Search

Zhongwei Sha, Jian Xu, Nana Li, Ou Li Department of Mental Diseases, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Zhongwei Sha, Department of Mental Diseases, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhijiang Road, Zhabei, Shanghai, 200071, People’s Republic of China, Tel/Fax +86 21-56639828, Email shazhongwei1989@163.comAbstract: Synaptic plasticity is the capacity of synaptic transmission between neurons to be strengthened or weakened. There are many signal molecules accumulated in the presynaptic and postsynaptic membranes that can lead to the regulation of synaptic plasticity and involvement in numerous of neurological and psychiatric diseases, including anxiety disorder. However, the regulatory mechanisms of synaptic plasticity in the development of anxiety disorder have not been well summarized. This review mainly aims to discuss the biological functions and mechanisms of synaptic plasticity-related molecules in anxiety disorder, with a particular focus on the metabotropic glutamate receptors, brain-derived neurotrophic factor, hyperpolarization-activated cyclic nucleotide–gated channels, and postsynaptic density 95. The summarized functions and mechanisms of synaptic plasticity-related molecules in anxiety will provide insight into novel neuroplasticity modifications for targeted therapy for anxiety.Keywords: synaptic plasticity, anxiety, mGluRs, BDNF, HCN, PSD95

Cuiju Wang,1 Yalei Lv,2 Ziyue Sha,3 Jingjing Zhang,3 Jianhua Wu,4 Yixin Qi,5 Zhanjun Guo3 1Department of Gynaecology Ultrasound, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 2Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 3Department of Immunology and Rheumatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 4Animal Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 5Breast Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of ChinaCorrespondence: Yixin Qi; Zhanjun Guo Email 13932153600@139.com; zjguo5886@aliyun.comPurpose: Vascular endothelial growth factor (VEGF) family members contribute greatly to the development and angiogenesis of hypervascular hepatocellular carcinoma (HCC). We have previously shown that Dicer inhibited HCC growth. In this study, we aimed to determine the relationship between Dicer and VEGF in HCC.Methods: Gain-of-function studies were performed to determine the effect of different treatments on the proliferation, migration, and invasion of HCC cells. Expression of VEGF-A in xenograft tumor tissues was analysed using Western blotting, and that of CD31 using immunohistochemical analysis.Results: We found that Dicer inhibited proliferation, migration and invasion of HCC cells by suppressing VEGF-A expression. Interestingly, VEGF-A165, which is the most prominent VEGF-A isoform, counteracted Dicer-induced inhibition of HCC cells. In addition, a monoclonal anti-VEGF antibody (bevacizumab) enhanced Dicer-induced inhibition of HCC in vitro and in vivo. Further, immunohistochemical analysis of CD31 indicated bevacizumab and Dicer synergized to reduce tumor microvessel density.Conclusion: Our data demonstrated that Dicer enhanced bevacizumab-related inhibition of HCC cell via the VEGF pathway; therefore, Dicer in coordination with bevacizumab may provide another potential approach for HCC therapy.Keywords: hepatocellular carcinoma, vascular endothelial growth factor, Dicer, bevacizumab, microvessel density

While microalloying of metallic glasses (MGs) using hydrogen emerged a few years ago, the underlying mechanism of how hydrogen microalloying influences mechanical behaviors is currently still under debate. Herein, we perform atomistic simulations to investigate the effect of hydrogen microalloying on the mechanical profiles of MGs. The mitigation of strain localization accompanied with plenty of shear transformation zones (STZs) is exhibited in H-alloyed MGs and becomes more significant with the increase of H content. The addition of hydrogen induces a loose atomic structure with fertile liquid-like regions and abundant free volume, which triggers more STZ events and the softening behavior. Furthermore, hydrogen doping lowers the STZ activation energy barrier, which is verified by a theoretical model based on the concept of energetic criterion. Our work provides some new insight on how to tune the local packing of MGs and further alter the deformation behavior. [ABSTRACT FROM AUTHOR]

While hydrogen microalloying in metallic alloys has been extensively investigated, the failure mechanism underlying the H-alloyed metallic glasses (MGs) remains elusive. Here, atomistic simulations are performed on the tensile failure of H-free and H-alloyed notched MGs. An intriguing transition in failure mechanism from shear banding to cracking occurs after hydrogen microalloying. A theoretical model based on the concept of energetic model is then proposed to rationalize this deformation mode transition. Cracking behavior is more significant with increasing H content, agreeing well with the simulation results. These results advance our understanding of failure mechanism in H-alloyed MGs. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays a crucial role in the global water and energy cycle. Upscaling instantaneous ET ([Formula: see text]) to daily ET ([Formula: see text]) is vital for thermal-based ET estimation. Conventional methods – such as the constant evaporative fraction method (ConEF), radiation-based method, and evaporative ratio method – often overlook environmental factors, leading to biased estimates of [Formula: see text] from [Formula: see text]. To resolve this issue, this study aimed to assess four machine learning (ML) algorithms—XGBoost, LightGBM, AdaBoost, and Random Forest—to integrate meteorological and remote sensing data for upscaling [Formula: see text] across 88 global flux sites. Each ML model was tested with eight different variable combinations. Results indicated that XGBoost exhibited the best performance, with a root mean square error (RMSE) generally below 13 W [Formula: see text] in estimating [Formula: see text] from [Formula: see text]. The best variable combination simultaneously considers evaporative fraction, available energy, meteorology factors, remote sensing albedo, normalized vegetation index, and leaf area index. Using this combination, the XGBoost model achieved an [Formula: see text] = 0.88 and an RMSE = 12.33 W [Formula: see text], outperforming the ConEF method ([Formula: see text] = 0.71 and RMSE = 18.86 W [Formula: see text]) and its expansions. These findings support the application of ML models in ET upscaling, enabling ET estimation across large spatiotemporal scales.

Abstract Purpose This study aims to investigate whether adding fosaprepitant to palonosetron and dexamethasone is effective in preventing postoperative nausea and vomiting (PONV) in high-risk patients undergoing gynecologic surgery. Methods Eligible patients undergoing gynecological surgery were randomized into two groups (1:1). One group received fosaprepitant (150 mg) and the other (control) received a placebo infusion. Both groups received a single dose of palonosetron (0.25 mg) and dexamethasone (5 mg) together with therapeutic medication. The primary endpoint was the absence of vomiting and no use of rescue antiemetics during the first 24 h after surgery; complete response rate (CRR). Results CRR was significantly higher in the fosaprepitant group compared to the control group 0–24 h after surgery (P = 0.037; relative risk [RR], 1.116; 95% confidence interval [CI], 1.007 to 1.235). Moreover, CRR was also significantly higher during the 24–48 h (P = 0.004; RR, 1.148; 95% CI, 1.045 to 1.261) and 48–72 h (P = 0.039; RR, 1.083; 95% CI, 1.005 to 1.168) observation periods respectively. The complete control rate was higher in the fosaprepitant group than in the control group during the 0–24 h observation period (P = 0.012; RR, 1.367; 95% CI, 1.067 to 1.751). Nausea and rescue antiemetic use were comparable between the two groups. The severity of vomiting was significantly higher in the fosaprepitant group than in the control group on the second day (P = 0.016). Dynamic pain visual analog scale score was lower in the fosaprepitant group and quality of recovery-15 scores were significantly higher in the same group during 0–24 h observation period (P = 0.018 and 0.005, respectively). Conclusions The triple combination of fosaprepitant, palonosetron, and dexamethasone was superior in the prevention of PONV after gynecologic surgery in high-risk patients. We suggest that for high-risk patients, a triple combination therapy may be a better choice. Trial registration Registered at the Chinese Clinical Trial Registry ( https://www.chictr.org.cn/showproj.html?proj=171741 ) with No. ChiCTR2200060890 on June 13, 2022. Principal investigator: Jingdun Xie.

Abstract Meningeal metastasis (LM) is commonly seen in the advanced stages of cancer patients, often leading to a rapid decline in survival time and quality of life. Currently, there is still a lack of standardized treatments. Oncolytic viruses (OVs) are a class of emerging cancer therapeutics with the advantages of selectively replicating in cancer cells, delivering various eukaryotic transgenes, inducing immunogenic cell death, and promoting anti-tumor immunity. Some studies applying OVs intrathoracically or intraperitoneally for the treatment of malignant pleural and peritoneal effusions have shown promising therapeutic effects. If OVs could be applied to treat LM, it would bring significant survival benefits to patients with LM. In this review, we analyzed past research on the use of viruses to treat meningeal metastasis, summarized the efficacy and safety demonstrated by the research results, and analyzed the feasibility of oncolytic virus therapy for meningeal metastasis. We also summarized the existing data to provide guidance for the development of OVs that can be injected into the cerebrospinal fluid (CSF).

Abstract Heat extremes pose pronounced threats to social-ecological systems and are projected to become more intense, frequent, and longer. However, the mechanisms driving heatwaves vary across heatwave types and are not yet fully understood. Here we decompose perturbations in the surface energy budget to categorize global heatwave-days into four distinct types: sunny–humid (38%), sunny-dry (26%), advective (18%), and adiabatic (18%). Notably, sunny-dry heatwave-days decrease net ecosystem carbon uptake by 0.09 gC m−2 day−1 over harvested areas, while advective heatwave-days increase the thermal stress index by 6.20 K in populated regions. In addition, from 2000 to 2020, sunny-dry heatwaves have shown the most widespread increase compared to 1979 to 1999, with 67% of terrestrial areas experiencing a doubling in their occurrence. Our findings highlight the importance of classifying heatwave-days based on their underlying mechanisms, as this can enhance our understanding of heatwaves and improve strategies for heat adaptation.

Abstract In the current economic downturn, consumers are showing increased price sensitivity. With mobile technology enabling anytime connection, understanding daily price sensitivity fluctuations is crucial. This study analyzes transaction data from two companies, covering both offline and online scenarios. Additionally, an online experiment was conducted to further reveal the causal relationship between time-of-day and consumers’ price sensitivity. The studies indicate that price sensitivity is highest in the morning, decreasing by approximately 0.5% per hour. These findings are interpreted using the circadian rhythms theory. This research deepens our understanding of how price sensitivity changes over time, offering invaluable insights for businesses to tailor their pricing and promotional strategies throughout the day.

BackgroundOral exposure to metals/metalloid elements in drinking water may be harmful to human health.ObjectiveTo assess potential health risks of oral exposure to 9 metals/metalloids in drinking water in Zibo City of Shandong Province from 2019 to 2023, and provide reference for the development of local drinking water management policies.MethodFrom 2019 to 2023, a total of 1178 drinking water samples were collected from 261 rural water monitoring sites and 14 urban water monitoring sites in 8 districts and counties of Zibo City. The US Environmental Protection Agency's (EPA) four-step health assessment model was used to evaluate the health risks of oral exposure to 9 metals/metalloids in drinking water for adults.ResultsA total of 1178 water samples were collected, including 561 urban water samples and 617 rural water samples; 769 samples of tap water and 409 samples of finished water; 634 samples collected in wet season and 544 in dry season. The median carcinogenic risk (CR) of arsenic exposure in drinking water for adults was 3.53×10−5, and the median hazard quotient (HQ) was 7.85×10−2. The HQs of arsenic and zinc showed an upward trend in recent years, while the HQ of aluminum showed a downward trend. The stratified analysis results showed that there was no statistically significant difference in the CR of arsenic between males and females or between urban water and rural water. The CR of arsenic in dry season was higher than that in wet season, and the CR of arsenic in tap water was higher than that in finished water (P

Abstract As the COVID-19 pandemic has accelerated the shift towards mobile Internet while decreasing traditional, non-mobile Internet usage, understanding the implications of this trend on individuals’ subjective well-being has become particularly crucial. While the distinction in connectivity is evident, the specific ways in which each modality influences subjective well-being are not well documented. This study, grounded in the uses and gratifications theory, asserts that while both Internet types fulfil some similar gratifications, their unique gratifications lead to varying impacts on subjective well-being in normal and socially disruptive times. Utilising a representative longitudinal dataset from China comprising 46,803 observations from 15,601 individuals, our findings indicate that traditional Internet generally exerts a more positive influence on subjective well-being than mobile Internet. However, the role of mobile Internet has become significantly more pronounced during the COVID-19 pandemic. We further reveal the substitution effect between mobile and non-mobile Internet, which diminished during the COVID-19 pandemic. This study offers novel insights into the comparative effects of mobile and traditional Internet on subjective well-being, especially during social disturbances. This research contributes to a deeper understanding of technology’s role in enhancing subjective well-being, as well as in mitigating the impacts of crises.

Abstract Background Although malnutrition is common in cancer patients, its molecular mechanisms has not been fully clarified. This study aims to identify significantly differential metabolites, match the corresponding metabolic pathways, and develop a predictive model of malnutrition in patients with gastric cancer. Methods In this cross-sectional study, we applied non-targeted metabolomics using liquid chromatography-mass spectrometry to explore the serum fingerprinting of malnutrition in patients with gastric cancer. Malnutrition-specific differential metabolites were identified by orthogonal partial least-squares discriminant analysis and t-test and matched with the Human Metabolome Database and the LIPID Metabolites and Pathways Strategy. We matched the corresponding metabolic pathways of malnutrition using pathway analysis at the MetaboAnalyst 5.0. We used random forest analyses to establish the predictive model. Results We recruited 220 malnourished and 198 non-malnourished patients with gastric cancer. The intensities of 25 annotated significantly differential metabolites were lower in patients with malnutrition than those without, while two others were higher in patients with malnutrition than those without, including newly identified significantly differential metabolites such as indoleacrylic acid and lysophosphatidylcholine(18:3/0:0). We matched eight metabolic pathways associated with malnutrition, including aminoacyl-tRNA biosynthesis, tryptophan metabolism, and glycerophospholipid metabolism. We established a predictive model with an area under the curve of 0.702 (95% CI: 0.651–0.768) based on four annotated significantly differential metabolites, namely indoleacrylic acid, lysophosphatidylcholine(18:3/0:0), L-tryptophan, and lysophosphatidylcholine(20:3/0:0). Conclusions We identified 27 specific differential metabolites of malnutrition in malnourished compared to non-malnourished patients with gastric cancer. We also matched eight corresponding metabolic pathways and developed a predictive model. These findings provide supportive data to better understand molecular mechanisms of malnutrition in patients with gastric cancer and new strategies for the prediction, diagnosis, prevention, and treatment for those malnourished.

Abstract Objective Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CTEs) in elderly patients with atrial fibrillation(AF). These events encompass newly diagnosed cerebral ischemia events, cardiovascular events, pulmonary embolism, and lower extremity arterial embolism. Methods This retrospective study included 6,079 elderly hospitalized patients (≥ 75 years old) with AF admitted to the People’s Liberation Army General Hospital in China from January 2010 to June 2022. Random forest imputation was used for handling missing data. In the descriptive statistics section, patients were divided into two groups based on the occurrence of CTEs, and differences between the two groups were analyzed using chi-square tests for categorical variables and rank-sum tests for continuous variables. In the machine learning section, the patients were randomly divided into a training dataset (n = 4,225) and a validation dataset (n = 1,824) in a 7:3 ratio. Four machine learning models (logistic regression, decision tree, random forest, XGBoost) were trained on the training dataset and validated on the validation dataset. Results The incidence of composite thromboembolic events was 19.53%. The Least Absolute Shrinkage and Selection Operator (LASSO) method, using 5-fold cross-validation, was applied to the training dataset and identified a total of 18 features that exhibited a significant association with the occurrence of CTEs. The random forest model outperformed other models in terms of area under the curve (ACC: 0.9144, SEN: 0.7725, SPE: 0.9489, AUC: 0.927, 95% CI: 0.9105–0.9443). The random forest model also showed good clinical validity based on the clinical decision curve. The Shapley Additive exPlanations (SHAP) showed that the top five features associated with the model were history of ischemic stroke, high triglyceride (TG), high total cholesterol (TC), high plasma D-dimer, age. Conclusions This study proposes an accurate model to stratify patients with a high risk of CTEs. The random forest model has good performance. History of ischemic stroke, age, high TG, high TC and high plasma D-Dimer may be correlated with CTEs.

Abstract Lane line images have the essential attribute of large-scale variation and complex scene information, and the similarity between adjacent lane lines is high, which can easily cause classification errors. And remote lane lines are difficult to recognize due to visual angle changes in width. To address this issue, this paper proposes an effective lane detection framework, which is a hybrid feature fusion network that enhances multiple spatial features and distinguishes key features throughout the entire lane line segment. It enhances and fuses lane line features at multiscale to enhance the feature representation of lane line images, especially at the far end. Firstly, in order to enhance the correlation of multiscale lane features, a multi-head self attention is used to construct a multi-space attention enhancement module for feature enhancement in multispace. Secondly, a spatial separable convolutional branch is designed for the jumping layer structure connecting multiscale lane line features. While retaining feature information of different scales, important lane areas in multiscale feature information are emphasized through the allocation of spatial attention weights. Finally, considering that lane lines are elongated areas in the image, and the background information in the image is much more abundant than lane line information, the flexibility of traditional pooling operations in capturing widely existing anisotropic contexts in actual environments is limited. Therefore, before embedding feature output branches, strip pooling is introduced to refine the representation of lane line information and optimize model performance. The experimental results show that the accuracy on the TuSimple dataset reaches 96.84%, and the F1 score on the CULane dataset reaches 75.9%.

Abstract Background Lifestyle has become a crucial modulator in the management of diabetes and is intimately linked with the development and exacerbation of comorbid depression. The study aimed to analyze lifestyle patterns and their impact on depression in individuals with diabetes and to explore the role of the Dietary Inflammatory Index (DII) in the relationship between lifestyle patterns and depression. Methods Data was attained from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2020. A latent class analysis (LCA) was performed on 3,009 diabetic adults based on lifestyle behaviors. A generalised linear model (GLM) was employed to analyse the effects of different lifestyle patterns on depression. The mediation effect model was utilised to examine the relationship between lifestyle patterns, DII and Patient Health Questionnaire-9 (PHQ-9) scores. Results The cohort was divided through LCA into unhealthy lifestyle (44.53%), unhealthy but non-alcohol use (48.06%) and healthy but smoking (7.41%) groups of lifestyle behaviors, the unhealthy but non-alcohol use group was identified as a risk factor for depression (OR = 1.379, 95%CI = 1.095 ~ 1.735, P = 0.006). The DII partially mediated the relationship between the unhealthy but non-alcohol use group and PHQ-9, and fully mediated the relationship between the healthy but smoking group and PHQ-9, with effect coefficients of − 0.018 (95%CI: −0.044 ~ − 0.001) and − 0.035 (95%CI: −0.083 ~ − 0.001). Conclusions Lifestyle patterns significantly influence the occurrence of depression among diabetes patients. The dietary inflammation plays a varying mediating role between different lifestyle patterns and depression. Restricting pro-inflammatory diets or encouraging anti-inflammatory diets, combined with the promotion of healthy lifestyle practices, may be an effective method for preventing and alleviating symptoms of depression among patients with diabetes.

Abstract Background TFE3-rearranged renal cell carcinoma (TFE3-rRCC) is a rare but highly heterogeneous renal cell carcinoma (RCC) entity, of which the clinical treatment landscape is largely undefined. This study aims to evaluate and compare the efficacy of different systemic treatments and further explore the molecular correlates. Methods Thirty-eight patients with metastatic TFE3-rRCC were enrolled. Main outcomes included progression-free survival (PFS), overall survival, objective response rate (ORR) and disease control rate. RNA sequencing was performed on 32 tumors. Results Patients receiving first-line immune checkpoint inhibitor (ICI) based combination therapy achieved longer PFS than those treated without ICI (median PFS: 11.5 vs. 5.1 months, P = 0.098). After stratification of fusion partners, the superior efficacy of first-line ICI based combination therapy was predominantly observed in ASPSCR1-TFE3 rRCC (median PFS: not reached vs. 6.5 months, P = 0.01; ORR: 67.5% vs. 10.0%, P = 0.019), but almost not in non-ASPSCR1-TFE3 rRCC. Transcriptomic data revealed enrichment of ECM and collagen-related signaling in ASPSCR1-TFE3 rRCC, which might interfere with the potential efficacy of anti-angiogenic monotherapy. Whereas angiogenesis and immune activities were exclusively enriched in ASPSCR1-TFE3 rRCC and promised the better clinical outcomes with ICI plus tyrosine kinase inhibitor combination therapy. Conclusions The current study represents the largest cohort comparing treatment outcomes and investigating molecular correlates of metastatic TFE3-rRCC based on fusion partner stratification. ICI based combination therapy could serve as an effective first-line treatment option for metastatic ASPSCR1-TFE3 rRCC patients. Regarding with other fusion subtypes, further investigations should be performed to explore the molecular mechanisms to propose pointed therapeutic strategy accordingly.

Abstract Maintenance of genome integrity requires tight control of DNA damage response (DDR) signalling and repair, with phosphorylation and ubiquitination representing key elements. How these events are coordinated to achieve productive DNA repair remains elusive. Here we identify the ubiquitin-conjugating enzyme UBE2D3 as a regulator of ATM kinase-induced DDR that promotes non-homologous end-joining (NHEJ) at telomeres. UBE2D3 contributes to DDR-induced chromatin ubiquitination and recruitment of the NHEJ-promoting factor 53BP1, both mediated by RNF168 upon ATM activation. Additionally, UBE2D3 promotes NHEJ by limiting RNF168 accumulation and facilitating ATM-mediated phosphorylation of KAP1-S824. Mechanistically, defective KAP1-S824 phosphorylation and telomeric NHEJ upon UBE2D3-deficiency are linked to RNF168 hyperaccumulation and aberrant PP2A phosphatase activity. Together, our results identify UBE2D3 as a multi-level regulator of NHEJ that orchestrates ATM and RNF168 activities. Moreover, they reveal a negative regulatory circuit in the DDR that is constrained by UBE2D3 and consists of RNF168- and phosphatase-mediated restriction of KAP1 phosphorylation.

The Yellow River Basin (YRB) has experienced severe floods and continuous riverbed elevation throughout history. Global climate change has been suggested to be driving a worldwide increase in flooding risk. However, owing to insufficient evidence, the quantitative correlation between flooding and climate change remains ill-defined. We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements. Variations in yearly maximum flood discharge show distinct periods: a dramatic decreasing period from 1843 to 1950, and an oscillating gentle decreasing from 1950 to 2021, with the latter period also showing increasing more extreme floods. A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods: an oscillating gentle decreasing period from 1950 to 2000, and a clear recent increasing period from 2000 to 2021. We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an ∼44.4 billion US dollars loss of floods in the YRB in 2100.

Photosynthesis (a key ecological process) is measured based on gross primary productivity (GPP), emphasizing the criticality of accurate GPP estimation to climate change research. The extant remote sensing-based approaches for GPP estimation were typically based on optical remote sensing data, neglecting the potential supplementary information from microwave remote sensing data. Thus, based on the random forest algorithm, we developed a GPP model through the integration of optical and microwave remote sensing with meteorological data (OMM-GPP). The software and tools used for data processing, modeling, and analysis are the standard and third-party libraries based on the Python Language. Our OMM-GPP model was trained and validated using GPP data (referred to as “observed GPP”) retrieved from carbon dioxide fluxes measured at 137 flux towers. The results indicated that GPP estimation by integrating optical and microwave data with meteorological data was more accurate than GPP estimation by integrating single-source remote sensing data (optical or microwave data) with meteorological data across eight vegetation types. The model performed well on daily and monthly scales, with determination coefficients (R2) (root-mean-square errors, RMSE) of 0.85 (1.52 gC m−2 d−1) and 0.83 (1.49 gC m−2 d−1), respectively, which increased (decreased) by 0.17–0.03 (0.58–0.12 gC m−2 d−1) and 0.11–0.02 (0.39–0.10 gC m−2 d−1) compared with the R2 (RMSE) values obtained by integrating single-source remote sensing data with meteorological variables. Further, the OMM-GPP model effectively captured the seasonal variations in daily and monthly GPP across most vegetation types. The eight-day-scale comparison of the model with the VODCA2GPP dataset revealed its enhanced performances, increasing R2 by 0.33 and decreasing RMSE by 0.97 gC m−2 d−1. Overall, the integration of microwave and optical remote sensing data with meteorological data can enhance GPP estimation accuracy, as demonstrated by the established OMM-GPP, across different vegetation types.

Abstract is missing (Quiz)

BackgroundCurrently, there remains substantial controversy in research regarding whether the concomitant use of colchicine and statins increases the occurrence of rhabdomyolysis, warranting further substantiation.ObjectiveThis study aimed to identify the likelihood drug-drug interactions (DDIs) for the co-administration of colchicine and statins resulting in rhabdomyolysis.MethodsA disproportionality analysis was conducted by using data sourced from the US Food and Drug Administration Adverse Event Reporting System (FAERS) to detect rhabdomyolysis signals associated with the combined use of colchicine and statins. The association between (colchicine/statins/colchicine and statins) and rhabdomyolysis were evaluated using information component (IC). DDI signals were calculated based on the Ω shrinkage measure and Bayesian confidence propagation neural network (BCPNN) method. Furthermore, stratification was performed based on colchicine and individual statins agents.ResultsIn total, 11,119 reports of rhabdomyolysis were identified in the FAERS database, 255 (2.29%) involved both colchicine and statins. Our analysis showed potential DDI signals of rhabdomyolysis (Ω025 = 1.17) among individuals concurrent use of colchicine and statins. Moreover, further drug-specific analysis suggests DDI signals in the colchicine-atorvastatin pair (Ω025 = 1.12), and colchicine-rosuvastatin pair (Ω025 = 1.05), along with a higher proportion of rhabdomyolysis (IC025 = 5.20) and (IC025 = 4.26), respectively.ConclusionThe findings suggest that concomitant use of colchicine and statins may increase the risk of rhabdomyolysis, particularly when combined with atorvastatin or rosuvastatin. Therefore, healthcare professionals should pay special attention to life-threatening AE such as rhabdomyolysis, when co-prescribing colchicine statins.

Objective To evaluate the project-based management in reducing acupressure medical adhesive-associated skin injury in patients with chronic gastritis, and provide a reliable basis for clinical practice. Methods Take the tendency score matching method, 1: 1 matching to find control. Finally, 235 cases of chronic gastritis were selected from the Department of Gastroenterology from October 2021 to March 2022 as the intervention group (2215 times of application) for project management; From October 2020 to March 2021, 235 patients with chronic gastritis were used as the control group (2215 times of application) and were managed by traditional mode, comparing the quality management results of the specific work, associated skin damage, and pain scores at removal of the acupressure applied in both groups. Results By adopting the project-based management model, the overall target achievement rate reached 93. 27% and the overall progress rate reached 63. 95%, which was better than the target and achieved the expected results, in which the quality monitoring results of the intervention group were significantly higher than those of the control group (P

Objective Through the problem-oriented clinical syndrome differentiation thinking, the Xianghu dispelling-cold cake moxibustion was adopted in the treatment of spleen-stomach deficiency cold type epigastric pain, and related nursing measures were summarized. Methods The clinical data of 106 hospitalized patients with epigastric pain from September 2021 to August 2022, were selected and randomized into 2 groups. 53 cases in the control group received routine care, and 53 cases in the intervention group received Xianghu dispelling-cold cake moxibustion treatment on the basis of the control group. The symptom scores, time to pain relief, patient satisfaction and treatment compliance were observed and compared between two groups. Results the Traditional Chinese Medicine syndrome scores in both groups decreased after intervention, and Traditional Chinese Medicine syndrome scores in the intervention group decreased more significantly than those in the control group (P

Ultra-fine grained magnesium alloys are usually prepared by severe deformation and medium-low temperature deformation. In this work, it has been found that the binary Mg-1.2Ce alloy with the uniform distributed Mg12Ce precipitates smaller than 3 μm is a good candidate to obtain ultra-fine grains by conventional one-step extrusion at high temperatures. All the three Mg-1.2Ce samples extruded at 300 °C, 350 °C and 400 °C show a bimodal microstructure with high-density dislocations, whose average grain sizes are 1.19 ± 0.92 μm, 1.32 ± 1.30 μm, and 1.44 ± 1.33 μm, respectively. A linear relation of ln(d) = -0.05ln(Z)+1.27 was determined relating the average grain size (d) to the Zener-Hollomon parameter (Z). The alloy extruded at 300 °C exhibits an exceptionally high ultimate tensile strength (UTS) of 412.3 ± 5.3 MPa and yield strength (TYS) of 387.6 ± 3.2 MPa, but a low elongation after fracture (El) of 4.9 ± 0.8 %. With the extrusion temperature increasing, the tensile strength gradually decreases. For the 1.2E-400 sample, the TYS and the UTS drop to 347.2 ± 2.1 MPa and 349.4 ± 2.8 MPa, while the El increases to a more acceptable value of 12.6 ± 1.4 %. The microstructure analysis reveals that Ce atoms segregate along grain boundaries and dislocations in the Mg-1.2Ce alloy, which can limit the gliding of GBs or the slipping and climbing of dislocations. Additionally, dislocations can be pinned by Mg12Ce precipitates, thereby also restricting dislocation and grain boundary mobility. Consequently, the dynamic recrystallization (DRX) process is delayed, leading to the formation of a bimodal microstructure.

Abstract Background Hypertension prevalence among the overall US adult population has been relatively stable during the last two decades. However, whether this stabilization has occurred across rural-urban communities and across different geographic regions is unknown, particularly among older adults with diabetes who are likely to have concomitant cardiovascular risk factors. Methods This serial cross-sectional analysis used the 5% national sample of Medicare administrative claims data (n = 3,516,541) to examine temporal trends (2005–2017) in diagnosed hypertension among older adults with diabetes, across urban-rural communities and US census regions (Northeast, Midwest, South, and West). Joinpoint regression was used to obtain annual percent change (APC) in hypertension prevalence across rural-urban communities and geographic regions, and multivariable adjusted regression was used to assess associations between rural-urban communities and hypertension prevalence. Results The APC in the prevalence of hypertension was higher during 2005–2010, and there was a slowdown in the increase during 2011–2017 across all regions, with significant variations across rural-urban communities within each of the regions. In the regression analysis, in the adjusted model, older adults living in non-core (most rural) areas in the Midwest (PR = 0.988, 95% CI: 0.981–0.995) and West (PR = 0.935, 95% CI: 0.923–0.946) had lower hypertension prevalence than their regional counterparts living in large central metro areas. Conclusions Although the magnitudes of these associations are small, differences in hypertension prevalence across rural-urban areas and geographic regions may have implications for targeted interventions to improve chronic disease prevention and management.

[Objective] The objectives of this study are to dissect the genetic basis of soybean flowering and maturity time and to identify genomic regions that can be used for molecular marker-assisted selection (MAS) and novel gene cloning. [Methods] 224 soybeans with dominant E1 alleles were planted in four en vironments to investigate phenotypic data. Six multi-locus association analysis models from the R-mrMLM software package were employed for a genome-wide association analysis (GWAS) on soybean flowering and maturity time. [Results] 91 flowering and 83 maturation QTNs (quantitative trait nucleotides) were detected by combining six multi-loci GWAS methods. Among them, 6 flowering and 10 maturation QTNs were detected in various environments. These stable QTNs were distributed in 15 haplotype blocks (ge nomic regions) with an interval size of 90-490 kb. 6 out of 15 genomic regions were newly detected. [Conclusion] The QTN composition of soybean flowering and maturity time at the dominant E1 gene back ground is complex. 15 genomic regions, including 39.52-40.01 Mb on chromosome 5, are loci control ling soybean flowering or maturity time in this population.

Abstract Background Osimertinib has become standard care for epidermal growth factor receptor (EGFR)-positive non-small cell lung cancer (NSCLC) patients whereas drug resistance remains inevitable. Now we recognize that the interactions between the tumor and the tumor microenvironment (TME) also account for drug resistance. Therefore, we provide a new sight into post-osimertinib management, focusing on the alteration of TME. Methods We conducted a retrospective study on the prognosis of different treatments after osimertinib resistance. Next, we carried out in vivo experiment to validate our findings using a humanized mouse model. Furthermore, we performed single-cell transcriptome sequencing (scRNA-seq) of tumor tissue from the above treatment groups to explore the mechanisms of TME changes. Results Totally 111 advanced NSCLC patients have been enrolled in the retrospective study. The median PFS was 9.84 months (95% CI 7.0–12.6 months) in the osimertinib plus anti-angiogenesis group, significantly longer than chemotherapy (P = 0.012) and osimertinib (P = 0.003). The median OS was 16.79 months (95% CI 14.97–18.61 months) in the osimertinib plus anti-angiogenesis group, significantly better than chemotherapy (P = 0.026), the chemotherapy plus osimertinib (P = 0.021), and the chemotherapy plus immunotherapy (P = 0.006). The efficacy of osimertinib plus anlotinib in the osimertinib-resistant engraft tumors (R-O+A) group was significantly more potent than the osimertinib (R-O) group (P

Abstract Symbiosis with soil-dwelling bacteria that fix atmospheric nitrogen allows legume plants to grow in nitrogen-depleted soil. Symbiosis impacts the assembly of root microbiota, but it is unknown how the interaction between the legume host and rhizobia impacts the remaining microbiota and whether it depends on nitrogen nutrition. Here, we use plant and bacterial mutants to address the role of Nod factor signaling on Lotus japonicus root microbiota assembly. We find that Nod factors are produced by symbionts to activate Nod factor signaling in the host and that this modulates the root exudate profile and the assembly of a symbiotic root microbiota. Lotus plants with different symbiotic abilities, grown in unfertilized or nitrate-supplemented soils, display three nitrogen-dependent nutritional states: starved, symbiotic, or inorganic. We find that root and rhizosphere microbiomes associated with these states differ in composition and connectivity, demonstrating that symbiosis and inorganic nitrogen impact the legume root microbiota differently. Finally, we demonstrate that selected bacterial genera characterizing state-dependent microbiomes have a high level of accurate prediction.

Abstract This study involved the production of 20 biochar samples derived from secondary medicinal residues of Snow Lotus Oral Liquid, processed within the temperature range of 200–600 °C. Additionally, four medicinal residues, including dissolved organic matter (DOM), from 24 samples obtained using the shaking method, served as the primary source material. The investigation focused on two key factors: the modifier and preparation temperature. These factors were examined to elucidate the spectral characteristics and chemical properties of the pharmaceutical residues, biochar, and DOM. To analyze the alterations in the spectral attributes of biochar and medicinal residues, we employed near-infrared spectroscopy (NIR) in conjunction with Fourier-infrared one-dimensional and two-dimensional correlation spectroscopy. These findings revealed that modifiers enhanced the aromaticity of biochar, and the influence of preparation temperature on biochar was diminished. This observation indicates the stability of the aromatic functional group structure. Comparative analysis indicated that Na2CO3 had a more pronounced structural effect on biochar, which is consistent with its adsorption properties. Furthermore, we utilized the fluorescence indices from UV–visible spectroscopy and excitation-emission-matrix spectra with the PARAFAC model to elucidate the characteristics of the fluorescence components in the DOM released from the samples. The results demonstrated that the DOM released from biochar primarily originated externally. Aromaticity reduction and increased decay will enhance the ability of the biochar to bind pollutants. Those results confirmed the link between the substantial increase in the adsorption performance of the high-temperature modified charcoal in the previous study and the structural changes in the biochar. We investigated the structural changes of biochar and derivative DOM in the presence of two perturbing factors, modifier and preparation temperature. Suitable modifiers were selected. Preparation for the study of adsorption properties of snow lotus medicinal residues.

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China. Presently, most remote sensing process models use the “biomass×harvest index (HI)” method to simulate regional-scale winter wheat yield. However, spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale. Time-series dry matter partition coefficients (Fr) can dynamically reflect the dry matter partition of winter wheat. In this study, Fr equations were fitted for each organ of winter wheat using site-scale data. These equations were then coupled into a process-based and remote sensing-driven crop yield model for wheat (PRYM-Wheat) to improve the regional simulation of winter wheat yield over the North China Plain (NCP). The improved PRYM-Wheat model integrated with the fitted Fr equations (PRYM-Wheat-Fr) was validated using data obtained from provincial yearbooks. A 3-year (2000–2002) averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination (R²=0.55) and lower root mean square error (RMSE=0.94 t ha–1) than PRYM-Wheat with a stable HI (abbreviated as PRYM-Wheat-HI), which had R² and RMSE values of 0.30 and 1.62 t ha–1, respectively. The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years (2013–2015). In conclusion, the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model, making it a useful tool for the simulation of regional winter wheat yield.