The N545S and K717N substitution at the N-glycosylation sites of the S2 subunit of avian infectious bronchitis virus can significantly enhance viral pathogenicity.

The S2 subunit of infectious bronchitis virus (IBV) is a heavily glycosylated protein that can impact various characteristics of the virus. It is currently known that N-glycosylation modifications are predominantly located on the S2 subunit. However, the exact role of their N-glycosylation modification remains undisclosed. To elucidate the function of these N-glycosylation sites, we identified 14 common sites distributed on the S2 subunit of the 5 genotypes of IBV in present study. Subsequently, we selected 7 sites to generate mutants and assessed their impact on viral virulence, replication ability, and antigenicity. Our finding revealed that only 2 substitutions, N545S and K717N, increased the viral replication titer and antigenicity, and ultimately the pathogenicity in chicks. To delve into the mechanisms underlying this increased pathogenicity, we discovered that K717N can change the structure of antigenic epitopes. The N545S substitution not only influenced antigenic epitope structure, but also enhanced the ability of the virus to enter CEKs during the early stages of viral replication. These results suggest that the enhanced viral pathogenicity associated with N545S and K717N substitutions is multifaceted, with acceleration of the viral membrane fusion process and alterations in epitope structure representing crucial factors in the capability of N-glycosylation modifications to boost viral virulence. These insights provide valuable guidance for the efficient development of live attenuated vaccines.

EMG-YOLO: road crack detection algorithm for edge computing devices.

Introduction: Road cracks significantly shorten the service life of roads. Manual detection methods are inefficient and costly. The YOLOv5 model has made some progress in road crack detection. However, issues arise when deployed on edge computing devices. The main problem is that edge computing devices are directly connected to sensors. This results in the collection of noisy, poor-quality data. This problem adds computational burden to the model, potentially impacting its accuracy. To address these issues, this paper proposes a novel road crack detection algorithm named EMG-YOLO. Methods: First, an Efficient Decoupled Header is introduced in YOLOv5 to optimize the head structure. This approach separates the classification task from the localization task. Each task can then focus on learning its most relevant features. This significantly reduces the model's computational resources and time. It also achieves faster convergence rates. Second, the IOU loss function in the model is upgraded to the MPDIOU loss function. This function works by minimizing the top-left and bottom-right point distances between the predicted bounding box and the actual labeled bounding box. The MPDIOU loss function addresses the complex computation and high computational burden of the current YOLOv5 model. Finally, the GCC3 module replaces the traditional convolution. It performs global context modeling with the input feature map to obtain global context information. This enhances the model's detection capabilities on edge computing devices. Results: Experimental results show that the improved model has better performance in all parameter indicators compared to current mainstream algorithms. The EMG-YOLO model improves the accuracy of the YOLOv5 model by 2.7%. The mAP (0.5) and mAP (0.9) are improved by 2.9% and 0.9%, respectively. The new algorithm also outperforms the YOLOv5 model in complex environments on edge computing devices. Discussion: The EMG-YOLO algorithm proposed in this paper effectively addresses the issues of poor data quality and high computational burden on edge computing devices. This is achieved through optimizing the model head structure, upgrading the loss function, and introducing global context modeling. Experimental results demonstrate significant improvements in both accuracy and efficiency, especially in complex environments. Future research can further optimize this algorithm and explore more lightweight and efficient object detection models for edge computing devices.

The association between cardiac T2*BOLD and quantitative flow ratio (QFR) in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease.

BACKGROUND: T2*BOLD is based on myocardial deoxyhemoglobin content to reflect the state of myocardial oxygenation. Quantitative flow ratio is a tool for assessing coronary blood flow based on invasive coronary angiography. PURPOSE: This study aimed to evaluate the correlation between T2*BOLD and QFR in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. METHODS: Fifty patients with MVCAD with at least 1 significant coronary artery stenosis (diameter stenosis > 50%) and 21 healthy control subjects underwent coronary angiography combined with QFR measurements and cardiovascular magnetic resonance (CMR). QFR ≤ 0.80 was considered to indicate the presence of hemodynamic obstruction. RESULTS: Totally 60 (54%) obstructive vessels had hemodynamic change. Between stenotic coronary arteries (QFR ≤ 0.8) and normal vessels, T2*BOLD showed AUCs of 0.97, 0.69, and 0.91 for left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries and PI displayed AUCs of 0.89, 0.77 and 0.90 (all p > 0.05, except for LAD). The AUCs of T2*BOLD between stenotic coronary arteries (QFR > 0.8) and normal vessels were 0.86, 0.72, and 0.85 for LAD, LCX and RCA; while, PI showed AUCs of 0.93, 0.86, and 0.88, respectively (p > 0.05). Moreover, T2*BOLD displayed AUCs of 0.96, 0.74, and 0.91 for coronary arteries as before between coronary arteries with stenosis (QFR ≤ 0.8 and > 0.8), but the mean PI of LAD, LCX and RCA showed no significant differences between them. CONCLUSION: T2* BOLD and QFR have good correlation in diagnosing stenotic coronary arteries with hemodynamic changes in patients with stable multi-vessel CAD. T2* BOLD is superior to semi-quantitative perfusion imaging in analyzing myocardial ischemia without stress.

Impact of diabetic kidney disease on post-operative complications after primary elective total hip arthroplasty: a nationwide database analysis.

BACKGROUND: The high prevalence of diabetic kidney disease (DKD) in the United States necessitates further investigation into its impact on complications associated with total hip arthroplasty (THA). This study utilizes a large nationwide database to explore risk factors in DKD cases undergoing THA. METHODS: This research utilized a case-control design, leveraging data from the national inpatient sample for the years 2016 to 2019. Employing propensity score matching (PSM), patients diagnosed with DKD were paired on a 1:1 basis with individuals free of DKD, ensuring equivalent age, sex, race, Elixhauser Comorbidity Index (ECI), and insurance coverage. Subsequently, comparisons were drawn between these PSM-matched cohorts, examining their characteristics and the incidence of post-THA complications. Multivariate logistic regression analysis was then employed to evaluate the risk of early complications after surgery. RESULTS: DKD's prevalence in the THA cohort was 2.38%. A 7-year age gap separated DKD and non-DKD patients (74 vs. 67 years, P < 0.0001). Additionally, individuals aged above 75 exhibited a substantial 22.58% increase in DKD risk (49.16% vs. 26.58%, P < 0.0001). Notably, linear regression analysis yielded a significant association between DKD and postoperative acute kidney injury (AKI), with DKD patients demonstrating 2.274-fold greater odds of AKI in contrast with non-DKD individuals (95% CI: 2.091-2.473). CONCLUSIONS: This study demonstrates that DKD is a significant risk factor for AKI in patients undergoing total hip arthroplasty. Optimizing preoperative kidney function through appropriate interventions might decrease the risk of poor prognosis in this population. More prospective research is warranted to investigate the potential of targeted kidney function improvement strategies in reducing AKI rates after THA. The findings of this study hold promise for enhancing preoperative counseling by surgeons, enabling them to provide DKD patients undergoing THA with more precise information regarding the risks associated with their condition.

Large-Scale Serological Survey of Influenza A Virus in South Korean Wild Boar (Sus scrofa).

In this comprehensive large-scale study, conducted from 2015 to 2019, 7,209 wild boars across South Korea were sampled to assess their exposure to influenza A viruses (IAVs). Of these, 250 (3.5%) were found to be IAV-positive by ELISA, and 150 (2.1%) by the hemagglutination inhibition test. Detected subtypes included 23 cases of pandemic 2009 H1N1, six of human seasonal H3N2, three of classical swine H1N1, 13 of triple-reassortant swine H1N2, seven of triple-reassortant swine H3N2, and seven of swine-origin H3N2 variant. Notably, none of the serum samples tested positive for avian IAV subtypes H3N8, H5N3, H7N7, and H9N2 or canine IAV subtype H3N2. This serologic analysis confirmed the exposure of Korean wild boars to various subtypes of swine and human influenza viruses, with some serum samples cross-reacting between swine and human strains, indicating potential infections with multiple IAVs. The results highlight the potential of wild boar as a novel mixing vessel, facilitating the adaptation of IAVs and their spillover to other hosts, including humans. In light of these findings, we recommend regular and frequent surveillance of circulating influenza viruses in the wild boar population as a proactive measure to prevent potential human influenza pandemics and wild boar influenza epizootics.

Fractal analysis of left ventricular trabeculae in heart failure with preserved ejection fraction patients with multivessel coronary artery disease.

OBJECTIVES: Endocardial trabeculae undergo varicose changes and hyperplasia in response to hemodynamic influences and are a variable phenotype reflecting changes in disease. Fractal analysis has been used to analyze the complexity of endocardial trabeculae in a variety of cardiomyopathies. The aim of this paper was to quantify the myocardial trabecular complexity through fractal analysis and to investigate its predictive value for the diagnosis of heart failure with preserved ejection fraction (HFpEF) in patients with multivessel coronary artery disease (CAD). METHODS: The retrospective study population consisted of 97 patients with multivessel CAD, 39 of them were diagnosed with HFpEF, while 46 healthy volunteers were recruited as controls. Fractal dimension (FD) was obtained through fractal analysis of endocardial trabeculae on LV short-axis cine images. Logistic regression analyses were used to confirm the predictors and compare different prediction models. RESULTS: Mean basal FD was significantly higher in patients with HFpEF than in patients without HFpEF or in the healthy group (median: 1.289; IQR: 0.078; p < 0.05). Mean basal FD was also a significant independent predictor in univariate and multivariate logistic regression (OR: 1.107 and 1.043, p < 0.05). Furthermore, adding FD to the prediction model improved the calibration and accuracy of the model (c-index: 0.806). CONCLUSION: The left ventricular FD obtained with fractal analysis can reflect the complexity of myocardial trabeculae and has an independent predictive value for the diagnosis of HFpEF in patients with multivessel CAD. Including FD into the diagnostic model can help improve the diagnosis. CRITICAL RELEVANCE STATEMENT: Differences show in the complexity of endocardial trabeculae in multivessel coronary artery disease patients, and obtaining fractal dimensions (FD) by fractal analysis can help identify heart failure with preserved ejection fraction (HFpEF) patients. KEY POINTS: The complexity of myocardial trabeculae differs among patients with multivessel coronary artery disease. Left ventricular fractal dimensions can reflect the complexity of the myocardial trabecular. Fractal dimensions have predictive value for the diagnosis of heart failure with preserved ejection fraction.

Cleavage of the syncytial protein of J paramyxovirus is required for its ability to promote cell-cell fusion.

Cell-cell fusion mediated by most paramyxovirus requires fusion protein (F) and attachment protein (H, HN, or G). The F protein is proteolytic cleaved to be fusogenically active. J paramyxovirus (JPV) has a unique feature in the family Paramyxoviridae: It encodes an integral membrane protein, syncytial protein (SP, formerly known as transmembrane protein, TM), which is essential in JPV-promoted cell-cell fusion (i.e., syncytial). In this study, we report that cleavage of SP is essential for its syncytial-promoting activity. We have identified the cleavage site of SP at amino acid residues 172 to 175, LKTG, and deletion of the "LKTG" residues abolished SP protein cleavage and its ability to promote cell-cell fusion. Replacing the cleavage site LKTG with a factor Xa protease cleavage site allows cleavage of the SP with factor Xa protease and restores its ability to promote cell-cell fusion. Furthermore, results from a hemifusion assay indicate that cleavage of SP plays an important role in the progression from the intermediate hemifusion state to a complete fusion. This work indicates that SP has many characteristics of a fusion protein. We propose that SP is likely a cell-cell fusion-promoting protein.

EZH2 inhibition induces senescence via ERK1/2 signaling pathway in multiple myeloma.

Epigenetic modifications play an important role in cellular senescence, and enhancer of zeste homolog 2 (EZH2) is a key methyltransferase involved in epigenetic remodeling in multiple myeloma (MM) cells. We have previously demonstrated that GSK126, a specific EZH2 inhibitor, exhibits anti-MM therapeutic efficacy and safety in vivo and in vitro; however, its specific mechanism remains unclear. This study shows that GSK126 induces cellular senescence in MM, which is characterized by the accumulation of senescence-associated heterochromatin foci (SAHF) and p21, and increased senescence-associated ß galactosidase activity. Furthermore, EZH2 is inhibited in ribonucleotide reductase regulatory subunit M2 (RRM2)-overexpressing OCI-MY5 and RPMI-8226 cells. RRM2 overexpression inhibits the methyltransferase function of EZH2 and promotes its degradation through the ubiquitin-proteasome pathway, thereby inducing cellular senescence. In this senescence model, Lamin B1, a key component of the nuclear envelope and a marker of senescence, does not decrease but instead undergoes aberrant accumulation. Meanwhile, phosphorylation of extracellular signal-regulated protein kinase (ERK1/2) is significantly increased. The inhibition of ERK1/2 phosphorylation in turn partially restores Lamin B1 level and alleviates senescence. These findings suggest that EZH2 inhibition increases Lamin B1 level and induces senescence by promoting ERK1/2 phosphorylation. These data indicate that EZH2 plays an important role in MM cellular senescence and provide insights into the relationships among Lamin B1, p-ERK1/2, and cellular senescence.

A temperature-sensitive and interferon-silent Sendai virus vector for CRISPR-Cas9 delivery and gene editing in primary human cells.

The transformative potential of gene editing technologies hinges on the development of safe and effective delivery methods. In this study, we developed a temperature-sensitive and interferon-silent Sendai virus (ts SeV) as a novel delivery vector for CRISPR-Cas9 and for efficient gene editing in sensitive human cell types without inducing IFN responses. ts SeV demonstrates unprecedented transduction efficiency in human CD34+ hematopoietic stem and progenitor cells (HSPCs) including transduction of the CD34+/CD38-/CD45RA-/CD90+(Thy1+)/CD49fhigh stem cell enriched subpopulation. The frequency of CCR5 editing exceeded 90% and bi-allelic CCR5 editing exceeded 70% resulting in significant inhibition of HIV-1 infection in primary human CD14+ monocytes. These results demonstrate the potential of the ts SeV platform as a safe, efficient, and flexible addition to the current gene-editing tool delivery methods, which may help to further expand the possibilities in personalized medicine and the treatment of genetic disorders.

Iodine Status and Its Influencing Factors in Hospitalized and Healthy Preschool-Age Children.

Iodine is a trace element necessary for synthesizing thyroid hormones. It is especially crucial for the neurodevelopment and intellectual development of children. Preschool-age children admitted to the hospital tend to have more fragile physical and mental health, but few studies demonstrate their iodine status. Our study aimed to investigate the iodine status of hospitalized and healthy preschool-age children and to explore the factors influencing them. From January to December 2021, 426 children aged 3-6 years were admitted to the respiratory department for pneumonia, bronchopneumonia, or bronchiectasis, but they could eat normally and were recruited as hospitalized children. Six hundred ten healthy children aged 3-6 years were included. We collected anthropometric measurements and urine samples from hospitalized and healthy preschool-age children, and iodine status was assessed through urinary iodine concentration (UIC) and urinary iodine/creatinine ratio (UI/Cr). UIC was 40.1 and 166.1 µg/L for hospitalized and healthy preschool-age children, respectively (P < 0.001). Urinary creatinine concentration (UCr) was 0.2 and 0.8 g/L for hospitalized and healthy preschool-age children, respectively (P < 0.001). UIC decreased with increasing height z-scores in hospitalized children (Spearman's rho = -0.11, P = 0.022). A significantly increased risk of UIC < 100 µg/L was found in hospitalized children (OR = 9.1 (6.8, 12.2), P < 0.001) when compared to healthy children. In conclusion, hospitalized preschool-age children are likelier to have iodine insufficiency than healthy preschool-age children, especially those with good linear growth. Measures should be implemented to ensure adequate iodine intake of preschool-age children during hospitalization to avoid affecting their intellectual and physical development. Due to lower UCr in hospitalized children, creatinine is not appropriate for assessing iodine status in hospitalized children.

The Effects of Resveratrol and Apigenin on Jejunal Oxidative Injury in Ducks and on Immortalized Duck Intestinal Epithelial Cells Exposed to H2O2.

Oxidative stress increases the apoptosis of intestinal epithelial cells and impairs intestinal epithelial cell renewal, which further promotes intestinal barrier dysfunction and even death. Extensive evidence supports that resveratrol and apigenin have antioxidant, anti-inflammatory, and antiproliferative properties. Here, we investigated the ability of these two compounds to alleviate diquat-induced jejunal oxidative stress and morphological injury, using the duck as a model, as well as the effects of apigenin on oxidative stress induced by H2O2 in immortalized duck intestinal epithelial cells (IDECs). Ducks were randomly assigned to the following four groups, with five replicates: a control (CON) group, a diquat-challenged (DIQ) group, a resveratrol (500 mg/kg) + diquat (RES) group, and an apigenin (500 mg/kg) + diquat (API) group. We found that serum catalase (CAT) activity and total antioxidant capacity (T-AOC) markedly reduced in the RES and API groups as compared to the DIQ group (p < 0.05); moreover, serum S superoxide dismutase (SOD) levels increased significantly in the API group as compared to the DIQ group (p < 0.05). In jejunal mucosa, the malondialdehyde (MDA) content in the RES and API groups decreased more than that in the DIQ group (p < 0.05). In addition, the jejunal expression levels of the NRF2 and GCLM genes in the RES and API groups increased notably compared with those in the DIQ group (p < 0.05); meanwhile, CAT activity in the RES and API groups was markedly elevated compared with that in the CON group (p < 0.05). In IDECs, apigenin significantly restrained the H2O2-mediated increase in MDA content and decrease in CAT levels (p < 0.05). Furthermore, apigenin increased the protein expression of p-NRF2, NRF2, p-AKT, and p-P38; downregulated that of cleaved caspase-3 and cleaved caspase-9; and reduced the ratio of Bax/Bcl-2 in H2O2-treated IDECs (p < 0.05). In conclusion, resveratrol and apigenin can be used as natural feed additives to protect against jejunal oxidative stress in ducks.

Quality of life and regional economic development: Evidence from China.

With the development of China's economy entering a new stage, the quality of life, which centers on the well-being of residents, provides an essential hand in promoting the transformation of the regional economy from high-speed development to high-quality development. Based on a panel threshold regression model, we examine in this paper whether quality of life helps regional economies realize developmental convergence. The research shows that: (1) The quality of life overall can promote regional economic development and passes the series test with relatively robust results. (2) The quality of life has a non-linear effect on regional economic growth, which is mainly manifested in the fact that the impact is more significant in regions with higher levels of quality of life and weaker in regions with lagging quality of life and may widen the gap between regions at the same time. (3) We categorize the study regions to test further regional heterogeneity based on regional location and development status. At the Quality of Life Level-I regions, their influence on economic development has a more substantial pulling effect. Therefore, each region should seize the strategic opportunity to improve the quality of life, focus on the balanced development of the quality of life, strengthen policy support and social security, and strive to promote the coordinated development of China's regional economy.

Characteristics and efficacy of traditional Chinese medicine in the therapeutic strategy of chronic coronary syndrome: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Chronic coronary syndrome (CCS) has always been controversial in its therapeutic strategy. Although invasive treatment and optimal medication therapy (OMT) are the most commonly used treatments, doctors continue to debate the best strategy. However, traditional Chinese medicine (TCM) for CCS is effective clinically. METHODS: To identify potentially eligible observational and experimental studies, we searched Pubmed, the Web of Science, and the China National Knowledge Internet. To be eligible, studies had to report with end-of treatment outcomes, such as major adverse cardiac events (MACE), deaths from myocardial infarctions (MI), all-cause mortality, angina, cardiac mortality, the effectiveness rate of electrocardiographs, and the reduction rate of the Nitroglycerin tablets. Risk differences (RDs) and 95 % confidence intervals (95 % CIs) were calculated based on random-effects models or fixed-effects models. Citation screening, data abstraction, risk assessment, and strength-of-evidence grading were completed by 2 independent reviewers. RESULTS: In Section 1 (13 studies, involving 17,287 patients), showed no significant difference between invasive treatment and medication treatment in MACE (RD = -0.04, 95% CI = -0.08 to 0.00, I2 = 76.4 %), all-cause mortality (RD = -0.01, 95%CI = -0.022 to 0.01, I2 = 73.44 %), MI (RD = 0.00, 95%CI = -0.00 to 0.01, I2 = 0.00 %) and cardiac mortality (RD = 0.00, 95 %CI = -0.01 to 0.01, I2 = 34.9 %). In Section 2 (21 studies, including 1820 patients), compared with WM treatment, TCM + WM treatment increased ECG effectiveness by 18 %, angina effectiveness by 20 %, and stopping or reducing Nitroglycerin tablets by 20 %. In Section 3 (25 studies, including 2859 patients) showed that TCM revealed a better electrocardiogram effective rate (RD = 0.10, 95 %CI = 0.05 to 0.14, I2 = 44.7 %) and angina effective rate (RD = 0.12, 95 %CI = 0.09 to 0.15, I2 = 44.9 %). We identified that TCM treatment properties of "Circulating blood and transforming stasis" and application of warm/heat-properties medicines were frequently used in CCS treatment. CONCLUSIONS: TCM treatment has shown superior beneficial cardioprotective in CCS therapy strategy, among which "Circulating blood and transforming stasis" and the application of warm/heat-properties medicine are its characteristics.

ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments.

Vision-language navigation is a task that requires an agent to follow instructions to navigate in environments. It becomes increasingly crucial in the field of embodied AI, with potential applications in autonomous navigation, search and rescue, and human-robot interaction. In this paper, we propose to address a more practical yet challenging counterpart setting - vision-language navigation in continuous environments (VLN-CE). To develop a robust VLN-CE agent, we propose a new navigation framework, ETPNav, which focuses on two critical skills: 1) the capability to abstract environments and generate long-range navigation plans, and 2) the ability of obstacle-avoiding control in continuous environments. ETPNav performs online topological mapping of environments by self-organizing predicted waypoints along a traversed path, without prior environmental experience. It privileges the agent to break down the navigation procedure into high-level planning and low-level control. Concurrently, ETPNav utilizes a transformer-based cross-modal planner to generate navigation plans based on topological maps and instructions. The plan is then performed through an obstacle-avoiding controller that leverages a trial-and-error heuristic to prevent navigation from getting stuck in obstacles. Experimental results demonstrate the effectiveness of the proposed method. ETPNav yields more than 10% and 20% improvements over prior state-of-the-art on R2R-CE and RxR-CE datasets, respectively. Our code is available at https://github.com/MarSaKi/ETPNav.

SEAOP: a statistical ensemble approach for outlier detection in quantitative proteomics data.

Quality control in quantitative proteomics is a persistent challenge, particularly in identifying and managing outliers. Unsupervised learning models, which rely on data structure rather than predefined labels, offer potential solutions. However, without clear labels, their effectiveness might be compromised. Single models are susceptible to the randomness of parameters and initialization, which can result in a high rate of false positives. Ensemble models, on the other hand, have shown capabilities in effectively mitigating the impacts of such randomness and assisting in accurately detecting true outliers. Therefore, we introduced SEAOP, a Python toolbox that utilizes an ensemble mechanism by integrating multi-round data management and a statistics-based decision pipeline with multiple models. Specifically, SEAOP uses multi-round resampling to create diverse sub-data spaces and employs outlier detection methods to identify candidate outliers in each space. Candidates are then aggregated as confirmed outliers via a chi-square test, adhering to a 95% confidence level, to ensure the precision of the unsupervised approaches. Additionally, SEAOP introduces a visualization strategy, specifically designed to intuitively and effectively display the distribution of both outlier and non-outlier samples. Optimal hyperparameter models of SEAOP for outlier detection were identified by using a gradient-simulated standard dataset and Mann-Kendall trend test. The performance of the SEAOP toolbox was evaluated using three experimental datasets, confirming its reliability and accuracy in handling quantitative proteomics.

Spatiotemporal link between El Niño Southern Oscillation (ENSO), extreme heat, and thermal stress in the Asia-Pacific region.

Climate change is closely monitored and numerous studies reports increasing air temperature and weather extremes across the globe. As a direct consequence of the increase of global temperature, the increased heat stress is becoming a global threat to public health. While most climate change and epidemiological studies focus on air temperature to explain the increasing risks, heat strain can be predicted using comprehensive indices such as Universal Thermal Climate Index (UTCI). The Asia-Pacific region is prone to thermal stress and the high population densities in the region impose high health risk. This study evaluated the air temperature and UTCI trends between 1990 and 2019 and found significant increasing trends for air temperature for the whole region while the increases of UTCI are not as pronounced and mainly found in the northern part of the region. These results indicate that even though air temperature is increasing, the risks of heat stress when assessed using UTCI may be alleviated by other factors. The associations between El Niño Southern Oscillation (ENSO) and heat stress was evaluated on a seasonal level and the strongest regional responses were found during December-January (DJF) and March-May (MAM).

Computational-aided analysis of the pathway and mechanism of dichloroacetonitrile formation from phenylalanine upon chloramination.

Dichloroacetonitrile (DCAN) is an emerging disinfection by-product (DBP) that is widespread in drinking water. However, the pathway for DCAN formation from aromatic amino acids remains unclear, leading to a lack of an understanding of its explicit fate during chloramination. In this study, we investigated the specific formation mechanism of DCAN during the chloramination of phenylalanine based on reaction kinetics and chemical thermodynamics. The reason for differences between aldehyde and decarboxylation pathways was explained, and kinetic parameters of the pathways were obtained through quantum chemistry calculations. The results showed that the reaction rate constant of the rate-limiting step of the aldehyde pathway with 1.9 × 10-11 s-1 was significantly higher than that of decarboxylation (3.6 × 10-16 s-1 M-1), suggesting that the aldehyde pathway is the main reaction pathway for DCAN formation during the chloramination of phenylalanine to produce DCAN. Subsequently, theoretical calculations were performed to elucidate the effect of pH on the formation mechanism, which aligned well with the experimental results. Dehydrohalogenation was found to be the rate-limiting step under acidic conditions with reaction rate constants higher than those of the rate-limiting step (expulsion of amines) under neutral conditions, increasing the rate of DCAN formation. This study highlights the differences in DCAN formation between the decarboxylation and aldehyde pathways during the chloramination of precursors at both molecular and kinetic levels, contributing to a comprehensive understanding of the reaction mechanisms by which aromatic free amino acids generate DCAN.

Phosphorus recovery from sewage sludge via Mg-air battery system.

A pressing issue in contemporary society is the resource scarcity of phosphorus. Operating on the principle of electrochemical reactions between Mg as the anode and oxygen from air as the cathode, Mg-air batteries (MAB) have been employed to provide new prospects for phosphorus recovery in struvite form. Different phosphorus concentrations and reaction time impact struvite generation in MAB systems; however, the exact mechanism has rarely been investigated. We investigated how varying the initial phosphorus concentration and the reaction time affects phosphorus recovery, electricity generation, and the efficiency of struvite production in MAB. Additionally, we examine the impact of solid carbon sources on phosphorus transformation in sludge. The findings revealed that the incorporation of solid carbon sources facilitated the release of phosphate by changing phosphorus speciation. The electrolyte derived from the conditioned sludge filtrate exhibited a remarkable phosphorus removal efficiency of 91.7 % within 1 h, yielding the highest struvite purity of ∼70 %, whereas that using raw sludge filtrate or extending the reaction time was found to be less effective, even reducing struvite formation. Furthermore, different electrolytes influence the system's ability to passivate anode, and electrolytes with higher phosphorus concentrations have better electricity production performance. The results by Visual MINTEQ model confirmed that longer reaction times and lower initial phosphorus concentrations can negatively affect struvite formation by introducing Mg3(PO4)2 and Mg(OH)2. The integration of agricultural waste as carbon sources with MAB for phosphorus recovery represents a potential methodology for struvite recuperation from sewage sludge, thereby heralding a sustainable strategy for resource recovery.

Personalized Driver Gene Prediction Using Graph Convolutional Networks with Conditional Random Fields.

Cancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high heterogeneity. Thus, the discovery of driver genes at the individual level is becoming more valuable but is a great challenge. Although there have been some computational methods proposed to tackle this challenge, few can cover all patient samples well, and there is still room for performance improvement. In this study, to identify individual-level driver genes more efficiently, we propose the PDGCN method. PDGCN integrates multiple types of data features, including mutation, expression, methylation, copy number data, and system-level gene features, along with network structural features extracted using Node2vec in order to construct a sample-gene interaction network. Prediction is performed using a graphical convolutional neural network model with a conditional random field layer, which is able to better combine the network structural features with biological attribute features. Experiments on the ACC (Adrenocortical Cancer) and KICH (Kidney Chromophobe) datasets from TCGA (The Cancer Genome Atlas) demonstrated that the method performs better compared to other similar methods. It can identify not only frequently mutated driver genes, but also rare candidate driver genes and novel biomarker genes. The results of the survival and enrichment analyses of these detected genes demonstrate that the method can identify important driver genes at the individual level.

Prognostic value of left ventricular trabeculae fractal analysis in patients with dilated cardiomyopathy.

BACKGROUND: The prognostic value of left ventricular (LV) myocardial trabecular complexity on cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) remains unknown. This study aimed to evaluate the prognostic value of LV myocardial trabecular complexity using fractal analysis in patients with DCM. METHODS: Consecutive patients with DCM who underwent CMR between March 2017 and November 2021 at two hospitals were prospectively enrolled. The primary endpoints were defined as the combination of all-cause death and heart failure hospitalization. The events of cardiac death alone were defined as the secondary endpoints.LV trabeculae complexity was quantified by measuring the fractal dimension (FD) of the endocardial border based on fractal geometry on CMR. Cox proportional hazards regression and Kaplan-Meier survival analysis were used to examine the association between variables and outcomes. The incremental prognostic value of FD was assessed in nested models. RESULTS: A total of 403 patients with DCM (49.31 ± 14.68 years, 69% male) were recruited. After a median follow-up of 43 months (interquartile range, 28-55 months), 87 and 24 patients reached the primary and secondary endpoints, respectively. Age, heart rate, New York Heart Association functional class >II, N-terminal pro-B-type natriuretic peptide, LV ejection fraction, LV end-diastolic volume index, LV end-systolic volume index, LV mass index, presence of late gadolinium enhancement, global FD, LV mean apical FD, and LV maximal apical FD were univariably associated with the outcomes (all P < 0.05). After multivariate adjustment, LV maximal apical FD remained a significant independent predictor of outcome [hazard ratio = 1.179 (1.116, 1.246), P < 0.001]. The addition of LV maximal apical FD in the nested models added incremental prognostic value to other common clinical and imaging risk factors (all <0.001; C-statistic: 0.84-0.88, P < 0.001). CONCLUSION: LV maximal apical FD was an independent predictor of the adverse clinical outcomes in patients with DCM and provided incremental prognostic value over conventional clinical and imaging risk factors.