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Abstract Allergic rhinitis (AR) resulted in impairing human health and quality of life seriously. There is currently no definitive remedy for AR. Recent studies have shown that autophagy may regulate airway inflammation. Our comprehension of autophagy and its molecular mechanism in the field of AR condition remains incomplete. Our research endeavors to bridge this knowledge deficit by investigating the correlation between AR and autophagy. The AR-related gene expression profile GSE50223 was screened and downloaded. The “limma” package of R software was utilized to identify differentially expressed genes associated with autophagy. GO, KEGG, and Gene set enrichment analyses were conducted. A PPI network of differentially expressed autophagy-related genes were established and further identified through the CytoHubba algorithm. A receiver operating characteristic curve analysis was employed to evaluate the diagnostic effectiveness of the hub genes and to examine the relationship between autophagy-related genes and AR. Finally, qRT-PCR was carried out to confirm the chosen autophagy-related genes using clinical samples. 21 autophagy-related genes in allergic rhinitis were identified. BECN1, PIK3C3, GABARAPL2, ULK2, and UVRAG were considered as significant differentially expressed autophagy-related genes. However, additional molecular biological experiments will be necessary to elucidate the underlying mechanism connecting autophagy and AR.

Abstract RNA methylation is an important regulatory process to determine immune cell function but how it affects the anti-tumor activity of CD8 T cells is not fully understood. Here we show that the N 6-methyladenosine (m6A) RNA reader YTHDF2 is highly expressed in early effector or effector-like CD8 T cells. We find that YTHDF2 facilitates nascent RNA synthesis, and m6A recognition is fundamental for this distinctively nuclear function of the protein, which also reinforces its autoregulation at the RNA level. Loss of YTHDF2 in T cells exacerbates tumor progression and confers unresponsiveness to PD-1 blockade in mice and in humans. In addition to initiating RNA decay that is necessary for mitochondrial fitness, YTHDF2 orchestrates chromatin changes that promote T cell polyfunctionality. YTHDF2 interacts with IKZF1/3, which is important for sustained transcription of their target genes. Accordingly, immunotherapy-induced efficacy could be largely restored in YTHDF2-deficient T cells through combinational use of IKZF1/3 inhibitor lenalidomide in a mouse model. Thus, YTHDF2 coordinates epi-transcriptional and transcriptional networks to potentiate T cell immunity, which could inform therapeutic intervention.

Mg is easily segregated to the grain boundary of the Al–Mg alloy, which affects the mechanical properties of the alloy. In order to reveal the role of Mg element at grain boundaries in Al–Mg alloys, molecular dynamics simulation was used to study the tensile deformation behavior of nano-polycrystalline Al and Al–Mg alloys with different grain sizes. The results show that the elastic modulus and tensile strength of Al and Al–Mg alloys have a clear grain size dependence. The critical grain size at which the elastic modulus decreases as the grain size decreases is independent of Mg. As the Mg content increases to 3 at. %, the critical grain size for the transition from the Hall-Petch relationship to the inverse Hall-Petch relationship increases. The appropriate content of Mg segregation at the grain boundary can increase the elastic modulus, strength and plasticity of the alloy, and inhibit the grain boundary cracking. This result provides important theoretical support for the composition design and microstructure regulation of high-performance Al–Mg alloys.

In July 2022, an outbreak of highly pathogenic avian influenza A(H5N1) virus clade 2.3.4.4b occurred among migratory birds at Qinghai Lake in China. The virus circulated in June, and reassortants emerged after its introduction into the area. Surveillance in 2023 showed that the virus did not establish a stable presence in wild waterfowl.

Abstract Background The kidney is exceptionally vulnerable during sepsis, often resulting in sepsis-associated acute kidney injury (SA-AKI), a condition that not only escalates morbidity but also significantly raises sepsis-related mortality rates. Circular RNA circ_001653 has been previously reported to be upregulated in the serum of SA-AKI patients, while the role and underlying mechanism of circ_001653 in SA-AKI remains unknown. In this study, we aimed to explore the functional role and the molecular mechanism of circ_001653 in the pathogenesis of SA-AKI. Methods LPS-stimulated HK-2 cells and ligation and perforation of cecum (CLP)-induced rats were used as in vitro and in vivo models of SA-AKI. The target gene expression levels were measured using qRT-PCR and western blot. Renal function (BUN, sCr, uNGAL, and uKIM-1), and renal pathological changes were detected in septic mice. TUNEL and EdU assays were conducted to measure apoptosis and proliferation rates in vitro. DCFH-DA staining was used to detect ROS levels in vitro and in vivo. Oxidative stress markers (SOD, GSH-Px, MDA, and SOD), and inflammation markers (IL-1β, IL-6, and TNF-α) were determined using commercial kits both in vitro and in vivo. Additionally, gain-and-loss-of-function assays and mechanistic experiments were conducted to explore the regulatory role of circ_001653 in SA-AKI pathogenesis. Results Data showed that circ_001653 expression was high in LPS-stimulated HK-2 cells and CLP-induced rat renal tissue and was mainly localized in the cytoplasm. Notably, circ_001653 silencing alleviated SA-AKI by reducing apoptosis and alleviating oxidative stress and inflammation in HK-2 cells and renal tissue of rats. Mechanistically, it was found that circ_001653 alleviated SA-AKI by recruiting BUD13 to activate the KEAP1/Nrf2/HO-1 signaling pathway. Conclusions To summarize, our study is the first to reveal elevated expression of circ_001653 in sepsis-associated AKI, and its downregulation effectively attenuates AKI by reducing apoptosis, inflammation, and oxidative stress. Mechanistically, circ_001653 exerts its effects by recruiting BUD13 to activate the KEAP1/Nrf2/HO-1 signaling pathway. These findings suggest circ_001653 as a potential therapeutic target for the drug development of sepsis-associated AKI.

Abstract Background The interleukin-1 receptor accessory protein (IL1RAP) is highly expressed on acute myeloid leukemia (AML) bulk blasts and leukemic stem cells (LSCs), but not on normal hematopoietic stem cells (HSCs), providing an opportunity to target and eliminate the disease, while sparing normal hematopoiesis. Herein, we report the activity of BIF002, a novel anti-IL1RAP/CD3 T cell engager (TCE) in AML. Methods Antibodies to IL1RAP were isolated from CD138+ B cells collected from the immunized mice by optoelectric positioning and single cell sequencing. Individual mouse monoclonal antibodies (mAbs) were produced and characterized, from which we generated BIF002, an anti-human IL1RAP/CD3 TCE using Fab arm exchange. Mutations in human IgG1 Fc were introduced to reduce FcγR binding. The antileukemic activity of BIF002 was characterized in vitro and in vivo using multiple cell lines and patient derived AML samples. Results IL1RAP was found to be highly expressed on most human AML cell lines and primary blasts, including CD34+ LSC-enriched subpopulation from patients with both de novo and relapsed/refractory (R/R) leukemia, but not on normal HSCs. In co-culture of T cells from healthy donors and IL1RAPhigh AML cell lines and primary blasts, BIF002 induced dose- and effector-to-target (E:T) ratio-dependent T cell activation and leukemic cell lysis at subnanomolar concentrations. BIF002 administered intravenously along with human T cells led to depletion of leukemic cells, and significantly prolonged survival of IL1RAPhigh MOLM13 or AML patient-derived xenografts with no off-target side effects, compared to controls. Of note, BiF002 effectively redirects T cells to eliminate LSCs, as evidenced by the absence of disease initiation in secondary recipients of bone marrow (BM) from BIF002+T cells-treated donors (median survival not reached; all survived > 200 days) compared with recipients of BM from vehicle- (median survival: 26 days; p = 0.0004) or isotype control antibody+T cells-treated donors (26 days; p = 0.0002). Conclusions The novel anti-IL1RAP/CD3 TCE, BIF002, eradicates LSCs and significantly prolongs survival of AML xenografts, representing a promising, novel treatment for AML.

Abstract Accurately assigning standardized diagnosis and procedure codes from clinical text is crucial for healthcare applications. However, this remains challenging due to the complexity of medical language. This paper proposes a novel model that incorporates extreme multi-label classification tasks to enhance International Classification of Diseases (ICD) coding. The model utilizes deformable convolutional neural networks to fuse representations from hidden layer outputs of pre-trained language models and external medical knowledge embeddings fused using a multimodal approach to provide rich semantic encodings for each code. A probabilistic label tree is constructed based on the hierarchical structure existing in ICD labels to incorporate ontological relationships between ICD codes and enable structured output prediction. Experiments on medical code prediction on the MIMIC-III database demonstrate competitive performance, highlighting the benefits of this technique for robust clinical code assignment.

Understanding how future climate scenarios impact land use/cover (LUC) and carbon storage (CS) is crucial for achieving carbon neutrality. However, research often overlooks the spatiotemporal impacts of future climate and socioeconomic changes on CS. This study integrates system dynamic (SD), patch-generating land use simulation (PLUS), the integrated valuation of ecosystem services and tradeoffs (InVEST) model, and the geographical detector to assess the LUC and CS evolution in the source of the Yellow River (SYR) from 2020 to 2060. Utilizing carbon density and LUC data, we explored the influence of natural and socioeconomic factors on CS under five shared socioeconomic pathways and representative concentration pathways (SSP-RCPs) scenarios. Our findings demonstrate that: (1) Ecological land, including woodland, grassland, and wetland, expanded more under SSP126 compared to SSP245, with SSP345, SSP460, and SSP585 showing a trend of degradation tied to deeper economic contribution. (2) By 2060, CS in terrestrial ecosystem under SSP126, SSP245, SSP345, SSP460, and SSP585 were 702.33 × 106 t, 700.33 × 106 t, 697.22 × 106 t, 696.03 × 106 t, and 691.21 × 106 t, respectively. This represents changes of 3.69 × 106 t, 1.69 × 106 t, −1.49 × 106 t, −2.68 × 106 t, and −7.43 × 106 t compared to 2020. (3) Soil type predominantly influenced the spatial differentiation of CS, with significant interactions with precipitation. This research provides new insights into land redistribution, economic strategies, and achieving carbon neutrality.

Cancer stem cells (CSCs) are a small population of less differentiated cells with robust self-renewal ability. CSCs have been recognized as the root cause of tumor initiation, progression, relapse, and drug resistance. Recent studies from us and others have highlighted that N6-methyladenosine (m6A), the most prevalent modification in mRNA, plays a crucial role in carcinogenesis and CSC homeostasis. Dysregulation of the m6A modification machinery has been implicated in CSC survival and self-renewal, thereby regulating cancer progression and therapeutic resistance. In this review, we provide an overview of the roles and molecular mechanisms of the RNA m6A modification machinery in CSC survival and self-renewal. Additionally, we summarize the currently known small-molecule inhibitors targeting the dysregulated m6A modification machinery and discuss proof-of-concept studies focusing on the efficacy of these compounds in eliminating CSCs and cancers.

Fractional Vegetation Cover (FVC) serves as a crucial indicator in ecological sustainability and climate change monitoring. While machine learning is the primary method for FVC inversion, there are still certain shortcomings in feature selection, hyperparameter tuning, underlying surface heterogeneity, and explainability. Addressing these challenges, this study leveraged extensive FVC field data from the Qinghai-Tibet Plateau. Initially, a feature selection algorithm combining genetic algorithms and XGBoost was proposed. This algorithm was integrated with the Optuna tuning method, forming the GA-OP combination to optimize feature selection and hyperparameter tuning in machine learning. Furthermore, comparative analyses of various machine learning models for FVC inversion in alpine grassland were conducted, followed by an investigation into the impact of the underlying surface heterogeneity on inversion performance using the NDVI Coefficient of Variation (NDVI-CV). Lastly, the SHAP (Shapley Additive exPlanations) method was employed for both global and local interpretations of the optimal model. The results indicated that: (1) GA-OP combination exhibited favorable performance in terms of computational cost and inversion accuracy, with Optuna demonstrating significant potential in hyperparameter tuning. (2) Stacking model achieved optimal performance in FVC inversion for alpine grassland among the seven models (R2 = 0.867, RMSE = 0.12, RPD = 2.552, BIAS = −0.0005, VAR = 0.014), with the performance ranking as follows: Stacking > CatBoost > XGBoost > LightGBM > RFR > KNN > SVR. (3) NDVI-CV enhanced inversion performance and result reliability by excluding data from highly heterogeneous regions that tended to be either overestimated or underestimated. (4) SHAP revealed the decision-making processes of the Stacking and CatBoost models from both global and local perspectives. This allowed for a deeper exploration of the causality between features and targets. This study developed a high-precision FVC inversion scheme, successfully achieving accurate FVC inversion on the Qinghai-Tibet Plateau. The proposed approach provides valuable references for other ecological parameter inversions.

Modified phosphogypsum (PG) was prepared via low-temperature thermal decomposition to remove fluoride ions from wastewater. This study discussed the effect of heat treatment (pyrolysis temperature and time) and operating conditions (initial fluoride ions concentration, dosage, solution temperature, and initial pH) on fluoride ions removal efficiency. The results showed that PG was most successful in removing fluoride at 140 ℃ for 5 h. At an initial fluoride ions concentration of 100 mg/L, a dosage of 10 g/L, a solution temperature of 20 ℃, and strongly acidic (pH=2) and neutral (pH=7) environments, the fluoride removal efficiency of the PG reached 93.9 % and 66.7 %, respectively. In addition, when the initial fluoride ion concentration was reduced (25 mg/L), the heat-treated modified PG exhibited inadequate fluoride removal (

The 10 vol% ZrMgMo3O12/2024Al composites were fabricated using the powder metallurgy process and consolidation via vacuum hot pressing. The effects of the ball milling process and solution treatment time on the composites’ microstructure, Vickers hardness, and compressive properties were studied. Increasing the ball milling speed and extending the ball milling duration reduce the size of ZrMgMo3O12 particles, resulting in a more uniform dispersion within the aluminum matrix. Extending the solution treatment duration facilitates the dissolution of more primary Al2Cu phase into the aluminum matrix reducing the presence of coarse primary Al2Cu phase and increasing the number of fine Al2Cu precipitates formed during the aging process. The results indicated that an appropriate increase in ball milling speed, extension of ball milling duration, and solution treatment time can enhance the Vickers hardness and room temperature compressive strength of the composites. Specifically, the composites processed with a ball milling speed of 350 rpm for 6 h, a solid solution treatment at 495 °C for 24 h, and an aging treatment at 190 °C for 8 h exhibited a Vickers hardness of 277 HV and a compressive yield strength of 687 MPa, along with a compressive strain of 7.8 %.

Abstract The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor technology. Proteins are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic effects. Electrochemical protein biosensors have achieved desirable specificity by using the specific antibody–antigen binding principle in immunology. However, the active centers of protein biomarkers are surrounded by a peptide matrix, which hinders charge transfer and results in insufficient sensor sensitivity. Therefore, electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein sensors. In this review, we summarize recent reports of electrochemical biosensors for protein biomarker detection. We highlight the latest research on electrochemical protein biosensors for the detection of cancer, viral infectious diseases, inflammation, and other diseases. The corresponding sensitive materials, transducer structures, and detection principles associated with such biosensors are also addressed generally. Finally, we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

Abstract The pathogenesis of major depressive disorder (MDD) involves lipid metabolism. Our earlier research also revealed that MDD patients had much lower total cholesterol (TC) concentrations than healthy controls (HCs). However, it is still unclear why TC decreased in MDD. Here, based on the Ingenuity Knowledge Base’s ingenuity pathway analysis, we found that sodium voltage-gated channel alpha subunit 11A (SCN11A) might serve as a link between low lipid levels and MDD. We analyzed the TC levels and used ELISA kits to measure the levels of SCN11A in the serum from 139 MDD patients, and 65 HCs to confirm this theory and explore the potential involvement of SCN11A in MDD. The findings revealed that TC levels were considerably lower and SCN11A levels were remarkably increased in MDD patients than those in HCs, while they were significantly reversed in drug-treatment MDD patients than in drug-naïve MDD patients. There was no significant difference in SCN11A levels among MDD patients who used single or multiple antidepressants, and selective serotonin reuptake inhibitors or other antidepressants. Pearson correlation analysis showed that the levels of TC and SCN11A were linked with the Hamilton Depression Rating Scales score. A substantial association was also found between TC and SCN11A. Moreover, a discriminative model made up of SCN11A was discovered, which produced an area under a curve of 0.9571 in the training set and 0.9357 in the testing set. Taken together, our findings indicated that SCN11A may serve as a link between low lipid levels and MDD, and showed promise as a candidate biomarker for MDD.

Introduction: Neuroinflammation and autophagy are implicated in stress-related major depressive disorder (MDD), but the underlying molecular mechanisms remain largely unknown. Objectives: Here, we identified that MDD regulated by HMGB1/STAT3/p65 axis mediated microglial activation and autophagy for the first time. Further investigations were performed to uncover the effects of this axis on MDD in vivo and in vitro. Methods: Bioinformatics analyses were used to re-analysis the transcriptome data from the dorsolateral prefrontal cortex (dlPFC) of post-mortem male MDD patients. The expression level of HMGB1 and its correlation with depression symptoms were explored in MDD clinical patients and chronic social defeat stress (CSDS)-induced depression model mice. Specific adeno-associated virus and recombinant (r)HMGB1 injection into the medial PFC (mPFC) of mice, and pharmacological inhibitors with rHMGB1 in two microglial cell lines exposed to lipopolysaccharide were used to analyze the effects of HMGB1/STAT3/p65 axis on MDD. Results: The differential expression of genes from MDD patients implicated in microglial activation and autophagy regulated by HMGB1/STAT3/p65 axis. Serum HMGB1 level was elevated in MDD patients and positively correlated with symptom severity. CSDS not only induced depression-like states in mice, but also enhanced microglial reactivity, autophagy as well as activation of the HMGB1/STAT3/p65 axis in mPFC. The expression level of HMGB1 was mainly increased in the microglial cells of CSDS-susceptible mice, which also correlated with depressive-like behaviors. Specific HMGB1 knockdown produced a depression-resilient phenotype and suppressed the associated microglial activation and autophagy effects of CSDS-induced. The effects induced by CSDS were mimicked by exogenous administration of rHMGB1 or specific overexpression of HMGB1, while blocked by STAT3 inhibitor or p65 knockdown. In vitro, inhibition of HMGB1/STAT3/p65 axis prevented lipopolysaccharide-induced microglial activation and autophagy, while rHMGB1 reversed these changes. Conclusion: Our study established the role of microglial HMGB1/STAT3/p65 axis in mPFC in mediating microglial activation and autophagy in MDD.

It is easy to form twins in Ni-based wrought superalloys with low stacking fault energy, but the effect of grain size and twin spacing on mechanical properties in nano-ploycrystalline Ni-based alloys is rarely studied. Based on the composition of a novel Ni-based wrought superalloy, molecular dynamics simulations were used to study the effect of grain size and twin spacing on the deformation behavior of the Ni57Cr19Co19Al5 alloy. The results show that the elastic modulus and tensile strength of the nano-polycrystalline Ni57Cr19Co19Al5 alloy exhibit clear grain size dependence. As the grain size exceeded 16 nm, the elastic modulus remained unchanged. The tensile strength and grain size satisfy the Hall–Petch relationship, and the dislocation motion dominates the plastic deformation. For the grain size below 16 nm, the elastic modulus decreases as the grain size decreases. The tensile strength and the grain size exhibit an inverse Hall–Petch relationship. The grain boundary sliding and grain torsion mechanisms dominated plastic deformation in the nano-polycrystalline Ni57Cr19Co19Al5 alloy without twin. In the nano-polycrystalline Ni57Cr19Co19Al5 alloy containing twins, the twin boundaries inhibited the torsion of grains, and grain boundary sliding dominated plastic deformation.

Objective Gut microbiota was closely involved in the pathogenesis of depression, but the underlying molecular mechanisms in depression remained unclear. This study was conducted to investigate the relationship between neurotransmitters/inflammatory factors and gut microbiota in depressed mice.Materials and methods A chronic social defeat stress (CSDS) depression model was established. Gut microbial composition was detected in faeces, neurotransmitters were detected in faeces, colon, blood and hippocampus, and inflammatory factors were detected in hippocampus. After a key neurotransmitter was identified, intervention experiment was conducted to explore whether it could improve depressive-like behaviours.Results Six differential genera in faeces, 14 differential neurotransmitters in gut-brain axis, and two differential inflammatory factors (interleukin-1 beta (IL-1β) and interleukin-6 (IL-6)) in hippocampus were identified in depressed mice. There were significant correlations among differential genera, differential neurotransmitters and IL-1β/IL-6. Among these differential neurotransmitters, 3-O-Methyldopa (3-OMDP) was found to be consistently decreased in faeces, colon, blood and hippocampus, and 3-OMDP was significantly correlated to Limosilactobacillus and IL-1β. After receiving 3-OMDP, the depressive-like behaviours in depressed mice were improved and the increased IL-1β/IL-6 levels were reversed.Conclusions These results indicated that gut microbiota might affect host’s inflammation levels in brain through regulating neurotransmitters, eventually leading to the onset of depression. ‘Limosilactobacillus-3-OMDP-IL-1β/IL-6’ might be a potential pathway in the crosstalk of gut and brain, and 3-OMDP held the promise as a therapeutic target for depression.

The discovery of alphacoronaviruses and betacoronaviruses in plateau pikas (Ochotona curzoniae) expanded the host range of mammalian coronavirus (CoV) to a new order – Lagomorpha. However, the diversity and evolutionary relationships of CoVs in these plateau-region-specific animal population remains uncertain. We conducted a five-year longitudinal surveillance of CoVs harboured by pikas around Qinghai Lake, China. CoVs were identified in 33 of 236 plateau pikas and 2 of 6 Gansu pikas (Ochotona cansus), with a total positivity rate of 14.5%, and exhibiting a wide spatiotemporal distribution across seven sampling sites and six time points. Through meta-transcriptomic sequencing and RT–PCR, we recovered 16 near-complete viral genome sequences. Phylogenetic analyses classified the viruses as variants of either pika alphacoronaviruses or betacoronaviruses endemic to plateau pikas from the Qinghai-Tibet Plateau region. Of particular note, the pika-associated betacoronaviruses may represent a novel subgenus within the genus Betacoronavirus. Tissue tropism, evaluated using quantitative real-time PCR, revealed the presence of CoV in the rectal and/or lung tissues, with the highest viral loads at 103.55 or 102.80 RNA copies/μL. Surface plasmon resonance (SPR) assays indicated that the newly identified betacoronavirus did not bind to human or pika Angiotensin-converting enzyme 2 (ACE2) or Dipeptidyl peptidase 4 (DPP4). The findings highlight the ongoing circulation and broadening host spectrum of CoVs among pikas, emphasizing the necessity for further investigation to evaluate their potential public health risks.

Gamma/delta T (γδ T)cells possess a unique mechanism for killing tumors, making them highly promising and distinguished among various cell therapies for tumor treatment. This review focuses on the major histocompatibility complex (MHC)-independent recognition of antigens and the interaction between γδ T cells and solid tumor cells. A comprehensive review is provided regarding the classification of human gamma-delta T cell subtypes, the characteristics and mechanisms underlying their functions, as well as their r545egulatory effects on tumor cells. The involvement of γδ T cells in tumorigenesis and migration was also investigated, encompassing potential therapeutic targets such as apoptosis-related molecules, the TNF receptor superfamily member 6(FAS)/FAS Ligand (FASL) pathways, butyrophilin 3A-butyrophilin 2A1 (BTN3A-BTN2A1) complexes, and interactions with CD4, CD8, and natural killer (NK) cells. Additionally, immune checkpoint inhibitors such as programmed cell death protein 1/Programmed cell death 1 ligand 1 (PD-1/PD-L1) have the potential to augment the cytotoxicity of γδ T cells. Moreover, a review on gamma-delta T cell therapy products and their corresponding clinical trials reveals that chimeric antigen receptor (CAR) gamma-delta T therapy holds promise as an approach with encouraging preclinical outcomes. However, practical issues pertaining to manufacturing and clinical aspects need resolution, and further research is required to investigate the long-term clinical side effects of CAR T cells. In conclusion, more comprehensive studies are necessary to establish standardized treatment protocols aimed at enhancing the quality of life and survival rates among tumor patients utilizing γδ T cell immunotherapy.

Abstract The colon is the largest compartment of the immune system, with innate immune cells exposed to antigens in the environment. However, the mechanisms by which the innate immune system is instigated are poorly defined in colorectal cancer (CRC). Here, a population of CD16+ neutrophils that specifically accumulate in CRC tumor tissues by imaging mass cytometry (IMC), immune fluorescence, and flow cytometry, which demonstrated pro‐tumor activity by disturbing natural killer (NK) cells are identified. It is found that these CD16+ neutrophils possess abnormal cholesterol accumulation due to activation of the CD16/TAK1/NF‐κB axis, which upregulates scavenger receptors for cholesterol intake including CD36 and LRP1. Consequently, these region‐specific CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, which interrupts NK lipid raft formation and blocks their antitumor signaling but also release neutrophil extracellular traps (NETs) to induce the death of NK cells. Furthermore, CD16‐knockout reverses the pro‐tumor activity of neutrophils and restored NK cell cytotoxicity. Collectively, the findings suggest that CRC region‐specific CD16+ neutrophils can be a diagnostic marker and potential therapeutic target for CRC.

The growth of vegetation on the Qinghai Tibet Plateau (QTP) is experiencing significant changes due to climate change. There is still a lack of high-precision simulation methods for alpine grassland cover (AGC), and the climate feedback mechanisms of AGC remain unclear, which poses challenges for the production of high-precision AGC products and the formulation of ecological conservation policies. In this study, a transferable stacking deep learning (Stacking-DL) model is proposed based on a CNN, a DNN, and a GRU for AGC time series simulation. The applicability of deep learning models for AGC simulation is evaluated based on long time series of measured data, MODIS data, and environmental factors. Finally, the AGC spatiotemporal changes and controlling environmental factors in the alpine region were analyzed based on Sen’s slope and structural equation modeling (SEM). The results showed that feature selection and parameter optimization improved the applicability of the deep learning models in AGC simulations, and the DNN (R2 = 0.899, RMSE = 0.078) model performed best among the base deep learning models. The Stacking-DL model combines the advantages of multiple models and achieves high transfer accuracy. In the YRSR, the AGC increase area (20.34 %) is greater than the AGC decrease area (3.34 %), the increase area is mainly located in the northeast, and the decrease area is mainly located in the southwest. AGC changes in the YRSR are mainly controlled by permafrost and climate. This study provides a high-precision and transferable vegetation monitoring model for alpine mountain regions based on advanced deep learning models and clarifies the response mechanism of AGC under climate change.

Abstract Dysregulated RNA modifications, stemming from the aberrant expression and/or malfunction of RNA modification regulators operating through various pathways, play pivotal roles in driving the progression of haematological malignancies. Among RNA modifications, N6‐methyladenosine (m6A) RNA modification, the most abundant internal mRNA modification, stands out as the most extensively studied modification. This prominence underscores the crucial role of the layer of epitranscriptomic regulation in controlling haematopoietic cell fate and therefore the development of haematological malignancies. Additionally, other RNA modifications (non‐m6A RNA modifications) have gained increasing attention for their essential roles in haematological malignancies. Although the roles of the m6A modification machinery in haematopoietic malignancies have been well reviewed thus far, such reviews are lacking for non‐m6A RNA modifications. In this review, we mainly focus on the roles and implications of non‐m6A RNA modifications, including N4‐acetylcytidine, pseudouridylation, 5‐methylcytosine, adenosine to inosine editing, 2′‐O‐methylation, N1‐methyladenosine and N7‐methylguanosine in haematopoietic malignancies. We summarise the regulatory enzymes and cellular functions of non‐m6A RNA modifications, followed by the discussions of the recent studies on the biological roles and underlying mechanisms of non‐m6A RNA modifications in haematological malignancies. We also highlight the potential of therapeutically targeting dysregulated non‐m6A modifiers in blood cancer.

Sesuvium portulacastrum L. is a flowering succulent halophyte in the ice plant family Aizoaceae. There are various ecotypes distributed in sandy coastlines and salty marshlands in tropical and subtropical regions with the common name of sea purslane. These plants are tolerant to salt, drought, and flooding stresses and have been used for the stabilization of sand dunes and the restoration of coastal areas. With the increased salinization of agricultural soils and the widespread pollution of toxic metals in the environment, as well as excessive nutrients in waterbodies, S. portulacastrum has been explored for the desalination of saline soils and the phytoremediation of metals from contaminated soils and nitrogen and phosphorus from eutrophic water. In addition, sea purslane has nutraceutical and pharmaceutical value. Tissue analysis indicates that many ecotypes are rich in carbohydrates, proteins, vitamins, and mineral nutrients. Native Americans in Florida eat it raw, pickled, or cooked. In the Philippines, it is known as atchara after being pickled. S. portulacastrum contains high levels of ecdysteroids, which possess antidiabetic, anticancer, and anti-inflammatory activities in mammals. In this review article, we present the botanical information, the physiological and molecular mechanisms underlying the tolerance of sea purslane to different stresses, its nutritional and pharmaceutical value, and the methods for its propagation and production in saline soils and waterbodies. Its adaptability to a wide range of stressful environments and its role in the production of valuable bioactive compounds suggest that S. portulacastrum can be produced in saline soils as a leafy vegetable and is a valuable genetic resource that can be used for the bioremediation of soil salinity and eutrophic water.

Abstract Background While liver cancer stem cells (CSCs) play a crucial role in hepatocellular carcinoma (HCC) initiation, progression, recurrence, and treatment resistance, the mechanism underlying liver CSC self-renewal remains elusive. We aim to characterize the role of Methyltransferase 16 (METTL16), a recently identified RNA N 6-methyladenosine (m6A) methyltransferase, in HCC development/maintenance, CSC stemness, as well as normal hepatogenesis. Methods Liver-specific Mettl16 conditional KO (cKO) mice were generated to assess its role in HCC pathogenesis and normal hepatogenesis. Hydrodynamic tail-vein injection (HDTVi)-induced de novo hepatocarcinogenesis and xenograft models were utilized to determine the role of METTL16 in HCC initiation and progression. A limiting dilution assay was utilized to evaluate CSC frequency. Functionally essential targets were revealed via integrative analysis of multi-omics data, including RNA-seq, RNA immunoprecipitation (RIP)-seq, and ribosome profiling. Results METTL16 is highly expressed in liver CSCs and its depletion dramatically decreased CSC frequency in vitro and in vivo. Mettl16 KO significantly attenuated HCC initiation and progression, yet only slightly influenced normal hepatogenesis. Mechanistic studies, including high-throughput sequencing, unveiled METTL16 as a key regulator of ribosomal RNA (rRNA) maturation and mRNA translation and identified eukaryotic translation initiation factor 3 subunit a (eIF3a) transcript as a bona-fide target of METTL16 in HCC. In addition, the functionally essential regions of METTL16 were revealed by CRISPR gene tiling scan, which will pave the way for the development of potential inhibitor(s). Conclusions Our findings highlight the crucial oncogenic role of METTL16 in promoting HCC pathogenesis and enhancing liver CSC self-renewal through augmenting mRNA translation efficiency.

Epigenetic pathways play a critical role in the initiation, progression, and metastasis of cancer. Over the past few decades, significant progress has been made in the development of targeted epigenetic modulators (e.g., inhibitors). However, epigenetic inhibitors have faced multiple challenges, including limited clinical efficacy, toxicities, lack of subtype selectivity, and drug resistance. As a result, the design of new epigenetic modulators (e.g., degraders) such as PROTACs, molecular glue, and hydrophobic tagging (HyT) degraders has garnered significant attention from both academia and pharmaceutical industry, and numerous epigenetic degraders have been discovered in the past decade. In this review, we aim to provide an in-depth illustration of new degrading strategies (2017–2023) targeting epigenetic proteins for cancer therapy, focusing on the rational design, pharmacodynamics, pharmacokinetics, clinical status, and crystal structure information of these degraders. Importantly, we also provide deep insights into the potential challenges and corresponding remedies of this approach to drug design and development. Overall, we hope this review will offer a better mechanistic understanding and serve as a useful guide for the development of emerging epigenetic-targeting degraders.

Calculating single-source shortest paths (SSSPs) rapidly and precisely from weighted digraphs is a crucial problem in graph theory. As a mathematical model of processing uncertain tasks, rough sets theory (RST) has been proven to possess the ability of investigating graph theory problems. Recently, some efficient RST approaches for discovering different subgraphs (e.g. strongly connected components) have been presented. This work was devoted to discovering SSSPs of weighted digraphs by aid of RST. First, SSSPs problem was probed by RST, which aimed at supporting the fundamental theory for taking RST approach to calculate SSSPs from weighted digraphs. Second, a heuristic search strategy was designed. The weights of edges can be served as heuristic information to optimize the search way of $ k $-step $ R $-related set, which is an RST operator. By using heuristic search strategy, some invalid searches can be avoided, thereby the efficiency of discovering SSSPs was promoted. Finally, the W3SP@R algorithm based on RST was presented to calculate SSSPs of weighted digraphs. Related experiments were implemented to verify the W3SP@R algorithm. The result exhibited that W3SP@R can precisely calculate SSSPs with competitive efficiency.

Abstract Our previous work has shown that d-ribose (RIB)-induced depressive-like behaviors in mice. However, the relationship between variations in RIB levels and depression as well as potential RIB participation in depressive disorder is yet unknown. Here, a reanalysis of metabonomics data from depressed patients and depression model rats is performed to clarify whether the increased RIB level is positively correlated with the severity of depression. Moreover, we characterize intestinal epithelial barrier damage, gut microbial composition and function, and microbiota-gut-brain metabolic signatures in RIB-fed mice using colonic histomorphology, 16 S rRNA gene sequencing, and untargeted metabolomics analysis. The results show that RIB caused intestinal epithelial barrier impairment and microbiota-gut-brain axis dysbiosis. These microbial and metabolic modules are consistently enriched in peripheral (fecal, colon wall, and serum) and central (hippocampus) glycerophospholipid metabolism. In addition, three differential genera (Lachnospiraceae_UCG-006, Turicibacter, and Akkermansia) and two types of glycerophospholipids (phosphatidylcholine and phosphatidylethanolamine) have greater contributions to the overall correlations between differential genera and glycerophospholipids. These findings suggest that the disturbances of gut microbiota by RIB may contribute to the onset of depressive-like behaviors via regulating glycerophospholipid metabolism, and providing new insight for understanding the function of microbiota-gut-brain axis in depression.

As the most common internal modification of mRNA, N6-methyladenosine (m6A) and its regulators modulate gene expression and play critical roles in various biological and pathological processes including tumorigenesis. It was reported previously that m6A methyltransferase (writer), methyltransferase-like 3 (METTL3) adds m6A in primary microRNAs (pri-miRNAs) and facilitates its processing into precursor miRNAs (pre-miRNAs). However, it is unknown whether m6A modification also plays a role in the maturation process of pre-miRNAs and (if so) whether such a function contributes to tumorigenesis. Here, we found that YTHDF2 is aberrantly overexpressed in acute myeloid leukemia (AML) patients, especially in relapsed patients, and plays an oncogenic role in AML. Moreover, YTHDF2 promotes expression of miR-126-3p (also known as miR-126, as it is the main product of precursor miR-126 (pre-miR-126)), a miRNA that was reported as an oncomiRNA in AML, through facilitating the processing of pre-miR-126 into mature miR-126. Mechanistically, YTHDF2 recognizes m6A modification in pre-miR-126 and recruits AGO2, a regulator of pre-miRNA processing, to promote the maturation of pre-miR-126. YTHDF2 positively and negatively correlates with miR-126 and miR-126's downstream target genes, respectively, in AML patients, and forced expression of miR-126 could largely rescue YTHDF2/Ythdf2 depletion-mediated suppression on AML cell growth/proliferation and leukemogenesis, indicating that miR-126 is a functionally important target of YTHDF2 in AML. Overall, our studies not only reveal a previously unappreciated YTHDF2/miR-126 axis in AML and highlight the therapeutic potential of targeting this axis for AML treatment, but also suggest that m6A plays a role in pre-miRNA processing that contributes to tumorigenesis.

A new pickup structure was introduced and modified to improve the resolution of the linear Sagnac optical fiber acoustic sensing system. The maximum strains corresponding to the material, diameter, wall thickness, and height of the pickups were analyzed by simulation. An aluminum cylinder with a diameter of 110 mm, a wall thickness of 3 mm, and a height of 120 mm was chosen as the basic pickup. A four-groove pickup with a vertical width of 80 mm and a horizontal width of 20 mm was introduced to improve the sensitivity of the system. The experiments showed that the average peak-to-peak sensitivity of the four-groove pickup increased by 215.54% to 106.806 mV/Pa. The improved pickup can be applied in areas to monitor the situation of invasion of the Sagnac optical fiber acoustic sensing system.

Variations in the cadmium (Cd) accumulation and root characteristics of different genotypes of rice during three developmental periods of dry cultivation were investigated in pot experiments in which two levels of Cd were added to the soil (0 and 10 mg kg−1). The results show that the Cd concentration in each organ of the different rice genotypes decreased in both the order of roots > shoots > grains and during the three developmental periods in the order of the maturity stage > booting stage > tillering stage. The lowest bioaccumulation factor (BCF) and translocation factor (TF) were found in Yunjing37 (YJ37) under Cd stress. At maturity, Cd stress inhibited the root length of Dianheyou34 (DHY34) the most and that of Dianheyou 918 (DHY918) the least, also affecting the root volume of DHY34 and Dianheyou615 (DHY615) the most and that of YJ37 and Yiyou 673 (YY673) the least; the inhibition rates were 41.80, 5.09, 40.95, and 10.51%, respectively. The exodermis showed the greatest thickening in YY673 and the lowest thickening in DHY615, while the endodermis showed the opposite result. The rates of change were 16.48, 2.45, 5.10, and 8.49%, respectively. The stele diameter of DHY615 decreased the most, and that of YY673 decreased the least, while the secondary xylem area showed the opposite result; the rates of change were −21.50, −14.29, −5.86, and −26.35%, respectively. Under Cd stress treatment at maturity, iron plaque was extracted using the dithionite–citrate–bicarbonate (DCB) method. The concentration of iron (DCB-Fe) was highest in YJ37, and the concentration of cadmium (DCB-Cd) was lowest in DHY34. YJ37 was screened as a low Cd-accumulating variety. The concentration of available Cd in the rhizosphere soil, iron plaque, root morphology, and anatomy affect Cd accumulation in rice with genotypic differences. Our screening of Cd-accumulating rice varieties provides a basis for the dry cultivation of rice in areas with high background values of Cd in order to avoid the health risks of Cd intake.

IntroductionBiliary Infection in patients is a common and important phenomenon resulting in severe complications and high morbidity, while the distributions and drug resistance profiles of biliary bacteria and related risk factors are dynamic. This study explored the characteristics of and risk factors for biliary infection to promote the rational use of antibiotics in clinically.MethodsBacterial identification and drug susceptibility testing were completed using the Vitek 2 Compact analysis system. The distribution and antibiotic-resistant characteristics of 3,490 strains of biliary bacteria in patients at Nankai Hospital from 2019 to 2021 were analyzed using Whonet 5.6 and SPSS 26.0 software. We then retrospectively analyzed the clinical data and risk factors associated with 2,340 strains of Gram-negative bacilli, which were divided into multidrug-resistant bacteria (1,508 cases) and non-multidrug-resistant bacteria (832 cases) by a multivariate Cox regression model.Results and discussionA total of 3,490 pathogenic bacterial strains were isolated from bile samples, including 2,340 (67.05%) Gram-negative strains, 1,029 (29.48%) Gram-positive strains, and 109 (4.56%) fungal strains. The top five pathogenic bacteria were Escherichia coli, Klebsiella pneumoniae, Enterococcus faecium, Enterococcus faecalis, and Pseudomonas aeruginosa. The rate of Escherichia coli resistance to ciprofloxacin increased (p

Flexible bioelectronic devices have attracted immense interest in the biomedical field because of their wearability, biocompatibility, diverse functionalities, and ease of personalization. Recently, flexible energy harvesters have been developed, and attempts have been made to integrate them with such devices, enabling them to operate without external batteries or power supply. In this review, the latest advances in flexible energy harvesters and their use in wearable devices are discussed. Energy harvesters for versatile biomedical applications are summarized. Finally, the challenges and future perspectives of self‐powered biomedical systems that enable wearable healthcare monitoring and management are outlined.

The current therapies used to treat sepsis are ineffective and sepsis-related mortality is high. Therefore, it is important to find new treatment options that reduce mortality from that disease. In the present study, the effects of probiotic pretreatment in septic rats were studied on morality, hematological parameters, oxidative stress, antioxidant capacity, and inflammation. After preparation of rats and administration of probiotic VSL # 3, cecal ligation and puncture (CLP) surgery was used to induce sepsis. Then, the animals were divided into four groups: sham, sham + VSL # 3, septic, and septic + VSL # 3. Sepsis-related mortality, hematological parameters, and biochemical factors were assessed. Also, the expression of inflammatory cytokines IL-6, TNF-α and IL-10 in serum were studied using enzyme-linked immunosorbent assay (ELISA). Then, the NF-κB gene and protein expression in intestinal tissue was studied by RT-qPCR and western blot techniques, respectively. Daily pretreatment with VSL # 3 in septic rats resulted in a 20 % reduction in mortality over 10 days and a significant modulation in hematological parameters. Evaluation of oxidant and antioxidant indices showed a decrease in oxidative stress and an increase in antioxidant capacity in septic rats receiving VSL # 3. Also, decreased expressions of inflammatory cytokines IL-6, TNF-α, IL-10, and NF-κB were observed in septic rats receiving VSL # 3. In general, it can be concluded that the administration of probiotic VSL # 3, which resulted in the improved survival of septic rats and better antioxidant and anti-inflammatory conditions, can be considered as a new adjutant therapeutic approach in the treatment of sepsis.

Abstract Background Osteosarcoma (OS) is a highly invasive primary malignancy of the bone that is common in children and adolescents. MicroRNAs (miRNAs) are novel diagnostic and predictive biomarkers for cancers. The miRNA miR-3195 is aberrantly expressed in multiple types of tumors. However, the expression levels and biological functions of miR-3195 in OS remain unclear. Methods Two Gene Expression Omnibus (GEO) datasets (GSE69470 and GSE16088) were used to analyze differentially expressed miRNAs and mRNAs in osteosarcoma cell lines and OS tissues. Quantitative RT-PCR was used to detect the expression levels of miR-3195 and the SRY-box transcription factor 4 (SOX4) mRNA in OS tissues and cell lines. The relationship between miR-3195 and the 3’-upstream region (3’-UTR) in the SOX4 mRNA (predicted through bioinformatics) was analyzed using Pearson's correlation analysis and confirmed by a dual-luciferase reporter gene experiment. Cell counting kit-8 assays, colony formation assays, flow cytometry, wound healing assays, transwell assays, and western blotting were performed to explore the effects of miR-3195 levels on SOX4 affected OS cell biological behavior. Results Our results revealed that miR-3195 was the most down-regulated miRNA and SOX4 was the most up-regulated mRNA by Bioinformatic analysis. It was further confirmed miR-3195 had low expression, and SOX4 had high expression levels in clinical OS tissue samples; the expression levels of both genes were negatively correlated with each other in OS tissues. Overexpression of miR-3195 in OS cell lines significantly inhibited cell proliferation, migration, and invasiveness, while promoting apoptosis; all these effects were reversed by increasing SOX4 expression levels. We also found that miR-3195 could directly bind with the SOX4 gene and down-regulate SOX4 expression. Conclusions miR-3195 can modulate proliferation, migration, invasiveness, and apoptosis in OS cells by regulating the SOX4 gene. Thus, the miR-3195/SOX4 signaling may be a novel therapeutic target in OS treatment.

Abstract The mechanisms underlying the transformation of chronic myeloid leukemia (CML) from chronic phase (CP) to blast crisis (BC) are not fully elucidated. Here, we show lower levels of miR-142 in CD34+CD38− blasts from BC CML patients than in those from CP CML patients, suggesting that miR-142 deficit is implicated in BC evolution. Thus, we create miR-142 knockout CML (i.e., miR-142 −/− BCR-ABL) mice, which develop BC and die sooner than miR-142 wt CML (i.e., miR-142 +/+ BCR-ABL) mice, which instead remain in CP CML. Leukemic stem cells (LSCs) from miR-142 −/− BCR-ABL mice recapitulate the BC phenotype in congenic recipients, supporting LSC transformation by miR-142 deficit. State-transition and mutual information analyses of “bulk” and single cell RNA-seq data, metabolomic profiling and functional metabolic assays identify enhanced fatty acid β-oxidation, oxidative phosphorylation and mitochondrial fusion in LSCs as key steps in miR-142-driven BC evolution. A synthetic CpG-miR-142 mimic oligodeoxynucleotide rescues the BC phenotype in miR-142 −/− BCR-ABL mice and patient-derived xenografts.

Abstract Background Headache disorders are widely prevalent and pose a considerable economic burden on individuals and society. Globally, misdiagnosis and inadequate treatment of primary headache disorders remain significant challenges, impeding the effective management of such conditions. Despite advancements in headache management over the last decade, a need for comprehensive evaluations of the status of primary headache disorders in China regarding diagnosis and preventative treatments persists. Methods In the present study, we analyzed the established queries in the Survey of Fibromyalgia Comorbidity with Headache (SEARCH), focusing on previous diagnoses and preventative treatment regimens for primary headache disorders. This cross-sectional study encompassed adults diagnosed with primary headache disorders who sought treatment at 23 hospitals across China between September 2020 to May 2021. Results The study comprised 2,868 participants who were systematically examined. Migraine and tension-type headaches (TTH) constituted a majority of the primary headache disorders, accounting for 74.1% (2,124/2,868) and 23.3% (668/2,868) of the participants, respectively. Medication overuse headache (MOH) affected 8.1% (231/2,868) of individuals with primary headache disorders. Over half of the individuals with primary headache disorders (56.6%, 1,624/2,868) remained undiagnosed. The previously correct diagnosis rates for migraine, TTH, TACs, and MOH were 27.3% (580/2,124), 8.1% (54/668), 23.2% (13/56), and 3.5% (8/231), respectively. The misdiagnosis of “Nervous headache” was found to be the most prevalent among individuals with migraine (9.9%, 211/2,124), TTH (10.0%, 67/668), trigeminal autonomic cephalalgias (TACs) (17.9%, 10/56), and other primary headache disorders (10.0%, 2/20) respectively. Only a minor proportion of individuals with migraine (16.5%, 77/468) and TTH (4.7%, 2/43) had received preventive medication before participating in the study. Conclusions While there has been progress made in the rate of correct diagnosis of primary headache disorders in China compared to a decade ago, the prevalence of misdiagnosis and inadequate treatment of primary headaches remains a veritable issue. As such, focused efforts are essential to augment the diagnosis and preventive treatment measures related to primary headache disorders in the future.

Bearing fault diagnosis is very important for the security and efficiency of electric machines. In recent years, the newly emerging deep learning methods have risen bearing fault diagnosis as a research hotspot again. To achieve better performance and interpretability and absorb novel methods, this paper proposes a novel framework based on adaptive Multi-Task Learning for bearing fault diagnosis, Gramian Angular Fields - Markov Transition Fields - Convolutional Neural Network (GM-CNN), including data augmentation, image encoding methods and adaptive Multi-Task Learning (MTL). Firstly, data augmentation (DA) methods are applied in data preprocessing for tackling the problems of lack of data and weak generalization ability. They include cropping, flipping, and noise injection. Secondly, Gramian Angular Fields (GAF), Markov Transition Fields (MTF), and their combination GAF-MTF are used to encode time series into images which are more proper for convolutional neural network (CNN) to extract features and classify. Then, the processed data are fed into the proposed MTL framework, and tasks for classifying the fault type and severity are trained jointly as they share some general knowledge and this saves more time. Besides, attention is applied to make the MTL adaptive, which is helpful for more balanced training. Some experiments are carried out. And the experiment results show that the proposed framework is relatively simple but more effective, classifying the fault type and severity with high accuracy (basically higher than 99%). It is shown that every step of the framework is important and essential. This paper provides a reference for future studies on bearing fault diagnosis from the perspective of feature extraction and CNN. It could also be applied to other time series classification situations which could be promising directions.

A major engineering challenge in construction projects lies in the stability assessment of rocky slopes with faults. The left bank slope of the Jinchuan Hydropower Station in the outlet field is notably influenced by the steeply inclined faults and rock joints, resulting in highly complex geological conditions and raising critical concerns regarding slope stability throughout construction and operation. The evolution mechanism of rock mass from fracture to deformation during slope excavation and unloading is determined using microseismic (MS) monitoring and numerical simulation. Results show that the MS activity can effectively reveal the influence of slope construction disturbance on geological structure damage and structural plane activation. Specifically, the g7 fault is a crucial factor influencing the failure mode of the left bank slope of the Jinchuan Hydropower Station in the outlet field. The comparison of monitoring data, numerical simulation, and in-situ failure demonstrates consistency between the deformation area of rock mass and the damage area defined by MS monitoring, confirming the accuracy of MS monitoring and numerical simulation results. Overall, the results can serve as a basis for the later-stage construction of the dam foundation slope at the Jinchuan Hydropower Station and provide guidance for the stability assessment of similar slope engineering projects.

Accurate forest tree-species classification not only provides data support for forest resource management but also serves as a crucial parameter for simulating various ecological processes. However, the results of forest tree-species classification have been affected by multiple factors, such as the spectral resolution, spatial resolution, and radiometric resolution of imagery, the classification algorithms used, the sample size, and the timing of image acquisition phases. Although there are many studies on the impact of individual factors on tree-species classification, there is a lack of systematic studies quantifying the magnitude of these factors’ influences, leading to uncertainties about the relative importance of different factors. In this study, Landsat-8, Landsat-9, and Sentinel-2 imagery was used as the foundational data, and random forest (RF), gradient tree boosting (GTB), and support vector machine (SVM) algorithms were employed to classify forest tree species. High-accuracy regional forest tree-species classification was achieved by exploring the impacts of spectral resolution, spatial resolution, radiometric resolution, classification algorithms, sample size, and image time phases. The results show that, for the commonly used Landsat-8, Landsat-9, and Sentinel-2 imagery, the tree-species classification results from Landsat-9 are the best, with an overall accuracy of 74.21% and a kappa of 0.71. Among the various influencing factors, the classification algorithm, image time phases, and sample size have relatively larger impacts on tree-species classification results, each exceeding 10%, while the positive impact of radiometric resolution is the smallest, at only 3.15%. Conversely, spectral and spatial resolutions had negative effects on tree-species classification results, at −4.09% and −1.4%, respectively. Based on the 30-m spring Landsat-9 and Sentinel-2 imagery, with 300 samples for each tree-species category, the classification results using the RF algorithm were the best, with an overall accuracy of 87.07% and a kappa coefficient of 0.85. The results indicate that different factors have different impacts on forest tree-species classification results, with classification algorithms, image time phases, and sample size having the largest impacts. Higher spatial and spectral resolutions do not improve the classification accuracy. Therefore, future studies should focus on selecting appropriate classification algorithms, sample sizes, and images from seasons with greater tree differences to improve tree-species classification results.

Sesuvium portulacastrum L. is a dicotyledonous halophyte belonging to the family Aizoaceae. Its young leaves are highly nutritious, and many ecotypes are used as leafy vegetable and medicinal crops. Additionally, due to their tolerance to soil salinity, flooding, and high temperatures, some ecotypes are used for the remediation of saline soils. As a result, there is an increasing need for a large number of disease-free S. portulacastrum propagules. This study developed an efficient protocol for the regeneration of S. portulacastrum through indirect shoot organogenesis. Leaf explants were cultured on Murashige and Skoog basal medium supplemented with different concentrations of zeatin (ZT) and indole-3-acetic acid (IAA). Callus was induced in all explants cultured with 1.5 mg/L ZT only or 1.5 mg/L ZT with 0.5 mg/L IAA. The callus was cut into small pieces and cultured on the same medium on which it was initially induced. ZT at 1.5 mg/L induced 73.7% of callus pieces to produce adventitious shoots, and the shoot numbers per callus piece were up to 20. To improve the in vitro rooting of adventitious shoots, commonly known as microshoots or microcuttings, an endophytic fungus, Cladosporium ‘BF-F’, was inoculated onto the rooting medium. ‘BF-F’ substantially enhanced rooting and plantlet growth, as the root numbers were three times more and plantlet heights were 70% greater than those without ‘BF-F’ inoculation. To detect the genes involved in the enhanced rooting and plantlet growth, qRT-PCR analysis was performed. Results showed that genes related to auxin responses and nitrogen uptake and metabolism were highly upregulated in ‘BF-F’-inoculated plantlets. Plants inoculated with ‘BF-F’ grew vigorously after being transplanted into a sand–soil substrate. Thus, this study not only established an efficient protocol for the regeneration of S. portulacastrum but also developed a novel method for improving the rooting of microshoots and plantlet growth. The established propagation system could be used for producing a large number of S. portulacastrum plantlets for commercial use and also for genetic transformation.

Objective: Motivated by Health Care 4.0, this study aims to reducing the dimensionality of traditional EEG features based on manual extracted features, including statistical features in the time and frequency domains. Methods: A total of 22 multi-scale features were extracted from the UNM and Iowa datasets using a 4th order Butterworth filter and wavelet packet transform. Based on single-channel validation, 29 channels with the highest R2 scores were selected from a pool of 59 common channels. The proposed channel selection scheme was validated on the UNM dataset and tested on the Iowa dataset to compare its generalizability against models trained without channel selection. Results: The experimental results demonstrate that the proposed model achieves an optimal classification accuracy of 100%. Additionally, the generalization capability of the channel selection method is validated through out-of-sample testing based on the Iowa dataset Conclusions: Using single-channel validation, we proposed a channel selection scheme based on traditional statistical features, resulting in a selection of 29 channels. This scheme significantly reduced the dimensionality of EEG feature vectors related to Parkinson’s disease by 50%. Remarkably, this approach demonstrated considerable classification performance on both the UNM and Iowa datasets. For the closed-eye state, the highest classification accuracy achieved was 100%, while for the open-eye state, the highest accuracy reached 93.75%.

Lead-free Cs3Cu2I5 metal halides have garnered significant attention recently due to their non-toxic properties and deep-blue emission. However, their relatively low photoluminescence quantum efficiency and poor stability have limited their applications. In this work, sodium iodide (NaI) is used to facilitate the synthesis of Cs3Cu2I5 nanocrystals (NCs), demonstrating improved photoluminescence intensity, photoluminescence quantum yield, and stability. Systematic optoelectronic characterizations confirm that Na+ is successfully incorporated into the Cs3Cu2I5 lattice without altering its crystal structure. The improved Photoluminescence Quantum Yield (PLQY) and stability are attributed to the strengthened chemical bonding, which effectively suppresses vacancy defects in the lattice. Additionally, light-emitting diodes (LEDs) based on 10% NaI-doped Cs3Cu2I5 NCs were assembled, emitting vibrant blue light with a maximum radiant intensity of 82 lux and Commission Internationale de l’Eclairage (CIE) chromaticity coordinates of (0.15, 0.1). This work opens new possibilities for commercial lighting display applications.

In this study, an advanced method for apricot tree disease detection is proposed that integrates deep learning technologies with various data augmentation strategies to significantly enhance the accuracy and efficiency of disease detection. A comprehensive framework based on the adaptive sampling latent variable network (ASLVN) and the spatial state attention mechanism was developed with the aim of enhancing the model’s capability to capture characteristics of apricot tree diseases while ensuring its applicability on edge devices through model lightweighting techniques. Experimental results demonstrated significant improvements in precision, recall, accuracy, and mean average precision (mAP). Specifically, precision was 0.92, recall was 0.89, accuracy was 0.90, and mAP was 0.91, surpassing traditional models such as YOLOv5, YOLOv8, RetinaNet, EfficientDet, and DEtection TRansformer (DETR). Furthermore, through ablation studies, the critical roles of ASLVN and the spatial state attention mechanism in enhancing detection performance were validated. These experiments not only showcased the contributions of each component for improving model performance but also highlighted the method’s capability to address the challenges of apricot tree disease detection in complex environments. Eight types of apricot tree diseases were detected, including Powdery Mildew and Brown Rot, representing a technological breakthrough. The findings provide robust technical support for disease management in actual agricultural production and offer broad application prospects.

Temperature affects the growth and development of tobacco. With the frequent occurrence of extreme high and low temperature disasters, temperature stress has become one of the important factors restricting the normal growth and physiological functions of flue-cured tobacco. Low temperature stress and high temperature stress are currently the most common disasters in the seedling and maturity stages of flue-cured tobacco, which have a serious impact on the quality and yield of flue-cured tobacco. This article reviews the effects of temperature stress on physiological mechanisms such as growth and development, photosynthetic function, carbon and nitrogen metabolism, and antioxidant system of flue-cured tobacco. It introduced the research progress of related plant proteins and molecular mechanisms in temperature stress, and systematically summarizes the current stress resistance control measures for field temperature stress, including field management and spraying exogenous substances. At present, most agronomic interventions for temperature stress management may not be complete. It is necessary to understand the genetic, biochemical and physiological processes of different varieties in order to identify and select traits, enhance their high-temperature resistance mechanism, and cultivate high-temperature resistant flue-cured tobacco varieties. Looking forward to future research on temperature stress in flue-cured tobacco, including exploring local germplasm resources, cultivating heat-resistant varieties, utilizing methods such as multi omics or cross omics to deeply explore the response mechanism of temperature stress in flue-cured tobacco, developing predictive research on temperature stress in flue-cured tobacco, and developing targeted management measures for stress resistance cultivation, in order to provide scientific support for the prevention of climate disasters and the enhancement of agricultural disaster reduction efficiency for flue-cured tobacco.

Abstract Aim This study aimed to develop a tool to measure paediatric specialist nurses' core competencies and examine the scale's validity and reliability. Design An exploratory quantitative study. Methods This study was performed in April 2022 with 302 paediatric specialist nurses in mainland China. Items were created through a literature review, a qualitative interview, and the Delphi method. The data were evaluated using descriptive statistics, independent sample t‐test, explanatory factor analysis, Pearson correlation coefficient, Cronbach’s alpha coefficient and split‐half reliability. Results The final scale consisted of five factors and 32 items. The factors were communication, coordination and judgement abilities; professional technology mastery ability; specialist knowledge mastery ability; medical‐related processes; and evidence‐based nursing competencies. The explained total variance of the five factors was 62.216%. The scale‐level and item‐level CVI of this scale was 1.00, and the mean CVR of the total scale was 0.788. The Pearson correlation coefficients of each dimension and the total dimension of the scale was 0.709–0.892, and within each dimension, it was 0.435–0.651. The Cronbach's α of this scale was 0.944, and its split‐half reliability was 0.883.

Abstract Neuropathy is a feature more frequently observed in pancreatic ductal adenocarcinoma (PDAC) than other tumors. Schwann cells, the most prevalent cell type in peripheral nerves, migrate toward tumor cells and associate with poor prognosis in PDAC. To unveil the effects of Schwann cells on the neuro-stroma niche, here we perform single-cell RNA-sequencing and microarray-based spatial transcriptome analysis of PDAC tissues. Results suggest that Schwann cells may drive tumor cells and cancer-associated fibroblasts (CAFs) to more malignant subtypes: basal-like and inflammatory CAFs (iCAFs), respectively. Moreover, in vitro and in vivo assays demonstrate that Schwann cells enhance the proliferation and migration of PDAC cells via Midkine signaling and promote the switch of CAFs to iCAFs via interleukin-1α. Culture of tumor cells and CAFs with Schwann cells conditioned medium accelerates PDAC progression. Thus, we reveal that Schwann cells induce malignant subtypes of tumor cells and CAFs in the PDAC milieu.

Abstract The spillover of oxygen species is fundamentally important in redox reactions, but the spillover mechanism has been less understood compared to that of hydrogen spillover. Herein Sn is doped into TiO2 to activate low-temperature (