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A novel penalty contact constitution was developed to replicate the hysteresis memory effect observed in contact interfaces. On this basis, a refined finite element analysis (FEA) was performed to study the stick–slip friction contact behavior of bolted joint interfaces. The analysis was validated by comparing it with the experimental hysteresis loops in the literature. The simulated hysteresis loops were subsequently used to identify four parameters of the Iwan model. Additionally, the effects of bolt clamping, friction coefficient, and excitation amplitude were individually examined. It was found that the deterioration in bolt clamping performance resulted in a decrease in both the equivalent joint stiffness and energy dissipation. Similarly, the reduction in the friction coefficient yielded a comparable impact. Furthermore, the identified model parameters of critical stick–slip force and displacement exhibited a quasi-linear relationship to the bolt preload and friction coefficient.

Perception plays a crucial role in ensuring the safety and reliability of autonomous driving systems. However, the recognition and localization of small objects in complex scenarios still pose challenges. In this paper, we propose a point cloud object detection method based on dynamic sparse voxelization to enhance the detection performance of small objects. This method employs a specialized point cloud encoding network to learn and generate pseudo-images from point cloud features. The feature extraction part uses sliding windows and transformer-based methods. Furthermore, multi-scale feature fusion is performed to enhance the granularity of small object information. In this experiment, the term “small object” refers to objects such as cyclists and pedestrians, which have fewer pixels compared to vehicles with more pixels, as well as objects of poorer quality in terms of detection. The experimental results demonstrate that, compared to the PointPillars algorithm and other related algorithms on the KITTI public dataset, the proposed algorithm exhibits improved detection accuracy for cyclist and pedestrian target objects. In particular, there is notable improvement in the detection accuracy of objects in the moderate and hard quality categories, with an overall average increase in accuracy of about 5%.

The realization of multifunctional advanced displays with better electro-optical properties is especially crucial at present. However, conventional integral full drive-based transparent display is increasingly failing to meet the demands of the day. Herein, partitioned polymerization as a novel preparation method was introduced innovatively into polymer-dispersed liquid crystals (PDLC) for realizing a step-driven display in agreement with fluorescent dye to solve the above drawback. At first, the utilization of fluorescent dye to endow the PDLC film with fluorescent properties resulted in a reduction in the saturation voltage of the PDLC from 39.7 V to 25.5 V and an increase in the contrast ratio from 58.4 to 96.6. Meanwhile, the experimental observations and theoretical considerations have elucidated that variation in microscopic pore size can significantly influence the electro-optical behavior of PDLC. Then, the step-driven PDLC film was fabricated through the exposure of different regions of the LC cell to different UV-light intensities, resulting in stepwise voltage–transmittance (V–T) responses of the PDLC film for the corresponding regions. Consequently, under appropriate driving voltages, the PDLC can realize three different states of total scattering, semi-transparent and total transparent, respectively. In addition, the PDLC film also embodied an outstanding anti-aging property and UV-shielding performance, which makes it fascinating for multifunctional advanced display applications.

Using the polymerization-induced phase separation (PIPS) method, bilayer polymer-dispersed liquid crystal (PDLC) films with a PDLC-PVA-PDLC structure were prepared in this work. It was found that all PDLC performance indexes were affected by polymer mesh size after comparing the microscopic morphology and electro-optical properties of samples with different monomer ratios. Gd2O3 nanoparticles and rhodamine B base fluorescent dyes introduced into the bilayer PDLC optimized the samples’ electro-optical properties and developed new functionalities. In addition, the bilayer PDLC doped with Gd2O3 and rhodamine B base held excellent progressive driving functions as well as stable durability properties. Samples doped with Gd2O3 nanoparticles and rhodamine B base also produced excellent anti-counterfeiting effects under UV irradiation at different angles, further exploiting the application potential of PDLC.

The continuous introduction of technologies such as distributed generation, wind power, and photovoltaic energy poses challenges to identifying abnormal waveforms in power disturbances. Due to the constant increase in abnormal features, existing waveform recognition schemes for power disturbance abnormalities cannot meet the requirements of high accuracy and reliability. In this paper, a Dimension-Enhanced Residual Multi-Scale Attention Framework for identifying power disturbance abnormal waveforms is proposed. This framework first employs the Phase Adaptive Adjustment (PAA) method to address the phase offset problem of original recording data, then uses the Gramian Angle Field method to perform dimensionality expansion on the data processed by PAA, and finally utilizes the Residual Pyramid Squeeze Attention Network (ResPSANet) for identifying power disturbance abnormal waveforms. Experiments demonstrate that the proposed approach improves the performance of power disturbance abnormal waveform recognition by 10% compared to existing schemes.

Terahertz detection technology has been confronted with formidable impediments, notably the paucity of sensitivity and operating temperature for photodetectors based on traditional bulk materials. In an attempt to surmount the difficulties, we propose an innovative terahertz detector based on a PtSe2 (type-II Dirac semimetallic material) integrated asymmetric antenna structure that can enhance the terahertz photoresponse by capitalizing on meticulous fabrication procedures. Experimental outcomes demonstrate the remarkable characteristics of the photodetector in the terahertz band, encompassing fast response time (7 µs), large responsivity (3.267 A/W), and low noise equivalent power (3.96 pW/Hz0.5). These accomplishments can be ascribed to the incorporation of the asymmetric metal contact of the four-leaf clover antenna structure and the excellent thermoelectric characteristics of PtSe2. This pioneering investigation consequently unveils a novel methodology for the creation of proficient PtSe2-based terahertz detectors and serves as a catalyst for the promotion of applications and further research within the terahertz sphere.

Abstract The dendritic cell (DC)‐T cell axis is a bridge that connects innate and adaptive immunities. The initial immune response against tumors is mainly induced by mature antigen‐presenting DCs. Enhancing the crosstalk between DCs and T cells may be an effective approach to improve the immune response to non‐small cell lung cancer (NSCLC). In this article, a review was made of the interaction between DCs and T cells in the treatment of NSCLC and how this interaction affects the treatment outcome.

IntroductionTumor-associated autoantibodies have been revealed as promising biomarkers for the early detection of lung cancer. This study was designed to develop an autoantibody panel for early detection of lung cancer in the Chinese population.MethodsRecruited prospectively in three clinical centers, the subjects (n = 991) who had a definite diagnosis during follow-up were included in the development of the autoantibody panel. The levels of 14 autoantibody candidates in plasma were detected.ResultsA panel of nine autoantibody markers (named as CN9), namely, P53, SOX2, SSX1, HuD, NY-ESO-1, CAGE, MAGE-A4, P62, and CK20, was preferably selected from 14 candidates. The overall specificity, sensitivity, and AUC were 90.5%, 40.8%, and 0.64, respectively. The CN9 panel demonstrated a reasonable detection rate in lung cancer patients at all stages, histological types, sizes of lesions, and risk levels. Its estimated overall accuracy is 85.5% and 90%, with PPV at 0.32 and 0.04, and NPV at 0.93 and 0.99 in the scenario of pulmonary nodules' characterizing and lung cancer screening, respectively. Two risk models were developed within the subgroups of malignant and benign pulmonary nodules in this study. By adding the CN9 result to the Mayo model indicators, it achieved a sensitivity of 41.3% and an AUC of 0.74 at a specificity of 91.3%. By adding the CN9 result to the Brock model indicators, it achieved a sensitivity of 47.7% and an AUC of 0.78 at a specificity of 91.3%. Both were improved compared with either the standalone Mayo or Brock model.DiscussionThis multi-center prospective study indicates a panel of nine autoantibody markers that can help in the detection of lung cancer and the classification of pulmonary nodules in the Chinese population.

Abstract Background ASXL2 encodes proteins involved in epigenetic regulation and the assembly of transcription factors at specific genomic loci. Germline de novo truncating variants in ASXL2 have been implicated in Shashi‐Pena syndrome, which results in features of developmental delay (DD), glabellar nevus flammeus, hypotonia, and cardiac disorders. However, the variants are rare, and the clinical spectrum may be incomplete. Methods The clinical data such as brain MRI were collect. The whole exome sequencing was performed for genetic etiology analysis. Results Here, we report a patient with DD, hypotonia, early atrial septal defect, and abnormal white matter signal. She presented with Shashi–Pena syndrome with a truncated variant in ASXL2 (NM_018263.6, c.2142_2152del, p.Ser714Argfs*5). She died of a digestive tract infection when she was 1 year and 6 months old. Conclusions Our study further expanded the spectrum of phenotypes and genetic variations of the syndrome, and we believe that it is necessary to screen the ASXL2 gene in patients with DD and cardiac and bone disorders.

BackgroundEmerging HIV drug resistance caused by increased usage of antiretroviral drugs (ARV) could jeopardize the success of standardized HIV management protocols in resource-limited settings. ObjectiveWe aimed to characterize pretreatment HIV drug resistance (PDR) among HIV-positive individuals and risk factors in China in 2022. MethodsThis cross-sectional study was conducted using 2-stage systematic sampling according to the World Health Organization’s surveillance guidelines in 8 provincial-level administrative divisions in 2022. Demographic information and plasma samples were obtained from study participants. PDR was analyzed using the Stanford HIV drug resistance database, and the Tamura-Nei 93 model in HIV-TRACE was used to calculate pairwise matches with a genetic distance of 0.01 substitutions per site. Logistic regression was used to identify and estimate factors associated with PDR. ResultsPDR testing was conducted on 2568 participants in 2022. Of the participants, 34.8% (n=893) were aged 30-49 years, 81.4% (n=2091) were male, and 3.2% (n=81) had prior ARV exposure. The prevalence of PDR to protease and reverse transcriptase regions, nonnucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 7.4% (n=190), 6.3% (n=163), 1.2% (n=32), and 0.2% (n=5), respectively. Yunnan, Jilin, and Zhejiang had much higher PDR incidence than did Sichuan. The prevalence of nonnucleoside reverse transcriptase inhibitor–related drug resistance was 6.1% (n=157) for efavirenz and 6.3% (n=163) for nevirapine. Multivariable logistic regression models indicated that participants who had prior ARV exposure (odds ratio [OR] 7.45, 95% CI 4.50-12.34) and the CRF55_01B HIV subtype (OR 2.61, 95% CI 1.41-4.83) were significantly associated with PDR. Among 618 (24.2%) sequences (nodes) associated with 253 molecular transmission clusters (size range 2-13), drug resistance mutation sites included K103, E138, V179, P225, V106, V108, L210, T215, P225, K238, and A98. ConclusionsThe overall prevalence of PDR in China in 2022 was modest. Targeted genotypic PDR testing and medication compliance interventions must be urgently expanded to address PDR among newly diagnosed people living with HIV in China.

Background: Gu-ben-hua-shi (AESS) formula is a clinical experienced prescription from Guangdong Hospital of Traditional Chinese Medicine (TCM), which is used to treat atopic dermatitis (AD). Our previous work has shown that AESS has therapeutic effect on AD by regulating yes-associated protein (YAP). AESS formula has multi-component and multi-target characteristic, and need to be analyzed by systematic chemical profiling and network pharmacology technology, as well as verification of key signaling pathways. Therefore, this study aimed at investigating the efficacy and effect of AESS formula in the treatment of AD and its effect on NLRP3 signaling pathway. Methods: The components of AESS formula were analyzed and identified by ultra high performance liquid chromatography/tandem mass spectrometry (UHPLC- MS/MS), and the potential mechanism of AESS formula in the treatment of AD was predicted by network pharmacology approach, with detected main components, and the potential components targeted NOD-like receptor thermal protein domain associated protein (NLRP3) signaling pathway [Direct binding with NLRP3, apoptosis-associated speck-like protein (ASC) and Caspase-1] were assessed using molecular docking. AD-like symptoms were constructed by DNCB induced BALB/c mice. The effect of AESS formula on dorsal skin structure in AD-like mice was observed using H&E staining. Furthermore, the western blotting experiment explored the expression of the NLRP3 pathway protein. Results: By UHPLC-MS/MS analysis, 91 compounds were detected in AESS formula, and 76 of them were identified, while by network pharmacological analysis, 1500 component targets were obtained, and 257 of them were obtained by intersection with eczema targets. Then one of the key pathways, nucleotide-binding oligomerization domain (NOD)-like signaling pathway was obtained by KEGG enrichment analysis. Molecular docking results showed 24 main components could effectively combine with ASC and Caspase-1 (≤−7 kcal/mol). The animal experiment results further showed that AESS formula alleviates symptoms in AD-like mice. ELISA kit results showed that the expression of IL-1β and IL-18 in serum was inhibited after AESS treatment. Additionally, western blotting analysis showed that the expressions of ASC, Caspase-1 and NLRP3 protein expression in the skin tissue of mice were down-regulated after AESS treatment. The experimental results show that AESS formula inhibited the expression of NLRP3 signaling pathway for the treatment of AD. Conclusions: AESS formula can improve AD symptoms in mice by inhibiting the activation of NLRP3 inflammasome and the expression of the related downstream inflammatory cytokines.

IntroductionChilling injury is one of the most common meteorological disasters affecting cucumber production. For implementing remedial measures as soon as possible to minimize production loss, a timely and precise assessment of chilling injury is crucial.MethodsTo evaluate the possibility of detecting cucumber chilling injury using chlorophyll fluorescence (ChlF) technology, we investigated the continuous changes in ChlF parameters under various low-temperature conditions and created the criteria for evaluating chilling injury. The ChlF induction curves were first collected before low-temperature as unstressed samples and daily 1 to 5 days after low-temperature as chilling injury samples. Principal component analysis was employed to investigate the public information on ChlF parameters and evaluate the differences between samples with different degrees of chilling injury. The parameters (Fv/Fm, Y(NO), qP, and Fo) accounted for a large proportion in the principal components and could characterize chilling injury. Uniform manifold approximation and projection method was employed to extract new features (Feature 1, Feature 2, Feature 3, and Feature 4) from ChlF parameters for subsequent classification model. Taking four features as input, a classification model based on the Fuzzy C-means clustering algorithm was constructed in order to identify the chilling injury classes of cucumber seedlings. The cucumber seedlings with different chilling injury classes were analyzed for ChlF images, rapid light curves, and malondialdehyde content.Results and discussionThe results demonstrated that the variations in these indicators among the different chilling injury classes supported the validity of the classification model. Our findings provide a better understanding of the relationship between ChlF parameters and the impact of low-temperature treatment on cucumber seedlings. This finding offers an additional perspective that can be used to evaluate the responses and damage that plants experience under stress.

Background Lung squamous cell carcinoma (LUSC) remains a leading cause of cancer-related deaths with few therapeutic strategies. Immune checkpoint inhibitors (ICIs) have demonstrated promising efficacy in patients with LUSC. However, ICIs could also lead to a unique spectrum of immune-related adverse events (irAEs), which dampen the clinical outcome. In-depth characterization of the immune hallmarks of antitumor responses and irAEs remains an unmet need to maximize ICI-treatment benefits of patients.Methods We performed single-cell RNA sequencing (scRNA-seq) on pre-ICI and on-ICI treatment tumor biopsies. We used bulk RNA-seq data of matched pretreatment/on-treatment tumors and irAE affected organs to validate observations from scRNA-seq analysis. Two independent patient cohorts were collected to determine circulating tumor necrosis factor (TNF) protein expression levels.Results We found that increased proportions of a macrophage subcluster with highly expressed secreted phosphoprotein 1 (SPP1) and two tumor cell subclusters in irAE patients, whereas proportions of two cytotoxic CD8+ T cell subclusters were higher in patients with partial response (PR). TNF signaling pathway was conversely associated with treatment efficacy and irAE development in most macrophage and tumor cell subclusters. Cell–cell communications for TNF ligand-receptor pairs between macrophage/T cells and tumor cells were also bidirectionally remodeled in responders versus non-responders and irAE versus non-irAE patients. Bulk RNA-seq analysis on matched pretreatment/on-treatment tumors and irAE affected organs revealed remarkably enhanced macrophage abundance and TNF signaling pathway in on-treatment tumors and organs developed irAEs. Furthermore, we observed significantly increased circulating TNF protein in plasma or serum of irAE patients but not ICI responders, based on analysis of two independent LUSC patient cohorts and one published ICI patient cohort.Conclusions Our data depicts specific reprogramming of macrophage, T cells and tumor cells associated with ICI response and irAEs, elucidates divergent roles of TNF signaling in antitumor immunity and irAEs, and highlights the significance of TNF expression in irAE development in the LUSC setting.

ObjectiveHIV/AIDS remains a global public health problem, and understanding the structure of social networks of people living with HIV/AIDS is of great importance to unravel HIV transmission, propose precision control and reduce new infections. This study aimed to investigate the epidemiological characteristics of HIV transmission in Fujian province, southeastern China from 2015 to 2020 based on HIV molecular network.MethodsNewly diagnosed, treatment-naive HIV/AIDS patients were randomly sampled from Fujian province in 2015 and 2020. Plasma was sampled for in-house genotyping resistance test, and HIV molecular network was created using the HIV-TRACE tool. Factors affecting the inclusion of variables in the HIV molecular network were identified using univariate and multivariate logistic regression analyses.ResultsA total of 1,714 eligible cases were finally recruited, including 806 cases in 2015 and 908 cases in 2020. The dominant HIV subtypes were CRF01_AE (41.7%) and CRF07_BC (38.3%) in 2015 and CRF07_BC (53. 3%) and CRF01_AE (29.1%) in 2020, and the prevalence of HIV drug resistance was 4.2% in 2015 and 5.3% in 2020. Sequences of CRF07_BC formed the largest HIV-1 transmission cluster at a genetic distance threshold of both 1.5 and 0.5%. Univariate and multivariate logistic regression analyses showed that ages of under 20 years and over 60 years, CRF07_BC subtype, Han ethnicity, sampling in 2015, absence of HIV drug resistance, married with spouse, sampling from three cities of Jinjiang, Nanping and Quanzhou resulted in higher proportions of sequences included in the HIV transmission molecular network at a genetic distance threshold of 1.5% (p < 0.05).ConclusionOur findings unravel the HIV molecular transmission network of newly diagnosed HIV/AIDS patients in Fujian province, southeastern China, which facilitates the understanding of HIV transmission patterns in the province.

Despite various treatment methods, the remission rate of membranous nephropathy remains limited. Refractory membranous nephropathy especially lacks effective treatment plans. Telitacicept achieves comprehensive inhibition of CD20-positive B cells, plasma cells, and T cells, thereby bringing new hope to the treatment of membranous nephropathy and refractory membranous nephropathy. Here, we report a case of a 46-year-old man with membranous nephropathy. Although the combined treatment with glucocorticoid, tacrolimus, mycophenolate mofetil, cyclophosphamide, and rituximab was not successful, the patient achieved complete remission of urinary protein after glucocorticoid combined with telitacicept. This is the first report on the application of telitacicept in the treatment of membranous nephropathy, especially refractory membranous nephropathy. The application of telitacicept in the treatment of membranous nephropathy deserves further attention.

IntroductionGradient vector flow (GVF) has been proven as an effective external force for active contours. However, its smoothness constraint does not take the image structure into account, such that the GVF diffusion is isotropic and cannot preserve weak edges well.MethodsIn this article, an image structure adaptive gradient vector flow (ISAGVF) external force is proposed for active contours. In the proposed ISAGVF model, the smoothness constraint is first reformulated in matrix form, and then the image structure tensor is incorporated. As the structure tensor characterizes the image structure well, the proposed ISAGVF model can be adaptive to image structure, and the ISAGVF snake performs well on weak edge preservation and deep concavity convergence while possessing some other desirable properties of the GVF snake, such as enlarged capture range and insensitivity to initialization.ResultsExperiments on synthetic and real images manifest these properties of the ISAGVF snake.

We construct a novel family of solutions of the holographic superfluid model with the excited states in the probe limit. We observe that the higher excited state or larger superfluid velocity will make the scalar hair more difficult to be developed, and the higher excited state or smaller mass of the scalar field makes it easier for the emergence of translating point from the second-order transition to the first-order one. We note that the difference of the critical chemical potential between the consecutive states increases as the superfluid velocity increases. Interestingly, the “Cave of Winds” phase structure will disappear but the first-order phase transition occurs for the excited states, which is completely different from the holographic superfluid model with the ground state. This means that the excited state will hinder the appearance of the Cave of Winds. Moreover, we find that there exist additional poles in Im[σ(ω)] and delta functions in Re[σ(ω)] arising at low temperature for the excited states, and the higher excited state or larger superfluid velocity results in the larger deviation from the expected relation in the gap frequency.

Abstract Projecting precipitation changes is essential for researchers to understand climate change impacts on hydrological cycle. This study projected future precipitation over the Hanjiang River Basin (HRB) based on the multimodel ensemble (ME) of six global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). An ME method using the fusion of four machine learning (ML) algorithms (random forest [RF], K‐nearest neighbors [KNN], extra tree [ET], and gradient boosting decision tree [GBDT]) was proposed in this study. The future precipitation changes were investigated during 2023–2042 (Near‐term), 2043–2062 (Mid‐term), and 2081–2100 (Long‐term) periods, with reference to the base period 1995–2014, under three integrated scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5) of the Shared Socioeconomic Pathways (SSPs) and the representative concentration pathways (RCPs). The results show that: (1) the proposed ME method performs better than the ME mean and individual ML algorithms, with a correlation coefficient value reaching 0.88 and Taylor skill score reaching 0.764. (2) The precipitation under SSP5‐8.5 has the largest upward trend with the annual precipitation variation range of −9.27% to 112.84% from 2023 to 2100, followed by SSP2‐4.5 with −30.48% to 44.67%, and the smallest under SSP1‐2.6 with −37.19% to 37.78%, which show a significant trend of humidification over the HRB in the future. (3) The precipitation changes over the HRB are projected to increase over time, with the largest in the Long‐term, followed by Mid‐term, and the smallest in the Near‐term. (4) The northeastern parts of the HRB are projected to experience a large precipitation in the future, and the southeastern parts are smaller. (5) Uncertainties in the projected precipitation over the HRB still exist, which can be reduced by ME. The findings obtained in this study have important implications for hydrological policymakers to make adaptive strategies to reduce the risks of climate change.

BackgroundThe COVID-19 pandemic has led to an increase in known risk factors for mental health problems. Although medical information available through the internet and smartphones has greatly expanded, people’s ability to seek, eschew, and use reliable web-based medical information and services to promote their mental health remains unknown. ObjectiveThis study aims to explore the associations between coronaphobia and 4 frequently reported mental health problems, loneliness, irritability, depression, and stigma, during the COVID-19 pandemic and to assess the moderating effects of eHealth literacy (eHL) on the adjustment of these relationships in Chinese young adults. MethodsThe data used in this study were collected from a web-based survey of the general Chinese population, aged between 18 and 30 years, conducted in China between December 2022 and January 2023. A nonprobability snowball sampling method was used for data collection. A Bayesian structural equation model (BSEM) using parameter expansion was used to estimate the moderating effect of eHL on the relationship between coronaphobia and psychological problems. The posterior mean and 95% highest density intervals (HDIs) were estimated. ResultsA total of 4119 participants completed the questionnaire and provided valid responses. Among them, 64.4% (n=2653) were female and 58.7% (n=2417) were rural residents. All measures showed statistically significant but minor-to-moderate associations (correlation coefficients ranged from −0.04 to 0.65). Significant heterogeneity was observed between rural and urban residents at the eHL level, and coronaphobia was observed. The BSEM results demonstrated that eHL was a significant moderator in reducing the negative effects of coronaphobia on loneliness (posterior mean −0.0016, 95% HDI −0.0022 to −0.0011), depression (posterior mean −0.006, 95% HDI −0.0079 to −0.004), stigma (posterior mean −0.0052, 95% HDI −0.0068 to −0.0036), and irritability (posterior mean −0.0037, 95% HDI −0.0052 to −0.0022). The moderating effects of eHL varied across the rural and urban subsamples. ConclusionsUsing BSEM, this study demonstrated that improving eHL can significantly mitigate the negative effects of coronaphobia on 4 COVID-19–related mental health problems in Chinese young adults. Future eHL initiatives should target rural communities to ensure equal access to information and resources that can help protect their mental health during the pandemic.

Regular checkups for thyroid-stimulating hormone (TSH) levels are essential for the diagnosis of thyroid disease. The enzyme-linked immunosorbent assay (ELISA) technique is a standard method for detecting TSH in the serum or plasma of hospitalized patients. A recently developed next-generation ELISA, the digital immunoassay (d-IA), has facilitated detection of molecules with ultra-high-sensitivity. In this study, we developed a TSH assay system using the d-IA platform. By utilizing the ultrasensitivity of d-IA, we were able to use a sample volume of as little as 5 µL for each assay (the dead volume was 5 µL). The limits of blank, detection, and quantification (i.e., functional sensitivity), were 0.000346, 0.001953, and 0.002280 μIU/mL, respectively, and the precision of the total coefficient of variation did not exceed 10%. The correlation between serum and plasma levels indicated good agreement. Thus, our system successfully measured TSH using d-IA with a small sample volume and equal functional sensitivity to the current third generation like ARCHITECT TSH assay, which has a functional sensitivity of 0.0038 μIU/mL.

CO2 capture using monoethanolamine (MEA) is one of the important decarbonization options and often considered as a benchmark, while the optimal MEA contraction and systematic process study are still lacking. In this work, firstly, the MEA concentrations between 15 and 30 wt% were studied from both process simulations with Aspen Plus and experimental measurements in the pilot-scale. 20 wt% MEA was identified as the preferable solution. Subsequently, a systematic analysis was conducted for CO2 capture using 20 wt% MEA with/without CO2 compression to study how various parameters, including gas flow rate, CO2 concentration, and CO2 removal rate, affected the energy demand and techno-economic performances quantitatively. The influence of each parameter on both energy demand and cost showed an obvious non-linear relationship, evidencing the importance of systematic analysis for further study on decarbonization. The evaluation indicated that the regeneration heat required the largest portion of energy demand. The economic analysis showed that the capital cost was more sensitive to the selected parameters than the operational cost, while the operational cost created a major change in the overall cost. In addition, the gas flow rate and CO2 concentration were the main parameters affecting the cost, rather than the CO2 removal rate. Finally, it was suggested that, for a new plant, CO2 capture showed the minimum investment cost per ton CO2 when operating the plant on a large scale, high CO2 concentration, and high CO2 removal rate; for an existing plant, the capture preferred to run with the high CO2 removal rate.

Giant cell arteritis (GCA) is a kind of systemic vasculitis affecting individuals over 50 years old and is often the cause of new-onset headaches in older adults. Patients with GCA sometimes have rheumatic polymyalgia (PMR). The diagnosis of GCA generally depends on clinical manifestation, elevated erythrocyte sedimentation rate (ESR) or C-reactive protein, and positive imaging findings commonly obtained by ultrasound or temporal artery biopsy. In this study, we report a case of an 83-year-old woman with a new-onset headache and an elevated ESR. The result of the temporal artery ultrasound did not distinguish between vasculitis and atherosclerosis. The F18-fluorodeoxyglucose positron emission tomography and computed tomography (18F FDG PET-CT) were performed and suggested large vessel vasculitis with temporal artery involvement. In addition, polyarticular synovitis and bursitis were also revealed. Finally, the diagnosis of secondary headache attributed to CGA complicated with PMR was established. The patient experienced remission of symptoms after glucocorticoid therapy. PET can become a powerful tool for diagnosis and differential diagnosis when the ultrasound result is ambiguous and a biopsy is not obtained.

Tumor metastasis causes over 90% of cancer related death and no currently available therapies target it. However, there is limited understanding regarding the epigenetic regulation of genes during this complex process. Here by integrating single-cell ATAC-seq (scATAC-seq), single-cell RNA-seq (scRNA-seq), microarray, bulk RNA-seq, immunohistochemistry (IHC) staining, as well as proteomics datasets from paired primary and liver metastatic colorectal cancer (CRC) patient-derived xenograft (PDX) model and patients, we discovered that liver metastatic CRC cells lose their colon-specific chromatin accessible sites yet gain liver-specific ones. Importantly, we observed elevated accessibility of HNF4A, a liver-specific transcription factor, in liver metastatic CRC cells. Subsequently, we performed clustering analysis of liver metastatic CRC cells together with cells involved in liver development, revealing significant heterogeneity among the liver metastatic CRC cells. Over 50% of the liver metastatic CRC cells exhibited characteristics similar to those of erythroid progenitors and hepatocytes, showing increased expression of genes involved in oxidative phosphorylation and glycolysis. Moreover, our discovery further revealed that the MHC and IFN response genes in these cells exhibit moderate epigenetic activity, which is significantly associated with the low objective response rates in checkpoint blockade immunotherapy. Our findings uncovered the critical roles of HNF4A and the cell populations within liver metastatic CRC cells might serve as crucial therapeutic targets for addressing liver metastasis and improving the immunotherapy response in patients with CRC.

Osteosarcoma, occurring most frequently in adolescents, are highly malignant bone tumor and prone to develop local recurrence and long-distance metastasis. Therefore, new comprehensive therapeutic strategies for osteosarcoma are urgently needed. Different from traditional photothermal therapy (PTT), low temperature PTT (LTPTT) not only brings less heat damages to the surrounding normal tissues but also prevent tumor metastasis. Nevertheless, its therapeutic effects are severely attenuated due to the tumor thermo-resistance induced by the overexpression of heat shock protein (HSP). In our work, an acid-responsive core–shell nanocomposite was fabricated for cancer therapy. The nanoplatform can independently encapsulate alkyl radical initiator 2,2-azobis[2-(2-imidazolin-2-yl) propane]-dihydroch-loride (AIPH) in the mesoporous polydopamine (MPDA) core and HSP inhibitor (gambogic acid, GA) in the zeolite imidazolate framework-8 (ZIF-8) microporous shell, called MPDA/AIPH@ZIF-8/GA (MAZG), which could achieve the combined functions of LTPTT and thermodynamic therapy (TDT). After endocytosing by tumor cells, the pH-responsive degradation of the ZIF-8 coating stimulates the rapid release of GA, which can effectively inhibit HSP expression in advance, and then simultaneously enhanced the therapeutic efficacy of LTPTT. Further, both in vitro and in vivo experiments have demonstrated that the as-synthesized MAZG nanocomposite exhibited favorable biosafety and remarkable tumor growth inhibition.

Objective To evaluate the role of anti-HBc detection in current blood screening strategy by the follow-up of repeated donors with antibody to hepatitis B virus core antigen. Methods Plasma samples were collected randomly from Dalian Blood Center. to test anti-HBc(dual reagents) and anti-HBs via ELISA. The re-donation of eligible donors who were anti-HBc+ and donors reactive to HBV detection were followed up. Results A total of 1 291 plasma samples were collected randomly from May 2017 to March 2018, among which 405 samples(31.4%)were anti-HBc+. The median age of anti-HBc+ group was observed much higher than that of anti-HBc-group (39 vs 31 years old) (P0.05). Among the 405 anti-HBc+ donors, 3 donors were OBI (0.7%), of which one was screened out in second donation. No HBV DNA was detected out in 3 OBI cases. Conclusion Although anti-HBc detection is not suitable in blood screening currently, it is of great value in the assessment of blood donor re-entry for HBV reactive donors in blood screening due to the high anti-HBc prevalence among blood donors.

Abstract Background Visceral adiposity index (VAI) has been recognized as a reliable indicator for visceral adiposity. However, it remains largely unexplored on its association with fasting plasma glucose (FPG). The current study aims to explore the association between VAI and FPG using a representative dataset. Methods A cross-sectional study was carried out based on the dataset from National Health and Nutrition Examination Survey (NHANES) 2017–2020. Univariate and Multiple linear regression analysis were performed to explore the relationship between VAI and FPG. Generalized additive model (GAM) and smooth curve fitting analysis were performed to explore the nonlinear relationship between VAI and FPG. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of VAI for FPG elevation. Results A total of 4437 participants with complete data were finally included in the research. Individuals were divided into 4 quartiles according to the calculated VAI value: Q1 (VAI

In order to solve the problem that the transient response of ZPW-2000A track circuit cannot be calculated directly in time domain, the modified nodal admittance method (MNA) combined with Q-D method is proposed to analyze the transient response of ZPW-2000A track circuit. Firstly, the hybrid model of traction network lines and ZPW-2000A track circuit is established. Secondly, using this model and Kirchhoff’s law, the MNA time domain equation is obtained. Through Laplace transform and decoupling, the complex frequency domain solution of the rail surface voltage at the receiving end of ZPW-2000A track circuit is obtained. Then, the numerical time domain solution of rail surface voltage is obtained by using Fourier transform and Q-D algorithm, and a simulation model is built to verify the correctness of the proposed method. Furthermore, the variation laws of the rail surface voltage at the receiving end affected by frequency, transmission distance and ballast resistance are analyzed. Finally, when the train enters and leaves the track section, there is a transient process, which can provide a reference for the train occupancy inspection and when the air core coil is in fault state, its transient response is different from that in normal state, which provides a reference for fault detection of track circuit.

Covalent organic frameworks are more and more used in the design of stimuli responsive materials. Here, the authors expand the application range of COFs by demonstrating a sweat induced colour change for detection of fingerprints using a sweat responsive COF.

Pea (Pisum sativum L.) is an annual cool-season legume crop. Owing to its role in sustainable agriculture as both a rotation and a cash crop, its global market is expanding and increased production is urgently needed. For both technical and regulatory reasons, neither conventional nor transgenic breeding techniques can keep pace with the demand for increased production. In answer to this challenge, CRISPR/Cas9 genome editing technology has been gaining traction in plant biology and crop breeding in recent years. However, there are currently no reports of the successful application of the CRISPR/Cas9 genome editing technology in pea. We developed a transient transformation system of hairy roots, mediated by Agrobacterium rhizogenes strain K599, to validate the efficiency of a CRISPR/Cas9 system. Further optimization resulted in an efficient vector, PsU6.3-tRNA-PsPDS3-en35S-PsCas9. We used this optimized CRISPR/Cas9 system to edit the pea phytoene desaturase (PsPDS) gene, causing albinism, by Agrobacterium-mediated genetic transformation. This is the first report of successful generation of gene-edited pea plants by this route.

Activated red mud (RM) has been proved to be a promising base material for the selective catalysis reduction (SCR) of NOx. The inherent low reducibility and acidity limited its low–temperature activity. In this work, molybdenum oxide, tungsten oxide, and cerium oxide were used to reconfigure the redox sites and acid sites of red mud based catalyst. When activated red mud was reconfigured by cerium-tungsten oxide (Ce–W@RM), the NOx conversion kept above 90% at 219–480 °C. The existence of Ce3+/Ce4+ redox electron pairs provided more surface adsorbed oxygen (Oα) and served as a redox cycle. Positive interactions between Ce, W species and Fe oxide in red mud occurred, which led to the formation of unsaturated chemical bond and promoted the activation of adsorbed NH3 species. WO3 and Ce2(WO4)3 (formed by solid–state reaction between Ce and W species) could provide more Brønsted acid sites (W–O modes of WO3, WO or W–O–W modes of Ce2(WO4)3). CeO2 species could provide more Lewis acid sites. The Langmuir–Hinshelwood (L-H) routes and Eley-Rideal (E-R) routes occurred in the low-temperature SCR reaction on the Ce–W@RM surface. NH4+ species on Brønsted acid sites, NH3 species on Lewis acid sites, bidentate nitrate and bridging nitrate species were key active intermediates species.

The morbidity and mortality of prostate cancer are increasing year by year, and the survival rate of prostate cancer patients after treatment is low. Therefore, investigating the molecular mechanism underlying prostate cancer is crucial for developing effective treatments. Recent studies have shown the important role of long-chain non-coding RNAs (lncRNAs) in tumorigenesis. VPS9D1-AS1 can modulate the progression of multiple cancers, but its molecular action mechanism in prostate cancer remains unknown. This study, therefore, intended to investigate the regulatory mechanism of VPS9D1-AS1 in prostate cancer. First, differentially expressed lncRNAs in prostate cancer were identified through bioinformatics approaches. The target lncRNA for the study was determined by reviewing the relevant literature and its downstream miRNA/mRNA axis was uncovered. Then, quantitative reverse transcription polymerase chain reaction was introduced to assess the expression of VPS9D1-AS1, miR-187-3p, and fibroblast growth factor receptor-like 1 (FGFRL1) at a cellular level, and Western blot was conducted to assess the protein level of FGFRL1 in cells. The results indicated that VPS9D1-AS1 and FGFRL1 were highly expressed in prostate cancer while miR-187-3p was less expressed. Besides, MTT, colony formation, wound healing, and cell invasion assays showed that silencing VPS9D1-AS1 inhibited the viability, migration ability, and invasion ability of prostate cancer cells. Dual-luciferase assay and RNA binding protein immunoprecipitation assay were performed to explore the interplay of miR-187-3p and VPS9D1-AS1 or FGFRL1. The results showed that VPS9D1-AS1 could sponge miR-187-3p, and FGFRL1 could serve as a direct target of miR-187-3p. Moreover, combined with the results of the rescue experiment, VPS9D1-AS1 was found to upregulate FGFRL1 by competitively sponging miR-187-3p to accelerate the malignant behaviors of prostate cancer cells. In conclusion, VPS9D1-AS1 could promote the phenotype progression of prostate cancer cells through targeting the miR-187-3p/FGFRL1 axis, and it has the potential to be a target for prostate cancer patients.

Gas insulated transmission lines (GIL) have a wide application prospect in special occasions such as cross terrain power transmission. Metal particle pollution is an important reason for the low insulation performance of GIL. When micron metal particles (MMPs), which are the most common metal particles in engineering, adhere to insulators or high-voltage electrodes, the insulation performance will be reduced. Based on that, this paper mainly studied the static adhesion characteristics of MMPs. Firstly, the static adhesion models and their applicable conditions were introduced. Then, through the atomic force microscope (AFM) test, the adhesion force of MMP-electrode and MMP-insulator was obtained. The test results show that MD model should be used to calculate the adhesion force of MMP-electrode and MMP-insulator. In addition, the adhesion force presents the characteristics of random distribution due to the surface asperities of MMPs and samples. Therefore, according to the test results, this paper introduced the equivalent adhesion work, which is a random variable, and obtained the probability distribution model of equivalent adhesion work. Finally, the distribution of adhesion force was obtained. The above research results provide guidance for inhibiting the adhesion of metal particles in GIL.

We present a dispersion-independent phase stabilized distribution architecture for broadband signal based on photonic microwave phase conjugation. RoF signals are distributed from the central station to each base station via a fiber ring network. The elimination of dispersion-induced optical phase decorrelation is achieved because the backward transmission of the phase-conjugated signal, thus the EVM of the RoF signal is optimized. A proof-of-concept experiment is demonstrated. A distribution of QPSK modulated 23-GHz, 400M Baud RoF signals from the central station to a remote base station is obtained via a fiber optic loop. The demodulated constellation and error vector magnitude with and without dispersion compensation are measured at the remote base station. When we set the length of the fiber loop to 58 km, the EVM is reduced by 8% after dispersion compensation, and the compensated EVM can reach the threshold value of 17.5% specified by 3 GPP for 5G when the received optical power of PD is 4 dBm.

Cell-free massive MIMO precoding leverages the large number of antennas and dense access point (AP) deployment to concurrently serve multiple users in a wide coverage area, thus promising efficient interference mitigation and significant network capacity enhancement. Most existing centralized precoding methods for cell-free massive MIMO systems, whether optimization-based or learning-based, suffer from high computational complexity or expensive communication overhead, introducing additional latency to the network in practical applications. To address the above issues, in this paper we propose two decentralized precoding methods based on the horizontal federated learning (HFL) and vertical federated learning (VFL) frameworks, respectively. In the HFL-based precoding method, we design a low-cost residual global channel state information (CSI) feature acquisition mechanism called RFAM at each AP to create local datasets. RFAM eliminates the need for point-to-point CSI exchange between APs, resulting in reduced communication overhead. In the VFL-based precoding method, each AP utilizes its own CSI for precoding scheme design, thereby eliminating the communication overhead associated with obtaining CSI from other APs. Furthermore, the computational complexity is considerably reduced due to the low overhead of model inference. Experimental results conducted in various channel environments show that the proposed HFL-based method achieves faster convergence rate and outperforms traditional decentralized methods in terms of sum-rate performance. The results also show that the proposed VFL-based method achieves similar sum-rate performance to centralized schemes.

Epilepsy is the unstable state caused by excessive discharge of brain cells. In more than 30 percent of epilepsy cases, seizures cannot be controlled with medication or surgery. Refractory epilepsy seriously affects the health of patients and brings great economic burden to families. Therefore, this requires an effective seizure classification and prediction method to reduce risk in epilepsy patients. Researchers proposed machine learning or deep learning methods to predict seizures. However, automatic screening of electrode channels and improvement of predictive accuracy remain a challenge. A multi-channel feature fusion model CNN-Bi-LSTM. This method only requires simple preprocessing. CNN is responsible for extracting spatial features, Bi-LSTM is responsible for extracting temporal features, and finally, two channel weights are allocated through the attention mechanism to filter out the results of the more weighted electrode channel output classification. The performance of the model is tested on the CHB-MIT dataset, and the output is divided into three categories, including normal, pre-seizure and mid-seizure. The ten-fold cross-validation average accuracy is 94.83%, the precision is 94.84%, the recall is 94.84%, the F1-score is 94.83%, and the MCC is 92.26% across CHB-MIT EEG. The ten-fold cross-validation average accuracy of UCI data set is 77.62%, the precision is 77.66%, the recall is 77.62%, the F1-score is 77.60%, and the MCC is 72.03%. The results showed that this method is superior to existing methods and can predict the EEG signals of epilepsy in advance. This work will be extended to design a removable epilepsy predictive device for real-time use.

Accurate prediction of network traffic trends is important for self-management, intelligent scheduling and network resource optimization of base stations. Network traffic prediction is a prerequisite for intelligent scheduling of base stations, and accurate prediction will be beneficial for improving network utilization and energy saving in scheduling. In this paper, a hybrid deep learning method for network traffic prediction, CEEMDAN-TGA which consists of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Temporal Convolutional Network (TCN), Gated Recurrent Unit (GRU), and Attention Mechanism is proposed. Firstly, CEEMDAN is introduced to decompose the original network traffic data into different modes, then reconstruct the modes into trend sequence and noise sequence. Secondly, TCN is used to extract the short-term local features in the network traffic, GRU is used to obtain the long-term data-dependent features, and the attention mechanism is used to improve the prediction accuracy and stability. Finally, through the comparison of experiments, the prediction effect and accuracy of the proposed method are verified to have significant advantages, and the network traffic scheduling strategy is proposed on the basis of prediction.

AbstractAmyloid-beta (Aβ) deposition and altered brain structure are the most relevant neuroimaging biomarkers for Alzheimer’s disease (AD). However, their spatial inconsistency was always confusing and misleading. Furthermore, the relationship between this spatial inconsistency and AD progression is unclear. The current study introduced a regional radiomics similarity network (R2SN) to map structural MRI and Aβ positron emission tomography (PET) images to study their cross-modal interregional coupling. A total of 790 participants (248 normal controls, 390 mild cognitive impaired patients, and 152 AD patients) with their structural MRI and PET images were studied. The results showed that global and regional R2SN coupling significantly decreased according to the severity of cognitive decline, from mild cognitive impairment to AD dementia. The global coupling patterns are discriminative between different APOE ε4, Aβ, and Tau subgroups. R2SN coupling was probed for relationships with neuropsychiatric measures and peripheral biomarkers. Kaplan–Meier analysis showed that lower global coupling scores could reveal worse clinical progression of dementia. The R2SN coupling scores derived from the coupling between Aβ and atrophy over individual brain regions could reflect the specific pathway of AD progression, which would be a reliable biomarker for AD.

To achieve lightweight B4C-based composite ceramics with high electrical conductivities and hardness, B4C–TiB2 ceramics were fabricated by reactive spark plasma sintering (SPS) using B4C, TiC, and amorphous B as raw materials. During the sintering process, fine B4C–TiB2 composite particles are firstly in situ synthesized by the reaction between TiC and B. Then, large raw B4C particles tend to grow at the cost of small B4C particles. Finally, small TiB2 grains surround large B4C grains to create a three-dimensional interconnected intergranular TiB2 network, which is beneficial for an electro-conductive network and greatly improves the conductivity of the ceramics. The effect of the B4C particle size on the mechanical and electrical properties of the ceramics was investigated. When the particle size of initial B4C powders is 10.29 µm, the obtained B4C–15 vol% TiB2 composite ceramics exhibit an electrical conductivity as high as 2.79×104 S/m and a density as low as 2.782 g/cm3, together with excellent mechanical properties including flexural strength, Vickers hardness (HV), and fracture toughness (KIC) of 676 MPa, 28.89 GPa, and 5.28 MPa·m1/2, respectively.

Background & Aims: Liver ischemia-reperfusion (IR) injury represents a major risk factor in both partial hepatectomy and liver transplantation. Nerve injury–induced protein 1 (Ninj1) is widely recognized as an adhesion molecule in leukocyte trafficking under inflammatory conditions, but its role in regulating sterile inflammation during liver IR injury remains unclear. Methods: Myeloid Ninj1-deficient mice were generated by bone marrow chimeric models using Ninj1 knockout mice and wild-type mice. In vivo, a liver partial warm ischemia model was applied. Liver injury and hepatic inflammation were investigated. In vitro, primary Kupffer cells (KCs) isolated from Ninj1 knockout and wild-type mice were used to explore the function and mechanism of Ninj1 in modulating KC inflammation upon lipopolysaccharide stimulation. Results: Ninj1 deficiency in KCs protected mice against liver IR injury during the later phase of reperfusion, especially in neutrophil infiltration, intrahepatic inflammation, and hepatocyte apoptosis. This prompted ischemia-primed KCs to decrease proinflammatory cytokine production. In vitro and in vivo, using small-interfering RNA against dual-specificity phosphatase 1 (DUSP1), we found that Ninj1 deficiency diminished the inflammatory response in KCs and neutrophil infiltration through DUSP1-dependent deactivation of the c-Jun-N-terminal kinase and p38 pathways. Sivelestat, a neutrophil elastase inhibitor, functioned similarly to Ninj1 deficiency, resulting in both mitigated hepatic IR injury in mice and a more rapid recovery of liver function in patients undergoing liver resection. Conclusions: The Ninj1/Dusp1 axis contributes to liver IR injury by regulating the proinflammatory response of KCs, and influences neutrophil infiltration, partly by subsequent regulation of C-X-C motif chemokine ligand 1 (CXCL1) production after IR.

Mobile Low-Duty-Cycle Wireless Sensor Network (MLDC-WSN) is a new type of wireless multi-hop network composed of sensor nodes that have mobility and sleep for a long time in a wireless self-organizing manner. Neighbor discovery protocols are used for sensor nodes to discover neighbor nodes within their communication range and can provide neighbor information to other protocols. MLDC-WSN uses low duty cycle technology to reduce energy consumption, and captures dynamic environmental information through the movement of nodes. However, the random mobility and long dormancy of nodes lead to frequent changes in the network topology, and nodes need to consume a lot of energy and time to discover all their neighbors. The sensor nodes are often powered by energy-limited batteries, and battery replacement is difficult. How to implement efficient neighbor discovery with low-latency and low-energy is a challenge of current research. Different from the previous slot model that couples the listening and transmitting of beacons in one slot, this paper proposes a new discovery schedule based on the slot model that separates the listening and transmitting of beacons. The discovery schedule can guarantee unidirectional discovery. And the node proactively transmits the beacon to accelerate bidirectional discovery after unilaterally discovering its neighbor nodes. On this basis, a proactive asynchronous neighbor discovery protocol called Fedab is proposed in this paper. Ignoring beacon collisions and other realistic interference factors, Fedab can enable neighbor discovery within the theoretical worst-case discovery latency. Moreover, Fedab is extended to the scenario where nodes perform different duty cycles, i.e., asymmetric scenarios. After experimental simulations and numerical analysis, the Fedab protocol has better performance compared to other existing neighbor discovery protocols.

This work reports the formation of nanoflowers after annealing of Au/Ni bilayers deposited on SiO2/Si substrates. The cores of the nanoflowers consist of segregated Ni silicide and Au parts and are surrounded by SiOx branches. The SiO2 decomposition is activated at 1050 °C in a reducing atmosphere, and it can be enhanced more by Au compared to Ni. SiO gas from the decomposition of SiO2 and the active oxidation of Si is the source of Si for the growth of the SiOx branches of the nanoflowers. The concentration of SiO gas around the decomposition cavities is inhomogeneously distributed. Closer to the cavity border, the concentration of the Si sources is higher, and SiOx branches grow faster. Hence, nanoflowers present shorter and shorter branches as they are getting away from the border. However, such inhomogeneous SiO gas concentration is weakened in the sample with the highest Au concentration due to the strong ability of Au to enhance SiO2 decomposition, and nanoflowers with less difference in their branches can be observed across the whole sample.

Abstract Objective To observe the clinical features and efficacy of immunosuppressive therapy in patients with primary Sjögren's syndrome (PSS) combined with peripheral neuropathy (PN) syndrome and to explore the risk factors for PN in patients with PSS. Methods Sixty consecutive patients with PSS admitted to the Department of Rheumatology and Immunology, Wuhan No. 1 Hospital, from January 2014 to June 2020 were analysed retrospectively. Patients were divided into a PN group (N = 15) and a non-PN group (N = 45). The clinical characteristics of the two groups were compared, and the independent risk factors for PN combined with PSS were analysed by multivariate logistic regression. The patients with PSS combined with PN were followed up to observe the effect of immunosuppressive therapy. Results The patients with PN had a longer course of disease than those without PN (z = − 3.225, P = 0.001), and the incidence of Raynaud's phenomenon, anti-SSB antibody, rheumatoid factor and hyperglobulinaemia was higher (all P

Abstract Temperature has an important influence on plant growth and development. In protected agriculture production, accurate prediction of temperature environment is of great significance. However, due to the time series, nonlinear and multi coupling characteristics of temperature, it is difficult to achieve accurate prediction. We proposed a method for building a solar greenhouse temperature prediction model based on a timeseries analysis, that considers the time series characteristics and dynamic temperature changes in the greenhouse system. The method would predict the temperature of greenhouse, and provide reference for the temperature change law in protected agriculture. A parameter analysis was performed on the nonlinear autoregressive exogenous (NARX) neural network, and a solar greenhouse temperature time series prediction model was established using the NARX regression neural network. The results showed that the proposed model depicted a maximum absolute error of 0.67 °C, and model correlation coefficient of 0.9996. Compared with the wavelet and BP neural networks, the NARX regression neural network accurately predicted and significantly outperformed in the solar greenhouse temperature prediction model. Moreover, the prediction model can accurately predict temperature trends within the solar greenhouse and is pivotal to obtaining precise control of solar greenhouse temperature.

Abstract To compare the clinical efficacy of an innovative modified single-incision technique without special extraperitoneal PORT with that of transperitoneal multi-incision robot-assisted laparoscopic radical prostatectomy and to explore the feasibility and safety of the former. A retrospective analysis was performed on 259 patients who received robot-assisted laparoscopic radical prostatectomy in the Robot Minimally Invasive Center of Sichuan Provincial People's Hospital between September 2018 and August 2021. Among them were 147 cases involving extraperitoneal single incision with no special PORT (Group A) and 112 cases involving multiple incisions by the transperitoneal method (Group B). Differences in age, PSA level, Gleason score, prostate volume, body mass index, clinical stage, lower abdominal operation history, and lymph node dissection ratio between the two groups were not statistically significant (P > 0.05). All operations were performed by the same operator. In this study, all 259 operations were completed successfully, and there was no conversion. There was no significant difference in transperitoneal blood loss, postoperative hospital stay, positive rate of incision margin, indwelling time of urinary catheter, satisfaction rate of immediate urine control, satisfaction rate of urine control 3 months after operation, positive rate of postoperative lymph node pathology or postoperative pathological stage between the two groups (P > 0.05). There were significant differences in operation time, postoperative exhaust time and incision length (P

Abstract Background With the gradual increase of residents’ income and the continuous improvement of medical security system, people’s demand for pursuing higher quality and better medical and health services has been released. However, so far little research has been published on China's high quality medical resources (HQMR). This study aims to understand the spatiotemporal variation trend of HQMR from 2006 to 2020, analyze regional disparity of HQMR in 2020, and further explore the main factors influencing the distribution of HQMR in China. Methods The study selected Class III level A hospitals (the highest level medical institutions in China) to represent HQMR. Descriptive statistical methods were used to address the changes in the distribution of HQMR from 2006 to 2020. Lorentz curve, Gini coefficient (G), Theil index (T) and High-quality health resource density index (HHRDI) were used to calculate the degree of inequity. The geographical detector method was used to reveal the key factors influencing the distribution of HQMR. Results The total amount of HQMR in China had increased year by year, from 647 Class III level A hospitals in 2006 to 1580 in 2020. In 2020, G for HQMR by population was 0.166, while by geographic area was 0.614. T was consistent with the results for G, and intra-regional contribution rates were higher than inter-regional contribution rates. HHRDI showed that Beijing, Shanghai, and Tianjin had the highest allocated amounts of HQMR. The results of the geographical detector showed that total health costs, government health expenditure, size of resident populations, GDP, number of medical colleges had a significant impact on the spatial distribution of HQMR and the q values were 0.813, 0.781, 0.719, 0.661, 0.492 respectively. There was an interaction between the influencing factors. Conclusions China's total HQMR is growing rapidly but is relatively inadequate. The distribution of HQMR by population is better than by geography, and the distribution by geography is less equitable. Population size and geographical area both need to be taken into account when formulating policies, rather than simply increasing the number of HQMR.

T7 RNA polymerase (RNAP) is widely used for synthesizing RNA molecules with synthetic modifications and unnatural base pairs (UBPs). Here, authors show the structural basis of how UBPs are recognized as template and substrate, providing mechanistic insights into UBP transcription by T7 RNAP.

Abstract Background The microbiome of the Sinai Desert farming system plays an important role in the adaptive strategy of growing crops in a harsh, poly-extreme, desert environment. However, the diversity and function of microbial communities under this unfavorable moisture and nutritional conditions have not yet been investigated. Based on culturomic and metagenomic methods, we analyzed the microbial diversity and function of a total of fourteen rhizosphere soil samples (collected from twelve plants in four farms of the Sinai desert), which may provide a valuable and meaningful guidance for the design of microbial inoculants. Results The results revealed a wide range of microbial taxa, including a high proportion of novel undescribed lineages. The composition of the rhizosphere microbial communities differed according to the sampling sites, despite similarities or differences in floristics. Whereas, the functional features of rhizosphere microbiomes were significantly similar in different sampling sites, although the microbial communities and the plant hosts themselves were different. Importantly, microorganisms involved in ecosystem functions are different between the sampling sites, for example nitrogen fixation was prevalent in all sample sites while microorganisms responsible for this process were different. Conclusion Here, we provide the first characterization of microbial communities and functions of rhizosphere soil from the Sinai desert farming systems and highlight its unexpectedly high diversity. This study provides evidence that the key microorganisms involved in ecosystem functions are different between sampling sites with different environment conditions, emphasizing the importance of the functional microbiomes of rhizosphere microbial communities. Furthermore, we suggest that microbial inoculants to be used in future agricultural production should select microorganisms that can be involved in plant-microorganism interactions and are already adapted to a similar environmental setting.