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Abstract Background Diabetic cardiomyopathy (DCM), characterized by myocardial fibrosis, is a major cause of mortality and morbidity in diabetic patients; the inhibition of cardiac fibrosis is a fundamental strategy for treating DCM. Gastrodin (GAS), a compound extracted from Gastrodia elata protects against DCM, but the molecular mechanism underlying its antifibrotic effect has not been elucidated. Methods In vivo, the effects of GAS were investigated using C57BL/6 mice with DCM, which was induced by administering a high-sugar, high-fat (HSF) diet and streptozotocin (STZ). We assessed the cardiac function in these mice and detected histopathological changes in their hearts and the degree of cardiac fibrosis. In vitro, neonatal rat cardiac fibroblasts (CFs) were transformed into myofibroblasts by exposing them to high glucose combined with high palmitic acid (HG-PA), and CFs were induced by pEX-1 (pGCMV/MCS/EGFP/Neo) plasmid-mediated overexpression of KLK8, which contains the rat KLK8 gene. The KLK8 siRNA was knocked down to study the effects of GAS on CF differentiation, collagen synthesis, and cell migration by specific mechanisms of action of GAS. Results GAS attenuated pathological changes in the hearts of DCM mice, rescued impaired cardiac function, and attenuated cardiac fibrosis. Additionally, the results of molecular docking analysis showed that GAS binds to kinin-releasing enzyme-related peptidase 8 (KLK8) to inhibit the increase in protease-activated receptor-1 (PAR-1), thus attenuating myocardial fibrosis. Specifically, GAS attenuated the transformation of neonatal rat CFs to myofibroblasts exposed to HG-PA. Overexpressing KLK8 promoted CF differentiation, collagen synthesis, and cell migration, and KLK8 siRNA attenuated HG-PA-induced CF differentiation, collagen synthesis, and cell migration. Further studies revealed that a PAR-1 antagonist, but not a PAR-2 antagonist, could attenuate CF differentiation, collagen synthesis, and cell migration. Additionally, GAS inhibited KLK8 upregulation and PAR1 activation, thus blocking the differentiation, collagen synthesis, and cell migration of HG-PA-exposed CFs and triggering TGF-β1/Smad3 signaling. Conclusion GAS alleviated pathological changes in the hearts of DCM model mice induced by an HSF diet combined with STZ. KLK8 mediated HG-PA-induced differentiation, collagen synthesis, and the migration of CFs. GAS attenuated the differentiation, collagen synthesis, and migration of CFs by inhibiting the KLK8-PAR1 signaling axis, a process in which TGF-β1 and Smad3 are involved. Graphical Abstract

Abstract As oil production increasingly transitions from shallow to deep formation, the need for efficient PDC cutters to drill through deep hard rock becomes paramount. Currently, there is a lack of effective methods for optimizing cutter shapes and their cutting parameters. This study addresses this gap by developing a rock-breaking mechanism model for PDC cutters and proposing a Stability Index (SI) based on cutting force variations during the cutting process. Using the FDEM method, we simulated the rock-breaking processes of planar, stinger, and machete cutters under various cutting depths and angles. SI and Mechanical Specific Energy (MSE) were employed as evaluation metrics to analyze the rock-breaking characteristics and determine the optimal cutting parameters for each cutter type. The results indicate that at shallow cutting depths, cutting force changes are minimal, predominantly causing plastic damage to the rock, resulting in lower stress and reduced wear on the PDC cutters. Conversely, at greater cutting depths, significant fluctuations in cutting force occur, leading to brittle failure and the generation of large cuttings. This sudden increase in cutting force can accelerate rock breaking but also increases the risk of cutter wear. Our findings suggest that the planar cutter offers stable performance with high cutting force requirements, optimal at a cutting depth of 1.5 mm and an angle of less than 20°. The stinger cutter, requiring lower cutting forces, performs best at a cutting depth of 2 mm and an angle of 20°. The machete cutter exhibits characteristics similar to the stinger cutter at shallow depths and the planar cutter at deeper depths, making it suitable for drilling at a depth of 2 mm and an angle of less than 10°. By balancing SI and MSE, this study provides a comprehensive approach to optimizing PDC cutter performance, enhancing drilling efficiency while minimizing cutter wear.

Objective This study investigated the effects of Apidaecin Api-PR19 as feed additive on growth performance, intestinal health, and small intestinal microbiota of broilers. Methods A total of 360 1-d-old Arbor Acres broilers were randomly assigned to 3 groups with 6 replicates including control group with basal diet (CON), antibiotic growth promotor group with basal plus 10 mg/kg colistin sulfate and 50 mg/kg roxarsone (AGP), and antibacterial peptide group with basal diet plus 330 mg/kg Apidaecin Api-PR19 (ABP). The trial lasted 35 d. Results Results showed that dietary Api-PR19 addition increased (p

Abstract Background Overactivated microglia are a key contributor to Parkinson’s disease (PD) by inducing neuroinflammation. CD200R1, a membrane glycoprotein mainly found on microglia, is crucial for maintaining quiescence with its dysregulation linked to microglia’s abnormal activation. We and other groups have reported a decline in CD200R1 levels in several neurological disorders including PD. However, the mechanism regulating CD200R1 expression and the specific reasons for its reduction in PD remain largely unexplored. Given the pivotal role of transcription factors in gene expression, this study aimed to elucidate the transcriptional regulation of CD200R1 and its implications in PD. Methods The CD200R1 promoter core region was identified via luciferase assays. Potential transcription factors were predicted using the UCSC ChIP-seq database and JASPAR. NFKB1 binding to the CD200R1 core promoter was substantiated through electrophoretic mobility shift and chromatin immunoprecipitation assays. Knocking-down or overexpressing NFKB1 validated its regulatory effect on CD200R1. Correlation between decreased CD200R1 and deficient NFKB1 was studied using Genotype-Tissue Expression database. The clinical samples of the peripheral blood mononuclear cells were acquired from 44 PD patients (mean age 64.13 ± 9.78, 43.2% male, median Hoehn-Yahr stage 1.77) and 45 controls (mean age 64.70 ± 9.41, 52.1% male). NFKB1 knockout mice were utilized to study the impact of NFKB1 on CD200R1 expression and to assess their roles in PD pathophysiology. Results The study identified the CD200R1 core promoter region, located 482 to 146 bp upstream of its translation initiation site, was directly regulated by NFKB1. Significant correlation between NFKB1 and CD200R1 expression was observed in human PMBCs. Both NFKB1 and CD200R1 were significantly decreased in PD patient samples. Furthermore, NFKB1-/- mice exhibited exacerbated microglia activation and dopaminergic neuron loss after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment. Conclusion Our study identified that NFKB1 served as a direct regulator of CD200R1. Reduced NFKB1 played a critical role in CD200R1 dysregulation and subsequent microglia overactivation in PD. These findings provide evidence that targeting the NFKB1-CD200R1 axis would be a novel therapeutic strategy for PD.

Abstract Exposure to mercury has been associated with adverse effects on pregnancy outcomes. However, there is limited literature on mercury exposure and pregnancy outcomes in Chinese pregnant women. Our study was to investigate the possible association between maternal mercury exposure and spontaneous preterm birth and birth weight. This study was a nested case-control study. The association between blood mercury concentration and both spontaneous preterm birth and birth weight was analyzed using conditional logistic regression and linear regression adjusted for the potential confounding factors, respectively. The dose-response relationship between mercury concentration and birth outcomes was estimated using restricted cubic spline regression. The mean concentration of mercury was 2.8 ± 2.2 µg/L. A positive relationship was observed between maternal blood mercury concentration and SPB when analyzed as a continuous variable. However, it was not found to be statistically significant (adjusted OR = 1.10, 95% CI = 0.95–1.26, P = 0.202). Moderate mercury exposure was associated with a higher risk of SPB (Q3 vs. Q1: crude OR = 2.50, 95% CI = 1.16–5.41, P = 0.02; adjusted OR = 3.49, 95% CI = 1.33–9.11, P = 0.011). After considering the combined effects of chemicals other than mercury exposure (including lead, selenium, and cadmium), the results remained consistent. There was no statistically significant association between blood mercury levels and birth weight (adjusted coefficient = 18.64, P-value = 0.075). There were no statistically significant dose-response associations between mercury concentration and birth outcomes (SPB: P = 0.076; birth weight: P = 0.885). Public health policies should focus on reducing environmental releases of mercury, improving food safety standards, and providing education to pregnant women about the risks of mercury exposure and preventive measures.

IntroductionLiver fibrosis is a pathological condition in response to chronic liver injuries. Currently, there is no Food and Drug Administration (FDA) approved pharmacotherapy for liver fibrosis. Advances in understanding hepatic fibrogenesis have led to the development of anti-fibrotic agents, and some of them have shown promise in phase 3 and above clinical trials. However, adverse drug reactions (ADRs) associated with emerging anti-fibrotic agents may hinder their efficacy and clinical applicability. This study assessed ADRs associated with anti-fibrotic agents as reported in the World Health Organization (WHO) VigiAccess database and compared the adverse reaction characteristics of these agents for optimizing therapeutic strategies.MethodsA detailed search was conducted on ClinicalTrial.gov to identify phase 3 or 4 clinical trials involving hepatic anti-fibrotic agents. The ADR reports were retrieved from the WHO-VigiAccess database, with data categorized by demographic characteristics, geographic distribution, and System Organ Classes (SOCs). The most frequently reported ADRs were identified through descriptive analysis. Disproportionality analysis, measured by reporting odd ratio (ROR) and proportional reporting ratio (PRR), was performed to evaluate ADRs related to gastrointestinal disorders.ResultsFive hepatic anti-fibrotic agents (empagliflozin, liraglutide, candesartan, obeticholic acid, and resmetirom) were identified. A total of 130,567 ADR reports were analyzed, with empagliflozin, liraglutide, and candesartan showing significantly higher ADRs. The most frequently reported SOCs included gastrointestinal disorders (29.44%), general disorders (24.12%), and nervous system disorders (14.42%). Liraglutide demonstrated a higher risk of gastrointestinal ADRs (ROR: 4.629, 95% CI: 4.517–4.744; PRR: 3.566, 95% CI: 3.492–3.642) compared to the other agents. Severe ADRs were reported in empagliflozin, such as ketoacidosis and infections, while liraglutide was associated with pancreatitis and candesartan with acute kidney injury. Serious ADR rates varied, with candesartan reporting the highest proportion (7.28%).ConclusionWhile hepatic anti-fibrotic agents showed promise in addressing liver fibrosis, their ADR profiles underscore the importance of pharmacovigilance and personalized treatment approaches. Future efforts should focus on improving the pharmacovigilance system, expanding population diversity in trials, and conducting ongoing research and extensive post-marketing surveillance.

ABSTRACTLake distribution on the Tibetan Plateau (TP) is extensive, and lake area changes are key indicators of the TP's climate change response. Many multisource remote sensing big data for the TP, particularly optical images, are unusable due to cloud cover. Therefore, an improved isobath interpolation-based lake area extraction method is proposed and applied to obtain annual average lake areas (≥ 50 km²) on the TP from 1986 to 2020 using remote sensing big data. The lake area result accuracy was verified using existing lake area and level datasets, yielding correlation coefficients of ∼0.9. The change points and segmented trends of each lake's interannual area sequence were obtained. The relationships between lake area and climatic variables were investigated. The positive accumulation of the total precipitation minus total evaporation explains the overall lake area expansion trend after 1995. The exorheic lake interannual area is related to precipitation more than that of endorheic lakes, but endorheic lake area changes are stronger. The shrinking of lakes on the southern TP may not be climate-driven but probably attributed to lake bottom leakage. We explore detailed interannual variation characteristics of lake areas on the TP and provide reference data for studying lake responses to climate change.

To assess the impact of vaccines on clinical outcomes among hospitalized COVID-19-infected patients requiring oxygen supplementation during the Beijing Omicron outbreak. We conducted a retrospective cohort study at Beijing Chaoyang Hospital, Capital Medical University, from November 15, 2022, to March 31, 2023. Vaccination statuses were categorized into 3 doses, 2 doses, and unvaccinated (0 dose). The primary outcome was 28-day all-cause mortality. Secondary outcomes included poor outcomes, intensive care unit admission, cardiovascular thromboembolism events, and hospital readmission. Among the included patients, 117 were 2 doses, 285 received booster doses, and 503 were unvaccinated. After propensity score inverse probability weighting, the 3 doses group showed a significantly lower 28-day all-cause mortality compared to the unvaccinated group (inverse probability of treatment weighting-adjusted HR: 0.64, 95% CI: 0.50–0.81). No significant difference was observed in all-cause mortality between the 2 doses and unvaccinated groups. No significant differences were observed in secondary outcome analyses when comparing the 3 doses or 2 doses group to the unvaccinated group. Subgroup analysis revealed significant benefits of booster vaccination in patients with shorter symptom duration, lower Charlson Comorbidity Index, and without immunosuppression status. Our study highlights the significant reduction in all-cause mortality among hospitalized Omicron-infected patients who received a third dose vaccine. These findings underscore the importance of prioritizing booster vaccinations, especially among the elderly. Further research is warranted to confirm and extend these observations.

Compared with the commonly used synchronous brain-computer interface (BCI), the asynchronous BCI is a more flexible and natural way to control the real-world robotic devices. The major difficulty of building a robust asynchronous BCI lies in the discrimination between control states (CSs) and non-control states (NSs). This article presents an open-source 63-channel electroencephalogram (EEG) dataset of 24 subjects for asynchronous steady-state visual evoked potential (SSVEP)-BCI research. The data was recorded from an SSVEP based CS task and three different types of NS tasks, namely NS1, NS2 and NS3. The dataset was evaluated using three processes, including analysis of temporal waveform, amplitude spectrum and signal-to-noise (SNR), recognition of SSVEP frequencies, and classification between CS and NS. The dataset can be used to support studies of asynchronous classification, NS detection, and discrimination between different NSs.

Solar thermochemical energy storage based on calcium looping (CaL) process is a promising technology for next-generation concentrated solar power (CSP) systems. However, conventional calcium carbonate (CaCO3) pellets suffer from slow reaction kinetics, poor stability, and low solar absorptance. Here, we successfully realized high power density and highly stable solar thermochemical energy storage/release by synergistically accelerating energy storage/release via binary sulfate and promoting cycle stability, mechanical strength, and solar absorptance via Al–Mn–Fe oxides. The energy storage density of proposed CaCO3 pellets is still as high as 1455 kJ kg−1 with only a slight decay rate of 4.91% over 100 cycles, which is higher than that of state-of-the-art pellets in the literature, in stark contrast to 69.9% of pure CaCO3 pellets over 35 cycles. Compared with pure CaCO3, the energy storage power density or decomposition rate is improved by 120% due to lower activation energy and promotion of Ca2+ diffusion by binary sulfate. The energy release or carbonation rate rises by 10% because of high O2− transport ability of molten binary sulfate. Benefiting from fast energy storage/release rate and high solar absorptance, thermochemical energy storage efficiency is enhanced by more than 50% under direct solar irradiation. This work paves the way for application of direct solar thermochemical energy storage techniques via achieving fast energy storage/release rate, high energy density, good cyclic stability, and high solar absorptance simultaneously.

Abstract The high‐voltage pulse discharge technology, which is based on the electrohydraulic effect, can generate powerful, controllable, and repetitive electrohydraulic shock waves (EHSWs) in underground confined space, so it has been applied in the petroleum industry to improve the permeable of the reservoir. In this paper, a numerical model based on LS‐DYNA is built to study the damage analysis of the cement sheath and rock subjected to EHSWs during perforation completion. The results show that the stress state of the cement sheath and rock surrounding the perforation hole is determined by the shock pressure from both the perforation hole and the wellbore; the damage of the cement sheath and rock is mainly caused by tensile stress; the damage zone of the cement sheath is mainly distributed on the inner surface and near the perforation hole, while the damage zone of rock is distributed near the perforation hole; after multiple discharges, the damage of cement sheath and rock gradually accumulates, and the damage zone eventually forms a vertical plane along perforation holes. Overall, these results provide guidance for the safe application of the high‐voltage pulse discharge technology in the oil field.

Abstract Background The occurrence, development, and outbreak of tea diseases and pests pose a significant challenge to the quality and yield of tea, necessitating prompt identification and control measures. Given the vast array of tea diseases and pests, coupled with the intricacies of the tea planting environment, accurate and rapid diagnosis remains elusive. In addressing this issue, the present study investigates the utilization of transfer learning convolution neural networks for the identification of tea diseases and pests. Our objective is to facilitate the accurate and expeditious detection of diseases and pests affecting the Yunnan Big leaf kind of tea within its complex ecological niche. Results Initially, we gathered 1878 image data encompassing 10 prevalent types of tea diseases and pests from complex environments within tea plantations, compiling a comprehensive dataset. Additionally, we employed data augmentation techniques to enrich the sample diversity. Leveraging the ImageNet pre-trained model, we conducted a comprehensive evaluation and identified the Xception architecture as the most effective model. Notably, the integration of an attention mechanism within the Xeption model did not yield improvements in recognition performance. Subsequently, through transfer learning and the freezing core strategy, we achieved a test accuracy rate of 98.58% and a verification accuracy rate of 98.2310%. Conclusions These outcomes signify a significant stride towards accurate and timely detection, holding promise for enhancing the sustainability and productivity of Yunnan tea. Our findings provide a theoretical foundation and technical guidance for the development of online detection technologies for tea diseases and pests in Yunnan.

Valproic acid (VPA) is predominantly prescribed for epilepsy, convulsions, and other psychiatric disorders. As an epigenetic regulator, it is also used to treat various forms of cancer. The clinical demand for the drug may pose an environmental hazard. Evidence indicates that VPA’s significant therapeutic value comes at the cost of possible side toxic effects, as symptoms of birth defects have been confirmed in animal experiments using VPA. However, the effects of VPA during the development of the circulatory system remain unclear. In this study, zebrafish embryos were exposed to a series of concentrations of VPA between three hours post fertilization (hpf) and five days post fertilization (dpf). The results demonstrated time- and dose-dependent developmental delays in the zebrafish, including cardiovascular malformation and decreased movement and reaction time. Consistent with the in vivo results, exposure to VPA increased the levels of myocardial reactive oxygen species (ROS) and cell apoptosis through cardiac mitochondrial turnover disorders. The expression levels of genes related to cardiovascular development and antioxidant response were downregulated, while genes related to apoptosis pathways were upregulated. Overall, our toxicological studies of VPA exposure illustrate the damage to cardiovascular development, raising concerns about the hazard of VPA exposure in early pregnancy. Our study provides novel insights into the potential environmental risks of VPA.

Genomic structural variation (SV) refers to differences in gene sequences between individuals on a genomic scale. It is widely distributed in the genome, primarily in the form of insertions, deletions, duplications, inversions, and translocations. Due to its characterization by long segments and large coverage, SVs significantly impact the genetic characteristics and production performance of livestock, playing a crucial role in studying breed diversity, biological evolution, and disease correlation. Research on SVs contributes to an enhanced understanding of chromosome function and genetic characteristics and is important for understanding hereditary diseases mechanisms. In this article, we review the concept, classification, main formation mechanisms, detection methods, and advancement of research on SVs in the genomes of cattle, buffalo, equine, sheep, and goats, aiming to reveal the genetic basis of differences in phenotypic traits and adaptive genetic mechanisms through genomic research, which will provide a theoretical basis for better understanding and utilizing the genetic resources of herbivorous livestock.

The study of fine-grained sedimentation has consistently concentrated on investigating the mechanisms and principles governing the enrichment of organic matter. However, the lack of unified stratigraphic framework has always existed as fine-grained sedimentation covers two distinct grain-size grades, namely, mud and silt, which has impeded the progress of subsequent production research. This study exemplified this issue by analyzing the first member of the Qingshankou Formation in the southern Songliao Basin. We established reconstructed gamma and density curves that mitigated filter noise interference, integrated high-resolution sequence results with astronomical cycle divisions, and created a high-frequency isochronous stratigraphic framework for clastic fine-grained sedimentation by leveraging the weak sensitivity of sandstone density curves and the robust stability in eccentricity cycle extraction. This approach addresses the inconsistencies in stratigraphic division methodologies and mismatched outcomes stemming from the use varying techniques to delineate mud and silt components within clastic fine-grained sedimentary sequences. Furthermore, it elucidates how tectonic-scale variations in sediment supply coupled with potential accommodation changes dictate macroscopic stacking patterns within strata, whereas climate fluctuations on orbital time scales govern sand-mud progradation degrees within these layers, culminating in periodic rhythmic characteristics characterized by vertical sand-mud interbedding. A model for stratigraphic development pertaining to lake delta systems constrained by a “synchronous heterotopy” paradigm is proposed for the southern Songliao Basin. The organic matter enrichment pattern aligns with its filling dynamics, indicating an “overfilling” type developmental pattern at lower strata levels where organic material predominantly originates from terrestrial plant debris external to the basin; this material accumulates primarily within silty zones along layers—with areas exhibiting heightened enrichment values slightly lagging behind short-eccentric maxima positions. In contrast, under an upper “balanced filling” type developmental framework, sources of organic matter are derived both internally and externally relative to the basin—exhibiting substantial heterogeneity—and regions marked by elevated organic matter concentrations are directly associated with locations identified as short-eccentric maxima.

Objective: The diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline. Methods: Simulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations. Results: REST produced small errors (the root mean square error (RMSE): 0.2936–0.4583; absolute errors: 0.2343–0.3657) and high correlations (>0.9) between the estimated signals and true ones. The comparison of configuration similarities in power among various electrode distributions revealed that REST induced infinity reference could maintain a perfect performance similar (>0.9) to that of true one. Conclusion: These results demonstrated that REST transformation could be adopted to resolve the channel location harmonization problem in large-scale EEG applications.

Omics methodologies, such as genomics, transcriptomics, proteomics, metabolomics, lipidomics and microbiomics, have revolutionized biological research by allowing comprehensive molecular analysis in livestock animals. However, despite being widely used in various animal species, research on donkeys has been notably scarce. China, renowned for its rich history in donkey husbandry, plays a pivotal role in their conservation and utilization. China boasts 24 distinct donkey breeds, necessitating conservation efforts, especially for smaller breeds facing extinction threats. So far, omics approaches have been employed in studies of donkey milk and meat, shedding light on their composition and quality. Similarly, omics methods have been utilized to explore the molecular basis associated with donkey growth, meat production, and quality traits. Omics analysis has also unraveled the critical role of donkey microbiota in health and nutrition, with gut microbiome studies revealing associations with factors such as pregnancy, age, transportation stress, and altitude. Furthermore, omics applications have addressed donkey health issues, including infectious diseases and reproductive problems. In addition, these applications have also provided insights into the improvement of donkey reproductive efficiency research. In conclusion, omics methodologies are essential for advancing knowledge about donkeys, their genetic diversity, and their applications across various domains. However, omics research in donkeys is still in its infancy, and there is a need for continued research to enhance donkey breeding, production, and welfare in China and beyond.

IntroductionTo investigate the differences in the response of radial growth of larch (Larix gmelinii) at varying altitude gradients to climatic factors, this study established tree-ring width chronologies of Larix gmelinii at altitudes of 900 m, 1,120 m and 1,300 m based dendroclimatology.MethodsWe also employed R packages including “dplR,” “static” and “moving” to determine the correlation between larch at different altitudes and climatic factors and to explore the sensitivity and stability between radial growth and the climate of larch at different altitudes in the northern part of the Greater Khingan Mountains Range in Northeast China.ResultsThe results revealed the radial growth of larch in high altitude areas to exhibit a downward trend due to climate warming, while the growth of trees in intermediate and low altitude areas showed an upward trend. The growth–climate relationship exhibited a significant negative correlation between radial growth in low altitude larch (900 m) and temperatures in the current winter (February and March) and growing season (July, October of the current year, and October of the previous year) (p

The tendril is a climbing organ in cucurbits and functions in physical support and to avoid shading by neighboring vegetation. However, how cucurbits produce tendrils to obtain climbing ability is largely unknown. In this study, tendril phenotypes were investigated during different developmental stages. Our results revealed that tendril growth exhibited an age-dependent pattern in cucurbits. Tendril growth was inhibited, and the tendril was formed as a short tendril [nonfunctional tendril (nonF-tendril), approximately 0.1 cm] during the seedling stage. In contrast, enhanced cell proliferation and cell expansion led to rapid elongation of the tendril during the climbing stage, and the tendril formed as a functional tendril (F-tendril, approximately 30 cm) to obtain climbing ability. RT-qPCR detection showed that age-dependent tendril growth correlated negatively with the abundance of the conserved age regulator CsmiR156. Defoliation induced CsmiR156 to inhibit CsSPLs, and F-tendril formation and climbing ability were delayed in defoliated cucumbers, which confirmed the role of CsmiR156 in regulating tendril growth in vivo. Additionally, exogenous gibberellin (GA) treatment showed that GA positively regulated tendril growth, and RT-qPCR detection showed that the GA bio-synthetic genes and metabolic genes were affected by age pathway, suggesting that the age pathway depended on GA bio-synthetic and metabolic pathway to regulate cell expansion to determine tendril growth. In summary, our work reveals that change in tendril type is an important marker of phase transition in cucumber, and tendril growth is regulated by an intrinsic developmental age signal, ensuring that the cucumber obtains climbing ability at a suitable age.

Abstract Chili pepper (Capsicum) is known for its unique fruit pungency due to the presence of capsaicinoids. The evolutionary history of capsaicinoid biosynthesis and the mechanism of their tissue specificity remain obscure due to the lack of high-quality Capsicum genomes. Here, we report two telomere-to-telomere (T2T) gap-free genomes of C. annuum and its wild nonpungent relative C. rhomboideum to investigate the evolution of fruit pungency in chili peppers. We precisely delineate Capsicum centromeres, which lack high-copy tandem repeats but are extensively invaded by CRM retrotransposons. Through phylogenomic analyses, we estimate the evolutionary timing of capsaicinoid biosynthesis. We reveal disrupted coding and regulatory regions of key biosynthesis genes in nonpungent species. We also find conserved placenta-specific accessible chromatin regions, which likely allow for tissue-specific biosynthetic gene coregulation and capsaicinoid accumulation. These T2T genomic resources will accelerate chili pepper genetic improvement and help to understand Capsicum genome evolution.

Abstract Background Few studies have utilized whole blood samples to investigate the association between metal mixture exposure during early pregnancy and spontaneous preterm birth (SPB). We conduct this nested case–control study to investigate both the independent and joint effect of each metal, and identify critical metals in the metal mixture. Results A total of 120 pregnant women with SPB and 120 pregnant women with full-term delivery were selected from the prospective birth cohort. We measured 14 metal concentrations in maternal blood collected during 10–13 weeks gestation. Conditional logistic regression showed that high concentrations of vanadium (V), magnesium, and copper were positively associated with SPB (Adjusted OR = 5.76 (95% CI 2.46–13.53), 3.64 (95% CI 1.64–8.09), 2.88 (95% CI 1.29–6.41), respectively). Moderate manganese (Mn) concentration (50th–75th percentile) group had the lowest estimated OR (Adjusted OR = 0.32 (95% CI 0.13–0.76)). The high level of strontium (Sr) was negatively associated with SPB (Adjusted OR = 0.39 (95% CI 0.17–0.91)). The BKMR model showed a significant positive joint effect of metal mixture exposure on SPB, while V was the most important metal. The non-linear effects of V and lead (Pb) on SPB, and the interaction effects between V–Pb, Sr–Mn were also revealed. Conclusions Maternal blood metal mixtures in the first trimester were found to be positively associated with SPB, with V exhibiting the strongest independent association. Mn had a potential U-shaped association with SPB. Elimination of metal contamination in the environment has a positive impact on maternal and child health.

Abstract This study aimed to evaluate the etiology and pregnancy outcomes of fetuses underwent invasive prenatal diagnosis for fetal growth restriction (FGR) accompanied by structural malformations. Data from 130 pregnancies referred for prenatal diagnosis for FGR accompanied by structural malformations were obtained between July 2011 and July 2023. Traditional karyotyping was conducted for all the subjects. A total of 37 (28.5%) cases of chromosomal abnormalities were detected by karyotyping, including 30 cases of numerical anomalies and seven cases of unbalanced structural anomalies. Trisomy 18 was the most common abnormalities, accounting for 51.4%, significantly higher than any other chromosomal abnormality. The cohort was predominantly comprised of early-onset FGR (88.5%) compared to late-onset FGR (11.5%). The incidences of chromosomal abnormalities in this two groups were 29.6% (34/115) and 20.0% (3/15), respectively (p > 0.05). The majority (74.6%, 97/130) of the cohort were affected by a single system malformation, with chromosomal abnormalities found in 19.6% (19/97) of cases. In pregnancies of structural malformations involving two and multiple systems, the frequencies were 56.5% (13/23), and 50.0% (5/10), respectively. Single nucleotide polymorphism array (SNP array) was performed in parallel for 65 cases, revealing additional 7.7% cases of copy number variants (CNVs) compared to karyotyping. Polymerase chain reaction (PCR) was used for detection of cytomegalovirus (CMV) DNA in 92 cases. All fetuses with FGR associated with two or more system malformations were either terminated or stillborn, irrespective of chromosomal aberrations. Conversely, 71.8% of pregnancies with a single-system malformation and normal genetic testing results resulted in live births. Furthermore, two (2.2%) cases tested positive for CMV DNA, leading to one termination and one case of serious developmental disorder after birth. Our study suggests that structural malformations associated with FGR are more likely to affect a single organ system. When multiple systems are involved, the incidence of chromosomal abnormalities and termination rates are notably high. We advocate for the use of CMA and CMV DNA examinations in FGR cases undergo invasive prenatal diagnosis, as these tests can provide valuable insights for etiological exploration and pregnancy management guidance.

With the advancement of remote sensing technology, the acquisition of ultra-high-resolution remote sensing imagery has become a reality, opening up new possibilities for detailed research and applications of Earth’s surface. These ultra-high-resolution images, with spatial resolutions at the meter or sub-meter level and pixel counts exceeding 4 million, contain rich geometric and attribute details of surface objects. Their use significantly improves the accuracy of surface feature analysis. However, this also increases the computational resource demands of deep learning-driven semantic segmentation tasks. Therefore, we propose the Transform Dual-Branch Attention Net (TDBAN), which effectively integrates global and local information through a dual-branch design, enhancing image segmentation performance and reducing memory consumption. TDBAN leverages a cross-collaborative module (CCM) based on the Transform mechanism and a data-related learnable fusion module (DRLF) to achieve adaptive content processing. Experimental results show that TDBAN achieves mean intersection over union (mIoU) of 73.6% and 72.7% on DeepGlobe and Inria Aerial datasets, respectively, and surpasses existing models in memory efficiency, highlighting its superiority in handling ultra-high-resolution remote sensing images. This study not only advances the development of ultra-high-resolution remote sensing image segmentation technology, but also lays a solid foundation for further research in this field.

In this paper, we propose a smoothing estimation method for censored quantile regression models. The method associates the convolutional smoothing estimation with the loss function, which is quadratically derivable and globally convex by using a non-negative kernel function. Thus, the parameters of the regression model can be computed by using the gradient-based iterative algorithm. We demonstrate the convergence speed and asymptotic properties of the smoothing estimation for large samples in high dimensions. Numerical simulations show that the smoothing estimation method for censored quantile regression models improves the estimation accuracy, computational speed, and robustness over the classical parameter estimation method. The simulation results also show that the parametric methods perform better than the KM method in estimating the distribution function of the censored variables. Even if there is an error setting in the distribution estimation, the smoothing estimation does not fluctuate too much.

(1) Background: To develop a novel capillary refill time measurement system and evaluate its reliability and reproducibility. (2) Methods: Firstly, the utilization of electromagnetic pressure technology facilitates the automatic compression and instantaneous release of the finger. Secondly, the employment of pressure sensing technology and photoelectric volumetric pulse wave analysis technology enables the dynamic monitoring of blood flow in distal tissues. Thirdly, the subjects were recruited to compare the average measurement time and the number of measurements required for successful measurements. The satisfaction of doctors and patients with the instrument was investigated through the administration of questionnaires. Finally, 71 subjects were recruited and divided into two groups, A and B. Three doctors repeated the measurement of the right index fingers of the subjects. In Group A, the same measuring instrument was used, and the consistency of the measurements was evaluated using the intragroup correlation coefficient. In Group B, one doctor repeated the measurement of each subject three times using the same measuring instrument, and the reproducibility of the CRT was evaluated using the analysis of variance of the repeated measurement data. (3) Results: The development of the capillary refill time meter was successful, with an average measurement time of 18 s and a single measurement. This study found that doctor–patient satisfaction levels were 98.3% and 100%, respectively. The intraclass correlation coefficient was 0.995 in Group A, and the p-value was greater than 0.05 in Group B. (4) Conclusions: The non-invasive monitoring of microcirculation has been rendered both rapid and effective, thus paving the way for the further mechanization and standardization of this process. The CRT, when measured using the capillary refill time meter test machine, demonstrated consistent and reproducible results, both when assessed by different researchers and when evaluated across varying measurement sets.

An intelligent prediction model for rice yield in small-scale cultivation areas can provide precise forecasting results for farmers, rice planting enterprises, and researchers, holding significant importance for agricultural industries and crop science research within small regions. Although machine learning can handle complex nonlinear problems to enhance prediction accuracy, further improvements in models are still needed to accurately predict rice yields in small areas facing complex planting environments, thereby enhancing model performance. This study employs four rice phenotypic traits, namely, panicle angle, panicle length, total branch length, and grain number, along with seven machine learning methods—multiple linear regression, support vector machine, MLP, random forest, GBR, XGBoost, and LightGBM—to construct a yield prediction model group. Subsequently, the top three models with the best performance in individual model predictions are integrated using voting and stacking ensemble methods to obtain the optimal integrated model. Finally, the impact of different rice phenotypic traits on the performance of the stacked ensemble model is explored. Experimental results indicate that the random forest model performs best after individual machine learning modeling, with RMSE, R2, and MAPE values of 0.2777, 0.9062, and 17.04%, respectively. After model integration, Stacking–3m demonstrates the best performance, with RMSE, R2, and MAPE values of 0.2483, 0.9250, and 6.90%, respectively. Compared to the performance after random forest modeling, the RMSE decreased by 10.58%, R2 increased by 1.88%, and MAPE decreased by 0.76%, indicating improved model performance after stacking ensemble. The Stacking–3m model, which demonstrated the best comprehensive evaluation metrics, was selected for model validation, and the validation results were satisfactory, with MAE, R2, and MAPE values of 8.3384, 0.9285, and 0.2689, respectively. The above research findings demonstrate that this integrated model possesses high practical value and fills a gap in precise yield prediction for small-scale rice cultivation in the Yunnan Plateau region.

The monitoring of peripheral circulation, as indicated by the capillary refill time, is a sensitive and accurate method of assessing the microcirculatory status of the body. It is a widely used tool for the evaluation of critically ill patients, the guidance of therapeutic interventions, and the assessment of prognosis. In recent years, there has been a growing emphasis on microcirculation monitoring which has led to an increased focus on capillary refill time. The International Sepsis Guidelines, the American Academy of Pediatrics, the World Health Organization, and the American Heart Association all recommend its inclusion in the evaluation of the system in question. Furthermore, the methodology for its measurement has evolved from a traditional manual approach to semiautomatic and fully automatic techniques. This article presents a comprehensive overview of the current research on the measurement of capillary refill time, with a particular focus on its clinical significance. The aim is to provide a valuable reference for clinicians and researchers and further advance the development and application of microcirculation monitoring technology.

Objective: This study aimed to investigate the relationship between maternal serum uric acid levels in the first trimester and the incidence of congenital heart diseases (CHDs) in offspring. Methods: This prospective cohort study was conducted in the southeast of China and involved 21,425 pregnant women and their offspring in the final analysis between 2019 and 2022. Fasting blood samples from pregnant women participating in the Fujian birth cohort study (11.3 ± 1.40 weeks of gestation) were analyzed for serum uric acid levels. The perinatal outcome was the incidence of CHDs. All fetuses with CHDs were confirmed by echocardiography doctors and pediatric cardiologists. Logistic regression analysis and restricted cubic spline (RCS) modeling were employed to investigate the relationship between serum uric acid level and the incidence of CHDs. Results: We observed that maternal log2-transformed values of serum uric acid were strongly associated with odds of CHDs in offspring (adjusted odds ratio [AOR] 1.589, 95 % CI [1.149, 2.198]). Compared to the lowest quartile, the AORs for maternal uric acid levels in the other quartiles and the corresponding risk of CHDs in offspring were 1.363 (95 % CI [1.036, 1.793]), 1.213 (95 % CI [0.914, 1.610]), and 1.472 (95 % CI [1.112, 1.949]), respectively. Hyperuricemia in the first trimester significantly increased the risk of CHDs in offspring 1.837 (95 % CI [1.073, 3.145]). Furthermore, RCS showed a linear relationship between maternal serum uric acid levels in the first trimester and the incidence of CHDs (P for nonlinearity = 0.71). Conclusions: The results of this study indicated that elevated maternal serum uric acid levels in the first trimester were associated with an increased incidence of CHDs in offspring.

IntroductionIn response to the issues of complexity and low efficiency in line loss calculations for actual distribution networks, this paper proposes a fast power flow calculation method for distribution networks based on Neo4j graph models and a hierarchical forward-backward sweep parallel algorithm.MethodsFirstly, Neo4j is used to describe the distribution network structure as a simple graph model composed of nodes and edges. Secondly, a hierarchical forward-backward sweep method is adopted to perform power flow calculations on the graph model network. Finally, during the computation of distribution network subgraphs, the method is combined with the Bulk Synchronous Parallel (BSP) computing model to quickly complete the line loss analysis.Results and DiscussionResults from the IEEE 33-node test system demonstrate that the proposed method can calculate network losses quickly and accurately, with a computation time of only 0.175s, which is lower than the MySQL and Neo4j graph methods that do not consider hierarchical parallel computing.

Traditional load prediction methods are unable to effectively predict the loads according to the spatial topology of each electricity consumer in neighboring areas and the load dependency correlations. In order to further improve the load prediction accuracy of each consumer in the region, this paper proposes a short-term prediction method of electric load based on multi-graph convolutional network. First, the input data are selected with maximum information coefficient method by integrating multi-dimensional information such as load, weather, electricity price and date in the areas. Then, a gated convolutional network is used as a temporal convolutional layer to capture the temporal features of the loads. Moreover, a physical-virtual multi-graph convolutional network is constructed based on the spatial location of each consumer as well as load dependencies to capture the different evolutionary correlations of each spatial load. Comparative studies have validated the effectiveness of the proposed model in improving the prediction accuracy of power loads for each consumer.

Investigating the long-term dynamics in the canopy proves to be difficult due to the short observational records of the normalized difference vegetation index (NDVI). To explore the linkage between tree growth, NDVI dynamics and large-scale atmospheric circulation in the Greater Khingan Mountain, Northeast China, we established a chronology of Larix gmelinii tree ring width at three elevations (870–920 m, 1,100–1,150 m and 1,270–1,320 m) in the northern foothills of the mountain range. We then calculated the correlations between the tree ring chronologies and NDVI and climate factors, and reconstructed the NDVI time series from June to September 1759–2021 in the region based on the middle-elevation tree ring chronology. The results identify the positive effect of temperature (r = 0.56, p < 0.01) and the negative effect of precipitation (r = −0.44, p < 0.01) in the growing season as the main influencing factors of NDVI for the study period (1981–2019). The 11-year moving average of the reconstructed NDVI series reveals two periods of high canopy vigor (1898–1926 and 2009–2013) and three periods of low canopy vigor (1860–1962, 1882–1888 and 1968–1977) in the last 263 years. These periods correspond to drought events recorded in the historical literature. Wavelet analysis shows that the reconstructed sequences exhibited 11–13, 23–25, and 39–42 years period variations. Integrating this with spatial correlation analysis reveals that tree growth in the Mangui region was impacted by the combined effect of the North Pacific Decadal Oscillation and the North Atlantic Multidecadal Oscillation. The results of this paper provide a reference for the study of vegetation change patterns in the northern foothills of the Greater Khingan Mountains.

Abstract This study aimed to investigate the association of lipid profile in early pregnancy and the risk of congenital heart disease (CHD) in offspring. This study was a prospective cohort design based on the Fujian Birth Cohort Study in China. We recruited pregnant women at ≤ 14 weeks of gestation between 2019 and 2022, and all participants in this study filled out the questionnaire about periconceptional exposure. Simultaneously, we collected participants’ fasting blood samples to measure their lipid profile by automatic biochemical analyzer. The outcome was defined as offspring with CHD. A multivariable logistic regression model was used to calculate adjusted odds ratio (AOR) risk estimates, which indicate the associations between maternal lipid profiles and CHD in offspring. Restricted cubic splines were used to estimate their nonlinear relationship. A total of 21,425 pregnant women with an average gestational age of 11.3 (± 1.40) weeks were included in the analysis. The higher triglyceride (AOR 1.201, 95% CI [1.036, 1.394]), low-density lipoprotein (AOR 1.216, 95% CI [1.048, 1.410]), apolipoprotein B (Apo B) (AOR 2.107, 95% CI [1.179, 3.763]) levels were correlated with increased odds of CHD in offspring, while high-density lipoprotein (OR 0.672, 95% CI [0.490, 0.920]) related with decreased odds of CHD in offspring. The restricted cubic spline suggested a nonlinear relationship between total cholesterol (TC) levels and the risk of CHD in offspring (P = 0.0048), but no significant nonlinear relationships were found in other lipid profile. Apolipoprotein A was not related to the risk of CHD in offspring as either a continuous variable or a hierarchical variable. Elevated lipid profile in early pregnancy levels are associated with an increased risk of CHD in offspring. Additionally, there is a non-linear relationship between TC levels and the risk of CHD in offspring.

Abstract Background Amyotrophic lateral sclerosis (ALS) is an irreversible degenerative disease. Placebo-controlled randomized trials are currently the main trial design to assess the clinical efficacy of drugs for ALS treatment. The aim of this study was to establish models to quantitatively describe the course of ALS, explore influencing factors, and provide the necessary information for ALS drug development. Methods We conducted a comprehensive search of PubMed and the Cochrane Library Central Register for placebo-controlled trials that evaluated treatments for ALS. From these trials, we extracted the clinical and demographic characteristics of participants in the placebo group, as well as outcome data, which encompassed overall survival (OS) and Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) scores, at various time points. Results In total, 47 studies involving 6118 participants were included. Disease duration and the proportion of patients receiving riluzole were identified as significant factors influencing OS in the placebo group. Specifically, the median OS was 35.5 months for a disease duration of 9 months, whereas it was 20.0 months for a disease duration of 36 months. Furthermore, for every 10% increase in the proportion of patients treated with riluzole (100 mg daily), there was an association with a median OS extension of approximately 0.4 months. The estimated time for the ALSFRS-R score in the placebo group to decrease to 50% of its maximum effect from baseline level was approximately 17.5 months, and the time to reach a plateau was about 40 months. Conclusions The established disease course model of the historical placebo group is valuable in the decision-making process for the clinical development of ALS drugs. It serves not only as an external control to evaluate the efficacy of the tested drug in single-arm trials but also as prior information that aids in accurately estimating the posterior distribution of the disease course in the placebo group during small-sample clinical trials.

Abstract Alzheimer’s disease (AD) is a neurodegenerative disease with insidious onset and progressive development. It is clinically characterized by cognitive impairment, memory impairment and behavioral change. Chinese herbal medicine and acupuncture are important components of traditional Chinese medicine (TCM), and are commonly used in clinical treatment of AD. This paper systematically summarizes the research progress of traditional Chinese medicine natural products and acupuncture treatment of AD, which combined with existing clinical and preclinical evidence, based on a comprehensive review of neuroinflammation, and discusses the efficacy and potential mechanisms of traditional Chinese medicine natural products and acupuncture treatment of AD. Resveratrol, curcumin, kaempferol and other Chinese herbal medicine components can significantly inhibit the neuroinflammation of AD in vivo and in vitro, and are candidates for the treatment of AD. Acupuncture can alleviate the memory and cognitive impairment of AD by improving neuroinflammation, synaptic plasticity, nerve cell apoptosis and reducing the production and aggregation of amyloid β protein (Aβ) in the brain. It has the characteristics of early, safe, effective and benign bidirectional adjustment. The purpose of this paper is to provide a basis for improving the clinical strategies of TCM for the treatment of AD. Graphical Abstract

Abstract Chinese motherwort (Leonurus japonicus), a member of Lamiaceae family, is a commonly used medicinal herb for treating obstetrical and gynecological diseases, producing over 280 officinal natural products. Due to limited genomic resources, little progress has been made in deciphering the biosynthetic pathway of valuable natural products in L. japonicus. Here, we de novo assembled the L. japonicus genome using high-coverage ONT long reads and Hi-C reads. The chromosome-level genome assembly contained ten chromosomes representing 99.29% of 489.34 Mb genomic sequence with a contig and scaffold N50 of 7.27 Mb and 50.86 Mb, respectively. Genome validations revealed BUSCO and LAI score of 99.2% and 21.99, respectively, suggesting high quality of genome assembly. Using transcriptomic data from various tissues, 22,531 protein-coding genes were annotated. Phylogenomic analysis of 13 angiosperm plants suggested L. japonicus had 58 expanded gene families functionally enriched in specialized metabolism such as diterpenoid biosynthesis. The genome assembly, annotation, and sequencing data provide resources for the elucidation of biosynthetic pathways behind natural products of pharmaceutical applications in L. japonicus.

Abstract Background Transforming growth factor β (TGFβ) is a critical regulator of lung metastasis of breast cancer and is correlated with the prognosis of breast cancer. However, not all TGFβ stimulated genes were functional and prognostic in breast cancer lung metastatic progress. In this study, we tried to determine the prognosis of TGFβ stimulated genes in breast cancer. Methods TGFβ stimulated genes in MDA-MB-231 cells and lung metastasis-associated genes in LM2-4175 cells were identified through gene expression microarray. The prognosis of the induced gene (TGFBI) in breast cancer was determined through bioinformatics analysis and validated using tissue microarray. The immune infiltrations of breast cancer were determined through “ESTIMATE” and “TIMER”. Results TGFBI was up-regulated by TGFβ treatment and over-expressed in LM2-4175 cells. Through bioinformatics analysis, we found that higher expression of TGFBI was associated with shorted lung metastasis-free survival, relapse-free survival, disease-free survival, and overall survival of breast cancer. Moreover, the prognosis of TGFBI was validated in 139 Chinese breast cancer patients. Chinese breast cancer patients with higher TGFBI expression had lower overall survival. Correspondingly, breast cancer patients with higher TGFBI methylation had higher overall survival. TGFBI was correlated with the score of the TGFβ signaling pathway and multiple immune-related signaling pathways in breast cancer. The stromal score, immune score, and the infiltrations of immune cells were also correlated with TGFBI expression in breast cancer. Conclusions TGFβ-induced gene TGFBI was correlated with the prognosis and immune infiltrations of breast cancer.

Previous studies reported that DDB1 and CUL4 associated factor 7 (DCAF7) is associated with craniofacial, muscle, fat and bone growth and development. Therefore, the objective of this study was to explore genetic variation in the DCAF7 gene and its potential association with number of thoracolumbar vertebrae and carcass traits in Dezhou donkeys. Seven single-nucleotide polymorphisms (SNPs) were detected by targeted sequencing and Sanger sequencing in the intron region of the DCAF7 gene in 406 Dezhou donkeys. The polymorphism at g.48991059 T > G was significantly associated with hide weight (P C, g.48985896 A > G, g.48987539 C > T, g.48988058 A > G and g.48992171 C > T sites were associated with number of thoracic vertebrae (P

Certain amino acids changes in the human Na+/K+-ATPase pump, ATPase Na+/K+ transporting subunit alpha 1 (ATP1A1), cause Charcot-Marie-Tooth disease type 2 (CMT2) disease and refractory seizures. To develop in vivo models to study the role of Na+/K+-ATPase in these diseases, we modified the Drosophila gene homolog, Atpα, to mimic the human ATP1A1 gene mutations that cause CMT2. Mutations located within the helical linker region of human ATP1A1 (I592T, A597T, P600T, and D601F) were simultaneously introduced into endogenous Drosophila Atpα by CRISPR/Cas9-mediated genome editing, generating the AtpαTTTF model. In addition, the same strategy was used to generate the corresponding single point mutations in flies (AtpαI571T, AtpαA576T, AtpαP579T, and AtpαD580F). Moreover, a deletion mutation (Atpαmut) that causes premature termination of translation was generated as a positive control. Of these alleles, we found two that could be maintained as homozygotes (AtpαI571T and AtpαP579T). Three alleles (AtpαA576T, AtpαP579 and AtpαD580F) can form heterozygotes with the Atpαmut allele. We found that the Atpα allele carrying these CMT2-associated mutations showed differential phenotypes in Drosophila. Flies heterozygous for AtpαTTTF mutations have motor performance defects, a reduced lifespan, seizures, and an abnormal neuronal morphology. These Drosophila models will provide a new platform for studying the function and regulation of the sodium-potassium pump.

Donkey meat has gained popularity as an emerging meat product due to its superior nutritional value and distinctive flavor. Despite this, research on the molecular mechanisms that contribute to meat quality, particularly within the field of proteomics, remains limited. This study aimed to address this gap by utilizing the data-independent acquisition (DIA) technique to identify differentially expressed proteins (DEPs) in the gluteus superficialis (WG), longissimus thoracis (WLT), and semitendinosus (WS) muscles of donkeys. Our analysis revealed 189 and 384 DEPs in the WG/WLT and WS/WLT muscles, respectively. Several significant potential pathways, involving these DEPs, were found to be closely associated with donkey meat quality. These pathways include fatty acid biosynthesis, TGF-β signaling, FOXO signaling, mTOR signaling, oxidative phosphorylation, citrate cycle, alanine, aspartate, and glutamate metabolism, arginine biosynthesis, and valine, leucine, and isoleucine degradation. The identified DEPs and their regulated pathways were involved in regulating intramuscular fat deposition, protein metabolism, and amino acid metabolism in donkey muscles. These mechanisms have a direct impact on the physicochemical properties and flavor of donkey meat. Our findings contribute to a better understanding of the molecular processes influencing the quality of donkey meat. Additionally, the findings of our study may be influenced by the sample size. Therefore, further research with a larger sample is needed to provide a more comprehensive evaluation of meat quality.

A method for identifying six estrogen preparations by thin-layer chromatography combined with Raman imaging microscopy (TLC-RIM) was established. An appropriate pretreatment method was adopted to extract and purify the six estrogen preparations. After that, each estrogen extraction solution was spotted on a thin-layer chromatography plate. Estriol (E3), estradiol (E2), estradiol valerate (EV), estradiol benzoate (EB), nilestriol (CEE), and ethinylestradiol (EE2) were separated by TLC, and their Rf value and localization were determined under a UV lamp at 254 nm, followed by the in situ enrichment of the drug component. Using a 532 nm laser as the light source, the Raman scattering spectrum of the component was directly collected by micro-Raman imaging. The Rf values after TLC separation of the six estrogens and their Raman spectra can, respectively, reflect differences in polarity and structure, and they are not affected by the excipients of preparation. The detection limits of the six estrogens are 0.636, 1.00, 0.687, 0.497, 0.649, and 0.626 mg/mL. Based on the intensity of the minimum characteristic peak, the stability results within 40 min showed that the RSD of each substance is 1.34, 2.06, 1.65, 3.99, 1.16, and 2.71%, respectively. This method has strong specificity, good stability, and high sensitivity, and it can provide a new reference for improving the identification standards of estrogen preparations.

Presently, on-orbit calibration methods have several problems, such as low calibration accuracy and broken traceability links, so an urgent need exists to unify traceable and high-precision on-orbit radiometric calibration loads as benchmarks for cross-transfer radiometric calibration. Considering the deficiencies of current on-orbit calibration, this paper proposes adjusting the size of the variable diaphragm at the entrance pupil and the integration time to attain large dynamic attenuation, converting the radiometric calibration into absolute geometric calibration of the attenuation device, and realizing a self-calibrating real entrance pupil imaging spectrometer (SCREPIS) that can be directly used to view the Earth and the Sun and quickly obtain apparent reflectance data. An initial structural design method based on the distance between individual mirrors is proposed according to the instrument design requirements. The design of a real entry pupil image-side telecentricity off-axis three-reflector front optical system with a 7° field of view along the slit direction, a 3.7 systematic F-number, and a 93 mm focal length is finally realized, and the system image plane energy is verified to change proportionally to the variable diaphragm area. Finally, the front system and rear Offner optical system are jointly simulated and optically designed. The system provides instrumental support for cross-calibration and theoretical support and a technical basis for planning space-based radiation references.

A carbon fiber-reinforced polymer (CFRP) is a common material utilized for the enhancement in reinforced concrete (RC) constructions. Previous research indicates that the bonding performance between a CFRP sheet and concrete determines whether the bonding of CFRP material is effective. However, the majority of existing research on the bonding performance of the CFRP–concrete interface is concentrated on static loading conditions. In order to clarify the effect of dynamic load on the bonding performance of the CFRP sheet–concrete interface, this study adopts the double-sided shear test method to carry out dynamic experimental research. The test findings reveal that the damage pattern of the CFRP sheet–concrete interface remains consistent across different loading rates. The ultimate bearing capacity increases as the strain rate increases. As the strain rate increases from 10−5 s−1 to 10−2 s−1, the effect of bond length on ultimate bearing capacity increases by about 7%. As the strain rate increases, both the maximum strain of CFRP and the maximum interfacial shear stress demonstrate a corresponding increase, with respective increase rates of 60% and 20%. The effective bond length decreases by about 20% when the strain rate rises from 10−5 s−1 to 10−2 s−1. Finally, a formula for calculating the dynamic effective bond length of a CFRP sheet, grounded in the Chen and Teng formula, has been proposed and verified.

The current seismic prediction methods of the shale brittleness index are all based on the pre-stack seismic inversion of elastic parameters, and the elastic parameters are transformed by Rickman and other simple linear mathematical relationship formulas. In order to address the low accuracy of the seismic prediction results for the brittleness index, this study proposes a method for predicting the brittleness index of shale reservoirs based on an error backpropagation neural network (BP neural network). The continuous static rock elastic parameters were calculated by fitting the triaxial test data with well logging data, and the static elastic parameters with good correlation with the brittleness index of shale minerals were selected as the sample data of the BP neural network model. A dataset of 1970 data points, characterized by Young’s modulus, Poisson’s ratio, shear modulus, and the mineral brittleness index, was constructed. A total of 367 sets of data points from well Z4 were randomly retained as model validation data, and 1603 sets of data points from the other three wells were divided into model training data and test data at a ratio of 7:3. The calculation accuracy of the model with different numbers of nodes was analyzed and the key parameters of the BP neural network structure such as the number of input layers, the number of output layers, the number of hidden layers, and the number of neurons were determined. The gradient descent method was used to determine the weight and bias of the model parameters with the smallest error, the BP neural network model was trained, and the stability of the brittleness index prediction model of the BP neural network was verified by posterior data. After obtaining Young’s modulus, Poisson’s ratio, and shear modulus through pre-stack seismic inversion, the BP neural network model established in this study was used to predict the brittleness index distribution of the target layer in the study area. Compared with the conventional Rickman method, the prediction coincidence rate is 69.16%, and the prediction coincidence rate between the prediction results and the real value is 95.79%, which is 26.63% higher. The BP neural network method proposed in this paper provides a reliable new method for seismic prediction of the shale reservoir brittleness index, which has important practical significance for clarifying the shale gas development scheme and improving shale gas exploitation efficiency.

Abstract Background Genetic 1p deletion is reported in 30% of all neuroblastoma and is associated with the unfavorable prognosis of neuroblastoma. The expressions and prognosis of 1p candidate genes in neuroblastoma are unclear. Methods Public neuroblastoma cohorts were obtained for secondary analysis. The prognosis of 1p candidate genes in neuroblastoma was determined using Kaplan-Meier and cox regression analysis. The prediction of the nomogram model was determined using timeROC. Results First, we confirmed the bad prognosis of 1p deletion in neuroblastoma. Moreover, zinc finger protein 436 (ZNF436) located at 1p36 region was down-regulated in 1p deleted neuroblastoma and higher ZNF436 expression was associated with the longer event free survival and overall survival of neuroblastoma. The expression levels of ZNF436 were lower in neuroblastoma patients with MYCN amplification or age at diagnosis ≥ 18months, or with stage 4 neuroblastoma. ZNF436 had robust predictive values of MYCN amplification and overall survival of neuroblastoma. Furthermore, the prognostic significance of ZNF436 in neuroblastoma was independent of MYCN amplification and age of diagnosis. Combinations of ZNF436 with MYCN amplification or age of diagnosis achieved better prognosis. At last, we constructed a nomogram risk model based on age, MYCN amplification and ZNF436. The nomogram model could predict the overall survival of neuroblastoma with high specificity and sensitivity. Conclusions Chromosome 1p36 candidate gene ZNF436 was a prognostic maker of neuroblastoma.

Abstract Background Tumor cells can resist chemotherapy-induced pyroptosis through glycolytic reprogramming. Estrogen-related receptor alpha (ERRα) is a central regulator of cellular energy metabolism associated with poor cancer prognosis. Herein, we refine the oncogenic role of ERRα in the pyroptosis pathway and glycolytic metabolism. Methods The interaction between ERRα and HIF-1α was verified using co-immunoprecipitation. The transcriptional binding sites of ERRα and NLRP3 were confirmed using dual-luciferase reporter assay and cleavage under targets and tagmentation (CUT&Tag). Flow cytometry, transmission electron microscopy, scanning electron microscopy, cell mito stress test, and extracellular acidification rate analysis were performed to investigate the effects of ERRα on the pyroptosis pathway and glycolytic metabolism. The results of these experiments were further confirmed in endometrial cancer (EC)-derived organoids and nude mice. In addition, the expression of ERRα-related pyroptosis genes was analyzed using The Cancer Genome Atlas and Gene Expression Omnibus database. Results Triggered by a hypoxic microenvironment, highly expressed ERRα could bind to the promoter of NLRP3 and inhibit caspase-1/GSDMD signaling, which reduced inflammasome activation and increased pyroptosis resistance, thereby resulting in the resistance of cancer cells to cisplatin. Moreover, ERRα activated glycolytic rate-limiting enzyme to bridge glycolytic metabolism and pyroptosis in EC. This phenomenon was further confirmed in EC-derived organoids and nude mice. CUT & Tag sequencing and The Cancer Genome Atlas database analysis showed that ERRα participated in glycolysis and programmed cell death, which resulted in EC progression. Conclusions ERRα inhibits pyroptosis in an NLRP3-dependent manner and induces glycolytic metabolism, resulting in cisplatin resistance in EC cells.

Abstract Background and purpose Malignant brain edema (MBE) occurring after mechanical thrombectomy (MT) in acute ischemic stroke (AIS) could lead to severe disability and mortality. We aimed to investigate the incidence, predictors, and clinical outcomes of MBE in patients with AIS after MT. Methods The clinical and imaging data of 155 patients with AIS of anterior circulation after MT were studied. Standard non-contrast CT was used to evaluate baseline imaging characteristics at admission. Clinical outcomes were measured using the 90-day modified Rankin Scale (mRS) score. Based on the follow-up CT scans performed within 72 h after MT, the patients were classified into MBE and non-MBE group. MBE was defined as a midline shift of ≥ 5 mm with signs of local brain swelling. Univariate and multivariate regression analyses were used to analyze the relationship between MBE and clinical outcomes and identify the predictors that correlate with MBE. Results MBE was observed in 19.4% of the patients who underwent MT and was associated with a lower rate of favorable 90-day clinical outcomes. Significant differences were observed in both MBE and non-MBE groups: baseline Alberta Stroke Program Early CT (ASPECT) score, hyperdense middle cerebral artery sign (HMCAS), baseline signs of early infarct, angiographic favorable collaterals, number of retrieval attempts, and revascularization rate. Multivariate analysis indicated that low baseline ASPECT score, absent HMCAS, angiographic poor collaterals, more retrieval attempt count, and poor revascularization independently influenced the occurrence of MBE in AIS patients with anterior circulation after MT. Conclusion MBE was associated with a lower rate of favorable 90-day clinical outcomes. Low baseline ASPECT score, absent HMCAS, angiographic poor collaterals, more retrieval attempt count and poor revascularization were independently associated with MBE after MT.

IntroductionThe uridine diphosphate (UDP)-glycosyltransferase (UGT) family is the largest glycosyltransferase family, which is involved in the biosynthesis of natural plant products and response to abiotic stress. UGT has been studied in many medicinal plants, but there are few reports on Platycodon grandiflorus. This study is devoted to genome-wide analysis of UGT family and identification of UGT genes involved in drought stress of Platycodon grandiflorus (PgUGTs).MethodsThe genome data of Platycodon grandiflorus was used for genome-wide identification of PgUGTs, online website and bioinformatics analysis software was used to conduct bioinformatics analysis of PgUGT genes and the genes highly responsive to drought stress were screened out by qRT-PCR, these genes were cloned and conducted bioinformatics analysis.ResultsA total of 75 PgUGT genes were identified in P.grandiflorus genome and clustered into 14 subgroups. The PgUGTs were distributed on nine chromosomes, containing multiple cis-acting elements and 22 pairs of duplicate genes were identified. Protein-protein interaction analysis was performed to predict the interaction between PgUGT proteins. Additionally, six genes were upregulated after 3d under drought stress and three genes (PGrchr09G0563, PGrchr06G0523, PGrchr06G1266) responded significantly to drought stress, as confirmed by qRT-PCR. This was especially true for PGrchr06G1266, the expression of which increased 16.21-fold after 3d of treatment. We cloned and conducted bioinformatics analysis of three candidate genes, both of which contained conserved motifs and several cis-acting elements related to stress response, PGrchr06G1266 contained the most elements.DiscussionPgGT1 was confirmed to catalyze the C-3 position of platycodin D and only eight amino acids showed differences between gene PGr008G1527 and PgGT1, which means PGr008G1527 may be able to catalyze the C-3 position of platycodin D in the same manner as PgGT1. Seven genes were highly expressed in the roots, stems, and leaves, these genes may play important roles in the development of the roots, stems, and leaves of P. grandiflorus. Three genes were highly responsive to drought stress, among which the expression of PGrchr06G1266 was increased 16.21-fold after 3d of drought stress treatment, indicating that PGrchr06G1266 plays an important role in drought stress tolerance. To summarize, this study laied the foundation to better understand the molecular bases of responses to drought stress and the biosynthesis of platycodin.

Abstract Background At present, donkey meat in the market shows an imbalance between supply and demand, and there is an urgent need to cultivate a meat-type Dezhou donkey breed. On the one hand, it can improve the imbalance in the market, and on the other hand, it can promote the rapid development of the donkey industry. This study aimed to reveal significant genetic variation in the NK1 homeobox 2 gene (NKX1-2) of Dezhou donkeys and investigate the association between genotype and body size in Dezhou donkeys. Results In this study, a SNP (g.54704925 A > G) was identified at the exon4 by high-depth resequencing of the Dezhou donkey NKX1-2 gene. The AA genotype is the dominant genotype. The g.54704925 A > G site was significantly associated with body length, thoracic girth, and hide weight (P G locus could be used as a marker locus for selection and breeding.