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Abstract Background Our previous genome‑wide association studies (GWAS) have suggested rs912304 in 14q12 as a suggestive risk variant for type 1 diabetes (T1D). However, the association between this risk region and T1D subgroups and related clinical risk features, the underlying causal functional variant(s), putative candidate gene(s), and related mechanisms are yet to be elucidated. Methods We assessed the association between variant rs912304 and T1D, as well as islet autoimmunity and islet function, stratified by the diagnosed age of 12. We used epigenome bioinformatics analyses, dual luciferase reporter assays, and expression quantitative trait loci (eQTL) analyses to prioritize the most likely functional variant and potential causal gene. We also performed functional experiments to evaluate the role of the causal gene on islet function and its related mechanisms. Results We identified rs912304 as a risk variant for T1D subgroups with diagnosed age ≥ 12 but not

Abstract Background This study aimed to investigate the knowledge, attitudes, and practices (KAP) toward cardiovascular complications among end-stage renal disease patients undergoing maintenance hemodialysis. Methods This web-based cross-sectional study was conducted at Guangdong Provincial People’s Hospital between December 2022, and May 2023. Results A total of 545 valid questionnaires were collected, with an average age of 57.72 ± 13.47 years. The mean knowledge, attitudes and practices scores were 8.17 ± 2.9 (possible range: 0–24), 37.63 ± 3.80 (possible range: 10–50), 33.07 ± 6.10 (possible range: 10–50) respectively. Multivariate logistic regression analysis showed that patients from non-urban area had lower knowledge compared to those from urban area (odds ratio (OR) = 0.411, 95% CI: 0.262–0.644, P

Introduction: Refractory lupus nephritis (LN) causes kidney disease progression and increases the risk of loss of renal function. Due to the high specificity and few side effects of biological agents, they are recommended for the treatment of systemic lupus erythematosus. There are few data on telitacicept for the treatment of refractory LN. Case Presentation: Here, we report the efficacy and safety of telitacicept in the treatment of refractory LN in a 25-year-old female patient. This patient with refractory lupus developed Pneumocystis jirovecii pneumonia while using multitargeted therapy, and the patient’s urine protein was rapidly relieved after telitacicept combination with low-dose mycophenolate mofetil (MMF). Conclusion: This result suggests that telitacicept has a positive effect on refractory LN with no significant side effects. Further reports and a registry are necessary to confirm that telitacicept with low-dose MMF should be preferred in refractory LN.

Abstract As testicular mesenchymal stromal cells, stem Leydig cells (SLCs) show great promise in the treatment of male hypogonadism. The therapeutic functions of mesenchymal stromal cells are largely determined by their reciprocal regulation by immune responses. However, the immunoregulatory properties of SLCs remain unclear. Here, we observe that SLCs transplantation restore male fertility and testosterone production in an ischemia‒reperfusion injury mouse model. SLCs prevent inflammatory cascades through mitochondrial transfer to macrophages. Reactive oxygen species (ROS) released from activated macrophages inducing mitochondrial transfer from SLCs to macrophages in a transient receptor potential cation channel subfamily member 7 (TRPM7)-mediated manner. Notably, knockdown of TRPM7 in transplanted SLCs compromised therapeutic outcomes in both testicular ischemia‒reperfusion and testicular aging mouse models. These findings reveal a new mechanism of SLCs transplantation that may contribute to preserve testis function in male patients with hypogonadism related to immune disorders.

Sea surface temperature (SST) is one of the most important parameters in the global ocean–atmosphere system, and its long-term changes will have a significant impact on global climate and ecosystems. Accurate prediction of SST, therefore, especially the improvement of long-term predictive skills is of great significance for fishery farming, marine ecological protection, and planning of maritime activities. Since the effective and precise description of the long-range dependence between input and output requires higher model prediction ability, it is an extremely challenging task to achieve accurate long-term prediction of SST. Inspired by the successful application of the transformer and its variants in natural language processing similar to time-series prediction, we introduce it to the SST prediction in the China Sea. The model Transformer with temporal embedding, attention Distilling, and Stacked connection in Part (TransDtSt-Part) is developed by embedding the temporal information in the classic transformer, combining attention distillation and partial stacked connection, and performing generative decoding. High-resolution satellite-derived data from the National Oceanic and Atmospheric Administration is utilized, and long-term SST predictions with day granularity are achieved under univariate and multivariate patterns. With root mean square error and mean absolute error as metrics, the TransDtSt-Part outperforms all competitive baselines in five oceans (i.e., subareas of Bohai, Yellow Sea, East China Sea, Taiwan Strait, and South China Sea) and six prediction horizons (i.e., 30, 60, 90, 180, 270, and 360 days). Experimental results demonstrate that the performance of the innovative model is encouraging and promising for the long-term prediction of SST.

Abstract The definition of scaled p‐norm and its properties are given here. Compared with the norm‐normalized sign function, using scaled p‐norm in the controller design can not only achieve the time‐synchronized stability of non‐linear dynamic systems, but also improve the convergence rate of the system. Besides, the scaled p‐norm is applied to design the consensus protocol for multi‐agent systems, which enables the states of all agents to achieve fast time‐synchronized consensus. The simulation results demonstrate the superiority of this method in improving the convergence rate of the system.

In the evolving field of Intelligent Transportation Systems (ITSs), accurate and reliable traffic prediction is essential in enhancing management and planning capabilities. Accurately predicting traffic conditions over both short-term and long-term intervals is vital for the practical application of ITS. The integration of deep learning into traffic prediction has proven crucial in advancing traffic prediction beyond traditional approaches, particularly in analyzing and forecasting complex traffic scenarios. Despite these advancements, the existing methods are unable to effectively handle both short-term and long-term traffic patterns given their complex nature, revealing a need for more comprehensive forecasting solutions. To address this need, we propose a new approach named the Short-Term and Long-Term Integrated Transformer (SLIT). SLIT is a Transformer-based encoder–decoder architecture, designed for the effective prediction of both short-term and long-term travel time durations. The architecture integrates the Enhanced Data Preprocessing (EDP) with the Short-Term and Long-Term Integrated Encoder–Decoder (SLIED). This harmonious combination enables SLIT to effectively capture the complexities of traffic data over varying time horizons. Extensive evaluations on a large-scale real-world traffic dataset demonstrate the excellence of SLIT compared with existing competitive methods in both short- and long-term travel time predictions across various metrics. SLIT exhibits significant improvements in prediction results, particularly in short-term forecasting. Remarkable improvements are observed in SLIT, with enhancements of up to 9.67% in terms of all evaluation metrics across various time horizons. Furthermore, SLIT demonstrates the capability to analyze traffic patterns across various road complexities, proving its adaptability and effectiveness in diverse traffic scenarios with improvements of up to 10.83% in different road conditions. The results of this study highlight the high potential of SLIT in significantly enhancing traffic prediction within ITS.

Abstract Achalasia is a rare motility disorder of the esophagus caused by the gradual degeneration of myenteric neurons. Immune-mediated ganglionitis has been proposed to underlie the loss of myenteric neurons. Here, we measure the immune cell transcriptional profile of paired lower esophageal sphincter (LES) tissue and blood samples in achalasia and controls using single-cell RNA sequencing (scRNA-seq). In achalasia, we identify a pattern of expanded immune cells and a specific transcriptional phenotype, especially in LES tissue. We show C1QC+ macrophages and tissue-resident memory T cells (TRM), especially ZNF683+ CD8+ TRM and XCL1+ CD4+ TRM, are significantly expanded and localized surrounding the myenteric plexus in the LES tissue of achalasia. C1QC+ macrophages are transcriptionally similar to microglia of the central nervous system and have a neurodegenerative dysfunctional phenotype in achalasia. TRM also expresses transcripts of dysregulated immune responses in achalasia. Moreover, inflammation increases with disease progression since immune cells are more activated in type I compared with type II achalasia. Thus, we profile the immune cell transcriptional landscape and identify C1QC+ macrophages and TRM as disease-associated immune cell subsets in achalasia.

Aim:This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）.Background: Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery.Methods: A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined.Results: Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1–19.1), compared to those who did achieve breast pCR, P

PurposeThis aims to investigate the efficacy and safety of intercostal nerve anastomosis among breast cancer patients who undergo immediate subpectoral prosthetic breast reconstruction after nipple–areola-sparing mastectomy.MethodsFrom 2022 to 2023, female patients between the ages of 20 and 60 diagnosed with stage I–IIIA breast cancer, who required and were willing to undergo immediate subpectoral prosthetic breast reconstruction after nipple–areola-sparing mastectomy, were screened and assigned to take the operation with (treatment group) or without (control group) intercostal nerve anastomosis (the nerves with appropriate length and thickness were selected from the 2nd-4th intercostal nerves, which were then dissociated and anastomosed to the posterior areola tissue). A radial incision at the surface projection of the tumor location was used. The patients’ breast local sensation was assessed using Semmes–Weinstein monofilaments before the operation as well as at 10 days, 3 months, and 6 months postoperatively. Furthermore, the patients’ quality of life was evaluated 6 months postoperatively using the EORTC QLQ-C30 questionnaire. Adverse events, operation duration, drainage volume, and the duration of drainage tube carrying time were also monitored and recorded.ResultsCompared to the pre-operative period, a significant decrease in local sensation was observed 10 days after surgery in both groups. However, the control group showed a significant reduction in sensation at 3 and 6 months postoperatively, while the treatment group showed noticeable recovery. A statistically significant difference (P < 0.001) in local sensation between the pre-operative and post-operative periods was observed at the final follow-up in the two groups. By the time of 3 and 6 months postoperatively, a significant difference was seen in the local sensation between the two groups. Intercostal nerve anastomosis was found to significantly improve the patients’ quality of life, including emotional (P = 0.01), physical (P = 0.04), and social functioning (P = 0.02) and pain (P = 0.04). There were no significant differences in general characteristics (such as age, BMI, and subtypes). Although intercostal nerve anastomosis increased the duration of operation by around 20 min (P < 0.001), it did not affect the volume or duration of postoperative drainage tube usage between the two groups.ConclusionThis study indicated that intercostal nerve anastomosis improved the local sensation and quality of life of patients who underwent immediate subpectoral prosthetic breast reconstruction after nipple–areola-sparing mastectomy.Clinical Trial Registrationhttps://www.chictr.org.cn/showproj.html?proj=42487, identifier ChiCTR1900026340.

Disinfection by-products (DBPs), including trihalomethanes (THMs) and haloacetic acids (HAAs), have attracted attention due to their carcinogenic properties, leading to varying conclusions. This meta-analysis aimed to evaluate the dose-response relationship and the dose-dependent effect of DBPs on cancer risk. We performed a selective search in PubMed, Web of Science, and Embase databases for articles published up to September 15th, 2023. Our meta-analysis eventually included 25 articles, encompassing 8 cohort studies with 6038,525 participants and 10,668 cases, and 17 case-control studies with 10,847 cases and 20,702 controls. We observed a positive correlation between increased cancer risk and higher concentrations of total trihalomethanes (TTHM) in water, longer exposure durations, and higher cumulative TTHM intake. These associations showed a linear trend, with relative risks (RRs) and 95 % confidence intervals (CIs) being 1.02 (1.01–1.03), 1.04 (1.02–1.06), and 1.02 (1.00–1.03), respectively. Gender-specific analyses revealed slightly U-shaped relationships in both males and females, with males exhibiting higher risks. The threshold dose for TTHM in relation to cancer risk was determined to be 55 µg/L for females and 40 µg/L for males. A linear association was also identified between bladder cancer risk and TTHM exposure, with an RR and 95 % CI of 1.08 (1.05–1.11). Positive linear associations were observed between cancer risk and exposure to chloroform, bromodichloromethane (BDCM), and HAA5, with RRs and 95 % CIs of 1.02 (1.01–1.03), 1.33 (1.18–1.50), and 1.07 (1.03–1.12), respectively. Positive dose-dependent effects were noted for brominated THMs above 35 µg/L and chloroform above 75 µg/L. While heterogeneity was observed in the studies for quantitative synthesis, no publication bias was detected. Exposure to TTHM, chloroform, BDCM, or HAA5 may contribute to carcinogenesis, and the risk of cancer appears to be dose-dependent on DBP exposure levels. A cumulative effect is suggested by the positive correlation between TTHM exposure and cancer risk. Bladder cancer and endocrine-related cancers show dose-dependent and positive associations with TTHM exposure. Males may be more susceptible to TTHM compared to females.

Abstract The inconsistent response curve of delicate micro/nanofiber (MNF) sensors during cycling measurement is one of the main factors which greatly limit their practical application. In this paper, we proposed a temperature sensor based on the copper rod-supported helical microfiber (HMF). The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements. Two neural networks, the deep belief network (DBN) and the backpropagation neural network (BPNN), were employed respectively to predict the temperature of the HMF sensor in different sensing processes. The input variables of the network were the sensor geometric parameters (the microfiber diameter, wrapped length, coiled turns, and helical angle) and the output optical intensity under different working processes. The root mean square error (RMSE) and Pearson correlation coefficient (R) were used to evaluate the predictive ability of the networks. The DBN with two restricted Boltzmann machines (RBMs) provided the best temperature prediction results (RMSE and R of the heating process are 0.9705 °C and 0.9969, while the values of RMSE and R of the cooling process are 0.786 6 °C and 0.997 7, respectively). The prediction results obtained by the optimal BPNN (five hidden layers, 10 neurons in each layer, RMSE=1.126 6 °C, R=0.995 7) were slightly inferior to those obtained by the DBN. The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation, which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.

Abstract Virtual Shack-Hartmann wavefront sensing (vSHWS) has some significant advantages and is promising for aberration measurement in the field of biomedical optical imaging. The illumination sources used in vSHWS are almost broadband, but are treated as monochromatic sources (only using center wavelength) in current data processing, which may cause errors. This work proposed a data processing method to take into account the multiple wavelengths of the broadband spectrum, named multiple-wavelength centroid-weighting method. Its feasibility was demonstrated through a series of simulations. A wavefront generated with a set of statistical human ocular aberrations was used as the target wavefront to evaluate the performance of the proposed and current methods. The results showed that their performance was very close when used for the symmetrical, but the wavefront error of the proposed method was much smaller than that of the current method when used for the asymmetrical spectrum, especially for the broader spectrum. These results were also validated by using 20 sets of clinical human ocular aberrations including normal and diseased eyes. The proposed method and the obtained conclusions have important implications for the application of vSHWS.

Au nanoparticles (NPs) were designed to be embedded into III-V semiconductors to form Au/GaAs Schottky heterostructures, which were used as top-modified cover layers for quantum dot semiconductor saturable absorption mirrors (QD-SESAMs). By harnessing the distinctive localized surface plasmon resonance (LSPR) effect exhibited by Au NPs, a remarkable enhancement in photogenerated carrier concentration is achieved at the heterojunction interface. Consequently, this leads to a significant improvement in the nonlinear optical characteristics of the device. The modulation depth (MD) and saturation fluence of the device are optimized from the initial 2.2% and 16.1 MW/cm2 to 2.8% and 8.3 MW/cm2, respectively. Based on the optimized device, a Q-switched laser has been developed with an impressive output power of 17.61 mW and a single pulse energy of 274.9 nJ. These results unequivocally showcase the exceptional advantages offered by utilizing Au NPs to optimize the nonlinear optical characteristics of III-V semiconductor devices, thereby highlighting its immense potential for practical applications in various fields.

Bisphenol A (BPA), an endocrine disruptor widely used in industrial production, is found in various environmental sources. Despite numerous reports on BPA degradation and removal, the details remain unclear. This paper aims to address this gap by providing a comprehensive review of BPA degradation methods, focusing on biological, physical, and chemical treatments and the factors that affect the degradation of BPA. Firstly, the paper uses VOSviewer software (version 1.6.15) to map out the literature on BPA degradation published in the past 20 years, which reveals the trends and research focus in this field. Next, the advantages and limitations of different BPA degradation methods are discussed. Overall, this review highlights the importance of BPA degradation to protect the environment and human health. The paper provides significant insights for researchers and policymakers to develop better approaches for BPA degradation and removal.

Abstract Free-spectral-range (FSR)-free optical filters have always been a critical challenge for photonic integrated circuits. A high-performance FSR-free filter is highly desired for communication, spectroscopy, and sensing applications. Despite significant progress in integrated optical filters, the FSR-free filter with a tunable narrow-band, high out-of-band rejection, and large fabrication tolerance has rarely been demonstrated. In this paper, we propose an exact and robust design method for add-drop filters (ADFs) with an FSR-free operation capability, a sub-nanometer optical bandwidth, and a high out-of-band rejection (OBR) ratio. The achieved filter has a 3-dB bandwidth of

Polystyrene (PS) possesses numerous remarkable properties like high transparency, impressive mechanical strength, and a large specific surface area, making it an excellent mask plate or template for the preparation of anti-opal structures. Moreover, it should be noted that PS also exhibits exceptional nonlinear properties due to the subwavelength periodic configuration. In this paper, a self-assembled PS microsphere photonic crystal saturable absorber (PSM-SA) has been proposed and fabricated. It exhibits impressive properties including high stability, high damage threshold, high refractive index, and large specific surface area. It is suggested that the periodic structure of PS in the film has a significant impact on the photonic band gap, resulting in excellent adjustable optical nonlinear characteristics. By integrating PSM-SA into a self-built ring fiber laser system, a Q-switched laser with a pulse width of approximately 2 μs and a repetition rate of 40 kHz at a wavelength of 1562 nm is obtained. These findings demonstrate its potential for enabling efficient and adjustable nonlinear optical functionalities in various optical devices, contributing to the expanding realm of PS microsphere photonic crystals and their significant impact on advancing nonlinear optics technology.

Background: Increased leisure-time physical activity (LTPA) is linked with decreased mortality risk, while also with increased left ventricular mass, which may induce left ventricular hypertrophy (LVH). We investigated whether LVH modifies the association between higher LTPA and lower mortality risk in population at high cardiovascular risk. Methods: In a prospective national cohort, we used the left ventricular mass/body surface area (LVM/BSA) method to define LVH. Baseline LTPA was self-reported and divided into: low (

The Au ion implantation process has emerged as an effective and simple method to be utilized for the fabrication of opto-electronic materials and devices due to numerous fascinating features of Au nanoparticles such as surface plasmon resonance (SPR), large third-order nonlinearity and a fast response time. In this paper, we describe the fabrication of a novel Au nanoparticle saturable absorber (Au NP-SA) by embedding the Au NPs into a SiO2 thin film using the ion implantation process, which shows excellent saturable absorption features due to the localized surface plasmon resonance (LSPR) effect of Au NPs. A stable and high-quality pulsed laser with a repetition rate of 33.3 kHz and a single pulse energy of 11.7 nJ was successfully constructed with the Au NP-SA. Both the stable operation characteristic of the obtained Q-switched pulsed laser and the high repeatability of the fabrication process of the Au NP-SA were demonstrated. In addition, the simple feasibility and maturity of the ion implantation process allow for the plasmonic nanoparticles to be easily integrated into other types of opto-electronic materials and devices to further improve their performance, and shows immense potential for the production of wafer-level products.

Gene-gating of a MYC oncogenic super-enhancer (OSE) increases its expression in colon cancer cells in a poorly understood process. Here the authors show that MYC gating requires a CTCF binding site (CTCFBS) within the OSE that directs the stepwise trafficking of the OSE to the nuclear pore to facilitate increased nuclear export of MYC mRNA, which results in a growth advantage.

We developed a new computational method, Single-Cell Entropy Network (SCEN) to analyze single-cell RNA-seq data, which used the information of gene-gene associations to discover new heterogeneity of immune cells as well as identify existing cell types. Based on SCEN, we defined association-entropy (AE) for each cell and each gene through single-cell gene co-expression networks to measure the strength of association between each gene and all other genes at a single-cell resolution. Analyses of public datasets indicated that the AE of ribosomal protein genes (RP genes) varied greatly even in the same cell type of immune cells and the average AE of RP genes of immune cells in each person was significantly associated with the healthy/disease state of this person. Based on existing research and theory, we inferred that the AE of RP genes represented the heterogeneity of ribosomes and reflected the activity of immune cells. We believe SCEN can provide more biological insights into the heterogeneity and diversity of immune cells, especially the change of immune cells in the diseases.

To figure out the energy attenuation of micro/nanofibers (MNFs) more flexibly and conveniently, a backpropagation neural network (BPNN) is proposed to forecast the output intensity of rhodamine B (RhB) doped polymer microfibers (PMFs). According to the diameter, doping concentration, and propagation distance (L), we realize the L-dependence of output energy predictions for the excitation light (IE) and fluorescence (IF) of the doped PMFs. Hundreds of propagation distance-intensity data pairs acquired from dozens of RhB doped PMFs are used for the BPNN training. The prediction ability of the model is evaluated by the root-mean-square error (RMSE), the mean absolute percentage error (MAPE), and R2. The output intensity prediction performance of BPNN is compared with the traditional exponential-fitting (EF) method. The prediction results indicate that the two-hidden-layer network with one and seventeen neurons respectively provides the best performance. After training, BPNN gives a good intensity prediction for both the IE (RMSE = 3.16×10−2, MAPE = 7.3%, and R2 = 0.9802) and the IF (RMSE = 0.91×10−2, MAPE = 0.89%, and R2 = 0.9696) from the output end of the PMF with different diameters and doping concentrations. The energy losses of the two kinds of light from different doped PMFs are also calculated based on the predicted values, which are similar to the ones obtained from the EF method. The approach based on the BPNN prediction for the energy attenuation of the PMFs shows superiority in flexibility and applicability toward the traditional methods, which could promote the optimal design of the MNF devices and the practical application.

Quantum measurements can produce unpredictable randomness arising from the uncertainty principle. When measuring a state with von Neumann measurements, the intrinsic randomness can be quantified by the quantum coherence of the state on the measurement basis. Unlike projection measurements, there are additional and possibly hidden degrees of freedom in an apparatus for generic measurements. We propose an adversary scenario to characterize the intrinsic randomness of general measurements with arbitrary input states. Interestingly, we discover that certain measurements, including symmetric and information-complete ones, generate nonzero randomness for all states, which suggests a new approach for designing source-independent random number generators without state characterization. Furthermore, our results reveal that intrinsic randomness can quantify coherence under general measurements, which generalizes the result in the standard resource theory of state coherence.

ObjectiveThis study aimed to investigate the prognostic roles of marital status in patients with invasive breast cancer. Method: We extracted the data of patients with invasive breast cancer who were diagnosed during 2010–2015 and had complete staging and molecular typing from the Surveillance, Epidemiology, and End Results (SEER)-18 database. Kaplan–Meier curve method and Cox regression analysis were performed to investigate the differences in breast cancer–specific survival (BCSS) and overall survival (OS) in the total population and various subgroups with different marital statuses.ResultsAmong the 324,062 patients with breast cancer in this study, 55.0%, 40.0%, and 5.0% were married, unmarried, and unknown, respectively; 51.8%, 32.2%, 10.5%, and 5.5% were patients with Stages I, II, III, and IV breast cancer, respectively. The 5-year BCSS and OS of married patients were 92.6% and 88.1%, respectively, higher than those of unmarried patients (88.3% and 78.1%, P < 0.001). After adjustment for sex, age, T and N stages, histological grade, insurance status, race, year of diagnosis, and molecular subtypes, married status was an independent predictor of better BCSS [hazard ratio (HR) = 0.775, 95% confidence interval (CI) = 0.753–0.797, P < 0.001) and OS (HR = 0.667, 95% CI = 0.653–0.681, P < 0.001). After multivariate analysis of various subgroups of sex, age, stage, histological grade, insurance status, race, and molecular subtype, married status was an independent predictor of better BCSS in all subgroups except for Grade IV, age < 35 years, and uninsured subgroups. Marital status was an independent predictor of better OS in all subgroups except the subgroup with age

ObjectiveThis study aims to reveal the association between JAZF1 rs864745 A>G variant and type 2 diabetes (T2D), type 1 diabetes (T1D) risk, and their correlation with clinical features, including islet function, islet autoimmunity, and plasma lipid levels.MethodsWe included 2505 healthy controls based on oral glucose tolerance test (OGTT), 1736 unrelated T2D, and 1003 unrelated autoantibody-positive T1D individuals. Binary logistic regression was performed to evaluate the relationships between rs864745 in JAZF1 and T2D, T1D, and islet-specific autoantibody status under the additive model, while multiple linear regression was used to assess its effect on glycemic-related quantitative traits and plasma lipid levels.ResultsWe did not find any association between rs864745 in JAZF1 and T2D, T1D, or their subgroups (All P > 0.05). For glycemic traits, we found that the G allele of this variant was significantly associated with higher 120 min insulin level, insulinogenic index (IGI), corrected insulin response (CIR), and acute insulin response (BIGTT-AIR) (P = 0.033, 0.006, 0.009, and 0.016, respectively) in healthy individuals. Similar associations were observed in newly diagnosed T2D but not T1D individuals. Although this variant had no impact on islet autoimmunity (All P > 0.05), significant associations with plasma total cholesterol (TC) and low-density lipoprotein (LDL) level stratified by JAZF1 rs864745 variant were observed in the disease status of T2D (P = 0.002 and 0.003) and T1D (P = 0.024 and 0.009), with significant heterogeneity to healthy individuals.ConclusionsThe common JAZF1 rs864745 variant contributes to islet function and lipid metabolism, which might be put into genetic risk scores to assess the risk of related clinical features.

Abstract Background Acetylcholine (ACh) and norepinephrine (NE) are representative neurotransmitters of parasympathetic and sympathetic nerves, respectively, that antagonize each other to coregulate internal body functions. This also includes the control of different kinds of hormone secretion from pancreatic islets. However, the molecular mechanisms have not been fully elucidated, and whether innervation in islets is abnormal in diabetes mellitus also remains unclear. Methods and results Immunofluorescence colocalization and islet perfusion were performed and the results demonstrated that ACh/NE and their receptors were highly expressed in islet and rapidly regulated different hormones secretion. Phosphorylation is considered an important posttranslational modification in islet innervation and it was identified by quantitative proteomic and phosphoproteomic analyses in this study. The phosphorylated islet proteins were found involved in many biological and pathological processes, such as synaptic signalling transduction, calcium channel opening and insulin signalling pathway. Then, the kinases were predicted by motif analysis and further screened and verified by kinase‐specific siRNAs in different islet cell lines (αTC1‐6, Min6 and TGP52). After functional verification, Ksr2 and Pkacb were considered the key kinases of ACh and NE in insulin secretion, and Cadps, Mlxipl and Pdcd4 were the substrates of these kinases measured by immunofluorescence co‐staining. Then, the decreased expression of receptors, kinases and substrates of ACh and NE were found in diabetic mice and the aberrant rhythm in insulin secretion could be improved by combined interventions on key receptors (M3 (pilocarpine) or α2a (guanfacine)) and kinases (Ksr2 or Pkacb). Conclusions Abnormal innervation was closely associated with the degree of islet dysfunction in diabetic mice and the aberrant rhythm in insulin secretion could be ameliorated significantly after intervention with key receptors and kinases in the early stage of diabetes mellitus, which may provide a promising therapeutic strategy for diabetes mellitus in the future.

Objective: Insulin resistance is a major risk factor for coronary artery disease (CAD). The C-peptide-to-insulin ratio (C/I) is associated with hepatic insulin clearance and insulin resistance. The current study was designed to establish a novel C/I index (CPIRI) model and provide early risk assessment of CAD. Methods: A total of 865 adults diagnosed with new-onset diabetes mellitus (DM) within one year and 54 healthy controls (HC) were recruited to develop a CPIRI model. The CPIRI model was established with fasting C/I as the independent variable and homeostasis model assessment of insulin resistance (HOMA-IR) as the dependent variable. Associations between the CPIRI model and the severity of CAD events were also assessed in 45 hyperglycemic patients with CAD documented via coronary arteriography (CAG) and whom underwent stress echocardiography (SE) and exercise electrocardiography test (EET). Results: Fasting C-peptide/insulin and HOMA-IR were hyperbolically correlated in DM patients and HC, and log(C/I) and log(HOMA-IR) were linearly and negatively correlated. The respective correlational coefficients were −0.83 (p < 0.001) and −0.76 (p < 0.001). The equations CPIRI(DM) = 670/(C/I)2.24 + 0.25 and CPIRI(HC) = 670/(C/I)2.24 − 1 (F = 1904.39, p < 0.001) were obtained. Patients with insulin resistance exhibited severe coronary artery impairment and myocardial ischemia. In CAD patients there was no significant correlation between insulin resistance and the number of vessels involved. Conclusions: CPIRI can be used to effectively evaluate insulin resistance, and the combination of CPIRI and non-invasive cardiovascular examination is of great clinical value in the assessment of CAD.

The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity. However, compared to bulk RNA sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq) suffers from higher noise and lower coverage, which brings new computational difficulties. Based on statistical independence, cell-specific network (CSN) is able to quantify the overall associations between genes for each cell, yet suffering from a problem of overestimation related to indirect effects. To overcome this problem, we propose the c-CSN method, which can construct the conditional cell-specific network (CCSN) for each cell. c-CSN method can measure the direct associations between genes by eliminating the indirect associations. c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells. Intuitively, each CCSN can be viewed as the transformation from less “reliable” gene expression to more “reliable” gene–gene associations in a cell. Based on CCSN, we further design network flow entropy (NFE) to estimate the differentiation potency of a single cell. A number of scRNA-seq datasets were used to demonstrate the advantages of our approach. 1) One direct association network is generated for one cell. 2) Most existing scRNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices. 3) CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell. c-CSN is publicly available at https://github.com/LinLi-0909/c-CSN.

In this study, oxidized maltodextrins with a high concentration of carboxyl groups were produced using CuSO4 as a catalyst and H2O2 as an eco-friendly oxidant. Infrared spectroscopy, proton-nuclear magnetic resonance spectroscopy, and thermogravimetric analysis were utilized to examine the structure and properties of oxidized maltodextrins. The reaction conditions were optimized in terms of oxidant content, catalyst content, temperature, pH, and reaction time. The prepared oxidized maltodextrin had a carboxyl group content of 105% under the conditions of 200% molar H2O2, 1% molar catalyst, 55 °C, initial pH = 9.7, and 2 h reaction time. In comparison to the commonly used sodium hypochlorite oxidation process, the carboxyl group content was increased by 58%.

Abstract Chronic graft-versus-host disease (cGVHD) is a major cause of mortality and morbidity after allogeneic stem cell transplantation (alloSCT). The individual risk of severe cGVHD remains difficult to predict and may involve CXCR3 ligands. This study investigated the role of single-nucleotide polymorphisms (SNPs) of CXCL4, CXCL9, CXCL10, and CXCL11, and their day +28 serum levels, in cGVHD pathogenesis. Eighteen CXCR3 and CXCL4, CXCL9–11 SNPs as well as peri-transplant CXCL9–11 serum levels were analyzed in 688 patients without (training cohort; n = 287) or with statin-based endothelial protection cohort (n = 401). Clinical outcomes were correlated to serum levels and SNP status. Significant polymorphisms were further analyzed by luciferase reporter assays. Findings were validated in an independent cohort (n = 202). A combined genetic risk comprising four CXCR3 ligand SNPs was significantly associated with increased risk of severe cGVHD in both training cohort (hazard ratio (HR) 2.48, 95% confidence interval (CI) 1.33–4.64, P = 0.004) and validation cohort (HR 2.95, 95% CI 1.56–5.58, P = 0.001). In reporter assays, significantly reduced suppressive effects of calcineurin inhibitors in constructs with variant alleles of rs884304 (P

With the assistance of the evaluation algorithms based on the well-performed backpropagation neural network (BPNN), we quantitatively analyze the importance of the structural parameters of the supported helical microfiber (HMF) temperature sensor. The relative output intensities of HMF sensor at different temperatures are predicted by the BPNN with the HMF’s structural parameters as the input variables. The best-forecasted performance is obtained by the BPNN with one hidden layer of ten neurons. Compared with the actual values, the root-mean-square error (RMSE) and the correlation coefficient of the predicted values are 9.7 $\times \,\,10^{-3}$ dB and 99.84%, respectively. Based on the BPNN with precise prediction, the backward stepwise elimination and the holdback input randomization methods are used to quantitatively discuss the influence of the structural parameters on the output intensity of the HMF. The relative importance from high to low is the helical length (~38%), microfiber diameter (~27%), helical angle (~25%), and cone angle (~10%). The importance of four geometric parameters obtained by the two methods is ranked the same. Quantitative analysis of structural parameters relying on the well-predicted BPNN can give basic information on the structural characteristics of the HMF sensor, which helps to optimize the structure design of the optical sensors based on micro/nanofiber and provides a powerful guarantee for its practical application.

Testicular torsion-detorsion is an ischaemia-reperfusion-induced male gonad injury that may lead to male infertility. Oxidative stress plays an important role in the ischaemia-reperfusion injury. Icariside II (ICA II) prevents oxidative stress and has obvious protective effects on spermatogenic function. The present study was aimed to investigate therapeutic potentials of ICA II on testicular torsion. 72 mice were randomly divided into three groups: sham-operated control group (n = 24), testicular ischemia-reperfusion + saline group (n = 24) and testicular ischemia-reperfusion + icariside II treated group (n = 24). Testicular ischemia-reperfusion was induced by the left testis rotated 360 degrees in a clockwise direction for 30 minutes followed by detorsion, the contralateral testis was removed. ICA II in saline (5 mg/kg/day) was administrated by gavage immediately after detorsion. The results demonstrated that ICA II alleviated testicular damage by mitigating spermatogenic cell injury and improving testosterone production in mouse models of testicular torsion. We revealed that ICA II alleviated oxidative stress and apoptosis in the testes, reduced inflammatory infiltration and accelerated angiogenesis. Briefly, ICA II administration ameliorated testicular damage by improving spermatogenic function and testosterone production, which supports its use as a pharmacological treatment of testicular torsion.

Abstract Background Esophageal cancer (EC) is one of the most common human cancers, with a particularly aggressive behavior and increased incidence worldwide. The aim of this study was to assess the associations of single-nucleotide polymorphisms (SNPs) in IL-1B with the risk of EC in a northwest Chinese Han population. Methods In order to evaluate the correlations between IL-1B polymorphisms and EC risk, an Agena MassARRAY platform was used to determine the genotype of the candidate SNPs among 384 EC patients and 499 controls. The associations between IL-1B variants and EC risk were examined using logistic regression analysis with adjustment for gender and age. Haplotype construction and analysis were performed to detect the potential associations between haplotypes within IL-1B and EC susceptibility. Additionally, bioinformatics databases were used for gene expression analysis and SNP functional prediction. Results A significant relationship was found between IL-1B rs2853550 and an increased risk of EC in the allele model [odds ratio (OR) = 1.38, 95% confidence interval (95% CI): 1.01–1.89, p = 0.041), the codominant model (A/G, OR = 1.63, 95% CI: 1.10–2.42, p = 0.011), and the dominant model (OR = 1.49, 95% CI: 1.02–2.18, p = 0.041). Functional analysis revealed the potential effects of rs2853550, which further reinforced its influence on EC susceptibility. However, there were no statistically significant differences for other SNPs or haplotypes between EC cases and healthy controls. Expression analysis conducted with dataset indicated that the expression level of IL-1B was higher in EC cases than that in normal samples. Conclusions This study demonstrated that rs2853550 in IL-1B might increase EC susceptibility in the Chinese Han population of Northwest China.

Background: Heart failure with preserved ejection fraction (HFpEF) is increasingly recognized as a major global public health burden and lacks effective risk stratification. We aimed to assess a multi-biomarker model in improving risk prediction in HFpEF.Methods: We analyzed 18 biomarkers from the main pathophysiological domains of HF in 380 patients hospitalized for HFpEF from a prospective cohort. The association between these biomarkers and 2-year risk of all-cause death was assessed by Cox proportional hazards model. Support vector machine (SVM), a supervised machine learning method, was used to develop a prediction model of 2-year all-cause and cardiovascular death using a combination of 18 biomarkers and clinical indicators. The improvement of this model was evaluated by c-statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI).Results: The median age of patients was 71-years, and 50.5% were female. Multiple biomarkers independently predicted the 2-year risk of death in Cox regression model, including N-terminal pro B-type brain-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-TnT), growth differentiation factor-15 (GDF-15), tumor necrosis factor-α (TNFα), endoglin, and 3 biomarkers of extracellular matrix turnover [tissue inhibitor of metalloproteinases (TIMP)-1, matrix metalloproteinase (MMP)-2, and MMP-9) (FDR < 0.05). The SVM model effectively predicted the 2-year risk of all-cause death in patients with acute HFpEF in training set (AUC 0.834, 95% CI: 0.771–0.895) and validation set (AUC 0.798, 95% CI: 0.719–0.877). The NRI and IDI indicated that the SVM model significantly improved patient classification compared to the reference model in both sets (p < 0.05).Conclusions: Multiple circulating biomarkers coupled with an appropriate machine-learning method could effectively predict the risk of long-term mortality in patients with acute HFpEF. It is a promising strategy for improving risk stratification in HFpEF.

Owing to its broadband absorption, ultrafast recovery time, and excellent saturable absorption feature, graphene has been recognized as one of the best candidates as a high-performance saturable absorber (SA). However, the low absorption efficiency and reduced modulation depth severely limit the application of graphene-based SA in ultrafast fiber lasers. In this paper, a single-layer graphene saturable absorber mirror (SG-SAM) was coated by a quarter-wave SiO2 passivated layer, and a significantly enhanced modulation depth and reduced saturation intensity were obtained simultaneously compared to the SG-SAM without the SiO2 coating layer. In addition, long-term operational stability was found in the device due to the excellent isolation and protection of the graphene absorption layer from the external environment by the SiO2 layer. The high performance of the SAM was further confirmed by the construction of a ring-cavity EDF laser generating mode-locked pulses with a central wavelength of 1563.7 nm, a repetition rate of 34.17 MHz, and a pulse width of 830 fs.

Infrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. Despite the promising progress of principal component analysis methods, it is still challenging to detect small targets of unknown polarity (bright or dark) with strong edge interference. Using the partial sum of tubal nuclear norm to estimate low-rank background components and weighted l1 norm to estimate sparse components is an effective method for target extraction. In order to suppress the strong edge interference, considering that the uniformity of the target scattering field is significantly higher than that of the background scattering field in the eigenvalue of the structure tensor, a prior weight based on the multidirectional uniformity of structure tensor eigenvalue was proposed and applied to the optimization model. In order to detect targets with unknown polarity, the images with opposite polarity were substituted into the optimization model, respectively, and the sparse-weight similarity is used to judge the polarity of the target. In order to make the method more efficient, the polarity judgment is made in the second iteration, and then, the false iteration will stop. The proposed method is compared with nine advanced baseline methods on 14 datasets and shows significant strong robustness, which is beneficial to engineering applications.

Background: Interleukin-18 (IL-18) is involved in endothelial activation and dysfunction, and in the pathogenesis and severity of acute graft-versus-host disease (aGVHD). Its relevance for patient outcome after allogeneic stem cell transplantation (alloSCT) has not yet been comprehensively addressed. Methods: Pre-transplant serum levels of free IL-18 were retrospectively assessed in a cohort of 589 patients (training cohort). Results were validated in 688 patients allografted in a different centre. The primary endpoint was overall survival (OS). Secondary endpoints included incidences of non-relapse mortality (NRM), relapse, and aGVHD. Findings: In the training cohort, higher pre-transplant levels of free IL-18 were significantly associated with worse OS (hazard ratio [HR] per 1-log2 increase, 1.25, P = 0.008) in multivariable models. This was due to a higher hazard of NRM (HR per 1-log2 increase, 1.39, P = 0.001), rather than relapse. The associations of pre-transplant free IL-18 with higher NRM (HR per 1-log2 increase, 1.24, P = 0.02) and shorter OS (HR per 1-log2 increase, 1.22, P = 0.006) were confirmed in the validation cohort. In both cohorts, the correlations of higher pre-transplant free IL-18 serum levels with increased NRM and worse OS were mainly driven by fatal infectious complications. No associations with incidence of aGVHD were observed. Interpretation: Higher pre-transplant levels of free IL-18 were associated with non-relapse and overall mortality after alloSCT. Our results may provide a rationale for prospective studies evaluating IL-18 status and inhibition of IL-18 activity in patients undergoing allografting. Keywords: Interleukin-18, Allogeneic stem cell transplantation, Outcome, Mortality

Objective: To investigate the association between polymorphisms in PTPN2 (rs1893217 and rs478582) and type 1 diabetes (T1D) risk with different diagnosed age, as well as related clinical characteristics in Chinese Han population. Methods: A total of 2270 Chinese Han individuals (1023 T1D patients and 1247 healthy controls) were genotyped for rs1893217 and rs478582. And 306 newly diagnosed T1D patients were measured for C-peptide levels based on a standard mixed-meal tolerance test. In addition, 40 healthy controls were analyzed for different T cell subsets by multi-color flow cytometry. Results: Neither rs1893217 nor rs478582 showed any association with T1D risk under an additive model. Stratified analysis for T1D diagnosed age revealed that rs1893217, but not rs478582, was significantly associated with T1D patients diagnosed age ≤18 (OR =0.80, 95% CI: 0.67–0.97, p = 0.02). For those diagnosed age >18, neither of them showed any association. We also found that rs1893217 had a higher positive rate of ZnT8A (CC vs. TT carrier, OR = 2.07, 95% CI: 1.07–4.03, p = 0.026) and IA-2A (CT vs. TT carrier, OR = 1.36, 95% CI: 1.02–1.80, p = 0.038). Furthermore, for rs478582, compared with TT, healthy individuals carrying CC/CT carriers had significantly lower frequency and Helios expression of naive Treg subsets (p = 0.049 and 0.048 respectively), but not secreting or activating Treg subsets. In addition, we did not find any association between these two polymorphisms and residual β-cell function in newly diagnosed T1D patients. Conclusions: Our results suggest that rs1893217 may increase the risk of early-onset T1D and affect humoral immunity, while rs478582 may affect Treg subsets.

Because of the superiority in distinguishing the target from the background by learning mechanism, discriminative classifier attracts a great deal of attention in target detection and tracking systems. Generally, a discriminative classifier is learned from the initial image patch. However, the other algorithms, using only one image frame inhibit the performance of the classifier. A novel training strategy of cascade iteration, which is based on the multiple image frames, is used to initialize the discriminative classifier for the purpose of weakening the initialization limitation and improving the algorithms' adaptability and robustness. Furthermore, to cope with the changes in natural images, online learning is usually adopted to enhance the performance of classifiers, but it easily leads to tracking failures, especially in the case of full occlusion. In order to attenuate the influence of full occlusion, a multi-classifiers parallel tracking algorithm is proposed by designing the multi-classifiers and inducing extra constraints. The experiments are performed on the visual tracking benchmark, and the proposed algorithm is more robust while the target is fully occluded. The simulation results show that the proposed algorithm exhibits better performance compared to the state-of-the-art trackers, especially with KCF, TLD, and STRUCK.

Semiconductor superluminescent light-emitting diodes (SLEDs) have emerged as ideal and vital broadband light sources with extensive applications, such as optical fiber-based sensors, biomedical sensing/imaging, wavelength-division multiplexing system testing and optoelectronic systems, etc. Self-assembled quantum dots (SAQDs) are very promising candidates for the realization of broadband SLED due to their intrinsic large inhomogeneous spectral broadening. Introducing excited states (ESs) emission could further increase the spectral bandwidth. However, almost all QD-based SLEDs are limited to the ground state (GS) or GS and first excited state (ES1) emission. In this work, multiple five-QD-layer structures with large dot size inhomogeneous distribution were grown by optimizing the molecular beam epitaxy (MBE) growth conditions. Based on that, with the assistance of a carefully designed mirror-coating process to accurately control the cavity mirror loss of GS and ESs, respectively, a broadband QD-SLED with three simultaneous states of GS, ES1 and second excited-state (ES2) emission has been realized, exhibiting a large spectral width of 91 nm with a small spectral dip of 1.3 dB and a high continuous wave (CW) output power of 40 mW. These results pave the way for a new fabrication technique for high-performance QD-based low-coherent light sources.

It has widely been accepted that food restriction (FR) without malnutrition has multiple health benefits. Various calorie restriction (CR) and intermittent fasting (IF) regimens have recently been reported to exert neuroprotective effects in traumatic brain injury (TBI) through variable mechanisms. However, the evidence connecting CR or IF to neuroprotection in TBI as well as current issues remaining in this research field have yet to be reviewed in literature. The objective of our review was therefore to weigh the evidence that suggests the connection between CR/IF with recovery promotion following TBI. Medline, Google Scholar and Web of Science were searched from inception to 25 February 2022. An overwhelming number of results generated suggest that several types of CR/IF play a promising role in promoting post-TBI recovery. This recovery is believed to be achieved by alleviating mitochondrial dysfunction, promoting hippocampal neurogenesis, inhibiting glial cell responses, shaping neural cell plasticity, as well as targeting apoptosis and autophagy. Further, we represent our views on the current issues and provide thoughts on the future direction of this research field.

Optogenetics is emerging as an ideal method for controlling cellular activity. It overcomes some notable shortcomings of conventional methods in the elucidation of neural circuits, promotion of neuroregeneration, prevention of cell death and treatment of neurological disorders, although it is not without its own limitations. In this review, we narratively review the latest research on the improvement and existing challenges of optogenetics, with a particular focus on the field of brain injury, aiming at advancing optogenetics in the study of brain injury and collating the issues that remain. Finally, we review the most current examples of research, applying photostimulation in clinical treatment, and we explore the future prospects of these technologies.

Weight loss and metabolic activity influence outcome after allogeneic stem cell transplantation (alloSCT). This study evaluates pre-conditioning Leptin, a peptide hormone involved in metabolism and immune homeostasis, as a prognostic factor for survival, relapse and non-relapse mortality (NRM) following alloSCT. Leptin serum levels prior to conditioning were determined in a cohort of patients transplanted for various hematologic malignancies (n = 524) and correlated retrospectively with clinical outcome. Findings related to patients with acute leukemia (AL) from this sample were validated in an independent cohort. Low pre-conditioning serum Leptin was an independent prognostic marker for increased risk of relapse (but not of NRM and overall mortality) following alloSCT for AL of intermediate and advanced stage (beyond first complete remission). Multivariate analysis revealed a hazard ratio (HR) for relapse of 0.75 per log2 increase (0.59–0.96, p = 0.020). This effect was similar in an independent validation cohort. Pre-conditioning serum Leptin was validated as a prognostic marker for early relapse by fitting the multivariate Cox model to the validation data. Pre-conditioning serum Leptin levels may serve as an independent prognostic marker for relapse following alloSCT in intermediate and advanced stage AL patients. Prospective studies are required to prove whether serum Leptin could be used for guiding nutritional intervention in patients with AL undergoing alloSCT.

An unsteady tightly-coupled icing model is established in this paper to solve the numerical simulation problem of unsteady aircraft icing. The multi-media fluid of air and droplets is regarded as a single medium fluid with variable material properties. Taking the droplet concentration as the phase parameter and the droplet resistance coefficient as the interphase force, the mass concentration distribution of the droplet is obtained by solving the Cahn–Hilliard equation. Fick’s law is introduced to improve the Cahn–Hilliard equation to predict the droplet shadow zone. On this basis, the procedure of the unsteady numerical simulation method for aircraft icing is established, including grid generation, the dual-time-step method to realize the unsteady calculation of the air and droplet tightly-coupled mixed flow field, and the improved shallow water icing model. Finally, through the comparative analysis of numerical examples, the effectiveness of the new model in predicting the droplet impact characteristics and the droplet shadow zone are verified. Compared with other icing models, the ice shapes predicted by the unsteady tightly-coupled model were found to be the most consistent with the experiments. In the icing comparison conditions in this manuscript, the prediction accuracy of the ice thickness at the stagnation point of the leading edge was up to 35% higher than that of LEWICE.

Virtual Shack–Hartmann wavefront sensing (vSHWS) can flexibly adjust parameters to meet different requirements without changing the system, and it is a promising means for aberration measurement. However, how to optimize its parameters to achieve the best performance is rarely discussed. In this work, the data processing procedure and methods of vSHWS were demonstrated by using a set of normal human ocular aberrations as an example. The shapes (round and square) of a virtual lenslet, the zero-padding of the sub-aperture electric field, sub-aperture number, as well as the sequences (before and after diffraction calculation), algorithms, and interval of data interpolation, were analyzed to find the optimal configuration. The effect of the above optimizations on its anti-noise performance was also studied. The Zernike coefficient errors and the root mean square of the wavefront error between the reconstructed and preset wavefronts were used for performance evaluation. The performance of the optimized vSHWS could be significantly improved compared to that of a non-optimized one, which was also verified with 20 sets of clinical human ocular aberrations. This work makes the vSHWS’s implementation clearer, and the optimization methods and the obtained results are of great significance for its applications.

Aircraft icing presents a serious threat to the aerodynamic performance and safety of aircraft. The numerical simulation method for the accurate prediction of icing shape is an important method to evaluate icing hazards and develop aircraft icing protection systems. Referring to the phase-field method, a new ice accretion mathematical model is developed to predict the ice shape. The mass fraction of ice in the mixture is selected as the phase parameter, and the phase equation is established with a freezing coefficient. Meanwhile, the mixture thickness and temperature are determined by combining mass conservation and energy balance. Ice accretions are simulated under typical ice conditions, including rime ice, glaze ice and mixed ice, and the ice shape and its characteristics are analyzed and compared with those provided by experiments and LEWICE. The results show that the phase-field ice accretion model can predict the ice shape under different icing conditions, especially reflecting some main characteristics of glaze ice.

Abstract Localized surface plasmon polaritons (SPPs), which can decay non-radiatively into hot carriers, have been widely employed to extend the responses of traditional semiconductor-based photocatalytic and photovoltaic devices to sub-bandgap photons. However, radiative decay is unavoidable and adverse to device performances. Here, we propose to take advantage of propagating SPPs, another form of SPPs, which possess non-radiative decay only. A special gold-titanium dioxide nanowire array with each nanowire capped with a nanocone is proposed. The adjacent nanocones forming top gradual openings attribute to efficient sunlight harvesting, while the neighbouring nanowires forming bottom nanoslots allow sufficient absorption due to the propagating SPPs. With the combined advantages, almost 100% of light is absorbed by a very thin gold film in the visible range, and 73% in the whole considered range of 400–1170 nm, superior to the nanocone cell based on localized SPPs, let alone the nanowire-based and planar counterparts. Therefore, much better photovoltaic conversion performance is achieved with short-circuit current density of 0.74 mA/cm2 and open-circuit voltage of 0.41 V. This work confirms the superiority of non-radiative decay of propagating SPPs to the localized SPPs in terms of generation of hot carriers, providing a promising way of extracting electrons in metal into photocurrent.

The trillions of cells in the human body can be viewed as elementary but essential biological units that achieve different body states, but the low resolution of previous cell isolation and measurement approaches limits our understanding of the cell-specific molecular profiles. The recent establishment and rapid growth of single-cell sequencing technology has facilitated the identification of molecular profiles of heterogeneous cells, especially on the transcription level of single cells [single-cell RNA sequencing (scRNA-seq)]. As a novel method, the robustness of scRNA-seq under changing conditions will determine its practical potential in major research programs and clinical applications. In this review, we first briefly presented the scRNA-seq-related methods from the point of view of experiments and computation. Then, we compared several state-of-the-art scRNA-seq analysis frameworks mainly by analyzing their performance robustness on independent scRNA-seq datasets for the same complex disease. Finally, we elaborated on our hypothesis on consensus scRNA-seq analysis and summarized the potential indicative and predictive roles of individual cells in understanding disease heterogeneity by single-cell technologies.

Increasing evidence suggests that endothelial cell distress is associated with mortality after allogeneic stem cell transplantation and acute graft-versus-host disease. Asymmetric dimethylarginine is an endogenous nitric oxide synthase inhibitor that induces endothelial cell dysfunction. We analyzed the impact of pre-transplant serum levels of asymmetric dimethylarginine on outcome after allogeneic stem cell transplantation. Since acute graft-versus-host disease and its treatment are major contributors to post-transplant mortality, the effect of asymmetric dimethylarginine on outcome measures was also assessed after onset of acute graft-versus-host disease. A total of 938 patients allografted at two centers between 2002 and 2013 were included in the retrospective study. In multivariable models, higher pre-transplant asymmetric dimethylarginine levels were significantly associated with an increased risk of non-relapse mortality (hazard ratio 1.43 per 1-log2 increase, P=0.005) but not with relapse (hazard ratio 1.21, P=0.109) within the first year after transplantation. This translated into worse overall survival (hazard ratio 1.45, P

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is already known to be involved in the development and progression of many types of tumors. In the present study, we set to seek the role of MALAT1and the molecular mechanisms in breast cancer.