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Abstract Background The Daur people are one of the 55 minority ethnic groups in China and have lived in Northern China for 300 years. In traditional Daur medicine, medicinal and edible plants (MEPs) are utilised for health benefits and therapeutic purposes; however, related ethnobotanical knowledge is rarely reported, which is disadvantageous for the sustainable development of these MEPs. Methods Semi-structured interviews with 122 informants, six focus group discussions, and a resource survey were conducted in a Daur minority nationality area in Inner Mongolia from 2015 to 2020, and the data statistics were analysed. In this study, we simulated a system dynamics model aimed at understanding the multiple feedback mechanisms involved in the relationships between the cultural influences and socioeconomic factors, sustainable environment, and development of MEPs. Results A total of 52 species of MEPs were identified and relevant ethnobotanical knowledge was assessed using Daur medicinal species data from Inner Mongolia and the Xinjiang region, with the literature and Ewenki ethnic group data used for comparison. The most commonly used medicinal plant species by the Daur were found to be Betula pendula subsp. mandshurica, Artemisia integrifolia, Crataegus pinnatifida, Saposhnikovia divaricata, Artemisia argyi, and Jacobaea cannabifolia. The MEPs most frequently targeted the digestive and rheumatic immunity systems, as well as infectious diseases or parasitic infections and other common diseases and basic health issues. MEP knowledge was primarily limited to older generations; thus, the valuable ethnobotanical knowledge on traditional medicines must be protected from future losses. Conclusions Our findings provide insights for future research aimed at exploiting the rich phytochemical diversity in traditional medicine and promote its use in modern lifestyles. Effective assessment and management of plant resources will lead to their application for the improvement of dietary diversity, nutrition, and health care.

Abstract Background The incidence and mortality of lung cancer is the highest in China and the world. Brain is the most common distant metastasis site of lung cancer. Its transfer mechanism and predictive biomarkers are still unclear. EZH2 participates in the catalysis of transcriptional inhibition complex, mediates chromatin compactness, leads to the silencing of its downstream target genes, participates in the silencing of multiple tumor suppressor genes, and is related to cell proliferation, apoptosis and cycle regulation. In physiology, EZH2 has high activity in stem cells or progenitor cells, inhibits genes related to cell cycle arrest and promotes self-renewal. To detect the expression and mutation of EZH2 gene in patients with brain metastasis of lung cancer, and provide further theoretical basis for exploring the pathogenesis of brain metastasis of lung cancer and finding reliable biomarkers to predict brain metastasis of lung cancer. Methods This study investigated susceptible genes for brain metastasis of lung cancer. The second-generation sequencing technology was applied to screen the differential genes of paired samples (brain metastasis tissues, lung cancer tissues and adjacent tissues) of lung cancer patients with brain metastasi. Results It revealed that there was a significant difference in the G553C genotype of EZH2 between lung cancer brain metastasis tissues and lung cancer tissues (p = 0.045). The risk of lung cancer brain metastasis in G allele carriers was 2.124 times higher than that in C allele carriers. Immunohistochemistry showed that compared with lung cancer patients and lung cancer patients with brain metastasis, the expression level of EZH2 in lung cancer tissues of lung cancer patients was significantly higher than that in adjacent lung tissues (p

Abstract Purpose This study aims to elucidate the biological functions of ferroptosis-related genes in periodontitis, along with their correlation to tumor microenvironment (TME) features such as immune infiltration. It aims to provide potential diagnostic markers of ferroptosis for clinical management of periodontitis. Methods Utilizing the periodontitis-related microarray dataset GSE16134 from the Gene Expression Omnibus (GEO) and a set of 528 ferroptosis-related genes identified in prior studies, this research unveils differentially expressed ferroptosis-related genes in periodontitis. Subsequently, a protein–protein interaction network was constructed. Subtyping of periodontitis was explored, followed by validation through immune cell infiltration and gene set enrichment analyses. Two algorithms, randomForest and SVM(Support Vector Machine), were employed to reveal potential ferroptosis diagnostic markers for periodontitis. The diagnostic efficacy, immune correlation, and potential transcriptional regulatory networks of these markers were further assessed. Finally, potential targeted drugs for differentially expressed ferroptosis markers in periodontitis were predicted. Results A total of 36 ferroptosis-related genes (30 upregulated, 6 downregulated) were identified from 829 differentially expressed genes between 9 periodontitis samples and the control group. Subsequent machine learning algorithm screening highlighted 4 key genes: SLC1A5(Solute Carrier Family 1 Member 5), SLC2A14(Solute Carrier Family 1 Member 14), LURAP1L(Leucine Rich Adaptor Protein 1 Like), and HERPUD1(Homocysteine Inducible ER Protein With Ubiquitin Like Domain 1). Exploration of these 4 key genes, supported by time-correlated ROC analysis, demonstrated reliability, while immune infiltration results indicated a strong correlation between key genes and immune factors. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted for the four key genes, revealing enrichment in GO/KEGG pathways that have a significant impact on periodontitis. Finally, the study predicted potential transcriptional regulatory networks and targeted drugs associated with these key genes in periodontitis. Conclusions The ferroptosis-related genes identified in this study, including SLC1A5, SLC2A14, LURAP1L, and HERPUD1, may serve as novel diagnostic and therapeutic targets for periodontitis. They are likely involved in the occurrence and development of periodontitis through mechanisms such as immune infiltration, cellular metabolism, and inflammatory chemotaxis, potentially linking the ferroptosis pathway to the progression of periodontitis. Targeted drugs such as flurofamide, L-733060, memantine, tetrabenazine, and WAY-213613 hold promise for potential therapeutic interventions in periodontitis associated with these ferroptosis-related genes.

Objective Bedding deep cutting slopes containing weak interlayers are commonly found in slope engineering, whose stability is influenced by two key factors: The strength of the sliding zone soil and the reserved thickness of the base (the distance from the base of an excavated slope to the weak interlayer). Methods In this research, taking the K42 cutting slope of the Yang-Xuan Expressway as an example, the evolution process of slope deformation was analyzed, especially the characteristics of basal heave deformation. The properties of the deep sliding zone soil in the slope were revealed by ring shear tests, which are suitable for studying the shear strength of soil that has experienced large shear displacements. Moreover, the residual strength parameters of the saturated sliding zone soil were applied to analyze the reserved thickness of the base. Results The results show that sliding zone soils exhibit obvious strain softening characteristics, which become more evident as the normal stress decreases. As the soil shear strength transitions from peak strength to residual strength, both the cohesion force and internal friction angle decrease, with the cohesion force decreasing to a greater extent than the internal friction angle. The residual cohesion force of sliding zone soil varies slightly with the shear rate, while the relationship between the residual internal friction angle and shear rate varies as a logarithmic function. When the shear rate is less than 2 mm/min, the residual shear strength parameter of sliding zone soil is more sensitive to the shear rate and vice versa. Conclusion Furthermore, according to the regression equations of the critical states of slope stability, the reserved thickness of the base under different slope rates was divided into four zones: A (extremely unstable zone), B (unstable zone), C (basically stable zone) and D (stable zone), and based on this, the criterion and early warning model of the reserved thickness of the base for slope excavation were established.

Abstract Bolt looseness may occur on wind turbine (WT) blades exposed to operational and environmental variability conditions, which sometimes can cause catastrophic consequences. Therefore, it is necessary to monitor the loosening state of WT blade root bolts. In order to solve this problem, this paper proposes a method to monitor the looseness of blade root bolts using the sensors installed on the WT blade. An experimental platform was first built by installing acceleration and strain sensors for monitoring bolt looseness. Through the physical experiment of blade root bolts' looseness, the response data of blade sensors is then obtained under different bolt looseness numbers and degrees. Afterwards, the sensor signal of the blade root bolts is analyzed in time domain, frequency domain, and time‐frequency domain, and the sensitivity features of various signals are extracted. So the eigenvalue category as the input of the state discrimination model was determined. The LightGBM (light gradient boosting machine) classification algorithm was applied to identify different bolt looseness states for the multi‐domain features. The impact of different combinations of sensor categories and quantities as the data source on the identification results is discussed, and a reference for the selection of sensors is provided. The proposed method can discriminate four bolt states at an accuracy of around 99.8% using 5‐fold cross‐validation.

Abstract Patients suffering from osteoporotic fractures often require effective fixation and subsequent bone repair. However, the currently available materials are functionally limited and often fail to improve outcomes in this patient population. In this study, we developed orthopedic adhesives doped with romosozumab-loaded mesoporous bioactive glass nanoparticles to aid in osteoporotic fracture fixation and restore dysregulated bone homeostasis. These adhesives were designed to promote osteoblast formation while simultaneously inhibiting osteoclastic bone-resorbing activity, thus working synergistically to promote the healing of osteoporotic fractures. Orthopedic adhesives exhibit injectability, reversible adhesiveness, and malleability, enhancing their adaptability to complex clinical scenarios. Furthermore, the release of romosozumab from mesoporous bioactive glass nanoparticles accelerated osteogenesis and inhibited osteoclastogenesis, delaying the bone resorption process. This dual action contributes to the regulation of bone regeneration and remodeling. Notably, our orthopedic adhesive could restore the disrupted bone homeostasis associated with osteoporotic fractures.

Abstract Exercise is usually regarded to have short-term beneficial effects on immune health. Here we show that early-life regular exercise exerts long-term beneficial effects on inflammatory immunity. Swimming training for 3 months in male mice starting from 1-month-old curbs cytokine response and mitigates sepsis when exposed to lipopolysaccharide challenge, even after an 11-month interval of detraining. Metabolomics analysis of serum and liver identifies pipecolic acid, a non-encoded amino acid, as a pivotal metabolite responding to early-life regular exercise. Importantly, pipecolic acid reduces inflammatory cytokines in bone marrow-derived macrophages and alleviates sepsis via inhibiting mTOR complex 1 signaling. Moreover, early-life exercise increases histone 3 lysine 4 trimethylation at the promoter of Crym in the liver, an enzyme responsible for catalyzing pipecolic acid production. Liver-specific knockdown of Crym in adult mice abolishes this early exercise-induced protective effects. Our findings demonstrate that early-life regular exercise enhances anti-inflammatory immunity during middle-aged phase in male mice via epigenetic immunometabolic modulation, in which hepatic pipecolic acid production has a pivotal function.

Abstract Background Residential mobility is believed to influence the occurrence and development of cancer; however, the results are inconclusive. Furthermore, limited studies have been conducted on Asian populations. This study aimed to evaluate the relationship between residential mobility and liver cancer risk among Chinese women. Methods We enrolled 72,818 women from urban Shanghai between 1996 and 2000, and then followed them until the end of 2016. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the association between residential mobility and liver cancer risk. A linear trend test was conducted by ranking variables. A sensitivity analysis was also conducted, excluding participants with follow-up times of less than 2 years, to prevent potential bias. Results During the 1,269,765 person-years of follow-up, liver cancer was newly diagnosed in 259 patients. Domestic migration (HR = 1.47, 95% CI, 1.44–1.50), especially immigration to Shanghai (HR = 1.47, 95% CI, 1.44–1.50) was associated with an increased risk of liver cancer. In addition, migration frequency, age at initial migration and first immigration to Shanghai had linear trends with an increased liver cancer risk (P trend

ABSTRACTLow thermal conductivity and excellent high-temperature stability make lanthanum zirconate (La2Zr2O7, LZO) a very promising material for high-temperature insulation applications. In this study, LZO porous ceramics with ultra-high porosity and an open-pore structure were prepared by the replica method using a polyurethane template. The flowability and coating quality of the ceramic slurry were optimized. When the dispersant content of the slurry was 0.6 wt% and the alcohol to water ratio was 1:1, the slurry had low surface tension and low viscosity, leading to good coating quality of the ceramic slurry on the sponge template. The pore size between hollow skeletons was 100–500 μm with the hollow structure of the skeletons forming secondary pores. LZO porous ceramics showed high porosity of 87.6%-96.0%, low thermal conductivity of 0.048–0.126 W/(m·K), and compressive strength of 0.13–0.74 MPa by adjusting the ceramic content. A high temperature insulation performance test showed that the temperature difference between the cold side and the hot side of the sample was over 1000°C, indicating the excellent thermal insulation properties of LZO porous ceramics. LZO porous ceramics had good high-temperature stability without sintering shrinkage at heat treatment temperatures below 1500°C.

There is currently no effective targeted therapeutic strategy for the treatment of central nervous system acute lymphoblastic leukemia (CNS-ALL). Integrin α6 is considered a potential target for CNS-ALL diagnosis and therapy because of its role in promoting CNS-ALL disease progression. The targeted peptide D(RWYD) (abbreviated RD), with nanomolar affinity to integrin α6 was identified by peptide scanning techniques such as alanine scanning, truncation, and D-substitution. Herein, we developed a therapeutic nanoparticle based on the integrin α6-targeted peptide for treating CNS-ALL. The self-assembled proapoptotic nanopeptide D(RWYD)-D(KLAKLAK)2-GD(FFY) (abbreviated RD-KLA-Gffy) contains the integrin α6-targeted peptide RD, the well-known proapoptotic peptide D(KLAKLAK)2 (abbreviated KLA), and the self-assembling tetrapeptide GD(FFY) (abbreviated Gffy). The functional mechanism of RD-KLA-Gffy is clarified using different experiments. Our results demonstrate that RD-KLA-Gffy is highly enriched in CNS-ALL lesions and induces tumor cell apoptosis, thus reducing CNS-ALL disease burden and prolonging the survival of CNS-ALL mice without obvious toxicity. Moreover, the combined use of RD-KLA-Gffy and methotrexate (MTX) shows a potent antitumor effect in treating CNS-ALL, indicating that RD-KLA-Gffy plays an important role in suppressing CNS-ALL progression either as a single agent or in combination with MTX, which shows promise for application in CNS-ALL therapy.

When a curling rock slides on an ice sheet with an initial rotation, a lateral movement occurs, which is known as the curling phenomenon. The force of friction between the curling rock and the ice sheet changes continually with changes in the environment; thus, the sport of curling requires great skill and experience. The throwing of the curling rock is a great challenge in robot design and control, and existing curling robots usually adopt a combination scheme of a wheel chassis and gripper that differs significantly from human throwing movements. A hexapod curling robot that imitates human kicking, sliding, pushing, and curling rock rotating was designed and manufactured by our group, and completed a perfect show during the Beijing 2022 Winter Olympics Games. Smooth switching between the walking and throwing tasks is realized by the robot’s morphology transformation based on leg configuration switching. The robot’s controlling parameters, which include the kicking velocity vk, pushing velocity vp, orientation angle θc, and rotation velocity ω, are determined by aiming and sliding models according to the estimated equivalent friction coefficient μequ and ratio e of the front and back frictions. The stable errors between the target and actual stopping points converge to 0.2 and 1.105 m in the simulations and experiments, respectively, and the error shown in the experiments is close to that of a well-trained wheelchair curling athlete. This robot holds promise for helping ice-makers rectify ice sheet friction or assisting in athlete training.

Abstract Bone is a mechanosensitive tissue and undergoes constant remodeling to adapt to the mechanical loading environment. However, it is unclear whether the signals of bone cells in response to mechanical stress are processed and interpreted in the brain. In this study, we found that the hypothalamus of the brain regulates bone remodeling and structure by perceiving bone prostaglandin E2 (PGE2) concentration in response to mechanical loading. Bone PGE2 levels are in proportion to their weight bearing. When weight bearing changes in the tail-suspension mice, the PGE2 concentrations in bones change in line with their weight bearing changes. Deletion of cyclooxygenase-2 (COX2) in the osteoblast lineage cells or knockout of receptor 4 (EP4) in sensory nerve blunts bone formation in response to mechanical loading. Moreover, knockout of TrkA in sensory nerve also significantly reduces mechanical load-induced bone formation. Moreover, mechanical loading induces cAMP-response element binding protein (CREB) phosphorylation in the hypothalamic arcuate nucleus (ARC) to inhibit sympathetic tyrosine hydroxylase (TH) expression in the paraventricular nucleus (PVN) for osteogenesis. Finally, we show that elevated PGE2 is associated with ankle osteoarthritis (AOA) and pain. Together, our data demonstrate that in response to mechanical loading, skeletal interoception occurs in the form of hypothalamic processing of PGE2-driven peripheral signaling to maintain physiologic bone homeostasis, while chronically elevated PGE2 can be sensed as pain during AOA and implication of potential treatment.

Abstract Background The latent and incubation periods characterize the transmission of infectious viruses and are the basis for the development of outbreak prevention and control strategies. However, systematic studies on the latent period and associated factors with the incubation period for SAS-CoV-2 variants are still lacking. We inferred the two durations of Delta, BA.1, and BA.2 cases and analyzed the associated factors. Methods The Delta, BA.1, and BA.2 (and its lineages BA.2.2 and BA.2.76) cases with clear transmission chains and infectors from 10 local SAS-CoV-2 epidemics in China were enrolled. The latent and incubation periods were fitted by the Gamma distribution, and associated factors were analyzed using the accelerated failure time model. Results The mean latent period for 672 Delta, 208 BA.1, and 677 BA.2 cases was 4.40 (95%CI: 4.24 ~ 4.63), 2.50 (95%CI: 2.27 ~ 2.76), and 2.58 (95%CI: 2.48 ~ 2.69) days, respectively, with 85.65% (95%CI: 83.40 ~ 87.77%), 97.80% (95%CI: 96.35 ~ 98.89%), and 98.87% (95%CI: 98.40 ~ 99.27%) of them starting to shed viruses within 7 days after exposure. In 405 Delta, 75 BA.1, and 345 BA.2 symptomatic cases, the mean latent period was 0.76, 1.07, and 0.79 days shorter than the mean incubation period [5.04 (95%CI: 4.83 ~ 5.33), 3.42 (95%CI: 3.00 ~ 3.89), and 3.39 (95%CI: 3.24 ~ 3.55) days], respectively. No significant difference was observed in the two durations between BA.1 and BA.2 cases. After controlling for the sex, clinical severity, vaccination history, number of infectors, the length of exposure window and shedding window, the latent period [Delta: exp(β) = 0.81, 95%CI: 0.66 ~ 0.98, p = 0.034; Omicron: exp(β) = 0.82, 95%CI: 0.71 ~ 0.94, p = 0.004] and incubation period [Delta: exp(β) = 0.69, 95%CI: 0.55 ~ 0.86, p

Abstract As testicular mesenchymal stromal cells, stem Leydig cells (SLCs) show great promise in the treatment of male hypogonadism. The therapeutic functions of mesenchymal stromal cells are largely determined by their reciprocal regulation by immune responses. However, the immunoregulatory properties of SLCs remain unclear. Here, we observe that SLCs transplantation restore male fertility and testosterone production in an ischemia‒reperfusion injury mouse model. SLCs prevent inflammatory cascades through mitochondrial transfer to macrophages. Reactive oxygen species (ROS) released from activated macrophages inducing mitochondrial transfer from SLCs to macrophages in a transient receptor potential cation channel subfamily member 7 (TRPM7)-mediated manner. Notably, knockdown of TRPM7 in transplanted SLCs compromised therapeutic outcomes in both testicular ischemia‒reperfusion and testicular aging mouse models. These findings reveal a new mechanism of SLCs transplantation that may contribute to preserve testis function in male patients with hypogonadism related to immune disorders.

Abstract Purpose The clinical outcomes of patients who received a cervical collar after anterior cervical decompression and fusion were evaluated by comparison with those of patients who did not receive a cervical collar. Methods All of the comparative studies published in the PubMed, Cochrane Library, Medline, Web of Science, and EMBASE databases as of 1 October 2023 were included. All outcomes were analysed using Review Manager 5.4. Results Four studies with a total of 406 patients were included, and three of the studies were randomized controlled trials. Meta-analysis of the short-form 36 results revealed that wearing a cervical collar after anterior cervical decompression and fusion was more beneficial (P 0.05) between the cervical collar group and the no cervical collar group. Conclusions This systematic review and meta-analysis revealed no significant differences in the 6-week postoperative cervical range of motion, fusion rate, or neck disability index between the cervical collar group and the no cervical collar group. However, compared to patients who did not wear a cervical collar, patients who did wear a cervical collar had better scores on the short form 36. Interestingly, at the final follow-up visit, the neck disability index scores were better in the no cervical collar group than in the cervical collar group. PROSPERO registration number: CRD42023466583.

Abstract Background Spinal muscular atrophy (SMA) is a rare autosomal recessive hereditary neuromuscular disease caused by survival motor neuron 1 (SMN1) gene deletion or mutation. Homozygous deletions of exon 7 in SMN1 result in 95% of SMA cases, while the remaining 5% are caused by other pathogenic variants of SMN1. Methods We analyzed two SMA-suspected cases that were collected, with no SMN1 gene deletion and point mutation in whole-exome sequencing. Exon 1 deletion of the SMN gene was detected using Multiplex ligation-dependent probe amplification (MLPA) P021. We used long-range polymerase chain reaction (PCR) to isolate the SMN1 template, optimized-MLPA P021 for copy number variation (CNV) analysis within SMN1 only, and validated the findings via third-generation sequencing. Results Two unrelated families shared a genotype with one copy of exon 7 and a novel variant, g.70919941_70927324del, in isolated exon 1 of the SMN1 gene. Case F1-II.1 demonstrated no exon 1 but retained other exons, whereas F2-II.1 had an exon 1 deletion in a single SMN1 gene. The read coverage in the third-generation sequencing results of both F1-II.1 and F2-II.1 revealed a deletion of approximately 7.3 kb in the 5’ region of SMN1. The first nucleotide in the sequence data aligned to the 7385 bp of NG_008691.1. Conclusion Remarkably, two proband families demonstrated identical SMN1 exon 1 breakpoint sites, hinting at a potential novel mutation hotspot in Chinese SMA, expanding the variation spectrum of the SMN1 gene and corroborating the specificity of isolated exon 1 deletion in SMA pathogenesis. The optimized-MLPA P021 determined a novel variant (g.70919941_70927324del) in isolated exon 1 of the SMN1 gene based on long-range PCR, enabling efficient and affordable detection of SMN gene variations in patients with SMA, providing new insight into SMA diagnosis to SMN1 deficiency and an optimized workflow for single exon CNV testing of the SMN gene.

Abstract Background In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres. Methods A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results. Results A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248—3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results. Conclusions The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.

Abstract. Background:. The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate. Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome, who subjected to preimplantation genetic testing for aneuploidy (PGT-A) treatment. However, it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement. Methods:. From February 2020 to May 2021, we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos, the clinical information of couples, and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment. Initially, we developed a novel deep learning model called the Attentive Multi-Focus Selection Network (AMSNet) to analyze time-lapse videos in real time and predict blastocyst formation. Building upon AMSNet, we integrated additional clinically predictive variables and created a second deep learning model, the Attentive Multi-Focus Video and Clinical Information Fusion Network (AMCFNet), to assess the euploidy status of embryos. The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements. The receiver operating characteristic curve (ROC) was used to evaluate the superiority of the model. Results:. A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task, and 1422 qualified blastocysts received PGT-A (n = 589) or PGT for chromosomal structural rearrangement (PGT-SR, n = 833) were enrolled for the euploidy assessment task in this study. The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy. The real-time accuracy for AMSNet to predict blastocyst formation reached above 70% on the day 2 of embryo culture, and then increased to 80% on the day 4 of embryo culture. Combing with 4 clinical features of couples, the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement. Conclusion:. Integrating seven focal raw time-lapse images of embryos and parental clinical information, AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

Abstract Conventional food production is restricted by energy conversion efficiency of natural photosynthesis and demand for natural resources. Solar-driven artificial food synthesis from CO2 provides an intriguing approach to overcome the limitations of natural photosynthesis while promoting carbon-neutral economy, however, it remains very challenging. Here, we report the design of a hybrid electrocatalytic−biocatalytic flow system, coupling photovoltaics-powered electrocatalysis (CO2 to formate) with five-enzyme cascade platform (formate to sugar) engineered via genetic mutation and bioinformatics, which achieves conversion of CO2 to C6 sugar (L-sorbose) with a solar-to-food energy conversion efficiency of 3.5%, outperforming natural photosynthesis by over three-fold. This flow system can in principle be programmed by coupling with diverse enzymes toward production of multifarious food from CO2. This work opens a promising avenue for artificial food synthesis from CO2 under confined environments.

Safe, high-efficient, green and low-carbon mining is an eternal theme of coal mines. Near zero rock burst, near zero ecological damage and low-carbon, zero-carbon and carbon-negative green mining will become new requirements to ensure China's energy security supply and green low-carbon development. Backfill mining is the inevitable way to achieve these requirements. However, the existing theories, technologies, and methods of backfill mining are difficult to overcome the technical bottlenecks of high yield, high efficiency, and low-carbon mining, and it is imperative to reform the filling materials and filling modes. In view of the strategic goal of low-carbon coal mining of “kilometer deep mine resource development and ten-million-ton productivity mine filling (two thousands) ” and “near zero ecological damage and near zero rock burst (two near zeros)”. The definition and concept of carbon-negative & high-efficient backfill mining in coal mines has been systematically expounded, and the theoretical development for carbon-negative & high-efficient backfill mining in coal mines has been proposed, including the topological configuration and strength theory of CGIF (CO2 Gangue Innovative Framework) for high porosity filling materials structure, the carbon sequestration theory of CGIF mixture filling body, the reaction kinetics theory of fast adhesive gel bonding material, and the prevention and control of rock burst by filling mining in mining area. The key technical systems have been proposed, such as the preparation technology of gangue fast and efficient cementation high porosity filling material, the green and efficient preparation technology of fast and efficient cementation gel binding material, the negative carbon efficient filling mining technology of CGIF backfill, the negative carbon efficient filling mining technology, the technology of multi-face mining, and the full cycle three-dimensional efficient filling mining and rock burst prevention technology. On this basis, the “three stage” development plan of “basic research, technical research, and engineering demonstration” for carbon-negative & high-efficient backfill mining in coal mines has been clarified, and a theoretical and technical system for carbon-negative & high-efficient backfill mining in coal mines has been constructed. The CO2 storage capacity with carbon-negative & high-efficient backfill mining in coal mines has been evaluated. It is expected to achieve a new pattern of carbon neutrality in the entire process of coal development and utilization through carbon-negative mining and low-carbon utilization.

The high-performance alloy, 304 stainless steel, is widely used in various industries. However, its material properties lead to severe tool wear during milling processes, significantly increasing milling force and adversely impacting machining quality and efficiency. Consequently, an accurate milling-force model is crucial for guiding the formulation and optimization of machining parameters. This paper presents a milling-force prediction model for 304 stainless steel that incorporates the effect of tool wear, based on the mechanistic modeling approach. Side-milling experiments on 304 stainless steel were conducted to analyze the relationship between milling force and tool wear, identify the model coefficients, and validate the prediction accuracy of the milling-force model. The results demonstrate that the model accurately predicts the milling forces of worn tools while side milling 304 stainless steel under various machining parameters and tool wear conditions.

In the field of magnetic confinement plasma control, the accurate feedback of plasma position and shape primarily relies on calculations derived from magnetic measurements through equilibrium reconstruction or matrix mapping method. However, under harsh conditions like high-energy neutron radiation and elevated temperatures, the installation of magnetic probes within the device becomes challenging. Relying solely on external magnetic probes can compromise the precision of EFIT in determining the plasma shape. To tackle this issue, we introduce a real-time, non-magnetic measurement method on the HL-3 tokamak, which diagnoses the plasma position and shape via imaging. Particularly, we put forward an adapted Swin Transformer model, the Poolformer Swin Transformer (PST), to accurately and fastly interpret the plasma shape from the Charge-Coupled Device Camera images. By adopting multi-task learning and knowledge distillation techniques, the model is capable of robustly detecting six shape parameters under visual interference conditions such as bright light from the divertor and gas injection, thereby avoiding cumbersome manual labeling. Specifically, the well-trained PST model capably infers R and Z within the mean average error below 1.1 cm and 1.8 cm, respectively, while requiring less than 2 ms for end-to-end feedback, an 80% improvement over the smallest Swin Transformer model, laying the foundation for real-time control. Finally, we deploy the PST model in the Plasma Control System using TensorRT, and achieve 500 ms stable PID feedback control based on the PST-computed horizontal displacement information. In conclusion, this research opens up new avenues for the practical application of image-computing plasma shape diagnostic methods in the realm of real-time feedback control.

ALMT (aluminum-activated malate transporter) proteins play crucial roles in the transport of organic acids and have significant implications for plant stress responses and development. While extensively studied in some plants, the characteristics and functional divergence of the ALMT gene family have not yet been thoroughly explored in Prunus mume and some other Rosaceae species. In this study, we systematically analyzed the ALMT gene family across nine Rosaceae species to explore their evolutionary relationships, structural characteristics, and functional roles. A total of 138 ALMT genes were identified and categorized into four groups based on a phylogenetic analysis. The motif analysis confirmed the accuracy of the phylogenetic grouping. The collinearity analysis indicated that whole-genome duplication events were the primary drivers of ALMT gene expansion in these species. Furthermore, the cis-acting element analysis revealed diverse regulatory elements associated with environmental responses, including abscisic acid, light, and jasmonic acid. The gene expression correlation analysis showed that PmALMT1 is primarily associated with malic acid accumulation, whereas PmALMT8 is related to citric acid accumulation. Further transient expression in Nicotiana benthamiana validated the above conclusion. This comprehensive analysis provides valuable insights into the evolution, function, and regulation of the ALMT gene family in Rosaceae species.

Background/Objectives: Hemerocallis citrina Baroni (HCB) is a traditional herb for the treatment of depression in China. However, the active constituents and the underlying mechanisms of its antidepressant effects remain unclear. The aim of this study was to identify the bioactive constituents of HCB and elucidate its underlying mechanism for the treatment of depression. Methods: The constituents of HCB were systematically analyzed using UHPLC-Q-Orbitrap HRMS. Its antidepressant effect was evaluated by chronic unpredictable mild stress (CUMS)-induced depression. The mechanism of HCB in treating depression was investigated through network pharmacology and molecular docking. Subsequently, its potential mechanism for the treatment of depression was carried out by RNA sequencing. Finally, the mechanism was further verified by Western blot. Results: A total of 62 chemical constituents were identified from HCB using UHPLC-Q-Orbitrap HRMS, including 17 flavonoids, 11 anthraquinones, 11 alkaloids, 10 caffeoylquinic acid derivatives, five phenolic acids, five triterpenoids, and three phenylethanosides, 13 of which were identified as potential active constituents targeting 49 depression-associated proteins. Furthermore, HCB was found to significantly reduce cognitive impairment, anxiety-like behavior, and anhedonia-like behavior. The expression levels of 5-hydroxytryptamine (5-HT), dopamine (DA), and brain-derived neurotrophic factor (BDNF) were elevated in the hippocampal CA3 region. Results from network pharmacology and transcriptomics indicated that the PI3K/Akt/CREB signaling pathway is essential for the therapeutic effects of HCB on depression. Research in the field of molecular biology has conclusively demonstrated that HCB is associated with an increase in the expression levels of several important proteins. Specifically, there was a notable upregulation of phosphorylated PI3K (p-PI3K) relative to its unphosphorylated form PI3K, as well as an elevation in the ratio of phosphorylated Akt (p-Akt) to total Akt. Additionally, the study observed increased levels of phosphorylated CREB (p-CREB) compared to its unphosphorylated CREB. Conclusions: This study provides compelling evidence that HCB possesses the ability to mitigate the symptoms of depression through its influence on the PI3K/Akt/CREB signaling pathway. HCB could be developed as a promising therapeutic intervention for individuals struggling with depression, offering new avenues for treatment strategies that target this particular signaling mechanism.

With the rise in the intelligence levels of automated vehicles, increasing numbers of modules of automated driving systems are being combined to achieve better performance and adaptability by reducing information loss. In this study, an integrated decision and motion planning system is designed for multi-object highways. A two-layer structure is presented to decouple the influence of the traffic environment and the dynamic control of ego vehicles using the cognitive safety area, the size of which is determined by naturalistic driving behavior. The artificial potential field method is used to comprehensively describe the influence of all external objects on the cognitive safety area, the lateral motion dynamics of which are determined by the attention mechanism of the human driver during lane changes. Then, the interaction between the designed cognitive safety area and the ego vehicle can be simplified into a spring-damping system, and the desired dynamic states of the ego vehicle can be obtained analytically for better computational efficiency. The effectiveness of this on improving traffic efficiency, driving comfort, safety, and real-time performance was validated using several comparative tests utilizing complicated scenarios with multiple vehicles.

Surrounding rock squeezing is a common geological disaster in underground excavation projects (e.g., TBM tunneling and deep mining), which has adverse effects on construction safety, schedule, and property. To predict the squeezing of the surrounding rock accurately and quickly, this study proposes a hybrid machine learning paradigm that integrates generative artificial intelligence and deep ensemble learning. Specifically, conditional tabular generative adversarial network is devised to solve the problems of data shortage and class imbalance for data augmentation at the data level, and the deep random forest is built based on the augmented data for subsequent squeezing classification. A total of 139 historical squeezing cases are collected worldwide to validate the efficacy of the proposed modeling paradigm. The results reveal that this paradigm achieves a prediction accuracy of 92.86% and a macro F1-score of 0.9292. In particular, the individual F1-scores on strong squeezing and extremely strong squeezing are more than 0.9, with excellent prediction reliability for high-intensity squeezing. Finally, a comparative analysis with traditional machine learning techniques is conducted and the superiority of this paradigm is further verified. This study provides a valuable reference for surrounding rock squeezing classification under a limited data environment.