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Abstract Although nanocatalytic medicine has demonstrated its advantages in tumor therapy, the outcomes heavily relie on substrate concentration and the metabolic pathways are still indistinct. We discover that violet phosphorus quantum dots (VPQDs) can catalyze the production of reactive oxygen species (ROS) without requiring external stimuli and the catalytic substrates are confirmed to be oxygen (O2) and hydrogen peroxide (H2O2) through the computational simulation and experiments. Considering the short of O2 and H2O2 at the tumor site, we utilize calcium peroxide (CaO2) to supply catalytic substrates for VPQDs and construct nanoparticles together with them, named VPCaNPs. VPCaNPs can induce oxidative stress in tumor cells, particularly characterized by a significant increase in hydroxyl radicals and superoxide radicals, which cause substantial damage to the structure and function of cells, ultimately leading to cell apoptosis. Intriguingly, O2 provided by CaO2 can degrade VPQDs slowly, and the degradation product, phosphate, as well as CaO2-generated calcium ions, can promote tumor calcification. Antitumor immune activation and less metastasis are also observed in VPCaNPs administrated animals. In conclusion, our study unveils the anti-tumor activity of VPQDs as catalysts for generating cytotoxic ROS and the degradation products can promote tumor calcification, providing a promising strategy for treating tumors.

Abstract Elucidating the intricate interactions between viral pathogens and host cellular machinery during infection is paramount for understanding pathogenic mechanisms and identifying potential therapeutic targets. The RNA modification N 6-methyladenosine (m6A) has emerged as a significant factor influencing the trajectory of viral infections. Hence, the precise and quantitative mapping of m6A modifications in both host and viral RNA is pivotal to understanding its role during viral infection. With the rapid advancement of sequencing technologies, scientists are able to detect m6A modifications with various quantitative, high-resolution, transcriptome approaches. These technological strides have reignited research interest in m6A, underscoring its significance and prompting a deeper investigation into its dynamics during viral infections. This review provides a comprehensive overview of the historical evolution of m6A epitranscriptome sequencing technologies, highlights the latest developments in transcriptome-wide m6A mapping, and emphasizes the innovative technologies for detecting m6A modification. We further discuss the implications of these technologies for future research into the role of m6A in viral infections. Graphical Abstract

Abstract The evolution of gas hydrates influenced by the seawater environment is unknown. We present a model of structural transformation from sI hydrate to sII hydrate due to the influence of seawater environment and vent fluid in nature through in situ experiments of gas hydrate formation in the Haima cold seep area. The in situ experimental results indicate that gas hydrates preferentially form as sI hydrates even in cold seep environments where C2+ hydrocarbons are present. During subsequent evolution, the sI hydrates could restructured at the effect of seawater environment and vent fluid, causing transformation to sII hydrates under the influence of hydrate stability. The supply of gas and direct contact with seawater environment are critical factors for structural transformation. Such structural transformation is the result of gas hydrates seeking thermodynamic stability and may be common in active cold seep areas.

Abstract Background Alzheimer’s disease (AD), affecting many elders worldwide, is characterized by A-beta and tau-related cognitive decline. Accumulating evidence suggests that brain iron accumulation is an important characteristic of AD. However, the function and mechanism of the iron-mediated gut-brain axis on AD is still unclear. Methods A Caenorhabditis elegans model with tau-overexpression and a high-Fe diet mouse model of cognitive impairment was used for probiotic function evaluation. With the use of qPCR, and immunoblotting, the probiotic regulated differential expression of AD markers and iron related transporting genes was determined. Colorimetric kits, IHC staining, and immunofluorescence have been performed to explore the probiotic mechanism on the development of gut-brain links and brain iron accumulation. Results In the present study, a high-Fe diet mouse model was used for evaluation in which cognitive impairment, higher A-beta, tau and phosphorylated (p)-tau expression, and dysfunctional phosphate distribution were observed. Considering the close crosstalk between intestine and brain, probiotics were then employed to delay the process of cognitive impairment in the HFe mouse model. Pediococcus acidilactici (PA), but not Bacillus subtilis (BN) administration in HFe-fed mice reduced brain iron accumulation, enhanced global alkaline phosphatase (AP) activity, accelerated dephosphorylation, lowered phosphate levels and increased brain urate production. In addition, because PA regulated cognitive behavior in HFe fed mice, we used the transgenic Caenorhabditis elegans with over-expressed human p-tau for model, and then PA fed worms became more active and longer lived than E.coli fed worms, as well as p-tau was down-regulated. These results suggest that brain iron accumulation influences AD risk proteins and various metabolites. Furthermore, PA was shown to reverse tau-induced pathogenesis via iron transporters and AP-urate interaction. Conclusions PA administration studies demonstrate that PA is an important mediator of tau protein reduction, p-tau expression and neurodegenerative behavior both in Caenorhabditis elegans and iron-overload mice. Finally, our results provide candidates for AP modulation strategies as preventive tools for promoting brain health. Video Abstract

Abstract Background Obstructive sleep apnea (OSA) is a globally prevalent disease with a complex diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to develop an interpretable machine learning (ML) model for predicting the risk of severe OSA and analyzing the risk factors based on clinical characteristics and questionnaires. Methods This was a retrospective study comprising 1656 subjects who presented and underwent polysomnography (PSG) between 2018 and 2021. A total of 23 variables were included, and after univariate analysis, 15 variables were selected for further preprocessing. Six types of classification models were used to evaluate the ability to predict severe OSA, namely logistic regression (LR), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), bootstrapped aggregating (Bagging), and multilayer perceptron (MLP). All models used the area under the receiver operating characteristic curve (AUC) was calculated as the performance metric. We also drew SHapley Additive exPlanations (SHAP) plots to interpret predictive results and to analyze the relative importance of risk factors. An online calculator was developed to estimate the risk of severe OSA in individuals. Results Among the enrolled subjects, 61.47% (1018/1656) were diagnosed with severe OSA. Multivariate LR analysis showed that 10 of 23 variables were independent risk factors for severe OSA. The GBM model showed the best performance (AUC = 0.857, accuracy = 0.766, sensitivity = 0.798, specificity = 0.734). An online calculator was developed to estimate the risk of severe OSA based on the GBM model. Finally, waist circumference, neck circumference, the Epworth Sleepiness Scale, age, and the Berlin questionnaire were revealed by the SHAP plot as the top five critical variables contributing to the diagnosis of severe OSA. Additionally, two typical cases were analyzed to interpret the contribution of each variable to the outcome prediction in a single patient. Conclusions We established six risk prediction models for severe OSA using ML algorithms. Among them, the GBM model performed best. The model facilitates individualized assessment and further clinical strategies for patients with suspected severe OSA. This will help to identify patients with severe OSA as early as possible and ensure their timely treatment. Trial registration Retrospectively registered.

Abstract Background To investigate the relationship between tongue fat content and severity of obstructive sleep apnea (OSA) and its effects on the efficacy of uvulopalatopharyngoplasty (UPPP) in the Chinese group. Method Fifty-two participants concluded to this study were diagnosed as OSA by performing polysomnography (PSG) then they were divided into moderate group and severe group according to apnea hypopnea index (AHI). All of them were also collected a series of data including age, BMI, height, weight, neck circumference, abdominal circumference, magnetic resonance imaging (MRI) of upper airway and the score of Epworth Sleepiness Scale (ESS) on the morning after they completed PSG. The relationship between tongue fat content and severity of OSA as well as the association between tongue fat content in pre-operation and surgical efficacy were analyzed.Participants underwent UPPP and followed up at 3rd month after surgery, and they were divided into two groups according to the surgical efficacy. Results There were 7 patients in the moderate OSA group and 45 patients in the severe OSA group. The tongue volume was significantly larger in the severe OSA group than that in the moderate OSA group. There was no difference in tongue fat volume and tongue fat rate between the two groups. There was no association among tongue fat content, AHI, obstructive apnea hypopnea index, obstructive apnea index and Epworth sleepiness scale (all P > 0.05), but tongue fat content was related to the lowest oxygen saturation (r=-0.335, P

Diabetic Peripheral Neuropathy (DPN) poses an escalating threat to public health, profoundly impacting well-being and quality of life. Despite its rising prevalence, the pathogenesis of DPN remains enigmatic, and existing clinical interventions fall short of achieving meaningful reversals of the condition. Notably, neurostimulation techniques have shown promising efficacy in alleviating DPN symptoms, underscoring the imperative to elucidate the neurobiochemical mechanisms underlying DPN. This study employs an integrated multi-omics approach to explore DPN and its response to neurostimulation therapy. Our investigation unveiled a distinctive pattern of vesicular glutamate transporter 2 (VGLUT2) expression in DPN, rigorously confirmed through qPCR and Western blot analyses in DPN C57 mouse model induced by intraperitoneal Streptozotocin (STZ) injection. Additionally, combining microarray and qPCR methodologies, we revealed and substantiated variations in the expression of the Amyloid Precursor Protein (APP) family in STZ-induced DPN mice. Analyzing the transcriptomic dataset generated from neurostimulation therapy for DPN, we intricately explored the differential expression patterns of VGLUT2 and APPs. Through correlation analysis, protein-protein interaction predictions, and functional enrichment analyses, we predicted the key biological processes involving VGLUT2 and the APP family in the pathogenesis of DPN and during neurostimulation therapy. This comprehensive study not only advances our understanding of the pathogenesis of DPN but also provides a theoretical foundation for innovative strategies in neurostimulation therapy for DPN. The integration of multi-omics data facilitates a holistic view of the molecular intricacies of DPN, paving the way for more targeted and effective therapeutic interventions.

Accurate traffic prediction is pivotal when constructing intelligent cities to enhance urban mobility and to efficiently manage traffic flows. Traditional deep learning-based traffic prediction models primarily focus on capturing spatial and temporal dependencies, thus overlooking the existence of spatial and temporal heterogeneities. Heterogeneity is a crucial inherent characteristic of traffic data for the practical applications of traffic prediction. Spatial heterogeneities refer to the differences in traffic patterns across different regions, e.g., variations in traffic flow between office and commercial areas. Temporal heterogeneities refer to the changes in traffic patterns across different time steps, e.g., from morning to evening. Although existing models attempt to capture heterogeneities through predefined handcrafted features, multiple sets of parameters, and the fusion of spatial–temporal graphs, there are still some limitations. We propose a self-supervised learning-based traffic prediction framework called Traffic Prediction with Self-Supervised Learning (TPSSL) to address this issue. This framework leverages a spatial–temporal encoder for the prediction task and introduces adaptive data masking to enhance the robustness of the model against noise disturbances. Moreover, we introduce two auxiliary self-supervised learning paradigms to capture spatial heterogeneities and temporal heterogeneities, which also enrich the embeddings of the primary prediction task. We conduct experiments on four widely used traffic flow datasets, and the results demonstrate that TPSSL achieves state-of-the-art performance in traffic prediction tasks.

The widespread use of non-renewable phosphate fertilizers in agriculture poses a significant pollution threat to soil, necessitating the exploration of sustainable alternatives for phosphate fertility. Releasing phytate phosphorus through microbial phytases presents an eco-friendly solution for sustainable phosphate fertility in agriculture. This study directly inoculated dual-domain β-propeller alkaline phytase (phyHT) derived from Bacillus sp. HJB17 into the soil. The study analyzed the impact of inoculated phyHT on the physicochemical properties of the soil, assessed the variations in enzyme activity of phyHT within the soil, and examined the effects of the treated soil on wheat growth. Additionally, the study explored the enhancement of the available phosphorus in the soil through the inoculation of phyHT in both crop residues and organic fertilizer. PhyHT exhibited the highest catalytic activity at 37 °C and pH 8.0. After soil adsorption, phyHT maintained stable enzymatic activity. PhyHT markedly boosted the available phosphorus in the soil while reducing the soil phytate content by about 20%, increasing the phosphorus levels and enhancing soil fertility. PhyHT effectively degraded phytates in an organic fertilizer and crop residues, increasing the available phosphorus. PhyHT supplementation enhanced growth, biomass, and phosphorus content in both the shoot and root weights of Triticum aestivum. This study establishes phyHT as a viable and eco-friendly method to enhance phosphorus fertility in soil. The direct application of microbial phytases can serve as a sustainable source of phosphate fertility in soil.

Abstract Background Obstructive sleep apnea (OSA) is mainly characterized by sleep fragmentation and chronic intermittent hypoxia (CIH), the latter one being associated with multiple organ injury. Recently, OSA-induced cognition dysfunction has received extensive attention from scholars. Astrocytes are essential in neurocognitive deficits via A1/A2 phenotypic changes. Nucleotide oligomerization domain (NOD)-like receptor protein 3 (NLRP3) inflammasome is considered the most important factor inducing and maintaining neuroinflammation. However, whether the NLRP3 regulates the A1/A2 transformation of astrocytes in CIH-related brain injury remains unclear. Methods We constructed an OSA-related CIH animal model and assessed the rats' learning ability in the Morris water maze; the histopathological assessment was performed by HE and Nissl staining. The expression of GFAP (astrocyte marker), C3d (A1-type astrocyte marker), and S100a10 (A2-type astrocyte marker) were detected by immunohistochemistry and immunofluorescence. Western blotting and RT-qPCR were used to evaluate the changes of A1/A2 astrocyte-related protein and NLRP3/Caspase-1/ASC/IL-1β. Results The learning ability of rats decreased under CIH. Further pathological examination revealed that the neurocyte in the hippocampus were damaged. The cell nuclei were fragmented and dissolved, and Nissl bodies were reduced. Immunohistochemistry showed that astrocytes were activated, and morphology and number of astrocytes changed. Immunofluorescence, Western blotting and RT-qPCR showed that the expression of C3d was increased while S100a10 was decreased. Also, the expression of the inflammasome (NLRP3/Caspase-1/ASC/IL-1β) was increased. After treatment of MCC950 (a small molecule inhibitor of NLRP3), the damage of nerve cells was alleviated, the Nissl bodies increased, the activation of astrocytes was reduced, and the expression of A2-type astrocytes was increased. In contrast, A1-type astrocytes decreased, and the expression of inflammasome NLRP3/Caspase-1/ASC/IL-1β pathway-related proteins decreased. Conclusion The NLRP3 inflammasome could regulate the A1/A2 transformation of astrocytes in brain injury induced by CIH

Abstract Background Rare diseases impose a heavy economic burden on patients’ families and society worldwide. This study used the samples from Sichuan Province in China to estimate the curative care expenditure (CCE) of ten rare diseases, for supporting the prioritization of rare disease health policies. Methods Multi-stage cluster sampling method was adopted to investigate 9714 rare disease patients from 1556 medical institutions in Sichuan Province. Based on the System of Health Accounts 2011, this study estimated the total CCE of 10 rare diseases, financing schemes, and their allocation among different medical institutions and groups of people. Results In 2018, the total CCE of the ten rare diseases was $19.00 million, the three costliest rare diseases were Hemophilia ($4.38 million), Young-onset Parkinson’s disease ($2.96 million), and Systemic Sclerosis ($2.45 million). Household out-of-pocket expenditure (86.00% for outpatients, 41.60% for inpatients) and social health insurance (7.85% for outpatients; 39.58% for inpatients) were the main sources of financing CCE. The out-of-pocket expenditures for patients with Young-onset Parkinson’s disease, Congenital Scoliosis, and Autoimmune Encephalitis accounted for more than 60% of the total CCE. More than 80% of the rare disease CCE was incurred in general hospitals. The 40–59 age group accounted for the highest CCE (38.70%) while men spent slightly more (55.37%) than women (44.64%). Conclusions As rare disease treatment is costly and household out-of-pocket expenditure is high, we suggest taking steps to include rare disease drugs in the National Reimbursement Drug List and scientifically re-design insurance coverage. It is also necessary to explore a multi-tiered healthcare security system to pay for the CCE of rare diseases and reduce the economic burden on patients.

Abstract Background In children, obstructive sleep apnea (OSA) can cause cognitive dysfunctions. Amyloid-beta and tau are elevated in OSA. Neurofilament light (NfL) is a marker of neuro-axonal damage, but there are no reports of NfL for OSA. The objective was to investigate the serum levels of NfL and tau in children with or without OSA and explore their relationship with cognitive dysfunctions caused by OSA. Methods This retrospective case–control study included children diagnosed with adenoid tonsil hypertrophy from July 2017 to September 2019 at the Second Affiliated Hospital of Xi’an Jiaotong University. Correlations between cognitive scores and tau and NfL were examined. Results Fifty-six OSA and 49 non-OSA children were included. The serum NfL levels were higher in the OSA group (31.68 (27.29–36.07) pg/ml) than in the non-OSA group (19.13 (17.32–20.95) pg/ml) (P

IntroductionVibriosis causes enormous economic losses of marine fish. The present study investigated the intestinal microbial response to acute infection of half-smooth tongue sole with different-dose Vibrio alginolyticus within 72 h by metagenomic sequencing.MethodsThe inoculation amount of V. alginolyticus for the control, low-dose, moderate-dose, and high-dose groups were 0, 8.5 × 101, 8.5 × 104, and 8.5 × 107 cells/g respectively, the infected fish were farmed in an automatic seawater circulation system under a relatively stable temperature, dissolved oxygen and photoperiod, and 3 ~ 6 intestinal samples per group with high-quality DNA assay were used for metagenomics analysis.ResultsThe acute infections with V. alginolyticus at high, medium, and low doses caused the change of different-type leukocytes at 24 h, whereas the joint action of monocytes and neutrophils to cope with the pathogen infection only occurred in the high-dose group at 72 h. The metagenomic results suggest that a high-dose V. alginolyticus infection can significantly alter the intestinal microbiota, decrease the microbial α-diversity, and increase the bacteria from Vibrio and Shewanella, including various potential pathogens at 24 h. High-abundance species of potential pathogens such as V. harveyii, V. parahaemolyticus, V. cholerae, V. vulnificus, and V. scophthalmi exhibited significant positive correlations with V. alginolyticus. The function analysis revealed that the high-dose inflection group could increase the genes closely related to pathogen infection, involved in cell motility, cell wall/ membrane/envelope biogenesis, material transport and metabolism, and the pathways of quorum sensing, biofilm formation, flagellar assembly, bacterial chemotaxis, virulence factors and antibiotic resistances mainly from Vibrios within 72 h.DiscussionIt indicates that the half-smooth tongue sole is highly likely to be a secondary infection with intestinal potential pathogens, especially species from Vibrio and that the disease could become even more complicated because of the accumulation and transfer of antibiotic-resistance genes in intestinal bacteria during the process of V. alginolyticus intensified infection.

This study aimed to assess the changes of small intestinal morphology, progenitors, differentiated epithelial cells, and potential mechanisms in neonatal piglets. Hematoxylin and eosin staining of samples from 36 piglets suggested that dramatic changes were observed in the jejunum crypts depth and crypt fission index of neonatal piglets (P

The roughskin sculpin (Trachidermus fasciatus) is an endangered fish species in China. In recent years, artificial breeding technology has made significant progress, and the population of roughskin sculpin has recovered in the natural environment through enhancement programs and the release of juveniles. However, the effects of released roughskin sculpin on the genetic structure and diversity of wild populations remain unclear. Studies on genetic diversity analysis based on different types and numbers of molecular markers have yielded inconsistent results. In this study, we obtained 2,610,157 high-quality SNPs and 494,698 InDels through whole-genome resequencing of two farmed populations and one wild population. Both farmed populations showed consistent levels of genomic polymorphism and a slight increase in linkage compared with wild populations. The population structure of the two farmed populations was distinct from that of the wild population, but the degree of genetic differentiation was low (overall average Fst = 0.015). Selective sweep analysis showed that 523,529 genes were selected in the two farmed populations, and KEGG enrichment analysis showed that the selected genes were related to amino acid metabolism, which might be caused by artificial feeding. The findings of this study provide valuable additions to the existing genomic resources to help conserve roughskin sculpin populations.

Maize, a crop of international relevance, frequently undergoes xylem embolism due to water shortage, negatively impacting growth, yield, and quality. Consequently, a refined comprehension of xylem embolism is vital for enhancing maize cultivation. Notwithstanding extensive research and the generation of analytical models for embolism mechanisms, prevalent models often disregard crop-specific hydraulic processes and the formation of embolisms via air bubbles in the xylem conduit. In this research, we present an inventive model applying pipe cavitation parameters to discern water potential and bubble formation in maize leaf xylem. The model integrates pivotal physiological traits of the maize–leaf count, leaf vein count, and diameter of xylem vessels—demonstrating robust correlations. Furthermore, we constructed Percent Loss of Conductivity (PLC) curve based on water potential and compared it with our model, offering interval data to observe embolization events triggered by air bubbles. Utilizing experimental data, our novel cavitation-parameter-based model effectively corresponds with observed bubble phenomena and appropriately characterizes water transport in plant xylem conduits. This method enabled us to observe the transition from bubble occurrence to cavitation embolism microscopically, which aligned with the embolism intervals provided by the model. This procedure reveals potential trends in bubble-induced embolism and deepens our knowledge of microscopic plant hydraulics and crop embolism. This work establishes a basis for understanding the generation of bubble embolisms in maize, assists in evaluating maize-plant water status for efficient water supply management throughout the growth cycle, and contributes towards potential water management strategies for maize.

Abstract Background Diabetic retinopathy (DR) is the primary oculopathy causing blindness in diabetic patients. Currently, there is increasing interest in the role of lipids in the development of diabetic retinopathy, but it remains controversial. Remnant cholesterol (RC) is an inexpensive and easily measurable lipid parameter; however, the relationship between RC and DR in type 2 diabetes mellitus (T2DM) has not been elucidated. This research investigates the relevance between RC levels and DR severity while building a risk prediction model about DR. Methods In this single-centre retrospective cross-sectional study. Each hospitalised T2DM patient had no oral lipid-lowering drugs in the past three months, and coronary angiography showed epicardial coronary artery stenosis of less than 50% and completed seven-field stereo photographs, fluorescein fundus angiography, and optical coherence tomography detection. The RC value is calculated according to the internationally recognised formula. Binary logistic regression was used to correct confounding factors, and the receiver operating characteristic (ROC) analysis was used to identify risk factors and assess the nomogram’s diagnostic efficiency. Results A total of 456 T2DM patients were included in the study. The RC levels in the DR team was higher [0.74 (0.60–1.12) mmo/l vs 0.54 (0.31–0.83) mmol/l P

BackgroundAs an important neuroprotective factor, the brain-derived neurotrophic factor (BDNF) may have a key role in cognitive impairment in children with sleep-disordered breathing (SDB). The main aim of this study was to compare the levels of BDNF and tyrosine kinase receptor B (TrkB) in normal children and those with obstructive sleep apnea (OSA) and primary snoring (PS) and to explore a possible link between BDNF/TrkB, inflammation, and SDB with cognitive impairment in children.MethodsA total of 44 OSA children and 35 PS children who completed polysomnography between October 2017 and October 2019 were enrolled. At the same time, 40 healthy children during the same period were included as a control. Enzyme-linked immunosorbent assay was used to measure serum indices of BDNF, TrkB, interleukin-1beta (IL-1β), and tumor necrosis factor-alpha (TNF-α). Correlation and pooled analyses were performed between the cognitive scores and four serological indicators. Logistic regression was used to analyze the risk factors for cognitive impairment.ResultsSignificant differences were found in serum BDNF, TrkB, IL-1β, and TNF-α between the three groups (all P

BackgroundObstructive sleep apnea (OSA) is a globally prevalent disease closely associated with hypertension. To date, no predictive model for OSA-related hypertension has been established. We aimed to use machine learning (ML) to construct a model to analyze risk factors and predict OSA-related hypertension.Materials and methodsWe retrospectively collected the clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 and randomly divided them into training and validation sets. A total of 1,493 OSA patients with 27 variables were included. Independent risk factors for the risk of OSA-related hypertension were screened by the multifactorial logistic regression models. Six ML algorithms, including the logistic regression (LR), the gradient boosting machine (GBM), the extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), bootstrapped aggregating (Bagging), and the multilayer perceptron (MLP), were used to develop the model on the training set. The validation set was used to tune the model hyperparameters to determine the final prediction model. We compared the accuracy and discrimination of the models to identify the best machine learning algorithm for predicting OSA-related hypertension. In addition, a web-based tool was developed to promote its clinical application. We used permutation importance and Shapley additive explanations (SHAP) to determine the importance of the selected features and interpret the ML models.ResultsA total of 18 variables were selected for the models. The GBM model achieved the most extraordinary discriminatory ability (area under the receiver operating characteristic curve = 0.873, accuracy = 0.885, sensitivity = 0.713), and on the basis of this model, an online tool was built to help clinicians optimize OSA-related hypertension patient diagnosis. Finally, age, family history of hypertension, minimum arterial oxygen saturation, body mass index, and percentage of time of SaO2 < 90% were revealed by the SHAP method as the top five critical variables contributing to the diagnosis of OSA-related hypertension.ConclusionWe established a risk prediction model for OSA-related hypertension patients using the ML method and demonstrated that among the six ML models, the gradient boosting machine model performs best. This prediction model could help to identify high-risk OSA-related hypertension patients, provide early and individualized diagnoses and treatment plans, protect patients from the serious consequences of OSA-related hypertension, and minimize the burden on society.

Wheel-legged robots have fast and stable motion characteristics on flat roads, but there are the problems of poor balance ability and low movement level in special terrains such as rough roads. In this paper, a new type of wheel-legged robot with parallel four-bar mechanism is proposed, and the linear quadratic regulator (LQR) controller and fuzzy proportion differentiation (PD) jumping controller are designed and developed to achieve stable motion so that the robot has the ability to jump over obstacles and adapt to rough terrain. The amount of energy released by the parallel four-bar linkage mechanism changes with the change of the link angle, and the height of the jump trajectory changes accordingly, which improves the robot’s ability to overcome obstacles facing vertical obstacles. Simulations and real scene tests are performed in different terrain environments to verify obstacle crossing capabilities. The simulation results show that, in the pothole terrain, the maximum height error of the two hip joint motors is 2 mm for the obstacle surmounting method of the adaptive retractable wheel-legs; in the process of single leg obstacle surmounting, the maximum height error of the hip joint motors is only 6.6 mm. The comparison of simulation data and real scene experimental results shows that the robot has better robustness in moving under complex terrains.

AimTo explore the role of smell and taste changes in preventing and controlling the COVID-19 pandemic, we aimed to build a forecast model for trends in COVID-19 prediction based on Google Trends data for smell and taste loss.MethodsData on confirmed COVID-19 cases from 6 January 2020 to 26 December 2021 were collected from the World Health Organization (WHO) website. The keywords “loss of smell” and “loss of taste” were used to search the Google Trends platform. We constructed a transfer function model for multivariate time-series analysis and to forecast confirmed cases.ResultsFrom 6 January 2020 to 28 November 2021, a total of 99 weeks of data were analyzed. When the delay period was set from 1 to 3 weeks, the input sequence (Google Trends of loss of smell and taste data) and response sequence (number of new confirmed COVID-19 cases per week) were significantly correlated (P < 0.01). The transfer function model showed that worldwide and in India, the absolute error of the model in predicting the number of newly diagnosed COVID-19 cases in the following 3 weeks ranged from 0.08 to 3.10 (maximum value 100; the same below). In the United States, the absolute error of forecasts for the following 3 weeks ranged from 9.19 to 16.99, and the forecast effect was relatively accurate. For global data, the results showed that when the last point of the response sequence was at the midpoint of the uptrend or downtrend (25 July 2021; 21 November 2021; 23 May 2021; and 12 September 2021), the absolute error of the model forecast value for the following 4 weeks ranged from 0.15 to 5.77. When the last point of the response sequence was at the extreme point (2 May 2021; 29 August 2021; 20 June 2021; and 17 October 2021), the model could accurately forecast the trend in the number of confirmed cases after the extreme points. Our developed model could successfully predict the development trends of COVID-19.ConclusionGoogle Trends for loss of smell and taste could be used to accurately forecast the development trend of COVID-19 cases 1–3 weeks in advance.

Global warming is accelerating permafrost thaw, forming new thermokarst lakes and substantially influencing the old ones. However, the biological communities in thermokarst lakes on the Qinghai-Tibet Plateau (QTP) are rarely studied. Here, we assessed the biogeographical patterns of zooplankton communities in 44 thermokarst lakes across the QTP. Across all lakes, 17 Cladocera and 13 Copepoda species were identified, with most of the lakes dominated by Cladocera. Chydorus sphaericus and Cyclops vicinus were the most frequently detected species. Both cladoceran and copepod communities had very low species richness and density, which lacked a clear spatial pattern but positively associated to dissolved oxygen. In general, species richness was negatively influenced by seston particle quantity while the density was positively influenced by water nutrient concentrations. Cladoceran and copepod communities had a high β-diversity (0.89 and 0.91, respectively), which was dominated by species turnover. However, Cladocera had significantly lower β-diversity and turnover component than copepod communities. β-diversity of Cladocera and Copepoda showed a significant but weak distance decay relationship and also significantly correlated with longitude, latitude, mean annual temperature, as well as concentrations of seston particle carbon and nitrogen. In addition, their β-diversities differentially correlated to other environmental variables. Overall, the results suggested that the geographical barriers, climate, and some local environmental variables are key factors in shaping the biogeography of zooplankton community. Although a general biogeographic pattern of zooplankton across the QTP cannot be drawn from this limited dataset, this study provided the first large spatial scale investigation and analyses of zooplankton biogeography in thermokarst lakes on the QTP. Given the important roles of zooplankton in aquatic ecosystems, this study could provide insights for understanding the influences of future environmental changes on thermokarst lake ecosystems.

Diabetic neuropathy is regarded as one of the most debilitating outcomes of diabetes. It can affect both the peripheral and central nervous systems, leading to pain, decreased motility, cognitive decline, and dementia. S-palmitoylation is a reversible posttranslational lipid modification, and its dysregulation has been implicated in metabolic syndrome, cancers, neurological disorders, and infections. However, the role of S-palmitoylation in diabetic neuropathy remains unclear. Here we demonstrate a potential association between activating protein palmitoylation and diabetic neuropathy. We compared the proteomic data of lumbar dorsal root ganglia (DRG) of diabetes mice and palmitoylome profiling data of the HUVEC cell line. The mapping results identified peroxiredoxin-6 (PRDX6) as a novel target in diabetic neuropathy, whose biological mechanism was associated with S-palmitoylation. Bioinformatic prediction revealed that PRDX6 had two palmitoylation sites, Cys47 and Cys91. Immunofluorescence results indicated PRDX6 translocating between the cytoplasm and cell membrane. Protein function analysis proposed that increased palmitoylation could competitively inhibit the formation of disulfide-bond between Cys47 and Cys91 and change the spatial topology of PRDX6 protein. Cl–HCO3- anion exchanger 3 (AE3) was one of the AE family members, which was proved to express in DRG. AE3 activity evoked Cl- influx in neurons which was generally associated with increased excitability and susceptibility to pain. We demonstrated that the S-palmitoylation status of Cys47 could affect the interaction between PRDX6 and the C-terminal domain of AE3, thereby regulating the activity of AE3 anion exchanger enzyme in the nervous system. The results highlight a central role for PRDX6 palmitoylation in protection against diabetic neuropathy.

The effects of excessive dietary iron intake on the body have been an important topic. The purpose of this study was to investigate the effects of high-dose iron on intestinal damage and regeneration in dextran sodium sulfate (DSS)-induced colitis model mice. A total of 72 8-week-old adult C57BL/6 mice were randomly divided into two dietary treatment groups: the basal diet supplemented with 45 (control) and 450 mg/kg iron (high-iron) from ferrous sulfate. The mice were fed different diets for 2 weeks, and then 2.5% DSS was orally administered to all mice for 7 days. Samples of different tissues were collected on days 0, 3, and 7 post administration (DPA). High-iron treatment significantly decreased the relative weight of the large intestine at 7 DPA but not at 0 DPA or 3 DPA. High dietary iron increased the jejunal villus width at 0 DPA, decreased the villus width and the crypt depth of the jejunum at 3 DPA, and decreased the number of colonic crypts at 7 DPA. Meanwhile, high dietary iron decreased the number of goblet cells in the jejunal villi and the Paneth cells in the jejunal crypts at 0 DPA, increased the number of goblet cells per crypt of the colon at 3 DPA, and the number of Paneth cells in the jejunal crypts, the goblet cells in the colon, the Ki67-positive proliferating cells in the colon, and the Sex-determining region Y-box transcription factor 9+ (SOX9) cells in the jejunum crypts and colon at 7 DPA. The organoid formation rate was increased by high-iron treatments at 3 DPA and 7 DPA. High dietary iron treatment decreased the mRNA level of jejunal jagged canonical Notch ligand 2 (Jag-2) at 0 DPA and bone morphogenetic protein 4 (Bmp4) and neural precursor cell-expressed developmentally downregulated 8 (Nedd8) in the jejunum and colon at 7 DPA, whereas it increased the mRNA expression of the serum/glucocorticoid-regulated kinase 1 (Sgk1) in the colon at 3 DPA. The results suggested that a high dose of iron aggravated intestinal injury but promoted intestinal repair by regulating intestinal epithelial cell renewal and intestinal stem cell activity in adult mice with colitis.

Abstract Background Hepatocellular carcinoma (HCC) is the most common malignant disease worldwide. Although the diagnosis and treatment of HCC have greatly improved in the recent years, there is still a lack of accurate methods to predict the prognosis of patients. Evidence has shown that Hippo signaling in tissues adjacent to HCC plays a significant role in HCC development. In the present study, we aimed to construct a model based on the expression of Hippo‐related genes (HRGs) in tissues adjacent to HCC to predict the prognosis of HCC patients. Methods Gene expression data of paired normal tissues adjacent to HCC (PNTAH) and clinical information were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The HRG signature was constructed using four canonical Hippo‐related pathways. Univariate Cox regression analysis was used to screen survival‐related HRGs. LASSO and multivariate Cox regression analyses were used to construct the prognostic model. The true and false positive rates of the model were confirmed using receiver operating characteristic (ROC) analysis. Results The prognostic model was constructed based on the expression levels of five HRGs (NF2, MYC, BIRC3, CSNK1E, and MINK1) in PNTAH. The mortality rate of HCC patients increased as the risk score determined by the model increased. Furthermore, the risk score was found to be an independent risk factor for the survival of patients. ROC analysis showed that the prognostic model had a better predictive value than the other conventional clinical parameters. Moreover, the reliability of the prognostic model was confirmed in TCGA‐LIHC cohort. A nomogram was generated to predict patient survival. An exploration of the predictive value of the model in HCC tissues indicated that the model is PNTAH‐specific. Conclusions We developed and validated a prognostic model based on the expression levels of five HRGs in PNTAH, and this model should be helpful in predicting the prognosis of patients with HCC.

Thermokarst lakes are formed following ice-rich permafrost thaw and widely distribute in the cold regions with high latitude and elevation. However, the micro-eukaryotic communities (MECs) in thermokarst lakes are not well studied. Employing 18S rRNA gene sequencing, we assessed the biogeography of MECs and their driving factors in sediments of thermokarst lakes across the Qinghai-Tibet Plateau (QTP). Results showed that Diatom, Gastrotricha, Nematozoa, Ciliophora, and Cercozoa were dominant lineages in relative abundance and OTU richness. MECs varied substantially across the lakes in terms of diversity and composition. Structural equation modeling and mantel test showed that both OTU richness and community structure of MECs had close relationships with spatial factors, climatic factors, and sediment properties, particularly with latitude, mean annual precipitation, pH, as well as nutrient concentrations and stoichiometric ratios. Moreover, different groups of microbial eukaryotes (taxonomic groups and co-occurrence modules) responded differentially to the measured environmental variables. The results suggested that the biogeography of sediment MECs of thermokarst lakes on the QTP were jointly controlled by spatial and climatic factors as well as sediment properties. This study provides the first view of the composition, diversity, and underlying drivers of MECs dynamic in surface sediments of thermokarst lakes across the QTP.

Despite much attention on the history of goat evolution, information on origin, demographic history, and expansion route remains controversial. To address these questions, we collected 4,189 published goat DNA sequences including 1,228 sequences from 57 breeds in China and 2,961 sequences including 193 goat breeds from 71 other countries and carried out an integrated analysis. We found goat breeds from South China had the highest genetic diversity of lineage B, and subclades B2 only were found in Southwest China, suggesting that lineage B (particularly, subclade B2) probably originated from Southwest China and its surrounding areas. In addition, in this study, we found that lineage A from South China also presented higher genetic diversity and earlier expansion time (10, 606 years ago), even earlier than breeds from the Middle East. Hence, we speculated that South China and surrounding areas were the origin of lineage B and also the transportation hub for lineage A spreading to North China and Southwest Asia. Furthermore, according to the analysis of correlation between genetic differentiation value λ1 and λ2 and geographical distance, we further confirmed two phases of migration in goat breeds of North China. These results will contribute to a better understanding of the origin and migration history of domestic goat.

Dehydrins (DHNs) belong to group II of late embryogenesis-abundant (LEA) proteins, which are up-regulated in most plants during cold, drought, heat, or salinity stress. Despite the importance of dehydrins for the plants to resist abiotic stresses, it is necessary to obtain plant-derived dehydrins from different biomass. Generally, dehydrin PicW1 from Picea wilsonii is involved in Kn-type dehydrin with five K-segments, which has a variety of biological activities. In this work, Picea wilsonii dehydrin PicW1 was expressed in Escherichia coli and purified by chitin-affinity chromatography and size-exclusion chromatography, which showed as a single band by SDS-PAGE. A cold-sensitive enzyme of lactate dehydrogenase (LDH) is used to explore the protective activities of other proteins. Temperature stress assays showed that PicW1 had an effective protective effect on LDH activity, which was better than that of bovine serum albumin (BSA). This study provides insights into the purification and protective activity of K5 DHNs for the advancement of dehydrin structure and function from biomass.

Abstract Background As a lipid metabolic disorder, non-alcoholic fatty liver disease (NAFLD) is an important cause of cirrhosis and hepatocellular carcinoma, with no effective drug up to date. Previous studies have demonstrated increased methylation levels of key genes in NAFLD, suggesting that hydroxymethylation, a key step in demethylation, may be a possible strategy to reverse NAFLD. TET1 is well known as a key hydroxymethylase, however, its role and mechanism in NAFLD remains unclear. Methods In this study, we utilized TET1 knockout mice, fed with high-fat diet. Furthermore, by ChIP and hMeDIP. TET1 knockdown L02 and HepG2 cell lines. Results Their degree of liver steatosis was more severe than that of wild-type mice, suggesting that TET1 had a significant protective effect against NAFLD. We further found that PPARα, a key regulator of fatty acid oxidation, and its downstream key enzymes ACOX1 and CPT1A, as well as the fatty acid oxidation product β-HB were significantly decreased in TET1 knockout mice. While the key genes for fatty acid synthesis and uptake were not significantly changed, suggesting that TET1 inhibits NAFLD by promoting fatty acid oxidation via PPARα pathway. TET1 was confirmed to directly bind to the promoter of PPARα and elevate its hydroxymethylation level. Conclusions This study is the first to show that TET1 can activate PPARα, promote fatty acid oxidation and inhibit NAFLD progression by hydroxymethylation of PPARα promoter, which may be a new strategy to reverse NAFLD.

BackgroundBreast cancer (BRCA) is a malignant tumor with a high mortality rate and poor prognosis in patients. However, understanding the molecular mechanism of breast cancer is still a challenge.Materials and MethodsIn this study, we constructed co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene-expression profiles and clinical data were integrated to detect breast cancer survival modules and the leading genes related to prognostic risk. Finally, we introduced machine learning algorithms to build a predictive model aiming to discover potential key biomarkers.ResultsA total of 42 prognostic modules for breast cancer were identified. The nomogram analysis showed that 42 modules had good risk assessment performance. Compared to clinical characteristics, the risk values carried by genes in these modules could be used to classify the high-risk and low-risk groups of patients. Further, we found that 16 genes with significant differential expressions and obvious bridging effects might be considered biological markers related to breast cancer. Single-nucleotide polymorphisms on the CYP24A1 transcript induced RNA structural heterogeneity, which affects the molecular regulation of BRCA. In addition, we found for the first time that ABHD11-AS1 was significantly highly expressed in breast cancer.ConclusionWe integrated clinical prognosis information, RNA sequencing data, and drug targets to construct a breast cancer–related risk module. Through bridging effect measurement and machine learning modeling, we evaluated the risk values of the genes in the modules and identified potential biomarkers for breast cancer. The protocol provides new insight into deciphering the molecular mechanism and theoretical basis of BRCA.

S-palmitoylation, catalyzed by a family of 23 zinc finger Asp-His-His-Cys (DHHC) domain-containing (ZDHHC) protein acyltransferases localized on the cell membrane. However, stemness genes modulated by ZDHHCs in lung adenocarcinoma (LUAD) remain to be defined. Previously, we have constructed a network of cancer stem cell genes, including INCENP, based on mRNA stemness indices (mRNAsi) of LUAD. INCENP has the function of a chromosomal passenger complex locating to centromeres, which is performed by the conserved region of its N-terminal domain. INCENP protein with a deletion of the first non-conserved 26 amino acid sequence failed to target centromeres. However, the exact function of the deleted sequence has not been elucidated. To identify novel cancer stem cell-relevant palmitoylated proteins and responsible ZDHHC enzymes in LUAD, we analyzed multi-omics data obtained from the database of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA). ZDHHC5 is distinguished from the ZDHHC family for being up-regulated in mRNA and protein levels and associated with malignant prognosis. ZDHHC5 was positively associated with INCENP, and the correlation score increased with LUAD stages. CSS-Palm results showed Cys15 was the S-palmitoylation site of INCENP. Interestingly, Cys15 locates in the 1–26 aa sequence of INCENP, and is a conserved site across species. As INCENP is a nuclear protein, we predicted that the nuclear localization signal of ZDHHC5 was specific to the importin αβ pathway, and the result of immunofluorescence proves that ZDHHC5 is located in the nucleoplasm, in addition to the plasma membrane. Therefore, our study indicates the S-palmitoylation of INCENP mediated by ZDHHC5 as a potential mechanism of S-palmitoylation to modulate CSCs in LUAD.

A new cell line Japanese flounder spleen (JFSP) derived from the spleen of Japanese flounder (Paralichthys olivaceus) was established and characterized in this study. The JFSP cells grew rapidly at 29 °C, and the optimum fetal bovine serum concentration in the L-15 medium was 15%. Cells were subcultured for more than 80 passages. The JFSP cells have a diploid chromosome number of 2n = 68, which differs from the chromosome number of normal diploid Japanese flounder. The established cells were susceptible to Bohle virus (BIV), Viral hemorrhagic septicemia virus (VHSV), Hirame rhabdovirus (HIRRV), Infectious hematopoietic necrosis virus (IHNV), and Lymphocystis disease virus (LCDV), as evidenced by varying degrees of cytopathic effects (CPE). Replication of the virus in JFSP cells was confirmed by qRT-PCR and transmission electron microscopy. In addition, the expression of four immune-related genes, TRAF3, IL-1β, TNF-α, and TLR2, was differentially altered following viral infection. The results indicated that the cells underwent an antiviral immune response. JFSP cell line is an ideal tool in vitro for virology. The use of fish cell lines to study the immune genes and immune mechanism of fish and to clarify the immune mechanism of fish has important theoretical significance and practical application value for the fundamental prevention and treatment of fish diseases.

For high-energy π0 mesons, the angle between the two final-state photons decreases with the increase in the energy of the π0, which enhances the probability of overlapping electromagnetic showers. The performance of the cluster splitting algorithm in the EMC reconstruction is crucial for the mass resolution measurement of π0 with high energy. The cluster splitting algorithm is based on the theoretical lateral distribution of the electromagnetic showers. A simple implementation of the lateral distribution can be described as a (multi-)exponential function. In a realistic electromagnetic calorimeter, considering the granularity of the detector, the measured energy in a cell is actually the integral of the theoretical energy deposition, which deviates from the exponential function. Based on the simulation of the barrel EMC in the P¯ANDA experiment, a cluster splitting algorithm with a new lateral energy development function is developed. The energy resolution of overlapping showers with high energy has been improved.

A novel nidovirus, CSBV Bces-Po19, was isolated from the marine fish, Japanese flounder (Paralichthys olivaceus). The viral genome was 26,597 nucleotides long and shared 98.62% nucleotide identity with CSBV WHQSR4345. PacBio Sequel and Illumina sequencing were used to perform full-length transcriptome sequencing on CSBV Bces-Po19-sensitive (S) and -resistant (R) Japanese flounder. The results of negative staining revealed bacilliform and spherical virions. There were in total 1444 different genes between CSBV Bces-Po19 S and R groups, with 935 being up-regulated and 513 being down-regulated. Metabolism-, immune-, and RNA-related pathways were significantly enriched. Furthermore, CSBV Bces-Po19 infection induced alternative splicing (AS) events in Japanese flounder; the S group had a higher numbers of AS events (12,352) than the R group (11,452). The number of long non-coding RNA (lncRNA) in the S group, on the other hand, was significantly lower than in the R group. In addition to providing valuable information that sheds more light on CSBV Bces-Po19 infection, these research findings provide further clues for CSBV Bces-Po19 prevention and treatment.