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Numerous electrochemistry reactions require the precise calculation of the ion solvation energy. Despite the significant progress in the first-principles calculations for crystals and defect formation energies for solids, the liquid system free energy calculations still face many challenges. Ion solvation free energies can be calculated via different semiempirical ways, e.g., using implicit solvent models or cluster of explicit molecule models; however, systematically improving these models is difficult due to their lack of a solid theoretical base. A theoretically sound approach for calculating the free energy is to use thermodynamic integration. Nevertheless, owing to the difficulties of self-consistent convergence in first-principles calculations for unphysical atomic configurations, the computational alchemy approach has not been widely used for first-principles calculations. This study proposes a general approach to use first-principles computational alchemy for calculating the ion solvation energy. This approach is also applicable for other small molecules. The calculated ion solvation free energies for Li+, Na+, K+, Be2+, Mg2+, and Ca2+ are close to the experimental results, and the standard deviation due to molecular dynamics fluctuations is within 0.06 eV. [ABSTRACT FROM AUTHOR]

Hypoglycemia is a common metabolic disorder that occurs in the neonatal period. Early identification of neonates at risk of developing hypoglycemia can optimize therapeutic strategies in neonatal care. This study aims to develop a machine learning model and implement a predictive application to assist clinicians in accurately predicting the risk of neonatal hypoglycemia within four hours after birth. Our retrospective study analyzed data from neonates born ≥35 weeks gestational age and admitted to the well-baby nursery between 1 January 2011 and 31 August 2021. We collected electronic medical records of 2687 neonates from a tertiary medical center in Southern Taiwan. Using 12 clinically relevant features, we evaluated nine machine learning approaches to build the predictive models. We selected the models with the highest area under the receiver operating characteristic curve (AUC) for integration into our hospital information system (HIS). The top three AUC values for the early neonatal hypoglycemia prediction models were 0.739 for Stacking, 0.732 for Random Forest and 0.732 for Voting. Random Forest is considered the best model because it has a relatively high AUC and shows no significant overfitting (accuracy of 0.658, sensitivity of 0.682, specificity of 0.649, F1 score of 0.517 and precision of 0.417). The best model was incorporated in the web-based application integrated into the hospital information system. Shapley Additive Explanation (SHAP) values indicated mode of delivery, gestational age, multiparity, respiratory distress, and birth weight < 2500 gm as the top five predictors of neonatal hypoglycemia. The implementation of our machine learning model provides an effective tool that assists clinicians in accurately identifying at-risk neonates for early neonatal hypoglycemia, thereby allowing timely interventions and treatments. [ABSTRACT FROM AUTHOR]

Background: Plantar sensation and ankle proprioception occur in a stage-like variance across the life span. However, changes in adolescents, young adults, middle-aged adults, and older adults remain unclear. The aim of this study was to investigate the differences of plantar sensation and ankle proprioception in adolescents to older adults. Methods: A total of 212 participants were recruited in the study and were divided into four groups, including adolescents (n = 46), young adults (n = 55), middle-aged adults (n = 47), and older adults (n = 54). Plantar tactile sensitivity/tactile acuity/vibration threshold and ankle movement threshold/joint position sense/force sense were assessed in all groups. The Kruskal–Wallis H test was used to analyze the differences in Semmes–Weinstein monofilaments between different age groups in different plantar positions. One-way analysis of variance was used to determine differences in foot vibration threshold, two-point discrimination, and ankle proprioception between different age groups. Results: Significant differences were found in the Semmes–Weinstein monofilament test (p <.001), the two-point discrimination test (p <.05), and the vibration threshold test (p <.05) in the six tested plantar positions among adolescents, young adults, middle-aged adults, and older adults. For ankle proprioception, significant differences were found in movement thresholds in ankle plantar flexion (p =.01), ankle dorsiflexion (p <.001), ankle inversion (p <.001), and ankle eversion (p <.001), as well as relative absolute errors in the ankle force senses of ankle plantar flexion (p =.02) and ankle dorsiflexion (p =.02) across the four age groups. Conclusion: Plantar sensation and ankle proprioception were sensitive in adolescents and young adults than in middle-aged adults and older adults. [ABSTRACT FROM AUTHOR]

Background: The association between ambient temperature and mortality has yielded inconclusive results with previous studies relying on in-patient data to assess the health effects of temperature. Therefore, we aimed to estimate the effect of ambient temperature on non-accidental mortality among elderly hypertensive patients through a prospective cohort study conducted in northeastern China. Methods: A total of 9634 elderly hypertensive patients from the Kailuan research who participated in the baseline survey and follow-up from January 1, 2006 to December 31, 2017, were included in the study. We employed a Poisson generalized linear regression model to estimate the effects of monthly ambient temperature and temperature variations on non-accidental mortality. Results: After adjusting for meteorological parameters, the monthly mean temperature (RR = 0.989, 95% CI: 0.984–0.993, p < 0.001), minimum temperature (RR = 0.987, 95% CI: 0.983–0.992, p < 0.001) and maximum temperature (RR = 0.989, 95% CI: 0.985–0.994, p < 0.001) exhibited a negative association with an increased risk of non-accidental mortality. The presence of higher monthly temperature variation was significantly associated with an elevated risk of mortality (RR = 1.097, 95% CI:1.051–1.146, p < 0.001). Further stratified analysis revealed that these associations were more pronounced during colder months as well as among male and older individuals. Conclusions: Decreased temperature and greater variations in ambient temperature were observed to be linked with non-accidental mortality among elderly hypertensive patients, particularly notable within aging populations and males. These understanding regarding the effects of ambient temperature on mortality holds clinical significance for appropriate treatment strategies targeting these individuals while also serving as an indicator for heightened risk of death. [ABSTRACT FROM AUTHOR]

Flexible perovskite solar cells (f-PSCs) have achieved significant success. However, high-quality tin dioxide (SnO2) electron transport layers (ETLs) fabricated via chemical bath deposition (CBD) have not been achieved on flexible PEN/ITO substrates. This limitation is primarily due to the corrosion of the poor-quality ITO layer by the strongly acidic CBD solution. Here, we analyzed the reasons for the poor corrosion resistance of ITO films on PEN substrate from multiple perspectives, such as element composition, microstructure, and crystallinity. Then, we proposed a modified CBD method for SnO2 films suitable for flexible PEN/ITO substrates. We employed SnCl2·2H2O as the tin source and regulated the pH of the CBD solution by NH3·H2O, which effectively avoided the corrosion of the ITO layer by the CBD solution and achieved high-quality SnO2 films on the ITO layers. Compared to the commercial SnO2 dispersion, the SnO2 films prepared by this method have smaller grains and higher transmittance. As a result, we achieved an unprecedented power conversion efficiency (PCE) of 20.71% for f-PSCs fabricated on PEN/ITO substrates with SnO2 ETLs by CBD method. This breakthrough facilitates the development of high-performance f-PSCs by a low-cost and large-scale chemical bath deposition of high-quality ETLs on flexible substrates. [ABSTRACT FROM AUTHOR]

Ferroelectrics are essential in memory devices for multi-bit storage and high-density integration. Ferroelectricity mainly exists in compounds but rare in single-element materials due to their lack of spontaneous polarization in the latter. However, we report a room-temperature ferroelectricity in quasi-one-dimensional Te nanowires. Piezoelectric characteristics, ferroelectric loops and domain reversals are clearly observed. We attribute the ferroelectricity to the ion displacement created by the interlayer interaction between lone-pair electrons. Ferroelectric polarization can induce a strong field effect on the transport along the Te chain, giving rise to a self-gated ferroelectric field-effect transistor. By utilizing ferroelectric Te nanowire as channel, the device exhibits high mobility (~220 cm2·V−1·s−1), continuous-variable resistive states can be observed with long-term retention (>105 s), fast speed (<20 ns) and high-density storage (>1.92 TB/cm2). Our work provides opportunities for single-element ferroelectrics and advances practical applications such as ultrahigh-density data storage and computing-in-memory devices. Authors find room-temperature ferroelectricity in single element Te nanowires, highlighting that reducing dimensions to 1D in low-dimensional piezoelectric materials with chain structures is an effective strategy to induce ferroelectricity absent in their 2D form. [ABSTRACT FROM AUTHOR]

Background: Our previous study demonstrated that long intergenic noncoding RNA 02454 (LINC02454) may act as an oncogene to promote the proliferation and inhibit the apoptosis of papillary thyroid cancer (PTC) cells. This study was designed to investigate the mechanisms whereby LINC02454 is related to PTC tumorigenesis. Methods: Thyroid cancer RNA sequence data were obtained from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify modules closely associated with PTC. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways, and the maximal clique centrality (MCC) topological method was used to identify the hub genes. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to compare expression levels of key genes between PTC samples and normal samples and explore the prognostic value of key genes. The key genes were further validated with GEO dataset. Results: The top 5000 variable genes were investigated, followed by an analysis of 8 modules, and the turquoise module was the most positively correlated with the clinical stage of PTC. KEGG pathway analysis found the top two pathways of the ECM − receptor interaction and MAPK signaling pathway. In addition, five key genes (FN1, LAMB3, ITGA3, SDC4, and IL1RAP) were identified through the MCC algorithm and KEGG analysis. The expression levels of the five key genes were significantly upregulated in thyroid cancer in both TCGA and GEO datasets, and of these five genes, FN1 and ITGA3 were associated with poor disease-free prognosis. Conclusions: Our study identified five key genes and two key pathways associated with LINC02454, which might shed light on the underlying mechanism of LINC02454 action in PTC. [ABSTRACT FROM AUTHOR]

Background: Small renal masses (SRMs) have been shown to have low malignant potential. Active surveillance (AS), typically characterized by regular follow-up and delayed nephrectomy if necessary, is recommended as an option for frail patients with SRMs. Nevertheless, the impact of tumor size on survival in T1a RCC patients undergoing delayed nephrectomy for SRMs remains unclear. Methods: Patients diagnosed with non-metastatic T1a RCC who underwent nephrectomy were identified from the Surveillance, Epidemiology, and End Results (SEER) database and divided into immediate (< 6 months) and delayed nephrectomy (≥ 6 months) groups based on the duration from diagnosis to nephrectomy. After propensity score matching (PSM), overall survival (OS) and cancer-specific survival (CSS) were estimated by K-M curves and compared with log-rank test. Results: A total of 27,502 patients were enrolled, of whom 26,915 (97.9%) received immediate nephrectomy and 587 (2.1%) received delayed nephrectomy. After PSM, 1174 patients who underwent immediate nephrectomy and 587 patients who underwent delayed nephrectomy were included. With a median delay of 7 months, delayed nephrectomy resulted in non-inferior OS for RCC tumors sized 0.1–2.0 cm (HR = 1.12, p = 0.636). However, for RCC tumors sized 2.1–3.0 cm (HR = 1.60, p = 0.008) and 3.1–4.0 cm (HR = 1.89, p < 0.001), delayed nephrectomy showed inferior OS compared to immediate nephrectomy. Delayed nephrectomy did not result in significantly worse CSS than immediate nephrectomy in all tumor size subgroups (all p > 0.05), however this may be due to sample size limiting statistical power. Conclusion: Based on the SEER database, we found that with a median delay of 7 months, 2 cm may be an appropriate cut-off point of delayed nephrectomy for patients diagnosed with non-metastatic T1a RCC. [ABSTRACT FROM AUTHOR]

In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography–tandem mass spectrometry (LC–MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation. [ABSTRACT FROM AUTHOR]

Interactions between cells are of fundamental importance in affecting cell function. In vivo, endothelial cells and islet cells are close to each other, which makes endothelial cells essential for islet cell development and maintenance of islet cell function. We used endothelial cells to construct 3D pseudo-islets, which demonstrated better glucose regulation and greater insulin secretion compared to conventional pseudo-islets in both in vivo and in vitro trials. However, the underlying mechanism of how endothelial cells promote beta cell function localized within islets is still unknown. We performed transcriptomic sequencing, differential gene analysis, and enrichment analysis on two types of pseudo-islets to show that endothelial cells can promote the function of internal beta cells in pseudo-islets through the BTC-EGFR-JAK/STAT signaling pathway. Min6 cells secreted additional BTC after co-culture of endothelial cells with MIN6 cells outside the body. After BTC knockout in vitro, we found that beta cells functioned differently: insulin secretion levels decreased significantly, while the expression of key proteins in the EGFR-mediated JAK/STAT signaling pathway simultaneously decreased, further confirming our results. Through our experiments, we elucidate the molecular mechanisms by which endothelial cells maintain islet function in vitro, which provides a theoretical basis for the construction of pseudo-islets and islet cell transplants for the treatment of diabetes mellitus. [ABSTRACT FROM AUTHOR]

Past research suggests that personal Internet usage (PIU) at work can carry both costs and benefits for employees, but offers no explanation for these mixed results. In this research, we argue that the competing findings might be due to the existence of different types of PIU. We take a daily approach and propose that hedonic PIU (HPIU, i.e. relaxing oneself) benefits employees' end‐of‐workday well‐being and work engagement while utilitarian PIU (UPIU, i.e. solving others' problems) hinders their well‐being and work engagement. We test our theorizing using three studies. In Study 1, we summarized previous PIU studies and relied on machine learning methods to classify the 618 PIU activities identified in prior studies. We found that prior research mixed HPIU and UPIU and might reach different conclusions. In Study 2, we condensed the PIU activity list in Study 1 and developed measurement scales of HPIU and UPIU. In Study 3, we analysed 1063 multi‐wave daily inputs from 125 employees and found that on a daily basis, HPIU benefits employees' well‐being by fostering a state of recovery, while UPIU impedes well‐being and work engagement by inducing a state of depletion. Moreover, supervisor support for employees' personal behaviours strengthens the beneficial effect of HPIU. [ABSTRACT FROM AUTHOR]

Objectives: Sinonasal inverted papilloma (SNIP) is a noncancerous tumor that develops in the mucous membrane of the nasal sinuses. Many malignancies are tightly linked to autophagy, an intracellular self‐degradation mechanism. HMGB1 has demonstrated its ability to modulate autophagy in many pathological conditions. This work investigates how HMGB1 and other genes involved in autophagy contribute to SNIP. Material and Methods: The study included 45 patients with SNIP and a control group consisting of 28 individuals. In each group, qPCR was employed to examine the mRNA expression levels of genes correlated with autophagy and HMGB1. HMGB1 and genes associated with autophagy were examined for protein expression levels via Western Blot and immunohistochemical staining assays. At the same time, the association between HMGB1 and genes involved in autophagy was discovered through correlation analysis. Furthermore, Krouse staging was utilized for investigating the expression levels of HMGB1 and other autophagy‐related genes at various stages in clinically staged SNIP patients. Results: LC3B, ATG5, and Beclin1 autophagy‐related genes and HMGB1 were substantially expressed in SNIP. Additionally, there was a positive correlation between HMGB1 and these genes. During various phases of SNIP, the levels of HMGB1 expression and autophagy‐related genes were notably elevated at stage T4 compared with stage T2. Conclusion: Clinical staging in SNIP is correlated with HMGB1 expression in conjunction with autophagy‐related genes LC3B, ATG5, and Beclin1, suggesting the possibility of novel prognostic indicators. Level of Evidence: NA Laryngoscope, 134:3941–3946, 2024 [ABSTRACT FROM AUTHOR]

The accurate forecasting of agricultural futures prices is critical for ensuring national food security. Therefore, this study proposes a text‐based deep learning forecasting model. This model first uses the ChineseBERT + a text convolution neural network to classify Weibo text and obtain a raw sentiment index. Then, complete ensemble empirical mode decomposition with adaptive noise, variational mode decomposition, correlation coefficient, and sample entropy are combined to decompose and reconstruct the raw sentiment index and obtain a denoised sentiment index. Subsequently, the neural basis expansion analysis with exogenous variables is improved by designing a weight coefficient and Optuna is used to optimize the designed weight coefficient and the hyperparameters. Finally, the SHapley Additive exPlanations value is used to increase the interpretability of prediction results. Corn futures prices for the Dalian Exchange are used in forecasting to validate the accuracy and stability of the proposed model. Experimental results show that the proposed denoising sentiment index contributes more to the improvement of predictive model performance than the raw sentiment index. The proposed text‐based deep predictive model demonstrates strong predictive ability for prediction horizons of 30 and 60 days. SHapley Additive exPlanations value analysis shows that the three features with greater effects on corn futures prices are as follows: "Corn Spot Price of Zhengzhou market," "CBOT_corn_futures_price," and "Pork futures price." [ABSTRACT FROM AUTHOR]

Wind power has emerged as a successful component within power systems. The ability to reliably and accurately forecast wind speed is of great importance in maintaining the security and stability of the power grid. However, the significance of explaining prediction models has often been overlooked by researchers. To address this gap, this study introduces a novel approach to wind speed forecasting that incorporates a significant decomposition method, attention‐based machine learning, and local explanation techniques. The proposed model utilizes grid search variational mode decomposition to decompose the wind speed sequence into different modes while employing gate recurrent unit with an attention mechanism to achieve superior forecasting performance. Experimental evaluations conducted on eight real‐world wind speed datasets demonstrate that the proposed approach outperforms other popular models across multiple performance criteria. In two specific experiments, the proposed approach achieved a minimal mean absolute percentage error of 2.74% and 1.70%, respectively. Furthermore, local interpretable model‐agnostic explanations (LIME) were employed to assess the influence of factors, highlighting whether they positively or negatively affected the predicted values. [ABSTRACT FROM AUTHOR]

Background and Aims Leaf area (A) is a crucial indicator of the photosynthetic capacity of plants. The Montgomery equation (ME), which hypothesizes that A is proportional to the product of leaf length (L) and width (W), is a valid tool for non-destructively measuring A for many broadleaved plants. At present, the methods used to compute L and W for the ME can be broadly divided into two kinds: using computer recognition and measuring manually. However, the potential difference in the prediction accuracy using either method has not been thoroughly examined in previous studies. Methods In the present study, we measured 540 Alangium chinense leaves, 489 Liquidambar formosana leaves and 215 Liriodendron  ×  sinoamericanum leaves, utilizing computer recognition and manual measurement methods to determine L and W. The ME was used to fit the data determined by the two methods, and the goodness of fits were compared. The prediction errors of A were analysed by examining the correlations with two leaf symmetry indices (areal ratio of the left side to the right side, and standardized index for bilateral asymmetry), as well as the leaf shape complexity index (the leaf dissection index). Key Results The results indicate that there is a neglectable difference in the estimation of A between the two methods. This further validates that the ME is an effective method for estimating A in broadleaved tree species, including those with lobes. Additionally, leaf shape complexity significantly influenced the estimation of A. Conclusions These results show that the use of computer recognition and manual measurement in the field are both effective and feasible, although the influence of leaf shape complexity should be considered when applying the ME to estimate A in the future. [ABSTRACT FROM AUTHOR]

Background: The development of acquired EGFR-TKI treatment resistance is still a major clinical challenge in the treatment of non-small cell lung cancer (NSCLC). This study aimed to investigate the role of HDAC1/FOXK1/miR-33a signaling in EGFR-TKI resistance. Methods: The expression levels of miR‐33a, HDAC1, and FOXK1 were examined using quantitative polymerase chain reaction (PCR) and bioinformatics analysis. Cell proliferation, migration, and apoptosis were explored by cell number assay, Transwell, and flow cytometry assays, respectively. After overexpression or knockdown of HDAC1, miR-33a expression in the cells, cell functions were tested. Immunoprecipitation and correlation analyses were used to evaluate the interaction between HDAC1 and FOXK1 protein. The tumor-suppressive role of miR-33a was investigated by animal experiments. Results: The suppression of miR-33a increased TKI resistance by affecting cell proliferation, migration, and apoptosis in gefitinib-resistant cells. HDAC1 is the key upstream molecule that inhibits miR-33 expression. HDAC1 upregulation increased gefitinib resistance by its binding to FOXK1 in cells to silence miR-33a expression. MiR-33a overexpression exerts tumor-suppressive effects by negatively regulating ABCB7 and p70S6K1 expression. Moreover, overexpression of miR-33a inhibited tumor growth in a xenograft nude mouse model. Conclusions: HDAC1/FOXK1 upregulation and miR-33a silencing are new mechanisms of EGFR-TKI resistance in NSCLC. [ABSTRACT FROM AUTHOR]

Micro‐expressions are spontaneous and unconscious facial movements that reveal individuals' genuine inner emotions. They hold significant potential in various psychological testing fields. As the face is a 3D deformation object, the emergence of facial expression leads to spatial deformation of the face. However, existing databases primarily offer 2D video sequences, limiting descriptions of 3D spatial information related to micro‐expressions. Here, a new micro‐expression database is proposed, which contains 2D image sequences and corresponding 3D point cloud sequences. These samples were classified using both an objective method based on the facial action coding system and a non‐objective emotion classification method that considers video contents and participants' self‐reports. A variety of feature extraction techniques are applied to 2D data, including traditional algorithms and deep learning methods. Additionally, a novel local curvature‐based algorithm is developed to extract 3D spatio‐temporal deformation features from the 3D data. The authors evaluated the classification accuracies of these two features individually and their fusion results under leave‐one‐subject‐out (LOSO) and tenfold cross‐validation. The results demonstrate that fusing 3D features with 2D features results in improved recognition performance compared to using 2D features alone. [ABSTRACT FROM AUTHOR]

Metal containing oxides and halides offer a wide range of design spaces for solid-state electrolytes. However, the stability of these electrolytes at the anode/electrolyte interface remains a concern. It is commonly believed that electrolytes containing metals, such as lithium perovskite and lithium metal halides, are inherently unstable at the anode. This issue of electrochemical stability has been somewhat overlooked amidst the surge of research focusing on the development of new superionic conductors. In this work, we employ a computational framework to uncover the underlying causes of anode instability in different electrolytes that contain metals. Our findings indicate that deficient compounds in lithium, such as lithium perovskite or lithium metal halide, tend to be unstable at the anode regardless of the metal chemistry involved. This instability is primarily due to their unsuitable lithium stoichiometry, positioning them in regions of the phase diagram where stronger decomposition phases prevail. Conversely, lithium-rich compounds, such as newly identified overlithiated disordered rocksalt-type electrolytes, exhibit significantly better anode stability. Additionally, our research also shows that while anode stability is generally less problematic for sodium metal oxide-based electrolytes in solid-state sodium-ion batteries, it remains a challenge for sodium metal halides. This work rationales the choice of metal species and structural phases as stoichiometry for more electrochemical stable solid-state electrolytes. [ABSTRACT FROM AUTHOR]

Background: Despite recent advances the prognosis of pulmonary hypertension remains poor and warrants novel therapeutic options. Extensive studies, including ours, have revealed that hypoxia-induced pulmonary hypertension is associated with high oxidative stress. Cerium oxide nanozyme or nanoparticles (CeNPs) have displayed catalytic activity mimicking both catalase and superoxide dismutase functions and have been widely used as an anti-oxidative stress approach. However, whether CeNPs can attenuate hypoxia-induced pulmonary vascular oxidative stress and pulmonary hypertension is unknown. Results: In this study, we designed a new ceria nanozyme or nanoparticle (AuCeNPs) exhibiting enhanced enzyme activity. The AuCeNPs significantly blunted the increase of reactive oxygen species and intracellular calcium concentration while limiting proliferation of pulmonary artery smooth muscle cells and pulmonary vasoconstriction in a model of hypoxia-induced pulmonary hypertension. In addition, the inhalation of nebulized AuCeNPs, but not CeNPs, not only prevented but also blunted hypoxia-induced pulmonary hypertension in rats. The benefits of AuCeNPs were associated with limited increase of intracellular calcium concentration as well as enhancement of extracellular calcium-sensing receptor (CaSR) activity and expression in rat pulmonary artery smooth muscle cells. Nebulised AuCeNPs showed a favorable safety profile, systemic arterial pressure, liver and kidney function, plasma Ca2+ level, and blood biochemical parameters were not affected. Conclusion: We conclude that AuCeNPs is an improved reactive oxygen species scavenger that effectively prevents and treats hypoxia-induced pulmonary hypertension. [ABSTRACT FROM AUTHOR]

The experiment combined aramid fiber-reinforced polymer (AFRP) and stainless steel (SS) into a laminated structure, which was an AFRP/SS/AFRP co-cured material. The milling cutter and drill bit were used in the experiment to study the hole machining effect of the co-cured material. The effects of machining parameters on the hole processing quality were compared, and the cutting mechanism of the co-cured material was revealed. The research results show that the processing effect of milling is better than that of drilling, and the cutting force during the hole machining process is small, only 53.619% of that of drilling. In the milling method, the tool wear is minor, and the material is primarily shear-fractured, while there are partial tensile fractures under drilling conditions. The damage form and mechanism of the co-cured material laminated interface were experimentally studied, the chip shapes of AFRP and stainless steel under different process methods were summarized, and the mechanism analysis was conducted based on cutting force and tool wear. Additionally, the experiment discovered a type of AFRP chip, which was resin chips. The morphology and forming mechanism of resin chips were analyzed, which provided a theoretical basis and auxiliary support for revealing the cutting mechanism of the co-cured material. [ABSTRACT FROM AUTHOR]

Fast-moving soft robotics usually suffer large-strain deformation with a relatively high velocity. To improve their performance, it is necessary to study the underly dynamical mechanism. However, the inherent strong material nonlinearity brings considerable difficulties in modeling and calculating the soft structure's nonlinear dynamics. This work focuses on the large-strain vibrations of the hyperelastic rod under an axial tensile force. Several typical hyperelastic models, including the neo-Hookean, Mooney, and Yeoh models, are used to derive the equations governing the rod's dynamics. The equations based on these models are relatively complex, and their corresponding numerical calculation diverges in some cases. Therefore, a reference stretch ratio(s) polynomial fitting (RSRPF) model is proposed to derive the concise governing equation. Such a governing equation is effectively solved by the combination of the Galerkin discretization and the fourth-order Runge–Kutta integration algorithm. The correctness of the developed model and the employed algorithm is verified by comparing with the previous data of a hyperelastic membrane. In most cases, the rod periodically vibrates under a periodic tensile force. However, when the structural damping is small and the load frequency approaches the resonant frequency, the hyperelastic rod may quasi-periodically vibrate. The revealed large-strain vibration mechanism is supposed to be useful for guiding the dynamical design of soft structures. [ABSTRACT FROM AUTHOR]

Identifying seismic CH4 anomalies via remote sensing has been verified as a legitimate method. However, there are still some problems, such as unknown reliability due to the complex characteristics of seismic anomalies. In this study, a multi-dimensional and multi-scale methane seismic anomaly extraction process for remote sensing was constructed with the Robust Satellite Technique (RST) based on the Atmospheric Infrared Sounder (AIRS) CH4 data and then applied to the 2023 Türkiye–Syria earthquake. This study obtained the two-dimensional temporal–spatial distribution of methane anomalies and temporal variation in the anomaly index. Based on this, the three-dimensional profile structure of the 8-day methane anomaly was extracted to determine the reliability of the anomaly. Finally, based on the daily methane anomaly, combined with atmospheric circulation and backward trajectory analysis as auxiliary tools, the influence of air mass migration was excluded to enhance the accuracy of CH4 anomaly determination. The results show that the three-dimensional anomalous structure is consistent with the geological characteristics of tectonic activities, and it appears as a "pyramid" or "inverted pyramid" type in a three-dimensional space. The anomalies caused by air mass migration can be eliminated by combining them with synoptic-scale circulation motion. The time series calculated at the epicenter or a certain point in a region may not accurately reflect the influence of regional or specific tectonic activity in the atmosphere. Thus, the optimal determination of the range and magnitude of atmospheric anomalies caused by tectonic activities is a difficult task for future research. [ABSTRACT FROM AUTHOR]

Mixing involves blending raw rubber or masticated rubber with additives using a rubber mixer, which is the most critical process in rubber production. The internal mixer, as the most important mixing equipment, experiences rotor wear during prolonged operation, affecting the gap between the mixer rotor and the chamber wall. This wear reduces mixing effectiveness, weakens filler dispersion, and ultimately impacts rubber performance. In recent years, as research on multi-walled carbon nanotubes (MWCNTs) and nanomaterials has deepened, their broad application prospects have become increasingly apparent. The objective of the present study is to understand and quantify rotor wear in rubber blends during the mixing process as influenced by multi-walled carbon nanotubes. This study found that with the increase in MWCNT content, the proportion of abrasive wear rises, while the proportion of corrosive wear decreases, leading to reduced overall wear. Compared to rubber without MWCNTs, the Payne effect decreased by 6.78%, 9.57%, 13.03%, 20.48%, and 26.06% with the addition of 1 phr, 3 phr, 5 phr, 7 phr, and 9 phr of MWCNTs, respectively. The friction coefficients between the rubber and metal increased by 6.31%, 8.57%, 25.43%, 39.31%, and 47.61%, while the metal wear rate decreased by 9.08%, 10.73%, 13.41%, 17.46%, and 25%. Conversely, the friction coefficients were reduced by 19.39%, 22.42%, 33.94%, 66.06%, and 76.36%. [ABSTRACT FROM AUTHOR]

Proposed is a Satellite network cache placement strategy (PNCCP) based on popularity and node cooperation to address the issue of significant delays in end-to-end connectivity due to instability among satellites. Initially, the strategy employs spectral clustering algorithm to partition the satellite network's topology, limiting the retrieval scope of content and reducing unnecessary propagation delays. Within each partition, a cache collaboration open mechanism among satellites is devised to share cache resources, utilizing the proximity of neighboring nodes to share popular content and cache space. Furthermore, the data naming network (NDN) cache model is enhanced and integrated with the open mechanism, with an update mechanism designed to address the invalidation caused by the dynamic nature of satellite networks. Finally, aiming to minimize users' average retrieval delay, the artificial bee colony algorithm is employed to solve the optimal cache placement problem. Simulation results demonstrate that compared to three contrasting cache strategies, the proposed strategy reduces user content retrieval delays, improves cache hit rates, and holds an advantage in reducing request hop counts. [ABSTRACT FROM AUTHOR]

The electrochemical conversion of glycerol into high-value chemicals through the selective glycerol oxidation reaction (GOR) holds importance in utilizing the surplus platform chemical component of glycerol. Nevertheless, it is still very limited in producing three-carbon chain (C3) chemicals, especially glyceric acid/glycerate, through the direct oxidation of its primary hydroxyl group. Herein, Pd microstructure electrodeposited on the Ni foam support (Pd/NF) is designed and fabricated to achieve a highly efficient GOR, exhibiting a superior current density of ca. 120 mA cm−2 at 0.8 V vs. reversible hydrogen electrode (RHE), and high selectivity of glycerate at ca. 70%. The Faradaic efficiency of C3 chemicals from GOR can still be maintained at ca. 80% after 20 continuous electrolysis runs, and the conversion rate of glycerol can reach 95% after 10-h electrolysis. It is also clarified that the dual-component interfaces constructed by the adjacent Pd and Ni sites are responsible for this highly efficient GOR. Specifically, Ni sites can effectively strengthen the generative capacity of the active adsorbed hydroxyl (OHad) species, which can steadily immigrate to the Pd sites, so that the surface adsorbed glycerol species are quickly oxidized into C3 chemicals, rather than breaking the C–C bond of glycerol; thus, neither form the C2/C1 species. This study may yield fresh perspectives on the electrocatalytic conversion of glycerol into high-value C3 chemicals, such as glyceric acid/glycerate. [ABSTRACT FROM AUTHOR]

Lymphoplasmacytic lymphoma (LPL) is an incurable low-grade lymphoma with no standard therapy. Nine asymptomatic patients treated with a first-in-human, neoantigen DNA vaccine experienced no dose limiting toxicities (primary endpoint, NCT01209871). All patients achieve stable disease or better, with one minor response, and median time to progression of 72+ months. Post-vaccine single-cell transcriptomics reveal dichotomous antitumor responses, with reduced tumor B-cells (tracked by unique B cell receptor) and their survival pathways, but no change in clonal plasma cells. Downregulation of human leukocyte antigen (HLA) class II molecules and paradoxical upregulation of insulin-like growth factor (IGF) by the latter suggest resistance mechanisms. Vaccine therapy activates and expands bone marrow T-cell clonotypes, and functional neoantigen-specific responses (secondary endpoint), but not co-inhibitory pathways or Treg, and reduces protumoral signaling by myeloid cells, suggesting favorable perturbation of the tumor immune microenvironment. Future strategies may require combinations of vaccines with agents targeting plasma cell subpopulations, or blockade of IGF-1 signaling or myeloid cell checkpoints. Lymphoplasmacytic lymphoma is a B-cell low-grade lymphoma with no approved standard therapy. Here the authors report a non-randomized phase 1 clinical trial performing early intervention with personalized neoantigen vaccines in asymptomatic patients and associating clinical efficacy with successful perturbation of the tumor immune microenvironment. [ABSTRACT FROM AUTHOR]

This article explores the interaction between the human coronavirus HKU1 spike receptor binding domain (RBD) and its receptor TMPRSS2. The researchers used cryo-EM structures to determine the complex between the HKU1 RBD and TMPRSS2, identifying key regions involved in their interaction. The study found that the binding primarily relies on hydrophobic packing and shape complementarity, with no significant conformational changes. The researchers also discovered that specific residues in the HKU1 spike protein are responsible for binding to TMPRSS2, and variations in certain amino acids can impact the binding affinity. This research provides valuable insights into the entry mechanism of HKU1 and could potentially contribute to the development of vaccines and antiviral treatments. [Extracted from the article]

Membranous nephropathy (MN) is a leading cause of nephrotic syndrome in adults and is associated with high rates of end-stage renal disease. Early detection and precise interventions are crucial for improving patient prognosis and quality of life. However, the current diagnosis primarily relies on renal biopsies and traditional biomarkers, which have limitations. Additionally, targeted therapeutic strategies are lacking. Exosomes, small vesicles that facilitate intercellular communication, have emerged as potential noninvasive diagnostic markers due to their stability, diverse cargo, and rapid detectability. They also hold promise as carriers for gene and drug delivery, presenting innovative opportunities in renal disease prognosis and treatment. However, research on exosomes in the context of idiopathic membranous nephropathy (IMN) remains limited, with a focus on exploring urinary exosomes as IMN markers. In this review, we summarize the current status of MN diagnosis and treatment, highlight the fundamental characteristics of exosomes, and discuss recent advancements in their application to IMN diagnosis and therapy. We provide insights into the clinical prospects of exosomes in IMN and acknowledge potential challenges. This article aims to offer forward-looking insights into the future of exosome-mediated IMN diagnosis and treatment, indicating a revolutionary transformation in this field. [ABSTRACT FROM AUTHOR]

Endothelialization is important for offering an anticoagulant surface, which is crucial for the construction of tissue‐engineered heart valves. Silk sericin is extensively investigated in the biomedical field due to its remarkable biological activities and diverse functional groups, favoring chemical modifications for the formation of versatile constructs. Herein, a sericin covalently modified valve (SCMV) is successfully fabricated by coupling maleylated silk sericin (MSS) with thiolated decellularized heart valve (DHV) through a Michael addition reaction. The results demonstrate that SCMV exhibits a smooth surface, higher hydrophilicity, and excellent resistance to platelets adhesion compared to DHV. Additionally, SCMV promotes endothelial cells (ECs) adhesion under both static and flow conditions and enhances their survival in a mouse subcutaneous implant model. The study also discovered that MSS‐stimulated ECs exhibit increased RhoA activation, expression of rho‐associated protein kinase 2 (ROCK2) and phosphorylated myosin light chain 2 (MLC2), actin polymerization, and cell adhesion; whereas actin organization and cell adhesion are significantly reduced by treatment with Y‐27632, a ROCK inhibitor. Furthermore, several integrin subunits, including α1, α2, α3, α5, α6, β1, β3, and β5, are involved in this regulatory process. Collectively, the findings highlight the potential application of silk sericin in promoting endothelialization of DHV while uncovering novel mechanisms underlying its regulatory effect on ECs adhesion. [ABSTRACT FROM AUTHOR]

While perovskite solar cells (PSCs) have achieved remarkable power conversion efficiencies (PCEs) exceeding 26.1%, significant challenges remain in enhancing their efficiency and stability for commercial viability. Recently, the preparation of perovskite thin films based on solution methods has been widely studied. Most of the solvents used are organic solvents, which are highly toxic and therefore not conducive to large-scale production. However, the emergence of ionic liquids (ILs) with low toxicity and excellent properties will effectively solve this problem. In addition, many studies have shown that ILs play an active role in achieving efficient and stable PSCs. In this review, we focus on the recent advances in utilizing ILs as solvents, additives, and interface engineering within PSCs, and conclude with prospects for their future optimization and application in enhancing PSC performance. [ABSTRACT FROM AUTHOR]

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for ~15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits. The authors present a comprehensive regulome atlas for rice by mapping chromatin accessibility across 23 tissues from three rice varieties. By integrating matched RNA-seq data, they accurately predict numerous associations between non-coding regulatory elements and target genes. This study provides a foundational resource for gene editing and breeding strategies targeting non-coding regions in rice, potentially advancing crop improvement efforts. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to investigate the knowledge, attitude, and practice (KAP) of patients admitted to the gastroenterology department in the Shanxi region concerning chronic gastritis. Methods: This study was conducted in Shanxi between April and July 2023. The participants were enrolled when they consulted at the clinic. Demographic characteristics and KAP scores were collected through a self-administered questionnaire. KAP scores > 60% were considered good. Structural equation modeling (SEM) was utilized to examine the relationships among the dimensions of knowledge, attitude, and practice. Results: A total of 416 valid questionnaires were collected. The median knowledge score was 28 (0– 60) (with possible values of 0– 60), the median attitude score was 60 (28– 77) (with possible values of 16– 80), and the median practice score was 45 (12– 60) (with possible values of 12– 60). Hence, 133, 379, and 343 participants had knowledge, attitude, and practice scores, respectively, above the 60% threshold. Significant positive correlations were found between knowledge and attitude (r=0.300, P< 0.001), knowledge and practice (r = 0.297, P< 0.001), and attitude and practice (r=0.353, P=0.004) through correlation analysis. Structural Equation Modeling (SEM) revealed that knowledge directly and significantly influenced attitude (β=0.643, P< 0.001), as well as practice (β=0.095, P=0.034), and attitude had a direct effect on practice (β=0.094, P=0.009). Conclusion: Insufficient knowledge, positive attitudes, and proactive practices concerning chronic gastritis were observed in patients in the gastroenterology department. Prioritizing patient education and addressing patient attitudes during clinical consultations can enhance healthcare practices and improve the management of chronic gastritis. [ABSTRACT FROM AUTHOR]

Silty soil is a transitional soil between clay and sand and is widely distributed around the world. With the rapid urban development and associated infrastructure need, silty soil has become more widely used as the bearing soil for foundations and roads. The liquefaction of silty soil under the earthquake can cause serious damage to buildings and infrastructure resting on such soil. Correctly analyzing the dynamic characteristics of silty soil in earthquake areas plays a major role in the success or failure of infrastructure construction. Therefore, it is particularly important to study the various factors affecting the dynamic characteristics of silty soil and to analyze the changing trend and associated mechanism on the dynamic characteristics of silty soil. In this paper, a set of cycle triaxial tests were carried out using the orthogonal design method to study the effects of four factors, namely initial void ratio, load frequency, clay content and silt content, on the dynamic characteristics of saturated silty soil at different levels. The orthogonal design method is used to study the order of influence of four factors on the dynamic strength and excess pore water pressure of silty soil, and the significance level of each factor was also assessed. [ABSTRACT FROM AUTHOR]

This research highlights that street layouts, including the vegetation ratio, street orientation, and aspect ratio, are key in diminishing urban heat islands (UHIs), building energy use, and carbon emissions. The optimal street layout for minimal building energy consumption, carbon emissions, and maximal outdoor thermal comfort in Tianjin was established via field measurements, ENVI-met 5.6.1, Energy Plus simulations, and correlation analysis. The findings indicate the following: (1) The carbon emissions of winter residential heating energy consumption are 2.9–3.2 times higher than those for summer cooling. Urban design should thus prioritize winter energy efficiency and summer thermal comfort outdoors. (2) The summer street PET (physiological equivalent temperature) inversely correlates with the vegetation ratio and aspect ratio. Winter heating energy use inversely correlates with the street orientation and directly correlates with the aspect ratio. Adequate vegetation and proper orientation can decrease energy and carbon output while enhancing summer outdoor comfort. (3) Streets with an NW–SE orientation, H/W = 0.9, and 50% trees in summer yield the best thermal comfort, while those with an NE–SW orientation, H/W = 0.3, and 50% vegetative trees in winter produce the lowest carbon emissions. These insights are instrumental in refining urban streets and building designs in cold zones. [ABSTRACT FROM AUTHOR]

Foliar zinc (Zn) application can affect the accumulation and bioaccessibility of cadmium (Cd) and Zn in crops. However, the mechanisms by which foliar Zn application influences Cd and Zn bioaccessibility remain elusive. This study examined the effects of spraying ZnSO4 and ZnNa2EDTA on bioaccessibility and chemical forms of Cd and Zn in pakchoi (Brassica chinensis L.) shoots and evaluated human health risks via pakchoi consumption. Spraying ZnSO4 reduced the concentrations of ethanol-extractable (Fethanol) and deionized water-extractable (Fd-H2O) Cd, as well as the corresponding bioaccessible Cd concentrations (20.3–66.4%) and attendant health risks of Cd, whereas spraying high-dose ZnNa2EDTA significantly increased the concentrations of both Cd forms and bioaccessible Cd. Spraying ZnSO4 and high-dose ZnNa2EDTA significantly increased the concentrations of Zn in Fethanol and Fd-H2O and the corresponding bioaccessible Zn concentrations (0.8–8.3-fold). Fethanol and Fd-H2O were the primary sources of bioaccessible Cd and Zn, contributing more than 59% of the bioaccessible Cd and Zn. These results indicate that foliar Zn application can affect Cd and Zn bioaccessibility in pakchoi mainly by modulating Cd and Zn in Fethanol and Fd-H2O. These findings provide scientific support for the development of more efficient measures to produce safe and high-quality leafy vegetables from Cd-polluted soils. [ABSTRACT FROM AUTHOR]

In order to improve the ability of avoiding dynamic threats during the flight of unmanned aerial vehicles (UAVs), a deep reinforcement learning-based reactive trajectory planning method is proposed in this paper. Firstly, a constrained Rapidly-exploring Random Tree-Connect algorithm (C-RRT-Connect) is proposed as the basic algorithm of reactive trajectory planning to globally plan for avoiding static obstacles in the environment. The C-RRT-Connect algorithm introduces the idea of target attraction to constrain the optimal growth point in the RRT-Connect algorithm. Then, based on the global trajectory, the local optimization is carried out according to the dynamic threats detected by the UAV during the flight. According to the real-time relative state between the UAV and the detected dynamic threat, the reaction sampling points and directional coefficients for avoiding the corresponding dynamic threat are generated online via the action network trained with the depth deterministic policy gradient algorithm (DDPG). And then the local trajectory is adjusted to modify the flight trajectory of the UAV to achieve reactive obstacle avoidance. The simulation experiment firstly compares the global trajectory planning performance of C-RRT-Connect and RRT-Connect in static environment, and secondly compares the local trajectory planning performance of DDPG algorithm and the artificial potential field method in dynamic environment. The experimental results show that in static environment, C-RRT-Connect algorithm has faster searching speed, less invalid samples and higher searching trajectory quality than RRT-Connect algorithm; In a dynamic environment, DDPG algorithm reduces the average running time by about 26% compared with the artificial potential field method, and has a stronger ability to evade dynamic threats in real time. [ABSTRACT FROM AUTHOR]

Oxygenated volatile organic compound (OVOC) emissions play a critical role in tropospheric ozone (O3) formation. This paper aims to establish an emission inventory and source profile database for OVOCs in Beijing, utilizing revised and reconstructed data from field measurements and existing literature. The study also assesses their potential impact on the O3 base on the ozone formation potential (OFP). Results indicate that OVOC emissions in Beijing predominantly originate from natural and residential sources, encompassing commercial solvent usage, cooking, residential combustion, construction adhesives, and construction coatings. OVOCs contributed 5.6% to OFP, which is significantly less than their emission contribution of 20.1%. Major OFP contributors include plant sources (26.2%), commercial solvent use (21.0%), cooking (20.5%), and construction adhesives (8.4%). The primary OVOC species contributing to OFP for OVOCs are acetaldehyde, methanol, hexanal, ethanol, and acetone, collectively contributing 59.0% of the total OFP. Natural sources exhibit significant seasonal variability, particularly in summer when plant emissions peak, constituting 78.9% of annual emissions and significantly impacting summer ozone pollution (OFP of 13,954 t). Conversely, emissions from other OVOC sources remain relatively stable year-round. Thus, strategies to mitigate summer ozone pollution in Beijing should prioritize plant sources while comprehensively addressing residential sources in other seasons. District-specific annual OVOC emissions are from Fangshan (3967 t), Changping (3958 t), Daxing (3853 t), and Chaoyang (3616 t), which reflect year-round forested areas in these regions and high populations. [ABSTRACT FROM AUTHOR]

CD27 as a marker of memory B cells is belong to the tumor necrosis factor receptor (TNFR) superfamily, CD27 is ligated by CD70, they can co-stimulate T-cell growth and differentiation through their interaction. Uncertainty surrounds CD27's function in esophageal cancer (EC). This study investigated the role of CD27 in the prognosis of EC using the TCGA, cbioportal, linkedomics and GEPIA databases as well as the proliferation assay was applied. CD27 differential expression may be a key factor in the development of EC. different level of CD27 expression in EC has profound impacts on TOR complex, and many kinds of kinase (KIT proto-oncogene receptor tyrosine kinase, transforming growth factor beta receptor 1, and G protein-coupled receptor kinase 3.), as well as the cell membrane, and survival analysis revealed that it had a significant impact on both the overall survival and disease-free survival of EC. CD27 overexpression will suppress the viability of the KYSE150 and TE3 cells. Our findings suggested that the degree of CD27 expression could serve as an esophageal cancer prognosis biomarker. [ABSTRACT FROM AUTHOR]

Background: Maize stalk rot (MSR) caused by Fusarium graminearum is the primary factor contributing to the reduction in maize yield and quality. However, this soil‐borne disease presents a significant challenge for sustainable control through field management and chemical agents. The screening of novel biocontrol agents can aid in developing innovative and successful strategies for MSR control. Results: A total of 407 strains of bacteria were isolated from the rhizosphere soil of a resistant maize inbred line. One strain exhibited significant antagonistic activity in plate and pot experiments, and was identified as Burkholderia ambifaria H8. The strain could significantly inhibit the mycelial growth and spore germination of F. graminearum, induce resistance to stalk rot, and promote plant growth. The volatile compounds produced by strain H8 and its secondary metabolites in the sterile fermentation broth exhibited antagonistic activity. The primary volatile compound produced by strain H8 was identified as dimethyl disulfide (DMDS) using gas chromatography tandem mass spectrometry. Through in vitro antagonistic activity assays and microscopic observation, it was confirmed that DMDS was capable of inhibiting mycelial growth and disrupting the mycelial structure of F. graminearum, suggesting it may be the major active compound for strain H8. The transcriptome data of F. graminearum further indicated that strain H8 and its volatile compounds could alter pathogenic fungi metabolism, influence the related metabolic pathways, and potentially induce cell apoptosis within F. graminearum. Conclusion: Our results showed that B. ambifaria H8 was capable of producing the volatile substance dimethyl disulfide, which influenced the synthesis and permeability of cell membranes in pathogens. Thus, B. ambifaria H8 was found to be a promising biological control agent against MSR. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Examining the pollination biology of plant species is not only crucial for enhancing our understanding of their reproductive biology, but also essential for elucidating their adaptation and evolutionary history. Here, we investigated the breeding system and pollination biology of two closely related species in Actaea. The flower of A. purpurea is unique in the genus with purple and chartaceous (paper-like) sepals, fewer stamens with yellow anthers and purple filaments. Through three seasons of field observation and exclusion experiments, we determined that A. purpurea was primarily pollinated by a hornet species, Vespa bicolor , which also served as the most efficient pollinator. In contrast, A. japonica was primarily pollinated by large flies. Actaea purpurea exhibited a significantly higher cumulative nectar volume than A. japonica , which could be a crucial factor in attracting V. bicolor. A control experiment further demonstrated that removing the nectar leaf (petal) significantly decreased the visiting frequency of V. bicolor. Breeding system studies revealed that both species were self-compatible, yet they primarily underwent outcrossing in natural habitats. Our study presents a compelling case of possible pollinator shift in A. purpurea accompanied by morphological divergence. A more in-depth investigation of this system would offer crucial insights into the extent to which pollinators are involved in the plant speciation process and whether they contribute to reproductive isolation between closely related species. [ABSTRACT FROM AUTHOR]

The spin-torsion theory is a gauge theory approach to gravity that expands upon Einstein's general relativity (GR) by incorporating the spin of microparticles. In this study, we further develop the spin-torsion theory to examine spherically symmetric and static gravitational systems that involve free-falling macroscopic particles. We posit that the quantum spin of macroscopic matter becomes noteworthy at cosmic scales. We further assume that the Dirac spinor and Dirac equation adequately capture all essential physical characteristics of the particles and their associated processes. A crucial aspect of our approach involves substituting the constant mass in the Dirac equation with a scale function, allowing us to establish a connection between quantum effects and the scale of gravitational systems. This mechanism ensures that the quantum effect of macroscopic matter is scale-dependent and diminishes locally, a phenomenon not observed in microparticles. For any given matter density distribution, our theory predicts an additional quantum term, the quantum potential energy (QPE), within the mass expression. The QPE induces time dilation and distance contraction, and thus mimics a gravitational well. When applied to cosmology, our theory yields a static cosmological model. The QPE serves as a counterpart to the cosmological constant introduced by Einstein to balance gravity in his static cosmological model. The QPE also offers a plausible explanation for the origin of Hubble redshift (traditionally attributed to the universe's expansion). The predicted luminosity distance–redshift relation aligns remarkably well with SNe Ia data from the cosmological sample of SNe Ia. In the context of galaxies, the QPE functions as the equivalent of dark matter. The predicted circular velocities align well with rotation curve data from the SPARC (Spitzer Photometry and Accurate Rotation Curves database) sample. Importantly, our conclusions in this paper are reached through a conventional approach, with the sole assumption of the quantum effects of macroscopic matter at large scales, without the need for additional modifications or assumptions. [ABSTRACT FROM AUTHOR]

The enhancement of economic sustainability and the reduction of greenhouse gas (GHG) emissions are becoming more relevant in power system planning. Thus, renewable energy sources (RESs) have been widely used as clean energy for their lower generation costs and environmentally friendly characteristics. However, the strong random uncertainties from both the demand and generation sides make planning an economic, reliable, and ecological power system more complicated. Thus, this paper considers a variety of resources and technologies and presents a coordinated planning model including energy storage systems (ESSs) and grid network expansion, considering the trustworthiness of demand-side response (DR). First, the size of a single ESS was considered as its size has a close effect on maintenance costs and ultimately affects the total operating cost of the system. Second, it evaluates the influence of the trustworthiness of DR. Third, multiple resources and technologies were included in this high-penetration renewable energy integrated power system, such as ESSs, networks, DR technology, and GHG reduction technology. Finally, this model optimizes the decision variables such as the single size and location of ESSs and the operation parameters such as thermal generation costs, loss load costs, renewable energy curtailment costs, and GHG emission costs. Since the problem scale is very large not only due to the presence of various devices but also both binary and continuous variables considered simultaneously, we reformulate this model by decomposition. Then, we transform it into a master problem (MP) and a dual sub-problem (SP). Finally, the proposed method is applied to a modified IEEE 24-bus test system. The results show computational effectiveness and provide a helpful method in planning low-carbon electricity power systems. [ABSTRACT FROM AUTHOR]