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Abstract Background Nanosecond pulsed electric fields (nsPEF)‐based electroporation is a new therapy modality potentially synergized with radiation therapy to improve treatment outcomes. To verify its treatment accuracy intraoperatively, electroacoustic tomography (EAT) has been developed to monitor in‐vivo electric energy deposition by detecting ultrasound signals generated by nsPEFs in real‐time. However, utility of EAT is limited by image distortions due to the limited‐angle view of ultrasound transducers. Methods This study proposed a supervised learning‐based workflow to address the ill‐conditioning in EAT reconstruction. Electroacoustic signals were detected by a linear array and initially reconstructed into EAT images, which were then fed into a deep learning model for distortion correction. In this study, 56 distinct electroacoustic data sets from nsPEFs of different intensities and geometries were collected experimentally, avoiding simulation‐to‐real‐world variations. Forty‐six data were used for model training and 10 for testing. The model was trained using supervised learning, enabled by a custom rotating platform to acquire paired full‐view and single‐view signals for the same electric field. Results The proposed method considerably improved the image quality of linear array‐based EAT, generating pressure maps with accurate and clear structures. Quantitatively, the enhanced single‐view images achieved a low‐intensity error (RMSE: 0.018), high signal‐to‐noise ratio (PSNR: 35.15), and high structural similarity (SSIM: 0.942) compared to the reference full‐view images. Conclusions This study represented a pioneering stride in achieving high‐quality EAT using a single linear array in an experimental environment, which improves EAT's utility in real‐time monitoring for nsPEF‐based electroporation therapy.

Abstract Background Hepatocellular carcinoma (HCC) is a common gastrointestinal malignancy with a high incidence and poor prognosis. The subunits of the integrator complex (INTS1-14) play a crucial role in regulating genes dependent on RNA Polymerase II, which may be associated with cancer. However, the role of INTSs in HCC remains unclear. This study aims to comprehensively analyze the clinical value and potential role of INTS family genes in HCC through systematic bioinformatics analysis. Methods We employed various public databases, including UALCAN, HPA, Kaplan–Meier Plotter, GEPIA2, TNMplot, STRING, TIMER, and TISIDB, to investigate the expression levels, clinicopathological correlations, diagnostic and prognostic value, genetic alterations, co-expression network, molecular targets, and immune infiltration of INTSs in HCC. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to investigate the biological functions of genes associated with INTSs. Furthermore, Western blot, real-time fluorescence quantitative reverse transcription polymerase chain reaction (RT-qPCR), and immunohistochemistry techniques were employed to assess the expression of relevant proteins and genes. The proliferation of HCC cells was evaluated using the CCK8 assay. Results We found that in HCC, there was a significant upregulation of INTSs at the transcriptional level, particularly INTS1, INTS4, INTS7, and INTS8. Additionally, the protein levels of INTS1 and INTS8 were notably elevated. The overexpression of these INTSs was strongly correlated with tumor stages in HCC patients. INTS1, INTS4, INTS7, and INTS8 exhibited significant diagnostic and prognostic value in HCC. Moreover, their expression was associated with immune infiltrations and activated status, including B cells, CD8 + T cells, CD4 + T cells, NK cells, macrophages, and dendritic cells. Functional predictions indicated that INTS1, INTS4, INTS7, and INTS8 were involved in various cancer-related signaling pathways, such as TRAIL, IFN-gamma, mTOR, CDC42, Apoptosis, and the p53 pathway. Furthermore, we observed a significant upregulation of INTS1, INTS4, INTS7, and INTS8 expression in HCC cell lines compared to normal liver cell lines. The level of INTS1 protein was higher in cancerous tissues compared to adjacent non-cancerous tissues (n = 16), and the suppression of INTS1 resulted in a significant decrease in the proliferation of Huh7 cells. Conclusion These findings indicate the potential of INTS family genes as diagnostic biomarkers and therapeutic targets in HCC. Further research is needed to understand the underlying mechanisms and explore clinical applications.

Post-stroke depression (POSD) is a common difficulty and most predominant emotional syndrome after stroke often consequences in poor outcomes. In the present investigation, we have designed and studied the neurologically active celastrol/minocycline encapsulated with macrophages-derived exosomes functionalized PLGA nanoformulations (CMC-EXPL) to achieve enhanced anti-inflammatory behaviour and anti-depressant like activity in a Rat model of POSD. The animal model of POSD was established through stimulating process with chronic unpredictable mild stress (CUM) stimulations after procedure of middle cerebral artery occlusion (MCAO). Neuronal functions and Anti-inflammation behaviours were observed by histopathological (H&E) examination and Elisa analyses, respectively. The anti-depressive activity of the nanoformulations treated Rat models were evaluated by open-field and sucrose preference test methods. Microglial polarization was evaluated via flow-cytometry and qRT-PCR observations. The observed results exhibited that prepared nanoformulations reduced the POSD-stimulated depressive-like activities in rat models as well alleviated the neuronal damages and inflammatory responses in the cerebral hippocampus. Importantly, prepared CMC-EXPL nanoformulation effectively prevented the M1 pro-inflammatory polarization and indorsed M2 anti-inflammatory polarization, which indicates iNOS and CD86 levels significantly decreased and upsurged Arg-1 and CD206 levels. CMC-EXPL nanoformulation suggestively augmented anti-depressive activities and functional capability and also alleviated brain inflammation in POSD rats, demonstrating its therapeutic potential for POSD therapy.

By engaging in redox processes, ferroptosis plays a crucial role in sepsis-induced acute lung injury (ALI). Although iron stimulates calcium signaling through the stimulation of redox-sensitive calcium pathways, the function of calcium signals in the physiological process of ferroptosis in septic ALI remains unidentified. Iron homeostasis disequilibrium in ferroptosis is frequently accompanied by aberrant calcium signaling. Intracellular calcium overflow can be a symptom of dysregulation of the cellular redox state, which is characterized by iron overload during the early phase of ferroptosis. This can lead to disruptions in calcium homeostasis and calcium signaling. The mechanisms controlling iron homeostasis and ferroptosis are reviewed here, along with their significance in sepsis-induced acute lung injury, and the potential role of calcium signaling in these processes is clarified. We propose that the development of septic acute lung injury is a combined process involving the bidirectional interaction between iron homeostasis and calcium signaling. Our goal is to raise awareness about the pathophysiology of sepsis-induced acute lung injury and investigate the relationship between these mechanisms and ferroptosis. We also aimed to develop calcium-antagonistic therapies that target ferroptosis in septic ALI and improve the quality of survival for patients suffering from acute lung injury.

Abstract In this work, we studied four types of cosmological models with different mechanisms driving the accelerated expansion of the universe, include Braneworld models, Chaplygin Gas models, Emergent Dark Energy models, and cosmological torsion models. Considering that the dynamics of these models at low redshifts are very similar and difficult to distinguish, we used the latest and largest UV and X-ray measurements of quasars (QSOs) observations covering the range of redshift $$0.009

Highlights Janus quasi-solid electrolyte membranes with asymmetric porous structure were constructed, showing a high σLi+ of 1.5 × 10-4 S cm-1 and a high t + of 0.71. The solvation structures and ion transport dynamics in nanopores have been deciphered, manifesting a concentrated electrolyte-like structure and regulated transport behaviors. Quasi-solid NCM 622||Li cells have been demonstrated to stably cycle for 200 cycles at 1 C, and pouch cell has shown high tolerance for abuse.

Over the past decade, advancements in high-throughput sequencing technologies have led to a qualitative leap in our understanding of the role of the microbiota in human diseases, particularly in oncology. Despite the low biomass of the intratumoral microbiota, it remains a crucial component of the tumor immune microenvironment, displaying significant heterogeneity across different tumor tissues and individual patients. Although immunotherapy has emerged a major strategy for treating tumors, patient responses to these treatments vary widely. Increasing evidence suggests that interactions between the intratumoral microbiota and the immune system can modulate host tumor immune responses, thereby influencing the effectiveness of immunotherapy. Therefore, it is critical to gain a deep understanding of how the intratumoral microbiota shapes and regulates the tumor immune microenvironment. Here, we summarize the latest advancements on the role of the intratumoral microbiota in cancer immunity, exploring the potential mechanisms through which immune functions are influenced by intratumoral microbiota within and outside the gut barrier. We also discuss the impact of the intratumoral microbiota on the response to cancer immunotherapy and its clinical applications, highlighting future research directions and challenges in this field. We anticipate that the valuable insights into the interactions between cancer immunity and the intratumoral microbiota provided in this review will foster the development of microbiota-based tumor therapies.

Abstract Ulcerative colitis (UC) is a complicated and recurrent intestinal disease. Currently available drugs for UC treatment are scarce, therefore, novel therapeutic drugs for the UC are urgently to be developed. Gingerenone A (GA) is a phenolic compound known for its anti‐inflammatory effect, but its effect on UC remains unknown. Here, it is shown that GA protects mice against UC, which is closely associated with inhibiting intestinal mucosal inflammation and enhancing intestinal barrier integrity in vivo and in vitro. Of note, RNA sequencing analysis demonstrates an evident correlation with IL‐17 signaling pathway after GA treatment, and this effect is further corroborated by Western blot. Mechanistically, GA directly interacts with IL‐17RA protein through pull‐down, surface plasmon resonance analysis and molecular dynamics simulation. Importantly, lentivirus‐mediated IL‐17RA/Act1 knock‐down or GA co‐treatment with brodalumab/ixekizumab significantly impairs the protective effects of GA against DSS‐induced inflammation and barrier dysfunction, suggesting a critical role of IL‐17RA signaling for GA‐mediated protection against UC. Overall, these results indicate that GA is an effective agent against UC mainly through the direct binding of IL‐17RA to inhibit inflammatory signaling activation.

Establishing ecological management zones based on the supply-demand relationship of ecosystem services (ESs) is essential for fostering sustainable development within social-ecological systems and improving human well-being. In this study, the spatial pattern between supply and demand in five ESs (grain production (GP), carbon sequestration (CS), soil conservation (SC), water conservation (WC), and habitat quality (HQ)) is analyzed using the ESs supply-demand ratio (ESDR) method, the spatial autocorrelation method, and the coupled coordination degree model. Zoning is performed according to the differences in their spatial combinations, and differential zoning management policies are proposed. The following results were obtained: (1) In terms of the ESDR, except for a slight increase in GP surplus from 2010 to 2020, there is a decline in the surplus of the other four ESs. (2) CS, WC, and HQ are dominated by cluster types LH and HL. GP and SC are dominated by cluster types HH and LL. The average value of the coupling coordination degree (CCD) of comprehensive ESs supply and demand show five types: moderate disharmony, slight disharmony, near disharmony, basic coordination, and slight coordination. (3) Based on the multiple spatial heterogeneity of ESs supply and demand, differentiated ecological management strategies are proposed at the grid scale. Overall, this study discover the spatial pattern of mismatch between the supply and demand of ecosystem services (ESs) in mountainous urban areas. This contribution enhances the discourse surrounding sustainable development theory and advances research on the coupling of social-ecological systems. Furthermore, it offers valuable insights for the formulation of sustainable ecological management policies tailored to mountainous urban settings.

Fusobacterium vincentii brain abscesses are relatively rare. Here, we report our treatment of an anaerobic brain abscess caused by a mixed infection of Parvimonas micra, Streptococcus constellatus, Fusobacterium vincentii, and Bacteroides heparinolyticus diagnosed by metagenomic next-generation sequencing (mNGS). This is the first reported case of Fusobacterium vincentii in a brain abscess. This case highlights the possibility that oral anaerobic microbes can cause a brain abscess and demonstrates that mNGS has the potential to be deployed to provide rapid infection diagnosis and rationalize antimicrobial therapy for brain abscesses.

In this letter, we propose a novel cosmological model-independent method to determine cosmic curvature, combining the recent measurements of transverse and line-of-sight directions in the baryon acoustic oscillations (BAO) with cosmic chronometers (CC) datasets. Considering that the CC dataset is discrete and includes only 32 H(z) measurements, we apply Gaussian process (GP) regression to fit the CC dataset and reconstruct them. Our methodology, which does not need the calibration or selection of any cosmological model, provide multiple measurements of spatial curvature (ΩK) at different redshifts (depending on the redshift coverage of BAO dataset). For combination of all BAO data, we find that the constraint result on cosmic curvature is ΩK=−0.096−0.195+0.190 with 1σ observational uncertainty. Although the measured ΩK is in good agreement with zero cosmic curvature within 1σ confidence level, our result revels the fact of a closed universe. More importantly, our results show that the obtained ΩK measurements are almost unaffected by different priors of the Hubble constant. This could help solve the issue of the Hubble tension that may be caused by inconsistencies in the spatial curvature between the early and late universes.

Battery recycling is viewed in China as an important means of achieving primary sustainability goals and greater economic and environmental development. With the notice of high battery recycling intentions through relevant investigations, this study examine the influencing factors of these recycling behaviors of e-bikes citizens by incorporating the place identity and environmental concern into the Extended Normative Activation Model (NAM), which fill the research gap on how place identity and environmental concern affect the batteries recycling behavior. This study proposes that the consequence awareness, personal norms, and attitudes have mediating effect on place identity to the recycling behavior, and the environmental concern has moderating effect on consequence awareness, personal norms, and attitudes to the recycling behavior, respectively. Based on 1068 valid surveys, hypotheses were examined using partial least square structural equation modeling (PLS-SEM). The results show that personal norms and awareness of consequences positively impact e-bike users' intentions to recycle waste batteries, and environmental concerns have no moderating effect on attitude, recycling intention, personal norms, and recycling intention. Theoretical and practical implications are discussed at last.

Infrared small target detection (IRSTD) aims to segment small targets from infrared clutter background. Existing methods mainly focus on discriminative approaches, i.e., a pixel-level front-background binary segmentation. Since infrared small targets are small and low signal-to-clutter ratio, empirical risk has few disturbances when a certain false alarm and missed detection exist, which seriously affect the further improvement of such methods. Motivated by the dense prediction generative methods, in this article, we compensate pixel-level discriminant with mask posterior distribution modeling. Specifically, we propose a diffusion model framework for IRSTD. This generative framework maximizes the posterior distribution of the small target mask to surmount the performance bottleneck associated with minimizing discriminative empirical risk. This transition from the discriminative paradigm to generative one enables us to bypass the target-level insensitivity. Furthermore, we design a low-frequency isolation in wavelet domain to suppress the interference of intrinsic infrared noise on the diffusion noise estimation. The low-frequency component of the infrared image in the wavelet domain is processed by a neural network, and the high-frequency component is utilized to restore the targets information, to estimate the residuals of the enhanced features. Experiments show that the proposed method achieves competitive performance gains over state-of-the-art methods on NUAA-SIRST, NUDT-SIRST, and IRSTD-1 k datasets.

Introduction Studies on economic evaluations of the 13-valent pneumococcal conjugate vaccine (PCV13) have been increasing over the last decade. No systematic reviews have synthesized the evidence of economic evaluations of the PCV13. Areas covered We systematically searched the literature which published on peer-reviewed journals from January 2010 to June 2022. The literature search was conducted in the following electronic databases: PubMed, Web of Science, Embase, the Cochrane Library, CNKI, Wanfang database, VIP database. We identified 1827 records from the database search. After excluding 511 duplicates, 1314 records were screened, of which 156 records were retained for the full-text reviews. A total of 44 studies were included in the review. Among the included studies, 33 studies were economic evaluations of PCV13 among children, and 11 studies were conducted among adults. The literature search initiated in April, 2022, and updated in June 2022. Expert opinion Vaccination with PCV13 was found to significantly reduce the mortality and morbidity of pneumococcal diseases and was cost-effective compared to no vaccine or several other pneumococcal vaccines (e.g. PCV10, PPV23). Future research is advised to expand economic evaluations of PCV13 combined with dynamic model to enhance methodologic rigor and prediction accuracy.

ABSTRACTMosquitoes carry a large number of known and unknown viruses, some of which could cause serious diseases in humans or animals. Metagenomic sequencing for mosquito viromes is crucial for understanding the evolutionary history of viruses and preventing emerging mosquito-borne diseases. We collected 1,598 mosquitoes belonging to four species from five counties in Shandong Province, China in 2021. They were grouped by species and sampling locations and subjected to metagenomic next-generation sequencing for the analysis of the viromes. A total of 233,317,352 sequencing reads were classified into 30 viral families and an unclassified group. Comparative analysis showed that mosquitoes in Shandong Province generally possessed host-specific virome. We detected mosquito-borne viruses including Japanese encephalitis virus, Getah virus, and Kadipiro virus in Culex tritaeniorhynchus and Anopheles sinensis samples. Phylogenetic analysis showed that these pathogenic viruses may have existed in mosquitoes in Shandong Province for a long time. Meanwhile, we identified 22 novel viruses belonging to seven families and the genus Negevirus. Our study comprehensively described the viromes of several common mosquito species in Shandong Province, China, and demonstrated the major role of host species in shaping mosquito viromes. Furthermore, the metagenomic data provided valuable epidemiological information on multiple mosquito-borne viruses, highlighting the potential risk of infection transmission.IMPORTANCEMosquitoes are known as the source of various pathogens for humans and animals. Culex tritaeniorhynchus, Armigeres subalbatus, and Anopheles sinensis have been found to transmit the Getah virus, which has recently caused increasing infections in China. Cx. tritaeniorhynchus and Culex pipiens are the main vectors of Japanese encephalitis virus and have caused epidemics of Japanese encephalitis in China in past decades. These mosquitoes are widely present in Shandong Province, China, leading to a great threat to public health and the breeding industry. This study provided a comprehensive insight into the viromes of several common mosquito species in Shandong Province, China. The metagenomic sequencing data revealed the risks of multiple pathogenic mosquito-borne viruses, including Japanese encephalitis virus, Getah virus, and Kadipiro virus, which are of great importance for preventing emerging viral epidemics.

Background: Epstein-Barr virus (EBV) is widely infected in humans and causes various diseases. Among them, microRNAs of EBV play a key role in the progression of EBV-associated febrile diseases. There're few specific indicators for rapid differential diagnosis of various febrile diseases associated with EBV, and the lack of more reliable screening methods with high diagnostic utility has led to spaces for improvement in the accurate diagnosis and efficient treatment of relevant patients, making EBV infection a complicated clinical problem. With recent advances in plasma microRNA testing, the apparent presence of EBV microRNAs in plasma can help screen for EBV infection. The gene networks targeted by these microRNAs can also indicate potential biomarkers of EBV-associated febrile diseases. This study aimed to identify some novel miRNAs as potential biomarkers for early diagnosis of respectively EBV-associated febrile diseases. Materials and methods: A total of 110 participants were recruited for this task. First, we performed high-throughput sequencing and preliminary PCR validation of differentially expressed miRNAs in 15 participants with EBV-associated fever (divided into 5 groups, common EBV carriers, infectious mononucleosis (IM) and chronic active EBV infection (CAEBV), EBV-associated Hemophagocytic Lymphohistiocytosis (EBV-HLH), and 3 healthy individuals). After a comprehensive analysis, 10 miRNAs with abnormal expression were screened, and then qRT-PCR was performed in the rest of 95 participants to detect the validation of miRNAs expression in plasma samples. Thereafter, we further investigated their potential for clinical application in EBV-related febrile diseases by using a combination of Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Protein-protein interaction network analysis. Results: Through identification and detailed analysis of the obtained data, we found significant differences in the expression of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in blood samples from patients with different EBV-related febrile diseases. We found that the expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p in plasma are indicative of determining different disease types of EBV-related febrile diseases, while EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets. Conclusion: The expression levels of Hsa-miR-320d, EBV-miR-BART22, and EBV-miR-BART2-3p suggest that they may be used as transcriptional features for early differential diagnosis of EBV-related febrile diseases, and EBV-miR-BART22 and EBV-miR-BART2-3p may be potential therapeutic targets.

Abstract Despite the widespread applications of electroporation in biotechnology and medicine, monitoring the distribution of deep tissue electrical fields in real-time during treatment continues to pose a challenge. Current medical imaging modalities are unable to monitor electroporation during pulse delivery. Here we propose a method to use electroacoustic tomography (EAT) to prompt the emission of broadband ultrasound waves via electrical energy deposition. EAT boasts submillimeter resolution at depths reaching 7.5 centimeters and can deliver imaging speeds up to 100 frames per second when paired with an ultrasound array system. We’ve successfully detected EAT signals at electric field strengths ranging from 60 volts per centimeter to several tens of kilovolts per centimeter. This establishes EAT as a potential label-free, high-resolution approach for real-time evaluation of deep tissue electroporation during therapeutic procedures.

Background: Similar to the high-fat diet (HFD), the high-glycemic diet (HGD) contributes to the development and progression of type 2 diabetes mellitus (T2DM). However, the effect of HGD on gastrointestinal motility in T2DM and its u nderlying mechanisms remain unclear. Methods: Thirty C57BL/6J mice were randomly designated into the normal-feeding diet (NFD) group, HFD group, and HGD group. The plasma glucose, plasma insulin, and gastrointestinal motility were examined. Meanwhile, the tension of isolated colonic smooth muscle rings was calculated, and the gut microbiota was analyzed by 16s rDNA high-throughput sequencing. Result: After 16 weeks of HGD feeding, obesity, hyperglycemia, insulin resistance, and constipation were observed in HGD mice. Autonomic contraction frequency of the colonic neuromuscular system and electrical field stimulation-induced contractions were reduced in HGD mice. On the contrary, neuronal nitric oxide synthase activity and neuromuscular relaxation were found to be enhanced. Finally, gut microbiota analysis revealed that Rhodospirillaceae abundance significantly increased at the family level in HGD mice. At the genus level, the abundance of Insolitispirillum increased remarkably, whereas Turicibacter abundance decreased significantly in HGD mice. Conclusion: HGD induced constipation in obese diabetic mice, which we speculated that it may be related to neuromuscular dysmotility and intestinal microbiota dysbiosis.

The pathogenesis of psoriasis has not been fully defined. The dysfunction of T cell subsets is considered to play a key role in the pathogenesis of psoriasis, and the biologics targeting T cell subsets have also become a milestone in the treatment of psoriasis. However, there are still some problems in the application of existing biologics, suggesting that the current understanding of the pathogenesis of psoriasis is still insufficient. There is increasing evidence that tumor necrosis factor-α-induced protein 3 (TNFAIP3), a negative feedback regulator of NF-κB, plays an important role in the pathogenesis of psoriasis through the regulation of T cells, keratinocytes, dendritic cells and other immune cells. In this review, the research progress of TNFAIP3 gene, its relationship with psoriasis and its mechanisms of action are reviewed, providing reference for the search for new therapeutic targets for psoriasis.

Abstract Background Facial symmetry severely affects appearance and function. Large numbers of patients seek orthodontic treatment to improve facial symmetry. However, the correlation between hard- and soft-tissue symmetry is still unclear. Our aim was to investigate the hard- and soft-tissue symmetry in subjects with different levels of menton deviation and sagittal skeletal classes with 3D digital analysis and to investigate the relationship between the entire and individual hard- and soft-tissues. Methods A total of 270 adults (135 males and 135 females) consisting of 45 subjects of each sex in each sagittal skeletal classification group. All subjects were further classified into relative symmetry (RS), moderate asymmetry (MA) and severe asymmetry (SA) groups based on the degree of menton deviation from the mid-sagittal plane (MSP). The 3D images were segmented into anatomical structures and mirrored across the MSP after establishing a coordinate system. Original and mirrored images were registered by a best-fit algorithm, and the corresponding root mean square (RMS) values and colormap were obtained. The Mann‒Whitney U test and Spearman correlation were conducted for statistical analysis. Results The RMS increased with greater deviations with regard to the deviation of the menton in most of anatomical structures. Asymmetry was represented in the same way regardless of sagittal skeletal pattern. The soft-tissue asymmetry had a significant correlation with dentition in the RS group (0.409), while in the SA group, it was related to the ramus (0.526) and corpus (0.417) in males and was related to the ramus in the MA (0.332) and SA (0.359) groups in females. Conclusions The mirroring method combining CBCT and 3dMD provides a new approach for symmetry analysis. Asymmetry might not be influenced by sagittal skeletal patterns. Soft-tissue asymmetry might be reduced by improving the dentition in individuals with RS group, while among those with MA or SA, whose menton deviation was larger than 2 mm, orthognathic treatment should be considered.

Background. Atherosclerosis is an inflammatory cardiovascular disease. However, whether the association of immune cells in plaques promotes the progression of this disease has not yet been completely elucidated. Materials and Methods. Thus, this study aimed to investigate the relationship between C1q+ macrophages and CD8T cells through scRNA-seq data reanalysis, quantitative real-time PCR, and flow cytometry. Chromatin immunoprecipitation-quantitative polymerase chain reaction, western blot, and antibody-blocking experiments were performed to investigate the role of macrophage–CD8T interaction in atherosclerosis. An atherosclerotic mouse model was developed to confirm our findings. Results. Mechanistically, Spi1 expression induced by granulocyte–macrophage colony-stimulating factor promoted C1q expression in the macrophages. Moreover, C1q+ macrophages suppressed CD8T cell apoptosis by upregulating Slc7a7 expression to enhance the L-arginine uptake of CD8T cells. CD8T-derived interferon-γ promoted macrophage activation to induce atherosclerosis. Blockade of the C1q–C1qbp axis attenuated atherosclerosis. Conclusion. In conclusion, macrophages interacting with CD8T promote atherosclerosis development via the C1q–C1qbp axis.

We previously demonstrated that glycyrrhizin (GL) suppressed inflammation and carcinogenesis in an azoxymethane (AOM)/dextran sodium sulfate (DSS)-induced murine model of colorectal cancer (CC). In this study, we found an accumulation of regulatory T cells (Tregs) in the spleen and suppression by GL in model mice. ICR mice were divided into four groups: Control, GL, CC, and GL-treated CC (CC+GL), and were sacrificed 20 weeks after AOM/DSS treatment. We measured spleen weight, areas of white and red pulp, and CD8+ T cells (cytotoxic T lymphocytes, CTL), and CD11c-positive cells (dendritic cells) in splenic tissues and forkhead box protein 3 (FoxP3)-positive cells (Tregs) in colorectal and splenic tissues. In all cases, the CC group showed a significant increase compared with those in Control group, and GL administration significantly attenuated this increase. These results indicate that Tregs accumulated in the spleen may participate in inflammation-related carcinogenesis by suppressing CTL. We also suggest that GL which binds to high-mobility group box 1 (HMGB1), suppresses carcinogenesis with decreasing Tregs in the spleen. Furthermore, there was an expression of FoxP3 in cancer cells, indicating that it may be involved in the malignant transformation of cancer cells.

Primary ciliary dyskinesia (PCD) is a hereditary disease caused by genes related to motile cilia. We report two male pediatric cases of PCD caused by hemizygous pathogenic variants in the OFD1 centriole and centriolar satellite protein (OFD1) gene. The variants were NM_003611.3: c.[2789_2793delTAAAA] (p.[Ile930LysfsTer8]) in Case 1 and c.[2632_2635delGAAG] (p.[Glu878LysfsTer9]) in Case 2. Both cases had characteristic recurrent respiratory infections. Neither case had symptoms of oral-facial-digital syndrome type I. We identified a variant (c.2632_2635delGAAG) that has not been previously reported in any case of OFD1-PCD.

Abstract Cryogenic transmission electron microscopy (cryo‐TEM) has impacted biology and materials science profoundly due to its power in studying aqueous specimens. However, it remains challenging to extend this technique to organic solvent systems as organic solvents are often difficult to vitrify and are unstable under electron beams. Here, we studied the response of the 23 most commonly used organic solvents to vitrification and electron exposure in cryo‐TEM experiments. Optimized vitrification method was determined for each of the solvents, and the electron tolerances of the solvents were thoroughly measured using high‐resolution imaging. Generic rules underlying the different performances of the solvents were discussed. Based on the rules, methods were developed to enhance the electron exposure stability of the organic solvents. Our results provide guidance for optimizing cryo‐TEM experiments on organic solvent specimens.

Objectives Chronic obstructive pulmonary disease (COPD) is a disease associated with ageing. However, actual age does not accurately reflect the degree of biological ageing. Phenotypic age (PhenoAge) is a new indicator of biological ageing, and phenotypic age minus actual age is known as phenotypic age acceleration (PhenoAgeAccel). This research aimed to analyse the relationship between PhenoAgeAccel and lung function and COPD.Design A cross-sectional study.Participants Data for the study were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007–2010. We defined people with forced expiratory volume in 1 s/forced vital capacity

Highlights Defect engineering for constructing Zn2+ reservoir to anchor anions. The quasi-solid electrolyte interphase as Zn2+ reservoir boosting charge and mass transfer for dendrite-free zinc battery. A Coulombic efficiency of 99.8% was achieved in Zn||Cu cell.

Climate change exerts significant impacts on regional agricultural production. This study assesses the implications of climate change on winter wheat yields in the Huang-Huai-Hai Plain (3H Plain), utilizing bias-corrected climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for mid-21st century (2041–2060) and late 21st century (2081–2100) periods under two shared socioeconomic pathways (SSP2–4.5 and SSP5–8.5). These projections were incorporated into the decision support system for agrotechnology transfer (DSSAT) CERES-Wheat model to forecast potential alterations in winter wheat production. Initial findings reveal that uncorrected CMIP6 projections underestimated temperature and precipitation while overestimating solar radiation across the southern 3H Plain. Following bias correction through the equidistant cumulative distribution function (EDCDF) method, the regional average biases for temperature, precipitation, and solar radiation were reduced by 18.3%, 5.6%, and 30.7%, respectively. Under the SSP2–4.5 and SSP5–8.5 scenarios, mid-21st century simulations predicted a 13% increase in winter wheat yields. Late 21st century projections indicated yield increases of 11.3% and 3.6% under SSP2-4.5 and SSP5-8.5 scenarios, respectively, with a notable 8.4% decrease in yields south of 36° N under the SSP5-8.5 scenario. The analysis of climate change factors and winter wheat yields in the 3H Plain under both scenarios identified precipitation as the key contributing factor to yield increases in the northern 3H Plain, while temperature limitations were the primary constraint on yields in the southern region. Consequently, adaptive strategies are essential to mitigate climate change impacts, with a particular focus on addressing the challenges posed by elevated temperature in the southern 3H Plain.

In recent years, the excessive of antibiotics in livestock and poultry husbandry, stemming from extensive industry experience, has resulted in the accumulation of residual antibiotics and antibiotic resistance genes (ARGs) in livestock manure. Composting, as a crucial approach for the utilization of manure resources, has the potential to reduce the levels of antibiotics and ARGs in manure, although complete elimination is challenging. Previous studies have primarily focused on the diversity and abundance of ARGs in compost or have solely examined the correlation between ARGs and their carriers, potentially leading to a misjudgment of the actual risk associated with ARGs in compost. To address this gap, this study investigated the transfer potential of ARGs in compost and their co-occurrence with opportunistic pathogenic bacteria by extensively analyzing metagenomic sequencing data of compost worldwide. The results demonstrated that the potential risk of ARGs in compost was significantly lower than in manure, suggesting that composting effectively reduces the risk of ARGs. Further analysis showed that the microbes shifted their life history strategy in manure and compost due to antibiotic pressure and formed metabolic interactions dominated by antibiotic-resistant microbes, increasing ARG dissemination frequency. Therefore, husbandry practice without antibiotic addition was recommended to control ARG evolution, dissemination, and abatement both at the source and throughout processing.

Context Amauroderma rugosum (Blume & T. Nees) Torrend (Ganodermataceae) is an edible mushroom with medicinal properties. However, the effects of A. rugosum on gastric ulcer remain unclear.Objective To investigate the gastroprotective efficacy of water extract of A. rugosum (WEA) on gastric ulcer.Materials and methods Sprague-Dawley rats were randomly grouped as control, model, lansoprazole and 200, 100 and 50 mg/kg of WEA. After pre-treatment for seven days, ethanol- and indomethacin-induced gastric ulcer models were established. The gastric ulcer and histopathology were investigated. Enzyme-linked immunosorbent assay (ELISA), quantitative polymerase chain reaction (Q-PCR) and Western blot assays were conducted to explore the potential anti-inflammatory effect and mechanism of WEA. Additionally, the pyloric ligation model was used to explore the influence of WEA on gastric acid and mucus.Results Pre-treatment with WEA (200, 100 and 50 mg/kg) effectively reduced ulcerous area in both ethanol-induced (71%, 88% and 71%) and indomethacin-induced (77%, 65% and 86%) gastric ulcer model. The gastric levels of tumour necrosis factor-alpha (TNF-α) (34% and 50 mg/kg), interleukin-6 (IL-6) (32% and 100 mg/kg) and interleukin-1β (IL-1β) (36%, 45% and 41%) were reduced significantly (p

Shaanxi earthquake intensity quick report and early warning system has a total of 1000 general stations, including 485 national projects and 515 provincial projects. The station infrastructure construction and instrument equipment installation were completed at the end of September 2021, and the data were sent back to Shaanxi Earthquake Early Warning Center. During the trial operation period, it basically met the technical requirements of the trial operation of general stations of China Earthquake Administration. In view of the different networking modes, equipment selection and installation sites of the two projects, this paper counted the project operation rate, data delay and other data for a total of four months from November 2021 to February 2022. Based on the comparative analysis of the networking modes, operation rate and communication conditions of the general stations of the two projects, it is found that the operation rate of the national general stations is more stable than the provincial general stations, but the delay time is larger. The delay time in the dense area of stations increased. The national and provincial general stations cannot meet the communication delay of less than or equal to 2 s. Considering that in the future earthquake monitoring efficiency improvement project, general stations may be encrypted and deployed to all township streets in the province. This work can form a certain reference value of operation data supporting for the construction of networking mode of general stations in the future, and give some suggestions for communication delay, equipment installation, etc.

Objectives: This study was aimed at describing antibiotic susceptibility patterns and developing a predictive model by assessing risk factors for carbapenem-resistant Pseudomonas aeruginosa (CRPA). Methods: A retrospective case-control study was conducted at a teaching hospital in China from May 2019 to July 2021. Patients were divided into the carbapenem-susceptible P. aeruginosa (CSPA) group and the CRPA group. Medical records were reviewed to find an antibiotic susceptibility pattern. Multivariate analysis results were used to identify risk factors and build a predictive model. Results: A total of 61 among 292 patients with nosocomial pneumonia were infected with CRPA. In the CSPA and CRPA groups, amikacin was identified as the most effective antibiotic, with susceptibility of 89.7%. The CRPA group showed considerably higher rates of resistance to the tested antibiotics. Based on the results of mCIM and eCIM, 28 (45.9%) of 61 isolates might be carbapenemase producers. Independent risk factors related to CRPA nosocomial pneumonia were craniocerebral injury, pulmonary fungus infection, prior use of carbapenems, prior use of cefoperazone-sulbactam, and time at risk (≥15 d). In the predictive model, a score >1 point indicated the best predictive ability. Conclusions: CRPA nosocomial pneumonia could be predicted by risk factor assessment particularly based on the underlying disease, antimicrobial exposure, and time at risk, which could help prevent nosocomial pneumonia.

Summary: Sodium-ion batteries (SIBs) are promising candidates for large-scale energy storage. Increasing the energy density of SIBs demands anode materials with high gravimetric and volumetric capacity. To overcome the drawback of low density of conventional nanosized or porous electrode materials, compact heterostructured particles are developed in this work with improved Na storage capacity by volume, which are composed of SnO2 nanoparticles loaded into nanoporous TiO2 followed by carbon coating. The resulted TiO2@SnO2@C (denoted as TSC) particles inherit the structural integrity of TiO2 and extra capacity contribution from SnO2, delivering a volumetric capacity of 393 mAh cm−3 notably higher than that of porous TiO2 and commercial hard carbon. The heterogeneous interface between TiO2 and SnO2 is believed to promote the charge transfer and facilitate the redox reactions in the compact heterogeneous particles. This work demonstrates a useful strategy for electrode materials with high volumetric capacity.

Human infection with Chlamydia psittaci is rare but difficult to recognize. We report an outbreak of psittacosis among poultry processing workers in China. We applied metagenomic next-generation sequencing and identified Chlamydia psittaci reads from samples of all seven patients, four of which were subsequently confirmed by PCR. Epidemiological results suggested that the poultry processed in the factory was the possible source of human infection.

Abstract Electrochemical CO2 reduction reaction (CO2RR) to multi-carbon products would simultaneously reduce CO2 emission and produce high-value chemicals. Herein, we report Cu electrodes modified by metal–organic framework (MOF) exhibiting enhanced electrocatalytic performance to convert CO2 into ethylene and ethanol. The Zr-based MOF, UiO-66 would in situ transform into amorphous ZrOx nanoparticles (a-ZrOx), constructing a-ZrOx/Cu hetero-interface as a dual-site catalyst. The Faradaic efficiency of multi-carbon (C2+) products for optimal UiO-66-coated Cu (0.5-UiO/Cu) electrode reaches a high value of 74% at − 1.05 V versus RHE. The intrinsic activity for C2+ products on 0.5-UiO/Cu electrode is about two times higher than that of Cu foil. In situ surface-enhanced Raman spectra demonstrate that UiO-66-derived a-ZrOx coating can promote the stabilization of atop-bound CO* intermediates on Cu surface during CO2 electrolysis, leading to increased CO* coverage and facilitating the C–C coupling process. The present study gives new insights into tailoring the adsorption configurations of CO2RR intermediate by designing dual-site electrocatalysts with hetero-interfaces.

In lower-limb rehabilitation, human action recognition (HAR) technology can be introduced to analyze the surface electromyography (sEMG) signal generated by movements, which can provide an objective and accurate evaluation of the patient’s action. To balance the long cycle required for rehabilitation and the inconvenient factors brought by wearing sEMG devices, a portable sEMG signal acquisition device was developed that can be used under daily scenarios. Additionally, a mobile application was developed to meet the demand for real-time monitoring and analysis of sEMG signals. This application can monitor data in real time and has functions such as plotting, filtering, storage, and action capture and recognition. To build the dataset required for the recognition model, six lower-limb motions were developed for rehabilitation (kick, toe off, heel off, toe off and heel up, step back and kick, and full gait). The sEMG segment and action label were combined for training a convolutional neural network (CNN) to achieve high-precision recognition performance for human lower-limb actions (with a maximum accuracy of 97.96% and recognition accuracy for all actions reaching over 97%). The results show that the smartphone-based sEMG analysis system proposed in this paper can provide reliable information for the clinical evaluation of lower-limb rehabilitation.

IntroductionDevelopment of weed and crop detection algorithms provides theoretical support for weed control and becomes an effective tool for the site-specific weed management. For weed and crop object detection tasks in the field, there is often a large difference between the number of weed and crop, resulting in an unbalanced distribution of samples and further posing difficulties for the detection task. In addition, most developed models tend to miss the small weed objects, leading to unsatisfied detection results. To overcome these issues, we proposed a pixel-level synthesization data augmentation method and a TIA-YOLOv5 network for weed and crop detection in the complex field environment.MethodsThe pixel-level synthesization data augmentation method generated synthetic images by pasting weed pixels into original images. In the TIA-YOLOv5, a transformer encoder block was added to the backbone to improve the sensitivity of the model to weeds, a channel feature fusion with involution (CFFI) strategy was proposed for channel feature fusion while reducing information loss, and adaptive spatial feature fusion (ASFF) was introduced for feature fusion of different scales in the prediction head.ResultsTest results with a publicly available sugarbeet dataset showed that the proposed TIA-YOLOv5 network yielded an F1-scoreweed, APweed and mAP@0.5 of 70.0%, 80.8% and 90.0%, respectively, which was 11.8%, 11.3% and 5.9% higher than the baseline YOLOv5 model. And the detection speed reached 20.8 FPS.DiscussionIn this paper, a fast and accurate workflow including a pixel-level synthesization data augmentation method and a TIA-YOLOv5 network was proposed for real-time weed and crop detection in the field. The proposed method improved the detection accuracy and speed, providing very promising detection results.

Abstract Background To assess the effects of Epstein–Barr virus (EBV) and human papillomavirus (HPV) infection on the tumor microenvironment, we examined the relationship between viral infection status, macrophage migration inhibitory factor (MIF), and tumor-associated macrophages in nasopharyngeal carcinoma (NPC). Methods A tissue microarray containing 150 cores from 90 patients with NPC and six with chronic inflammation was used. EBV and HPV status were detected using in situ hybridization with commercial EBER1 and HPV16/18 probes. Immunofluorescence double staining of MIF, pan-macrophage marker CD68, M1 macrophage marker CD11c, and M2 macrophage marker CD163 were analyzed using the same tissue microarray. The levels of these markers between NPC and inflammation cases and between tumor nests and stroma were compared. Correlations among these markers were analyzed. Results We found EBER1(+) cases in 90% of NPC patients, including 10% EBV/HPV co-infection. M1 macrophages mainly infiltrated the tumor nest, while M2 macrophages infiltrated the tumor stroma. We found a significant positive correlation between EBER1 levels and MIF levels in tumor nests and a significant positive correlation between HPV16/18 and CD11c(+) cell levels in NPC tissues. Conclusions It is suggested that MIF is associated with EBV, and M1 macrophage infiltration is affected by HPV status in NPC.

Extensively drug-resistant and hypervirulent Klebsiella pneumoniae (XDR-hvKp) is a new problem for patients in Intensive Care Unit (ICU) and can become an even more severe threat if resistant to tigecycline, considered one of the ‘last lines of defense’ drugs. This study collected seven non-replicated tigecycline-resistant XDR-hvKp from seven patients and performed genome analysis and epidemiological investigation using whole genome equencing (WGS) and other methods. All strains in this study were identified as ST11-KL64 and showed high resistance to antibiotics such as β-lactams, aminoglycosides, quinolones, and tigecycline, and one strain was also resistant to colistin. All strains were determined to be hvKp by the results of serum resistance assay and Galleria mellonella infection models. All strains had resistance genes blaCTX-M-65,blaKPC-2,blaLAP-2,blaTEM-1B, rmtB, and qnrS1 and virulence factors such as rmpA, rmpA2, and aerobactin (iucABCD, iutA). The expression of the AcrAB-TolC efflux pump was upregulated in all strains, and the expression levels of the gene pmrK was significantly upregulated in colistin-resistant strain DP compared to colistin-sensitive strain WT in this study. In conclusion, we described an outbreak caused by tigecycline-resistant XDR-hvKp in the ICU of a teaching hospital in southwest China. The spread of these superbugs poses a great threat to patients and therefore requires us to closely monitor these XDR-hvKp and develop relevant strategies to combat them.

Background: Central fatigue (CF) is a subjective sense of tiredness associated with cognitive and memory disorders, accompanied by reduced physical endurance and negative emotions, such as anxiety and depression. Disease progression and prognosis with regards to CF have been unfavorable and possibly contribute to dementia, schizophrenia, and other diseases. Additionally, effective treatments for CF are lacking. KangPiLao decoction (KPLD) has been widely applied in clinical treatment and is composed of six Chinese herbal medicines, some of which have confirmed anti-fatigue effects. While glutamic acid (Glu) is the main excitatory transmitter in the central nervous system (CNS), gamma-aminobutyric acid (GABA) is the major inhibitory transmitter. Both are involved in emotional, cognitive, and memory functions. This research was designed to explore how KPLD regulates cognitive and emotional disorders in rats with CF and to identify the relationship between the regulatory effect and the GABA/Glu pathway.Methods: The compounds comprising KPLD were analyzed using high-performance liquid chromatography-mass spectrometry. Sixty Wistar rats were randomly divided into six groups. The modified multiple platform method was used to induce CF. Cognitive, emotional, and fatigue states were evaluated by performing behavioral tests (Morris water maze [MWM], open-field test [OFT], and grip strength test). Histomorphology, western blotting, immunohistochemistry, and RT-qPCR were performed to investigate protein and mRNA expression levels in the hippocampus and prefrontal cortexes involved in the GABA/Glu pathway.Results: Rats with CF exhibited impaired spatial cognition and increased negative emotions in the MWM and OFT. KPLD enabled the improvement of these symptoms, especially in the high-concentration group. Western blotting and RT-qPCR demonstrated that the expression of GABAARα1, GABAARγ2, GABABR1, and GAD67 in rats with CF was higher, whereas GAT-1 and NMDAR2B were lower in the hippocampus and prefrontal cortex. KPLD decreased the expression of GABAARα1, GABABR1, GABAARγ2, and GAD67 in the hippocampus and prefrontal cortex and enhanced the expression of NR2B in the prefrontal cortex.Conclusion: KPLD significantly improved cognitive and emotional disorders in rats with CF by regulating the GABA/Glu pathway. Overall, KPLD may be a promising candidate for developing a drug for treating CF.

Background: Three-dimensional facial soft tissue landmark prediction is an important tool in dentistry, for which several methods have been developed in recent years, including a deep learning algorithm which relies on converting 3D models into 2D maps, which results in the loss of information and precision. Methods: This study proposes a neural network architecture capable of directly predicting landmarks from a 3D facial soft tissue model. Firstly, the range of each organ is obtained by an object detection network. Secondly, the prediction networks obtain landmarks from the 3D models of different organs. Results: The mean error of this method in local experiments is 2.62±2.39, which is lower than that in other machine learning algorithms or geometric information algorithms. Additionally, over 72% of the mean error of test data falls within ±2.5 mm, and 100% falls within 3 mm. Moreover, this method can predict 32 landmarks, which is higher than any other machine learning-based algorithm. Conclusions: According to the results, the proposed method can precisely predict a large number of 3D facial soft tissue landmarks, which gives the feasibility of directly using 3D models for prediction.

User-generated content on various Internet platforms is growing explosively, and contains valuable information that helps decision-making. However, extracting this information accurately is still a challenge since there are massive amounts of data. Thereinto, sentiment analysis solves this problem by identifying people’s sentiments towards the opinion target. This article aims to provide an overview of deep learning for aspect-based sentiment analysis. Firstly, we give a brief introduction to the aspect-based sentiment analysis (ABSA) task. Then, we present the overall framework of the ABSA task from two different perspectives: significant subtasks and the task modeling process. Finally, challenges are proposed and summarized in the field of sentiment analysis, especially in the domain of aspect-based sentiment analysis. In addition, ABSA task also takes the relations between various objects into consideration, which is rarely discussed in the previous work.

Super resolution (SR) and Perceptual Image Enhancement (PIE) are gaining more and more interests in digital image processing and have been studied independently in the past decades. Although plenty of state-of-the-art researches have demonstrated great improvement in SR problem, they neglect practical requirements in real-world application. In practice, these two tasks are always mixed and combined to obtain a high-resolution enhanced (HRE) image with high quality from a low-resolution original image (LRO) with low quality. In this paper, we propose a joint SR-PIE learning framework called Deep SR-PIE, which comprises Multi-scale Backward Fusion Network (MBFNet), Perceptual Enhancement Network (PENet) and Dual-Path Unsampling Network (DUNet). MBFNet network is responsible for deep feature representation for further image reconstruction and perceptual enhancement, and PENet seeks the optimal local transformation to recover perceptual loss (color, tone, exposure and so on). DUNet works in different scales and exchanges each other to complement more details during upsampling. In our experiments, a real-world dataset is released to facilitate the development of joint learning for SR and PIE. Then, a thorough ablation study is provided to better understand the superiority of our method. Finally, extensive experiments suggest that the proposed method performs favorably against the state-of-the-arts in terms of visual quality, PSRN, SSIM, model size and inference time. By virtue of splitting operation and inverse residual blocks, as a lightweight deep neural network, our model is compatible with low-computation device.

As a C4 energy crop widely planted all over the world, sweet sorghum is mainly used in sugar making and brewing. Fresh sweet sorghum stalks contain many natural ingredients that have antioxidant properties and can significantly inhibit the growth of foodborne pathogens. In this study, the polyphenols in sweet sorghum were extracted by acid ethanol and ion precipitation, and the types of polyphenols were determined by HPLC-MS. The polyphenol content in fresh sweet sorghum stalks was 5.77 mg/g after process optimization with 18 types of phenolic acids identified. The extract had a total antioxidant capacity of 9.4 μmol Trolox/mL. Polyphenol extract of sweet sorghum displayed antibacterial activity against Staphylococcus aureus, Escherichia coli, Listeria spp., and Salmonella spp. The extract increased the conductivity of cell suspensions by destroying the membrane structure, resulting in leakage of cell electrolytes. Changes in bacterial morphology and internal structure were indicated. The data describe an optimized process to extract polyphenols from sweet sorghum stalks and the methodology to identify the major components within the extract. The data provide a novel option for the comprehensive utilization of fresh sweet sorghum stalks.

Mineralized collagen is the building block of bone but how the collagen directs hydroxyapatite formation remains unclear. Here, the authors demonstrate cylindrical pores in collagen and how the anisotropic growth of hydroxyapatite directs the orientation of crystal growth in mineralized collagen.

Abstract A robust solid-electrolyte interphase (SEI) enabled by electrolyte additive is a promising approach to stabilize Li anode and improve Li cycling efficiency. However, the self-sacrificial nature of SEI forming additives limits their capability to stabilize Li anode for long-term cycling. Herein, we demonstrate nanocapsules made from metal–organic frameworks for sustained release of LiNO3 as surface passivation additive in commercial carbonate-based electrolyte. The nanocapsules can offer over 10 times more LiNO3 than the solubility of LiNO3. Continuous supply of LiNO3 by nanocapsules forms a nitride-rich SEI layer on Li anode and persistently remedies SEI during prolonged cycling. As a result, lifespan of thin Li anode in 50 μm, which experiences drastic volume change and repeated SEI formation during cycling, has been notably improved. By pairing with an industry-level thick LiCoO2 cathode, practical Li-metal full cell demonstrates a remarkable capacity retention of 90% after 240 cycles, in contrast to fast capacity drop after 60 cycles in LiNO3 saturated electrolyte.

Weeds are among the major factors that could harm crop yield. Site-specific weed management has become an effective tool to control weed and machine vision combined with image processing is an effective approach for weed detection. In this work, an encoder-decoder deep learning network was investigated for pixel-wise semantic segmentation of crop and weed. Different input representations including different color space transformations and color indices were compared to optimize the input of the network. Three image enhancement methods were investigated to improve model robustness against different lighting conditions. The results show that for images without enhancement, color space transformation and vegetation indices without NIR (Near Infrared) information did not improve the segmentation results, while inclusion of NIR information significantly improved the segmentation accuracy, indicating the effectiveness of NIR information for precise segmentation under weak lighting condition. Image enhancement improved the image quality and consequently the robustness of segmentation models against different lighting conditions. The best MIoU value for pixel-wise segmentation was 88.91% and the best mean accuracy of object-wise segmentation was 96.12%. The deep network and image enhancement methods applied in this work provided promising segmentation results for weed detection and did not need large amount of data for model training, which is suitable for site-specific weed management.

It is very important to rapidly test the key indicators of water in the field to fully evaluate the quality of the regional water environment. However, a high-resolution measuring device that can generate small currents for low-concentration analytes in water samples is often bulky, complex to operate, and difficult for data sharing. This work introduces a portable multi-channel electrochemical device with a small volume, good interaction, and data-sharing capabilities called PMCED. The PMCED provides an easy-to-operate graphical interactive interface to conveniently set the parameters for cyclic voltammetry or a differential pulse method performed by the four electrode channels. At the same time, the device, with a current sensitivity of 100 nA V−1, was applied to the detection of water samples with high background current and achieved a high-resolution measurement at low current levels. The PMCED uses the Narrow Band Internet of Things (NB-IoT) to meet the needs for uploading data to the cloud in remote areas. The electrochemical signal preprocessing and chemometrics models run in the cloud, and the final results are visualized on a web page, providing a remote access channel for on-site testing results.

In order to evaluate the URTPSQ (Urban Rail Transit Passenger Service Quality) comprehensively, find the shortage of URTPSQ, find out the difference between the actual service situation and the passenger’s expectation and demand,and provide passengers with better travel services, a passenger-oriented KANO–Entropy–TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed and applied in this paper. Firstly, a KANO model is applied to select the service quality indicators from the 24 URTPSQ evaluation sub-indicators, according to the selection results, the KANO service quality indicators of URTPSQ are constructed. Then the sensitivity of the KANO service quality indicators based on the KANO model are calculated and ranked, the PS (Passenger Satisfaction) of each KANO service quality indicator by using the Entropy–TOPSIS method is calculated and ranked. Based on the difference between the sensitivity degree rank and the satisfaction degree rank of each KANO service quality indicator, determine the service quality KANO indicators of the URTPSQ that need to be improved significantly. A case study is conducted by taking the Chengdu subway system in China as a background. The results show that the Chengdu subway operation enterprises should pay attention to the must-be demand first, then the one-dimensional demand, finally the attractive demand. The three indicators, including transfer on the same floor in the station, service quality of staffs of urban rail transit enterprises,and cleanness in the station and passenger coach, need to be improved urgently. For the managers and operators of urban rail transit system, the passengers’ must-be demand should be satisfied first if the KANO model is applied to evaluate the service. The indicators with highest sensitivity degree and lowest TOPSIS value should be improved based on the KANO–Entropy–TOPSIS model. First published online 14 December 2021

Sentiment-controlled text generation aims to generate texts according to the given sentiment. However, most of the existing studies focus only on the document- or sentence-level sentiment control, leaving a gap for finer-grained control over the content of generated results. Fine-grained control allows a generated review to express different opinions toward multiple aspects. Some previous works attempted to generate reviews conditioned on aspect-level sentiments, but they usually suffer from low adaptability and the lack of an annotated dataset. To alleviate these problems, we propose a novel pre-trained extended generative model that can dynamically refer to the prompt sentiment, together with an auxiliary classifier that extracts the fine-grained sentiments from the unannotated sentences, thus we conducted training on both annotated and unannotated datasets. We also propose a query-hint mechanism to further guide the generation process toward the aspect-level sentiments at every time step. Experimental results from real-world datasets demonstrated that our model has excellent adaptability in generating aspect-level sentiment-controllable review texts with high sentiment coverage and stable quality since, on both datasets, our model steadily outperforms other baseline models in the metrics of BLEU-4, METETOR, and ROUGE-L etc. The limitation of this work is that we only focus on fine-grained sentiments that are explicitly expressed. Moreover, the implicitly expressed fine-grained sentiment-controllable text generation will be an important puzzle for future work.