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Digital twins can facilitate high-fidelity representations of container terminals by applying various technologies and methods to better measure, understand, and improve operations. In this paper, a decision support system (DSS) based on digital twin and big data technologies is designed to demonstrate how real-time monitoring and an integrated decision support can be established. The DSS provides optimal operation plans and the benchmark for vessel delay early warnings through different resource allocation simulations at the planning level. It further enables real-time operational decision making through real-time monitoring and efficiency analyses using big data engines at the operational level. A case study is conducted for the ultralarge Yangshan Deepwater Automated Container Terminal Phase IV (ACT4) in Shanghai (China) and experimental results have revealed that the proposed digital twin-based DSS can help ACT4 operators to evaluate vessel service using optimized resource allocation plans and operations.

The global outbreak of the mpox virus (MPXV) in 2022 highlights the urgent need for safer and more accessible new-generation vaccines. Here, we used a structure-guided multi-antigen fusion strategy to design a ‘two-in-one’ immunogen based on the single-chain dimeric MPXV extracellular enveloped virus antigen A35 bivalently fused with the intracellular mature virus antigen M1, called DAM. DAM preserved the natural epitope configuration of both components and showed stronger A35-specific and M1-specific antibody responses and in vivo protective efficacy against vaccinia virus (VACV) compared to co-immunization strategies. The MPXV-specific neutralizing antibodies elicited by DAM were 28 times higher than those induced by live VACV vaccine. Aluminum-adjuvanted DAM vaccines protected mice from a lethal VACV challenge with a safety profile, and pilot-scale production confirmed the high yield and purity of DAM. Thus, our study provides innovative insights and an immunogen candidate for the development of alternative vaccines against MPXV and other orthopoxviruses. Gao and colleagues report a structure-guided chimeric antigen based on the A35 and M1 antigens of the mpox virus (MPXV) that induces strong MPXV-specific antibody responses and protection against lethal doses of vaccinia virus in mice.

UV photolysis has been recommended as an alternative pretreatment method for the elimination of antibacterial activity of antibiotics against the indicator strain, but the pretreated antibiotic intermediates might not lose their potential to induce antibiotic resistance genes (ARGs) proliferation during subsequent biotreatment processes. The presence of florfenicol (FLO) in wastewater seriously inhibits the metabolic performance of anaerobic sludge microorganisms, especially the positive correlation between UV irradiation doses and ATP content, while it did not significantly affect the organics utilization ability and protein biosynthetic process of aerobic microorganisms. After sufficient UV pretreatment, the relative abundances of floR from genomic or plasmid DNA in subsequent aerobic and anaerobic biotreatment processes both decreased by two orders of magnitude, maintained at the level of the groups without FLO selective pressure. Meanwhile, the abundances of floR under anaerobic condition were always lower than that under aerobic condition, suggesting that anaerobic biotreatment systems might be more suitable for the effective control of target ARGs. The higher abundance of floR in plasmid DNA than in genome also indicated that the potential transmission risk of mobile ARGs should not be ignored. In addition, the relative abundance of intI1 was positively correlated with floR in its corresponding genomic or plasmid DNA ( p < 0.05), which also increased the potential horizontal transfer risk of target ARGs. This study provides new insights into the effect of preferential UV photolysis as a pretreatment method for the enhancement of metabolic performance and source control of target ARGs in subsequent biotreatment processes. Key points • Sufficient UV photolytic pretreatment efficiently controlled the abundance of floR • A synchronous decrease in abundance of intI1 reduced the risk of horizontal transfer • An appreciable abundance of floR in plasmid DNA was a potential source of total ARGs Graphical abstract

Lactic acid and other α-hydroxycarboxylic acids (α-HCAs) play crucial roles in various applications. Synthesizing α-HCAs from biomass platform feedstocks such as ethylene glycol (EG) and primary alcohols is novel and attractive. It was reported that the dehydrogenative cross-coupling of EG and primary alcohols can be achieved via homogeneous catalysis. Herein, we report a heterogeneous catalytic strategy to produce a series of α-HCAs through the same reaction pathway. Impressive catalytic activity and selectivity were achieved using various metals (Ru, Ir, Pt and Pd) supported on the nanodiamond-graphene (ND@G), with Ru exhibiting the best performance. This universally applicable process enables the easy synthesis of gram-scale α-HCAs, providing a straightforward and compelling C-C bond cross-coupling strategy for the utilization of alcohols derived from biomass feedstocks.

Zinc homeostasis and zinc transporter (ZHT) have been closely associated with the development of various cancers. Therefore, in this study, prognostic genes and their mechanisms related to ZHT in breast cancer (BC) were explored. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to identify genes associated with Zinc homeostasis and Zinc transporter-related genes (ZHTGs) in BC. Subsequently, independent prognostic factors and their correlations with clinical features were examined to investigate their association with the prognosis of BC. Finally, we further explored the pathways and immune cells associated with BC prognosis. We also verified gene expression in tissues and cells by quantitative polymerase chain reaction (qPCR). In this study, six prognostic genes were identified. Patients were subsequently classified into high-risk and low-risk cohorts based on the median risk score, with the low-risk group presenting superior survival outcomes. Subsequently, riskScore, age, tumor/node/metastasis (T/N/M) stage showed significant associations with the prognosis of BC, and the constructed nomogram demonstrated strong predictive performance. Clinical analysis revealed differences in risk scores among sub-cohorts with different clinical characteristics, such as race (white and others) and T-stage (T1 and T2, T1 and T3). Furthermore, significant disparities were noted in immune cells and immune checkpoints across different risk cohorts. The results of reverse transcription quantitative PCR were basically consistent with the prediction. In addition, the IHC results from the Human Protein Atlas database further validated our prediction. We screened six prognosis genes related to ZHT in BC, providing a reference for the prognosis and personalized treatment of BC.

Cell-in-cell structures (CICs), a novel biomarker for complex cellular interactions, have garnered increasing attention for their potential in predicting cancer patient prognosis. However, the prognostic significance of CICs in tumor outcomes remains inconclusive. To address this, we conducted a meta-analysis to assess the prognostic value of CICs in solid tumors, adhering to the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines. PubMed, Web of Science, and Cochrane Library databases were searched up to October 2024 for the retrieval of full articles. Studies related to the prognosis of cell-in-cell and solid tumors were considered eligible for analysis. The quality of the included studies was assessed according to the National Institute for Health and Clinical Excellence (NICE) Quality assessment tool. We included 1836 patients with solid tumors to evaluate the association between overall cell-in-cell structures (oCICs) and prognosis, and 429 patients to evaluate the association between four subtypes of CICs (tumor-in-tumor [TiT], tumor-in-macrophage [TiM], macrophage-in-tumor [MiT], and lymphocyte-in-tumor [LiT]) and prognosis. We present the hazard ratio (HR) for overall survival (OS) for the number of CICs for each solid tumor. The combined HR for OS of oCICs was 1.64 (95% CI, 1.18-2.28; = 0.003), and for LiT, it was 1.43 (95% CI, 1.12-1.83; = 0.005), indicating that both oCICs and LiT are reliable prognostic factors for solid tumors. However, the combined HRs for OS of TiT, TiM, and MiT were 0.72 (95% CI, 0.35-1.48; = 0.37), 1.28 (95% CI, 0.67-2.45; = 0.46), and 1.54 (95% CI, 0.93-2.56; = 0.09), respectively, suggesting that these subtypes may not be reliable prognostic factors due to the limited number of studies. The presence of higher numbers of oCICs and LiT is an adverse prognostic factor for patients and affects OS.

To construct a novel immune-inflammatory-nutritional (IIN) score based on peripheral blood biomarkers related to inflammation, immunity, and nutrition, and to predict the efficacy of neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer (TNBC). We retrospectively selected 431 patients with TNBC from Xijing Hospital, and then randomly divided the patients into a training set and an internal validation set in a ratio of 7:3. An external validation set was included with 154 patients selected from West China Hospital of Sichuan University. In the training set, patients were divided into the pathological complete response (pCR) group and the non-pathological complete response group. Univariate logistic regression analysis and LASSO regression analysis were used to select biomarkers that affect the efficacy of NAC in TNBC patients and to construct the IIN score. A nomogram model was constructed based on the IIN score and clinical pathological characteristics to predict whether TNBC patients could achieve pCR after NAC before treatment. The predictive performance and clinical application value of the nomogram model were assessed using the receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis, and confusion matrix. Through LASSO regression analysis, 6 biomarkers were ultimately identified to construct the scoring system. A nomogram model was constructed based on the IIN score and clinical pathological characteristics, and the ROC curve showed the areas under the curve to be 0.827, 0.786, and 0.754 in the training set, internal validation set, and external validation set, respectively. Calibration curves, decision curves, and confusion matrices all demonstrated that the nomogram model exhibited robust predictive performance and holds certain clinical application value. The nomogram model based on the IIN score offers high predictive performance and can accurately predict the efficacy of NAC in TNBC patients before treatment, highlighting its clinical application potential.

Microbial fuel cells (MFCs) are promising technologies, aiming at treating different types of industrial and domestic wastewater. In recent years, more and more publications focusing on wastewater treatment have been published. Based on the retrieval of publications from Web of Science Core Collection database, the new emerging trends of microbial fuel cells in wastewater treatment was evaluated with a scientometric analysis method from 1995 to 2020. All publications downloaded from (WOS) were screened by inclusion criteria, and 2233 publications were obtained for further analysis. Document co-citation and burst detection of MFCs in wastewater treatment were analyzed and visualized by software of CiteSpace. Our study indicated that “Environmental Science” is the most popular discipline, while the journal of Bioresource Technology published the greatest quantity of articles in the field of MFCs applied wastewater treatment. China and the Chinese Academy of Science are the most productive country and institution, respectively. “Azo dye” has become the new research topic, which indicates the application area and the development of MFCs. The performance of MFCs for wastewater treatment has been widely discussed. The findings of this study may ameliorate the researcher in seizing the frontier of MFCs in wastewater treatment.

Marine Oil spills have become a serious environmental problem, and contribute to severe impacts and economic losses. Fast and efficient cleanup of oil from marine environment is vital. The use of sorbents is one of the most efficient techniques in removing oil from water. In this work, pure polypropylene (PP) ultrafine fibers with 2 μm diameter were prepared by air assisted melt electrospinning device to be used as oil sorbent. Two fiber samples were used in this study, fluffy, cotton like appearance and oriented, cloth like appearance with different porosities. The influence of temperature change on oil/water mixture was studied. Fluffy fibers showed a better performance in sorption capacity. Results indicated that change in temperature was an important factor in determining the sorption capacity of the fibers. Additionally, in contrast to solution electrospinning, melt electrospinning is safer, cost effective and environmental friendly because of solvents elimination.