Search

Abstract Background The occurrence of complications following radical gastrectomy for gastric cancer significantly impacts patients’ quality of life. Elderly patients are susceptible to postoperative complications. This study seeks to investigate the risk factors associated with Clavien-Dindo ≥IIgrade complications following radical gastrectomy for advanced gastric cancer in elderly patients, develop a nomogram risk prediction model, and validate its accuracy. Methods Retrospective collection of clinical and pathological data was conducted on 442 elderly patients with advanced gastric cancer who underwent radical gastrectomy at Shaanxi Provincial People’s Hospital from January 2015 to December 2020. They were randomly divided into a training set (n = 310) and a validation set (n = 132) in a 7:3 ratio. The severity of postoperative complications was graded using the Clavien-Dindo classification system, resulting in two complication groups: Clavien-Dindo

Abstract The rainfall variabilities of the West African and South American summer monsoons, pivotal for local and global climate systems, are strongly influenced by tropical Atlantic sea surface temperature anomalies. This study investigates the impacts of two recently identified Atlantic Niño types, central and eastern Atlantic Niño (CAN and EAN), on these monsoon systems using observational data and numerical experiments. During boreal summer, EAN events exhibit increased rainfall over West Africa compared to CAN events, indicating a strengthened West African summer monsoon. Enhanced moisture flux convergence from eastern Atlantic warming drives these wetting conditions during EAN events. Conversely, CAN events have a more pronounced influence on South American monsoon rainfall during austral summer, causing a rainfall anomaly dipole between the Amazon and eastern Brazil, suggesting an eastward shift in the South American summer monsoon rainfall belt. These rainfall changes are linked to cyclonic circulation anomalies over the southwest Atlantic Ocean, attributed to central Atlantic warming during CAN events. Furthermore, a statistical model assesses hindcast skills of rainfall variability in the two summer monsoon regions, affirming the benefits of separating Atlantic Niño into CAN and EAN events for improved seasonal climate predictions.

Acetaminophen (APAP) overdose can induce hepatocyte necrosis and acute liver failure in experimental rodents and humans. APAP is mainly metabolized via hepatic cytochrome P450 enzymes to generate the highly reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI), which forms acetaminophen protein adducts (APAP-adducts) and damages mitochondria, triggering necrosis. APAP-adducts and damaged mitochondria can be selectively removed by autophagy. Increasing evidence implies that the activation of autophagy may be beneficial for APAP-induced liver injury (AILI). In this minireview, we briefly summarize recent progress on autophagy, in particular, the pharmacological targeting of SQSTM1/p62 and TFEB in AILI.

Abstract In recent years, museums have become valuable venues for students to develop career awareness outside of school. However, optimizing the educational potential of museums and improving learners’ outcomes presents a significant challenge in museum learning design. This study integrates three main game elements—goals, stories, and role-playing—into museum visits to design a Gamified Learning Activity (GLA). To verify the effectiveness of the GLA, we conducted a quasi-experiment with 66 elementary school students at the Handicraft Museum. Using a mixed-methods approach with convergent parallel design, we collected quantitative data from knowledge tests and qualitative data from DAST (Draw-a-Scientist-Test) and interviews for a comprehensive analysis. The results showed that learners who participated in the GLA paid more attention to the details of the handicrafts, appreciated the craftsmen more, and eliminated stereotypes about the age of craftsmen. This indicates that the GLA not only enhances learners’ acquisition of museum knowledge but also has a profound impact on their non-cognitive aspects, such as career awareness.

Verticillium dahliae is a soilborne fungal pathogen that causes disease on many economically important crops. Based on the resistance or susceptibility of differential cultivars in tomato, isolates of V. dahliae are divided into three races. Avirulence (avr) genes within the genomes of the three races have also been identified. However, the functional role of the avr gene in race 3 isolates of V. dahliae has not been characterized. In this study, bioinformatics analysis showed that VdR3e, a cysteine-rich secreted protein encoded by the gene characterizing race 3 in V. dahliae, was likely obtained by horizontal gene transfer from the fungal genus Bipolaris. We demonstrate that VdR3e causes cell death by triggering multiple defense responses. In addition, VdR3e localized at the periphery of the plant cell and triggered immunity depending on its subcellular localization and the cell membrane receptor BAK1. Furthermore, VdR3e is a virulence factor and shows differential pathogenicity in race 3-resistant and -susceptible hosts. These results suggest that VdR3e is a virulence factor that can also interact with BAK1 as a pathogen-associated molecular pattern (PAMP) to trigger immune responses. IMPORTANCE Based on the gene-for-gene model, research on the function of avirulence genes and resistance genes has had an unparalleled impact on breeding for resistance in most crops against individual pathogens. The soilborne fungal pathogen, Verticillium dahliae, is a major pathogen on many economically important crops. Currently, avr genes of the three races in V. dahliae have been identified, but the function of avr gene representing race 3 has not been described. We investigated the characteristics of VdR3e-mediated immunity and demonstrated that VdR3e acts as a PAMP to activate a variety of plant defense responses and induce plant cell death. We also demonstrated that the role of VdR3e in pathogenicity was host dependent. This is the first study to describe the immune and virulence functions of the avr gene from race 3 in V. dahliae, and we provide support for the identification of genes mediating resistance against race 3.

Abstract Although it is well documented that mountains tend to exhibit high biodiversity, how geological processes affect the assemblage of montane floras is a matter of ongoing research. Here, we explore landform-specific differences among montane floras based on a dataset comprising 17,576 angiosperm species representing 140 Chinese mountain floras, which we define as the collection of all angiosperm species growing on a specific mountain. Our results show that igneous bedrock (granitic and karst-granitic landforms) is correlated with higher species richness and phylogenetic overdispersion, while the opposite is true for sedimentary bedrock (karst, Danxia, and desert landforms), which is correlated with phylogenetic clustering. Furthermore, we show that landform type was the primary determinant of the assembly of evolutionarily older species within floras, while climate was a greater determinant for younger species. Our study indicates that landform type not only affects montane species richness, but also contributes to the composition of montane floras. To explain the assembly and differentiation of mountain floras, we propose the ‘floristic geo-lithology hypothesis’, which highlights the role of bedrock and landform processes in montane floristic assembly and provides insights for future research on speciation, migration, and biodiversity in montane regions.

IntroductionHopea hainanensis Merrill & Chun is considered a keystone and indicator species in the tropical lowland rainforests of Hainan Island. Owing to its high-quality timber, H. hainanensis has been heavily exploited, leading to its classification as a first-class national protected plant in China and a plant species with extremely small populations (PSESPs).MethodsThis study analyzed genome-wide single nucleotide polymorphisms obtained through restriction site-associated DNA sequencing from 78 adult trees across 10 H. hainanensis populations on Hainan Island.Results and discussionThe nucleotide diversity of the sampled populations ranged from 0.00096 to 0.00138, which is lower than that observed in several other PSESPs and endangered tree species. Bayesian unsupervised clustering, principal component analysis, and neighbor-joining tree reconstruction identified three to five genetic clusters in H. hainanensis, most of which were geographically widespread and shared by multiple populations. Demographic history analysis based on pooled samples indicated that the decline in the H. hainanensis population began approximately 20,000 years ago, starting from an ancestral population size of approximately 10,000 individuals. The reduction in population size accelerated approximately 4,000 years ago and has continued to the present, resulting in a severely reduced population on Hainan Island. Intensified genetic drift in small and isolated H. hainanensis populations may contribute to moderate differentiation between some of them, as revealed by pairwise Fst. In conclusion, our conservation genomic study confirms a severe population decline and an extremely low level of nucleotide variation in H. hainanensis on Hainan Island. These findings provide critical insights for the sustainable management and genetic restoration of H. hainanensis on Hainan Island.

ABSTRACT To quickly and accurately assess tea plant growth, this study aims to find a new way to predict the chlorophyll content in tea plant canopies using machine learning. Using remotely piloted aircraft equipped with multispectral cameras, images of tea plantation areas are captured and reflectance from four spectral bands is extracted, leading to the calculation of vegetation indices. Simultaneously, chlorophyll relative content in the tea plant canopies was collected on the ground using a detector. Four models, namely Random Forest (RF), Backpropagation neural network (BPNN), Radial basis function network (RBFN), and General Regression Neural Network (GRNN), were constructed to predict the chlorophyll relative content in tea plant canopies. Subsequently, important remote sensing variables were identified through RF filtering, followed by a comparison of the predictive performance of machine learning models under different input conditions. Lastly, by integrating the Sparrow Search Algorithm (SSA) to optimize the smoothing factor in the GRNN, the study explores the impact of optimization algorithms on the predictive performance of the GRNN model. Experiments indicate that within the established machine learning models, the GRNN demonstrates the highest predictive accuracy. By ranking the importance of remote sensing variables through RF, 18 significant remote sensing variables were selected, which enhanced the predictive accuracy of the machine learning models. The optimization of the GRNN smoothing factor through the SSA algorithm can significantly enhance the predictive accuracy of the GRNN model. Based on a series of experiments, the established RFSSA-GRNN prediction model demonstrates good predictive performance, with an reaching 0.84.

Sulfate-reducing bacteria (SRB) are essential functional microbial taxa for degrading organic matter (OM) in anoxic marine environments. However, there are little experimental data regarding how SRB regulates microbial communities. Here, we applied a top-down microbial community management approach by inhibiting SRB to elucidate their contributions to the microbial community during OM degradation. Based on the highly replicated microcosms (n = 20) of five different incubation stages, we found that many microbial community properties were influenced after inhibiting SRB, including the composition, structure, network, and community assembly processes. We also found a strong coexistence pattern between SRB and other abundant phylogenetic lineages via positive frequency-dependent selection. The relative abundances of the families Synergistaceae, Peptostreptococcaceae, Dethiosulfatibacteraceae, Prolixibacteraceae, Marinilabiliaceae, and Marinifilaceae were simultaneously suppressed after inhibiting SRB during OM degradation. A close association between SRB and the order Marinilabiliales among coexisting taxa was most prominent. They contributed to preserved modules during network successions, were keystone nodes mediating the networked community, and contributed to homogeneous ecological selection. The molybdate tolerance test of the isolated strains of Marinilabiliales showed that inhibited SRB (not the inhibitor of SRB itself) triggered a decrease in the relative abundance of Marinilabiliales. We also found that inhibiting SRB resulted in reduced pH, which is unsuitable for the growth of most Marinilabiliales strains, while the addition of pH buffer (HEPES) in SRB-inhibited treatment microcosms restored the pH and the relative abundances of these bacteria. These data supported that SRB could modify niches to affect species coexistence. IMPORTANCE Our model offers insight into the ecological properties of SRB and identifies a previously undocumented dimension of OM degradation. This targeted inhibition approach could provide a novel framework for illustrating how functional microbial taxa associate the composition and structure of the microbial community, molecular ecological network, and community assembly processes. These findings emphasize the importance of SRB during OM degradation. Our results proved the feasibility of the proposed study framework, inhibiting functional taxa at the community level, for illustrating when and to what extent functional taxa can contribute to ecosystem services.

In this editors corner, the section editors were asked to indicate where they see the autophagy field heading and to suggest what they consider to be key unanswered questions in their specialty area.

Abstract With the advent of the big data era, edge cloud computing has developed rapidly. In this era of popular digital music, various technologies have brought great convenience to online music education. But vast databases of digital music prevent educators from making specific-purpose choices. Music recommendation will be a potential development direction for online music education. In this paper, we propose a deep learning model based on multi-source information fusion for music recommendation under the scenario of edge-cloud computing. First, we use the music latent factor vector obtained by the Weighted Matrix Factorization (WMF) algorithm as the ground truth. Second, we build a neural network model to fuse multiple sources of music information, including music spectrum extracted from extra music information to predict the latent spatial features of music. Finally, we predict the user’s preference for music through the inner product of the user vector and the music vector for recommendation. Experimental results on public datasets and real music data collected by edge devices demonstrate the effectiveness of the proposed method in music recommendation.

Abstract Aim Small bowel obstruction is a common condition that requires emergency surgery. Slow recovery of bowel function after surgery or the occurrence of one or more complications can exacerbate the disease and result in severe small bowel obstruction (SSBO), significantly impacting recovery. It is characterized by a failure to regain enteral nutrition promptly, requiring long-term intensive care. Therefore, it is necessary to identify factors that predict SSBO, to allow early intervention for patients likely to develop this condition. Methods Of the 260 patients who underwent emergency or elective surgery for small bowel obstruction between January 2018 and December 2022, 45 developed SSBO. The least absolute shrinkage and selection operator regression model was applied to optimize factor selection and multivariable logistic regression analysis was used to construct a predictive model. The performance and clinical utility of the nomogram were determined and internal validation was conducted. In addition, the effects of the Houpu Paiqi mixture on postoperative recovery were analyzed by comparing the clinical data of 28 patients who were treated with the mixture and 61patients who did not receive it. Results The predictors included in the prediction nomogram were age, peritonitis, intestinal resection and anastomosis, complications, operation time, Acute Physiology and Chronic Health Evaluation II score, white blood cell count, and procalcitonin level. The model had an area under the receiver operating characteristic curve of 0.948 (95% confidence interval: 0.814–0.956). Decision curve analysis demonstrated that the SSBO risk nomogram had a good net clinical benefit. In addition, treatment with the Houpu Paiqi mixture reduced postoperative exhaust time, postoperative defecation time, time to first postoperative liquid feed, and length of stay in hospital. Conclusions We developed a nomogram that can assist clinicians in identifying patients at greater risk of SSBO, which may aid in early diagnosis and intervention. Additionally, we found that the Houpu Paiqi mixture promoted postoperative recovery.

Glutamine synthetase (GS) catalyzes de novo synthesis of glutamine that facilitates cancer cell growth. In the liver, GS functions next to the urea cycle to remove ammonia waste. As a dysregulated urea cycle is implicated in cancer development, the impact of GS's ammonia clearance function has not been explored in cancer. Here, we show that oncogenic activation of β-catenin (encoded by CTNNB1) led to a decreased urea cycle and elevated ammonia waste burden. While β-catenin induced the expression of GS, which is thought to be cancer promoting, surprisingly, genetic ablation of hepatic GS accelerated the onset of liver tumors in several mouse models that involved β-catenin activation. Mechanistically, GS ablation exacerbated hyperammonemia and facilitated the production of glutamate-derived nonessential amino acids, which subsequently stimulated mechanistic target of rapamycin complex 1 (mTORC1). Pharmacological and genetic inhibition of mTORC1 and glutamic transaminases suppressed tumorigenesis facilitated by GS ablation. While patients with hepatocellular carcinoma, especially those with CTNNB1 mutations, have an overall defective urea cycle and increased expression of GS, there exists a subset of patients with low GS expression that is associated with mTORC1 hyperactivation. Therefore, GS-mediated ammonia clearance serves as a tumor-suppressing mechanism in livers that harbor β-catenin activation mutations and a compromised urea cycle.

Acute pancreatitis is a common inflammatory gastrointestinal disease without any successful treatment. Pancreatic exocrine acinar cells have high rates of protein synthesis to produce and secrete large amounts of digestive enzymes. When the regulation of organelle and protein homeostasis is disrupted, it can lead to endoplasmic reticulum (ER) stress, damage to the mitochondria and improper intracellular trypsinogen activation, ultimately resulting in acinar cell damage and the onset of pancreatitis. To balance the homeostasis of organelles and adapt to protect themselves from organelle stress, cells use protective mechanisms such as autophagy. In the mouse pancreas, defective basal autophagy disrupts ER homoeostasis, leading to ER stress and trypsinogen activation, resulting in spontaneous pancreatitis. In this review, we discuss the regulation of autophagy and its physiological role in maintaining acinar cell homeostasis and function. We also summarise the current understanding of the mechanisms and the role of defective autophagy at multiple stages in experimental pancreatitis induced by cerulein or alcohol.

Integrated logic circuits using atomically thin, two‐dimensional (2D) materials offer several potential advantages compared to established silicon technologies such as increased transistor density, circuit complexity, and lower energy dissipation leading to scaling benefits. In this article, a novel approach to achieve tunable doping in 2D semiconductors is explored to achieve complementary transistors and logic integration. By selectively transferring WSe2 onto hBN and SiO2 substrates, complementary transistor behavior (n‐ and p‐type) was achieved using a UV light source and electrostatic activation. Furthermore, advanced characterization techniques, including high‐resolution transmission electron microscopy (HRTEM) and Kelvin probe force microscopy (KPFM), provided insights into the chemical composition and surface potential changes after UV writing. Finally, a logic inverter was successfully implemented using selectively photo‐induced doped WSe2 transistors, showcasing the potential for practical logic applications. This innovative method opens new avenues for designing energy‐efficient and reconfigurable 2D semiconductor circuits, addressing key challenges in modern electronics.

Fatty liver is a highly heterogenous condition driven by various pathogenic factors in addition to the severity of steatosis. Protein insufficiency has been causally linked to fatty liver with incompletely defined mechanisms. Here we report that fatty liver is a sulfur amino acid insufficient state that promotes metabolic inflexibility via limiting coenzyme A availability. We demonstrate that the nutrient-sensing transcriptional factor EB synergistically stimulates lysosome proteolysis and methionine adenosyltransferase to increase cysteine pool that drives the production of coenzyme A and glutathione, which support metabolic adaptation and antioxidant defense during increased lipid influx. Intriguingly, mice consuming an isocaloric protein-deficient Western diet exhibit selective hepatic cysteine, coenzyme A and glutathione deficiency and acylcarnitine accumulation, which are reversed by cystine supplementation without normalizing dietary protein intake. These findings support a pathogenic link of dysregulated sulfur amino acid metabolism to metabolic inflexibility that underlies both overnutrition and protein malnutrition-associated fatty liver development.