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AIM: To evaluate the efficacy, timing of retreatment and safety of dexamethasone (DEX) implant on macular edema (ME) secondary to diabetic retinopathy (DME) and retinal vein occlusion (RVO-ME) patients who were refractory to anti-vascular endothelial growth factor (VEGF) treatment. METHODS: This retrospective study included 37 eyes received at least one DEX implant treatment for DME or RVO-ME between January 1, 2019, and January 1, 2023. These refractory DME and RVO-ME cases received at least 5 anti-VEGF injections and failure to gain more than 5 letters or a significant reduction in central retinal thickness (CRT). The best corrected visual acuity (BCVA) and CRT were measured at baseline, and at 1, 3, 4 and 6mo post-DEX implant injection. Adverse events such as elevated intraocular pressure (IOP) and cataract were recorded. RESULTS: For RVO cases (n=22), there was a significant increase in BCVA from 0.27±0.19 to 0.35±0.20 at 6mo post-DEX injection (P

Abstract Lettuce is one of the most widely cultivated and consumed dicotyledonous vegetables globally. Despite the availability of its reference genome sequence, lettuce gene annotation remains incomplete, impeding comprehensive research and the broad application of genomic resources. Long-read RNA isoform sequencing (Iso-Seq) offers substantial advantages for analyzing RNA alternative splicing and aiding gene annotation, yet it faces throughput limitations. We present the HIT-ISOseq method tailored for bulk sample analysis, significantly enhancing RNA sequencing throughput on the PacBio platform by concatenating cDNA. Here we show, HIT-ISOseq generates 3-4 cDNA molecules per CCS read in lettuce, yielding 15.7 million long reads per PacBio Sequel II SMRT Cell 8 M. We validate its effectiveness in analyzing six lettuce tissue samples, including roots, stems, and leaves, revealing tissue-specific gene expression patterns and RNA isoforms. Leveraging diverse tissue long-read RNA sequencing, we refine the transcript annotation of the lettuce reference genome, expanding its GO and KEGG annotation repertoire. Collectively, this study serves as a foundational reference for genome annotation and the analysis of multi-sample isoform expression, utilizing high-throughput long-read transcriptome sequencing.

To enhance the transmission capabilities in power system scheduling, this paper develops a unit commitment model that incorporates dynamic transmission line capacities and proposes an efficient solving algorithm. A multi-scenario unit commitment model that integrates dynamic transmission line capacities is introduced, using quantile regression to construct a data-driven capacity increase model based on historical environmental data. The model is solved using Lagrangian relaxation and the Alternating Direction Method of Multipliers (ADMM) to decouple dynamic constraints, allowing the dual problem to be decomposed into sub-problems and solved iteratively. The proposed model and algorithm are validated using the IEEE-118 and IEEE-300 test cases, demonstrating their effectiveness in handling dynamic transmission line capacities and improving scheduling performance.The approach provides a robust and flexible solution for power system scheduling, enhancing reliability and economic efficiency.

Abstract Voice identification is being increasingly adopted in various domains, including security infrastructures, intelligent home systems, and personalised digital assistants. Notably, it harbours significant promise in transforming healthcare, especially in electronic health record detecting and speech impairment monitoring such as aphasia. Current strategies such as acoustic models based on deep learning, voice bio‐metrics, and spectrogram analysis, have been identified with several drawbacks including vulnerability to altered voices, susceptibility to ambient noise, and the necessity for significant computational power. In response to these issues, the authors introduce a ground‐breaking method of voice identification using Ultra‐Wideband (UWB) technology. This method capitalises on the micro‐Doppler shifts associated with movements of the laryngeal prominence. The distinctive nature of these bio‐metric traits related to speech production provides superior resistance against common pitfalls of voice identification. The proposed model leverages the high‐resolution characteristics of UWB to register tiny variations in laryngeal movements produced during speech, thus forming a distinct voice profile for each speaker. Through rigorous testing, the proposed system demonstrated significant progress in voice identification, achieving close to 90% accuracy in controlled experimental settings. This breakthrough indicates that UWB‐enabled voice identification could have a profound effect on medical applications, providing potential improvements in diagnosing, monitoring, possibly treating speech disorders, and thereby shaping a future of enhanced and secured healthcare services.

The sliding mode observer (SMO) has the advantages of small influence by parameter changes and strong robustness, which is widely used in the sensorless control of permanent magnet synchronous motor (PMSM). However, when the sliding mode observer is used to observe the position and speed information of the PMSM, the problem of slow response and excessive chattering is always accompanied. In order to reduce the time of observation position and improve the anti-interference of the system, the super-twisting sliding mode observer(STSMO) is proposed, which can be used to reduce the chattering amplitude effectively, Additionally, the fast and terminal factors is added to the sliding mode surface so that it can converge quickly in a finite time. Then, an improved fast terminal super-twisting sliding mode observer (FTSTSMO) is proposed in the extended state. It can be proved that the observer can converge by Lyapunov stability, and the new observer can suppress chattering and improve the convergence speed. Finally, the experimental analysis is carried out on the 1kW permanent magnet synchronous motor experimental platform, and the SMO and STSMO are compared with FTSTSMO. The results show that FTSTSMO can effectively reduce the fluctuation of the system, improve the tracking effect of rotor speed and rotor position when the speed changes, and further make the whole control system of PMSM have stronger robustness and stability.

Abstract Small-scale motion detection using non-invasive remote sensing techniques has recently garnered significant interest in the field of speech recognition. Our dataset paper aims to facilitate the enhancement and restoration of speech information from diverse data sources for speakers. In this paper, we introduce a novel multimodal dataset based on Radio Frequency, visual, text, audio, laser and lip landmark information, also called RVTALL. Specifically, the dataset consists of 7.5 GHz Channel Impulse Response (CIR) data from ultra-wideband (UWB) radars, 77 GHz frequency modulated continuous wave (FMCW) data from millimeter wave (mmWave) radar, visual and audio information, lip landmarks and laser data, offering a unique multimodal approach to speech recognition research. Meanwhile, a depth camera is adopted to record the landmarks of the subject’s lip and voice. Approximately 400 minutes of annotated speech profiles are provided, which are collected from 20 participants speaking 5 vowels, 15 words, and 16 sentences. The dataset has been validated and has potential for the investigation of lip reading and multimodal speech recognition.

Lacking self-repair abilities, injuries to articular cartilage can lead to cartilage degeneration and ultimately result in osteoarthritis. Tissue engineering based on functional bioactive scaffolds are emerging as promising approaches for articular cartilage regeneration and repair. Although the use of cell-laden scaffolds prior to implantation can regenerate and repair cartilage lesions to some extent, these approaches are still restricted by limited cell sources, excessive costs, risks of disease transmission and complex manufacturing practices. Acellular approaches through the recruitment of endogenous cells offer great promise for in situ articular cartilage regeneration. In this study, we propose an endogenous stem cell recruitment strategy for cartilage repair. Based on an injectable, adhesive and self-healable o-alg-THAM/gel hydrogel system as scaffolds and a biophysio-enhanced bioactive microspheres engineered based on hBMSCs secretion during chondrogenic differentiation as bioactive supplement, the as proposed functional material effectively and specifically recruit endogenous stem cells for cartilage repair, providing new insights into in situ articular cartilage regeneration.

Abstract Biologics are increasingly used to treat Vogt-Koyanagi-Harada disease, but head-to-head comparisons with conventional immunosuppressants are lacking. Here in this randomized trial (Chinese Clinical Trial Registry, ChiCTR2100043061), we assigned 110 patients (27 early-phase and 83 late-phase) to cyclosporine-based immunosuppressant strategy (N = 56) or adalimumab-based biologic strategy (N = 54), each combined with a modified corticosteroid regimen. The primary outcome is change from baseline in best-corrected visual acuity at week 26. The margin of non-inferiority for cyclosporine is −7 letters. The primary outcome is 11.2 letters (95% CI, 7.5 to 14.9) in the cyclosporine group and 6.3 letters (95% CI, 3.1 to 9.6) in the adalimumab group (difference, 4.9; 95% CI, 0.2 to 9.5; P

As the genome is organized into a three-dimensional structure in intracellular space, epigenomic information also has a complex spatial arrangement. However, most epigenetic studies describe locations of methylation marks, chromatin accessibility regions, and histone modifications in the horizontal dimension. Proper spatial epigenomic information has rarely been obtained. In this study, we designed spatial chromatin accessibility sequencing (SCA-seq) to resolve the genome conformation by capturing the epigenetic information in single-molecular resolution while simultaneously resolving the genome conformation. Using SCA-seq, we are able to examine the spatial interaction of chromatin accessibility (e.g. enhancer–promoter contacts), CpG island methylation, and spatial insulating functions of the CCCTC-binding factor. We demonstrate that SCA-seq paves the way to explore the mechanism of epigenetic interactions and extends our knowledge in 3D packaging of DNA in the nucleus.

Abstract Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics.

Abstract This work introduces an attention mechanism that can be integrated into any standard convolution neural network to improve model sensitivity and prediction accuracy with minimal computational overhead. The attention mechanism is introduced in a lightweight network – Alexnet and its classification performance for human micro‐Doppler signatures is evaluated. The Alexnet model trained with an attention module can implicitly highlight the salient regions in the radar signatures while suppressing the irrelevant background regions and consistently improving network predictions. Network visualizations are provided through class activation mapping, providing better insights into how the predictions are made. The visualizations demonstrate how the attention mechanism focusses on the region of interest in the radar signatures.

Abstract Epigenetic modifications of histones are associated with development and pathogenesis of disease. Existing approaches cannot provide insights into long-range interactions and represent the average chromatin state. Here we describe BIND&MODIFY, a method using long-read sequencing for profiling histone modifications and transcription factors on individual DNA fibers. We use recombinant fused protein A-M.EcoGII to tether methyltransferase M.EcoGII to protein binding sites to label neighboring regions by methylation. Aggregated BIND&MODIFY signal matches bulk ChIP-seq and CUT&TAG. BIND&MODIFY can simultaneously measure histone modification status, transcription factor binding, and CpG 5mC methylation at single-molecule resolution and also quantifies correlation between local and distal elements.

Wearing masks is an effective protective measure for residents to prevent respiratory infectious diseases when going out. Due to issues such as a small target size, target occlusion leading to information loss, false positives, and missed detections, the effectiveness of face mask-wearing detection needs improvement. To address these issues, an improved YOLOv7 object detection model is proposed. Firstly, the C2f_SCConv module is introduced in the backbone network to replace some ELAN modules for feature extraction, enhancing the detection performance of small targets. Next, the SPPFCSPCA module is proposed to optimize the spatial pyramid pooling structure, accelerating the model convergence speed and improving detection accuracy. Finally, the HAM_Detect decoupled detection head structure is introduced to mitigate missed and false detections caused by target occlusion, further accelerating model convergence and improving detection performance in complex environments. The experimental results show that improved YOLOv7 achieved an mAP of 90.1% on the test set, a 1.4% improvement over the original YOLOv7 model. The detection accuracy of each category improved, effectively providing technical support for mask-wearing detection in complex environments.

Depression is a common mental illness. Ferroptosis is a form of cell death that may be responsible for neurological disease, but the role of ferroptosis in depression remains unclear. tRNA-derived small RNA (tsRNA) is an emerging non-coding small RNA, making it an important medium for studying neurological diseases. Chronic unpredictable mild stress (CUMS) was used to construct the depression model in mice, which was treated with ferrostatin-1 (Fer-1). Classical behavioral test, immunofluorescence and small RNA sequencing were used to detect depression-like behaviors, neuronal proliferation and the expression profile of tsRNAs in mice, respectively. The primary neuronal cell damage model was constructed by corticosterone (CORT), and the function of key tsRNA was investigated by quantitative real-time PCR, western blot and CCK-8 assays. Here, Fer-1 reduced the depression-like behavior of CUMS-induced mice and promoted neuronal growth. In addition, CUMS caused the disorder of tsRNA expression profile in hippocampal tissues of mice, and Fer-1 alleviated the abnormal tsRNA expression, among which tsRNA-3029b was an effective target. In vitro experiments manifested that ROS accumulation and decreased expression of SLC7A11 and GPX4 were found in CORT-induced depression-like cell model, suggesting that ferroptosis was involved in neuronal injury. However, inhibition of tsRNA-3029b suppressed neuronal cell ferroptosis and facilitated neuronal regeneration. In conclusion, Fer-1 showed an antidepressant effect in CUMS-induced mice and alleviated the abnormal expression profile of tsRNA. tsRNA-3029b was a key target in depression, and silencing of tsRNA-3029b reduced the occurrence of ferroptosis and protected neurons from injury, which may provide novel target for the treatment of depression.

Semantic segmentation of human images is a research hotspot in the field of computer vision. At present, the semantic segmentation models based on U-net generally lack the ability to capture the spatial information of images. At the same time, semantic incompatibility exists because the feature maps of encoder and decoder are directly connected in the skip connection stage. In addition, in low light scenes such as at night, it is easy for false segmentation and segmentation accuracy to appear. To solve the above problems, a portrait semantic segmentation method based on dual-modal information complementarity is proposed. The encoder adopts a double branch structure, and uses a SK-ASSP module that can adaptively adjust the convolution weights of different receptor fields to extract features in RGB and gray image modes respectively, and carries out cross-modal information complementarity and feature fusion. A hybrid attention mechanism is used in the jump connection phase to capture both the channel and coordinate context information of the image. Experiments on human matting dataset show that the PA and MIoU coefficients of this algorithm model reach 96.58% and 94.48% respectively, which is better than U-net benchmark model and other mainstream semantic segmentation models.

Disruptions in glucose metabolism are frequently observed among patients undergoing peritoneal dialysis (PD) who utilize glucose-containing dialysis solutions. We aimed to investigate the relationship between glucometabolic indices, including fasting glucose, insulin resistance, advanced glycation end products (AGEs), PD-related glucose load, and icodextrin usage, and aortic stiffness in PD patients with and without diabetic mellitus (DM). This study involved 172 PD patients (mean age 58.3 ± 13.5 years), consisting of 110 patients without DM and 62 patients with DM. Aortic stiffness was assessed using the carotid-femoral pulse wave velocity (cfPWV). Impaired fasting glucose was defined as a fasting glucose level ≥ 100 mg/dL. Homeostatic model assessment for insulin resistance (HOMA-IR) scores, serum AGEs, dialysate glucose load, and icodextrin usage were assessed. Patients with DM exhibited the highest cfPWV (9.9 ± 1.9 m/s), followed by those with impaired fasting glucose (9.1 ± 1.4 m/s), whereas patients with normal fasting glucose had the lowest cfPWV (8.3 ± 1.3 m/s), which demonstrated a significant trend. In non-DM patients, impaired fasting glucose (β = 0.52, 95% confidence interval [CI] = 0.01–1.03, p = 0.046), high HOMA-IR (β = 0.60, 95% CI = 0.12–1.08, p = 0.015), and a high PD glucose load (β = 0.58, 95% CI = 0.08–1.08, p = 0.023) were independently associated with increased cfPWV. In contrast, none of the glucometabolic factors contributed to differences in cfPWV in DM patients. In conclusion, among PD patients without DM, impaired fasting glucose, insulin resistance, and PD glucose load were closely associated with aortic stiffness.

Measurement(s) Human physical activity • Human location Technology Type(s) WiFi sensing device • ultra-wideband impulse radar • passive WiFi radar • Kinect motion sensor Factor Type(s) Human location • Human physical activity • Room geometry • Participant demographics • Contactless sensing devices Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment Office building Sample Characteristic - Location United Kingdom

Abstract Software defined radar (SDRadar) systems have become an important area for future radar development and are based on similar concepts to Software defined radio (SDR). Most of the processing like filtering, frequency conversion and signal generation are implemented in software. Currently, radar systems tend to have complex signal processing and operate at wider bandwidth, which means that limits on the available computational power must be considered when designing a SDRadar system. This paper presents a feasible solution to this potential limitation by accelerating the signal processing using a GPU to enable the development of a high speed SDRadar system. The developed system overcomes the limitation on the processing speed by CPU‐only, and has been tested on three different SDR devices. Results show that, with GPU accelerator, the processing rate can achieve up to 80 MHz compared to 20 MHz with the CPU‐only. The high speed processing makes it possible to run in real‐time and process full bandwidth across the WiFi signal acquired by multiple channels. The gains made through porting the processing to the GPU moves the technology towards real‐world application in various scenarios ranging from healthcare to IoT, and other applications that required significant computational processing.

BackgroundThe best choice of first-line treatment for metastatic hormone-sensitive prostate cancer (mHSPC) is unclear. We aimed to compare the effectiveness and safety determined in randomized clinical trials of doublet and triplet treatments for mHSPC.MethodsMedline, Embase, Cochrane Central and ClinicalTrials.gov were searched from inception through July 01, 2022. Eligible studies were phase III randomized clinical trials evaluating androgen deprivation treatment (ADT) alone, doublet therapies [ADT combined with docetaxel (DOC), novel hormonal agents (NHAs), or radiotherapy (RT)], or triplet therapies (NHA+DOC+ADT) as first-line treatments for mHSPC. Outcomes of interest included overall survival (OS), progression-free survival (PFS) and grades 3-5 adverse events (AEs). Subgroup analyses were performed based on tumor burden. The effects of competing treatments were assessed by Bayesian network meta-analysis using R software.ResultsTen trials with 12,298 patients comparing nine treatments were included. Darolutamide (DARO) +DOC+ADT ranked best in terms of OS benefits (OR 0·52 [95% CI 0·39–0·70]), but its advantages were all statistically insignificant compared with other therapy options except for DOC+ADT (OR 0·68 [95% CI 0·53–0·88]) and RT+ADT (OR 0·57 [95% CI 0·40–0·80]). In terms of PFS, enzalutamide(ENZA)+DOC+ADT (OR 0·32 [95% CI 0·24–0·44]) and abiraterone and prednisone (AAP) +DOC+ADT (OR 0·33 [95% CI 0·25–0·45]) ranked best. For patients with high volume disease (HVD), low volume disease (LVD), and visceral metastases, the optimal therapies were AAP+DOC+ADT (OR 0·52 [95% CI 0·33–0·83]), apalutamide+ADT (OR 0·52 [95% CI 0·26–1·05]) and DARO+DOC+ADT (OR 0·42 [95% CI 0·13–1·34]), respectively. For safety, AAP+DOC+ADT (OR 3·56 [95% CI 1·51–8·43]) ranked worst with the highest risk of grade 3−5 AEs.ConclusionsTriple therapies may further improve OS and PFS but may be associated with a decrease in safety. Triplet therapies could be suggested for HVD patients, while doublet combinations should still be preferred for LVD patients.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPEROFILES/303117_STRATEGY_20220202.pdf, identifier CRD4202303117.

Objective To investigate the effect of autophagy expression levels of different weight‐bearing states and different stages of osteoarthritis in animal models, as well as the corresponding mechanisms. Methods We used the male Sprague–Dawley (SD) rats (12‐week‐old, SPF) to establish the OA animal models by modified Hulth method, and grouped animal models according to the length of time after surgery and different weight‐bearing areas. RT‐qPCR was carried out for detection of autophagy‐related genes such as Atg7, Atg12, P62, etc. Western blot analysis was used to detect the expression levels of corresponding autophagy‐related proteins such as LC3B, P62, etc. T test was performed for statistical analysis to compare different groups, while the differences were deemed statistically significant with P

The random finite difference method (RFDM) is a popular approach to quantitatively evaluate the influence of inherent spatial variability of soil on the deformation of embedded tunnels. However, the high computational cost is an ongoing challenge for its application in complex scenarios. To address this limitation, a deep learning-based method for efficient prediction of tunnel deformation in spatially variable soil is proposed. The proposed method uses one-dimensional convolutional neural network (CNN) to identify the pattern between random field input and factor of safety of tunnel deformation output. The mean squared error and correlation coefficient of the CNN model applied to the newly untrained dataset was less than 0.02 and larger than 0.96, respectively. It means that the trained CNN model can replace RFDM analysis for Monte Carlo simulations with a small but sufficient number of random field samples (about 40 samples for each case in this study). It is well known that the machine learning or deep learning model has a common limitation that the confidence of predicted result is unknown and only a deterministic outcome is given. This calls for an approach to gauge the model's confidence interval. It is achieved by applying dropout to all layers of the original model to retrain the model and using the dropout technique when performing inference. The excellent agreement between the CNN model prediction and the RFDM calculated results demonstrated that the proposed deep learning-based method has potential for tunnel performance analysis in spatially variable soils.

Modeling only constitutes one aspect of decision making. The prevailing limitation of applying modeling to practice is the absence of explicit consideration of uncertainties. This review paper covers uncertainty quantification (soil properties, stratification, and model performance) and uncertainty calculation with a focus on how it enhances the role of modeling in decision making (reliability analysis, reliability-based design, and inverse analysis). The key output from a reliability analysis is the probability of failure, where “failure” is defined as any condition that does not meet a performance criterion or a set of criteria. In contrast to the global factor of safety, the probability of failure respects both mechanics and statistics, is sensitive to data (thus opening one potential pathway to digital transformation), and it is meaningful for both system and component failures. Resilience engineering requires system level analysis. As such, geotechnical software can provide better decision support by computing the probability of failure/reliability index as one basic output in addition to stresses, strains, forces, and displacements. It is further shown that more critical non-classical failure mechanisms can emerge from spatially variable soils that can escape notice if the engineer were to restrict analysis to conventional homogeneous or layered soil profiles.

Abstract Background Although extrachromosomal DNA (ecDNA) has been intensively studied for several decades, the mechanisms underlying its tumorigenic effects have been revealed only recently. In most conventional sequencing studies, the high-throughput short-read sequencing largely ignores the epigenetic status of most ecDNA regions except for the junctional areas. Methods Here, we developed a method of sequencing enzyme-accessible chromatin in circular DNA (CCDA-seq) based on the use of methylase to label open chromatin without fragmentation and exonuclease to enrich ecDNA sequencing depth, followed by long-read nanopore sequencing. Results Using CCDA-seq, we observed significantly different patterns in nucleosome/regulator binding to ecDNA at a single-molecule resolution. Conclusions These results deepen the understanding of ecDNA regulatory mechanisms.

ABSTRACT: Background: Generalized anxiety disorder (GAD) is a common chronic mental disorder, and it also can cause depressive symptoms and cognitive impairment. The primary aim of this study was to determine whether inflow-frequency transcranial magnetic stimulation (ILF-TMS) improves anxiety symptoms in patients with GAD. Methods: Sixty-two patients with GAD were randomly divided into 2 groups. Thirty-one patients in the active ILF-TMS group and 31 patients in the sham ILF-TMS group. All participants were assessed at baseline, week 2, week 4 and week 12. The intention-to-treat methodology was used for the analysis. Results: The response rate was higher in the active group than in the sham group, with a significant difference at week 12 (response rate: 80.6% vs. 54.8%, respectively; P = 0.03). Although the remission rate was higher in the active group at week 12, there was no statistically significant difference between the groups (remission rate: 71.0% vs. 48.4%; P > 0.05). No statistically significant differences on the Hamilton Depression Rating Scale, Clinical Global Impression scale, and neurocognitive test between groups were observed (overall P > 0.05). Adverse events that occurred in the active group were similar to those in the sham group, with no significant differences (P > 0.05). Conclusion: The response rate was higher in the active group at the end of the trial, which indicated that ILF-TMS may be an effective and safe adjunctive tool to improve anxiety symptoms in patients with GAD.

Textile effluents containing synthetic refractory azo dyes are one of the most important sources of water pollution. However, these kinds of refractory organic pollutants did not resist a persulfate (PS) oxidation process which was correctly activated. In this study, PS was activated by ferrous sulfide (FeS) in a heterogeneous system to break down azo dyes wastewater. The results showed that all five selected azo dyes were efficiently broken down using the PS/FeS system, except for DY 12, and more than 95% of azo dyes were decolored within 60 minutes. The decolorization efficiency of DR 81 in the PS/FeS system was comparable to PS activated with heat (60 °C) or Fe2+, and was slightly superior to Fe0 powders under the same conditions. Quenching studies indicated that both SO4−• and •OH were formed in the FeS surface and diffused into the solution to facilitate the successive transformation of DR 81, the •OH reaction with DR 81 might the crucial reaction. The coexisting chelating agents in real azo dye effluents at high concentrations had a negative influence on azo dye decolorization by PS/FeS. However, the superior factor of the PS/FeS system was the regenerability and reusability of the heterogeneous catalyst. HIGHLIGHTS Five selected azo dyes were efficiently broken down using the PS/FeS system.; DR 81 decolorization by PS activated with FeS was comparable to other activators.; •OH might play a crucial role on DR 81 decolorization by PS/FeS system.; DR 81 decolorization proceeded by PS/FeS with correct coexisting chelating agents.; FeS was regenerable and recyclable in the heterogeneous PS/FeS system.;

By September 20, 2021, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been pandemic in 237 countries and regions, resulting in 228,506,698 confirmed cases and 4,692,361 deaths. At the same time, a total of 1123 cases of COVID-19 had been confirmed in Beijing, China. Peking University Shougang Hospital has 4 community hospitals with 174 staff members, covering 230,000 residents in Shijingshan district, Beijing. The community hospitals were the basic units of China’s healthcare system for public health services, as the main battlefield for screening and controlling of COVID-19. We reported our experience about the prevention of SARS-CoV-2. We suggest that community hospitals should change their process for admitting patients. While the screening of suspected cases of COVID-19 is vital, patients with suspected infections should be isolated immediately.

Different from the traditional deep tillage, deep vertical rotary tillage can smash deep soil without disturbing the soil layer, which improves soil water infiltration and promotes salt leaching. This has gradually been applied in the research into saline alkali improvements. However, there is limited knowledge about the effect of deep vertical rotary tillage on the temporal–spatial distributions of soil water and salt under the shallow underground water level. Therefore, a preliminary soil column experiment was carried out to explore the results of water and salt movement under three different tillage methods: traditional rotary tillage depth of 20 cm (XG−20), deep vertical rotary tillage depth of 20 cm (FL−20) and deep vertical rotary tillage depth of 40 cm (FL−40). The temporal–spatial variation in soil water and salt was analyzed. The results showed that the average infiltration rate of FL−40 increased by 1.25 and 0.46 cm h−1 in 0−40 cm soil layer compared with that of XG−20 and FL−20. At the same time, soil water content was also increased, and the order of soil water content was FL−40 > FL−20 > XG−20. With the increase in tillage depth, the desalinization rate and the soil electric conductivity (EC) of FL−40 were increased and decreased, respectively. The FL−40 treatment’s average desalinization rates increased by 16.32% and 13.99% compared with XG−20 and FL−20 treatments’ in 0−60 cm soil layer. In conclusion, FL−40 had a better effect on regulating water and salt. The deep vertical rotary tillage provided an effective method for the control and optimization of water and salt in coastal saline soil.

Abstract Background This study aimed to investigate the differences in the serum levels of glucose, lipid, and thyroid function markers between unipolar and bipolar depressed patients, as well as the effect of anhedonia and suicidal thoughts on the levels of these biochemical parameters. Methods A total of 287 unmedicated depressed patients from January 2016 to December 2017 were included in this study, including 92 bipolar depressions and 195 unipolar depressions. Anhedonia was determined using the item 32 of Symptom Checklist (SCL-90). Suicide ideation was assessed by item 15 of SCL-90. Results The bipolar group had significantly lower lipid levels (including triglycerides, cholesterol, low-density lipoprotein cholesterol [LDL], very low-density lipoprotein cholesterol [VLDL]) and insulin resistance index but higher levels of prolactin, low triiodothyronine (T3) and free T3 (FT3) as well as higher incidence of anhedonia as compared with the unipolar group. Depressed patients with anhedonia had significantly higher LDL level than those without anhedonia. Depressed patients with suicidal thoughts had cholesterol and high-density lipoprotein cholesterol (HDL) level. The above-mentioned differences were confirmed by logistic regression analysis. Receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve (AUC) ranged from 0.546 to 0.685. Conclusion Triglycerides, cholesterol, LDL, VLDL T3, FT3 levels were significantly different between unipolar and bipolar depressed patients, which might have the potential to be the markers for differential diagnosis. Patients with anhedonia had lower LDL level, while patients with suicidal thoughts had higher levels of cholesterol and HDL as compared with the corresponding control groups.

Abstract Background Transposable elements (TEs) make up > 50% of the human genome, and the majority of retrotransposon insertions are truncated and many are located in introns. However, the effects of retrotransposition on the host genes remain incompletely known. Results We report here that insertion of a chimeric L1 (cL1), but not IAP solo LTR, into intron 6 of Axin1 using CRIPSR/Cas9 induced the kinky tail phenotype with ~ 80% penetrance in heterozygous Axin cL1 mice. Both penetrant (with kinky tails) and silent (without kinky tails) Axin cL1 mice, regardless of sex, could transmit the phenotype to subsequent generations with similar penetrance (~ 80%). Further analyses revealed that a longer Axin1 transcript isoform containing partial cL1-targeted intron was present in penetrant, but absent in silent and wild type mice, and the production of this unique Axin1 transcript appeared to correlate with altered levels of an activating histone modification, H3K9ac. Conclusions The mechanism for Axin cL1 mice is different from those previously identified in mice with spontaneous retrotransposition of IAP, e.g., Axin Fu and A vy , both of which have been associated with DNA methylation changes. Our data suggest that Axin1 locus is sensitive to genetic and epigenetic alteration by retrotransposons and thus, ideally suited for studying the effects of new retrotransposition events on target gene function in mice.

Abstract Background Whole exome sequencing (WES) has been widely used in human genetics research. BGISEQ-500 is a recently established next-generation sequencing platform. However, the performance of BGISEQ-500 on WES is not well studied. In this study, we evaluated the performance of BGISEQ-500 on WES by side-to-side comparison with Hiseq4000, on well-characterized human sample NA12878. Results BGISEQ demonstrated similarly high reproducibility as Hiseq for variation detection. Also, the SNVs from BGISEQ data is highly consistent with Hiseq results (concordance 96.5%~ 97%). Variation detection accuracy was subsequently evaluated with data from the genome in a bottle project as the benchmark. Both platforms showed similar sensitivity and precision in SNV detection. While in indel detection, BGISEQ showed slightly higher sensitivity and lower precision. The impact of sequence depth and read length on variation detection accuracy was further analyzed, and showed that variation detection sensitivity still increasing when the sequence depth is larger than 100x, and the impact of read length is minor when using 100x data. Conclusions This study suggested that BGISEQ-500 is a qualified sequencing platform for WES.

Abstract Background Environmental toxicants such as DDT have been shown to induce the epigenetic transgenerational inheritance of disease (e.g., obesity) through the germline. The current study was designed to investigate the DDT-induced concurrent alterations of a number of different epigenetic processes including DNA methylation, non-coding RNA (ncRNA) and histone retention in sperm. Methods Gestating females were exposed transiently to DDT during fetal gonadal development, and then, the directly exposed F1 generation, the directly exposed germline F2 generation and the transgenerational F3 generation sperm were investigated. Results DNA methylation and ncRNA were altered in each generation sperm with the direct exposure F1 and F2 generations being predominantly distinct from the F3 generation epimutations. The piRNA and small tRNA were the most predominant classes of ncRNA altered. A highly conserved set of histone retention sites were found in the control lineage generations which was not significantly altered between generations, but a large number of new histone retention sites were found only in the transgenerational generation DDT lineage sperm. Conclusions Therefore, all three different epigenetic processes were concurrently altered as DDT induced the epigenetic transgenerational inheritance of sperm epimutations. The direct exposure generations sperm epigenetic alterations were distinct from the transgenerational sperm epimutations. The genomic features and gene associations with the epimutations were investigated to help elucidate the integration of these different epigenetic processes. Observations demonstrate all three epigenetic processes are involved in transgenerational inheritance. The different epigenetic processes appear to be integrated in mediating the epigenetic transgenerational inheritance phenomenon.

Abstract Background Post-transcriptional regulation of gene expression can be achieved through the control of mRNA stability, cytoplasmic compartmentalization, 3′ UTR length and translational efficacy. Spermiogenesis, a process through which haploid male germ cells differentiate into spermatozoa, represents an ideal model for studying post-transcriptional regulation in vivo because it involves a large number of transcripts that are physically sequestered in ribonucleoprotein particles (RNPs) and thus subjected to delayed translation. To explore how small RNAs regulate mRNA fate, we conducted RNA-Seq analyses to determine not only the levels of both mRNAs and small noncoding RNAs, but also their cytoplasmic compartmentalization during spermiogenesis. Result Among all small noncoding RNAs studied, miRNAs displayed the most dynamic changes in both abundance and subcytoplasmic localization. mRNAs with shorter 3′ UTRs became increasingly enriched in RNPs from pachytene spermatocytes to round spermatids, and the enrichment of shorter 3′ UTR mRNAs in RNPs coincided with newly synthesized miRNAs that target these mRNAs at sites closer to the stop codon. In contrast, the translocation of longer 3′ UTR mRNAs from RNPs to polysomes correlated with the production of new miRNAs that target these mRNAs at sites distal to the stop codon. Conclusions miRNAs appear to control cytoplasmic compartmentalization of mRNAs based on 3′ UTR length. Our data suggest that transcripts with longer 3′ UTRs tend to contain distal miRNA binding sites and are thus targeted to polysomes for translation followed by degradation. In contrast, those with shorter 3′ UTRs only possess proximal miRNA binding sites, which, therefore, are targeted into RNPs for enrichment and delayed translation.