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Straw is an important source of organic fertilizer for soil enrichment, however, the effects of different nitrogen(N) application rates and depths on straw decomposition microorganisms and carbon and nitrogen cycling under full straw return conditions in cool regions of Northeast China are not clear at this stage. In this paper, we applied macro-genome sequencing technology to investigate the effects of different N application rates (110 kg hm −2 , 120 kg hm −2 , 130 kg hm −2 , 140 kg hm −2 , 150 kg hm −2 ) and depths (0–15 cm, 15–30 cm) on straw decomposing microorganisms and N cycling in paddy fields in the cool zone of Northeast China. The results showed that (1) about 150 functional genes are involved in the carbon cycle process of degradation during the degradation of returned straw, of which the largest number of functional genes are involved in the methane production pathway, about 42, the highest abundance of functional genes involved in the citric acid cycle pathway. There are 22 kinds of functional genes involved in the nitrogen cycle degradation process, among which there are more kinds involved in nitrogen fixation, with 4 kinds. (2) High nitrogen application (150 kg hm −2 ) inhibited the carbon and nitrogen conversion processes, and the abundance of straw-degrading microorganisms and nitrogen-cycling functional genes was relatively high at a nitrogen application rate of 130 kg hm −2 . (3) Depth-dependent heterogeneity of the microbial community was reduced throughout the vertical space. At 71 days of straw return, the nitrogen cycling function decreased and some carbon functional genes showed an increasing trend with the increase of straw return depth. The nitrogen cycle function decreased with the increase of straw returning depth. The microbial community structure was best and the abundance of functional genes involved in the nitrogen cycling process was higher under the conditions of 0–15 cm of returning depth and 130 kg hm −2 of nitrogen application.

The degradation process of returned straw in rice fields can improve soil organic matter and promote sustainable agriculture. The degradation process of returned straw is a humification process as well as a mineralization process involving microorganisms and enzymes. However, the degradation process of returned straw, the effect on straw decomposing microorganisms and the regulatory mechanism on potential functionality under cool climate flooding conditions are currently unknown.For this purpose, we investigated the biodegradation of straw from a biodegradation point of view at 20, 40, 71, 104, and 137 d after return under conventional (130 kg hm −2 ), 1/3 straw return (2933 kg hm −2 ), 2/3 straw return (5866 kg hm −2 ), and full straw return (8800 kg hm −2 ) applications in cool climate rice fields.. The test found Paludibacteraceae and Archaeaceae were the dominant bacteria for straw degradation, and their relative abundance was highest when 2/3 of straw was returned to the field. The straw degradation extracellular enzyme activity was higher in the late return period (104 d). At this time, the potential functionality of the soil differed significantly among the different return amounts, with the best extracellular enzyme activity and potential functionality at the 2/3 straw return amount. Therefore, the optimal amount of rice straw returned to the field is 5866 kg hm −2 at the current conventional N application rate (130 kg hm −2 ) in the cold zone.

To address the challenges posed by weak early fault signal features, strong noise interference, low diagnostic accuracy, poor reliability when using single information sources, and the limited availability of high-quality samples in practical applications for permanent magnet synchronous motor (PMSM) bearings, this paper proposes an early bearing fault diagnosis method based on Hippopotamus Optimization Variational Mode Decomposition (HO-VMD) and weighted evidence fusion of current–vibration signals. The HO algorithm is employed to optimize the parameters of VMD for adaptive modal decomposition of current and vibration signals, resulting in the generation of intrinsic mode functions (IMFs). These IMFs are then selected and reconstructed based on their kurtosis to suppress noise and harmonic interference. Subsequently, the reconstructed signals are demodulated using the Teager–Kaiser Energy Operator (TKEO), and both time-domain and energy spectrum features are extracted. The reliability of these features is utilized to adaptively weight the basic probability assignment (BPA) functions. Finally, a weighted modified Dempster–Shafer evidence theory (WMDST) is applied to fuse multi-source feature information, enabling an accurate assessment of the PMSM bearing health status. The experimental results demonstrate that the proposed method significantly enhances the signal-to-noise ratio (SNR) and enables precise diagnosis of early bearing faults even in scenarios with limited sample sizes.

Background Glioblastoma (GBM) is the most malignant primary tumor in the brain, with poor prognosis and limited effective therapies. Although Bevacizumab (BEV) has shown promise in extending progression-free survival (PFS) treating GBM, there is no evidence for its ability to prolong overall survival (OS). Given the uncertainty surrounding BEV treatment strategies, we aimed to provide an evidence map associated with BEV therapy for recurrent GBM (rGBM). Methods PubMed, Embase, and the Cochrane Library were searched for the period from January 1, 1970, to March 1, 2022, for studies reporting the prognoses of patients with rGBM receiving BEV. The primary endpoints were overall survival (OS) and quality of life (QoL). The secondary endpoints were PFS, steroid use reduction, and risk of adverse effects. A scoping review and an evidence map were conducted to explore the optimal BEV treatment (including combination regimen, dosage, and window of opportunity). Results Patients with rGBM could gain benefits in PFS, palliative, and cognitive advantages from BEV treatment, although the OS benefits could not be verified with high-quality evidence. Furthermore, BEV combined therapy (especially with lomustine and radiotherapy) showed higher efficacy than BEV monotherapy in the survival of patients with rGBM. Specific molecular alterations (IDH mutation status) and clinical features (large tumor burden and double-positive sign) could predict better responses to BEV administration. A low dosage of BEV showed equal efficacy to the recommended dose, but the optimal opportunity window for BEV administration remains unclear. Conclusions Although OS benefits from BEV-containing regimens could not be verified in this scoping review, the PFS benefits and side effects control supported BEV application in rGBM. Combining BEV with novel treatments like tumor-treating field (TTF) and administration at first recurrence may optimize the therapeutic efficacy. rGBM with a low apparent diffusion coefficient (ADCL), large tumor burden, or IDH mutation is more likely to benefit from BEV treatment. High-quality studies are warranted to explore the combination modality and identify BEV-response subpopulations to maximize benefits.

To solve the problem of a low signal-to-noise ratio of fault signals and the difficulty in effectively and accurately identifying the fault state in the early stage of motor bearing fault occurrence, this paper proposes an early fault diagnosis method for bearings based on the Differential Local Mean Decomposition (DLMD) and fusion of current–vibration signals. This method uses DLMD to decompose the current signal and vibration signal, respectively, and weights the decomposed product function (PF) according to the kurtosis value to reconstruct the signal, and then fuses the reconstructed signals to obtain the current–vibration fusion signal after normalization, and then analyzes the fusion signal spectrally through the Hilbert envelope spectrum. Finally, the fusion signal is analyzed by the Hilbert envelope spectrum, and a clear fault characteristic frequency is obtained. The experimental results demonstrate that compared to traditional bearing fault diagnosis methods, the proposed method significantly improves the signal-to-noise ratio of fault signals, effectively enhances the sensitivity of early-stage fault detection in motor bearings, and improves the accuracy of fault identification.

Background The Mediterranean diet (MD) has shown promising results in preventing type 2 diabetes, particularly in Mediterranean and European populations. However, the applicability of these benefits to non-Mediterranean populations is unclear, with contradictory findings in the literature. Methods In this study, we included 12,575 participants without diabetes at baseline from the China Health and Nutrition Survey (CHNS). Dietary intake was measured by three consecutive 24-h dietary recalls. The Mediterranean diet adherence (MDA) was measured by a score scale that included nine components of vegetables, legumes, fruits, nuts, cereals, fish, red meat, dairy products, and alcohol. New-onset diabetes was defined as self-reported physician-diagnosed diabetes during the follow-up. Results During a median follow-up of 9.0 years, 445 (3.5%) subjects developed diabetes. Overall, there was an inverse association between the MDA score and new-onset diabetes (per score increment, HR 0.83, 95% CI 0.76–0.90). Moreover, age, sex, BMI, and energy intake significantly modified the association between the MDA score and the risk of new-onset diabetes (all P interactions < 0.05). Greater fruit, fish, and nut intake was significantly associated with a lower risk of new-onset diabetes. Conclusion There was an inverse association between Mediterranean diet adherence and new-onset diabetes in the Chinese population.

Dysregulated cell death leading to uncontrolled cell proliferation is a hallmark of cancer. Chemotherapy-induced cell death is critical for the success of cancer treatment but this process is impaired by metabolic byproducts. How these byproducts interfere with anti-cancer therapy is unclear. Here, we show that the metabolic byproduct acrolein derived from polyamines, tobacco smoke or fuel combustion, induces ferroptosis independently of ZBP1, while suppressing necroptosis in cancer cells by inhibiting the oligomerization of the necroptosis effector MLKL. Loss of the enzyme SAT1, which contributes to intracellular acrolein production, sensitizes cells to necroptosis. In mice, administration of an acrolein-trapping agent relieves necroptosis blockade and enhances the anti-tumor efficacy of the chemotherapeutic drug cyclophosphamide. Human patients with cancer coupled with a higher cell death activity but a lower expression of genes controlling polyamine metabolism exhibit improved survival. These findings highlight that the removal of metabolic byproducts improves the success of certain chemotherapies. Acrolein, a byproduct of polyamine metabolism and chemotherapeutic agents, is also found in cigarette smoke. Here the authors report that acrolein mediates spermine-induced ferroptosis, while in ferroptosis-resistant cancer cells, acrolein suppresses necroptosis by inhibiting the oligomerization of MLKL, contributing to chemotherapy resistance.

The expression dysregulation of microRNAs (miRNA) has been widely reported during cancer development, however, the underling mechanism remains largely unanswered. In the present work, we performed a systematic integrative study for genome-wide DNA methylation, copy number variation and miRNA expression data to identify mechanisms underlying miRNA dysregulation in lower grade glioma. We identify 719 miRNAs whose expression was associated with alterations of copy number variation or promoter methylation. Integrative multi-omics analysis revealed four subtypes with differing prognoses. These glioma subtypes exhibited distinct immune-related characteristics as well as clinical and genetic features. By construction of a miRNA regulatory network, we identified candidate miRNAs associated with immune evasion and response to immunotherapy. Finally, eight prognosis related miRNAs were validated to promote cell migration, invasion and proliferation through in vitro experiments. Our study reveals the crosstalk among DNA methylation, copy number variation and miRNA expression for immune regulation in glioma, and could have important implications for patient stratification and development of biomarkers for immunotherapy approaches. A miRNA multi-omics study reveals not only mechanisms for miRNA dysregulation, but also the tumor heterogeneity and immunological diversity within low grade glioma, and presents better prognostic value than traditional molecular markers.

Gliomas exhibit high heterogeneity and poor prognosis. Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. In this study, we perform proteomic profiling of gliomas using 343 formalin-fixed and paraffin-embedded tumor samples and 53 normal-appearing brain samples from 188 patients, integrating these data with genomic panel information and clinical outcomes. The proteomic analysis uncovers two distinct subgroups: Subgroup 1, the metabolic neural subgroup, enriched in metabolic enzymes and neurotransmitter receptor proteins, and Subgroup 2, the immune subgroup, marked by upregulation of immune and inflammatory proteins. These proteomic subgroups show significant differences in prognosis, tumorigenesis, microenvironment dysregulation, and potential therapeutics, highlighting the critical roles of metabolic and immune processes in glioma biology and patient outcomes. Through a detailed investigation of metabolic pathways guided by our proteomic findings, dihydropyrimidine dehydrogenase (DPYD) and thymidine phosphorylase (TYMP) emerge as potential prognostic biomarkers linked to the reprogramming of nucleotide metabolism. Functional validation in patient-derived glioma stem cells and animal models highlights nucleotide metabolism as a promising therapy target for gliomas. This integrated multi-omics analysis introduces a proteomic classification for gliomas and identifies DPYD and TYMP as key metabolic biomarkers, offering insights into glioma pathogenesis and potential treatment strategies. Comprehensive molecular characterisations could shed light on the high heterogeneity and poor prognosis of gliomas. Here, the authors perform proteomic profiling of 188 glioma patients, revealing immune and metabolic neuron-related subgroups as well as metabolic biomarkers linked to prognosis.

Increasing evidence highlights the role of aberrant circadian rhythm gene expression in glioblastoma (GBM) progression, but the impact of the circadian rhythm gene network on GBM molecular profiles and prognosis remains unclear. A total of 1042 GBM samples from six public datasets, TCGA and CGGA, were analyzed, with GBM samples stratified into three circadian core-gene patterns using unsupervised clustering based on the expression profiles of 17 circadian rhythm genes. The Limma R package identified differentially expressed genes (DEGs) among the three patterns, and a secondary clustering system, termed circadian-related gene pattern, was established based on DEGs. A circadian risk score was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, and the efficiency of these patterns and the circadian risk score in distinguishing molecular profiles and predicting prognosis was systematically analyzed. The relationship between the circadian risk score and response to immune or targeted therapy was examined using the GSE78200 and IMvigor210 datasets. The results showed that GBM patients were clustered into three circadian core-gene patterns based on the expression profiles of 17 core circadian genes, with distinct molecular profiles, malignant characteristics, and patient prognoses among the patterns. Thirty-two DEGs among these patterns were identified and termed circadian-related genes, and secondary clustering based on these 32 DEGs classified GBM samples into two circadian-related gene patterns, which also predicted molecular profiles and prognosis. A circadian risk scoring system was established, allowing the calculation of individual risk scores based on the expression of 10 genes, where GBM patients with lower circadian risk scores had prolonged overall survival and less aggressive molecular subtypes, while higher circadian risk scores correlated with better responses to MAPK-targeted therapy. In conclusion, this study established two clustering patterns based on 17 circadian rhythm genes or 32 circadian-related genes, enabling the rapid classification of GBM patients with distinct molecular profiles and prognoses, while the circadian risk scoring system effectively predicted survival, molecular profiles, and therapeutic responses for individual GBM patients, demonstrating that the circadian rhythm gene network can distinguish molecular profiles and prognosis in GBM.