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The purpose of this study is to investigate the effect of dietary supplementation with rhamnolipids (RLs) on the growth performance, slaughter performance, apparent digestibility and fat metabolism of broilers. Broiler chicks were randomly divided into 3 groups: control (C) group, 100 mg/kg (L) and 1,000 mg/kg (H) RL supplementation groups. The results, after dietary supplementation with RLs for 42 days, revealed a RL dose-dependent promoting effect on feed intake, and an increase of the evisceration index of 42-day-old broilers, but a decrease in the rate of abdominal fat gain. The dietary supplementation with RLs significantly increased the digestibility of protein and fat in broilers. The serum total cholesterol and high-density lipoprotein cholesterol levels of the H group were significantly higher than those of the C group (p

Abstract This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted and randomly divided into training and validation sets using the Surveillance, Epidemiology, and End Results database. We developed a prediction model using 10 machine learning algorithms across 101 combinations to forecast cancer-related mortality in patients with gNENs, selecting the best model using the highest mean over a sequence of time-dependent area under the receiver operating characteristic (ROC) curve (AUC). The performance of the final model was assessed through time-dependent ROC curves for discrimination and calibration curves for calibration. The maximum selection rank method was used to determine the best prognostic risk score threshold for classifying patients into high- and low-risk groups. Afterward, Kaplan–Meier analysis and log-rank test were used to compare survival rates among these groups. Our study examined 775 patients with gNENs, dividing them into training and validation sets. A training set comprised 543 patients, with a median follow-up of 42 months and cumulative mortality rates of 40.0% at 1 year, 48.6% at 3 years, and 54.0% at 5 years. A validation set comprised 232 patients, with cumulative mortality rates of 29.1% at 1 year, 43.5% at 3 years, and 53.2% at 5 years. The optimal random survival forest (RSF) model (mtry = 4, node size = 5) achieved an AUC of 0.839 for survival prediction in the training set. Comprising 11 variables such as demographics, treatment details, tumor characteristics, T staging, N staging, and M staging, the RSF model revealed high predictive accuracy with AUCs of 0.92, 0.96, and 0.96 for 1-, 3-, and 5-year survival, respectively, which was consistently reflected in the validation set with AUCs of 0.88, 0.92, and 0.89, respectively. Moreover, patients were risk-stratified. Although our RSF model effectively stratified patients into different prognostic groups, it needs external validation to confirm its utility for noninvasive prognostic prediction and risk stratification in gNENs. Further research is required to verify its broader clinical applicability.

Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements. We evaluated the robustness of multiple models, such as the Global Land Data Assimilation System (GLDAS), the Famine Early Warning System Network Land Data Assimilation System (FLDAS), the National Centers for Environmental Prediction (NCEP), and the WaterGAP Global Hydrology Model (WGHM). Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series, satellite gravity field Mascon solutions, and Global Precipitation Climatology Centre (GPCC) guide our assessment. Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP. In the Amazon River Basin, a 5-month lag between FLDAS, GLDAS, and satellite gravity results is observed. In eastern Asia and Australia, NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models. Three combined hydrological models (H-VCE, H-EWM, and H-CVM) utilizing Variance Component Estimation (VCE), Entropy Weight Method (EWM), and Coefficient of Variation Method (CVM) are formulated. Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%–17%. Correlation with precipitation increases by 25%–30%, and with satellite gravity, rises from 0.2 to 0.8 at maximum. The combined model eliminates time lag in the Amazon Basin TWSC analysis, exhibiting a four times higher signal-to-noise ratio than single models. H-VCE demonstrates the highest accuracy. In summary, the combined hydrological model minimizes discrepancies among individual models, significantly improving accuracy for monitoring large-scale TWSC.

Static stretching (SS) may reduce maximal muscle force and power output, while short-duration, high-intensity conditioning contractions (CC) have the potential to increase force and power output. However, the precise effects of CC on athletic performance and lower limb muscle coordination after SS are not yet fully understood. This investigation sought to explore the effects of SS (four sets of 30 seconds each) and its combination with CC (10 repetitive drop jumps), denoted as SC, on the synergy patterns of key lower limb muscles and jump performance during squat jumps (SJ) executed at two distinct knee joint starting angles (90° and 120°). Eleven participants were randomly assigned to three experimental conditions, with each condition encompassing three SJs at both angles. A three-dimensional motion capture system, force platform, and electromyography (EMG) system were employed to quantify jump height, extract ground contact time, and perform non-negative matrix factorization. Our findings revealed that at a knee joint starting angle of 120°, both SS and SC altered the weighting of the five major muscles (cosine similarity: SS: r = 0.897; SC: r = 0.767) and augmented the activity strength of the primary synergy (SS: 59.6%; SC: 10.48%). Additionally, SC demonstrably advanced the phase shift (90°: 14%; 120°: 61%). Notably, neither SS nor SC exerted a statistically significant influence on jump height (p > 0.05). However, SS significantly increased ground contact time (p = 0.029). In conclusion, at a knee joint angle of 120°, both SS and CC were observed to alter lower limb muscle synergy patterns and influence ground contact time. While SS led to an increase in ground contact time, CC effectively countered this rise. These findings suggest that athletes in disciplines demanding rapid movements might benefit from omitting SS in isolation during warm-ups or consider combining SS with CC to optimize performance.

Abstract The NLRP3 inflammasome plays a crucial role in inflammatory responses, particularly in alcohol-related liver disease (ALD). Given that NLRP3 has emerged as a potential therapeutic target for ALD, the development of effective inhibitors is of great importance. In this study, we trained 11 regression models, and the results showed that LightGBM, Random Forest, and XGBoost performed the best, achieving R² values of 0.774, 0.755, and 0.719, respectively. Using machine learning models and physical methods, we screened more than 11.5 million compounds from Asinex, Princeton, UkrOrgSynthesis, Chemdiv, Chembridge, Alinda, Enamine, and Lifechemicals, which led to the identification of 26 potential NLRP3 inhibitors. Furthermore, molecular dynamics simulations and MMGBSA binding energy calculations confirmed the stability of the interactions between NLRP3 and three key molecules: 19,655,631 (source Chembridge), 38,214,692 (source Chembridge), and Z1180203703 (source Enamine). Additionally, ADMET analysis revealed their favorable pharmacokinetic properties. This study provides insights and candidate molecules for discovering NLRP3 inhibitors, potentially applicable in treating related diseases.

Abstract Objective This report details the experience of a patient who developed a second primary glioblastoma (GB), offering insights into the treatment process and reviewing relevant literature. Case presentation A male patient, who was diagnosed with medulloblastoma at age 9, received treatment with cobalt-60 craniospinal irradiation (CSI) (36 Gy/20 fractions) and a tumor bed boost (total of 56 Gy). After 32 years, at age 41, an MRI revealed a space-occupying mass in the left cerebellar hemisphere. Surgical resection was performed, and postoperative pathology confirmed a diagnosis of radiation-induced glioblastoma (RIGB). Given the history of irradiation and the current tolerability of brainstem doses, proton beam therapy (PBT) combined with Temozolomide (75 mg/m2) was chosen. The treatment plan included 60 Gy on the gross tumor bed and 54 Gy on the clinical target volume, delivered in 30 fractions. The patient underwent regular follow-up and achieved a complete response. Clinical discussion For childhood cancer survivors, the development of a second primary tumor significantly impacts prognosis. RIGB is a rare form of secondary tumor with distinct molecular characteristics compared to primary GB and recurrent secondary GB. Molecular markers such as IDH and MGMT status can help differentiate between primary GB, recurrent secondary GB, and radiation-induced secondary GB in patients with a history of prior radiation therapy. Surgical resection remains a primary treatment option, while PBT is preferred for postoperative treatment due to its superior protection of normal tissues and the ability to deliver high-dose irradiation. Conclusion RIGB is a rare second primary tumor that requires strategic molecular profiling and individualized management. Proton beam therapy provides effective high-dose irradiation in the postoperative phase and is the preferred treatment option for such cases.

In this study, the optimal laser powder bed fusion (LPBF) processing parameters for fabricating fully dense LaCe(Fe,Mn,Si)13 thin walls have been identified through a machine-learning approach based on the Gaussian process regression (GPR) model. All the specimens and components were fabricated using a continuous laser source. The relationship between the defect fraction of the fabricated thin wall and the line energy density (EL) and hatch (h) is established. The measured defect fraction of specimens fabricated using the validation data sets was very well in agreement with the predicted values of the GPR model, with an error of less than 1%. The microstructure of as-fabricated lattices is contained by α-Fe phases, LaFeSi phases, NaZn13-type phases, and the La/Ce/Si rich phases, which has an amorphous matrix embedded with nanocrystalline. The microstructure of the HTHed lattices presents the α-Fe phases, LaFeSi phases, and NaZn13-type phases. The diamond lattice has high heat exchange efficiency among the four lattices because of its large surface area (1577.1 mm2) and excellent thermal conductivity. Although the LPBF parameters are the same, the maximum isothermal magnetic entropy change (ΔSm) and Tc of the four samples differ. The X-ray powder diffraction test confirms that the HTHed Tube exhibits the highest volume of the NaZn13-type phase. The HTHed Tube saw ΔSm, about 1.63 J kg−1K−1 at 264.5 K. The ΔSm of HTHed Diamond around Tc (1.13 J kg−1K−1 at 219.5 K) is slightly higher than HTHed Gyroid (0.99 J kg−1K−1 at 250.5 K). Essentially, our work accelerates the search for optimal process parameters and guides the direction for lattice design of LaCe(Fe,Mn,Si)13.

Abstract In practical engineering, noise and impact hazards are pervasive, indicating the pressing demand for materials that can absorb both sound and stress wave energy simultaneously. However, the rational design of such multifunctional materials remains a challenge. Herein, inspired by cuttlebone, we present bioinspired architected metamaterials with unprecedented sound-absorbing and mechanical properties engineered via a weakly-coupled design. The acoustic elements feature heterogeneous multilayered resonators, whereas the mechanical responses are based on asymmetric cambered cell walls. These metamaterials experimentally demonstrated an average absorption coefficient of 0.80 from 1.0 to 6.0 kHz, with 77% of the data points exceeding the desired 0.75 threshold, all with a compact 21 mm thickness. An absorptance-thickness map is devised for assessing the sound-absorption efficiency. The high-fidelity microstructure-based model reveals the air friction damping mechanism, with broadband behavior attributed to multimodal hybrid resonance. Empowered by the cambered design of cell walls, metamaterials shift catastrophic failure toward a progressive deformation mode characterized by stable stress plateaus and ultrahigh specific energy absorption of 50.7 J/g—a 558.4% increase over the straight-wall design. After the deformation mechanisms are elucidated, a comprehensive research framework for burgeoning acousto-mechanical metamaterials is proposed. Overall, our study broadens the horizon for multifunctional material design.

Abstract Currently, cocrystallization is a promising strategy for tailoring the physicochemical properties of active pharmaceutical ingredients. Theophylline, an alkaloid and the most primary metabolite of caffeine, is a readily available compound found in tea and coffee. It functions primarily as a bronchodilator and respiratory stimulant, making it a mainstay treatment for lung diseases like asthma. Theophylline’s additional potential benefits, including anti-inflammatory and anticancer properties, and its possible role in neurological disorders, have garnered significant research interest. Cocrystal formation presents a viable approach to improve the physicochemical properties of theophylline and potentially mitigate its toxic effects. This review comprehensively explores several successful studies that utilized cocrystallization to favorably alter the physicochemical properties of theophylline or its CCF. Notably, cocrystals can not only enhance the solubility and bioavailability of theophylline but also exhibit synergistic effects with other APIs. The review further delves into the hydrogen bonding sites within the theophylline structure and the hydrogen bonding networks observed in cocrystal structures. Graphical Abstract

Abstract Thermoelectrics converting heat and electricity directly attract broad attentions. To enhance the thermoelectric figure of merit, zT, one of the key points is to decouple the carrier-phonon transport. Here, we propose an entropy engineering strategy to realize the carrier-phonon decoupling in the typical SrTiO3-based perovskite thermoelectrics. By high-entropy design, the lattice thermal conductivity could be reduced nearly to the amorphous limit, 1.25 W m−1 K−1. Simultaneously, entropy engineering can tune the Ti displacement, improving the weighted mobility to 65 cm2 V−1 s−1. Such carrier-phonon decoupling behaviors enable the greatly enhanced μ W/κ L of ~5.2 × 103 cm3 K J−1 V−1. The measured maximum zT of 0.24 at 488 K and the estimated zT of ~0.8 at 1173 K in (Sr0.2Ba0.2Ca0.2Pb0.2La0.2)TiO3 film are among the best of n-type thermoelectric oxides. These results reveal that the entropy engineering may be a promising strategy to decouple the carrier-phonon transport and achieve higher zT in thermoelectrics.

Abstract Floquet engineering is a promising tool to manipulate quantum systems coherently. A well-known example is the optical Stark effect, which has been used for optical trapping of atoms and breaking time-reversal symmetry in solids. However, as a coherent nonlinear optical effect, Floquet engineering typically requires high field intensities obtained in ultrafast pulses, severely limiting its use. Here, we demonstrate using cavity engineering of the vacuum modes to achieve orders-of-magnitude enhancement of the effective Floquet field, enabling Floquet effects at an extremely low fluence of 450 photons/μm2. At higher fluences, the cavity-enhanced Floquet effects lead to 50 meV spin and valley splitting of WSe2 excitons, corresponding to an enormous time-reversal breaking, non-Maxwellian magnetic field of over 200 T. Utilizing such an optically controlled effective magnetic field, we demonstrate an ultrafast, picojoule chirality XOR gate. These results suggest that cavity-enhanced Floquet engineering may enable the creation of steady-state or quasi-equilibrium Floquet bands, strongly non-perturbative modifications of materials beyond the reach of other means, and application of Floquet engineering to a wide range of materials and applications.

Abstract WNT signaling is fundamental in development and homeostasis, but how the Frizzled receptors (FZDs) propagate signaling remains enigmatic. Here, we present the cryo-EM structure of FZD4 engaged with the DEP domain of Dishevelled 2 (DVL2), a key WNT transducer. We uncover a distinct binding mode where the DEP finger-loop inserts into the FZD4 cavity to form a hydrophobic interface. FZD4 intracellular loop 2 (ICL2) additionally anchors the complex through polar contacts. Mutagenesis validates the structural observations. The DEP interface is highly conserved in FZDs, indicating a universal mechanism by which FZDs engage with DVLs. We further reveal that DEP mimics G-protein/β-arrestin/GRK to recognize an active conformation of receptor, expanding current GPCR engagement models. Finally, we identify a distinct FZD4 dimerization interface. Our findings delineate the molecular determinants governing FZD/DVL assembly and propagation of WNT signaling, providing long-sought answers underlying WNT signal transduction.

The microstructure evolution, cyclic oxidation, and hot corrosion behavior of the unheated-treated (As-built) and solution + double aging (SDA)-treated Inconel 718 alloys fabricated through laser-induction hybrid cladding (LIHC) were investigated. It was found that the as-built Inconel 718 alloy exhibits a columnar dendritic with intergranular Laves phase. After SDA-treated, γ'', γ′, δ and carbide phases precipitated, the Laves phase became fine and dispersed. After cyclic oxidation, the Cr2O3 scales were formed on both as-built and SDA-treated LIHC-produced Inconel 718 alloy, which could provide good cyclic oxidation resistance for the Inconel 718 alloy. However, the as-built and SDA-treated LIHC-produced Inconel 718 alloy suffered severe hot corrosion in 95 wt% Na2SO4 + 5 wt% NaCl mixed salt solution and many corrosion products were generated, including Cr2O3, NiCr2O4, NaNbO3, Na2CrO4, NiFe2O4, Fe3O4, and NiO. Nevertheless, the SDA-treated sample showed better cyclic oxidation and hot corrosion resistance than the as-built sample, owing to the more compact Cr2O3 scale.

Abstract Introduction The aim of this work is to develop a deep learning (DL) system for rapidly and accurately screening for intraocular tumor (IOT), retinal detachment (RD), vitreous hemorrhage (VH), and posterior scleral staphyloma (PSS) using ocular B-scan ultrasound images. Methods Ultrasound images from five clinically confirmed categories, including vitreous hemorrhage, retinal detachment, intraocular tumor, posterior scleral staphyloma, and normal eyes, were used to develop and evaluate a fine-grained classification system (the Dual-Path Lesion Attention Network, DPLA-Net). Images were derived from five centers scanned by different sonographers and divided into training, validation, and test sets in a ratio of 7:1:2. Two senior ophthalmologists and four junior ophthalmologists were recruited to evaluate the system's performance. Results This multi-center cross-sectional study was conducted in six hospitals in China. A total of 6054 ultrasound images were collected; 4758 images were used for the training and validation of the system, and 1296 images were used as a testing set. DPLA-Net achieved a mean accuracy of 0.943 in the testing set, and the area under the curve was 0.988 for IOT, 0.997 for RD, 0.994 for PSS, 0.988 for VH, and 0.993 for normal. With the help of DPLA-Net, the accuracy of the four junior ophthalmologists improved from 0.696 (95% confidence interval [CI] 0.684–0.707) to 0.919 (95% CI 0.912–0.926, p

BackgroundQuartz dust cannot be degraded in the lungs, and inhalation of a large amount of quartz dust in the occupational production process will lead to the occurrence of pulmonary fibrosis, and then develop into silicosis. In recent years, studies have found that exosomes may be involved in the pathogenesis of fibrotic diseases by carrying microribonucleic acid (miRNA), but the mechanism of their actions in silicosis still needs to be studied. ObjectiveTo investigate the role of exosome-derived miRNA-21-5p/mothers against decapentaplegic homolog 7 (Smad7) in quartz dust-induced pulmonary fibrosis in rats. MethodsTwenty-four healthy male SD rats were randomly divided into four groups (six rats in each group): control 4-week group, control 16-week group, quartz 4-week group, and quartz 16-week group. At the beginning of the experiment, 1 mL of quartz suspension (50 mg·mL−1) and 1 mL of normal saline were injected into the trachea of rats in the quartz group and the control group, respectively, by means of one-time non-exposure intratracheal dust staining. Alveolar lavage was performed at the 4th and 16th weeks after dust staining, the exosomes in lavage solution were extracted by polyethylene glycol (PEG) precipitation, morphological identification was conducted by transmission electron microscopy (TEM), particle size of exosomes was detected by nano-tracking analysis (NTA), and the marker proteins CD9 and CD63 of exosomes were detected by Western blotting (WB). The expression of miRNA-21-5p in exosomes was determined by reverse transcription polymerase chain reaction (RT-PCR). The degree of lung tissue injury and fibrosis was observed by hematoxylin-eosin staining (HE) and Masson staining. The collagen content of lung tissue was detected by hydroxyproline (HYP) method. The expression of Smad7 protein in lung tissue was detected by WB. ResultsThe results of pathological staining showed that compared with the control group, lung inflammatory cell infiltration, alveolar wall thickening, and collagen increase were observed after 4 weeks of dusting, and collagen deposition and silicon nodules appeared after 16 weeks of dusting. Compared with the control group, the expression level of HYP in the lung tissue of the quartz group was increased after 4 weeks and 16 weeks of dust staining (P

Abstract The fracture behaviour of artificial metamaterials often leads to catastrophic failures with limited resistance to crack propagation. In contrast, natural materials such as bones and ceramics possess microstructures that give rise to spatially controllable crack path and toughened material resistance to crack advances. This study presents an approach that is inspired by nature’s strengthening mechanisms to develop a systematic design method enabling damage-programmable metamaterials with engineerable microfibers in the cells that can spatially program the micro-scale crack behaviour. Machine learning is applied to provide an effective design engine that accelerate the generation of damage-programmable cells that offer advanced toughening functionality such as crack bowing, crack deflection, and shielding seen in natural materials; and are optimised for a given programming of crack path. This paper shows that such toughening features effectively enable crack-resisting mechanisms on the basis of the crack tip interactions, crack shielding, crack bridging and synergistic combinations of these mechanisms, increasing up to 1,235% absorbed fracture energy in comparison to conventional metamaterials. The proposed approach can have broad implications in the design of damage-tolerant materials, and lightweight engineering systems where significant fracture resistances or highly programmable damages for high performances are sought after.

Abstract Direct copper-to-copper (Cu-Cu) bonding is a promising technology for advanced electronic packaging. Nanocrystalline (NC) Cu receives increasing attention due to its unique ability to promote grain growth across the bonding interface. However, achieving sufficient grain growth still requires a high thermal budget. This study explores how reducing grain size and controlling impurity concentration in NC Cu leads to substantial grain growth at low temperatures. The fabricated NC Cu has a uniform nanograin size of around 50 nm and a low impurity level of 300 ppm. To prevent ungrown NC and void formation caused by impurity aggregation, we propose a double-layer (DL) structure comprising a normal coarse-grained (CG) layer underneath the NC layer. The CG layer, with a grain size of 1 μm and an impurity level of 3 ppm, acts as a sink, facilitating impurity diffusion from the NC layer to the CG layer. Thanks to sufficient grain growth throughout the entire NC layer, cross-interface Cu-Cu bonding becomes possible under a low thermal budget, either at 100 °C for 60 min or at 200 °C for only 5 min.

Abstract Chiral assemblies have become one of the most active research areas due to their versatility, playing an increasingly important role in bio-detection, imaging and therapy. In this work, chiral UCNPs/CuxOS@ZIF nanoprobes are prepared by encapsulating upconversion nanoparticles (UCNPs) and CuxOS nanoparticles (NPs) into zeolitic imidazolate framework-8 (ZIF-8). The novel excited-state energy distribution-modulated upconversion nanostructure (NaYbF4@NaYF4: Yb, Er) is selected as the fluorescence source and energy donor for highly efficient fluorescence resonance energy transfer (FRET). CuxOS NP is employed as chiral source and energy acceptor to quench upconversion luminescence (UCL) and provide circular dichroism (CD) signal. Utilizing the natural adsorption and sorting advantages of ZIF-8, the designed nanoprobe can isolate the influence of other common disruptors, thus achieve ultra-sensitive and highly selective UCL/CD dual-mode quantification of H2S in aqueous solution and in living cells. Notably, the nanoprobe is also capable of in vivo intra-tumoral H2S tracking. Our work highlights the multifunctional properties of chiral nanocomposites in sensing and opens a new vision and idea for the preparation and application of chiral nanomaterials in biomedical and biological analysis.

Climate change is expected to increase the frequency and severity of climate extremes, which will negatively impact crop production. As one of the main food and feed crops, maize is also vulnerable to extreme climate events. In order to accurately and comprehensively assess the future climate risk to maize, it is urgent to project and evaluate the stress of extreme climate related maize production under future climate scenarios. In this study, we comprehensively evaluated the spatio-temporal changes in the frequency and intensity of six extreme climate indices (ECIs) across China’s maize harvest region by using a multi-model ensemble method, and examined the capability of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to capture these variations. We found that the Independence Weight Mean (IWM) ensemble results calculated by multiple Global Climate Models (GCMs) with bias correction could better reproduce each ECI. The results indicated that heat stress for maize showed consistent increase trends under four future climate scenarios in the 21st century. The intensity and frequency of the three extreme temperature indices in 2080s were significantly higher than these in 2040s, and in the high emission scenario were significantly higher than these in the low emission scenario. The three extreme precipitation indices changed slightly in the future, but the spatial changes were more significant. Therefore, with the uncertainty of climate change and the differences of climate characteristics in different regions, the optimization of specific management measures should be considered in combination with the specific conditions of future local climate change.

Mycoviruses can alter the biological characteristics of host fungi, including change virulence or pathogenicity of phytopathogens and entomopathogenic fungi (EPF). However, most studies on the mycoviruses found in EPF have focused on the effects of the viruses on the virulence of host fungi towards insect pests, with relatively few reports on the effects to the host fungi with regard to plant disease resistance in hosts. The present study investigated the effects of the mycovirus Beauveria bassiana chrysovirus 2 (BbCV2) virus infection on host biological characteristics, evaluated antagonistic activity of BbCV2 against two phytopathogenic fungi (Sclerotinia sclerotiorum and Botrytis cinerea), and transcriptome analysis was used to reveal the interactions between viruses and hosts. Our results showed that BbCV2 virus infection increased B. bassiana‘s growth rate, spore production, and biomass, it also enhanced the capacity of host fungi and their metabolic products to inhibit phytopathogenic fungi. BbCV2 virus infection reduced the contents of the two pathogens in tomato plants significantly, and transcriptome analysis revealed that the genes related to competition for ecological niches and nutrition, mycoparasitism and secondary metabolites in B. bassiana were significantly up-regulated after viral infection. These findings indicated that the mycovirus infection is an important factor to enhance the ability of B. bassiana against plant disease after endophytic colonization. We suggest that mycovirus infection causes a positive effect on B. bassiana against phytopathogens, which should be considered as a potential strategy to promote the plant disease resistance of EPF.

Abstract The use of solar energy to produce hydrogen has been one of the research hotspots in recent years. With the continuous exploitation of solar hydrogen evolution, the performance of photo(electro)catalysts has been greatly optimized. However, the solar‐driven hydrogen production for most semiconductors, especially for organic semiconductors, is limited due to the lack of active centers and serious electron–hole recombination. Recently, it has been reported that carbon‐carbon triple bonds (C≡C) can function as active sites for hydrogen evolution, and diacetylenic moiety in organic semiconductors is able to increase carrier migration as well. Therefore, organic semiconductors containing C≡C have attracted considerable attention in the past few years. In this review, organic materials or organic–inorganic hybrids containing C≡C for photo(electro)catalytic solar hydrogen production are classified first, including graphdiyne, conjugated acetylene polymers, some covalent organic frameworks, and metal–organic frameworks. After that, the structure, properties, and advantages and disadvantages of C≡C‐containing materials are introduced and summarized. Apart from these, this review also presents advances in materials containing C≡C in the field of solar hydrogen generation. Finally, perspectives on the future development of C≡C‐containing materials in the field of solar hydrogen generation are also briefly anticipated. This review provides pertinent insights into the main challenges and potential advances in the organic semiconductors for solar‐driven hydrogen production, which will also greatly contribute to other photo(electro)catalytic reactions.

ABSTRACT Candida glabrata is an important and increasingly common pathogen of humans, particularly in immunocompromised hosts. Despite this, little is known about how this fungus causes disease. Here, we applied RNA sequencing and an in vivo invasive infection model to identify the attributes that allow this organism to infect hosts. Fungal transcriptomes show a dramatic increase in the expression of Fus3 and Kss1, two mitogen-activated protein kinases (MAPKs), during invasive infection. We further demonstrate that they are both highly induced under a combination of serum and high CO2 conditions. Deletion of both FUS3 and KSS1, but neither gene alone, results in a reduced fungal burden in organs, as well as in the gastrointestinal tract in the DSS (Dextran Sulfate Sodium)-induced colitis model. Similarly, the defect in persistence in macrophages and attenuated adhesion to epithelial cells are observed when FUS3 and KSS1 are both disrupted. The fus3 kss1 double mutant also displays defects in the induction of virulence attributes such as genes required for iron acquisition and adhesion and in the anti-fungal drug tolerance. The putative downstream transcription factors Ste12 (1), Ste12 (2), Tec1, and Tec2 are found to be involved in the regulation of these virulence attributes. Collectively, our study indicates that an evolutionary conserved MAPK pathway, which regulates mating and filamentous growth in Saccharomyces cerevisiae, is critical for C. glabrata pathogenicity.IMPORTANCEThe MAPK signaling pathway, mediated by closely related kinases Fus3 and Kss1, is crucial for controlling mating and filamentous growth in Saccharomyces cerevisiae, but this pathway does not significantly impact hyphal development and pathogenicity in Candida albicans, a commensal-pathogenic fungus of humans. Furthermore, deletion of Cpk1, the ortholog of Fus3 in pathogenic fungus Cryptococcus neoformans, has no effect on virulence. Here, we demonstrate that the MAPK pathway is crucial for the pathogenicity of Candida glabrata, a fungus that causes approximately one-third of cases of hematogenously disseminated candidiasis in the United States. This pathway regulates multiple virulence attributes including the induction of iron acquisition genes and adhesins, as well as persistence in macrophages and organs. Our work provides insights into C. glabrata pathogenesis and highlights an example in which regulatory rewiring of a conserved pathway confers a virulent phenotype in a pathogen.

BackgroundThe CIAO trial recently demonstrated a probable clinical benefit of omalizumab in the treatment of severe COVID-19; however, the mechanism underlying this benefit remains unclear. Therefore, we sought to longitudinally assess the impact of omalizumab on serum cytokines in CIAO trial patients to determine its mechanism of action.MethodsBlood samples were collected on days 0, 2, 7, and 14 from patients recruited into the CIAO trial and who consented to this substudy. Blood samples were tested by a panel of 25 inflammatory cytokines, as well as for markers of mast cell activation. Levels of inflammatory biomarkers were compared over time between omalizumab- and placebo-treated patients by generalized linear mixed-effects model. Associations between biomarkers and clinical outcomes were investigated by mixed-effects logistic regression.ResultsNineteen patients were recruited into this substudy; 10 were assigned to placebo and 9 to omalizumab. Monokine induced by gamma interferon was significantly positively associated with severe COVID-19 (Odds Ratio [OR] = 1.06, 95%CI = 1.00–1.11, p = 0.043). Further, omalizumab significantly reduced interleukin-15 (Coefficient = −0.95, p = 0.048) and macrophage inflammatory protein-1 (Coefficient = −1.31, p = 0.010) levels. However, neither was significant in analyses adjusting for multiple hypothesis testing.ConclusionAlthough limited by a small sample size, these results suggest that omalizumab’s potential benefit in COVID-19 may be mediated independently of modulation of the measured serum biomarkers. Further studies are needed to investigate omalizumab’s mechanism of action in COVID-19.

Background: Increased job stress and burnout are common among clinical nurses in China, reducing their work efficiency and nursing quality. Multiple studies have been conducted on brief interventions to reduce job stress and burnout among nurses. However, research has been hampered by a lack of psychological knowledge among nursing staff. Aim: To assess a solution-focused brief therapy for enhancing nurses' coping styles and mitigating job stress and burnout based on interdisciplinary cooperation. Design: This randomised controlled trial. Settings: We randomly allocated 60 nurses working at a tertiary general hospital in a city in China to an experimental (n = 30) or a control group (n = 30). Methods: A collaborative research team comprising psychology and nursing specialists was established to conduct this study. The control group received routine psychological intervention, whereas the intervention group received a solution-focused brief therapy based on interdisciplinary cooperation. Chinese nurses’ job stressors, Maslach Burnout Inventory, and simplified coping style questionnaire were used to evaluate both groups before and after the intervention. Results: A comparison of the scores for job burnout, total job stress, and positive coping before and after the interventions revealed significant improvements in the experimental group, whereas the scores for emotional exhaustion, depersonalisation, and total job stress in the control group demonstrated statistically significant differences. No significant differences were observed in the scores for negative coping, personal accomplishment, and coping style between the test and control groups before and after the intervention. Conclusions: Solution-focused brief therapy implemented through interdisciplinary collaboration effectively enhances clinical nurses' active coping style, alleviates job stress and burnout, and offers valuable guidance for nursing management practices.

BackgroundThalassemia is a inherited monogenic blood disorder and more prevalent in southern China. In this study, Our aim was to elucidate the molecular spectrum and phenotypic features of thalassemia in pregnant women in Changsha County.MethodsNext-generation sequencing (NGS) was conducted for 38,810 pregnant women to diagnose thalassemia in Changsha County. Further analysis of hematological parameters was conducted on subjects who had not previously undergone thalassemia screening in other hospitals.ResultsIn this study, 2,208 (5.69%) pregnant women were diagnosed as carriers of thalassemia using NGS analysis. Among 1,594 cases of α-thalassemia, 23 genotypes were identified, and among 578 cases of β-thalassemia, 22 genotypes were detected. Additionally, 18 genotypes were detected among 36 cases of composite α- and β-thalassemia. Among all carriers of thalassemia, 8 rare α-mutations and 11 rare β-mutations were found in the study population. Notably, pregnant women diagnosed as carriers of thalassemia tended to have lower hemoglobin levels. Furthermore, multivariable logistic regression analysis indicates that the values of MCV and MCH have the greatest impact on genetic diagnosis.ConclusionOur study has provided detailed genotypes and hematological parameters of thalassemia in pregnant women in Changsha county and reveal that certain abnormal blood parameters have a remarkably impact on genetic diagnosis results. Furthermore, our data suggest that combining hemoglobin electrophoresis and NGS provides a powerful tool for prenatal diagnosis, which will increase the accuracy of clinical diagnosis of thalassemia.

Abstract As 5G and early‐stage network technologies mature, a wealth of data and experience is accumulated. The ubiquitous sensing and communication network (USCN) can leverage these existing communication infrastructures to maximize resource utilization and reduce the costs of redeployment through integration with modern 6G and beyond 6G networks. However, implementing future integrated sensing and communication (ISAC) functions in USCN may possess different hardware capabilities and communication protocols, presenting significant challenges. This is due to the lack of a unified framework for managing and optimizing these heterogeneous resources, as well as the absence of reasonable performance metrics. This letter proposes a dynamic pricing coordinated resource allocation (DPCRA) mechanism to realize the emerging ISAC in legacy USCNs. The DPCRA is designed to optimize the spectrum efficiency (SE) of USCN and manages resource interactions between heterogeneous devices through price variables, thereby resolving resource conflicts and deadlocks. The novelties include: (1) employing a price mechanism to foster resource cooperation in non‐cooperative networks; (2) introducing an SE metric incorporating an information similarity factor for optimization; (3) dynamically selecting resources to enhance SE. Simulations demonstrate that the DPCRA effectively resolves device deadlock while maintaining high SE levels, promoting device collaboration.

Objective: The objective of this study is to develop and validate an effective prognostic nomogram for predicting the short-term survival rate of patients with acute heart failure (AHF) complicated by acute kidney injury (AKI) who are admitted to the intensive care unit (ICU). Patients and methods: We conducted an analysis of data from patients of AHF with AKI spanning the period from 2008 to 2019, utilizing the MIMIC-IV database. Patients were randomly divided into training and validation sets. The training set employed the least absolute shrinkage and selection operator regression model to identify predictors of AKI. Subsequently, a dynamic nomogram was constructed using multivariate Cox regression analysis within the training set and was subsequently validated using the validation set. The nomogram's predictive accuracy, calibration, and clinical utility were evaluated through the concordance index (C-index), calibration plots, and decision curve analysis (DCA). Results: A total of 978 AHF patients with AKI were analyzed. Multivariate analysis identified serum creatinine, race, age, use of human albumin, use of vasoactive drug, and hemoglobin as independent predictors significantly influencing the short-term prognosis of AHF patients with AKI upon ICU admission. The C-index for the training and validation sets were 0.81 (95%CI: 0.74–0.87) and 0.80 (95 % CI: 0.67–0.92), respectively. The calibration plot of the nomogram demonstrated a close alignment between predicted and observed probabilities. Furthermore, the DCA confirmed the clinical utility of the nomogram. Conclusions: This study presents a dynamic nomogram that incorporates clinical risk factors and can be conveniently utilized to predict short-term prognosis for AHF patients with AKI upon ICU admission.

The dense structure of solid tumor tissues and the selective permeability of cell membranes impede the effective penetration of chemotherapeutic agent-loaded liposomes into tumors and their subsequent uptake by cells. Dermaseptin-PP, a cationic antimicrobial peptide, has demonstrated the ability to enhance the penetration and accumulation of drugs within solid tumors due to its unique membrane-breaking action. Based on this, we designed glutathione (GSH)-sensitive paclitaxel liposomes modified with Dermaseptin-PP. Dermaseptin-PP was modified through disulfide bonding, which could be broken at the tumor site due to high GSH levels. This cleavage resulted in the release of Dermaseptin-PP, thereby enhancing the permeability of the paclitaxel liposomes within the tumor. We found that the paclitaxel liposomes modified with Dermaseptin-PP were extensively distributed to the tumor site, and the Dermaseptin-PP modification significantly enhanced liposome penetration within the tumor. Our study significantly increased the anti-tumor efficacy of paclitaxel liposomes. Our study confirms that paclitaxel liposomes modified with Dermaseptin-PP is an effective anti-tumor therapy that enhances deep penetration into tumors. Additionally, this broadens the applications of cationic antimicrobial peptides.

Costly third-party punishment (TPP) is an effective way to enforce fairness norms and promote cooperation. Recent studies have shown that the third party considers not only the proposer’s suggested allocation but also the receiver’s response to the allocation, which was typically ignored in traditional TPP studies when making punishment decisions. However, it remains unclear whether and how the varying unfair allocations and receivers’ responses are integrated into third-party punishment. The current study addressed these issues at behavioral and electrophysiological levels by employing a modified third-party punishment task involving proposers’ highly or moderately unfair allocations and the receivers’ acceptance or rejection responses. At the behavioral level, participants punished proposers more often when receivers rejected relative to accepted unfair allocations. This effect was further modulated by the unfairness degree of allocations, indicated by a more pronounced rejection-sensitive effect when participants observed the moderately unfair offers. Electrophysiologically, when the receiver rejected the moderately unfair allocations, a stronger late-stage component P300/LPP, which was considered to be involved in allocations of attention resources, was found. Meanwhile, separated from the P300/LPP, the P200 associated with early attention capture demonstrated a rejection-sensitive effect. Together, in the costly TPP studies, the receiver is typically designated as passive and silent, and her/his responses to unfairness are conventionally ignored. However, our results indicate that except for the proposer’s distribution behavior, the receiver’s response does have an impact on third-party punishment in a way that interacts with the unfairness of allocations.

Chemically protected sodium butyrate (CSB) is a novel form of sodium butyrate. This study aimed to investigate the effect of CSB supplementation on the gut mucosal immune, gut microbiota, and SCFAs in piglets. Results showed that supplementation with 2000 mg/kg (high CSB, HCSB) improved the average daily gain by 18.5 %, while supplementation with 1000 mg/kg (low CSB, LCSB) improved it by 6.9 %. qPCR results indicated HCSB treatment dramatically upregulated the mRNA expression levels of IL-10 by 47.1 %, CAT by 17.4 %, SOD1 by 48.2 %, and Claudin-1 by 50 %. Additionally, the SCFAs-producing bacteria Parabacteroides and Eubacterium coprostanoligenes were increased by HCSB supplementation. The levels of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid were significantly enhanced in the jejunal, duodenal, cecal, and colonic chyme of piglets by HCSB supplementation. Collectively, CSB supplementation improves anti-inflammatory and antioxidant capacities potentially through modulating gut microbiota and SCFAs in piglets.

Introduction. As nanotechnology continues to evolve and its industrial applications expand, the need for effective data management, analysis, and dissemination is becoming more urgent. Management analytics has emerged as a critical new interdisciplinary field in current business environments, enabling organizations to leverage data-driven insights for informed decision-making and strategic planning. Methods and materials. This study reviews and analyzes research in the interdisciplinary field of management analytics for the period from 2021 to 2023. To conduct bibliometric analysis, data from various sources were used, including academic publications, monographs, reviews, reports, etc. Through a systematic review of the relevant literature, this study aims to provide insight into key topics, methodologies and outcomes in the field of management analytics, as well as to identify directions for future research directions. Results: according to the results of the analysis, it was found that the main source of articles in this area is the Journal of Management Analytics. The total number of publications on this topic for the period amounted to 83 units, the total number of citations for a certain time period has been increasing. The leading countries in terms of the number of citations of academic articles on the topic under study are the United States, India and China. Discussion. So far, the interdisciplinary field of management analytics has not been widely discussed in academic circles. However, leading countries in the world in terms of the number of academic articles and citations are at the forefront of this emerging field. This should be taken into account especially in the development of the nanosystems and nanomaterials industry, which is one of the priority areas for the development of science and technology, where management analytics technologies will be in demand and can provide competitive advantages to companies. Conclusion. The importance of the new interdisciplinary field of management analytics will continue to grow. In the course of the study, it was found that this emerging field has been increasing its popularity and it could be an effective tool for organizations in the nearest fu-ture.

Fiber is highly escapable in conventional slickwater, making it difficult to form fiber-proppant agglomerate with proppant and exhibit limited effectiveness. To solve these problems, a novel structure stabilizer (SS) is developed. Through microscopic structural observations and performance evaluations in indoor experiments, the mechanism of proppant placement under the action of the SS and the effects of the SS on proppant placement dimensions and fracture conductivity were elucidated. The SS facilitates the formation of robust fiber-proppant agglomerates by polymer, fiber, and quartz sand. Compared to bare proppants, these agglomerates exhibit reduced density, increased volume, and enlarged contact area with the fluid during settlement, leading to heightened buoyancy and drag forces, ultimately resulting in slower settling velocities and enhanced transportability into deeper regions of the fracture. Co-injecting the fiber and the SS alongside the proppant into the reservoir effectively reduces the fiber escape rate, increases the proppant volume in the slickwater, and boosts the proppant placement height, conveyance distance and fracture conductivity, while also decreasing the proppant backflow. Experimental results indicate an optimal SS mass fraction of 0.3%. The application of this SS in over 80 wells targeting tight gas, shale oil, and shale gas reservoirs has substantiated its strong adaptability and general suitability for meeting the production enhancement, cost reduction, and sand control requirements of such wells.

Abstract Aims To test the association of C-reactive protein (CRP) with all-cause and cause-specific mortality in people with gout. Methods This cohort study included 502 participants with gout from the National Health and Nutrition Examination Survey. Multivariate Cox regression analysis, subgroup analysis, and restricted cubic spline (RCS) analyses were utilized to examine the association of CRP levels with all-cause, cardiovascular, and cancer mortality. Results After adjusting for multiple variables, Cox regression analysis showed that compared with individuals in the lowest tertile of CRP levels, those in the middle and highest tertiles experienced increases in all-cause mortality risk of 74.2% and 149.7%, respectively. Similarly, the cancer mortality risk for individuals in the highest tertile of CRP levels increased by 283.9%. In addition, for each standard deviation increase in CRP, the risks of all-cause and cancer mortality increased by 25.9% and 35.4%, respectively (P 60 years), gender (male), presence or absence of hypertension, non-diabetes, cardiovascular disease, non-cardiovascular disease and non-cancer. Furthermore, the association with cancer mortality was significant in subgroups including males, those without hypertension and cancer, and those with or without diabetes. However, the association with cardiovascular mortality was only significant in the non-hypertension subgroup (P

[ Objective ] The front piedmont belt of the northern slope of the Tianshan Mountains in Xinjiang is a crucial component of the mountain-oasis-desert ecosystem of the Tianshan northern slope. Investiga- ting the dynamic physiological adaptations of plants to drought stress and assessing methods for drought resistance , as well as selecting suitable tree species for vegetation restoration holds significant importance for the ecological restoration in this region. [ Methods ] 12 plant species planted in the piedmont belt of the northern slope of the Tianshan Mountains in Xinjiang were selected as the subjects. The study observed the spatiotemporal distribution of soil moisture following irrigation and analyzed the impact of drought stress and rewatering treatment on plant photosynthetic and physiological indicators. The drought resist- ance of these 12 species was evaluated using principal component analysis. [ Results ] ( 1 ) Following drought stress , soil moisture depletion occurred most rapidly in the 0-20 cm layer , followed by the 20- 40 cm layer , and was slowest in the 40-60 cm layer. Different plants employed different strategies to adapt their growth to drought stress. ( 2 ) Following drought stress , net photosynthetic rate ( P n ), stoma- tal conductance ( G s ), transpiration rate ( T r ), intercellular CO 2 concentration ( C i ), potential activity of PSⅡ ( F v / F o ), maximum photochemical efficiency of PSⅡ ( F v / F m ), electron transport rate ( ETR ), and chlorophyll content were decreased , while the activity of superoxide dismutase ( SOD ), proline content , malondialdehyde ( MDA ) content , and non-photochemical quenching coefficient ( q N ) were increased. Af- ter rehydration , there was a certain degree of recovery in each parameter , but none of them reached the in- itial levels. ( 3 ) The results of principal component analysis highlighted that factors like P n , chlorophyll content , ETR , and MDA content were major contributors. Species such as Haloxylon ammodendron , Tamarix chinensis , Rosa acicularis , and Caragana korshinskii demonstrated significant drought resili- ence. Hippophae rhamnoides , H . rhamnoides ‘ Xinji 5 ’, H . rhamnoides ‘ Xinji 1 ’, and Prunus sibirica showed moderate levels of drought resistance , while H . rhamnoides ‘ Xinji 4 ’, H . rhamnoides ‘ Xinji 3 ’, Xanthoceras sorbifolium , and H . rhamnoides ‘ Xinji 2 ’ exhibited relatively lower drought tolerance. [ Conclusion ] P n , chlorophyll content , ETR , and MDA content were crucial indicators for evaluating the adaptability of various plant species to drought stress. In the context of ecological restoration efforts in the piedmont belt of the Tianshan Mountains􀆴 northern slope in Xinjiang , prioritizing the cultivation of H . ammodendron , T . chinensis , R . acicularis , and C . korshinskii were recommended.

Abstract Inorganic semiconductors typically have limited p-type behavior due to the scarcity of holes and the localized valence band maximum, hindering the progress of complementary devices and circuits. In this work, we propose an inorganic blending strategy to activate the hole-transporting character in an inorganic semiconductor compound, namely tellurium-selenium-oxygen (TeSeO). By rationally combining intrinsic p-type semimetal, semiconductor, and wide-bandgap semiconductor into a single compound, the TeSeO system displays tunable bandgaps ranging from 0.7 to 2.2 eV. Wafer-scale ultrathin TeSeO films, which can be deposited at room temperature, display high hole field-effect mobility of 48.5 cm2/(Vs) and robust hole transport properties, facilitated by Te-Te (Se) portions and O-Te-O portions, respectively. The nanosphere lithography process is employed to create nanopatterned honeycomb TeSeO broadband photodetectors, demonstrating a high responsibility of 603 A/W, an ultrafast response of 5 μs, and superior mechanical flexibility. The p-type TeSeO system is highly adaptable, scalable, and reliable, which can address emerging technological needs that current semiconductor solutions may not fulfill.

Abstract Monolayer two-dimensional (2D) materials possess excellent in-plane mechanical strength yet extremely low bending stiffness, making them particularly susceptible to instability, which is anticipated to have a substantial impact on their physical functionalities such as 2D-based Micro/Nanoelectromechanical systems (M/NEMS), nanochannels, and proton transport membrane. In this work, we achieve quantitatively tuning instability in suspended 2D materials including monolayer graphene and MoS2 by employing a push-to-shear strategy. We comprehensively examine the dynamic wrinkling-splitting-smoothing process and find that monolayer 2D materials experience stepwise instabilities along with different recovery processes. These stepwise instabilities are governed by the materials’ geometry, pretension, and the elastic nonlinearity. We attribute the different instability and recovery paths to the local stress redistribution in monolayer 2D materials. The tunable instability behavior of suspended monolayer 2D materials not only allows measuring their bending stiffness but also opens up new opportunities for programming the nanoscale instability pattern and even physical properties of atomically thin films.

Abstract Background Cleidocranial dysplasia (CCD) is an autosomal dominant hereditary disorder. Besides skeletal abnormalities, CCD is often associated with dental complications, such as multiple supernumerary teeth and permanent teeth impaction or delayed eruption. Methods Supernumerary teeth of axial, sagittal and coronal CBCT view was characterized in detail and 3D image reconstruction was performed. Number and location of teeth, morphology of supernumerary teeth, positional relationship between supernumerary and adjacent permanent teeth, direction of supernumerary teeth in CCD patients were analyzed. Results The mean age of the 3 CCD patients in this study was 16.7 years. Among 36 supernumerary teeth, the majority of them were identified as apical side located and lingual side located. Normal orientation was the most common type in this study, followed by sagittal orientation, and horizontal orientation. Horizontal orientation teeth were all distributed in the mandible. Supernumerary teeth exhibited significantly shorter crown and dental-root lengths, as well as smaller crown mesiodistal and buccolingual diameters (P

Abstract Patients who suffer from myofascial orofacial pain could affect their quality of life deeply. The pathogenesis of pain is still unclear. Our objective was to assess Whether Voltage-gated calcium channel α2δ-1(Cavα2δ-1) is related to myofascial orofacial pain. Rats were divided into the masseter tendon ligation group and the sham group. Compared with the sham group, the mechanical pain threshold of the masseter tendon ligation group was reduced on the 4th, 7th, 10th and 14th day after operation(P

Abstract Background Myocarditis refers to an autoimmune inflammatory response of the myocardium with characterization of self-reactive CD4+ T cell activation, which lacks effective treatment and has a poor prognosis. Acacetin is a natural flavonoid product that has been reported to have anti-inflammatory effects. However, acacetin has not been investigated in myocarditis. Methods Oral acacetin treatment was administered in an experimental autoimmune myocarditis model established with myosin heavy chain-alpha peptide. Echocardiography, pathological staining, and RT-qPCR were used to detect cardiac function, myocardial injury, and inflammation levels. Flow cytometry was utilized to detect the effect of acacetin on CD4+ T cell function. RNA-seq, molecular docking, and microscale thermophoresis (MST) were employed to investigate potential mechanisms. Seahorse analysis, mitoSOX, JC-1, and mitotracker were utilized to detect the effect of acacetin on mitochondrial function. Results Acacetin attenuated cardiac injury and fibrosis as well as heart dysfunction, and reduced cardiac inflammatory cytokines and ratio of effector CD4+ T and Th17 cells. Acacetin inhibited CD4+ T cell activation, proliferation, and Th17 cell differentiation. Mechanistically, the effects of acacetin were related to reducing mitochondrial complex II activity thereby inhibiting mitochondrial respiration and mitochondrial reactive oxygen species in CD4+ T cells. Conclusion Acacetin may be a valuable therapeutic drug in treating CD4+ T cell-mediated myocarditis. Graphical Abstract

Abstract Background Traditional method of wood species identification involves the use of hand lens by wood anatomists, which is a time-consuming method that usually identifies only at the genetic level. Computer vision method can achieve "species" level identification but cannot provide an explanation on what features are used for the identification. Thus, in this study, we used computer vision methods coupled with deep learning to reveal interspecific differences between closely related tree species. Result A total of 850 images were collected from the cross and tangential sections of 15 wood species. These images were used to construct a deep-learning model to discriminate wood species, and a classification accuracy of 99.3% was obtained. The key features between species in machine identification were targeted by feature visualization methods, mainly the axial parenchyma arrangements and vessel in cross section and the wood ray in tangential section. Moreover, the degree of importance of the vessels of different tree species in the cross-section images was determined by the manual feature labeling method. The results showed that vessels play an important role in the identification of Dalbergia, Pterocarpus, Swartzia, Carapa, and Cedrela, but exhibited limited resolutions on discriminating Swietenia species. Conclusion The research results provide a computer-assisted tool for identifying endangered tree species in laboratory scenarios, which can be used to combat illegal logging and related trade and contribute to the implementation of CITES convention and the conservation of global biodiversity.

Abstract Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.47%. The heterogeneity analysis suggests that the impact of DIF on the reduction of carbon emissions is more pronounced in large and medium-sized cities and eastern regions. Further discussion reveals that the carbon reduction effect of DIF is also influenced by green technological innovation and industrial structure upgrading, showing threshold effects with marginal decreases and gradual increases, respectively.

Abstract While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Abstract Ferroptosis, an iron-dependent form of programmed cell death, is a promising strategy for cancer treatment. Bromodomain-containing protein 4 (BRD4) is an epigenetic reader and a promising target for cancer therapeutics. However, the role of BRD4 in ferroptosis is controversial and the value of the interaction between BRD4 inhibitors and ferroptosis inducers remains to be explored. Here, we found that BRD4 inhibition greatly enhanced erastin-induced ferroptosis in different types of cells, including HEK293T, HeLa, HepG2, RKO, and PC3 cell lines. Knocking down BRD4 in HEK293T and HeLa cells also promoted erastin-induced cell death. BRD4 inhibition by JQ-1 and I-BET-762 or BRD4 knockdown resulted in substantial accumulation of reactive oxygen species (ROS) in both HEK293T and HeLa cells. The effect of BRD4 inhibition on ferroptosis-associated genes varied in different cells. After using BRD4 inhibitors, the expression of FTH1, Nrf2, and GPX4 increased in HEK293T cells, while the levels of VDAC2, VDAC3, and FSP1 decreased. In HeLa cells, the expression of FTH1, VDAC2, VDAC3, Nrf2, GPX4, and FSP1 was reduced upon treatment with JQ-1 and I-BET-762. Consistently, the level of FSP1 was greatly reduced in HEK293T and HeLa cells with stable BRD4 knockdown compared to control cells. Furthermore, ChIP-sequencing data showed that BRD4 bound to the promoter of FSP1, but the BRD4 binding was greatly reduced upon JQ-1 treatment. Our results suggest that ROS accumulation and FSP1 downregulation are common mechanisms underlying increased ferroptosis with BRD4 inhibitors. Thus, BRD4 inhibitors might be more effective in combination with ferroptosis inducers, especially in FSP1-dependent cancer cells.

To analyze the speciation distribution of arsenic in agaric, shiitake mushroom, matsutake and agrocybe, the ion chromatography-inductive coupled plasma mass spectrometer (IC-ICP-MS) was used to determine arsenobetaine, dimethyl arsenic, arsenous acid, arsenic choline, monomethyl arsenic and arsenic acid, and the methodological investigation and content determination were carried out. The results showed that the method could completely separate all six arsenic forms within 5 minutes, and the peak patterns were good. The linear relationship of the method was good (mass concentration of 0.5~20 μg/L, r>0.999). The detection limit and quantification limit of six arsenic species were not more than 0.005 and 0.017 mg/kg respectively. The recovery rate of six arsenic forms in agaric, agrocybe and shiitake mushroom could reach 80%~120% with standard addition. For matsutake, the standard addition recovery rate could also reach 80%~120% when adding right standard amounts (0.05 mg/kg dimethyl arsenic, arsenic choline and arsenic acid; 0.2 mg/kg arsenite and monomethyl arsenic; 5 mg/kg arsenic betaine). Combined with the dehydration rate of dry products, the inorganic arsenic content of the tested samples met the requirements of GB 2762-2022. The content of total arsenic in matsutake was the highest, but the proportion of inorganic arsenic（arsenic choline+arsenic acid） in total arsenic was the lowest 3.6%~6.8%, and the highest proportion was arsenobetaine (75.8%~87.3%). The main form of arsenic in agaric, agrocybe, and shiitake mushroom were inorganic arsenic. The proportion of inorganic arsenic to total arsenic could reach 58.4%~66.1%、60.0%~66.7%、81.2%~91.7%, respectively. There was a risk of food safety when the total arsenic content was high.

The aurora arc is a separate auroral structure from the aurora oval, whose location and morphology are related to various solar-terrestrial circumstances. However, because of the low occurring frequency of aurora arc and the lack of the automatic identification technique, it can only be manually distinguished from a huge number of observed images, which is very inefficient. In order to improve the identification efficiency, we propose an identification algorithm based on YOLOX network and Convolutional Block Attention Module attention mechanism. Using the aurora images observed by Special Sensor Ultraviolet Spectrographic Imager carried by the Defense Meteorological Satellite Program F16-F19 satellites from 2013 to 2019, the automatic detection models for global and local areas were trained separately. The identification outputs will be integrated by calculating the intersection. According to the test results, the event identification precision is 86% and the position identification precision is 79%, both of which are greater than the results before integration. Therefore, the proposed method is not only able to identify whether the image contains the aurora arcs, but also accurately locate them, making it a highly effective tool for the advancement of future study.

Summary: Anoikis resistance allows cancer cells to avoid death caused by detachment from the extracellular matrix’s adhesion, enabling these cells to infiltrate and migrate to regions such as the peritoneum. This study emphasizes GRP94’s involvement in anoikis resistance and peritoneal metastasis in gastric cancer (GC). It’s found that GRP94 overexpression, linked to poor prognosis, was potentially due to SP1 and GRP94 promoter interactions, confirmed through dual luciferase reporter (DLR), chromatin immunoprecipitation (ChIP), and quantitative real-time PCR (real-time qPCR). Increased GRP94 enhanced GC cells’ anoikis resistance and metastasis. Decreasing GRP94 had opposite effects, potentially through yes-associated protein (YAP)/TEAD1 axis inhibition, with raised YAP phosphorylation and decreased TEAD1 levels detected by western blotting (WB). Inhibiting YAP counteracted GRP94’s effects on anoikis resistance and metastasis, while activating YAP reversed the effects of GRP94 reduction. Animal experiments verified GRP94’s contribution to GC’s peritoneal metastasis. In conclusion, our work highlights the effect of GRP94 on anoikis resistance, showing potential value in treating peritoneal metastasis of GC.

Ethane, the second most abundant gaseous hydrocarbon in vast anoxic environments, is an overlooked greenhouse gas. Microbial anaerobic oxidation of ethane can be driven by available electron acceptors such as sulfate and nitrate. However, despite nitrite being a more thermodynamically feasible electron acceptor than sulfate or nitrate, little is known about nitrite-driven anaerobic ethane oxidation. In this study, a microbial culture capable of nitrite-driven anaerobic ethane oxidation was enriched through the long-term operation of a nitrite-and-ethane-fed bioreactor. During continuous operation, the nitrite removal rate and the theoretical ethane oxidation rate remained stable at approximately 25.0 mg NO2–N L−1 d−1 and 11.48 mg C2H6 L−1 d−1, respectively. Batch tests demonstrated that ethane is essential for nitrite removal in this microbial culture. Metabolic function analysis revealed that a species affiliated with a novel genus within the family Rhodocyclaceae, designated as 'Candidatus Alkanivoras nitrosoreducens', may perform the nitrite-driven anaerobic ethane oxidation. In the proposed metabolic model, despite the absence of known genes for ethane conversion to ethyl-succinate and succinate-CoA ligase, 'Ca. A. nitrosoreducens' encodes a prospective fumarate addition pathway for anaerobic ethane oxidation and a complete denitrification pathway for nitrite reduction to nitrogen. These findings advance our understanding of nitrite-driven anaerobic ethane oxidation, highlighting the previously overlooked impact of anaerobic ethane oxidation in natural ecosystems.

Leptin has been widely studied and found to have a significant impact on the development of osteoarthritis (OA). However, there are conflicting findings regarding the impact of leptin on chondrocytes. The study aimed to examine the impact of leptin on human chondrocytes and rats with OA. In the in vitro experiment, cartilage tissue obtained from patients hospitalized for knee replacement due to OA was collected for primary culture of chondrocytes. The proliferation and apoptosis of chondrocytes were assessed using cell counting kit-8 and flow cytometry. Autophagy levels were evaluated through monodansylcadaverine staining, mRFP-GFP-LC3 fluorescence, and transmission electron microscopy. Additionally, the expression of autophagy-related genes and proteins was analyzed using qRT-PCR and western blotting. In the in vivo experiment, an OA rat model was established. Following treatment with leptin and leptin antagonists, the cartilage tissues were examined using histology analysis (hematoxylin-eosin and Safranin O/fast green staining) and immunohistochemical. Mankin's score was utilized to assess the severity of OA, while qRT-PCR and western blotting were employed to detect the expression of autophagy-related genes and proteins in the cartilage. The ability of leptin to protect chondrocytes is achieved through the inhibition of autophagy via phosphoinositide 3 kinase/protein kinase B/mammalian target of rapamycin signaling pathway.

Objective: To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-associated nuclear antigen Ki-67 value ≥ 15% in T 2 N X M 0 stage primary breast cancer (BC). Method: Data were collected from 228 randomly selected BC patients who received ultrasound screening and postoperative pathologic assessment from April 2015 to September 2018. The patients were classified into the study group (n = 80) and control group (n = 148), and the data were apportioned into the training set and test set at a 7:3 ratio based on time intervals. In the training set, crucial factors were identified from clinical features and grayscale and delta-radiomic features within ultrasound images, by using the chi-square test, t-test, and rank-sum test. The clinical model, imaging model, and combined model were built using multivariate logistic regression, respectively. The model's predictive performance and clinical net benefit were assessed using DeLong's method and decision curve analysis. Meanwhile, an XGBoost algorithm is used to establish a prediction model to verify the above results. Results: The crucial factors affecting Ki-67 value ≥ 15% included BMI, lymph node metastases, BC volume, CA153, pathology type, tumor boundaries, tumor morphology, elastography score, and delta-radscore. The predictive performance of the combined model [AUC 0.857, OR 0.0290, 95% CI 0.793-0.908] was considerably improved on the training set than the clinical model [AUC 0.724, OR 0.0422, 95% CI 0.648-0.792] and the imaging model [AUC 0.798, OR 0.0355, 95% CI 0.727-0.857]. The decision curve analysis also confirmed that the combined model delivered a higher clinical net benefit, and the verification on the test set yielded similar results. The nomogram and the calibration curve plotted based on the combined model achieved satisfactory clinical effects. The SHAP value of the XGBoost algorithm also confirmed that lymph node metastasis, BC volume, elastography score, and delta-radscore are the best independent factors for predicting BC Ki-67 value ≥ 15%. Conclusion: The XGBoost machine learning-based combined model integrating clinical features and delta-radiomic features on ultrasound images was able to predict the Ki-67 value ≥ 15% in an efficient and noninvasive manner, providing important clues for clinical decision-making and follow-up in BC.