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The purpose of this study was to look into the toxicity of arecoline on human stomach mucosal epithelial cells GES-1. GES-1 cells were treated with different concentrations (60, 90, 120, 150 μg/mL) of arecoline, detection of GES-1 cell viability, reactive oxygen species levels (ROS) and mitochondrial membrane potential (MMP). The levels of glutathione (GSH), superoxide dismutase (SOD), lactate dehydrogenase (LDH), adenosine triphosphate (ATP) enzymes were measured in GES-1 cellls. And the leves of tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), vascular endothelial growth factor (VEGF), transforming growth factor-β (TGF-β) were measured in GES-1 cells. Compared with the control group, the shape of GES-1 cells was altered after arecoline stimulation, with the lowest cell viability rate reduced to 24%, the highest reactive oxygen species level increased to 12.5 fold, and the lowest mitochondrial membrane potential decreased to 10.4%. Under 150 μg/mL arecoline stimulation, T-ATPase and Na+K+-ATPase activity decreased to 42.31% and 39.84%, GSH and SOD decreased by 40.23% and 34.1%, respectively, LDH increased by 30.46%, TNF-α, IL-6, VEGF and TGF-β levels increased by 4.67%, 10.2%, 23.14% and 22.83%. The results indicate that arecoline can produce oxidative stress and induce inflammatory factors that cause toxic damage to GES-1 cells.

With the development of underwater sonar detection technology, simultaneous localization and mapping (SLAM) approach has attracted much attention in underwater navigation field in recent years. But the weak detection ability of a single vehicle limits the SLAM performance in wide areas. Thereby, cooperative SLAM using multiple vehicles has become an important research direction. The key factor of cooperative SLAM is timely and efficient sonar image transmission among underwater vehicles. However, the limited bandwidth of underwater acoustic channels contradicts a large amount of sonar image data. It is essential to compress the images before transmission. Recently, deep neural networks have great value in image compression by virtue of the powerful learning ability of neural networks, but the existing sonar image compression methods based on neural network usually focus on the pixel-level information without the semantic-level information. In this paper, we propose a novel underwater acoustic transmission scheme called UAT-SSIC that includes semantic segmentation-based sonar image compression (SSIC) framework and the joint source-channel codec, to improve the accuracy of the semantic information of the reconstructed sonar image at the receiver. The SSIC framework consists of Auto-Encoder structure-based sonar image compression network, which is measured by a semantic segmentation network's residual. Considering that sonar images have the characteristics of blurred target edges, the semantic segmentation network used a special dilated convolution neural network (DiCNN) to enhance segmentation accuracy by expanding the range of receptive fields. The joint source-channel codec with unequal error protection is proposed that adjusts the power level of the transmitted data, which deal with sonar image transmission error caused by the serious underwater acoustic channel. Experiment results demonstrate that our method preserves more semantic information, with advantages over existing methods at the same compression ratio. It also improves the error tolerance and packet loss resistance of transmission.

Abstract Background Previous studies have suggested that oil-based contrast agents used during hysterosalpingography (HSG) in infertile patients can enhance fertility. However, limited research has investigated the effect of oil-based contrast medium specifically in individuals with endometriosis-related infertility. Objective This study aims to explore the impact of oil-based contrast medium on fertility outcomes in women with endometriosis-related infertility. Methods Conducted at the First Affiliated Hospital of Guangxi Medical University (January 2020 to June 2022), the study included 512 patients undergoing HSG. Patients were categorized into oil-based and non-oil-based groups, and after propensity score matching, demographic characteristics were compared. Main outcomes included clinical pregnancy rates, live birth rates, early miscarriage rates, and ectopic pregnancy rates. Results In our analysis, the Oil-based group showed significantly better outcomes compared to the Non-oil-based group. Specifically, the Oil-based group had higher clinical pregnancy rates (51.39% vs. 27.36%) and increased live birth rates (31.48% vs. 19.93%). This trend held true for expectant treatment, IUI, and IVF/ICSI, except for surgical treatment where no significant difference was observed. After adjusting for various factors using propensity score matching, the Non-oil-based group consistently exhibited lower clinical pregnancy rates compared to the Oil-based group. The Odds Ratio (OR) was 0.38 (95%CI: 0.27–0.55) without adjustment, 0.34 (0.22–0.51) in multivariable analysis, 0.39 (0.27–0.57) using inverse probability of treatment weighting (IPTW), and 0.22 (0.14–0.35) in propensity score matching. Conclusion Oil-based contrast medium used in HSG for women with endometriosis-related infertility is associated with higher clinical pregnancy rates and live birth rates compared to Non-oil-based contrast medium.

Abstract Background Survival rates of young women undergoing cancer treatment have substantially improved, with a focus on post-treatment quality of life. Ovarian tissue transplantation (OTT) is a viable option to preserve fertility; however, there is no consensus on the optimal transplantation site. Most studies on OTT are nonrandomized controlled trials with limited sample sizes and uncontrolled statistical analyses, leaving the question of which transplant site yields the highest chance of achieving a live birth unanswered. Objective This meta-analysis aimed to assess the effect of different ovarian transplant sites on postoperative reproductive outcomes. Methods We adhered to the PRISMA Reporting Items for Systematic Reviews and Meta-Analyses recommendations. Systematic searches were conducted in PubMed, Embase, Web of Science, and the Cochrane Library from inception to September 17, 2023. The inclusion criteria were as follows: (1) women who underwent OTT with a desire for future childbirth, and (2) reports of specific transplant sites and corresponding pregnancy outcomes. The exclusion criteria included the inability to isolate or extract relevant outcome data, case reports, non-original or duplicate data, and articles not written in English. Results Twelve studies (201 women) were included in the meta-analysis of cumulative live birth rates (CLBR) after OTT. The CLBR, which encompasses both spontaneous pregnancies and those achieved through assisted reproductive technology (ART) following OTT to the ovarian site, was 21% (95% CI: 6–40, I2: 52.81%, random effect). For transplantation to the pelvic site, the live birth rate was 30% (95% CI: 20–40, I2: 0.00%, fixed effect). Combining transplantation to both the pelvic and ovarian sites resulted in a live birth rate of 23% (95% CI: 11–36, I2: 0.00%, fixed effect). Notably, heterotopic OTT yielded a live birth rate of 3% (95% CI: 0–17, I2: 0.00%, fixed effect). Conclusion Pregnancy outcomes were not significantly different after orthotopic ovarian transplantation, and pregnancy and live birth rates after orthotopic OTT were significantly higher than those after ectopic transplantation. Registration Number INPLASY202390008.

Event type discovery in open domains aims to automate the induction of event types from completely unlabeled text data. Conventionally, small models utilize clustering techniques to address this task. Nonetheless, the fully unsupervised nature of these methods results in suboptimal performance by small models in this context. Recently, large language models (LLMs) have demonstrated excellent capabilities in contextual understanding, providing additional relevant information for specific task scenarios, albeit with challenges in precision and cost effectiveness. In this paper, we use LLM to guide the clustering of event texts and distill this process into a fine-tuning task for training smaller pre-trained language models. This approach enables effective event type discovery even in scenarios lacking annotated data. The study unfolds in three stages: in action acquisition, leveraging LLMs to extract type-relevant information from each event text, ensuring that the event representations are particular to task-specific details; in clustering refinement and dual-fine-tune, LLMs refine results from both task-agnostic and task-specific perspectives, with the refinement process designed as fine-tuning tasks under different viewpoints to adjust encoders; and in type generation, post-clustering, LLMs generate meaningful event type labels for each cluster. Experiments show that our method outperforms current state-of-the-art approaches and excels in event type discovery tasks even in completely open-domain with no labeled data.

ABSTRACTAutophagy is a central biodegradation pathway critical in eliminating intracellular cargo to maintain cellular homeostasis and improve stress resistance. At the same time, the key component of the mitogen-activated protein kinase cascade regulating cell wall integrity signaling MoMkk1 has an essential role in the autophagy of the rice blast fungus Magnaporthe oryzae. Still, the mechanism of how MoMkk1 regulates autophagy is unclear. Interestingly, we found that MoMkk1 regulates the autophagy protein MoAtg9 through phosphorylation. MoAtg9 is a transmembrane protein subjected to phosphorylation by autophagy-related protein kinase MoAtg1. Here, we provide evidence demonstrating that MoMkk1-dependent MoAtg9 phosphorylation is required for phospholipid translocation during isolation membrane stages of autophagosome formation, an autophagic process essential for the development and pathogenicity of the fungus. In contrast, MoAtg1-dependent phosphorylation of MoAtg9 negatively regulates this process, also impacting growth and pathogenicity. Our studies are the first to demonstrate that MoAtg9 is subject to MoMkk1 regulation through protein phosphorylation and that MoMkk1 and MoAtg1 dichotomously regulate autophagy to underlie the growth and pathogenicity of M. oryzae.IMPORTANCEMagnaporthe oryzae utilizes multiple signaling pathways to promote colonization of host plants. MoMkk1, a cell wall integrity signaling kinase, plays an essential role in autophagy governed by a highly conserved autophagy kinase MoAtg1-mediated pathway. How MoMkk1 regulates autophagy in coordination with MoAtg1 remains elusive. Here, we provide evidence that MoMkk1 phosphorylates MoAtg9 to positively regulate phospholipid translocation during the isolation membrane or smaller membrane structures stage of autophagosome formation. This is in contrast to the negative regulation of MoAtg9 by MoAtg1 for the same process. Intriguingly, MoMkk1-mediated MoAtg9 phosphorylation enhances the fungal infection of rice, whereas MoAtg1-dependant MoAtg9 phosphorylation significantly attenuates it. Taken together, we revealed a novel mechanism of autophagy and virulence regulation by demonstrating the dichotomous functions of MoMkk1 and MoAtg1 in the regulation of fungal autophagy and pathogenicity.

Abstract The utilization of novel noncollinear antiferromagnetic materials holds great promise for the development of energy‐efficient spintronic devices. However, only a few studies have reported on the all‐electrical control of perpendicular magnetization switching using noncollinear antiferromagnets as the spin source, and the underlying mechanism behind the unconventional spin‐orbit torque (SOT) is still a topic of debate. In this work, deterministic perpendicular magnetization switching in Mn3Sn/CoTb bilayers is successfully achieved. Compared to the control samples with heavy metal as the spin source, the critical switching current density is over one order of magnitude reduced, indicating an enhanced efficiency of the out‐of‐plane charge‐to‐spin conversion in the textured Mn3Sn films. The influence of film thickness and growth temperature on the efficiency of different spin polarizations suggests potential roles of crystal quality and spin texture in spin diffusion with different spin polarization directions. These findings provide valuable insights into the crystal structure, spin‐orbit torque effects, and charge‐to‐spin conversion in Mn3Sn films, highlighting the importance of understanding interface and bulk contributions in antiferromagnetic spin transport phenomena.

IntroductionInfertility affects 8-12% of couples worldwide, with 15-30% classified as unexplained infertility (UI). Thyroid autoimmunity (TAI), the most common autoimmune disorder in women of reproductive age, may impact fertility and pregnancy outcomes. However, the underlying mechanism is unclear. This study focuses on intrauterine insemination (IUI) and its potential association with TAI in UI patients. It is the first meta-analysis following a comprehensive literature review to improve result accuracy and reliability.MethodsRetrospective cohort study analyzing 225 women with unexplained infertility, encompassing 542 cycles of IUI treatment. Participants were categorized into TAI+ group (N=47, N= 120 cycles) and TAI- group (N=178, N= 422 cycles). Additionally, a systematic review and meta-analyses following PRISMA guidelines were conducted, incorporating this study and two others up to June 2023, totaling 3428 IUI cycles. ResultsAnalysis revealed no significant difference in independent variables affecting reproductive outcomes. However, comparison based on TAI status showed significantly lower clinical pregnancy rates (OR: 0.43, P= 0.028, 95%CI: 0.20-0.93) and live birth rate (OR: 0.20, P= 0.014, 95%CI: 0.05 ~ 0.71) were significantly lower than TAI- group. There was no significant difference in pregnancy rate between the two groups (OR: 0.61, P= 0.135, 95%CI: 0.32-1.17). However, the meta-analysis combining these findings across studies did not show statistically significant differences in clinical pregnancy rates (OR:0.77, P=0.18, 95%CI: 0.53-1.13) or live birth rates (OR: 0.68, P=0.64, 95%CI: 0.13-3.47) between the TAI+ and TAI- groups. DiscussionOur retrospective cohort study found an association between TAI and reduced reproductive outcomes in women undergoing IUI for unexplained infertility. However, the meta-analysis incorporating other studies did not yield statistically significant associations. Caution is required in interpreting the relationship between thyroid autoimmunity and reproductive outcomes. Future studies should consider a broader population and a more rigorous study design to validate these findings. Clinicians dealing with women with unexplained infertility and TAI should be aware of the complexity of this field and the limitations of available evidence.

Abstract Background The roles of low molecular mass polypeptide 2 (LMP2) and transporter-associated with antigen processing (TAP2) in tumorigenesis are controversial. Here we aimed to explore the effect of LMP2 and TAP2 on the oncogenesis and metastasis of cervical cancer cells. Methods The expressions of LMP2 and TAP2 in cervical cancer and normal tissues were determined by qPCR. Plate colony formation, cell counting kit-8 analysis and in vivo tumor xenograft assays were used to detect the tumor growth. Wound healing and transwell assays were used to detect the metastasis of cervical cancer. Gelatin zymography and western blotting assays were used to detect the effect of LMP2 and TAP2 on the EMT and Wnt/β-catenin pathway in cervical cancer cells. Results In the present study, we reported that LMP2 and TAP2 levels were overexpressed in cervical cancer. Overexpression of LMP2 and TAP2 impaired the proliferation of Hela cells. In vivo studies substantiated that LMP2 and TAP2 antagonized tumor growth. Likewise, LMP2 and TAP2 overexpression decreased the migration and invasion ability of Hela cells by regulating the process of epithelial-mesenchymal transition (EMT). Mechanically, LMP2 and TAP2 subverted the protein abundance of Wnt1 and β-catenin, thereby downregulating their downstream targets Cyclin D1 and c-Myc. In addition, Wnt1 overexpression partially rescued the observed consequences of ectopic expression of LMP2 and TAP2 in cervical cancer cells. Taken together, our study revealed that LMP2 and TAP2 suppress the oncogenesis and metastasis of cervical cancer cells by Wnt/β-catenin pathway and altering EMT. Conclusion LMP2 and TAP2 may inhibit the oncogenesis and metastasis of cervical cancer cells by inhibiting the process of EMT and the Wnt/β-catenin signaling pathway, which may provide important insight into prospective targets for the treatment of cervical cancer.

To investigate the ameliorative effect of the D-α-tocopheryl acetate compound on D-galactose-induced aging in mice, the in vitro antioxidant capacity of the compound of natural oils+phytosterols (VEO), the compound of D-α-tocopheryl acetate+phytosterol (VEZ), and the compound of D-α-tocopheryl acetat+phytosterol+astaxanthin (VEX) were measured. The aging model was established using mice injected with D-galactose on the back of the neck, while the intervention was carried out with different compounds. The results showed that all three groups of compounds had strong antioxidant effects, with the VEZ group showing better in vitro antioxidant effects. Compared with the aging model mice, the intervention of the three compounds increased glutathione peroxidase (GSH-Px) and total antioxidant capacity (T-AOC), decreased malondialdehyde (MDA) (P

In this experiment, dried bracken was used as the raw material, and an ultrasound-assisted method was used to extract and calculate the extraction rate of bracken crude polysaccharides. The bracken polysaccharides were then purified using the Sevage method, macroporous resin, and dialysis method. Chemical composition and physicochemical properties of bracken polysaccharides were determined. Infrared spectroscopy, Congo red test, high performance liquid chromatography, periodic acid oxidation, iodine-potassium iodide reaction, and other methods were used to characterize the structure of bracken polysaccharides, and the antioxidant capacity of bracken polysaccharides on DPPH free radicals, ABTS+ free radical scavenging ability, and FRAP ability were measured in vitro. The extraction rate of bracken crude polysaccharides was 8.91%, the content of purified bracken polysaccharides was 76.95%, the total phenolic content was 1.03%, the content of flavonoids was 1.90%, the sulfate content was 21.38%, and the content of uronic acid was 29.26%, according to the experimental results. The infrared spectroscopy results revealed that bracken polysaccharides had typical polysaccharide absorption peaks, as well as uronic acid and partial pyranose. The monosaccharide composition results revealed that bracken polysaccharide was a heteropolysaccharide made up of ten monosaccharides. Long side chains, more branched chains, complex chain structure, and no three-stranded helix structure of bracken polysaccharide. In vitro antioxidant testing revealed that bracken polysaccharides had a high ABTS+ radical scavenging ability (up to 92.61%), a good iron ion reduction ability (40.15±1.40 mg/g in Trolox equivalent), and a high DPPH free radical scavenging ability. The above findings will serve as a foundation for further research into the structure-activity relationship of bracken polysaccharides, as well as a theoretical reference for the rational use of bracken resources.

Abstract Oomycetes, such as Pythium species, contain numerous devastating plant pathogens that inflict substantial economic losses worldwide. Although CRISPR/Cas9-based genome editing is available, the selection markers available for genetic transformation in these species are limited. In this study, a mutated version of the Phytophthora capsici oxysterol-binding protein-related protein 1 (PcMuORP1), known to confer oxathiapiprolin resistance, was introduced into the CRISPR/Cas9 system for in situ complementation in Pythium ultimum. We targeted PuLLP, which encodes a loricrin-like protein, and showed significant downregulation when the Puf RNA-binding protein-encoding gene PuM90 was knocked out. The PuLLP knockout mutants could not produce oospores, indicating a similar biological function as PuM90. The reintroduction of PuLLP into the knockout mutant using PcMuORP1 as a selection marker restored oospore production. Further comparisons with the conventional selection marker NPTII indicated that PcMuORP1 could be applied at a lower concentration and cost, resulting in a higher screening efficiency. Successive subculturing in the absence of selective pressure showed that PcMuORP1 had little long-term effect on the fitness of transformants. Hence, it could be reused as an alternative selection marker. This study demonstrates the successful implementation of the PcMuORP1 gene as a selection marker in the genetic transformation of Py. ultimum and reveals the loricrin-like protein PuLLP as a sexual reproduction-related factor downstream of the Puf RNA-binding protein PuM90. Overall, these results will help accelerate the functional genomic investigation of oomycetes.

As an advanced surface-strengthening technology, laser shock peening (LSP) is suitable for strengthening high-energy beam additive manufacturing components by improving the uneven temperature distribution and mechanical anisotropy problems. The present study investigated the influence of multiple LSP impacts on the microstructure evolution and wear performance of wire-based laser directed energy deposition (LDED) 17-4 PH stainless steel. Results showed that with the increase of LSP impacts, the average grain size of the wire-based LDED layer decreases and the dislocation density increases. Meanwhile, the residual stress was completely converted from tensile state to compressive state, and reaches the maximum value of 424 ± 15 MPa. In addition, the significant improvement of microhardness and wear resistance after 3 LSP impacts is attributed to the combined effects of grain refinement and dislocation strengthening.

Abstract Background The aim of this retrospective study was to investigate whether oral antibiotics (doxycycline and metronidazole) combined with intrauterine perfusion (gentamicin and dexamethasone) are beneficial for patients with repeated implantation failure (RIF) and chronic endometritis (CE) to improve clinical pregnancy outcomes. Methods Patients with RIF and CE were diagnosed using hysteroscopy and histology together. A total of 42 patients were enrolled in the study. All patients received oral antibiotics (doxycycline combined with metronidazole) and 22 patients underwent intrauterine perfusion (gentamicin combined with dexamethasone) immediately after the end of oral antibiotic therapy. Pregnancy outcomes were evaluated during the first in vitro fertilization (IVF) and embryo transfer (ET) cycle. Results For the first D3 ET after treatment with oral antibiotics (doxycycline and metronidazole) combined with intrauterine perfusion (gentamicin and dexamethasone), higher embryo implantation rate (30.95% vs. 26.67%, P = 0.0308), clinical pregnancy rate (30% vs. 50%, P

Zero-shot event detection aims to involve the automatic discovery and classification of new events within unstructured text. Current zero-shot event detection methods have not considered addressing the problem more effectively from the perspective of improving event representations. In this paper, we propose dual-contrastive prompting (COPE) model for learning event representations to address zero-shot event detection, which leverages prompts to assist in generating event embeddings using a pretrained language model, and employs a contrastive fusion approach to capture complex interaction information between trigger representations and sentence embeddings to obtain enhanced event representations. Firstly, we introduce a sample generator to create ordered contrastive sample sequences with varying degrees of similarity for each event instance, aiding the model in better distinguishing different types of events. Secondly, we design two distinct prompts to obtain trigger representations and event sentence embeddings separately. Thirdly, we employ a contrastive fusion module, where trigger representations and event sentence embeddings interactively fuse in vector space to generate the final event representations. Experiments show that our model is more effective than the most advanced methods.

Minimal Model (MM) is the top-scoring model for assessing physiological characteristics to diagnose the potential or onset of type 2 diabetes mellitus (T2DM) through the intravenous glucose tolerance test (IVGTT) for the past four decades. Nevertheless it has been arguable that MM method either overestimates glucose effectiveness (GE) or underestimates insulin sensitivity (IS) in some cases by both biologists through in vivo experiments and mathematicians by analysis and/or simulations. We propose a novel model including the interstitial insulin according to physiology and adapted from the well accepted Sturis’ model for the glucose-insulin metabolic system suitable to the IVGTT setting. Our model consistently overcomes the aforementioned defects in a subgroup of subjects. In addition, the variable X for insulin action in MM might be appropriately interpreted as an increment of insulin in the interstitial space in response to the bolus stimulus, rather than being proportional to the interstitial insulin as believed.

Higher-order networks (HONs), which go beyond the limitations of pairwise relation modeling by graphs, capture higher-order dependencies involving three or more components for various systems. As the number of potential higher-order dependencies increases exponentially with both network size and the order of dependency, it is of particular importance for HON models to balance their representation power against model complexity. In this study, we propose a method, significant k -order dependencies mining (S k DM), based on hypothesis testing and the Markov chain Monte Carlo (MCMC), to identify significant higher-order dependencies in real systems. Through synthetic clickstreams with elaborately designed higher-order dependencies, S k DM shows a powerful ability to correctly identify all significant dependencies at preset significance levels of $\alpha = \textrm{{0}}\textrm{{.01, 0}}\textrm{{.05, 0}}\textrm{{.10}}$ , performing as the only method, in comparison to the state of the arts, that can robustly maintain the Type I error rate, and without generating any Type II error across all the experimental settings. We further apply the S k DM method to various empirical networks, including journal citations, air traffic, and email communications. Empirical results show that among those tested networks, only 6.03%, 1.47%, and 1.28% of all potential dependencies are of statistical significance ( $\alpha = \textrm{{0}}\textrm{{.01}}$ ). The proposed S k DM method, therefore, provides an efficient tool for higher-order network analysis tasks at reduced computational complexity.

Headwater streams are highly heterogenous and characterized by a sequence of riffles and pools, which are identified as distinct habitats. That higher species richness and density in riffles than in pools is considered a general pattern for macroinvertebrates. As temperate winters can last long up to half a year, however, macroinvertebrate communities of riffles and pools may assemble differently under ices or snows. Particularly, defoliation concentrating in autumn can largely change habitats in both riffles and pools by litter patching. According to the absence or presence of litter patches, there exist four types of subhabitats, i.e., riffle stones, riffle litters, and pool sediments, pool litters, which are selectively colonized by macroinvertebrates. To study the spatial pattern and temporal dynamics of colonization, macroinvertebrates were surveyed in a warmer temperate forest headwater stream in Northeast China during four periods: autumn, pre-freezing, freezing, and thawing periods. Our study focused on functional trait composition, functional diversity and functional redundancy of macroinvertebrate communities. The colonization of macroinvertebrates was found to be significantly different in these subhabitats. Riffle stones supported higher taxonomic and functional diversities than pool sediments; litter patches supported higher total macroinvertebrate abundance and higher functional redundancy than riffle stones or pool sediments. The functional trait composition changed significantly with seasonal freeze-thaw in both riffle stones and pool sediments, but not in litter patches. Macroinvertebrate community in litter patches showed seasonal stability in taxonomic and functional diversities and functional redundancy. Thus, this study strongly highlights that litter patches play an important role structuring macroinvertebrate community over winter, supporting high abundance and maintaining functional stability.

Environmentally induced or epigenetic-related beta-cell dysfunction and insulin resistance play a critical role in the progression to diabetes. We developed a mathematical modeling framework capable of studying the progression to diabetes incorporating various diabetogenic factors. Considering the heightened risk of beta-cell defects induced by obesity, we focused on the obesity-diabetes model to further investigate the influence of obesity on beta-cell function and glucose regulation. The model characterizes individualized glucose and insulin dynamics over the span of a lifetime. We then fit the model to the longitudinal data of the Pima Indian population, which captures both the fluctuations and long-term trends of glucose levels. As predicted, controlling or eradicating the obesity-related factor can alleviate, postpone, or even reverse diabetes. Furthermore, our results reveal that distinct abnormalities of beta-cell function and levels of insulin resistance among individuals contribute to different risks of diabetes. This study may encourage precise interventions to prevent diabetes and facilitate individualized patient treatment.

Functional redundancy is an essential component of ecological insurance and indicates the properties of community assembly, maintenance of ecosystem functions, and stability under disturbance. It can be measured as alpha redundancy within a local community and beta redundancy between pairs of local communities. Although functional redundancy has been measured and discussed widely, its spatial and temporal patterns remain unclear. We hypothesized that high functional alpha redundancy accumulates within local communities under low environmental disturbance and limited interspecific competition, while high functional beta redundancy can occur under small environmental distances due to trait similarity between local communities. To test these hypotheses, we surveyed macroinvertebrates in a (sub)tropical medium river subjected to multiple anthropogenic stressors in two hydrologically different disturbance regimes: wet and dry seasons. Following the framework of Ricotta and co-workers, functional alpha (beta) redundancy was defined as the fraction of species diversity (dissimilarity) that was not expressed by functional diversity (dissimilarity). Functional alpha redundancy reduced significantly under high hydrological disturbance during the wet season. That is, the functional alpha redundancy accumulated in the dry season enhanced community resilience and provided insurance to maintain the stability of community functional diversity during the flooding period. Taxonomic and functional beta diversities decreased synchronously from the dry to wet seasons. There were no significant seasonal changes in functional beta redundancy. Our study provides a case for quantitatively measuring functional alpha and beta redundancies in macroinvertebrates and their seasonal changes in (sub) tropical disturbed rivers.

Recently, there has been a surge of research in the field of superconducting spintronics, which combines superconductivity and magnetism. This emerging field is considered an alternative or complementary approach to traditional complementary metal-oxide semiconductor (CMOS) technology, offering high efficiency and effectiveness. Furthermore, the unique physical phenomena resulting from the interplay of these two competing properties have attracted increasing attention for their potential application in low-power quantum computing. In this review, we focus on the latest advancements in spin-related superconducting logic devices, specifically categorized as superconducting diodes based on their semiconductor counterparts. Additionally, given the ultralow operating temperatures required for these devices, we provide a comprehensive overview of compatible cryogenic memory technologies that incorporate spin-related principles. Finally, we address the key challenges currently hindering the practical implementation of spin-related superconducting electronics and offer insights and directions for future research in this field.

Mathematical modeling has provided quantitative information consistent with experimental data, greatly improving our understanding of the progression of type 1 and type 2 diabetes. However, diabetes is a complex metabolic disease and has been found to be involved in crosstalk interactions with diverse endocrine diseases. Mathematical models have also been developed to investigate the quantitative impact of various hormonal disorders on glucose imbalance, advancing the precision treatment for secondary diabetes. Here we review the models established for the study of dysglycemia induced by hormonal disorders, such as excessive glucocorticoids, epinephrine, and growth hormone. To investigate the influence of hyperthyroidism on the glucose regulatory system, we also propose a hyperthyroid-diabetes progression model. Model simulations indicate that timely thyroid treatment can halt the progression of hyperglycemia and prevent beta-cell failure. This highlights the diagnosis of hormonal disorders, together withblood sugar tests, as significant measures for the early diagnosis and treatment of diabetes. The work recapitulates updated biological research on the interactions between the glucose regulatory system and other endocrine axes. Further mathematical modeling of secondary diabetes is desired to promote the quantitative study of the disease and the development of individualized diabetic therapies.

Abstract Background Brassica carinata (A) Braun has recently gained increased attention across the world as a sustainable biofuel crop. B. carinata is grown as a summer crop in many regions where high temperature is a significant stress during the growing season. However, little research has been conducted to understand the mechanisms through which this crop responds to high temperatures. Understanding traits that improve the high-temperature adaption of this crop is essential for developing heat-tolerant varieties. This study investigated lipid remodeling in B. carinata in response to high-temperature stress. A commercial cultivar, Avanza 641, was grown under sunlit-controlled environmental conditions in Soil-Plant-Atmosphere-Research (SPAR) chambers under optimal temperature (OT; 23/15°C) conditions. At eight days after sowing, plants were exposed to one of the three temperature treatments [OT, high-temperature treatment-1 (HT-1; 33/25°C), and high-temperature treatment-2 (HT-2; 38/30°C)]. The temperature treatment period lasted until the final harvest at 84 days after sowing. Leaf samples were collected at 74 days after sowing to profile lipids using electrospray-ionization triple quadrupole mass spectrometry. Results Temperature treatment significantly affected the growth and development of Avanza 641. Both high-temperature treatments caused alterations in the leaf lipidome. The alterations were primarily manifested in terms of decreases in unsaturation levels of membrane lipids, which was a cumulative effect of lipid remodeling. The decline in unsaturation index was driven by (a) decreases in lipids that contain the highly unsaturated linolenic (18:3) acid and (b) increases in lipids containing less unsaturated fatty acids such as oleic (18:1) and linoleic (18:2) acids and/or saturated fatty acids such as palmitic (16:0) acid. A third mechanism that likely contributed to lowering unsaturation levels, particularly for chloroplast membrane lipids, is a shift toward lipids made by the eukaryotic pathway and the channeling of eukaryotic pathway-derived glycerolipids that are composed of less unsaturated fatty acids into chloroplasts. Conclusions The lipid alterations appear to be acclimation mechanisms to maintain optimal membrane fluidity under high-temperature conditions. The lipid-related mechanisms contributing to heat stress response as identified in this study could be utilized to develop biomarkers for heat tolerance and ultimately heat-tolerant varieties.

Rice (Oryza sativa) is a human staple food and serves as a model organism for genetic and molecular studies. Few studies have been conducted to determine the effects of ultraviolet-B (UV-B) stress on rice. UV-B stress triggers morphological and physiological changes in plants. However, the underlying mechanisms governing these integrated responses are unknown. In this study, we conducted a proteomic response of rice leaves to UV-B stress using two-dimensional gel electrophoresis and identified the selected proteins by mass spectrometry analysis. Four levels of daily biologically effective UV-B radiation intensities were imposed to determine changes in protein accumulation in response to UV-B stress: 0 (control), 5, 10, and 15 kJ m−2 d−1in two cultivars, i.e., IR6 and REX. To mimic the natural environment, we conducted this experiment in Sunlit Soil-Plant-Atmosphere-Research (SPAR) chambers. Among the identified proteins, 11% of differentially expressed proteins were found in both cultivars. In the Rex cultivar, only 45% of proteins are differentially expressed, while only 27.5% were expressed in IR6. The results indicate that REX is more affected by UV-B stress than IR6 cultivars. The identified protein TSJT1 (spot 16) in both cultivars plays a crucial role in plant growth and development during stress treatment. Additionally, we found that UV-B stress altered many antioxidant enzymes associated with redox homeostasis and cell defense response. Another enzyme, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH), has been identified as spot 15, which plays an essential role in glycolysis and cellular energy production. Another vital protein identified is glycosyl hydrolase (GH) as spot 9, which catalyzes the hydrolysis of glycosidic bonds in cell wall polymers and significantly affects cell wall architecture. Some identified proteins are related to photosynthesis, protein biosynthesis, signal transduction, and stress response. The findings of our study provide new insights into understanding how rice plants are tailored to UV-B stress via modulating the expression of UV-B responsive proteins, which will help develop superior rice breeds in the future to combat UV-B stress. Data are available via ProteomeXchange with identifier PXD032163.

Diabetes mellituse has been one of the major diseases in the world due to the high percentage of diabetics in the global population and the increasing growth rate of its onset. Identifying individual physiological characteristics, e.g., insulin sensitivity and glucose effectiveness and others, is extremely important in developing effective drugs and investigating genetic pathways causing the defects in these physiological responses. Intravenous glucose tolerance test (IVGTT) is such a protocol to determine an individual insulin sensitivity and glucose effectiveness indices. In this paper, we propose a stochastic delay differential equation model for the IVGTT protocol attempting to develop a method to increase the accuracy of parameter estimation. We first study the existence and uniqueness of the global positive solution and its asymptotic behavior of the stochastic path close to the steady state of the corresponding deterministic model. Then we develop a maximum likelihood estimation method to estimate the parameters involved in the proposed model. Our simulation studies numerically confirm our theoretical findings and demonstrate that the proposed model with estimated parameters can improve the fitness of clinical data.

The role of free fatty acids (FFA) on Type 2 diabetes mellitus (T2DM) progression has been studied extensively with prior studies suggesting that individuals with shared familial genetic predisposition to metabolic-related diseases may be vulnerable to dysfunctional plasma FFA regulation. A harmful cycle arises when FFA are not properly regulated by insulin contributing to the development of insulin resistance, a key indicator for T2DM, since prolonged insulin resistance may lead to hyperglycemia. We introduce a hypothesis-driven dynamical model and use it to evaluate the role of FFA on insulin resistance progression that is mathematically constructed within the context of individuals that have genetic predisposition to dysfunctional plasma FFA. The dynamics of the nonlinear interactions that involve glucose, insulin, and FFA are modeled by incorporating a fixed-time delay with the corresponding delay-differential equations being studied numerically. The results of computational studies, that is, extensive simulations, are compared to the known minimal ordinary differential equations model. Parameter estimation and model validation are carried out using clinical data of patients who underwent bariatric surgery. These estimates provide a quantitative measure that is used to evaluate the regulation of lipolysis by insulin action measured by insulin sensitivity, within a metabolically heterogeneous population (non-diabetic to diabetic). Results show that key metabolic factors improve after surgery, such as the effect of insulin inhibition of FFA on insulin and glucose regulation, results that do match prior clinical studies. These findings indicate that the reduction in weight or body mass due to surgery improve insulin action for the regulation of glucose, FFA, and insulin levels. This reinforces what we know, namely, that insulin action is essential for regulating FFA and glucose levels and is a robust effect that can be observed not only in the long-term, but also in the short-term; thereby preventing the manifestation of T2DM.

In order to explore the change in internal and external characteristics and the pressure fluctuation of the large bulb tubular pump unit during deceleration, a transient and steady three-dimensional (3D) numerical simulation is executed, based on the standard k-ε turbulence model and the change in boundary conditions such as flow rate. Finally, the pressure fluctuation data are analyzed by the wavelet method. There is a good agreement between the experimental data and numerical simulation results. During the deceleration process of the unit, the head decreases linearly while the efficiency remains stable. Meanwhile, the shock phenomenon and hysteresis effect appear before and after the unit head deceleration. Although there are vortex and backflow in the outlet conduit during deceleration, the pressure distribution on the suction surface of the impeller blades changes uniformly and significantly. The pressure fluctuation changes on the inlet surface of the impeller are more obvious during the deceleration: the closer to the hub, the greater the pressure, and this change decreases with decreasing radius. The fluctuation energy is mainly concentrated in the high-frequency region of 100–120 Hz and decreases uniformly with the deceleration of the rotational speed. This paper provides a reference for the energy utilization and safe operation of the water pump unit in adjusting speeds with variable frequency.

Silicon has been implicated as a factor affecting the degree of resistance to abiotic stresses in several plant species. However, the role of silicon in soybean (Glycine max) under water-limiting conditions is not yet fully understood. This study was conducted to evaluate the effects of silicon application on the vegetative growth of two soybean cultivars (Asgrow 5332 and Progeny 5333) grown under water-limiting conditions. Silicon was provided by adding silicate to the soil. Water-limiting treatments were imposed on plants at two vegetative growth stages for 20 days by irrigating with a reduced amount of water (66% or 33% of the required water). Silicate application enhanced plant height, leaf area, and total dry weight of soybean plants. Significant increases in root volumes were observed in both the silicate-treated cultivars compared to the control plants under water-limiting conditions (33% irrigation). Net photosynthesis and stomatal conductance were decreased, but the quantum efficiency of photosystem II (Fv’/Fm’) did not change under the same irrigation condition, which indicates photosynthesis downregulation through stomatal limitation. Silicate-treated plants in both cultivars had higher water use efficiency as compared to control plants under water-limiting conditions (irrigated with 66% or 33% of required water). Under water-limiting conditions, the soil moisture content was significantly higher in pots containing silicate than in those without added silicate, suggesting that silicon application improves water holding capacity. Taken together, the results from this study indicate that silicon application can improve the vegetative growth of soybeans under low water conditions by increasing the water use efficiency of plants and enhancing the soil’s ability to retain moisture.

The energy consumption of electric vehicles is closely related to the problems of charging station planning and vehicle route optimization. However, due to various factors, such as vehicle performance, driving habits and environmental conditions, it is difficult to estimate vehicle energy consumption accurately. In this work, a physical and data-driven fusion model was designed for electric bus energy consumption estimation. The basic energy consumption of the electric bus was modeled by a simplified physical model. The effects of rolling drag, brake consumption and air-conditioning consumption are considered in the model. Taking into account the fluctuation in energy consumption caused by multiple factors, a CatBoost decision tree model was constructed. Finally, a fusion model was built. Based on the analysis of electric bus data on the big data platform, the performance of the energy consumption model was verified. The results show that the model has high accuracy with an average relative error of 6.1%. The fusion model provides a powerful tool for the optimization of the energy consumption of electric buses, vehicle scheduling and the rational layout of charging facilities.

This study investigated the influence of the change in blade tip clearance on the internal flow characteristics of a vertical axial flow pump. Taking the actual running vertical axial flow pump of a pumping station as the research object, based on the SST k-ω turbulent flow model, the numerical simulation technology was used to study the effects of different tip clearances on the pressure, turbulent kinetic energy, Z–X section pressure and flow state of the impeller at the middle section. Furthermore, the impact of clearance layer tip leakage was also analyzed. Unsteady calculations of flow characteristics under the design conditions were performed. The research results showed that the variation trend of the pressure in the impeller was basically the same under different tip clearance values. With the increase in the clearance value, the pressure gradient along the water inlet direction of the blade decreased and the leakage vorticity increased. Observing the leakage vorticity distribution of the gap layer under the flow condition of 0.6Q0, it was found that when the tip clearance was smaller than 1 mm, the leakage flow was small and easily assimilated by the mainstream, and the leakage flow and mainstream had a certain ability to compete, which caused adverse effects on the performance of the pump device. The pressure pulsation characteristics showed that the leakage flow caused by the tip clearance caused a high-frequency distribution, and the clearance obviously influenced the pressure pulsation characteristics.

Determining the patterns of diversity and community composition in headwater streams is fundamental to river biodiversity conservation. Environmental selection has been assumed to be a major force driving temperate macroinvertebrate assembly. To test this assumption in the subtropics, we conducted identical surveys for headwater streams in two neighboring basins, which are located on two sides of a north–south mountain in southern China. We sampled macroinvertebrates and measured habitat and environmental variables in headwater streams of the two basins. The two groups of headwater streams share a species pool and have similar taxa, taxa richness, and functional composition. Beta diversity accounted for a high proportion of the within-basin diversity, and was mainly attributed to the replacement differences. Highly similarity between the two basins’ species composition showed similar environmental selection in structuring macroinvertebrate communities at the regional scale. Redundancy analysis showed that basin identity is the key factor explaining the variation of communities. Environmental selection is an important factor in structuring macroinvertebrate communities within individual basins. Annual precipitation differs significantly on the two sides of the mountain shaded by the East Asia monsoon, resulting in distinctive substrate compositions in the two basins. Our study provides empirical support for the roles of environmental selection in shaping subtropical macroinvertebrate communities.

Peanuts contain four major allergens with differences in allergenic potency. Thermal processing can influence the allergenic properties of peanuts. Until now, a kinetic model has not been reported to assess the changes of soluble allergen (extracted from processed peanuts) content as affected by various thermal processing methods. Our objective is to characterize the reaction kinetics of the thermal processing methods, including wet processing (boiling with/without high-pressure, steaming with/without high-pressure), deep-frying and dry processing (microwaving and roasting) using five time intervals. The relationships between processing time and extractable major allergen content could be explained by a simple linear regression kinetic model (except high-pressure steaming). Among all the methods with optimal processing point, frying for 6 min had a relatively lower IgE binding (linear epitopes) ratio, possibly due to the processing conditions, which caused break down, cross-linking and aggregation of Ara h 2, and a relatively lower solubility. Keywords: Peanut allergen, Thermal processing, Proximate analysis, Protein denaturation, Kinetic analysis, Water-soluble protein, SDS-sample-buffer-soluble protein, IgE-binding properties

Insulin signaling is essential for β-cell survival and proliferation in vivo. Insulin also has potent mitogenic and anti-apoptotic actions on cultured β-cells, with maximum effect in the high picomolar range and diminishing effect at high nanomolar doses. In order to understand whether these effects of insulin are constitutive or can be subjected to physiological modulation, it is essential to estimate the extracellular concentration of monomeric insulin within an intact islet. Unfortunately, the in vivo concentration of insulin monomers within the islet cannot be measured directly with current technology. Here, we present the first mathematical model designed to estimate the levels of monomeric insulin within the islet extracellular space. Insulin is released as insoluble crystals that exhibit a delayed dissociation into hexamers, dimers, and eventually monomers, which only then can act as signaling ligands. The rates at which different forms of insulin dissolve in vivo have been estimated from studies of peripheral insulin injection sites. We used this and other information to formulate a mathematical model to estimate the local insulin concentration within a single islet as a function of glucose. Model parameters were estimated from existing literature. Components of the model were validated using experimental data, if available. Model analysis predicted that the majority of monomeric insulin in the islet is that which has been returned from the periphery, and the concentration of intra-islet monomeric insulin varies from ~50-300 pM when glucose is in the physiological range. Thus, our results suggest that the local concentration of monomeric insulin within the islet is in the picomolar 'sweet spot' range of insulin doses that activate the insulin receptor and have the most potent effects on β-cells in vitro. Together with experimental data, these estimations support the concept that autocrine/paracrine insulin signalling within the islet is dynamic, rather than constitutive and saturated.