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Abstract The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transformers as the feature extraction and encoding layers for images, enabling the network to capture both local geometric and global semantic features for depth estimation. First, depth-separable convolution is used to construct a dilated convolution residual module based on a shallow network to improve the shallow CNN feature extraction receptive field. In the transformer, a multidepth separable convolution head transposed attention module is proposed to reduce the computational burden of spatial self-attention. In the feedforward network, a two-step gating mechanism is proposed to improve the nonlinear representation ability of the feedforward network. Finally, the CNN and transformer are integrated to implement a depth estimation network with a local-global context interaction function. Compared with other lightweight models, this model has fewer model parameters and higher estimation accuracy. It also has better generalizability for different outdoor datasets. Additionally, the inference speed can reach 87 FPS, achieving better real-time performance and accounting for both inference speed and estimation accuracy.

Abstract A dynamic nonline-of-sight (NLOS) angle discrimination method is proposed to address the insufficiency of current research on the NLOS error characteristics of ultrawideband (UWB) signals in dynamic environments as well as the problem that UWB signals frequently suffer from occlusion, leading to poor or impossible localization. The experimental results indicate that the degree of UWB signal occlusion increases as the horizontal angle decreases, and when the horizontal angle is less than 167°, the UWB ranging error is so large that no ranging value is available. On this basis, a tightly integrated UWB/MEMS IMU positioning algorithm incorporating NLOS angle discrimination and map constraints is proposed; it employs horizontal angles to discriminate UWB ranging values in NLOS environments in accordance with the dynamic NLOS characteristics of UWB signals to assign better weights to UWB observations. Through comparative analysis of the results from both groups of experiments, the algorithm achieved northward, eastward, and planar positioning errors of 0.189 m and 0.126 m, 0.119 m and 0.134 m, 0.243 m and 0.211 m, respectively. Compared to the Robust Adaptive Kalman Filtering algorithm, the positional accuracy in the plane improved by 22.9% and 28.5%, respectively.

Abstract Background Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS. Methods A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated. Results During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P

Abstract Objective To investigate pantothenate kinases 1 (PANK1) expression in kidney renal clear cell carcinoma (KIRC) tissues, analyze its correlation with clinicopathological features and prognosis, and explore its impact on invasion, migration, and apoptosis in KIRC cells. Methods GEPIA (gene expression profiling interactive analysis), UALCAN and LinkedOmics, were employed to analyze PANK1 expression in KIRC tissues and its correlation with clinical characteristics. Comparative analyses were performed between KIRC (Caki-1 and 786-O) and noncancerous renal cells (HK-2 and RPTEC). Transfection with PANK1 activation particles was conducted, followed by Wound healing, Transwell assay, Annexin V-fluorescein isothiocyanate/propidium iodide (Annexin V-FITC/PI) staining, quantitative reverse-transcription polymerase chain reaction (qRT-PCR), and Western blotting. Results PANK1 was down-regulated in KIRC tissues and cells compared to normal tissues and noncancerous cells. Correlation analyses linked PANK1 expression with clinicopathological features in KIRC, with high PANK1 expression associated with a favorable outcome. High PANK1 expression correlated positively with E-cadherin (CDH1), tight junction protein 1 (TJP1), Fas cell surface death receptor (FAS), caspase-8 (CASP8), and CASP9, while showing a negative correlation with vimentin (VIM), snail family transcriptional repressor 1 (SNAIL1), twist family BHLH transcription factor 1 (TWIST1), and TWIST2. PANK1 overexpression increased CDH1, TJP1, FAS, CASP8, and CASP9 while downregulating SNAIL1, VIM, TWIST1, and TWIST2, inhibiting invasion and migration, and promoting apoptosis in KIRC cells. Conclusion PANK1 down-regulation in KIRC tissues correlated with clinicopathological features and prognosis. Its overexpression modulated epithelial-mesenchymal transition (EMT)-related gene, inhibited invasion, promoted apoptosis in KIRC cells, highlighting its role in disease progression and therapeutic potential.

Abstract Mitochondrial RNA (mtRNA) in the cytosol can trigger the innate immune sensor MDA5, and autoinflammatory disease due to type I IFN. Here, we show that a dominant negative mutation in the gene encoding the mitochondrial exonuclease REXO2 may cause interferonopathy by triggering the MDA5 pathway. A patient characterized by this heterozygous de novo mutation (p.T132A) presented with persistent skin rash featuring hyperkeratosis, parakeratosis and acanthosis, with infiltration of lymphocytes and eosinophils around small blood vessels. In addition, circulating IgE levels and inflammatory cytokines, including IFNα, are found consistently elevated. Transcriptional analysis highlights a type I IFN gene signature in PBMC. Mechanistically, REXO2 (T132A) lacks the ability to cleave RNA and inhibits the activity of wild-type REXO2. This leads to an accumulation of mitochondrial dsRNA in the cytosol, which is recognized by MDA5, leading to the associated type I IFN gene signature. These results demonstrate that in the absence of appropriate regulation by REXO2, aberrant cellular nucleic acids may accumulate and continuously trigger innate sensors, resulting in an inborn error of immunity.

Abstract Pseudorabies have caused enormous economic losses in China’s pig industry and have recurred on many large pig farms since late 2011. The disease is caused by highly pathogenic, antigenic variant pseudorabies virus (vPRV) strains. Our laboratory isolated a pseudorabies virus in 2015 and named it XJ5. The pathogenic ability of this mutant strain was much stronger than that of the original isolate. After we sequenced its whole genome (GenBank accession number: OP512542), we found that its overall structure was not greatly changed compared with that of the previous strain Ea (KX423960.1). The whole genome alignment showed that XJ5 had a strong genetic relationship with the strains isolated in China after 2012 reported in GenBank. Based on the isolation time of XJ5 and the mutation and recombination analysis of programs, we found that the whole genome homology of XJ5 and other strains with Chinese isolates was greater than 95%, while the homology with strains outside Asia was less than 94%, which indicated that there may be some recombination and mutation patterns. We found that virulent PRV isolates emerged successively in China in 2011 and formed two different evolutionary clades from foreign isolates. At the same time, this may be due to improper immunization and the presence of wild strains in the field, and recent reports have confirmed that Bartha vaccine strains recombine with wild strains to obtain new pathogenic strains. We performed genetic evolution analysis of XJ5 isolated and sequenced in our laboratory to trace its possible mutations and recombination. We found that XJ5 may be the result of natural mutation of a virus in a branch of mutant strains widely existing in China.

Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process, where product structures and uncertainty are taken into account. First, a stochastic programming model is developed to minimize the maximum completion time (makespan). Second, a Q-learning based hybrid meta-heuristic (Q-HMH) is specially devised. In each iteration, a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones, including genetic algorithm (GA), artificial bee colony (ABC), shuffled frog-leaping algorithm (SFLA), and simulated annealing (SA) methods. At last, simulation experiments are carried out by using sixteen instances with different scales, and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for comparisons. By analyzing the results with the average relative percentage deviation (RPD) metric, we find that Q-HMH outperforms its rivals by 9.79%−26.76%. The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events, causing surveillance and energy loss. This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters. Initially, the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes. Subsequently, it delves into communication and data processing mechanisms, specifically focusing on central data processing (CDP), communication routers (CRs), and phasor measurement units (PMUs), to re-establish an equipment recovery model based on these data transmission methodologies. Furthermore, it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution. The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system. The findings suggest that the proposed branch- and-bound algorithm significantly augments the observational capabilities of a power system with limited resources, thereby bolstering its stability and emergency response mechanisms.

Objective: Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation. Ki-67, an indicator of cellular proliferation, has been used for tumor grading and classification in breast cancer and neuroendocrine tumors. However, its prognostic significance in pancreatic ductal adenocarcinoma (PDAC) remains uncertain. Methods: Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled, and relevant prognostic factors were examined. Grade of malignancy (GOM), a novel index based on histopathological differentiation and Ki-67, is proposed, and its clinical significance was evaluated. Results: The optimal threshold for Ki-67 was determined to be 30%. Patients with a Ki-67 expression level > 30% rather than ≤ 30% had significantly shorter 5-year overall survival (OS) and recurrence-free survival (RFS). In multivariate analysis, both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS. The GOM was used to independently stratify OS and RFS into 3 tiers, regardless of TNM stage and other established prognostic factors. The tumor-node-metastasis-GOM stage was used to stratify survival into 5 distinct tiers, and surpassed the predictive performance of TNM stage for OS and RFS. Conclusions: Ki-67 is a valuable prognostic indicator for PDAC. Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.

Abstract Background Numerous studies have been conducted to investigate the relationship between ABO and Rhesus (Rh) blood groups and various health outcomes. However, a comprehensive evaluation of the robustness of these associations is still lacking. Methods We searched PubMed, Web of Science, Embase, Scopus, Cochrane, and several regional databases from their inception until Feb 16, 2024, with the aim of identifying systematic reviews with meta-analyses of observational studies exploring associations between ABO and Rh blood groups and diverse health outcomes. For each association, we calculated the summary effect sizes, corresponding 95% confidence intervals, 95% prediction interval, heterogeneity, small-study effect, and evaluation of excess significance bias. The evidence was evaluated on a grading scale that ranged from convincing (Class I) to weak (Class IV). We assessed the certainty of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation criteria (GRADE). We also evaluated the methodological quality of included studies using the A Measurement Tool to Assess Systematic Reviews (AMSTAR). AMSTAR contains 11 items, which were scored as high (8–11), moderate (4–7), and low (0–3) quality. We have gotten the registration for protocol on the PROSPERO database (CRD42023409547). Results The current umbrella review included 51 systematic reviews with meta-analysis articles with 270 associations. We re-calculated each association and found only one convincing evidence (Class I) for an association between blood group B and type 2 diabetes mellitus risk compared with the non-B blood group. It had a summary odds ratio of 1.28 (95% confidence interval: 1.17, 1.40), was supported by 6870 cases with small heterogeneity (I 2 = 13%) and 95% prediction intervals excluding the null value, and without hints of small-study effects (P for Egger’s test > 0.10, but the largest study effect was not more conservative than the summary effect size) or excess of significance (P

Abstract A novel double side friction stir Z shape lap-butt welding (DS-FSZW) process was proposed to achieve excellent mechanical properties of Al/Cu medium-thick dissimilar joints. The influence of welding parameters on weld microstructure and properties of DS-FSZW joint were systematically investigated. It indicated that defect-free medium-thick Al/Cu DS-FSZW joint could be achieved under an optimal welding parameter. DS-FSZW joint was prone to form void defects in the bottom of the second-pass weld. The recrystallization mechanisms at the top and middle of the weld nugget zone (WNZ) were continuous dynamic recrystallization (CDRX) and geometric dynamic recrystallization (GDRX). While the major recrystallization mechanism at the bottom of the WNZ was GDRX. DS-FSZW joint of the optimal welding condition with 850 r/min-400 mm/min was produced with a continuous thin and crack-free IMCs layer at the Al/Cu interface, and the maximum tensile strength of this joint is 160.57 MPa, which is equivalent to 65.54% of pure Cu base material. Moreover, the corrosion resistance of Al/Cu DS-FSZW joints also achieved its maximum value at the optimal welding parameter of 850 r/min-400 mm/min. It demonstrates that the DS-FSZW process can simultaneously produce medium-thick Al/Cu joints with excellent mechanical performance and corrosion resistance.

Background: Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. Methods: The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. Results: Throughout a median follow-up of 37.60 (interquartile: 24.77–50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend

Avian pathogenic Escherichia coli (APEC) can spread beyond the intestines and cause systemic infections, leading to various clinical manifestations, including airsacculitis, pericarditis, perihepatitis and colisepticemia. The mechanisms facilitating this extraintestinal infections are not fully understood. In this study, we investigate how the tolA gene affects APEC virulence by encoding a protein involved in maintaining outer membrane integrity. We constructed a tolA deletion mutant of APEC strain E058 and evaluated its growth and survival in various environments, including in vitro cultures and in vivo infection models in chickens. We found that the motility-defective ΔtolA mutant exhibits reduced biofilm formation ability and weakened resistance to the environmental stresses, suggesting an important role for TolA in APEC's survival. The lack of tolA gene affects the bacterial ability to resist the host's immune system, such as complement-mediated serum killing or phagocytosis, as shown by the serum killing and macrophage phagocytosis assays. Additionally, in vivo infection studies using chickens demonstrated that the ΔtolA mutant displayed attenuated virulence, evidenced by reduced mortality and lower tissue bacterial burden. Reverse transcription quantitative real-time PCR (RT-qPCR) analysis revealed that inactivation of tolA led to downregulation of virulence genes associated with serum resistance (traT) and flagellar biosynthesis (fliR). Taken together, our findings demonstrate the multifaceted role of TolA protein in promoting the survival, immune evasion, biofilm formation, and virulence of APEC E058. This suggests that targeting TolA could potentially offer new strategies for combating APEC infections.

The pathogenic nature of bacteria can be increased by cleaving antimicrobial peptides using omptins, to avoid or counter the host’s natural immune defenses. Plasmid-encoded OmpT (pOmpT or ArlC) in avian pathogenic Escherichia coli (APEC), like the chromosome-encoded OmpT (cOmpT), belongs to the omptin family and both exhibit highly similar sequences and structures. Through sequence alignment and physiological examinations, pOmpT has been identified as a virulence factor, distinct from cOmpT in terms of substrate specificity. When pOmpT is compared with cOmpT regarding their proteolytic activities and target substrates, Asp267 and Ser276 on loop 5 of cOmpT are found to be binding sites that facilitate substrate anchoring and enhance substrate cleavage (protamine or synthetic peptide) by the catalytic center. Conversely, the characteristics of residues at positions 267 and 276 on loop 5 of pOmpT inhibit protamine cleavage, yet allow the specific cleavage of the human antimicrobial peptide RNase 7, which plays a role in host defense. This finding suggests a relationship between these two binding sites and substrate specificity. Furthermore, the substrate-binding sites (residues 267 and 276, particularly residue 267) of cOmpT and pOmpT are determined to be critical in the virulence of APEC. In summary, residues 267 and 276 of pOmpT are crucial for the pathogenicity of APEC and offer new insights into the determinants of APEC virulence and the development of antimicrobial drugs.

Fuel cell vehicles have been paid more and more attention, while the low temperature cold start capability has become the main reason that hinders their large-scale commercialization, especially for the fuel cell bus. Generally, liquid heating (positive temperature coefficient thermistor (PTC) as the heat source) and fuel cell self-starting heating are the common cold start methods. However, these methods can bring about low start speed and high energy consumption. Therefore, a new cold start method combined with liquid heating and fuel cell self-starting is proposed to solve the problems. Besides, phase change material (PCM) is introduced to reduce energy consumption further. The PCM can absorb the waste heat of the fuel cell stack. Then the heat can be used for stack cold start by circulating liquid. In this study, a fuel cell bus cold start system simulating model is built. Based on this model, the fuel cell temperature and energy consumption during the cold start are analyzed. The results show that the method combined with liquid heating and fuel cell self-starting is superior to the liquid heating method. The cold start time and PTC consumption of the PTC-PCM-self-starting heating mode are 19.0 % and 19.2 % less than that of PTC-PCM heating mode. As for the combined heating method, dropping the self-starting temperature can not only increase the cold start speed but also reduce the proportion of electric heating. For every 1 °C decrease, the start-up time is shortened by 1 % on average, and the waste heat utilization rate is increased by 0.5 %. Although increasing the self-starting current can increase energy consumption, it will save more cold start time and reduce the proportion of electric heating. For every 1 A increase, the start-up time is shortened by 0.3 % on average, and the waste heat utilization rate is increased by 0.1 %. The PTC-PCM-self-starting heating method provides a way for fuel cell stack to start quickly and energy-efficiently in low temperature environment.

Abstract In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack. This may be unacceptable in real applications since Machine Learning as a Service Platform (MLaaS) usually only returns the final result (i.e., hard-label) to the client and a system equipped with certain defense mechanisms could easily detect malicious queries. By contrast, a feasible way is a hard-label attack that simulates an attacked action being permitted to conduct a limited number of queries. To implement this idea, in this paper, we bypass the dependency on the to-be-attacked model and benefit from the characteristics of the distributions of adversarial examples to reformulate the attack problem in a distribution transform manner and propose a distribution transform-based attack (DTA). DTA builds a statistical mapping from the benign example to its adversarial counterparts by tackling the conditional likelihood under the hard-label black-box settings. In this way, it is no longer necessary to query the target model frequently. A well-trained DTA model can directly and efficiently generate a batch of adversarial examples for a certain input, which can be used to attack un-seen models based on the assumed transferability. Furthermore, we surprisingly find that the well-trained DTA model is not sensitive to the semantic spaces of the training dataset, meaning that the model yields acceptable attack performance on other datasets. Extensive experiments validate the effectiveness of the proposed idea and the superiority of DTA over the state-of-the-art.

Abstract Tumor cells must rewire nucleotide synthesis to satisfy the demands of unbridled proliferation. Meanwhile, they exhibit augmented reactive oxygen species (ROS) production which paradoxically damages DNA and free deoxy-ribonucleoside triphosphates (dNTPs). How these metabolic processes are integrated to fuel tumorigenesis remains to be investigated. MYC family oncoproteins coordinate nucleotide synthesis and ROS generation to drive the development of numerous cancers. We herein perform a Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based functional screen targeting metabolic genes and identified nudix hydrolase 1 (NUDT1) as a MYC-driven dependency. Mechanistically, MYC orchestrates the balance of two metabolic pathways that act in parallel, the NADPH oxidase 4 (NOX4)-ROS pathway and the Polo like kinase 1 (PLK1)-NUDT1 nucleotide-sanitizing pathway. We describe LC-1-40 as a potent, on-target degrader that depletes NUDT1 in vivo. Administration of LC-1-40 elicits excessive nucleotide oxidation, cytotoxicity and therapeutic responses in patient-derived xenografts. Thus, pharmacological targeting of NUDT1 represents an actionable MYC-driven metabolic liability.

Abstract Mechanical antennas have garnered considerable attention due to their ability to address the challenges posed by the significant size and high energy consumption associated with traditional electric antennas when operating at low frequencies. Here, a compact and structurally stable mechanical antenna design is presented. The proposed antenna is constructed using cylindrical piezoelectric ceramics, which have dimensions smaller than 1/1000 of the wavelength. The scrutiny of the influence exerted by the antenna feed area and material thickness on the radiation performance was undertaken, followed by an exhaustive discourse on these effects. Experimental measurements demonstrate the practical functionalities of signal coding, transmission, and reception in the low‐frequency communication system. Notably, at a frequency of 288 kHz, a single proposed antenna achieves an effective information transmission distance of 60 m using binary information coding. This remarkable outcome underscores the potential of this design in facilitating the development of portable and cost‐effective wireless communication equipment for low‐frequency applications.

Abstract Introduction Rheumatoid arthritis (RA) is an incurable autoimmune disease. The role of interleukin-38 (IL-38), an anti-inflammatory cytokine, in RA is not fully understood, and its clinical relevance in RA remains unclear. This study aims to investigate the correlation of IL-38 with disease activity and the clinical manifestation of RA. Methods In this cross-sectional study, patients with treatment-naïve RA (n = 63) and healthy controls (HC) (n = 60) were consecutively enrolled over a 15-month period. Patients with RA were categorized into three subgroups—low disease activity (LDA), moderate disease activity (MDA) and high disease activity (HDA)—using the Disease Activity Score in 28 joints based on C-reactive protein (DAS28-CRP). Circulating levels of IL-38, tumour necrosis factor (TNF), IL-6, IL-17, IL-1β, and 25(OH)D were assessed using enzyme-linked immunosorbent assay (ELISA). Clinical data, including duration, tender joints count (TJC), swollen joints count (SJC), patient global assessment (PGA), evaluator global assessment (EGA), bone mineral density (BMD), clinical disease activity index (CDAI), simplified disease activity index (SDAI), DAS28-CRP, joint musculoskeletal ultrasound (MSUS), and serological indicators were recorded. We determined the correlation between IL-38 and disease activity, as well as clinical manifestation in RA. Results At the macroscopic level, musculoskeletal ultrasonography of joints in different stages of disease activity in RA suggests that, as the disease progresses, arthritis in the hand becomes more severe, accompanied by synovial thickening and pronounced blood flow signals in the joint area. The expression of IL-38, TNF, IL-6, IL-17 and IL-1β significantly increased in patients with RA compared to HC. Noteworthy differences were observed in the blood flow signal score, synovial signal score, IL-38, TNF, IL-6, IL-17 and IL-1β among the three subgroups (LDA, MDA and HDA). As disease activity increased in patients with RA, the blood flow signal score, synovial signal score and expression of TNF, IL-6, IL-17 and IL-1β exhibited a gradual increase, while the expression of IL-38 showed the opposite pattern. Inverse correlations were identified between IL-38 and pro-inflammatory cytokines (IL-6, IL-17), as well as key clinical parameters, including disease duration, SJC, TJC and DAS28-CRP score. Conclusion IL-38, intricately linked to the pathogenesis of RA, emerges as a promising therapeutic target for the management of this debilitating disease.

Recycled aggregate concrete (RAC) has multiple interface transition zones (ITZs) due to its complex composition, providing convenient ion transfer channels. Therefore, it is significant to explore the changes of the internal pore structure in RAC under ion erosion conditions for quantifying and predicting ion transfer mechanisms. This paper innovatively utilizes the seepage effect for investigating the evolution of pore structures in RAC under sulfate attack. We conduct a systematic experimental study on the transport of sulfate ions in RAC with different fly ash (FA) substitution rates under dry-wet cycles. Combining backscattered electron imaging (BSE), permeation and fractal characteristics, this paper deeply explore the relationship between pore structure feature, sulfate percolation mechanism and the macroscopic properties of RAC incorporated with different amount of FA.

Vincristine (VCR), as a cytotoxic drug, is used clinically to treat acute lymphatic leukemia and breast cancer, and commonly used clinically as vincristine sulfate (VCRS). However, its clinical use is limited by unpredictable pharmacologic characteristics, a narrow therapeutic index, and neurotoxicity. The pH gradient method was used for active drug loading of VCRS, and the process route mainly includes the preparation of blank liposomes and drug-loaded liposomes. VCRS liposomes had suitable particle size, high encapsulation efficiency and good stability. The loading and release kinetics of VCRS liposomes were explored. By calculating the changes of encapsulation efficiency with time at different temperatures, it was confirmed that the drug-loading process of liposomes exhibited a first-order kinetic feature, and the activation energy required for the reaction was determined as 20.6 kcal/mol. The release behavior at different pH was also investigated, and it was demonstrated that the release behavior conformed to the first-order model, suggesting that the release mechanism of VCRS was simple transmembrane diffusion. VCRS liposomes also enhanced in vitro and in vivo antitumor activity. Thus, VCRS liposomes showed great potential for VCRS delivery, and the loading and release kinetics were well researched to provide a reference for investigating active drug loading liposomes.

Summary: Background: Despite numerous studies having evaluated the associations between human papillomavirus (HPV) infection and risk of specific cancers other than anogenital tract and oropharyngeal, the findings are inconsistent and the quality of evidence has not been systematically quantified. We aimed to summarise the existing evidence as well as to evaluate the strength and credibility of these associations. Methods: We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, EMBASE, and Web of Science were searched from inception to March 2024. Studies with systematic reviews and meta-analyses that examined associations between HPV or HPV-associated genotypes infection and specific cancers were eligible for this review. The quality of the methodology was evaluated using A Measurement Tool to Assess systematic Reviews (AMSTAR). The credibility of the evidence was assessed using GRADE. The protocol was preregistered with PROSPERO (CRD42023439070). Findings: The umbrella review identified 31 eligible studies reporting 87 associations with meta-analytic estimates, including 1191 individual studies with 336,195 participants. Of those, 29 (93.5%) studies were rated as over moderate quality by AMSTAR. Only one association indicating HPV-18 infection associated with an increased risk of breast cancer (odds ratio [OR] = 3.48, 95% confidence interval [CI] = 2.24–5.41) was graded as convincing evidence. There were five unique outcomes identified as highly suggestive evidence, including HPV infection increased the risk of oral squamous cell carcinoma (OR = 7.03, 95% CI = 3.87–12.76), oesophageal cancer (OR = 3.32, 95% CI = 2.54–4.34), oesophageal squamous cell carcinoma (OR = 2.69, 95% CI = 2.05–3.54), lung cancer (OR = 3.60, 95% CI = 2.59–5.01), and breast cancer (OR = 6.26, 95% CI = 4.35–9.00). According to GRADE, one association was classified as high, indicating that compared with the controls in normal tissues, HPV infection was associated with an increased risk of breast cancer. Interpretation: The umbrella review synthesised up-to-date observational evidence on HPV infection with the risk of breast cancer, oral squamous cell carcinoma, oesophageal cancer, oesophageal squamous cell carcinoma, and lung cancer. Further larger prospective cohort studies are needed to verify the associations, providing public health recommendations for prevention of disease. Funding: National Key Research and Development Program of China, Natural Science Foundation of China, Outstanding Scientific Fund of Shengjing Hospital of China Medical University, and 345 Talent Project of Shengjing Hospital of China Medical University.

Building change detection (CD) aims to detect changes in buildings from bi-temporal pairwise images obtained at different times. Typically, a deep learning-based building CD algorithm requires bi-temporal samples with significant building changes for training. However, obtaining such bi-temporal samples is challenging because building changes have a low probability of occurrence. Fortunately, it is relatively simple to obtain single-temporal samples that include a substantial number of buildings. By using these single-temporal building samples, pseudo bi-temporal building change samples can be generated, which can effectively address the problem of limited available bi-temporal building change samples. In view of that, this study proposes a metric guided single-temporal supervised learning framework that uses single-temporal building samples for building CD. In the proposed framework, patch-pairing single-temporal supervised learning (PPSL) adopts a patch-pairing method to construct pseudo bi-temporal building change samples, while equipping the network to effectively suppresses the negative impact of geometric offset and radiation difference in real samples. To further suppress the impact of radiation difference and enhance the effectiveness of our framework, a metric-guided spatial attention module (MGSAM) is designed to minimize the intra-class feature differences between temporal samples and augment the spatial context modeling ability. The proposed method is verified by experiments on different datasets, and the results demonstrate that the proposed method can outperform the existing methods and achieve superior performance.

Abstract Platinum-based chemotherapy remains one of the major choices for treatment of ovarian cancer (OC). However, primary or acquired drug resistance severely impairs their efficiency, thereby causing chemotherapy failure and poor prognosis. SH3 domain containing ring finger 2 (SH3RF2) has been linked to the development of cancer. Here we find higher levels of SH3RF2 in the tumor tissues from cisplatin-resistant OC patients when compared to those from cisplatin-sensitive patients. Similarly, cisplatin-resistant OC cells also express higher levels of SH3RF2 than normal OC cells. Through in vitro and in vivo loss-of-function experiments, SH3RF2 is identified as a driver of cisplatin resistance, as evidenced by increases in cisplatin-induced cell apoptosis and DNA damage and decreases in cell proliferation induced by SH3RF2 depletion. Mechanistically, SH3RF2 can directly bind to the RNA-binding protein mRNA processing factor (RBPMS). RBPMS has been reported as an inhibitor of cisplatin resistance in OC. As a E3 ligase, SH3RF2 promotes the K48-linked ubiquitination of RBPMS to increase its proteasomal degradation and activator protein 1 (AP-1) transactivation. Impairments in RBPMS function reverse the inhibitory effect of SH3RF2 depletion on cisplatin resistance. Collectively, the SH3RF2-RBPMS-AP-1 axis is an important regulator in cisplatin resistance and inhibition of SH3RF2 may be a potential target in preventing cisplatin resistance.

To accurately characterize the dynamic deformation mechanical properties of hot forming steels 6Mn6 and 22MnB5 under collision conditions, quasi-static tensile tests (0.001s−1) and Hopkinson compression bar tests (∼2000s−1, ∼3000s−1, ∼4000s−1) were conducted to analyze the influence of strain rate on the material mechanical properties. Based on the experimental results, four constitutive models including Johnson-Cook (JC), modified JC (m-JC), Cowper-Symond (CS), and Khan-Huang (KH) models were established for both 6Mn6 and 22MnB5. Additionally, a modified model based on the Swift-Voce strain hardening model coupled with the Cowper-Symond model was proposed. A numerical simulation model for compression bar tests was developed using JC and m-JC models. The experimental results indicate that both hot forming steels exhibit strain rate sensitivity, with 6Mn6 performed a more pronounced effect than 22MnB5. The average absolute error (AARE) and correlation coefficient (R) of the m-JC and CS models were 0.99 and 0.29 %, 0.95 and 0.4 %, respectively. The dynamic deformation behavior of 6Mn6 and 22MnB5 at high strain rates was accurately predicted. Comparing with the JC model, the utilization of the m-JC user subroutine has resulted in a significant improvement in simulation accuracy by 58 % and 84 % for these two materials, which laying a solid foundation for high-precision vehicle collision simulation.

Abstract Reducing inter-spin distance can enhance magnetic interactions and allow for the realization of outstanding magnetic properties. However, achieving reduced distances is technically challenging. Here, we construct a 3d-4f metal cluster (Dy2VN) inside a C80 cage, affording a heretofore unseen metallofullerene containing both paramagnetic 3d and 4f metal ions. The significantly suppressed 3d-4f (Dy-V) distances, due to the unique cage confinement effect, were observed by crystallographic and theoretical analysis of Dy2VN@I h (7)-C80. These reduced distances result in an enhanced magnetic coupling (J total, Dy-V = 53.30 cm−1; J total, Dy-Dy = −6.25 cm−1), leading to a high magnetic blocking temperature compared to reported 3d-4f single-molecule magnets and strong coercive field of 2.73 Tesla. Our work presents a new class of single-molecule magnets with both paramagnetic 3d and 4f metals confined in a fullerene cage, offering superior and tunable magnetic properties due to the unique cage confinement effect and the diverse composition of the entrapped magnetic core.

Abstract Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

Recycled aggregate concrete (RAC) is one of the most important ways to achieve sustainable development for concrete industry. However, the research on durability, especially on sulfate transport and erosion mechanism, of RAC needs deep investigation. Pore structure evolution is a vital parameter for sulfate transport, which is difficult to be traced. To investigate the dynamic changes of pore structure in metakaolin blended RAC under sulfate erosion, percolation theory is addressed in this study. Firstly, dry and wet cycle was applied to accelerate the sulfate transport in metakaolin (MK) blended RAC systems. Then the compressive strength of the samples after sulfate attack was measured to evaluate the sulfate erosion degree. Furthermore, backscattered electron imaging (BSE) was used to acquire the percolation parameters, such as wet site ratio, percolation probability and so forth. Finally, sulfate content and compressive strength of the sample were related to the percolation probability. Results present that MK exhibits excellent resistance to sulfate erosion and can be used to enhance the performance of RAC. There is a certain correlation between the degree of sulfate erosion, compressive strength, and percolation parameters. The influence of the number of dry–wet cycles and MK content on sulfate ion transport can be demonstrated using percolation theory, which can be employed for predicting sulfate transport and revealing erosion mechanisms. This enables a clear understanding of the ion transport mechanisms within concrete and holds significant importance on the investigation of durability issues of RAC.

Since 2008, annual outbreaks of green tides in the Yellow Sea have had severe impacts on tourism, fisheries, water sports, and marine ecology, necessitating effective interception and removal measures. Satellite remote sensing has emerged as a promising tool for monitoring large-scale green tides due to its wide coverage and instantaneous imaging capabilities. Additionally, drift prediction techniques can forecast the location of future green tides based on remote sensing monitoring information. This monitoring and prediction information is crucial for developing an effective plan to intercept and remove green tides. One key aspect of this monitoring information is the green tide distribution envelope, which can be generated automatically and quickly using buffer analysis methods. However, this method produces a large number of envelope vertices, resulting in significant computational burden during prediction calculations. To address this issue, this paper proposes a simplification method based on azimuth difference and side length (SM-ADSL). Compared to the isometric and Douglas–Peucker methods with the same simplification rate, SM-ADSL exhibits better performance in preserving shape and area. The simplified distribution envelope can shorten prediction times and enhance the efficiency of emergency decision-making for green tide disasters.

Background: Accumulating evidence indicates that PSAT1 not only reprogrammed metabolic function but also exhibits “moonlighting” functions in promoting tumor malignancy. However, the underlying molecular mechanisms of PSAT1 promoting ER-negative breast cancer cell migration need further investigation. Methods: Briefly, the PSAT1 and ITGA2 expression in cells and tissues was detected using qRT-PCR, immunofluorescence staining and western blot assay. The effect of PSAT1 and ITGA2 was verified both in vitro and in vivo. RNA-seq analysis explored a series of differently expressed genes. The regulation between SP1 and ITGA2 was investigated by ChIP analysis. Results: We reported PSAT1 was highly expressed in ER-breast cancer tissues and tumor cells and positively correlated with metastasis. Moreover, RNA-seq analysis explored a series of differently expressed genes, including ITGA2, in PSAT1 overexpressed cells. Mechanistically, PSAT1 facilitated breast cancer metastasis via the p-AKT/SP1/ITGA2 axis. We further elucidated that PSAT1 promoted the entry of SP1 into the nucleus through the upregulation of p-AKT and confirmed ITGA2 is a target of SP1. In addition, enhanced cell migration was remarkably reversed by ITGA2 depletion or p-AKT inhibitor treatment. Conclusion: This study clarified the mechanism of PSAT1 in promoting ER-negative breast cancer metastasis, which may provide mechanistic clues for attenuating breast cancer metastasis.

Change Detection (CD) is a vital monitoring method in Earth observation, especially pertinent for land-use analysis, city management, and disaster damage assessment. However, in the era of constellation interconnection and air-sky collaboration, the changes in the Regions Of Interest (ROI) cause many false detections due to geometric perspective rotation and temporal style difference. In response to these challenges, we introduce CDNeXt, this framework elucidates a robust and efficient method for combining Siamese networks based on the pre-trained backbone with the innovative Temporospatial Interactive Attention Module (TIAM) for remote sensing imagery. The CDNeXt can be categorized into four primary components: Encoder, Interactor, Decoder, and Detector. Notably, the Interactor, powered by TIAM, queries and rebuilds spatial perspective dependencies and temporal style correlations from binary temporal features extracted by the Encoder to enlarge the difference of ROI change. Culminating the process, the Detector integrates the hierarchical features generated by the Decoder, subsequently producing a binary change mask. We have achieved new State-Of-The-Art (SOTA) performance in change detection, with our method surpassing existing techniques on four benchmark datasets: an F1 score of 82.63% on SYSU-CD, 87.14% on LEVIR-CD+, 66.71% on S2Looking, and 71.11% BANDON. To further validate the effectiveness of the TIAM, we compared it to other attention modules in both interactive and non-interactive modes. Our code is available on GitHub: https://github.com/wjj282439449/CDNeXt.

Summary: Background: Benefits of Intermittent fasting (IF) on health-related outcomes have been found in a range of randomised controlled trials (RCTs). Our umbrella review aimed to systematically analyze and synthesize the available causal evidence on IF and its impact on specific health-related outcomes while evaluating its evidence quality. Methods: We comprehensively searched the PubMed, Embase, Web of Science, and Cochrane databases (from inception up to 8 January 2024) to identify related systematic reviews and meta-analyses of RCTs investigating the association between IF and human health outcomes. We recalculated the effect sizes for each meta-analysis as mean difference (MD) or standardized mean difference (SMD) with corresponding 95% confidence intervals (CIs). Subgroup analyses were performed for populations based on three specific status: diabetes, overweight or obesity, and metabolic syndrome. The quality of systematic reviews was evaluated using A Measurement Tool to Assess Systematic Reviews (AMSTAR), and the certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. This study is registered with PROSPERO (CRD42023382004). Findings: A total of 351 associations from 23 meta-analyses with 34 health outcomes were included in the study. A wide range of outcomes were investigated, including anthropometric measures (n = 155), lipid profiles (n = 83), glycemic profiles (n = 57), circulatory system index (n = 41), appetite (n = 9), and others (n = 6). Twenty-one (91%) meta-analyses with 346 associations were rated as high confidence according to the AMSTAR criteria. The summary effects estimates were significant at p