Epidemiological characteristics and antibody kinetics of elderly population with booster vaccination following both Omicron BA.5 and XBB waves in China.

After the termination of zero-COVID-19 policy, the populace in China has experienced both Omicron BA.5 and XBB waves. Considering the poor antibody responses and severe outcomes observed among the elderly following infection, we conducted a longitudinal investigation to examine the epidemiological characteristics and antibody kinetics among 107 boosted elderly participants following the Omicron BA.5 and XBB waves. We observed that 96 participants (89.7%) were infected with Omicron BA.5, while 59 (55.1%) participants were infected with Omicron XBB. Notably, 52 participants (48.6%) experienced dual infections of both Omicron BA.5 and XBB. The proportion of symptomatic cases appeared to decrease following the XBB wave (18.6%) compared to that after the BA.5 wave (59.3%). Omicron BA.5 breakthrough infection induced lower neutralizing antibody titers against XBB.1.5, BA.2.86, and JN.1, while reinfection with Omicron XBB broadened the antibody responses against all measured Omicron subvariants and may alleviate the wild type-vaccination induced immune imprinting. Boosted vaccination type and comorbidities were the significant factors associated with antibody responses. Updated vaccines based on emerging severe acute respiratory syndrome coronavirus 2 variants are needed to control the Coronavirus Disease 2019 pandemic in the elderly.

Robust Multiobjective Reinforcement Learning Considering Environmental Uncertainties.

Numerous real-world decision or control problems involve multiple conflicting objectives whose relative importance (preference) is required to be weighed in different scenarios. While Pareto optimality is desired, environmental uncertainties (e.g., environmental changes or observational noises) may mislead the agent into performing suboptimal policies. In this article, we present a novel multiobjective optimization paradigm, robust multiobjective reinforcement learning (RMORL) considering environmental uncertainties, to train a single model that can approximate robust Pareto-optimal policies across the entire preference space. To enhance policy robustness against environmental changes, an environmental disturbance is modeled as an adversarial agent across the entire preference space via incorporating a zero-sum game into a multiobjective Markov decision process (MOMDP). Additionally, we devise an adversarial defense technique against observational perturbations, which ensures that policy variations, perturbed by adversarial attacks on state observations, remain within bounds under any specified preferences. The proposed technique is assessed in five multiobjective environments with continuous action spaces, showcasing its effectiveness through comparisons with competitive baselines, which encompass classical and state-of-the-art schemes.

Parallel Driving with Big Models and Foundation Intelligence in Cyber-Physical-Social Spaces.

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs); on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the "6S" goals of parallel driving.

Unraveling Immune Heterogeneity across Pan-Cancer and Deep Insights in Lung Adenocarcinoma based on Alternative Splicing.

Alternative splicing (AS) participates in tumor development and tumor microenvironment formation. However, the landscape of immune infiltrating AS events (IIASE) in pan-cancer and mechanisms of AS in lung adenocarcinoma (LUAD) have not been comprehensively characterized. We systematically profiled the IIASE landscape of pan-cancer using data from The Cancer Genome Atlas (TCGA), analyzing both commonalities and specific characteristics among different cancer types. We found that AS events tend to occur specifically in one cancer type rather than in multiple cancer types. AS events were used to classify 512 LUAD samples into two subtypes by unsupervised clustering: aberrant splicing subtype (ABS) and immune infiltrating subtype (IIS). The two subtypes showed significant differences in clinicopathology, prognosis, transcriptomics, genomics and immune microenvironment. We constructed a classification signature comprising 10 genes involved in 14 AS events using Logistic regression. The robustness of the signature was validated in three independent datasets using survival analysis. To explore AS mechanisms in LUAD, we constructed subtype-specific co-expression networks using Pearson correlation analysis. AS event of AKT3 regulated by splicing factor ENOX1 was associated with poor prognosis in LUAD. Overall, we outline AS events associated with immune infiltration in pan-cancer and this study provides insights into AS mechanisms in LUAD patient classification.

Determining soil conservation strategies: Ecological risk thresholds of arsenic and the influence of soil properties.

The establishment of ecological risk thresholds for arsenic (As) plays a pivotal role in developing soil conservation strategies. However, despite many studies regarding the toxicological profile of As, such thresholds varying by diverse soil properties have rarely been established. This study aims to address this gap by compiling and critically examining an extensive dataset of As toxicity data sourced from existing literature. Furthermore, to augment the existing information, experimental studies on As toxicity focusing on barley-root elongation were carried out across various soil types. The As concentrations varied from 12.01 to 437.25 mg/kg for the effective concentrations that inhibited 10% of barley-root growth (EC10). The present study applied a machine-learning approach to investigate the complex associations between the toxicity thresholds of As and diverse soil properties. The results revealed that Mn-/Fe-ox and clay content emerged as the most influential factors in predicting the EC10 contribution. Additionally, by using a species sensitivity distribution model and toxicity data from 21 different species, the hazardous concentration for x% of species (HCx) was calculated for four representative soil scenarios. The HC5 values for acidic, neutral, alkaline, and alkaline calcareous soils were 80, 47, 40, and 28 mg/kg, respectively. This study establishes an evidence-based methodology for deriving soil-specific guidance concerning As toxicity thresholds.

The safety and efficacy of neoadjuvant immunochemotherapy following laparoscopic gastrectomy for gastric cancer: a multicenter Real-world clinical study.

BACKGROUND: The safety and efficacy of neoadjuvant immunochemotherapy (nICT) for locally advanced gastric cancer (LAGC) remain controversial. METHODS: Patients with LAGC who received either nICT or neoadjuvant chemotherapy (nCT) at 3 tertiary referral teaching hospitals in China between January 2016 and October 2022 were analysed. After propensity-score matching (PSM), comparing the radiological response, pathological response rate, perioperative outcomes, and early recurrence between the two groups. RESULTS: After PSM, 585 patients were included, with 195 and 390 patients comprising the nICT and nCT groups, respectively. The nICT group exhibited a higher objective response rate (79.5% versus [vs.] 59.0%; P<0.001), pathological complete response rate (14.36% vs. 6.41%; P=0.002) and major pathological response rate (39.49% vs. 26.15%; P=0.001) compared with the nCT group. The incidence of surgical complications (17.44% vs. 16.15%, P=0.694) and proportion of perioperative textbook outcomes (80.0% vs. 81.0%; P=0.767) were similar in both groups. The nICT group had a significantly lower proportion of early recurrence than the nCT group (29.7% vs. 40.8%; P=0.047). Furthermore, the multivariable logistic analysis revealed that immunotherapy was an independent protective factor against early recurrence (odds ratio 0.62 [95% CI 0.41-0.92]; P=0.018). No significant difference was found in neoadjuvant therapy drug toxicity between the two groups (51.79% vs. 45.38%; P=0.143). CONCLUSIONS: Compared with nCT, nICT is safe and effective, which significantly enhanced objective and pathological response rates, and reduced the risk for early recurrence among patients with LAGC. TRIAL REGISTRATION: Clinical Trials.gov.

circAMN1-Mediated Ferroptosis Regulates the Expulsion of Placenta in Trophoblast Cells.

After delivery, the death of trophoblast cells can promote the expulsion of the placenta. Ferroptosis, an iron-dependent programmed cell death, is involved in mammalian development. Circular RNAs are associated with placental development; however, it is unclear whether circular RNAs regulate the expulsion of fetal membranes through ferroptosis. The gene expression profiles in the tail vein blood of Holstein cows with normal and retained placentas were investigated using RNA sequencing and a GSE214588 dataset. circAMN1 and SLC39A8 expression was significantly downregulated in the blood of cows with a retained placenta, whereas miR-205_R-1 expression was significantly upregulated. We validated erastin-induced ferroptosis in trophoblast cells. Transfection with si-circAMN1 and miR-205_R-1 mimic reduced intracellular total iron, Fe2+, and glutathione disulfide levels; increased intracellular glutathione levels and glutathione/glutathione disulfide; and enhanced cell viability in these cells. In contrast, transfection with pcDNA3.1 circAMN1 and an miR-205_R-1 inhibitor promoted ferroptosis. As an miR-205_R-1 sponge, circAMN1 regulated the expression of SLC39A8 to control erastin-induced ferroptosis and regulated the proliferation, invasion, and migration of trophoblast cells. Our findings provide a theoretical basis for studying the mechanism by which programmed cell death regulates fetal membrane expulsion and indicate its potential as a therapeutic target for placenta retention.

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis.

BACKGROUND: The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. METHODS: We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level. FINDINGS: We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species. INTERPRETATION: The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions. FUNDING: National Key Research and Development Program of China.

Effects of periodic heat events on the reproduction and longevity of female and male Agasicles hygrophila (Coleoptera: Chrysomelidae).

Alternanthera philoxeroides (Amaranthaceae), commonly known as alligator weed, is a globally invasive and detrimental perennial weed. Agasicles hygrophila serves as an important biocontrol agent for alligator weeds. However, during mid-summer, when temperatures increase, A. hygrophila populations experience a significant decline, leading to ineffective weed control. This study has examined the impact of periodic heat events on the reproduction and survival of A. hygrophila females and males using various mating combinations and durations of temperature treatments. The results demonstrated significant effects on all of the studied parameters across mating combinations when compared with the control. Under the same temperature combination, the fecundity and survival rates of females, as well as the egg-hatching rate, decreased significantly with increasing repeated heat exposure. Furthermore, the egg-hatching rate varied significantly among different temperatures and time-interval combinations. In addition, the females displayed greater sensitivity to heat stress than males in terms of fecundity. These findings enhance our understanding of A. hygrophila population dynamics during summer and provide insights into the release of biocontrol agents in diverse regions with varying climates.

Evaluation Method of Fatigue Life for Asphalt Pavement on the Steel Bridge Deck Based on the Inhomogeneous Poisson Stochastic Process.

The paving layer on the steel box girder bridge deck is widely used when constructing pavements for steel bridges. Owing to the orthotropic feature of steel decks, a transverse clapboard and rib can lead to a concentration of stress. Consequently, fatigue cracks are often identified in asphalt concrete pavement layers due to re-compaction caused by heavy vehicles. This study aims to derive an evaluation method of fatigue life for asphalt pavement based on the inhomogeneous Poisson stochastic process in view of the highly random and uncertain working conditions of layered composite structures. According to the inhomogeneous Poisson stochastic process, along with Miner's fatigue damage accumulation theory and the linear elastic fracture mechanics theory, the fatigue life formula could be deduced. Meanwhile, fatigue experiments for asphalt concrete are designed to investigate the correlation between the theoretical formula and the actual fatigue damage life of the material. Compared with the test, the accuracy error is within 10%, which is better than other traditional methods. Therefore, the fatigue life prediction model could better reflect the loading order effect and the interaction between loads, providing a new path for the fatigue reliability design of steel bridge deck asphalt pavement.

Expanding carbon neutrality strategies: Incorporating out-of-boundary emissions in city-level frameworks.

Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.

Development and Validation of a Prognostic Model for Postoperative Anastomotic Recurrence in Siewert II or III Adenocarcinomas Without Neoadjuvant Therapy in an East Asian Population.

PURPOSE: Anastomotic recurrence leads to poor prognosis in patients with Siewert II or III adenocarcinoma who undergo radical gastrectomy and do not receive neoadjuvant therapy. We aimed to establish a prognostic model to evaluate the risk of postoperative anastomotic recurrence in patients with Siewert II or III adenocarcinoma who did not receive neoadjuvant therapy. METHODS: We included 366 patients with Siewert II or III adenocarcinoma who were treated with radical gastrectomy without neoadjuvant therapy at Fujian Provincial Hospital (FPH) between 2012 and 2018 as the development cohort. Cox regression was used to verify prognostic factors for anastomotic recurrence, and a nomogram was established. The nomogram was externally validated using a combined cohort of two external centers. Patients were classified into high- or low-risk groups according to the diagnostic threshold and nomogram scores, and recurrence-related survival analysis was analyzed. RESULTS: The average age was 64.6 years, and 285 patients were male. All surgeries were successfully performed (185 open vs 181 laparoscopic). The 3-year anastomotic recurrence rate was significantly lower in the low-risk group (3.5% vs 18.8%, P < 0.001). The predictive performance was verified in the external validation cohort. This model better stratified patient survival than the American Joint Committee on Cancer (AJCC) TNM staging system. CONCLUSIONS: This novel nomogram with surgical margin, postoperative tumor node metastasis (pTNM) stage, and neural invasion as prognostic factors has a significant predictive performance for the risk of anastomotic recurrence after radical gastrectomy in patients with Siewert II or III adenocarcinoma.

Examination of the role of the rotating nursing department in the training of nursing staff based on SWOT analysis.

BACKGROUND: The implementation of the rotation system in the Chinese medical industry has achieved significant results. OBJECTIVES: The present study aims to 1) explore the strengths, weaknesses, opportunities and challenges of rotational nursing department implementation and 2) provide references for developing nursing staff's competencies in leadership, performance evaluation, quality of care, communication in relationships and human resources. METHODS: A total of 16 rotational nursing department staff members from a tertiary tuberculosis specialist hospital in Beijing were interviewed, and the interview data were analysed using a strengths, weaknesses, opportunities and threats analysis and class analysis. RESULTS: The advantages of the rotational nursing department included: (1) stimulating the nursing staff's enthusiasm and creativity; (2) strengthening the communication and collaboration between departments; (3) improving the detailed management of nursing quality; and (4) enhancing the nursing staff's comprehensive abilities. The disadvantages included: (1) the design of the rotation programme focusing on practice; (2) a lack of personalisation; and (3) imperfect performance assessment of the rotating staff. Opportunities included: (1) deepening the connotation of nursing job management and (2) developing the construction of nursing discipline and the need for personal career development and value realisation. Threats included the lack of a sound rotation management model to draw on. CONCLUSION: A rotational nursing department is conducive to enhancing the competence of nursing staff in management positions and providing new ideas for hospitals to select and train nursing management talents. By taking full advantage of the benefits of vertical nursing management, designing personalised rotation training programmes, building a diversified learning and training platform and developing a positive performance incentive mechanism is recommended to fully engage the role of rotation in nursing management talent training.

LncRNA TYMSOS is a novel prognostic biomarker associated with immune infiltration in prostate cancer.

The long noncoding RNA thymidylate synthetase opposite strand (lncRNA TYMSOS) plays an important role in cancers; however, its impact on prostate cancer (PCa) is still unclear. By analyzing the online data, we found that lncRNA TYMSOS was highly expressed in PCa and associated with T stage, Gleason score, age, and primary therapy outcome. The results of the ROC curve showed that lncRNA TYMSOS has a significant diagnostic ability. Furthermore, Kaplan-Meier analyses suggested that lncRNA TYMSOS plays an important role in progression-free survival (PFS). Increased lncRNA TYMSOS expression was an independent risk factor correlated with PFS in PCa patients. GSEA and GSVA indicated that the lncRNA TYMSOS was involved in the cell cycle, neurodegenerative diseases, oxidative phosphorylation, spliceosomes, and adaptive immune system pathways. Additionally, lncRNA TYMSOS expression was also associated with immune cell infiltrates and tumor mutational burden in PCa. Functional experiments were further conducted, and we verified that lncRNA TYMSOS played an oncogenic role in regulating PCa aggressiveness. Specifically, silencing of lncRNA TYMSOS suppressed cell proliferation, division and epithelial-mesenchymal transition (EMT) but promoted cell apoptosis in PCa cells, and conversely, lncRNA TYMSOS overexpression had the opposite effects. In summary, our study revealed that the lncRNA TYMSOS could be a biomarker and therapeutic target in PCa and participate in tumor-immune cell infiltration.

EXOSC2 Mediates the Pro-tumor Role of WTAP in Breast Cancer Cells via Activating the Wnt/ß-Catenin Signal.

BC (breast cancer) is the leading cause of cancer death in women. Exosome component 2 (EXOSC2), an RNA exosome component, is elevated in BC tissues and may relate to BC carcinogenesis. In this work, the high EXOSC2 expression was correlated with TNM (Tumor Node Metastasis) stage. Moreover, overexpression of EXOSC2 enhanced tumorigenic capacity of BC cells via facilitating cell proliferation and cell cycle progression, increasing migration and angiogenesis, as well as exacerbating xenograft formation in vivo. Whereas, EXOSC2 knockdown showed anti-cancer effects, including inhibition of cell proliferation and angiogenesis. Mechanistically, EXOSC2 activated the wnt/ß-catenin pathway, which was also abolished by EXOSC2 knockdown. In addition, there were m6A methylation modification sites in the mRNA of EXOSC2. WTAP (Wilms tumor 1-associated protein) bound to EXOSC2 mRNA and increased its m6A methylation, resulting in extending the half-life of EXOSC2 mRNA. Luciferase data also confirmed that WTAP enhanced EXOSC2 mRNA stability through binding with the 3'-UTR containing m6A sites. Furthermore, WTAP silencing exhibited cancer-inhibiting effects on cell viability, cell cycle progression and tube formation, which was effectively reversed by EXOSC2 overexpression. In conclusion, our results demonstrate that EXOSC2 promotes the malignant behaviors of BC cells via activating the wnt/ß-catenin pathway. In addition, EXOSC2 mediates the function of WTAP which contributes to the m6A modification of EXOSC2. Totally, this study suggested that EXOSC2 mediated the pro-tumor role of WTAP via activating the wnt/ß-catenin signal.

Sampling Efficient Deep Reinforcement Learning Through Preference-Guided Stochastic Exploration.

Stochastic exploration is the key to the success of the deep Q -network (DQN) algorithm. However, most existing stochastic exploration approaches either explore actions heuristically regardless of their Q values or couple the sampling with Q values, which inevitably introduce bias into the learning process. In this article, we propose a novel preference-guided ϵ -greedy exploration algorithm that can efficiently facilitate exploration for DQN without introducing additional bias. Specifically, we design a dual architecture consisting of two branches, one of which is a copy of DQN, namely, the Q branch. The other branch, which we call the preference branch, learns the action preference that the DQN implicitly follows. We theoretically prove that the policy improvement theorem holds for the preference-guided ϵ -greedy policy and experimentally show that the inferred action preference distribution aligns with the landscape of corresponding Q values. Intuitively, the preference-guided ϵ -greedy exploration motivates the DQN agent to take diverse actions, so that actions with larger Q values can be sampled more frequently, and those with smaller Q values still have a chance to be explored, thus encouraging the exploration. We comprehensively evaluate the proposed method by benchmarking it with well-known DQN variants in nine different environments. Extensive results confirm the superiority of our proposed method in terms of performance and convergence speed.

Smart-seq2 Technology Reveals a Novel Mechanism That Zearalenone Inhibits the In Vitro Maturation of Ovine Oocytes by Influencing TNFAIP6 Expression.

Zearalenone (ZEN), a non-steroidal estrogenic fungal toxin widely present in forage, food, and their ingredients, poses a serious threat to animal and human reproductive health. ZEN also threatens ovine, a major source of human food and breeding stock. However, the mechanisms underlying the impact of ZEN on the in vitro maturation (IVM) of ovine oocytes remain unclear. This study aimed to elucidate these mechanisms using the Smart-seq2 technology. A total of 146 differentially expressed genes were obtained, using Smart-seq2, from sheep oocytes cultured in vitro after ZEN treatment. ZEN treatment inhibited RUNX2 and SPP1 expression in the PI3K signaling pathway, leading to the downregulation of THBS1 and ultimately the downregulation of TNFAIP6; ZEN can also decrease TNFAIP6 by reducing PTPRC and ITGAM. Both inhibit in vitro maturation of ovine oocytes and proliferation of cumulus cells by downregulating TNFAIP6. These findings provide data and a theoretical basis for elucidating ZEN's toxicity mechanisms, screening therapeutic drugs, and reducing ZEN-related losses in the ovine industry.

Inhibition characteristics research of aluminum alloy polishing dust explosion through addition of ultrafine Al(OH)3 inerting agent.

Investigations into the deactivation of explosion sensitivity and reduction of flame propagation for aluminium alloy polishing wastes were carried out by the addition of ultrafine Al(OH)3 inerting agent. Meanwhile, high-purity aluminium powders with similar mean diameters were also used as a comparative study. The explosion propagation characteristics of high-purity aluminium dust and aluminium alloy polishing waste dust under different inerting ratios (ε) were tested and investigated using a standardised Hartmann tester and a developed experimental platform. The results show that the minimum ignition energy of high-purity aluminium powder is between 40 and 45 mJ, and the minimum ignition energy of aluminium alloy polishing waste is between 500 and 550 mJ, which is one order of magnitude higher than that of high-purity aluminium powder. The lower explosion limit concentration of aluminium alloy polishing waste dust is 150 g/m3, which is 53.33% of that of high-purity aluminium powder. According to the analysis of the SEM image, the main reason is that the spherical particles of high-purity aluminium dust have a folded surface and good dispersion. Compared with the smooth fibre surface of aluminium alloy polishing waste dust, the former is easier to contact with air and the contact area is larger. Therefore, in engineering practice, it is not appropriate to use high-purity aluminium dust-related explosion parameters as the basis for the risk assessment of combustion and explosion at aluminium alloy polishing work sites. In addition, as the dust concentration decreases, the combustion intensity of high-purity aluminium dust and aluminium alloy polishing waste dust also decreases, and the flame propagation appears to be a discontinuous phenomenon. The peak flame propagation velocity of aluminium alloy polishing waste is 7.368 m/s at a concentration of 300 g/m3, which is 56.85% of that of high-purity aluminium powder. As the inerting ratio increases, the propagation velocity of the explosion flame slows down. When the inerting ratio reaches 30%, the minimum ignition energy of aluminium alloy polishing waste is inerted to 1 J, and self-sustained flame propagation cannot be formed. The results show that the ultra-fine Al(OH)3 powder has a significant inerting effect and is a realistic possibility in the production of aluminium alloy polishing.

A fully human monoclonal antibody targeting Semaphorin 5A alleviates the progression of rheumatoid arthritis.

Rheumatoid arthritis (RA) is the most common chronic autoimmune disease worldwide. Although progress has been made in RA treatment in recent decades, remission cannot be effectively achieved for a considerable proportion of RA patients. Thus, novel potential targets for therapeutic strategies are needed. Semaphorin 5A (SEMA5A) plays a pivotal role in RA progression by facilitating pannus formation, and it is a promising therapeutic target. In this study, we sought to develop an antibody treatment strategy targeting SEMA5A and evaluate its therapeutic effect using a collagen-induced arthritis (CIA) model. We generated SYD12-12, a fully human SEMA5A blocking antibody, through phage display technology. SYD12-12 intervention effectively inhibited angiogenesis and aggressive phenotypes of RA synoviocytes in vitro and dose-dependently inhibited synovial hyperplasia, pannus formation, bone destruction in CIA mice. Notably, SYD12-12 also improved the Treg/Th17 imbalance in CIA mice. We confirmed through immunofluorescence and molecular docking that SYD12-12 integrated with the unique TSP-1 domain of SEMA5A. In conclusion, we developed and characterized a fully human SEMA5A-blocking antibody for the first time. SYD12-12 effectively alleviated disease progression in CIA mice by inhibiting pannus formation and improving the Treg/Th17 imbalance, demonstrating its potential for the RA treatment.

FPattNet: A Multi-Scale Feature Fusion Network with Occlusion Awareness for Depth Estimation of Light Field Images.

A light field camera can capture light information from various directions within a scene, allowing for the reconstruction of the scene. The light field image inherently contains the depth information of the scene, and depth estimations of light field images have become a popular research topic. This paper proposes a depth estimation network of light field images with occlusion awareness. Since light field images contain many views from different viewpoints, identifying the combinations that contribute the most to the depth estimation of the center view is critical to improving the depth estimation accuracy. Current methods typically rely on a fixed set of views, such as vertical, horizontal, and diagonal, which may not be optimal for all scenes. To address this limitation, we propose a novel approach that considers all available views during depth estimation while leveraging an attention mechanism to assign weights to each view dynamically. By inputting all views into the network and employing the attention mechanism, we enable the model to adaptively determine the most informative views for each scene, thus achieving more accurate depth estimation. Furthermore, we introduce a multi-scale feature fusion strategy that amalgamates contextual information and expands the receptive field to enhance the network's performance in handling challenging scenarios, such as textureless and occluded regions.