [49.3], 80.9% men) from the Kailuan study. Arrhythmias were diagnosed through a 12-lead electrocardiograph (ECG). Mortality and CVD events were ascertained through multiple sources, including a municipal social insurance institution, hospital records, death certificates, and regular active follow-ups. During a median follow-up of 12.5 years, 18,301 total deaths and 13,208 cases of CVD were documented. The multivariable-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) comparing participants with AF to those without arrhythmia were 1.76 (1.61–1.93) for all-cause mortality, 2.11 (1.86–2.39) for CVD, 3.99 (3.33–4.79) for heart failure, and 1.56 (1.30–1.90) for stroke. Further, comparing participants with heart block to those without arrhythmia, the multivariable-adjusted HRs (95% CIs) were 1.31 (1.24–1.38) for all-cause mortality, 1.26 (1.18–1.35) for CVD, 1.40 (1.23–1.59) for heart failure, and 1.25 (1.15–1.37) for stroke. Additionally, there were generally stronger associations for AF and heart block with all-cause mortality and CVD in younger participants compared with their older counterparts (Ps-interaction ≤ 0.02) and a stronger association between AF and CVD in women compared with men (Ps-interaction ≤ 0.006). Conclusion AF and heart block were associated with a higher risk of subsequent adverse CVD events and mortality. Our findings highlight the importance of strategies for preventing cardiac arrhythmias to reduce the risk of CVD and mortality.

Abstract Soil biogenic components are subject to continuous sequestration, and export from soils into the surrounding air and water environments. However, the processes involving the stability or lability of their mineral states remain still unclear. To assess these issues, we have measured various biogenic components in a number of agricultural, forest, grassland, and deep soils, as well as desert sands from Inner Mongolia, both in the solid state and liquid extracts. The contents of soil organic carbon (SOC) and soil total nitrogen (STN) were higher in soils than in sands, whilst those of soil total sulfur (STS) and inorganic carbon were higher in sands and deeper soils. The significant positive correlations found between STS and SOC, and STN, and their significant negative correlations with pH and δ13C-SOC in all soils suggest a pH-dependent sequestration of C, N, and S. The decreased stability of organo-mineral complexes at acidic pH, resulting from the acidification of humic substance (HS) functionalities, leads to a higher availability of nutrients that facilitates the sequestration of soil organic matter (SOM). Conversely, an increase in pH enhances the stability of organo-mineral complexes by promoting negatively charged HS functionalities, which reduces the availability of nutrients and the sequestration of SOM. The δ13C-SOC enrichment in desert sands (-17.63 to -7.10‰) and its depleted values in soils (-24.9 to -18.8‰) suggest the occurrence of C sequestration in desert, via uptake of enriched atmospheric CO2 (-8.4‰). The fluorescence spectra of humic substance components and their molecular weights in sands were typically different from those of soils. The predominant relatively low molecular weight (MW) ( 25 − 15 kDa) of water-extracted (labile state: LS) components of all soils suggest, respectively, their involvement in organo-mineral complexes and for export into the surrounding environment. The quantities of LS and CS soil components differ significantly on dependence of soil characteristics, implying their corresponding lability or stability in soils. These findings will provide useful input for the management of the corresponding soil/sand ecosystems.

ObjectiveTo investigate the incidence, primary causes, and risk factors for unplanned readmissions within one year after the first primary total hip arthroplasty (THA) for osteonecrosis of the femoral head (ONFH).MethodsData were retrospectively collected from patients who had undergone the first primary THA for ONFH at two tertiary hospitals between January 2021 and December 2022, with complete 1-year follow-up assessments. Patients who experienced an unplanned readmission within 1 year were classified as the readmission group, while the others as the non-readmission group. The incidence rate and primary causes of unplanned readmission were determined, and the risk factors were identified through univariate and multivariate analyses.ResultsA total of 594 eligible patients were included, with 363 being men (61.1%) and an average age of 59.2 years at the time of surgery. Forty-seven patients were readmitted within one year, representing an accumulated rate of 7.9%. Among these, 18 (38.3%) readmissions occurred within 30 days and 27 (57.4%) within 90 days. The primary reasons for readmissions included hip dislocation (35.3%), followed by periprosthetic fracture, deep vein thrombosis, delayed incision healing, surgical site infection and others. The multivariate regression model revealed that age (every 10-year increment, OR, 1.39; 95% CI, 1.12–1.88), ARCO stage IV vs. Ⅲ (OR, 3.72; 95% CI, 1.96–7.22), CCI ≥4 vs.

Abstract Background Phosphorus plays a key role in plant adaptation to adversity and plays a positive role in the yield and quality formation of apples. Genes of the SPX domain-containing family are widely involved in the regulation of phosphorus signalling networks. However, the mechanisms controlling phosphorus deficiency are not completely understood in self-rooted apple stock. Results In this study, 26 members of the apple SPX gene family were identified by genome-wide analysis, and further divided into four subfamilies (SPX, SPX-MFS, SPX-EXS, and SPX-RING) based on their structural features. The chromosome distribution and gene duplications of MdSPXs were also examined. The promoter regions of MdSPXs were enriched for multiple biotic/abiotic stresses, hormone responses and typical P1BS-related elements. Analysis of the expression levels of 26 MdSPXs showed that some members were remarkably induced when subjected to low phosphate (Pi) stress, and in particular MdSPX2, MdSPX3, and MdPHO1.5 exhibited an intense response to low Pi stress. MdSPX2 and MdSPX3 showed significantly divergent expression levels in low Pi sensitive and insensitive apple species. Protein interaction networks were predicted for 26 MdSPX proteins. The interaction of MdPHR1 with MdSPX2, MdSPX3, MdSPX4, and MdSPX6 was demonstrated by yeast two-hybrid assay, suggesting that these proteins might be involved in the Pi-signaling pathway by interacting with MdPHR1. Conclusion This research improved the understanding of the apple SPX gene family and contribute to future biological studies of MdSPX genes in self-rooted apple stock.

Lung cancer, which is a leading cause of cancer-related deaths worldwide, frequently metastasizes to the bones, significantly diminishing patients’ quality of life and complicating treatment strategies. This study aims to develop an advanced 3D Mask R-CNN model, enhanced with the ConvNeXt-V2 backbone, for the automatic segmentation of bone tumors and identification of lung cancer metastasis to support personalized treatment planning. Data were collected from two hospitals: Center A (106 patients) and Center B (265 patients). The data from Center B were used for training, while Center A’s dataset served as an independent external validation set. High-resolution CT scans with 1 mm slice thickness and no inter-slice gaps were utilized, and the regions of interest (ROIs) were manually segmented and validated by two experienced radiologists. The 3D Mask R-CNN model achieved a Dice Similarity Coefficient (DSC) of 0.856, a sensitivity of 0.921, and a specificity of 0.961 on the training set. On the test set, it achieved a DSC of 0.849, a sensitivity of 0.911, and a specificity of 0.931. For the classification task, the model attained an AUC of 0.865, an accuracy of 0.866, a sensitivity of 0.875, and a specificity of 0.835 on the training set, while achieving an AUC of 0.842, an accuracy of 0.836, a sensitivity of 0.847, and a specificity of 0.819 on the test set. These results highlight the model’s potential in improving the accuracy of bone tumor segmentation and lung cancer metastasis detection, paving the way for enhanced diagnostic workflows and personalized treatment strategies in clinical oncology.

Yuanbaoshancha (YBSC) is characterized as a new wild tea relative morphologically and phytochemically distinguished from the closest wild tea plants Rongjiangcha (Camellia yungkiangensis, RJC) and Tulecha (Camellia costata, TLC). YBSC young leaves contain higher tea polyphenol and theobromine contents but lower caffeine and theanine as compared with RJC, TLC, and other tea landraces and modern cultivars. The major alkaloid detected in YBSC, TLC, and RJC is theobromine while caffeine is a minor; the primary catechins in YBSC leaves are non-galloylated catechins, significantly different from Camellia sinensis and other low-caffeine tea resources. The unique phytochemical profiles featured YBSC black tea with extremely lower caffeine and higher theobromine, as well as unique flavors and health benefits. This botanical characterization of YBSC and two related low-caffeine wild tea resources lays a foundation for future better utilization for the production of a highly valuable natural low-caffeine/high-theobromine tea. Chemical compounds: Caffeine (PubChem CID: 2519); Theobromine (PubChem CID: 5429); Catechins (PubChem CID: 9064); Epigallocatechin gallate (PubChem CID: 65064); Theanine (PubChem CID: 439378); Jasmone (PubChem CID: 1549018); cis-3-Hexenyl hexanoate (PubChem CID: 5352543); Hexyl 2-methylbutanoate (PubChem CID: 24838).

Abstract Background The association of longitudinal uric acid (UA) changes with cardiac conduction block risk is unclear. We aimed to identify the trajectories of UA and explore its association with cardiac conduction block. Methods A total of 67,095 participants with a mean age of 53.12 years were included from the Kailuan cohort in Tangshan, China, who were free of cardiac conduction block and with repeated measurements of UA from 2006 to 2012. UA trajectories during 2006 to 2012 were identified by group-based trajectory modeling. Cox proportional hazard regression models were used to assess the association of UA trajectories with cardiac conduction block. Results We categorized three observed discrete trajectories of UA during 2006–2012 period: low-stable, moderate-stable, and high-stable. Over a median follow-up of 6.19 years, we identified 1405 (2.09%) incident cardiac conduction block. Compared to those in the low-stable trajectory, the adjusted hazard ratios (HRs) (95% confidence interval [CI]) of cardiac conduction block in the moderate-stable and high-stable trajectory were 1.30 (1.16–1.47) and 1.86 (1.56–2.22), and HRs of atrioventricular block were 1.39 (1.12–1.72) and 2.90 (2.19–3.83), and HRs of bundle branch blocks were 1.27 (1.10–1.47) and 1.43 (1.13–1.79). Notably, although the average UA level in the moderate-stable UA trajectory group is within the normal range, the risk of cardiac conduction block has increased. Conclusions The moderate-stable and high-stable trajectories are associated with increased risk for new-onset cardiac conduction block. Monitoring UA trajectories may assist in identifying subpopulations at higher risk for cardiac conduction block.

Objective: This study aimed to assess the chemopreventive effect of ursodeoxycholic acid (UDCA) against COVID-19 and to analyze infection risk factors, symptoms, and recovery in outpatients with UDCA exposure.Methods: The study enrolled outpatients prescribed UDCA from the Second Affiliated Hospital of Chongqing Medical University, China, between 01 July 2022, and 31 December 2022. Data on demographics, comorbidities, and drug combinations were collected using electronic medical records. COVID-19 infection, symptoms, severity, prognosis, vaccinations, and UDCA administration were surveyed by telephone interviews. UDCA non-users served as controls and were matched in a 1:2 ratio with UDCA users using propensity score matching with the nearest neighbor algorithm. Infection rates, symptomatology, severity, and prognosis were compared between matched and control cohorts, and risk factors and infection and recovery symptoms were analyzed in UDCA-exposed outpatients.Results: UDCA-exposed outpatients (n = 778, 74.8%) and matched UDCA users (n = 95, 74.2%) showed significantly lower SARS-CoV-2 infection rates than control patients (n = 59, 92.2%) (p < 0.05). The matched UDCA group exhibited substantially lower fever, cough, sore throat, and fatigue rates than controls (p < 0.05). Participants with UDCA exposure generally experienced mild symptoms, while those without UDCA had moderate symptoms. The matched UDCA group also had significantly shorter durations of fever and cough (p < 0.05). Risk factors such as age over 60, less than 1 month of UDCA administration, diabetes mellitus, and coronary artery disease significantly increased SARS-CoV-2 infection rates (p < 0.05), while smoking led to a decrease (p < 0.05). Hypertension was associated with a prolonged COVID-19 recovery (p < 0.05), while smoking, vaccination, and fatty liver disease were associated with shorter recovery periods (p < 0.05). The main symptoms in the full UDCA cohort were fever, cough, and sore throat, with fatigue, cough, and hyposthenia being the most persistent.Conclusion: UDCA demonstrated chemopreventive effect against SARS-CoV-2 in outpatients by significantly reducing infection incidence and mitigating COVID-19 symptoms, severity, and recovery duration. Old age, short UDCA course, and comorbidities such as diabetes mellitus and CAD increased infection rates, while hypertension prolonged recovery. Smoking, vaccination, and fatty liver disease reduced infection rates and shortened recovery. UDCA had minimal impact on symptom types. Larger and longer-term clinical studies are needed further to assess UDCA’s effectiveness in COVID-19 prevention or treatment.

Background The Minqin Oasis, which is located in Wuwei City, Gansu Province, China, faces a very serious land desertification problem, with about 94.5% of its total area desertified. Accordingly, it is crucial to implement ecological restoration policies such as cropland abandonment in this region. In abandoned croplands, abiotic factors such as soil properties may become more important than biotic factors in driving vegetation succession. However, the connections between soil properties and vegetation succession remain unclear. To fill this knowledge gap, this study investigated these connections to explore major factors that affected vegetation succession, which is meaningful to designing management measures to restore these degraded ecosystems. Methods This study investigated seven 1–29-year-old abandoned croplands using the “space for time” method in Minqin Oasis. Vegetation succession was classified into different stages using a canonical correlation analysis (CCA) and two-way indicator species analysis (Twinspan). The link between soil properties and vegetation succession was analyzed using CCA. The primary factors shaping community patterns of vegetation succession were chosen by the “Forward selection” in CCA. The responses of dominant species to soil properties were analyzed using generalized additive models (GAMs). Results Dominant species turnover occurred obviously after cropland abandonment. Vegetation succession can be classified into three stages (i.e., early, intermediate, and late successional stages) with markedly different community composition and diversity. The main drivers of vegetation succession among soil properties were soil salinity and saturated soil water content and they had led to different responses of the dominant species in early and late successional stages. During the development of vegetation succession, community composition became simpler, and species diversity decreased significantly, which was a type of regressive succession. Therefore, measures should be adopted to manage these degraded, abandoned croplands.

Abstract The realization of compact and efficient broadband mid-infrared (MIR) lasers has enormous impacts in promoting MIR spectroscopy for various important applications. A number of well-designed waveguide platforms have been demonstrated for MIR supercontinuum and frequency comb generations based on cubic nonlinearities, but unfortunately third-order nonlinear response is inherently weak. Here, we propose and demonstrate for the first time a χ (2) micrometer waveguide platform based on birefringence phase matching for long-wavelength infrared (LWIR) laser generation with a high quantum efficiency. In a ZnGeP2-based waveguide platform, an octave-spanning spectrum covering 5–11 μm is generated through optical parametric generation (OPG). A quantum conversion efficiency of 74% as a new record in LWIR single-pass parametric processes is achieved. The threshold energy is measured as ~616 pJ, reduced by more than 1-order of magnitude as compared to those of MIR OPGs in bulk media. Our prototype micro-waveguide platform could be extended to other χ (2) birefringence crystals and trigger new frontiers of MIR integrated nonlinear photonics.

In this study, the inhibitory effect of rape bee pollen polyphenols on pancreatic lipase was measured by enzyme kinetics method, and the interaction between pancreatic lipase and rape bee pollen polyphenol extracts was analyzed by the ultravilolet, fluorescence spectra and synchronous fluorescence spectra. The results showed that rape bee pollen polyphenols had a certain inhibitory effect on the activity of pancreatic lipase, and the half maximal inhibitory concentration (IC50) was 1.670±0.045 mg/mL. The inhibitory type was a mixed inhibition of reversible inhibition. Fluorescence spectra showed that the maximal fluorescence intensity of pancreatic lipase gradually decreased with the increasing of rape bee pollen polyphenols concentration, and the maximal fluorescence peak had a redshift from 341 nm to 349 nm. Synchronous fluorescence spectra showed that the hydrophobicity inside the enzyme decreased and the stretch of the peptide chain increased when polyphenols bind to pancreatic lipase. The fluorescence quenching mechanism showed that the quenching constant decreased from 0.1000 to 0.0743 with increasing temperature, and the binding process was static quenching with about one binding site. In conclusion, the rape bee pollen polyphenols could inhibit the pancreatic lipase activity by changing the enzyme conformation, which provided a certain theoretical basis for the mechanism of bee pollen lipid reduction.

Abstract Background Punica granatum is a fundamentally important fruit tree that has important economic, medicinal and ornamental properties. At present, there are few reports on the mitochondrial genome of pomegranate. Hence, in this study the P. granatum mitogenome was sequenced and assembled to further understanding of organization, variation, and evolution of mitogenomes of this tree species. Results The genome structure was multi-chromosomes with seven circular contigs, measuring 382,774 bp in length with a 45.91% GC content. It contained 74 genes, including 46 protein-coding genes, 25 tRNA genes, and three rRNA genes. There were 188 pairs of dispersed repeats with lengths of 30 or greater, primarily consisting of reverse complementary repeats. The mitogenome analysis identified 114SSRs and 466 RNA editing sites. Analyses of codon usage, nucleotide diversity and gene migration from chloroplast to mitochondrial were also conducted. The collinear and comparative analysis of mitochondrial structures between P. granatum and its proximal species indicated that P. granatum ‘Taishanhong’ was closely related to P. granatum ‘Qingpitian’ and Lagerstroemia indica. Phylogenetic examination based on the mitogenome also confirmed the evolutionary relationship. Conclusion The results offered crucial information on the evolutionary biology of pomegranate and highlighted ways to promote the utilization of the species’ germplasm.

Objective To explore the value of immunoglobulin in differential diagnosis of primary biliary cholangitis (PBC), hepatitis E and liver cirrhosis. Methods Blood samples were collected from 121 patients with PBC and 107 healthy people. The serum r-glutamyltransferase (r-GT), alkaline phosphatase (ALP), immunoglobulin IgG and IgM, total cholesterol (TCH) and lipoprotein (a)[Lp(a)] were detected by biochemical routine tests; Blood routine counted white blood cells (WBC) and platelets (PC); The IgG and IgM antibodies of HEV were detected by enzyme-linked immunosorbent assay (ELISA). Results r-GT, ALP, IgG and IgM in PBC patients increased significantly (P＜0.05) accompanied by significant decrease in WBC and PC values (P＜0.05). In patients with PBC cirrhosis, IgG increased significantly (P＜0.05), while WBC and PC values decreased significantly(P＜0.05). IgG and IgM in patients with PBC+cirrhosis+HEV antibody positive increased significantly(P＜0.05), while WBC and PC values decreased significantly (P＜0.05). Conclusions The increase of IgG and IgM might be used as diagnostic markers for the development of cirrhosis in PBC patients with HEV infection.

Summary: Background: The epidemiological features of the Klebsiella pneumoniae causing bloodstream infections in Hong Kong and their potential threats to human health remained unknown. Methods: K. pneumoniae strains collected from four hospitals in Hong Kong during the period of 2009–2018 were subjected to molecular typing, string test, antimicrobial susceptibility testing, whole genome sequencing and analysis. Clinical data of patients from whom these strains were isolated were analyzed retrospectively using univariate and multivariate logistic regression approaches. Findings: The 240 Klebsiella spp. strains belonged to 123 different STs and 63 different capsule loci (KLs), with KL1 and KL2 being the major type. 86 out of 212 BSI-KP (40.6%) carried at least one of the virulence genes iuc, iro, rmpA or rmpA2. Virulence plasmid correlated well with the string test positive result, yet 8 strains without rmp genes were also hypermucoviscous, which was due to wzc mutation. The mortality rate of bloodstream infection patients was 43.0%. Univariant analysis showed that factors including renal replacement therapy (FDR adjusted p = 0.0007), mechanical ventilation (FDR adjusted p

BackgroundThe level at which cumulative blood pressure (BP) can increase the risk of ASCVD in different age groups remains unclear. This study aimed to investigate the association of 10-year cumulative BP levels with the long-term risk of ASCVD of different age groups.MethodsCumulative BP exposure was assessed using the time-weighted average (TWA) BP divided into four BP groups. The participants were also divided into four groups according to their baseline age (

Abstract Mammalian endogenous retroviruses (ERVs) are ancient retroviruses that have been integrated into genomes. ERVs were believed to be inactive until the discovery of ERV transcription in the mouse genome. However, the transcription level and function of ERV elements in mammalian genomes are not well understood. In this study, we performed the first genome‐wide scanning of ERV loci in the American mink (Neogale vison) genome (NeoERV) followed by transcriptomic analysis to detect actively transcribed NeoERV elements. A total of 365,791 NeoERV loci were identified, and161,205 (44%) of these loci were found to be actively transcribed based on transcriptomic data from three types of tissues (amygdala, trachea and lung). More than one third of the actively transcribed NeoERV loci were tissue‐specific. Furthermore, some of the active loci were associated with host gene transcription, and the level of NeoERV transcription was positively correlated with that of host genes, specifically when active loci were located in overlapped gene regions. An in‐depth analysis of the envelope protein coding env gene showed that, in general, its transcription level was higher than that of NeoERVs, which is believed to be associated with host immunity.

In this paper, three Pd-coated Cu (PCC) wires with different Pd-layer thicknesses were used to make bonding samples, and the influence of Pd-layer thickness on the reliability of bonded points before and after a high-temperature storage test was studied. The results show that smaller bonding pressure and ultrasonic power lead to insufficient plastic deformation of the ball-bonded point, which also leads to small contact area with the pad and low bonding strength. Excessive bonding pressure and ultrasonic power will lead to ‘scratch’ on the surface of the pad and large-scale Ag spatter. The wedge-bonded point has a narrowed width when the bonding pressure and ultrasonic power are too small, and the tail edge will be cocked, resulting in false bonding and low strength. When the bonding pressure or ultrasonic power is too large, it will cause stress concentration, and the pad will appear as an ‘internal injury’, which will improve the failure probability; a high-temperature environment can make Cu-Ag intermetallic compounds (IMCs) grow and improve the bonding strength. With the extension of high-temperature storage time, the shear force of Pd100 gradually reaches the peak and then decreases, due to Kirkendall pores caused by excessive growth of IMCs, while the shear force of Pd120 continued to increase due to the slow growth rate of IMCs. In the high-temperature storage test, the thicker the Pd layer of the bonding wire, the higher the bonding strength; in the cold/hot cycle test, the sample with the largest Pd-layer thickness has the lowest failure rate. The thicker the Pd layer, the stronger its ability to resist changes in the external environment, and the higher its stability and reliability.

Hydrogen has the potential to serve as a new energy resource, reducing greenhouse gas emissions that contribute to climate change. Natural hydrogenases exhibit impressive catalytic abilities for hydrogen production, but they often lack oxygen tolerance. Oxygen-tolerant hydrogenases can work under oxygen by reacting with oxygen to form inactive states, which can be reactivated to catalytic states by oxygen atom removal. Herein, we synthesized three NiFeSe complexes: (NiSe(CH3)FeCp, NiSe(CH3)FeCp* and NiSe(PhNMe2)FeCp) with features of active sites of [NiFeSe]-H2ases, which are the oxygen-tolerant hydrogenases, and we investigated the influence of electronic and steric factors on the oxygen reaction of these “biomimetic” complexes. In our research, we found that they react with oxygen, forming 1-oxygen species, which is related to the O2-damaged [NiFeSe] active site. Through a comparative analysis of oxygen reactions, we have discovered that electronic factors and steric hindrance on Se play a significant role in determining the oxygen reactivity of NiFe complexes related to hydrogenases’ active sites.

Variations in host traits that influence their exposure and susceptibility may impact probability of vector-transmitted diseases. Therefore, identifying the predictors of infection probability is necessary to understand the risk of disease outbreaks during expanding environmental perturbation. Here, we conducted a large survey based on microscopic examination and molecular analysis of haemosporidian parasite infection in raptors rescued at the Beijing Raptor Rescue Centre. Combining these data with biological and ecological variables of the raptors, we determined predictors that affect the probability of haemosporidian infection using generalized linear mixed models and multimodel inference. Our results showed that infection probability exhibited considerable variation across host species in raptors, and body mass, sex, and evolutionary history played relatively weaker roles in driving infection probability. Instead, activity pattern, age, geographic range size, migration distance, and nest type were important predictors of the probability of haemosporidian infection, and the role of each predictor differed in the three main haemosporidian genera (Plasmodium, Haemoproteus, and Leucocytozoon). This macro-ecological analysis will add to our understanding of host traits that influence the probability of avian haemosporidian infection and will help inform risk of emerging diseases.

Due to the low-cost fabrication, printing electronics on flexible substrates shows great potential in robotics, wearable healthcare, and persistent human-machine interfaces. Noninvasive dry-electrodes for electrocardiography (ECG) monitoring are an important technique for detecting early arrhythmias. This article describes a screen printing method for fabricating textile ECG electrodes. The biocompatible carbon ink served as the active electrochemical layer, while the silver paste acted as the conductive path, respectively. The measured results showed that the textile electrode had similar ECG signal monitoring performance compared to commercially available Ag/AgCl electrodes under conditions where the subjects were walking, stationary, and jogging. And the pre-made textile electrodes can be easily connected to the sports bra for monitoring daily exercise ECG. This study demonstrated the feasibility of utilizing textile electrodes for applications in the wearable healthcare industry.

Study region: Upper Shiyang River in the eastern Qilian Mountains, China. Study focus: Quantifying the impacts of anthropogenic and climate change on wet and dry hydrological variability was done by improving the Slope Change Ratio of Cumulative Quantities (ISCRCQ) method. New hydrological insights for the region: The scientific method is critical to quantify the driving factors of dry-wet hydrological changes. In this study, the slope change ratio of cumulative quantity (SCRCQ) method was improved to quantify the impacts of human activities and climate change on dry-wet hydrological changes. The results show a hydrological aridification trend at an annual scale from 1961 to 2016 in the upper reaches of the Shiyang River. However, the dry-wet hydrological change trends of the six tributaries differed: the hydrological humidification of the four western tributaries was apparent, while the remaining tributaries showed hydrological aridification. The influences of human activities and climate change on dry-wet hydrological changes were also evidently distinct in the different tributaries. Changing in climate is a vital factor triggering the dry-wet hydrological changes in the western tributaries, while human activities have completely changed the direction of the dry-wet hydrological changes and intensified the hydrological aridification in the eastern tributaries. Human activities have resulted in an increase both in the frequency of droughts and in the risk of socio-economic droughts. Thus, human activities in the region of eastern tributaries should be controlled within reasonable limits.

ABSTRACTAlthough previous studies have reported the dysregulation of respiratory tract microbiota in infectious diseases, insufficient data exist regarding respiratory microbiota imbalances in the lower respiratory tracts (LRTs) of children with Mycoplasma pneumoniae pneumonia (MPP). Here, we analysed the microbial community using 16S rRNA gene sequencing. Finally, bronchoalveolar lavage fluid (BALF) samples from 158 children with MPP and 29 with bacterial or viral pneumonia (control group) were collected. The diversity of the microbial community was significantly different between the two groups. A significantly increased abundance of Tenericutes and Mycoplasma was detected in the MPP group, exceeding 67% and 65% of the total bacterial population, respectively. Using Mycoplasma abundance as the diagnostic method, the sensitivity and specificity of the model was 97.5% and 96.6%, respectively. Compared to the mild MPP group, lower alpha diversity and significantly increased Mycoplasma abundance were found in the severe MPP group (P

BackgroundSchizophrenia is a serious mental disease. With increased research funding for this disease, schizophrenia has become one of the key areas of focus in the medical field. Searching for associations between diseases and genes is an effective approach to study complex diseases, which may enhance research on schizophrenia pathology and lead to the identification of new treatment targets. ObjectiveThe aim of this study was to identify potential schizophrenia risk genes by employing machine learning methods to extract topological characteristics of proteins and their functional roles in a protein-protein interaction (PPI)-keywords (PPIK) network and understand the complex disease–causing property. Consequently, a PPIK-based metagraph representation approach is proposed. MethodsTo enrich the PPI network, we integrated keywords describing protein properties and constructed a PPIK network. We extracted features that describe the topology of this network through metagraphs. We further transformed these metagraphs into vectors and represented proteins with a series of vectors. We then trained and optimized our model using random forest (RF), extreme gradient boosting, light gradient boosting machine, and logistic regression models. ResultsComprehensive experiments demonstrated the good performance of our proposed method with an area under the receiver operating characteristic curve (AUC) value between 0.72 and 0.76. Our model also outperformed baseline methods for overall disease protein prediction, including the random walk with restart, average commute time, and Katz models. Compared with the PPI network constructed from the baseline models, complementation of keywords in the PPIK network improved the performance (AUC) by 0.08 on average, and the metagraph-based method improved the AUC by 0.30 on average compared with that of the baseline methods. According to the comprehensive performance of the four models, RF was selected as the best model for disease protein prediction, with precision, recall, F1-score, and AUC values of 0.76, 0.73, 0.72, and 0.76, respectively. We transformed these proteins to their encoding gene IDs and identified the top 20 genes as the most probable schizophrenia-risk genes, including the EYA3, CNTN4, HSPA8, LRRK2, and AFP genes. We further validated these outcomes against metagraph features and evidence from the literature, performed a features analysis, and exploited evidence from the literature to interpret the correlation between the predicted genes and diseases. ConclusionsThe metagraph representation based on the PPIK network framework was found to be effective for potential schizophrenia risk genes identification. The results are quite reliable as evidence can be found in the literature to support our prediction. Our approach can provide more biological insights into the pathogenesis of schizophrenia.

Abstract Ferric ions can bind strongly with dissolved organic matter (DOM), including humic acids (HA), fulvic acids (FA), and protein-like substances, whereas isolation of Fe-DOM precipitates (Fe-DOMP) and their biochemical characteristics remain unclear. In this work FeCl3 was used to isolate DOM components from various sources, including river, lake, soil, cow dung, and standard tryptophan and tyrosine, through precipitation at pH 7.5–8.5. The Fe-DOMP contribute to total DOM by approximately 38.6–93.8% of FA, 76.2% of HA and 25.0–30.4% of tryptophan and tyrosine, whilst fluorescence spectra allowed to monitor/discriminate the various DOM fractions in the samples. The relative intensity of the main infrared peaks such as 3406‒3383 cm−1 (aromatic OH), 1689‒1635 cm−1 (‒COOH), 1523–1504 cm−1 (amide) and 1176–1033 cm−1 (‒S=O) show either to decline or disappear in Fe‒DOMP. These results suggest the occurrence of Fe bonds with various functional groups of DOM, indicating the formation of π–d electron bonding systems of different strengths in Fe‒DOMP. The novel method used for isolation of Fe-DOMP shows promising in opening a new frontier both at laboratory and industrial purposes. Furthermore, results obtained may provide a better understanding of metal–organic complexes involved in the regulation of the long-term stabilization/sequestration of DOM in soils and waters.

Abstract Background OXA-232-producing Klebsiella pneumoniae was first identified in China in 2016, and its clonal transmission was reported in 2019. However, there are no prevalence and genotypic surveillance data available for OXA-232 in China. Therefore, we investigated the trends and characteristics of OXA-232 type carbapenemase in Zhejiang Province, China from 2018 to 2021. Methods A total of 3278 samples from 1666 patients in the intensive care units were collected from hospitals in Zhejiang Province from 2018 to 2021. Carbapenem-resistant isolates were initially selected by China Blue agar plates supplemented with 0.3 μg/ml meropenem, and further analyzed by matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry identification, immune colloidal gold technique, conjugation experiment, antimicrobial susceptibility testing and whole genome sequencing. Results A total of 79 OXA-producing strains were recovered, with the prevalence increased from 1.8% [95% confidence interval (CI): 0.7–3.7%] in 2018 to 6.0% (95% CI: 4.4–7.9%) in 2021. Seventy-eight strains produced OXA-232 and one produced OXA-181. The bla OXA-232 gene in all strains was located in a 6141-bp ColKP3-type non-conjugative plasmid and the bla OXA-181 gene was located in a 51,391-bp ColKP3/IncX3-type non-conjugative plasmid. The bla OXA-232-producing K. pneumoniae was dominated (75/76) by isolates of sequence type 15 (ST15) that differed by less than 80 SNPs. All OXA-producing strains (100%, 95% CI: 95.4–100.0%) were multidrug-resistant. Conclusions From 2018 to 2021, OXA-232 is the most prevalent OXA-48-like derivative in Zhejiang Province, and ST15 K. pneumoniae isolates belonging to the same clone are the major carriers. The transmission of ColKP3-type plasmid to E. coli highlighted that understanding the transmission mechanism is of great importance to delay or arrest the propagation of OXA-232 to other species.

Abstract Objective To explore changes in the epidemiological and clinical characteristics of patients who underwent knee arthroplasty (KA) over a 10-year period in China. Methods Medical records of patients with knee osteoarthritis (KOA), who underwent primary unilateral KA in 5 level I center hospitals in China between January 2011 and December 2020, were retrospectively reviewed and analyzed. To more clearly define changes over the years, patients were divided into two groups according to time of admission at 5-year intervals. Age, sex, body mass index (BMI), Kellgren–Lawrence (K–L) classification, comorbid diseases, surgical procedures, hospital stay, and hospitalization costs were compared between the two groups. Results A total of 23,610 patients with KOA (5400 male and 18,210 females; mean age: 65.7 ± 7.6 years) who underwent primary unilateral KA were included. The number of KAs increased in recent years (group A, n = 7606 vs. group B, n = 16,004). Significant differences were noted in age, sex, BMI, K–L classification, comorbidities, surgical procedures, hospital stay, and hospitalization costs between the two periods (P

The epidemiological features of the newly emerged carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-HvKP) and its potential threat to human health are currently unknown. In this study, a total of 784 blaKPC-2-bearing CRKP strains collected from three hospitals located at different geographical locales in China during 2014–2017 were subjected to molecular typing, screening of virulence plasmid, string test and WGS (367/784 strains). The proportion of CRKP among all clinical K. pneumoniae strains increased sharply in China during 2014–2017. A large proportion (58%) of these CRKP strains were found to harbour a virulence-encoding plasmid, while only 13% of such strains exhibited a hypervirulent phenotype by string test and neutrophil assay. The lack of hypervirulent phenotype in virulent plasmid-bearing CRKP strains was found to be due to the mutation’s presence on rmpA and rmpA2 genes, which rendered them non-functional, while some strains carrying wild type rmpA did not exhibit hypervirulent phenotype either suggesting that other factors might also contribute to the hypervirulence of CRKP. Phylogenetic and SNP analysis indicated that the transmission of these CRKP strains in China likely involved several major clones of ST11. Carriage of IncFII pSWU01-like, blaKPC-2-bearing plasmid was found to be the major mechanism of carbapenem resistance in these CRKP strains. In conclusion, our data indicated that the prevalence of CRKP strains carrying the virulence plasmid has rapidly increased in China, while genetic markers were not correlated well with the hypervirulent phenotypes, which call for a better definition and screening for these truly hypervirulent CR-HvKP strains in clinical settings.

ABSTRACT In this work, we collected foodborne Salmonella strains in Shenzhen, China, during 2014–2017 and investigated the genetic profile of all cefotaxime-resistant isolates in the collection. The strains were subjected to antimicrobial susceptibility tests, whole-genome sequencing, bioinformatics analysis, and conjugation studies. A total of 79 cefotaxime-resistant Salmonella were identified and found to exhibit multidrug resistance. Resistance rate recorded during the study period increased from 1.9% to 9.1%. Salmonella Typhimurium was the predominant serovar, and CTX-M family genes were dominant among the ESBLs genes detected. Notably, CTX-M-bearing plasmids or transposons often contain other drug resistance genes. Furthermore, a combination of CTX-M-55 and CTX-M-65 genes was detected for the first time in foodborne Salmonella strains. Our findings reveal the prevalence and molecular characteristics of cefotaxime-resistant foodborne Salmonella strains in southern China. IMPORTANCE Cefotaxime-resistant Salmonella strains pose an increasing threat to human health by causing infections with limited treatment options. It is therefore necessary to undertake a surveillance on the prevalence of such strains and investigate the resistance and transmission mechanisms. In this work, various ESBL genes flanked by different IS located in different mobile genetic elements were detectable among cefotaxime-resistant Salmonella strains. These data show that the high prevalence and genotypic diversity of cefotaxime-resistant foodborne Salmonella strains in China are possibly attributed to the evolution and transmission of a wide range of multidrug resistance-encoding mobile genetic elements.

BackgroundGiven the threat posed by cancer to human health, there is a rapid growth in the volume of data in the cancer field and interdisciplinary and collaborative research is becoming increasingly important for fine-grained classification. The low-resolution classifier of reported studies at the journal level fails to satisfy advanced searching demands, and a single label does not adequately characterize the literature originated from interdisciplinary research results. There is thus a need to establish a multilabel classifier with higher resolution to support literature retrieval for cancer research and reduce the burden of screening papers for clinical relevance. ObjectiveThe primary objective of this research was to address the low-resolution issue of cancer literature classification due to the ambiguity of the existing journal-level classifier in order to support gaining high-relevance evidence for clinical consideration and all-sided results for literature retrieval. MethodsWe trained a multilabel classifier with scalability for classifying the literature on cancer research directly at the publication level to assign proper content-derived labels based on the “Bidirectional Encoder Representation from Transformers (BERT) + X” model and obtain the best option for X. First, a corpus of 70,599 cancer publications retrieved from the Dimensions database was divided into a training and a testing set in a ratio of 7:3. Second, using the classification terminology of International Cancer Research Partnership cancer types, we compared the performance of classifiers developed using BERT and 5 classical deep learning models, such as the text recurrent neural network (TextRNN) and FastText, followed by metrics analysis. ResultsAfter comparing various combined deep learning models, we obtained a classifier based on the optimal combination “BERT + TextRNN,” with a precision of 93.09%, a recall of 87.75%, and an F1-score of 90.34%. Moreover, we quantified the distinctive characteristics in the text structure and multilabel distribution in order to generalize the model to other fields with similar characteristics. ConclusionsThe “BERT + TextRNN” model was trained for high-resolution classification of cancer literature at the publication level to support accurate retrieval and academic statistics. The model automatically assigns 1 or more labels to each cancer paper, as required. Quantitative comparison verified that the “BERT + TextRNN” model is the best fit for multilabel classification of cancer literature compared to other models. More data from diverse fields will be collected to testify the scalability and extensibility of the proposed model in the future.

BackgroundThe normalization of institution names is of great importance for literature retrieval, statistics of academic achievements, and evaluation of the competitiveness of research institutions. Differences in authors’ writing habits and spelling mistakes lead to various names of institutions, which affects the analysis of publication data. With the development of deep learning models and the increasing maturity of natural language processing methods, training a deep learning–based institution name normalization model can increase the accuracy of institution name normalization at the semantic level. ObjectiveThis study aimed to train a deep learning–based model for institution name normalization based on the feature fusion of affiliation data from multisource literature, which would realize the normalization of institution name variants with the help of authority files and achieve a high specification accuracy after several rounds of training and optimization. MethodsIn this study, an institution name normalization–oriented model was trained based on bidirectional encoder representations from transformers (BERT) and other deep learning models, including the institution classification model, institutional hierarchical relation extraction model, and institution matching and merging model. The model was then trained to automatically learn institutional features by pretraining and fine-tuning, and institution names were extracted from the affiliation data of 3 databases to complete the normalization process: Dimensions, Web of Science, and Scopus. ResultsIt was found that the trained model could achieve at least 3 functions. First, the model could identify the institution name that is consistent with the authority files and associate the name with the files through the unique institution ID. Second, it could identify the nonstandard institution name variants, such as singular forms, plural changes, and abbreviations, and update the authority files. Third, it could identify the unregistered institutions and add them to the authority files, so that when the institution appeared again, the model could identify and regard it as a registered institution. Moreover, the test results showed that the accuracy of the normalization model reached 93.79%, indicating the promising performance of the model for the normalization of institution names. ConclusionsThe deep learning–based institution name normalization model trained in this study exhibited high accuracy. Therefore, it could be widely applied in the evaluation of the competitiveness of research institutions, analysis of research fields of institutions, and construction of interinstitutional cooperation networks, among others, showing high application value.

Geological hazard susceptibility assessment is an important basis for territorial space planning and geological hazard prevention and mitigation. In order to explore the evaluation method suitable for the geological hazard susceptibility of low hills and gullies in Yunnan plateau, Wuhua District of Kunming, Yunnan Province, China was selected as a typical study area. Eight factors including the engineering geology groups, distance from faults, elevation, slope, direction, curvature, distance from roads and land use covers were selected, and the weight evidence method based on Bayesian theory was applied to evaluate the susceptibility of geological hazards. After performing the Student-T test of the comprehensive evidence weight of each factor, the classification scheme of factors were optimized. The results of vulnerability zoning based on the evaluation of the model established in this paper showed that 89.9% and 9.1% of the geological hazard points fall into high and medium susceptibility areas. The comparative analysis showed that the modeling results are highly consistent with the geological hazards distribution, which better reveals the characteristics of geological hazards susceptibility in the study area. It can provide reference for the planning of geological hazards prevention in Wuhua District and other low hills and gullies areas of Yunnan plateau.

Background: Hair follicle development is important for the fineness of wool. Our previous methylated DNA immunoprecipitation sequencing showed that IGFBP2 and IGFBP4 were differentially methylated at different development stages of the hair follicle of Super Merino sheep. This study selected these two genes as candidates to uncover the influence of their promoter methylation on hair follicle development. Results: The results showed that the expression levels of IGFBP2 and IGFBP4 in the skin of very fine wool Super Merino sheep were higher than that in the very thick wool group, and the difference for IGFBP4 was significant. The total methylation rate of IGFBP2 promoter was extremely low, and no significant difference was found in the skin tissue of the Super Merino sheep at different fineness groups. However, the total methylation rate of IGFBP4 promoter in the very thick group was significantly higher than that in the very fine group, and the total DNA methylation levels of the IGFBP4 were significantly negatively correlated with mRNA expression. Furthermore, the transcription factor prediction results showed 104 and 91 candidate binding sites for transcription factors in the promoter regions of IGFBP2 and IGFBP4, respectively. Among these, JUN, EP300, SP1, PAX6, ETS1, and MYOD1 may be related to hair follicle development. Conclusions: The total methylation level of IGFBP4 promoter was negatively correlated with its mRNA expression in Super Merino sheep skin tissues with different degrees of fineness, which could be used as an epigenetic marker for wool breeding in Super Merino sheep.How to cite: Tian Y, Du J, Yang X, et al. Sheep IGFBP2 and IGFBP4 promoter methylation regulates gene expression and hair follicle development. Electron J Biotechnol 2022;59. https://doi.org/10.1016/j.ejbt.2022.07.001.

ABSTRACT Expression of the hypermucoviscosity (HMV) phenotype and capsular polysaccharide (CPS) biosynthesis in Klebsiella pneumoniae were reported to be encoded by genes located in the chromosomal rmp locus. However, the functions of the rmp locus in the virulence plasmid remained unclear, and most of the rmp loci in clinical K. pneumoniae are plasmid carried. In this study, we investigated the functional characteristics of plasmid-borne rmp homologues in clinical hypervirulent K. pneumoniae (hvKP) strains by cloning and introducing such gene homologues into K. pneumoniae strains of different capsule types, followed by the evaluation of phenotypic changes in these strains. Acquisition of the plasmid-borne prmpADC and prmpA2D2 loci were found to result in an increase in mucoviscosity and CPS production in K1 and K2 K. pneumoniae, while only the prmpA2D2 locus contributed to phenotypic changes in the ST11/KL64 strain. Consistently, both rmpD and rmpD2 increased HMV in K1 and K2 K. pneumoniae, while only rmpD2 contributed to HMV in the ST11/KL64 strain; rmpC contributed to CPS overproduction in K1 and K2 strains but not in the ST11/KL64 strain. Furthermore, we proposed a logistic molecular basis of the HMV phenotype of K. pneumoniae on which prmpD2-mediated HMV is attributed to the increase of cell-free CPS production. Our data confirm that the rmp homologues carried by the virulence plasmid play a key role in virulence expression in K. pneumoniae, but the phenotype is highly dependent on the genetic background of the host strain and explained why most of the clinical ST11 strains carry only the prmpA2D2 locus. IMPORTANCE Klebsiella pneumoniae has become the most frequently isolated bacterial pathogen in hospital settings, with a very high mortality rate worldwide. Factors contributing to the virulence of K. pneumoniae are the overproduction of capsular polysaccharide (CPS) as well as the hypermucoviscosity (HMV) phenotype. These two phenotypes were reported to be regulated by rmpA/A2 homologues, which are often carried by virulence plasmids. Here, we determined the functional role of two plasmid-borne rmpA in mediating expression of the HMV phenotype and CPS production in K. pneumoniae. Different capsule types exhibited differences in the expression of HMV and CPS production although they harbored an identical plasmid-borne rmpA or rmpA2 locus, indicating that these virulence-related phenotypes are strongly related to the genetic background of the host strains. Our study provides a novel understanding of the regulation of virulence-related phenotypes and clinical management of K. pneumoniae infections.

Pharmaceutical residues are the undecomposed remains from drugs used in the medical and food industries. Due to their potential adverse effects on human health and natural ecosystems, they are of increasing worldwide concern. The acute detection of pharmaceutical residues can give a rapid examination of their quantity and then prevent them from further contamination. Herein, this study summarizes and discusses the most recent porous covalent-organic frameworks (COFs) and metal–organic frameworks (MOFs) for the electrochemical detection of various pharmaceutical residues. The review first introduces a brief overview of drug toxicity and its effects on living organisms. Subsequently, different porous materials and drug detection techniques are discussed with materials’ properties and applications. Then the development of COFs and MOFs has been addressed with their structural properties and sensing applications. Further, the stability, reusability, and sustainability of MOFs/COFs are reviewed and discussed. Besides, COFs and MOFs’ detection limits, linear ranges, the role of functionalities, and immobilized nanoparticles are analyzed and discussed. Lastly, this review summarized and discussed the MOF@COF composite as sensors, the fabrication strategies to enhance detection potential, and the current challenges in this area.

Abstract Background Alpha-fetoprotein (AFP) is a biomarker used in clinical management of hepatocellular carcinoma (HCC), however, approximately 40% of HCC patients do not present with elevated serum AFP levels. This study aimed to investigate the clinical and pathologic characteristics between AFP positive and negative HCC patients to allow for improved clinical management and prognostication of the disease. Methods This study observed a cohort of HCC patients from Eastern and Southern China with comparisons of the clinical and pathologic features between serum AFP positive and negative patient groups; patients with decompensated hepatic cirrhosis, those with chronic hepatitis B, and hepatitis B virus (HBV) asymptomatic carrier patients were used as controls. Data included the laboratory results, pathology diagnosis, clinical staging and scores were obtained from routine clinical diagnostic methods. Results Patients with HCC, larger tumor sizes, liver cancer with hepatic cirrhosis, portal vein thrombosis, metastasis, high Child–Pugh score, high Barcelona-Clínic Liver Cancer (BCLC) stage, and advanced clinical stage had significantly higher serum AFP levels. Also, patients with HBsAg and HBeAg positive, high HBV DNA levels had significantly higher serum AFP levels. Patients with high serum AFP levels had higher protein induced by vitamin K absence or antagonist-II (PIVKA-II), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alpha-l-fucosidase (AFU), gamma-glutamyl transpeptidase (γ-GT), γ-GT /ALT, direct bilirubin (DBIL), indirect bilirubin (IDBIL), fibrinogen, and D-dimer levels. Patients with AFP positive had higher white blood cells (WBC), neutrophil, monocyte, and platelet count and neutrophil to lymphocyte ratio (NLR). Conclusions The are significant differences in clinical pathologic characteristics between AFP positive and negative HCC patients which may be helpful for the management and prognostication of the disease.

Purpose: We aim to present effective and computer aided diagnostics in the field of ophthalmology and improve eye health. This study aims to create an automated deep learning based system for categorizing fundus images into three classes: normal, macular degeneration and tessellated fundus for the timely recognition and treatment of diabetic retinopathy and other diseases.Methods: A total of 1,032 fundus images were collected from 516 patients using fundus camera from Health Management Center, Shenzhen University General Hospital Shenzhen University, Shenzhen 518055, Guangdong, China. Then, Inception V3 and ResNet-50 deep learning models are used to classify fundus images into three classes, Normal, Macular degeneration and tessellated fundus for the timely recognition and treatment of fundus diseases.Results: The experimental results show that the effect of model recognition is the best when the Adam is used as optimizer method, the number of iterations is 150, and 0.00 as the learning rate. According to our proposed approach we, achieved the highest accuracy of 93.81% and 91.76% by using ResNet-50 and Inception V3 after fine-tuned and adjusted hyper parameters according to our classification problem.Conclusion: Our research provides a reference to the clinical diagnosis or screening for diabetic retinopathy and other eye diseases. Our suggested computer aided diagnostics framework will prevent incorrect diagnoses caused by the low image quality and individual experience, and other factors. In future implementations, the ophthalmologists can implement more advanced learning algorithms to improve the accuracy of diagnosis.