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Microbial communities influence host phenotypes through microbiota-derived metabolites and interactions between exogenous active substances (EASs) and the microbiota. Owing to the high dynamics of microbial community composition and difficulty in microbial functional analysis, the identification of mechanistic links between individual microbes and host phenotypes is complex. Thus, it is important to characterize variations in microbial composition across various conditions (for example, topographical locations, times, physiological and pathological conditions, and populations of different ethnicities) in microbiome studies. However, no web server is currently available to facilitate such characterization. Moreover, accurately annotating the functions of microbes and investigating the possible factors that shape microbial function are critical for discovering links between microbes and host phenotypes. Herein, an online tool, CDEMI, is introduced to discover microbial composition variations across different conditions, and five types of microbe libraries are provided to comprehensively characterize the functionality of microbes from different perspectives. These collective microbe libraries include (1) microbial functional pathways, (2) disease associations with microbes, (3) EASs associations with microbes, (4) bioactive microbial metabolites, and (5) human body habitats. In summary, CDEMI is unique in that it can reveal microbial patterns in distributions/compositions across different conditions and facilitate biological interpretations based on diverse microbe libraries. CDEMI is accessible at http://rdblab.cn/cdemi/

Non-linear frequency modulation infrared thermal wave detection system was established to detect and analyze debonding defects of different sizes of CFRP laminates. Principal component analysis, thermal signal reconstruction, and total harmonic distortion are used to process the infrared image sequence collected by thermal imager, and the processing effect is evaluated by signal-to-noise ratio. Compared with the other two image sequence processing algorithms, principal component analysis has better effect, can effectively improve the signal-to-noise ratio, and the defect edge in the processed image is clearer.

Recently, novel 2D InGeTe3 has been successfully synthesized and attracted attention due to its excellent properties.

Heat shock factor 1 (HSF1) functions to maintain cellular and organismal homeostasis by regulating the expression of target genes, including those encoding heat shock proteins (HSPs). In the present study, the gene encoding HSF1 was cloned from the rice pest Chilo suppressalis, and designated Cshsf1. The deduced protein product, CsHSF1, contained conserved domains typical of the HSF1 family, including a DNA-binding domain, two hydrophobic heptad repeat domains, and a C-terminal transactivation domain. Real-time quantitative PCR showed that Cshsf1 was highly expressed in hemocytes. Expression analysis in different developmental stages of C. suppressalis revealed that Cshsf1 was most highly expressed in male adults. RNAi-mediated silencing of Cshsf1 expression reduced C. suppressalis survival at high temperatures. To investigate the regulatory interactions between Cshsf1 and Cshsps, the promoters and expression patterns of 18 identified Cshsps in C. suppressalis were analysed; four types of heat shock elements (HSEs) were identified in promoter regions including canonical, tail-tail, head-head, and step/gap. The expression of Cshsp19.0, Cshsp21.7B, Cshsp60, Cshsp70 and Cshsp90 was positively regulated by Cshsf1; however, Cshsp22.8, Cshsp702, Cshsp705 and Cshsp706 gene expression was not altered. This study provides a foundation for future studies of HSF1 in insects during thermal stress.

IntroductionChimeric antigen receptor (CAR) T cell therapy has achieved unprecedented efficacy recently. However, the factors related to responses and durable remission are elusive. This study was to investigate the impact of pre-lymphodepletion (pre-LD) absolute lymphocyte count (ALC) on CAR T cell therapy outcomes.MethodsWe conducted a retrospective study of 84 patients with relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL) who underwent CAR T cell treatment at the Affiliated Hospital of Xuzhou Medical University between March 1,2016 and December 31, 2021. The enrolled patients were divided into high group and low group according to the optimal cutoff value of pre-LD ALC. The Kaplan-Meier analyses was used to calculate survival curves. The Cox proportional hazards model was used for univariate and multivariate analysis to assess the prognostic factors.ResultsThe ROC showed that the optimal cutoff value of pre-LD ALC was 1.05 x 109/L. The overall response (defined as partial response or complete response) rate was significantly higher in patients with a high pre-LD ALC (75% versus 52.08%; P=0.032). Patients with a low pre-LD ALC had significantly inferior overall survival (OS) and progression-free survival (PFS) compared with those having a high pre-LD ALC (median OS, 9.6 months versus 45.17 months [P=0.008]; median PFS, 4.07 months versus 45.17 months [P= 0.030]). Meanwhile, low pre-LD ALC is an independent risk factor for PFS and OS.DiscussionThe data suggested that pre-LD ALC may serve as a helpful indicator to predict the outcomes of CAR T cell therapy in patients with R/R DLBCL.

The compression behavior of the lattice-walled tubes under variable strain rates are investigated by numerical simulation, and the stress-strain relationship of the structure under quasi-static loading is theoretically analyzed. The finite element software LS-DYNA is used to simulate the structure established by the beam element, and the critical impact velocity is obtained when the structure collapses layer by layer. According to the plastic hinge theory and considering the combined action of the beam's bending moment and axial force in the structure, the stress-strain relationship of the structure under quasi-static loading is derived and compared with the experimental results. The numerical simulation results reveal that the structure of the single-layer gradient tube(SGC) does not undergo shear deformation under quasi-static and low-speed impact. The critical speed of the gradient square tube(GS) is higher than that of a cylindrical tube. The theoretical model can correctly reflect the mechanical response of the structure under uniaxial compression.

Introduction: With the improvement of prenatal ultrasound, MR and other examination techniques, more and more hiatal hernia has been diagnosed in the neonatal period. At present, surgical indications and surgical opportunities of patients with hiatal hernia are still controversial. Through analyzing the clinical data for 11 neonates with esophageal hiatal hernia diagnosed prenatally and treated with laparoscopic hiatal hernia repair in Affiliated Children’s Hospital, this paper analyzed the laparoscopic surgical treatment and postoperative recovery of these 11 cases, explored the clinical efficacy of laparoscopic esophageal hernia repair for the esophageal hiatal hernia by ultrasonographic diagnosed prenatally, and provided clinical basis for the safety of laparoscopic surgery for prenatal diagnosed hiatal hernia in the neonatal period. Methods: This paper retrospectively analyzed the clinical data for 11 neonates (7 males and 4 females) with esophageal hiatal hernia diagnosed prenatally and treated with laparoscopic hiatal hernia repair in Affiliated Children’s Hospital of Capital Institute of Pediatrics from May 2015 to January 2022. The age at operation was 2-94 days old, with a median of 4 days old. The body weight was (2.82 ± 0.51) kg. Preoperative chest CT and upper gastrointestinal radiography were performed to confirm the diagnosis of esophageal hiatal hernia. All the 11 children underwent laparoscopic four-hole repair of esophageal hiatal hernia and fundoplication, including 9 cases of Nissen procedure and 2 cases of Thal procedure. Results: All the 11 operations were performed under laparoscopy without conversion to laparotomy. The operation time of 9 cases of Nissen procedure was (173.0 ± 43.8) mins, and that of Thal procedure was 184 mins and 206 mins, respectively. The time to postoperative diet was (2.54 ± 1.21) days. The hospital stay was (14.09 ± 4.13) days. The 11 neonates were followed up for 7-74 months, with a median of 28 months. No postoperative recurrence of esophageal hiatal hernia occurred. There was no significant difference in height and weight between children of the same age. No obvious vomiting or choking with milk was found. Conclusion: Prenatal diagnosis of hiatal hernia is of great significance for identifying the types of children as soon as possible after birth, determining treatment plan, and preventing recurrent vomiting, pneumonia, growth retardation and other complications. In order to avoid gastric torsion and incarceration, laparoscopic surgery in the neonatal period is safe and reliable for the treatment of prenatal diagnosed hiatal hernia.

This meta-analysis assessed the association between myasthenia gravis (MG) and cognitive disorders. The PubMed, Web of Science, OVID, EMBASE, CNKI and Wanfang electronic databases were comprehensively searched from inception to October 2020 for relevant studies. The primary outcomes were scores of the cognitive function battery. A random effects model was used to evaluate the cognitive function of patients with MG. Eight cross-sectional studies containing 381 patients and 220 healthy controls were included in this meta-analysis. In relation to global cognitive function, patients with MG performed significantly worse than healthy individuals (SMD = −0.4, 95% CI = −0.63 to −0.16, p I2 = 10%). Specifically, the impaired cognitive domains included language, visuospatial function, information processing, verbal immediate and delayed recall memory, visual immediate recall memory, and response fluency, while attention, executive function, and visual delayed recall memory were unimpaired. The patients with early-onset (SMD= −0.527, 95% CI = −0.855 to −0.199, p = 0.002) and generalized MG (SMD= −0.577, 95% CI = −1.047 to −0.107, p = 0.016) had poorer global cognitive performance than the healthy population. Patients with MG may have cognitive disorders, including those associated with the domains of language, visuospatial function, information processing, verbal immediate and delayed recall memory, visual immediate recall memory and response fluency. Furthermore, the age of onset and disease severity may be associated with cognitive disorders in patients with MG.

Peach shoot blight (PSB), caused by Phomopsis amygdali, is a serious threat to the healthy development of the peach industry and leads to 30 to 50% damage to peach production in southern China. In this study, loop-mediated isothermal amplification (LAMP) technology was used to detect the P. amygdali target of a gene of GME6801 that was unique in the whole genome of the pathogen compared with that of Diaporthe (Phomopsis) longicolla TWH P74, Fusarium graminearum PH-1, Colletotrichum gloeosporioides SMCG1 and Magnaporthe oryzae 70-15. Blast comparison of this gene sequence in NCBI database showed that no homologous sequences were found. Therefore, the gene sequence of GME6801 was used to design two pairs of LAMP primers and one pair of PCR primers. The results showed that both primer sets were specific to the 15 strains of P. amygdali, and the other 15 fungal strains presented negative reactions, similar to the control. In addition, 50 pg of genomic DNA of P. amygdali in a 25-μl reaction system could be detected by LAMP assay, which was 100 times more sensitive than PCR. Furthermore, the GME6801 LAMP assay was used to detect artificially inoculated twigs of the pathogen, disease twigs within significantly symptomatic PSB in the fields, and healthy twigs in the same orchard, with detection rates of 100, 75, and 20.8%, respectively. However, detection rates of conventional PCR were separately 100, 62.5, and 16.7%. The results indicated that GME6801-based LAMP could be used for P. amygdali detection as its specificity, sensitivity, and simplicity. This study provides a rapid experimental basis for the identification and prediction of P. amygdali that causes PSB and is beneficial for precise prevention and control of the disease.

Peach shoot blight (PSB), which kills shoots, newly sprouted leaf buds, and peach fruits, has gradually increased over the last 10 years and resulted in 30 to 50% of total production loss of the peach industry in China. Phomopsis amygdali has been identified as the common causal agent of this disease. In this study, two new species, Phomopsis liquidambaris (strain JW18-2) and Diaporthe eres (strain JH18-2), were also pathogens causing PSB, as determined through molecular phylogenetic analysis based on the sequences of the internal transcribed spacer (ITS) region, translation elongation factor 1-α (EF1-α) and beta-tubulin (TUB), and colony and conidial morphological characteristics. Biological phenotypic analysis showed that the colony growth rate of strain JW18-2 was faster than that of strains JH18-2 and ZN32 (one of the P. amygdali strains that we previously found and identified). All three strains produced α-conidia; however, JW18-2 could not produce β-conidia on alfalfa decoction and Czapek media, and the β-conidia produced by strain JH18-2 were shorter in length and thicker in width than those produced by strain ZN32. Pathogenicity tests showed that JW18-2 presented the strongest pathogenicity for peach fruits and twigs and was followed by strains JH18-2 and ZN32. The results shed light on the etiology of PSB and provide a warning that P. liquidambaris or D. eres might develop into dominant species after a few years while also potentially benefitting the development of effective disease control management strategies.

Referring Expression Segmentation (RES) is a widely explored multi-modal task, which endeavors to segment the pre-existing object within a single image with a given linguistic expression. However, in broader real-world scenarios, it is not always possible to determine if the described object exists in a specific image. Typically, we have a collection of images, some of which may contain the described objects. The current RES setting curbs its practicality in such situations. To overcome this limitation, we propose a more realistic and general setting, named Group-wise Referring Expression Segmentation (GRES), which expands RES to a collection of related images, allowing the described objects to be present in a subset of input images. To support this new setting, we introduce an elaborately compiled dataset named Grouped Referring Dataset (GRD), containing complete group-wise annotations of target objects described by given expressions. We also present a baseline method named Grouped Referring Segmenter (GRSer), which explicitly captures the language-vision and intra-group vision-vision interactions to achieve state-of-the-art results on the proposed GRES and related tasks, such as Co-Salient Object Detection and RES. Our dataset and codes will be publicly released in https://github.com/yixuan730/group-res.

Human intelligence can retrieve any person according to both visual and language descriptions. However, the current computer vision community studies specific person re-identification (ReID) tasks in different scenarios separately, which limits the applications in the real world. This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.Our instruct-ReID is a more general ReID setting, where existing ReID tasks can be viewed as special cases by designing different instructions. We propose a large-scale OmniReID benchmark and an adaptive triplet loss as a baseline method to facilitate research in this new setting. Experimental results show that the baseline model trained on our OmniReID benchmark can improve +0.6%, +1.4%, 0.2% mAP on Market1501, CUHK03, MSMT17 for traditional ReID, +0.8%, +2.0%, +13.4% mAP on PRCC, VC-Clothes, LTCC for clothes-changing ReID, +11.7% mAP on COCAS+ real2 for clothestemplate based clothes-changing ReID when using only RGB images, +25.4% mAP on COCAS+ real2 for our newly defined language-instructed ReID. The dataset, model, and code will be available at https://github.com/hwz-zju/Instruct-ReID.

Recently, experiments aimed at measuring gravity mediated entanglement (GME) using quantum information techniques have been proposed, based on the assumption that if two systems get entangled through local interactions with gravitational field, then this field must be quantum. While there is a debate about what could be drawn from GME, quantum simulation might provide some clarification. Here, we present electromagnetic analogy of GME using magnetic-field mediated interaction between the electron and nucleus in a single atom. Our work successfully implements the general procedures of GME experiments and confirms that the mediating field does not support the mean-field description. It also clarifies that, without considering the light-crossing time, the GME experiment would not distinguish a quantum-field-theory description from a quantum-controlled classical field one. Furthermore, this work provides a novel method to construct two-qubit systems in a single atom, and providing the first quantum simulation of GME using material qubits. It helps to conceive the future GME experiments on the scale of light-crossing time., Comment: 12 pages, 4 figures

Supplementary Material 1

Additional file 1: Supplementary Figure 1. FYN expression is upregulated in TCGA GC. A-F. Differential expression of FYN in T-stage, N-stage, M-stage, pathological stage, age, and gender. G-H. The related pathways correlated with high FYN expression by GSEA (p < 0.05). I. FYN protein expression in the human protein altas database is higher in gastric cancer tissues than in normal tissues. Supplementary Figure 2. Differential protein motif analysis after silencing of TOPK. A. Flow chart of proteomics and phosphoproteomics analysis. B. Analysis of COG and KOG entries of differentially phosphorylated proteins. C. Differential phosphorylation protein GO terms analysis. D-E. S motif and T motif analysis summary. Supplementary Figure 3. Differential phosphorylated protein enrichment signaling pathway. A-C. Differential phosphorylation protein biological processes, molecular function and protein domain enrichment analysis. D-F. Differential phosphorylation protein signaling pathway enrichment analysis, the main enrichment signaling pathways were HIPPO signaling pathway, VEGF signaling pathway and SPLICEOSOME signaling pathway. Supplementary Figure 4. TOPK expression is upregulated in TCGA GC patients. A. The TOPK genetic alterations (gene amplification, deep deletion, or somatic mutation) and mRNA expression in GC samples from the TCGA cohort (total alteration rate: 14%). B-H. TOPK mRNA expression is upregulated in the tumor tissues compared with it in normal tissue group from TCGA and expression differences in different T-stage, N-stage, M-stage, pathological stage, age, and gender.

Additional file 1: Fig. S1 Characteristics of the dataset and markers of cell subsets. Fig. S2 Trajectory and cell–cell interaction analyses of monocyte subtypes. Fig. S3 ScRNA-seq analysis reveals monocyte heterogeneity in septic patients with ARDS. Fig. S4 identification of splenic S100ahigh monocytes in murine sepsis. Fig. S5 S100A9 release of circulating and splenic monocytes upon septic challenge. Table S1 Clinical characteristics of enrolled patients. Table S2 Composition of clinical entities in each cluster.

In recommendation scenarios, there are two long-standing challenges, i.e., selection bias and data sparsity, which lead to a significant drop in prediction accuracy for both Click-Through Rate (CTR) and post-click Conversion Rate (CVR) tasks. To cope with these issues, existing works emphasize on leveraging Multi-Task Learning (MTL) frameworks (Category 1) or causal debiasing frameworks (Category 2) to incorporate more auxiliary data in the entire exposure/inference space D or debias the selection bias in the click/training space O. However, these two kinds of solutions cannot effectively address the not-missing-at-random problem and debias the selection bias in O to fit the inference in D. To fill the research gaps, we propose a Direct entire-space Causal Multi-Task framework, namely DCMT, for post-click conversion prediction in this paper. Specifically, inspired by users' decision process of conversion, we propose a new counterfactual mechanism to debias the selection bias in D, which can predict the factual CVR and the counterfactual CVR under the soft constraint of a counterfactual prior knowledge. Extensive experiments demonstrate that our DCMT can improve the state-of-the-art methods by an average of 1.07% in terms of CVR AUC on the five offline datasets and 0.75% in terms of PV-CVR on the online A/B test (the Alipay Search). Such improvements can increase millions of conversions per week in real industrial applications, e.g., the Alipay Search., Comment: 13 pages; Accepted by ICDE 2023

Human-centric perceptions (e.g., pose estimation, human parsing, pedestrian detection, person re-identification, etc.) play a key role in industrial applications of visual models. While specific human-centric tasks have their own relevant semantic aspect to focus on, they also share the same underlying semantic structure of the human body. However, few works have attempted to exploit such homogeneity and design a general-propose model for human-centric tasks. In this work, we revisit a broad range of human-centric tasks and unify them in a minimalist manner. We propose UniHCP, a Unified Model for Human-Centric Perceptions, which unifies a wide range of human-centric tasks in a simplified end-to-end manner with the plain vision transformer architecture. With large-scale joint training on 33 human-centric datasets, UniHCP can outperform strong baselines on several in-domain and downstream tasks by direct evaluation. When adapted to a specific task, UniHCP achieves new SOTAs on a wide range of human-centric tasks, e.g., 69.8 mIoU on CIHP for human parsing, 86.18 mA on PA-100K for attribute prediction, 90.3 mAP on Market1501 for ReID, and 85.8 JI on CrowdHuman for pedestrian detection, performing better than specialized models tailored for each task., Comment: Accepted for publication at the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 (CVPR 2023)

Human-centric perceptions include a variety of vision tasks, which have widespread industrial applications, including surveillance, autonomous driving, and the metaverse. It is desirable to have a general pretrain model for versatile human-centric downstream tasks. This paper forges ahead along this path from the aspects of both benchmark and pretraining methods. Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting. To learn both coarse-grained and fine-grained knowledge in human bodies, we further propose a \textbf{P}rojector \textbf{A}ssis\textbf{T}ed \textbf{H}ierarchical pretraining method (\textbf{PATH}) to learn diverse knowledge at different granularity levels. Comprehensive evaluations on HumanBench show that our PATH achieves new state-of-the-art results on 17 downstream datasets and on-par results on the other 2 datasets. The code will be publicly at \href{https://github.com/OpenGVLab/HumanBench}{https://github.com/OpenGVLab/HumanBench}., Comment: Accepted to CVPR2023

Long COVID hinders people from normal life and work, posing significant medical and economic challenges. Nevertheless, comprehensive studies assessing its impact on large populations in Asia are still lacking. We tracked over 20,000 patients infected with COVID-19 for the first time during the Omicron BA.2 outbreak in Shanghai from March-June 2022 for one year. Of the 21,799 COVID-19 patients who participated in the 6-month telephone follow-up, 1939 (8.89%) had self-reported long COVID symptoms. 450 long COVID patients participated in the 6-month outpatient follow-up. Participants underwent healthy physical examinations and questionnaires focused on long-COVID-related symptoms and mental health. Mobility problem (P < 0.001), personal care problem (P = 0.003), usual activity problem (P < 0.001), pain/discomfort (P < 0.001), anxiety/depression (P = 0.001) and PTSD (P = 0.001) were more prevalent in long COVID patients than in healthy individuals, but no significant differences were found between the two groups on chest CT and laboratory examinations. Of the 856 long COVID patients who participated in the 12-month follow-up, 587 (68.5%) had their symptoms resolved. In the multivariable logistic analysis, females (P < 0.001), youth (age P < 0.001), ≥ 2 comorbidities (P = 0.009), and severe infection in the acute phase (P = 0.006) were risk factors for developing long COVID. Middle age (40–60 years) was a risk factor for persistent long COVID one year after hospital discharge (P = 0.013). The study found that long COVID mainly manifested as subjective symptoms and impacts partial patients’ quality of life and mental status. After one year, most (68.5%) of the patients recovered from long COVID with no impairment of organ function observed.

We propose ADCLR: A ccurate and D ense Contrastive Representation Learning, a novel self-supervised learning framework for learning accurate and dense vision representation. To extract spatial-sensitive information, ADCLR introduces query patches for contrasting in addition with global contrasting. Compared with previous dense contrasting methods, ADCLR mainly enjoys three merits: i) achieving both global-discriminative and spatial-sensitive representation, ii) model-efficient (no extra parameters in addition to the global contrasting baseline), and iii) correspondence-free and thus simpler to implement. Our approach achieves new state-of-the-art performance for contrastive methods. On classification tasks, for ViT-S, ADCLR achieves 77.5% top-1 accuracy on ImageNet with linear probing, outperforming our baseline (DINO) without our devised techniques as plug-in, by 0.5%. For ViT-B, ADCLR achieves 79.8%, 84.0% accuracy on ImageNet by linear probing and finetune, outperforming iBOT by 0.3%, 0.2% accuracy. For dense tasks, on MS-COCO, ADCLR achieves significant improvements of 44.3% AP on object detection, 39.7% AP on instance segmentation, outperforming previous SOTA method SelfPatch by 2.2% and 1.2%, respectively. On ADE20K, ADCLR outperforms SelfPatch by 1.0% mIoU, 1.2% mAcc on the segme

Recent text-to-image generative models can generate high-fidelity images from text inputs, but the quality of these generated images cannot be accurately evaluated by existing evaluation metrics. To address this issue, we introduce Human Preference Dataset v2 (HPD v2), a large-scale dataset that captures human preferences on images from a wide range of sources. HPD v2 comprises 798,090 human preference choices on 430,060 pairs of images, making it the largest dataset of its kind. The text prompts and images are deliberately collected to eliminate potential bias, which is a common issue in previous datasets. By fine-tuning CLIP on HPD v2, we obtain Human Preference Score v2 (HPS v2), a scoring model that can more accurately predict text-generated images' human preferences. Our experiments demonstrate that HPS v2 generalizes better than previous metrics across various image distributions and is responsive to algorithmic improvements of text-to-image generative models, making it a preferable evaluation metric for these models. We also investigate the design of the evaluation prompts for text-to-image generative models, to make the evaluation stable, fair and easy-to-use. Finally, we establish a benchmark for text-to-image generative models using HPS v2, which includes a set of recent text-to-image models from the academia, community and industry. The code and dataset is / will be available at https://github.com/tgxs002/HPSv2., Comment: 19 pages, 10 figures

The certification of immunogenicity consistency at different production scales is indispensable for the quality control of vaccines. A randomized, double-blind immunobridging trial in healthy adults aged 18–59 was divided into Scale A (50 L and 800 L) and Scale B (50 L and 500 L) based on vaccine manufacturing scales. Eligible participants in Scale A were randomly assigned to receive the single-dose recombinant adenovirus type-5 vectored COVID-19 vaccine (Ad5-nCoV) of different scales at a 1:1 ratio, as was Scale B. The primary endpoint was the geometric mean titer (GMT) of anti-live SARS-CoV-2-specific neutralizing antibodies (NAb) 28 days post-vaccination. 1,012 participants were enrolled, with 253 (25%) per group. The post-vaccination GMTs of NAb were 10.72 (95% CI: 9.43, 12.19) and 13.23 (11.64, 15.03) in Scale A 50 L and 800 L, respectively; 11.64 (10.12, 13.39) and 12.09 (10.48, 13.95) in Scale B 50 L and 500 L, respectively. GMT ratios in Scale A and B have a 95% CI of 0.67–1.5. Most adverse reactions were mild or moderate. 17 of 18 participants reported non-vaccination-related serious adverse reactions. The Ad5-nCoV in the scale-up production of 500 L and 800 L showed consistent immunogenicity with the original 50 L production scale, respectively.

Rice blast disease caused by fungus Magnaporthe oryzae (syn. Pyricularia oryzae) is one of the most damaging diseases of rice, reducing plant production worldwide. In the present study, Bacillus subtilis strain GB519 was identified from the rhizosphere based on predicted signatures of 16S ribosomal DNA and gyrA gene and morphological, biochemical, and physiological characteristics. Treated with B. subtilis GB519, rice plants exhibited increased germination rate, vigor index, shoot length, shoot fresh weight, and root fresh weight coupled with more production of indole acetic acid, organic phosphorus, and inorganic phosphorus. In culture, GB519 inhibited growth of the following rice fungal pathogens (in order from most effective to least effective): M. oryzae, Ustilaginoidea virens, Fusarium graminearum, F. moniliforme, F. oxysporum, and Rhizoctonia solani. Three years of studies showed that, when rice was sprayed with GB519, there were significant reductions in rice blast incidence in both the greenhouse and fields: 70.3 and 62.1% in 2017, 69.9 and 71.6% in 2018, and 75.1 and 75.6% in 2019, respectively. Such reductions were correlated with accumulated hydrolytic enzymes, including amylases, proteases, chitinase, and lipases, and the defense enzyme activity of the total antioxidant capacity, catalase, and superoxide dismutase in rice. Field experiments showed that the biocontrol efficacy of GB519 was similar to that of other biological and chemical fungicides. Our results indicate that B. subtilis strain GB519 promoted plant growth and reduced blast disease and suggest that this strain has potential to be used as a biological control agent against rice blast. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Antibiotic resistance genes (ARGs) are emerging contaminants that pose a health risk to humans worldwide. Little information on ARGs in bee honey is available. This study profiles ARGs in bee honey samples produced in China, the biggest producer in the world. Of 317 known ARGs encoding resistance to 8 classes of antibiotics, 212 were found in collected honey samples by a real-time quantitative polymerase chain reaction approach. Occurrence frequencies of genes providing resistance to FCA (fluoroquinolone, quinolone, florfenicol, chloramphenicol, and amphenicol) and aminoglycosides were 21.0% and 18.5%, respectively. Frequencies of genes encoding efflux pumps were 42.5% and those of destructase genes 36.6%, indicating that these two mechanisms were predominant for resistance. Nine plasmid-mediated quinolone resistance genes were detected. Of the nine transposase genes known to be involved in antibiotic resistance, eight were found in the samples examined, with

A new aerobic bacterial strain, designated strain YIM B02290

Neuromyelitis optica spectrum disorders (NMOSD) are autoimmune, astrocytopathic diseases affecting the central nervous system(CNS), especially the central optic nerve and spinal cord. Aquaporin 4-immunoglobulin G (AQP4-IgG) is the dominant pathogenic antibody and can be detected in about 80% of patients with NMOSD. Although only a few cases were reported on NMOSD associated with cancer, they demonstrated the potential paraneoplastic link between cancer and NMOSD. In the present study, we report three NMOSD cases associated with cancer, which are teratoma and lung adenocarcinoma, teratoma, and transverse colon adenocarcinoma, respectively. Pathological staining of tumor sections revealed a high AQP4 expression. After tumor removal, all cases were stable and suffered no further relapses, which revealed the potential paraneoplastic mechanism between cancer and NMOSD. One of our patient's serum AQP4-IgG was transiently slightly elevated even though AQP4 was highly expressed in tumor cells, which indicates that AQP4 is not the main pathogenic antibody but might be induced by other underlying pathogenic antibody–antigen reactions.

Single-Photon Avalanche Detector (SPAD) arrays are a rapidly emerging technology. These multi-pixel sensors have single-photon sensitivities and pico-second temporal resolutions thus they can rapidly generate depth images with millimeter precision. Such sensors are a key enabling technology for future autonomous systems as they provide guidance and situational awareness. However, to fully exploit the capabilities of SPAD array sensors, it is crucial to establish the quality of depth images they are able to generate in a wide range of scenarios. Given a particular optical system and a finite image acquisition time, what is the best-case depth resolution and what are realistic images generated by SPAD arrays? In this work, we establish a robust yet simple numerical procedure that rapidly establishes the fundamental limits to depth imaging with SPAD arrays under real world conditions. Our approach accurately generates realistic depth images in a wide range of scenarios, allowing the performance of an optical depth imaging system to be established without the need for costly and laborious field testing. This procedure has applications in object detection and tracking for autonomous systems and could be easily extended to systems for underwater imaging or for imaging around corners.

By implementing NMR, inductively coupled plasma-atomic emission spectrometry (ICP-AES), and the UV–vis spectroscopic techniques, metabolites, mineral elements, and antioxidant activities (DPPH) of Peganum harmala L. samples from Manasi and Fuhai of Xinjiang were studied in this research to investigate the geographical environment impact at the molecular level. First of all, partial least squares discriminant analysis was conducted to explore differential endogenous metabolites. A total of 18 metabolites were identified, and 14 mineral element contents were calculated quantitatively, which displayed diverse changing trends from these two origins. Valine, succinic acid, betaine, sucrose, and vasicine exhibited significant differences between these two groups as well as mineral nutrient profiles (Mg, Cu, N, K, Na, P, Zn, C) and DPPH antioxidant activities (EC50). The obvious different characteristics of chemical components and antioxidant activities in these two groups were further verified by heat map cluster analysis. Pearson correlation analysis also revealed the remarkable relationship of chemical components and antioxidant activities, which are strongly associated with the regional environment. This study showed that the combination of methodologies proposed will be highly useful in evaluating the environmental variation and diversity in terrestrial ecosystems.

Currently, Radio Frequency Identification (RFID) is one of the key technologies to realize the Internet of Things (IoT), which is widely used in our daily life. However, there are some security threats such as impersonation attack, replay attack in existed RFID systems. In addition, most physical-layer authentication methods for RFID systems are mainly to authenticate tags without authenticating the user. In this paper, we present the design and implementation of Au-Hota, a system that can authenticate the tag and the user simultaneously, and can resist replaying attack and impersonation attack that cannot be solved by most physical-layer methods. Our idea is to assign a unique identifier to the user based on the inductive coupling between two adjacent tags. When the user draws the identity identifier on the tag, different identity identifiers correspond to unique phase features so that simultaneous authentication of the tag and the user can be achieved under the premise of ensuring security. The system is fully compatible with Ultra High Frequency (UHF) RFID systems without any modification. We implement a prototype of the system and conduct extensive experiments to evaluate performance. Our results demonstrate that the system has good authentication performance.

Enhanced recovery after surgery (ERAS) measures have not been systematically applied in transurethral surgery for benign prostatic hyperplasia (BPH). This study was performed on patients with BPH who required surgical intervention. From July 2019 to June 2020, the ERAS program was applied to 248 patients, and the conventional program was applied to 238 patients. After 1 year of follow-up, the differences between the ERAS group and the conventional group were evaluated. The ERAS group had a shorter time of urinary catheterization compared with the conventional group (mean ± standard deviation [s.d.]: 1.0 ± 0.4 days vs 2.7 ± 0.8 days, P0.01), and the pain (mean ± s.d.) was significantly reduced through postoperative hospitalization days (PODs) 0-2 (POD 0: 1.7 ± 0.8 vs 2.4 ± 1.0, P0.01; POD 1: 1.6 ± 0.9 vs 3.5 ± 1.3, P0.01; POD 2: 1.2 ± 0.7 vs 3.0 ± 1.3, P0.01). No statistically significant difference was found in the rate of postoperative complications, such as postoperative bleeding (P = 0.79), urinary retention (P = 0.40), fever (P = 0.55), and readmission (P = 0.71). The hospitalization cost of the ERAS group was similar to that of the conventional group (mean ± s.d.: 16 927.8 ± 5808.1 Chinese Yuan [CNY] vs 17 044.1 ± 5830.7 CNY, P =0.85). The International Prostate Symptom Scores (IPSS) and quality of life (QoL) scores in the two groups were also similar when compared at 1 month, 3 months, 6 months, and 12 months after discharge. The ERAS program we conducted was safe, repeatable, and efficient. In conclusion, patients undergoing the ERAS program experienced less postoperative stress than those undergoing the conventional program.

Increasing evidence have shown that regional lymph node metastasis is a critical prognostic factor in gastric cancer (GC). In addition, lymph node dissection is a key factor in determining the appropriate treatment for GC. However, the association between the number of positive lymph nodes and area of lymph node metastasis in GC remains unclear.To investigate the clinical value of regional lymph node sorting after radical gastrectomy for GC.This study included 661 patients with GC who underwent radical gastrectomy at Tianjin Medical University General Hospital between January 2012 and June 2020. The patients were divided into regional sorting and non-sorting groups. Clinicopathological data were collected and retrospectively reviewed to determine the differences in the total number of lymph nodes and number of positive lymph nodes between the groups. Independent sampleThere were no significant differences between the groups in terms of the surgical method, tumor site, immersion depth, and degree of differentiation. The total number of lymph nodes was significantly higher in the regional sorting group (Regional sorting of lymph nodes after radical gastrectomy may increase the number of detected lymph nodes, thereby improving the reliability and accuracy of lymph node staging in clinical practice.

ObjectiveExamine if the gut microbiota composition changes across repeated samples in paediatric-onset multiple sclerosis (MS) or monophasic-acquired demyelinating syndromes (monoADS).MethodsA total of 36 individuals (18 MS/18 monoADS) with ⩾2 stool samples were included. Stool sample-derived DNA was sequenced. Alpha/beta diversities and genus-level taxa were analysed.ResultsMean ages at first sample procurement (MS/monoADS) = 18.0/13.8 years. Median time (months) between first/second samples = 11.2 and second/third = 10.3. Alpha/beta diversities did not differ between stool samples (p > 0.09), while one genus - Solobacterium did (p = 0.001).ConclusionsThe gut microbiota composition in paediatric-onset MS and monoADS exhibited stability, suggesting that single stool sample procurement is a reasonable first approach.

BackgroundFat Mass and Obesity-Associated (FTO) and the Melanocortin-4 Receptor (MC4R) genes are strongly associated with obesity, an established risk factor for stroke. We aimed to assess the associations between rs17817449 at the FTO and rs6567160 at the MC4R and the risk of stroke events in middle-aged and older Chinese people.Materials and methodsStudy data were obtained from the Guangzhou Biobank Cohort Study; a total of 148 participants with a self-reported history of stroke and an equal volume of age- and sex-matched participants were selected as the cases and the controls in a case-control study; a total of 13,967 participants at the first follow-up and all participants with fatal stroke (up to April 2021) were included in a retrospective cohort study. Conditional logistic regression and the Cox proportional hazards regression analyses were used to assess the associations of the two genetic loci with the risk of stroke events.ResultsAfter adjusting for age, sex, education, job, smoking, alcohol consumption, body mass index, physical activity, hypertension, diabetes, and dyslipidemia, rs17817449 and rs6567160 shared minor alleles G and C, respectively, in the case-control analyses. The genotypes GG+GT of rs17817449 at the FTO were significantly associated with a decreased risk of fatal stroke occurrence, with fatal all strokes having an adjusted hazard ratio (aHR) of 0.71 (95% confidence intervals (CI) 0.52-0.97, P = 0.04) and fatal ischemic stroke having an aHR of 0.64 (95% CI 0.41–1.00, P = 0.05), when the genotype TT was taken as a reference and a series of multiplicities were adjusted; the risk of fatal all strokes was lowered by dyslipidemia (aHR = 0.63, 95% CI 0.39–1.00, P = 0.05) and non–diabetes (aHR = 0.68, 95% CI 0.46–0.99, P = 0.049) in the retrospective cohort analyses. Significances were observed neither in the associations between rs6567160 and the risk of stroke events nor in an interaction between rs17817449 and rs6567160 in the two-stage analyses.ConclusionThe G allele of rs17817449 at the FTO, not rs6567160 at the MC4R, was associated with a decreased risk of fatal stroke occurrence; its functional role in stroke should be explored in relatively healthy middle-aged to older Chinese people.

ObjectiveAdult-onset hypogonadism (AOH) is a common disease for males >40 years old and is closely associated with age-related comorbidities. Phthalates are compounds widely used in a number of products with endocrine-disrupting effects. However, little is known about the association between exposure to phthalates and the risk of AOH. Thus, we conducted this study to explore the potential association using the 2013-2016 National Health and Nutrition Examination Survey (NHANES) data.MethodData on AOH and urinary phthalate metabolites were collected, and univariable and multivariable logistic regression analyses were adapted to evaluate the association. The concentrations of each metabolite were calculated and grouped according to their quartiles for the final analysis.ResultFinally, we found that the odds ratio (OR) increased with increased concentrations of di-(2-ethylhexyl) phthalate (DEHP) metabolites, including mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP). Simultaneously, a significant dose-dependent effect was also observed. The OR for the fourth quartile was highest among all three groups. Specifically, the ORs for the third quartile and fourth quartile were 1.774 and 1.858, respectively, in the MECPP group. For the MEHHP group, the OR increased from 1.580 for the second quartile to 1.814 for the fourth quartile. Similarly, the OR for the higher three quartiles varied from 1.424 to 1.715 in the MEOHP group.ConclusionThis study first revealed that there was a positive association between exposure to DEHP metabolites and the risk of AOH. These findings add limited evidence to study this topic, while further studies are needed to explain the potential molecular mechanisms.

ObjectivesTo examine the association of protein intake from different sources with cognitive decline.MethodsOur analysis included 3,083 participants aged 55–93 years from the China Health and Nutrition Survey. Cognition was assessed in 1997, 2000, 2004, 2006, and 2015. Diet intake was assessed using weighing methods in combination with 24-h dietary recalls for three consecutive days at each survey.ResultsParticipants consumed 13.94% of energy intake from total protein, with 11.47 and 2.47% from plant and animal sources, respectively. During a follow-up of 9 years, participants in quintile 5 of plant protein intake (% energy) had a higher risk [odds ratio (95% CI): 3.03 (1.22–7.53)] of cognitive decline compared with those in quintile 1. Higher animal protein intake (% total protein) was associated with a lower risk of cognitive decline [odds ratio (95% CI) for quintile 5 vs. quintile 1: 0.22 (0.07–0.71)]. Grains (plant source) protein intake was inversely but fish/shrimp and poultry (animal source) protein intake were positively associated with change in cognitive Z-score.ConclusionIncreasing animal protein consumption in a population with plant dominant diets may help to prevent cognitive decline.

The fiber Bragg grating sensor is widely used in strain monitoring of large metal structure and trend to replace the resistance strain gauge due to its advantages of strong stability, high measurement accuracy, multiple points measuring, strong environmental suitability and long transmission distance. The temperature-induced strain, which can have the same order of magnitudes as the mechanically-induced strain, will cause great errors in the strain monitoring. Therefore, the temperature compensation for the sensors is essential to guarantee the measurement accuracy. The existing theoretical models and experiment platforms for analyzing the temperature compensation are established by assuming that the testing temperature is constant. However, the surrounding temperature of some large metal structure is not stable, and the effect of temperature change cannot be neglected. This paper aims to establish an analytic model and an experiment platform to compare the temperature compensation of the fiber bragg grating sensor and the resistance strain gauge. The superiority of the temperature compensation for the fiber bragg grating sensor is verified. The result provides theoretical support for choosing the fiber bragg grating sensor in the long-time strain monitoring.

Summary In this paper, a low‐complexity detection method for uplink Multi‐User Multiple‐Input Multiple‐Output (MU‐MIMO) of multi‐beam satellite communication systems is studied. Firstly, we derive ...

A Gram-stain-negative, aerobic, rod-shaped bacteria strain, named YIM B01951

Wall-clock convergence time and communication load are key performance metrics for the distributed implementation of stochastic gradient descent (SGD) in parameter server settings. Communication-adaptive distributed Adam (CADA) has been recently proposed as a way to reduce communication load via the adaptive selection of workers. CADA is subject to performance degradation in terms of wall-clock convergence time in the presence of stragglers. This paper proposes a novel scheme named grouping-based CADA (G-CADA) that retains the advantages of CADA in reducing the communication load, while increasing the robustness to stragglers at the cost of additional storage at the workers. G-CADA partitions the workers into groups of workers that are assigned the same data shards. Groups are scheduled adaptively at each iteration, and the server only waits for the fastest worker in each selected group. We provide analysis and experimental results to elaborate the significant gains on the wall-clock time, as well as communication load and computation load, of G-CADA over other benchmark schemes., submitted for conference publication