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Abstract Purpose This study aims to investigate the association of serum TSH with BMD in Chinese adults with normal thyroid function. Methods These participants were divided into tertiles based on serum TSH levels. Linear regression model and multinomial logistic regression models were used to analyze the associations of continuous BMD and categorical BMD with serum TSH, respectively. Results In women younger than 60 years, BMD decreased with the increase of TSH at normal level, while in women older than 60 years, BMD increased with the increase of TSH at normal level; besides, the BMD of women younger than 60 years old was significantly higher than that of women over 60 years old (156.05 ± 39.34 mg/cm3 vs. 86.95 ± 29.51 mg/cm3, P

Objective To address the challenge of difficult fault identification in rail transit vehicle bogie axle box bearings under rail service conditions, it is necessary to investigate the acoustic characteristics of these faults. Method Focusing on the faulty axle box bearings of rail transit vehicle bogies as research object, by adding external loads and excitations and introducing irregular faults, a dynamics model of the axle box bearing system is established in conjunction with the rotor-bearing system. Based on the pulsating point sound source radiation method, numerical simulation software is used to construct an irregular fault sound signal model for the inner and outer rings of the bearings. The fault characteristics of inner and outer rings of axle box bearings under rail service conditions, the impact of load and rotational speed on the fault characteristics parameters of bearing sound signals are explored. Experiments are conducted on an axle box bearing test bench under different working conditions to capture the acoustic sound signals of faulty bearings, and the results are analyzed. Result & Conclusion The sound signals of both faulty and normal bearings of inner and outer rings exhibit corresponding characteristic frequencies and harmonics. However, there are modulation frequencies of the rotational frequencies near the harmonics of the inner ring fault bearing sound signals. As the rotational speed increases, the characteristic parameters of both inner and outer ring faulty and normal bearings exhibit a distinctive and obvious positive correlation trend. Specifically, the time-domain waveform indicators decrease with increasing rotational speed, while the amplitude of the characteristic frequencies increases linearly with rotational speed. As the load increases, the characteristic parameters of both inner and outer ring faulty and normal bearings also all show a distinctive and obvious positive correlation, among which the time-domain variance indicators increase with higher loads, and the amplitude of the characteristic frequencies increases linearly as load increases.

Oolong tea was highly favored by consumers for its rich aroma. However, there was significant loss of fragrance in Oolong tea products during processing and storage, urgently necessitating the development of corresponding technologies to stabilize aroma molecules. Addressing this, this study investigated the stabilization of aroma compounds in Rougui Oolong tea. Employing spinning cone column distillation, volatile organic compounds (VOCs) were extracted from the tea. The effect of hydroxypropyl-β-cyclodextrin on inhibiting the aromatic loss of these extracted VOCs during storage was assessed using gas chromatography-ion mobility spectrometry. Results showed that after 7, 21, and 42 days of storage at room temperature (25 ℃), the samples treated with hydroxypropyl-β-cyclodextrin (experimental group) consistently contained significantly higher quantities of VOCs compared to the untreated controls (P

Deoxynivalenol (DON) is a mycotoxin that is produced by various species of Fusarium and is ubiquitous in food and feed. At low concentrations, it can cause metabolic disorders in animals and humans and, at high concentrations, it can lead to pathological changes in the body. The impact of DON on human/animal health and animal productivity has thus attracted a great deal of attention around the world. DON causes severe damage to the intestine, including compromised intestinal barrier, mucosal damage, weakened immune function, and alterations in gut microbiota composition. These effects exacerbate intestinal infections and inflammation in livestock and poultry, posing adverse effects on overall health. Furthermore, research into biological methods for DON detoxification is a crucial avenue for future studies. This includes the utilization of adsorption, enzymatic degradation, and other biological approaches to mitigate DON’s impact, offering new strategies for prevention and treatment of DON-induced diseases. Future research will focus on identifying highly efficient detoxifying microorganisms or enzymes to reduce DON levels in food and feed, thereby mitigating its risks to both animals and human health.

Abstract Background Promoting the work adaptation of nurses returning to work after childbirth is key to improving their physical and mental health and ensuring the quality of nursing care. Although postpartum nurses have reported high work stress and poor adaptation after returning to work, little is known regarding the experiences, problems and further needs. This study aimed to explore the adaptation experiences of postpartum nurses returning to work. Methods This was a qualitative study with descriptive phenomenological approach. Individual semi-structured interviews were conducted between March and May 2023 in four tertiary hospitals in Changsha, mainland China, which were selected using convenience sampling. A total of 16 postpartum nurses returning to work within one year were recruited using purposive sampling and maximum variation sampling. The interviews were analysed using the Colaizzi’s 7-step method. Results ‘Breakdown and healing’ is a strong thread in postpartum nurses’ work adaptation. It links 13 subthemes in the interview data, which can be grouped under three overarching themes: (a) changes and challenges of multiple roles; (b) self-coping and social support; and (c) further needs after returning to work. The phrase ‘breakdown and healing’ reflects the mutual relationship between stress and coping among postpartum nurses. The changes and challenges associated with being required to fulfil multiple roles of mothers, wives and nurses make the subjects feel on the verge of ‘breakdown’. When returning to work, most of them move slowly towards ‘healing’ through positive self-management and support from their partners, families, supervisors and colleagues. Moreover, their ongoing demands and unsolved problems – such as their desire for a workplace that is friendly and serves their needs – were generated by the constant process of ‘breakdown and healing’. Conclusions Understanding how postpartum nurses returning to work perceive adaptation experiences is essential for nursing managers, who can use the findings to implement targeted measures to shorten postpartum nurses’ maladaptation period after returning to work and promote their work adaptation. This study underscores the critical importance of personalized return-to-work training, flexible work arrangements, support from colleagues and managers, well-established maternal facilities and services, and targeted policy efforts in enhancing postpartum nurses’ work adaptation.

Abstract Aims Nonalcoholic fatty liver disease (NAFLD) is a common complication in snoring patients, especially in patients with obstructive sleep apnea syndrome (OSA). Triglyceride-glucose (TyG) index was a simple indicator of metabolic status and a surrogate marker of insulin resistance. This study aimed to explore the relationship between NAFLD and TyG index in snoring patients. Methods A retrospective study was conducted. The successive snoring patients enrolled in the Sleep Center of the First Affiliated Hospital of Fujian Medical University and had abdominal ultrasonography were included. The clinical characteristics of patients in different quartile TyG groups were compared. The relationship of the TyG index and NAFLD were valued via logistic regression models and restricted cubic spline analysis. The value of TyG index in predicting NAFLD was determined by receiver operating characteristic curve (ROC curve). Results A total of 463 NAFLD cases were found among the 654 snoring patients. TyG index was a risk factor of NAFLD in snoring patients (OR = 2.38, 95% CI = 1.71–3.36). The risk of NAFLD was much higher in patients with the highest quartile of TyG index (OR = 5.12, 95% CI = 2.85–9.22), compared with the lowest quartile group. Restricted cubic spline (RCS) analysis showed a significant dose-response relationship between TyG index and risk of NAFLD (p for non-linearity

Abstract Background Since May 2022, mpox outbreaks have been occurring in non-mpox endemic areas, with the main population affected being men who have sex with men (MSM). Outbreak prevention and control depend not only on the effectiveness of vaccines but also on people’s willingness to receive these vaccines. Currently, there is lack of synthesis on the overall rates and influence factors of MSMs’ willingness to vaccinate against mpox. Therefore, we systematically reviewed studies that assessed the willingness of MSM to receive mpox vaccine. Methods Studies reporting mpox vaccination intentions among MSM were included by searching five databases (PubMed, Web of Science, EMBASE, CINAHL, and SCOPUS) from inception to May 12, 2024. The quality of the included literature was assessed using Joanna Briggs Institute’s critical appraisal tool. The data analysis software is Stata17. The systematic review has been registered with Prospero (registration ID: CRD42023452357). Results Twenty cross-sectional studies were included in the review. Meta-analysis results showed that the pooled willingness rate of vaccinate against mpox was 77.0% (95% CI: 73-81%, I2 = 99.4%). According to subgroup analysis, study countries (P = 0.002), research sample size (P = 0.001), and whether participants were infected with HIV (P = 0.002) may be sources of heterogeneity. The results of the meta-analysis of influencing factors showed that more number of sexual partners (OR: 2.24, 95%CI: 1.86–2.69), pre-exposure prophylaxis use (OR: 6.04, 95%CI: 4.80–7.61), history of sexually transmitted infections (OR: 2.96, 95%CI: 2.33–3.76), confidence in the vaccine’s effectiveness (OR: 2.79, 95%CI: 2.04–3.80) and safety (OR: 10.89, 95%CI: 5.22–22.72), fear of mpox infection (OR: 2.47, 95%CI: 2.11–2.89) and epidemics (OR: 2.87, 95%CI: 2.22–3.70), high mpox knowledge (OR: 2.35, 95%CI: 1.51–3.66), and the belief that people at high risk should be prioritized for vaccination (OR: 3.09, 95%CI: 1.40–6.84) were the facilitators of vaccine willingness. In addition, as a secondary outcome, meta-analysis results showed a pooled unwillingness rate of 16% (95% CI: 13-20%, I2 = 98.1%, 9 studies). Conclusion Willingness to vaccinate mpox was high among MSM, but some participants still had negative attitudes towards vaccination. Therefore, the Ministry of Public Health should develop targeted and effective strategies against those influencing factors to prevent and manage mpox outbreaks.

Abstract Purpose To compare the clinical outcomes between nonsurgical and surgical treatment of distal radius fracture. Methods We performed a systematic literature search by using multiple databases, including Medline, PubMed, and Cochrane. All databases were searched from the earliest records through February 2023. The study compared nonsurgical versus surgical treatment of distal radius fractures and included only randomized controlled trials (RCTS). Results There were seventeen randomized controlled trials retrieved. A total of 1730 patients were included: 862 in the nonsurgical group and 868 in the surgical group. The results showed a significant reduction in DASH score with surgical treatment (WMD 3.98, 95% CI (2.00, 5.95), P

Fast homogenization without incipient melting is the key to designing solution heat treatment (SHT) process for single crystal superalloys. In this paper, a multicomponent phase-field model coupled with solidus temperature is developed for dynamically tracking incipient melting temperature, TIM, of alloy during SHT. The simulation process runs completely automatically only by inputting the composition information of as-cast specimen. Based on the obtained TIM-time profile, the holding temperature and the time of SHT are determined. Applying this approach to Co–30Ni–11Al–4W–1Ta–4Ti–5Cr single crystal specimen, a gradual increased TIM from 1247 °C to 1293 °C within 72,000 s is obtained, and thus a stepwise SHT process with a short time of less than 20 h is designed. The experimental verification shows that after SHT, the segregation coefficient of the slowest diffusing element W decreased from more than 2 to 1.065, the content of harmful secondary phase has decreased to below 0.1%, and no incipient melting occurs.

Based on the coseismic response data of water temperature and water level of 26 observation wells in Yunnan well network from 2008 to 2023, the coseismic response characteristics of water temperature and water level of each observation well were compared and analyzed with 8 earthquakes that have a significant impact on Yunnan region. The coseismic response mechanism was discussed from the perspectives of seismic wave energy density, lithology, control of fault zone and dynamic coordination. The results indicate that the response of water temperature and water level in the well pattern of Yunnan to the far-field earthquakes is more significant than near earthquakes, with the response primarily concentrated in the middle of Yunnan. The water level exhibits a more pronounced response than the water temperature. The coseismic variation of water level is mainly characterized by oscillation and rise, while the water temperature is mainly characterized by pulses. Dehong Fapa Dian No.22 well and Lijiang Xiangshan well have better seismic reflection performance in Yunnan well pattern. On the other hand, No.06 well in Jianchuan, No.01 well in Huize Gangou Dian, Xiaoshao well in Kunming Guandu District, Dayao geothermal well, and Nanhua Zhen 2 well exhibit weaker coseismic responses compared to the other 21 wells. Further analysis shows that the linear fitting correlation coefficient between seismic wave energy density and epicenter distance is greater than −0.9, which is significantly negative correlation and positive correlation with magnitude, and shows the corresponding relationship between energy density and permeability coefficient. Finally, we analyzed the mechanism of coseismic response of water temperature and water level.

Abstract Background Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastating clinical complication seriously affecting the therapeutic outcome of preterm infants. Hence, early prevention and timely diagnosis prior to pathological change is the key to reducing morbidity and improving prognosis. Our primary objective is to utilize machine learning techniques to build predictive models that could accurately identify BPD infants at risk of developing PH. Methods The data utilized in this study were collected from neonatology departments of four tertiary-level hospitals in China. To address the issue of imbalanced data, oversampling algorithms synthetic minority over-sampling technique (SMOTE) was applied to improve the model. Results Seven hundred sixty one clinical records were collected in our study. Following data pre-processing and feature selection, 5 of the 46 features were used to build models, including duration of invasive respiratory support (day), the severity of BPD, ventilator-associated pneumonia, pulmonary hemorrhage, and early-onset PH. Four machine learning models were applied to predictive learning, and after comprehensive selection a model was ultimately selected. The model achieved 93.8% sensitivity, 85.0% accuracy, and 0.933 AUC. A score of the logistic regression formula greater than 0 was identified as a warning sign of BPD-PH. Conclusions We comprehensively compared different machine learning models and ultimately obtained a good prognosis model which was sufficient to support pediatric clinicians to make early diagnosis and formulate a better treatment plan for pediatric patients with BPD-PH.

Abstracts Coinfusion of unrelated cord blood (UCB) units in haploidentical hematopoietic cell transplantation (haplo-HCT) (haplo-cord HCT) for hematopoietic malignancies showed promising results in previous reports, but the efficiency of haplo-cord HCT in acute myeloid leukemia (AML) still lacks sufficient evidence. This multicenter, randomized, phase 3 trial (ClinicalTrials.gov NCT03719534) aimed to assess the efficacy and safety of haplo-cord HCT in AML patients. A total of 268 eligible patients aged 18–60 years, diagnosed with measurable residual disease in AML (excluding acute promyelocytic leukemia), with available haploidentical donors and suitable for allotransplantation, were randomly allocated (1:1) to receive haplo-cord HCT (n = 134) or haplo-HCT (n = 134). The 3-year overall survival (OS) was the primary endpoint in this study. Overall median follow-up was 36.50 months (IQR 24.75–46.50). The 3-year OS of Haplo-cord HCT group was better than haplo-HCT group (80.5%, 95% confidence interval [CI]: 73.7–87.9 vs. 67.8% 95% CI 60.0–76.5, p = 0.013). Favorable progression-free survival (70.3%, 95% CI 62.6–78.8 vs. 57.6%, 95% CI 49.6–67.0, p = 0.012) and cumulative incidence of relapse (12.1%, 95% CI 12.0–12.2 vs. 30.3%, 95% CI 30.1–30.4, p = 0.024) were observed in haplo-cord HCT group. Grade 3–4 adverse events (AEs) within two years posttransplantation in the two groups were similar. Haplo-cord HCT patients exhibited a faster cumulative incidence of neutrophil recovery (p = 0.026) and increased T-cell reconstitution in the early period posttransplantation. Haplo-cord HCT can improve OS in AML patients without excessive AEs, which may exert additional benefits for recipients of haplo-HCT.

Abstract Background To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. Methods Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. Results Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P

Abstract To handle the disturbances and uncertainties issue in the control of the stabilized platform toolface angle, a composite control approach based on a backstepping sliding mode control (BSMC) method with a nonlinear disturbance observer (NDO) is proposed. First, a nonlinear mathematical model of the stabilized platform is established, and the NDO is employed to observe and compensate for the external disturbance. Then, the BSMC control approach based on the nonlinear mathematical model is designed to improve the robustness of the stabilized platform control system. The asymptotic stability of the designed controller and NDO convergence are mathematically verified using the Lyapunov theory. Furthermore, to address the dead zone torque caused by mechanical friction on the stabilized platform, which could lead to instability in the toolface angle, a novel dead zone torque estimation algorithm is presented. Finally, in comparison with other advanced control methods, simulation results show the superiority and robustness of the proposed scheme under complex disturbances from the downhole environment. And drilling simulation experiment results are provided to validate the robustness and adaptivity of the proposed method.

The deepwater area is one of the frontiers of oil and gas exploration, with the understanding of distribution and genesis of deepwater reservoirs being crucial for reservoir formation research. Despite Baodao Sag in the Qiongdongnan Basin being proven to be rich in hydrocarbon generation, significant oil and gas fields have yet to be discovered in the ultra-deepwater areas, and the distribution patterns of reservoirs in deep water remain unclear. Taking the southern slope area of the Baodao Sag as an example, the distribution characteristics of submarine fans are studied by employing seismic prediction methods, including seismic reflection structure analysis, seismic facies geometry, seismic attribute analysis, and the source-to-sink theory. The results show distinct characteristics: the fan delta exhibits parallel oblique progradational reflection, the slumping submarine fan displays lenticular reflection, and the submarine fan of the Sanya Formation demonstrates subparallel sheet reflection. The provenance of sediment is traced back to the denudation area of the Songnan low uplift and the Southern Uplift area in the southwest. The sediments were primarily transported through two main incised channel systems in the north and south, ultimately flowing into the southern slope area of the Baodao Sag. The application of seismic sedimentological prediction methods and source-sink theory has laid a solid geological foundation for oil and gas exploration and the analysis of reservoir forming conditions in the deepwater area of the Baodao Sag.

Abstract This project presents a quantitative detection method to identify raccoon‐derived ingredient adulteration in sausage products. The specific copy gene of the raccoon was selected as the target gene. According to the specificity of its primer and probe, the quantitative detection method of raccoon microdrops by droplet digital PCR was established. In addition, the accuracy of the proposed method was verified by artificially mixed samples, and the applicability of this method was tested based on the commercially available products. The experimental results indicate that the raccoon mass (M) and raccoon‐extracted DNA concentration have a good linear relationship when the sample content is 5–100 mg, and there is also a significant linear relationship between DNA content and DNA copy number (C) with R2 = .9982. Therefore, using DNA concentration as the median signal, the conversion equation between raw raccoon mass (M) and DNA copy number (C) could be obtained as follows: M = (C + 177.403)/16.954. The detection of artificially mixed samples and commercial samples shows that the method is accurate and suitable for quantitative adulteration detection of various sausage products in the market.

Hepatitis E is a globally distributed infection that varies in seroprevalence between developed and developing regions. In the less developed regions of Asia and Africa, a high seropositivity rate has been reported for hepatitis E virus (HEV) antibodies. Although acute hepatitis E is often self-limited and has a favorable prognosis, some populations experience severe manifestations, which may progress to liver failure. Moreover, some immunocompromised patients are at risk of developing chronic HEV infection and cirrhosis. Proactive screening, reducing misdiagnosis, improving patient management, timely antiviral therapy for severe and chronic cases, and vaccination of high-risk groups are important measures to reduce the morbidity of hepatitis E. This review focused on the clinical presentation, management, and prevention of hepatitis E.

Abstract Background In the past 40 years, China has experienced tremendous economic development, but the current situation of hematologists has rarely been reported. A landscape survey of human resources is essential for healthcare development and policy formulation in the future. Methods The Chinese Society of Hematology initiated a survey of Chinese hematologists in mainland China for evaluating demographic and practice characteristics. Respondents were anonymous, and there were no limitations regarding their age, sex, etc. Results Totally 2032 hematologists responded, with a median age bracket of 36–45 years. Respondents were well engaged into subspecialties, and 28.1% acquired doctorates of philosophy. Hematopoietic cell transplantation (HCT) centers have been established all over China. Higher-GDP regions reported more advantages, including bigger scale of transplant centers (P

Abstract Purpose Prostatitis is a highly prevalent condition that seriously affects men’s physical and mental health. Although epidemiological investigations have provided evidence of a correlation between insufficient sleep and prostatitis, the pathogenesis of prostatitis remains unclear. We sought to identify the underlying mechanism involved and identify a promising therapeutic target. Methods Sleep deprivation (SD) was utilized to establish a mouse model of insufficient sleep in a special device. Prostatitis was observed at different time points post-SD. The degree of prostatitis was evaluated by pathological section and behavioural tests. Using immunofluorescence, western blot, and proteomic analyses, the underlying mechanism of SD-related prostatitis was investigated, and the development and therapeutic target of prostatitis were elucidated. Results SD, as an initial pathological trigger, resulted in a reduction in dihydrotestosterone and melatonin levels. Proteomic analysis revealed that the cGAS-STING pathway may play a significant role in inducing prostatitis. The subsequent results illustrated that the dual reduction in dihydrotestosterone and melatonin led to an accumulation of reactive oxygen species and the release of mitochondrial DNA (mt-DNA). The accumulation of mt-DNA activated the cGAS-STING pathway, which recruited inflammatory cells into the prostatic stroma through the secretion of interferon-β. Consequently, an inflammatory microenvironment was formed, ultimately promoting the development of prostatitis. Notably, mice with SD-induced prostatitis gradually recovered to a normal state within 7 days of recovery sleep. However, after being subjected to SD again, these mice tended to have a more pronounced manifestation of prostatitis within a shorter timeframe, which suggested that prostatitis is prone to relapse. Conclusions The cGAS-STING pathway activated by dual deficiency of dihydrotestosterone and melatonin plays a comprehensive inflammatory role in SD-related prostatitis. This research provides valuable insights into the pathogenesis, therapeutic targets, and prevention strategies of prostatitis.

Abstract Background The N-terminal regulatory element (NRE) of Receptor-like kinases (RLKs), consisting of the juxtamembrane segment in receptor kinases (RKs) and the N-terminal extension segment in RLCKs, is a crucial component that regulates the activities of these proteins. However, the features and functions of the NRE have remained largely unexplored. Herein, we comprehensively analyze 510,233 NRE sequences in RLKs from 528 plant species, using information theory and data mining techniques to unravel their common characteristics and diversity. We also use recombinant RKs to investigate the function of the NRE in vitro. Results Our findings indicate that the majority of NRE segments are around 40–80 amino acids in length and feature a serine-rich region and a 14-amino-acid consensus sequence, ‘FSYEELEKAT[D/N]NF[S/D]’, which contains a characteristic α-helix and ST motif that connects to the core kinase domain. This conserved signature sequence is capable of suppressing FERONIA’s kinase activity. A motif discovery algorithm identifies 29 motifs with highly conserved phosphorylation sites in RK and RLCK classes, especially the motif ‘VGPWKpTGLpSGQLQKAFVTGVP’ in LRR-VI-2 class. Phosphorylation of an NRE motif in an LRR-VI-2 member, MDIS1, modulates the auto-phosphorylation of its co-receptor, MIK1, indicating the potential role of NRE as a ‘kinase switch’ in RLK activation. Furthermore, the characterization of phosphorylatable NRE motifs improves the accuracy of predicting phosphorylatable sites. Conclusions Our study provides a comprehensive dataset to investigate NRE segments from individual RLKs and enhances our understanding of the underlying mechanisms of RLK signal transduction and kinase activation processes in plant adaptation.

This work presents a generic strategy to create a series of metal mercaptides complexes via coordination self-assembly between transition metals (Mn, Cu, Co, Fe, and Ni) and cysteine (Cys) by forming the sulfur-metal bridges. This strategy involves dissolving metal chlorides and Cys into deep eutectic solvents (DES), followed by the precipitation of metal mercaptides complexes (such as Cys-Mn) by adding water as an antisolvent, where DES serves as the solvent, shape directing, and capping agent, thereby preventing the formation of other metal impurities. Interestingly, the prepared complexes possess both laccase and peroxidase-like properties, allowing the design of a technique for the detection of L-3,4-dihydroxyphenylalanine (l-DOPA) and uric acid, respectively. The prepared Cys-Mn can linearly oxidize l-DOPA with its concentrations from 0.1 to 130 μM and the detection limit was calculated to be 75.5 nM. Additionally, the Cys-Mn can mimic the activity of peroxidase towards oxidization of o-phenylenediamine at neutral pH, allowing single-step and one-pot cascade reactions for visual and fluorometric measurements of uric acid (UA) that could work in the range of 0.2–500 μM UA with a detection limit of 0.06 μM and 0.054 μΜ, respectively. The assay was successful in detecting UA in serum and urine samples with relative standard deviation (RSD) ranging from 7.3% to 10.2% and 3.0%–8.5% respectively, suggesting that it may prove useful in medical diagnostic testing.

Background: Cuproptosis, one of the most recently discovered forms of cell death, is induced by the disruption of copper binding to the mitochondrial respiratory acylation components. However, the mechanism underlying cuproptosis in uveal melanoma (UM) has not yet been adequately studied. Methods: RNA and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed cuproptosis-related genes were identified by R software. A prognostic signature was constructed by applying LASSO regression and Cox regression models. The associations between the signature and the immune microenvironment, overall survival, and drug sensitivity were studied. In addition, qPCR and Western blotting were performed on UM cells and RPE cell lines to verify the expression levels of the genes encoding dihydrolipoamide dehydrogenase (DLD) and dihydrolipoamide S-succinyltransferase (DLST) in UM cases. Results: Using a cuproptosis-related prognostic signature, UM samples were classified into high- and low-risk groups. A significant difference in overall survival between the two risk groups was evident. Receiver operating characteristic curves demonstrated that the signature is a reliable predictor of prognosis. Immune cell infiltration, drug sensitivity, and immune checkpoint expression were analysed. Significant immune difference between the two high-risk groups was found, and the high expression of immune checkpoints in high-risk groups suggests significant immunotherapy potential. In addition, drug sensitivity analysis experiments suggest that erlotinib may be a potential treatment for high-risk patients. The results of in vitro experiments confirmed that DLD and DLST had higher expression levels in UM cell lines. Conclusions: The prognostic signature developed in this study is a reliable biomarker for predicting the prognosis of UM and may serve as a tool for personalised treatment of patients with UM.

In the context of pandemic viruses and pathogenic bacteria, triclosan (TCS), as a typical antibacterial agent, is widely used around the world. However, the health risks from TCS increase with exposure, and it is widespread in environmental and human samples. Notably, environmental transformation and human metabolism could induce potentially undesirable risks to humans, rather than simple decontamination or detoxification. This review summarizes the environmental and human exposure to TCS covering from 2004 to 2023. Particularly, health impacts from the environmental and metabolic transformation of TCS are emphasized. Environmental transformations aimed at decontamination are recognized to form carcinogenic products such as dioxins, and ultraviolet light and excessive active chlorine can promote the formation of these dioxin congeners, potentially threatening environmental and human health. Although TCS can be rapidly metabolized for detoxification, these processes can induce the formation of lipophilic ether metabolic analogs via cytochrome P450 catalysis, causing possible adverse cross-talk reactions in human metabolic disorders. Accordingly, TCS may be more harmful in environmental transformation and human metabolism. In particular, TCS can stimulate the transmission of antibiotic resistance even at trace levels, threatening public health. Considering these accruing epidemiological and toxicological studies indicating the multiple adverse health outcomes of TCS, we call on environmental toxicologists to pay more attention to the toxicity evolution of TCS during environmental transformation and human metabolism.

Abstract Aim This study aimed to explore the association between patient‐reported items at different time points after hematopoietic stem cell transplantation (HSCT) and long‐term survival. Methods We conducted a study with 144 allogeneic HSCT patients, following them for 5 years post‐transplantation. Data from the Functional Assessment of Cancer Therapy‐Bone Marrow Transplant (FACT‐BMT) questionnaire were collected before transplantation and at 1, 3, 6, 12, 18, 36, and 60 months after transplantation. Demographic characteristics and survival status were also assessed. Results Among the 144 cases, the 5‐year overall survival (OS), progression‐free survival (PFS), non‐relapse mortality (NRM), and graft‐versus‐host disease‐free (GRFS) rates were 65%, 48%, 17%, and 36% respectively. Health‐related quality of life (HRQOL) showed a fluctuating pattern over 5 years. Using a latent class mixed model, patients were classified into two groups based on their physical well‐being (PWB) scores during the 60‐month follow‐up. Class 1 had initially lower PWB scores, which gradually increased over time. In contrast, Class 2 maintained higher PWB scores with slight increases over time. Kaplan–Meier survival analysis revealed that Class 1 had better OS (70.9% vs. 52.9%, p = 0.021), PFS (60.5% vs. 41.2%, p = 0.039), and GRFS (35.1% vs. 29.3%, p = 0.035) compared to Class 2. Conclusions Patients who had higher initial PWB scores after HSCT demonstrated improved long‐term survival outcomes. The PWB score could serve as a valuable predictor for the prognosis of HSCT.

ObjectiveThe aim of this study was to investigate the predictive value of systemic immune inflammation index (SII), systemic inflammatory response index (SIRI), and pan-immune inflammation value (PIV) in predicting intravenous immunoglobulin (IVIG) resistance in children diagnosed with Kawasaki disease (KD).MethodsThe clinical data of pediatric patients diagnosed with Kawasaki disease and admitted to our hospital between January 2006 and December 2022 were retrospectively analyzed.ResultsIn total, 771 children diagnosed with KD were included in this study, 86 (11.2%) of whom were diagnosed with IVIG resistance. The correlation between SII, SIRI, PIV and IVIG resistance was evaluated using univariate testing, binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis. Our study found that the SII, SIRI, and PIV were independent risk factors (p=0.001, p

The efficacy of berberine in managing diabetes through modulation of gut microbiome has been established through fecal sample analyses. However, relying solely on fecal materials constrains our comprehension of berberine's effects on diverse gastrointestinal locations. This study specifically explores the ileocecal region, a segment characterized by higher microbial diversity than fecal samples. Berberine exhibits a robust hypoglycemic impact by significantly reducing glucose levels in blood and urine. Beyond glycemic control, berberine ameliorates various diabetes-related symptoms in serum, including increased insulin and leptin, but decreased NEFA and MDA. Notably, berberine demonstrates liver-protective functions by alleviating oxidative stress and enhancing hepatic glycogen abundance. These outcomes prompted a high-throughput sequencing analysis of the ileocecal microbiome, revealing an augmentation of beneficial bacterial genera (four genera in the Lachnospiraceae family, Erysipelatoclostridium, and Escherichia-Shigella), along with a reduction in harmful bacterial genera (Romboutsia). Additionally, we predicted the impact of the ileocecal microbiome on clinically relevant factors associated with diabetes. These findings elucidate the multi-pathway mechanisms of berberine in treating T2D, underscoring its potential as a natural anti-diabetic agent or functional food, particularly through the modulation of the gut microbiota.

Background: Previous research has established carbon monoxide (CO) as a significant air pollutant contributing to coronavirus disease 2019 (COVID-19) transmission. The spatiotemporal heterogeneity in the relationship between short-duration CO exposure and COVID-19 incidence remain underexplored. Investigating such heterogeneity plays a crucial role in designing region-specific cost-effective public health policies, exploring the reasons for heterogeneity, and understanding the temporal trends in the association between CO and an emerging infectious disease such as COVID-19. Methods: The 49 states of the continental United States (U.S.) were examined in this study. Initially, we developed time-series generalized additive models (GAMs) for each state to assess the preliminary correlation between daily COVID-19 cases and short-term CO exposure from April 1, 2020, to December 31, 2021. Subsequently, the correlations were compiled utilizing Leroux-prior-based conditional autoregression (LCAR) to achieve a smoothed spatial distribution. Finally, we integrated a time-varying component into the GAM and LCAR to analyze temporal correlations and illuminate the factors contributing to spatiotemporal heterogeneity. Results: Our analysis revealed that, across the 49 states, a 10-ppb increase in CO concentration was associated with a 1.33 % (95%CI: 0.86%–1.81 %) increase in COVID-19 cases on average. Furthermore, spatial variability was noted, with weaker correlations observed in the central and southeastern regions, stronger associations in the northeastern regions, and negligible associations in the western regions. Temporally, the correlation was not significant from April 2020 to June 2021, but began to increase steadily thereafter until the end of 2021. Additionally, vaccination and temperature were determined to be potential causes contributing to the heterogeneity, indicating stronger positive associations in areas with higher vaccination rates and temperatures. Conclusion: The findings of this study underscore the importance of monitoring CO pollution in the central and northeastern US, especially in the aftermath of the pandemic.

Background: Remimazolam, a new ultrashort-acting benzodiazepine, is becoming increasingly applied in general anesthesia. This study is designed to investigate the effect of remimazolam-based total intravenous anesthesia and sevoflurane-based inhalation anesthesia on emergence delirium in pediatric tonsillectomy and adenoidectomy.Methods and analysis: This is a monocentric, prospective, randomized, double-blind clinical trial. A total of 90 pediatric patients will be randomized to receive remimazolam-based total intravenous anesthesia (remimazolam group, n = 45) or sevoflurane-based inhalation anesthesia (sevoflurane group, n = 45). The primary outcome will be the incidence of emergence delirium, which will be evaluated using the Pediatric Anesthesia Emergence Delirium (PAED) scale. The secondary outcomes include the extubation time, recovery time, behavior change using the post-hospitalization behavior questionnaire for ambulatory surgery (PHBQ-AS), and adverse events.Ethics and dissemination: This study has been approved by the Institutional Review Board (IRB) of the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University (2023-K-262-02).Clinical trial registration:ClinicalTrials.gov, identifier NCT06214117.

Chemotherapy has already proven widely effective in treating cancer. Chemotherapeutic agents usually include DNA damaging agents and non-DNA damaging agents. Assessing genotoxic effect is significant during chemotherapy drug development, since the ability to attack DNA is the major concern for DNA damaging agents which relates to the therapeutic effect, meanwhile genotoxicity should also be evaluated for chemotherapy agents’ safety especially for non-DNA damaging agents. However, currently applicability of in vitro genotoxicity assays is hampered by the fact that genotoxicity results have comparatively high false positive rates. γ-H2AX has been shown to be a bifunctional biomarker reflecting both DNA damage response and repair. Previously, we developed an in vitro genotoxicity assay based on γ-H2AX quantification using mass spectrometry. Here, we employed the assay to quantitatively assess the genotoxic effects of 34 classic chemotherapy agents in HepG2 cells. Results demonstrated that the evaluation of cellular γ-H2AX could be an effective approach to screen and distinguish types of action of different classes of chemotherapy agents. In addition, two crucial indexes of DNA repair kinetic curve, i.e., k (speed of γ-H2AX descending) and t50 (time required for γ-H2AX to drop to half of the maximum value) estimated by our developed online tools were employed to further evaluate nine representative chemotherapy agents, which showed a close association with therapeutic index or carcinogenic level. The present study demonstrated that mass spectrometric quantification of γ-H2AX may be an appropriate tool to preliminarily evaluate genotoxic effects of chemotherapy agents.

Microwave technology offers a rapid and uniform heating method. This study investigated how microwave pretreatment affects the aroma precursors and flavor of fragrant rapeseed oils (FROs). Microwave pretreatment led to decreased levels of polyunsaturated fatty acids, sugars, protein-bound amino acids, and glucosinolates. Using gas chromatography–mass spectrometry, we identified 66 volatile compounds in the oil samples. Among these, based on odor activity values (OAV ≥ 1), we found 9 aldehydes, 1 ketone, 6 pyrazines, 1 isothiocyanate, and 7 nitriles as the key aroma-active compounds, contributing fatty-like, nutty-like, and pungent-like odors, respectively. The electronic nose results highlighted W5S and W1W as primary sensors for determining the flavor profiles of FROs. Notably, aroma-active pyrazines exhibited strong negative correlations with sucrose, cysteine, lysine, and isoleucine. This research provides essential insights for enhancing the aroma of FROs.

The objective of this study was to assess and compare the characteristics of Yu-Shiang Shredded Pork made with different ingredients by using physicochemical measurements and intelligent sensory analysis. The study revealed that there were 18 varied amino acids present, with the taste active values (TAVs) of Leu, Glu, Asp, Asn, and Ala all higher than 1.0. Intelligent sensory analysis showed that the samples lacking lettuce and fungus had similar aromas and flavors, while those lacking shredded pork and pickled chillies had distinct aromas and flavors. Moreover, VOCs (volatile organic compounds) were detected in five types of Yu-Shiang Shredded Pork, with 43, 42, 53, 36, and 50 identified in GC-MS (gas chromatography-mass spectrometry), respectively. Olefins (20.62 %–30.93 %) were the most abundant. GC-IMS (gas chromatography-ion mobility spectrometry) detected 68 volatiles flavor compounds, with esters having a significantly higher relative content than other compounds, indicating their significant role in the flavor formation process of Yu-Shiang Shredded Pork. Furthermore, the Orthogonal Partial Least Squares-discriminant analysis (OPLS-DA) model analysis identified 19 marker compounds that could differentiate the five types of Yu-Shiang Shredded Pork. These fundamental results lay the groundwork for future research on the connection between ingredients and the flavor characteristics of Yu-Shiang Shredded Pork.

Cryptosporidium spp., Giardia spp. and Enterocytozoon bieneusi are common zoonotic pathogens in humans and animals. Although rodents are important parts of the ecosystem and common hosts for these pathogens, little is known of the distribution, genetic diversity and zoonotic potential of these pathogens in wild rodents. A total of 442 fecal samples were collected from eleven wild rodent species in three provinces of China, and analyzed for these pathogens by PCR and DNA sequencing. The infection rates of Cryptosporidium spp., Giardia spp. and E. bieneusi were 19.9% (88/442), 19.8% (75/378) and 12.2% (54/442), respectively. Altogether, 23 known Cryptosporidium species/genotypes were identified and their distribution varied among different sampling locations or rodent species. Subtyping of the zoonotic Cryptosporidium species identified two novel subtype families XVe and XVf in C. viatorum, the subtype family XIIh and a novel subtype family XIIj in C. ubiquitum, and the subtype family IId in C. parvum. Three Giardia species were identified, including G. microti (n = 57), G. muris (n = 15) and G. duodenalis (n = 3), with G. duodenalis assemblages A and G identified in brown rats in urban areas of Guangdong. In addition, 13 E. bieneusi genotypes including eight known and five novel ones were identified, belonging to Groups 1, 2, 10, 14 and 15. Within nine genotypes in the zoonotic Group 1, common human-pathogenic genotypes D, Type IV, PigEbITS7 and Peru8 were detected only in brown rats and Lesser rice-field rats in urban areas of Guangdong. Apparent host adaptation and geographical differences were observed among Cryptosporidium spp., Giardia spp. and E. bieneusi genotypes in wild rodents in the present study. Furthermore, the zoonotic Cryptosporidium species and E. bieneusi genotypes commonly found here suggest a high zoonotic potential of these pathogens in wild rodents, especially in brown rats in urban areas. Hygiene and One Health measures should be implemented in urban streets and food stores to reduce the possible direct and indirect transmission of these rodent-related pathogens.

Bone marrow stromal/stem cells (BMSCs) are primitive and heterogeneous cells that can be differentiated into osteoblasts, adipocytes and other subsets. Their bone-fat lineage commitment is responsible for the homeostasis of bone marrow microenvironment. However, there are little effective methods and evidence to simultaneously visualise the lineage commitment of BMSCs. Here we provide a bivalent differentiation medium that can enable BMSCs differentiation into osteoblasts and adipocytes in vitro, and establish a method to simultaneously distinguish osteoblasts or adipocytes from the heterogeneous BMSCs based on Alizarin red S and Oil red O staining, which have been used for detection of specific mineralized nodules and lipid droplets, respectively. This assay provides a specifically simple but effective and low-cost method to evaluate the efficiency of osteo-adipogenic (OA) allocation of BMSCs. ► Researchers can utilize the bivalent differentiation medium to evaluate the efficiency of osteogenic and adipogenic differentiation of BMSCs in vitro.

Abstract Cellular senescence represents an irreversible state of cell-cycle arrest during which cells secrete senescence-associated secretory phenotypes, including inflammatory factors and chemokines. Additionally, these cells exhibit an apoptotic resistance phenotype. Cellular senescence serves a pivotal role not only in embryonic development, tissue regeneration, and tumor suppression but also in the pathogenesis of age-related degenerative diseases, malignancies, metabolic diseases, and kidney diseases. The senescence of renal tubular epithelial cells (RTEC) constitutes a critical cellular event in the progression of acute kidney injury (AKI). RTEC senescence inhibits renal regeneration and repair processes and, concurrently, promotes the transition of AKI to chronic kidney disease via the senescence-associated secretory phenotype. The mechanisms underlying cellular senescence are multifaceted and include telomere shortening or damage, DNA damage, mitochondrial autophagy deficiency, cellular metabolic disorders, endoplasmic reticulum stress, and epigenetic regulation. Strategies aimed at inhibiting RTEC senescence, targeting the clearance of senescent RTEC, or promoting the apoptosis of senescent RTEC hold promise for enhancing the renal prognosis of AKI. This review primarily focuses on the characteristics and mechanisms of RTEC senescence, and the impact of intervening RTEC senescence on the prognosis of AKI, aiming to provide a foundation for understanding the pathogenesis and providing potentially effective approaches for AKI treatment.

Abstract Alcohol consumption during pregnancy can result in a range of adverse postnatal outcomes among exposed children. However, identifying at-risk children is challenging given the difficulty to confirm prenatal alcohol exposure and the lack of early diagnostic tools. Placental surveys present an important opportunity to uncover early biomarkers to identify those at risk. Here, we report the first transcriptome-wide evaluation to comprehensively evaluate human placental pathways altered by fetal alcohol exposure. In a prospective longitudinal birth cohort in Cape Town, South Africa, we performed bulk tissue RNAseq in placenta samples from 32 women reporting heavy drinking during pregnancy and 30 abstainers/light drinkers. Weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis were performed to assess associations between fetal alcohol exposure and placental gene expression patterns at a network-wide and single gene level, respectively. The results revealed altered expression in genes related to erythropoiesis and angiogenesis, which are implicated in established postnatal phenotypes related to alcohol exposure, including disruptions in iron homeostasis, growth, and neurodevelopment. The reported findings provide insights into the molecular pathways affected by prenatal alcohol exposure and highlight the potential of placental biomarkers for detecting and understanding the effects of alcohol on fetal development.

Abstract Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings.

Abstract Background Chemoresistance presents a significant obstacle in the treatment of colorectal cancer (CRC), yet the molecular basis underlying CRC chemoresistance remains poorly understood, impeding the development of new therapeutic interventions. Elongation factor Tu GTP binding domain containing 2 (EFTUD2) has emerged as a potential oncogenic factor implicated in various cancer types, where it fosters tumor growth and survival. However, its specific role in modulating the sensitivity of CRC cells to chemotherapy is still unclear. Methods Public dataset analysis and in-house sample validation were conducted to assess the expression of EFTUD2 in 5-fluorouracil (5-FU) chemotherapy-resistant CRC cells and the potential of EFTUD2 as a prognostic indicator for CRC. Experiments both in vitro, including MTT assay, EdU cell proliferation assay, TUNEL assay, and clone formation assay and in vivo, using cell-derived xenograft models, were performed to elucidate the function of EFTUD2 in sensitivity of CRC cells to 5-FU treatment. The molecular mechanism on the reciprocal regulation between EFTUD2 and the oncogenic transcription factor c-MYC was investigated through molecular docking, ubiquitination assay, chromatin immunoprecipitation (ChIP), dual luciferase reporter assay, and co-immunoprecipitation (Co-IP). Results We found that EFTUD2 expression was positively correlated with 5-FU resistance, higher pathological grade, and poor prognosis in CRC patients. We also demonstrated both in vitro and in vivo that knockdown of EFTUD2 sensitized CRC cells to 5-FU treatment, whereas overexpression of EFTUD2 impaired such sensitivity. Mechanistically, we uncovered that EFTUD2 physically interacted with and stabilized c-MYC protein by preventing its ubiquitin-mediated proteasomal degradation. Intriguingly, we found that c-MYC directly bound to the promoter region of EFTUD2 gene, activating its transcription. Leveraging rescue experiments, we further confirmed that the effect of EFTUD2 on 5-FU resistance was dependent on c-MYC stabilization. Conclusion Our findings revealed a positive feedback loop involving an EFTUD2/c-MYC axis that hampers the efficacy of 5-FU chemotherapy in CRC cells by increasing EFTUD2 transcription and stabilizing c-MYC oncoprotein. This study highlights the potential of EFTUD2 as a promising therapeutic target to surmount chemotherapy resistance in CRC patients.

Abstract Background Lung cancer is a malignant tumor with the highest mortality worldwide. Abnormalities in the ubiquitin proteasome system are considered to be contributed to lung cancer progression with deleterious effects. DDB1 and CUL4 associated factor 13 (DCAF13) is a substrate receptor of the E3 ubiquitin ligase CRL4, but its role in lung cancer remains unknown. In this study, we aimed to investigate the regulatory mechanisms of DCAF13 in lung adenocarcinoma (LUAD). Methods So as to investigate the effect of DCAF13 on lung adenocarcinoma cell function using in vivo and in vitro. Mechanistically, we have identified the downstream targets of DCAF13 by using RNA-sequencing, as well as ubiquitination assays, co-immunoprecipitation, immunofluorescence, immunohistochemistry and chromatin immunoprecipitation - qPCR experiments. Results Our findings reveal that DCAF13 is a carcinogenic factor in LUAD, as it is highly expressed and negatively correlated with clinical outcomes in LUAD patients. Through RNA-sequencing, it has been shown that DCAF13 negatively regulates the p53 signaling pathway and inhibits p53 downstream targets including p21, BAX, FAS, and PIDD1. We also demonstrate that DCAF13 can bind to p53 protein, leading to K48-linked ubiquitination and degradation of p53. Functionally, we have shown that DCAF13 knockdown inhibits cell proliferation and migration. Our results highlight the significant role of DCAF13 in promoting LUAD progression by inhibiting p53 protein stabilization and the p53 signaling pathway. Furthermore, our findings suggest that high DCAF13 expression is a poor prognostic indicator in LUAD, and DCAF13 may be a potential therapeutic target for treating with this aggressive cancer. Conclusions The DCAF13 as a novel negative regulator of p53 to promote LUAD progression via facilitating p53 ubiquitination and degradation, suggesting that DCAF13 might be a novel biomarker and therapeutical target for LUAD.

Intelligent interpretation of remote sensing images using deep learning is heavily reliant on large datasets, and models trained in one domain often struggle with crossdomain application. Pretraining the backbone network via masked image modeling can effectively diminish this reliance on extensive sample data, thereby reducing crossdomain transfer obstacles. However, current masked image models typically employ a pure Transformer architecture, which may not fully capitalize on low-level features. To address these issues, this article proposes masked feature modeling (MFM), a methodology for the generative self-supervised learning of high-resolution remote sensing images that combines convolutional neural network (CNN) and Transformer architectures. This methodology has several advantages: 1) The hybrid CNN + Transformer architecture not only retains the advantages of the local feature representation of the CNN architecture but also has the full-text information modeling capabilities of the Transformer architecture; 2) the feature extraction network outputs multiscale features, and it is easier to add upsampling and a skip connection to improve the accuracy of the downstream dense prediction task; and 3) the pretrained MFM can be applied to various downstream tasks through fine-tuning with limited samples. The publicly available WHU and Massachusetts Building Datasets are used to verify the effectiveness of the proposed method. Extensive experiments involving main properties of the MFM for generative self-supervised learning, fine-tuning the MFM on the downstream semantic segmentation task, and comparisons with the other state-of-the-art generative self-supervised learning algorithms show that, through the combined advantages of the CNN and Transformer architectures, the proposed method has better feature extraction capability and higher accuracy on downstream tasks such as semantic segmentation.

Abstract Background Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. Results The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. Conclusions We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases.

Epidemiological and experimental evidence has linked chronic inflammation to the etiology of myeloproliferative neoplasm (MPN). However, it remains unclear whether genetic associations with specific inflammatory biomarkers are causal or due to bias. This study aimed to assess the effect of C-reactive protein (CRP) and systemic inflammatory regulators on MPN within a bidirectional Mendelian randomization design. Genetic associations with MPN were derived from a publicly available genome-wide association study (GWAS) comprising 1,086 cases and 407,155 controls of European ancestry. Additionally, data on inflammation were extracted from two GWASs focusing on CRP and cytokines. The causal relationships between exposure and outcome were explored using the inverse variance weighted (IVW) method. To confirm the final results, multiple sensitivity analyses, including MR-Egger, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were simultaneously employed. Our results suggest that lower levels of macrophage-migration inhibitory factor (IVW estimate odds ratio [OR IVW] per SD genetic cytokines change: 0.641; 95% confidence interval [CI]: 0.427–0.964; p = 0.032) and higher levels of interleukin-2 receptor α (lL2Rα, 1.377, 95% CI: 1.006–1.883; p = 0.046) are associated with an increased risk of MPN. Genetically predicted MPN is related to increased levels of RANTES (IVW estimate β: 0.043, 95% CI: 0.002–0.084; p = 0.039) and interleukin-10 (IVW estimate β: 0.030, 95% CI: 0.001–0.060; p = 0.041). This study provides evidence for a causal relationship between CRP, systemic inflammatory regulators, and MPN, and new insights into the etiology, prevention, and prognosis of MPN.

Semantic segmentation is a basic task in the interpretation of remote sensing images. Mainstream deep-learning-based semantic segmentation algorithms typically process images with small sizes. However, remote sensing images typically involve large areas with buildings and water, which have weak textures. Because of the limited range of receptive fields, the semantic segmentation of such areas from small images may lead to problems, such as loss of spatial features and inaccurate boundary extraction. To address these problems, this article devises a patch-to-region framework for the semantic segmentation of large-format remote sensing images. This framework has a bottom–up pyramid structure, where the bottom layer is a small image patch, referred to as a “patch,” and the upper layer is a large image region, referred to as a “region.” The classical semantic segmentation network is first used to process small image patches to obtain pixel-by-pixel semantic features. Then, the pixel-by-pixel semantic features are sparsely reduced into patch-level semantic feature vectors, and the semantic feature vectors of the entire image region are processed through the contextual information extractor to extract the global semantic feature vectors. Subsequently, an information aggregation module is used to integrate the global semantic feature vectors and semantic features to obtain new semantic features with both global and local information. Finally, a lightweight decoding module is used to process the new semantic features to obtain the final semantic segmentation result. The developed framework is evaluated over three public datasets. The results of extensive experiments show that the framework can achieve more accurate and reliable semantic segmentation of high-resolution remote sensing images than state-of-the-art semantic segmentation algorithms. Moreover, ablation studies are performed to verify the effectiveness of each module of the framework.

Abstract Acute myeloid leukemia (AML), a prevalent form of leukemia in adults, is often characterized by low response rates to chemotherapy, high recurrence rates, and unfavorable prognosis. A critical barrier in managing refractory or recurrent AML is the resistance to chemotherapy. Increasing evidence indicates that tumor cell metabolism plays a crucial role in AML progression, survival, metastasis, and treatment resistance. Autophagy, an essential regulator of cellular energy metabolism, is increasingly recognized for its role in the metabolic reprogramming of AML. Autophagy sustains leukemia cells during chemotherapy by not only providing energy but also facilitating rapid proliferation through the supply of essential components such as amino acids and nucleotides. Conversely, the metabolic state of AML cells can influence the activity of autophagy. Their mutual coordination helps maintain intrinsic cellular homeostasis, which is a significant contributor to chemotherapy resistance in leukemia cells. This review explores the recent advancements in understanding the interaction between autophagy and metabolism in AML cells, emphasizing their roles in cell survival and drug resistance. A comprehensive understanding of the interplay between autophagy and leukemia cell metabolism can shed light on leukemia cell survival strategies, particularly under adverse conditions such as chemotherapy. This insight may also pave the way for innovative targeted treatment strategies.