A review of distribution and functions of extracellular DNA in the environment and wastewater treatment systems.

Extracellular DNA refers to DNA fragments existing outside the cell, originating from various cell release mechanisms, including active secretion, cell lysis, and phage-mediated processes. Extracellular DNA serves as a vital environmental biomarker, playing crucial ecological and environmental roles in water bodies. This review is summarized the mechanisms of extracellular DNA release, including pathways involving cell lysis, extracellular vesicles, and type IV secretion systems. Then, the extraction and detection methods of extracellular DNA from water, soil, and biofilm are described and analyzed. Finally, we emphasize the role of extracellular DNA in microbial community systems, including its significant contributions to biofilm formation, biodiversity through horizontal gene transfer, and electron transfer processes. This review offers a comprehensive insight into the sources, distribution, functions, and impacts of extracellular DNA within aquatic environments, aiming to foster further exploration and understanding of extracellular DNA dynamics in aquatic environments as well as other environments.

Recovery strategies and mechanisms of anammox reaction following inhibition by environmental factors: A review.

Anaerobic ammonium oxidation (anammox) is a promising biological method for treating nitrogen-rich, low-carbon wastewater. However, the application of anammox technology in actual engineering is easily limited by environmental factors. Considerable progress has been investigated in recent years in anammox restoration strategies, significantly addressing the challenge of poor reaction performance following inhibition. This review systematically outlines the strategies employed to recover anammox performance following inhibition by conventional environmental factors and emerging pollutants. Additionally, comprehensive summaries of strategies aimed at promoting anammox activity and enhancing nitrogen removal performance provide valuable insights into the current research landscape in this field. The review contributes to a comprehensive understanding of restoration strategies of anammox-based technologies.

Adaptive Surface Normal Constraint for Geometric Estimation From Monocular Images.

We introduce a novel approach to learn geometries such as depth and surface normal from images while incorporating geometric context. The difficulty of reliably capturing geometric context in existing methods impedes their ability to accurately enforce the consistency between the different geometric properties, thereby leading to a bottleneck of geometric estimation quality. We therefore propose the Adaptive Surface Normal (ASN) constraint, a simple yet efficient method. Our approach extracts geometric context that encodes the geometric variations present in the input image and correlates depth estimation with geometric constraints. By dynamically determining reliable local geometry from randomly sampled candidates, we establish a surface normal constraint, where the validity of these candidates is evaluated using the geometric context. Furthermore, our normal estimation leverages the geometric context to prioritize regions that exhibit significant geometric variations, which makes the predicted normals accurately capture intricate and detailed geometric information. Through the integration of geometric context, our method unifies depth and surface normal estimations within a cohesive framework, which enables the generation of high-quality 3D geometry from images. We validate the superiority of our approach over state-of-the-art methods through extensive evaluations and comparisons on diverse indoor and outdoor datasets, showcasing its efficiency and robustness.

Effect of biochar on the SPNA system at ambient temperatures.

Biochar has been extensively studied in wastewater treatment systems. However, the role of biochar in the single-stage partial nitritation anammox (SPNA) system remains not fully understood. This study explored the impact of biochar on the SPNA at ambient temperatures (20 °C and 15 °C). The nitrogen removal rate of the system raised from 0.43 to 0.50 g N/(L·d) as the biochar addition was raised from 2 to 4 g/L. Metagenomic analysis revealed that gene abundances of amino sugar metabolism and nucleotide sugar metabolism, amino acid metabolism, and quorum sensing were decreased after the addition of biochar. However, the gene abundance of enzymes synthesizing NADH and trehalose increased, indicating that biochar could stimulate electron transfer reactions in microbial metabolism and assist microorganisms in maintaining a steady state at lower temperatures. The findings of this study provide valuable insights into the mechanism behind the improved nitrogen removal facilitated by biochar in the single-stage partial nitritation anammox system.

Real-world effects of Yishen Tongbi decoction for rheumatoid arthritis: protocol for a prospective, observational, multicenter cohort study with validation against double-blind, randomized, controlled trial.

Introduction: Rheumatoid arthritis (RA) is a globally challenging and refractory autoimmune disease, constituting a serious menace to human health. RA is characterized by recurrent pain and is difficult to resolve, necessitating prolonged medication for control. Yishen Tongbi decoction is a traditional Chinese herbal compound prescribed for treating RA. We have completed a 3-year RCT study that confirmed the clinical efficacy of Yishen Tongbi decoction for RA. Notably, we observed a faster clinical remission rate compared to MTX by week 4 of treatment. In our forthcoming study, we intend to conduct a comprehensive assessment of the efficacy and safety of Yishen Tongbi decoction in the real-world treatment of RA through a prospective study. Methods and analysis: This prospective, multicenter, real-world observational study will be conducted at two designated centers in China from October 2023 to August 2025. The study will include 324 patients with active rheumatoid arthritis. One group will receive Yishen Tongbi decoction combined with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). The other group will receive standard treatment. Standard treatment can be further divided into subgroups: csDMARDs, targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs), and biologic disease-modifying antirheumatic drugs (bDMARDs). In each group, the number of tender joints, number of swollen joints, pain score, patient global assessment, physician global assessment, disease activity index (DAS28-ESR or DAS28-CRP), clinical disease activity index (cDAI), simplified disease activity index (sDAI) and relevant laboratory data will be compared. Clinical indicators and disease activity of the patients will be assessed at baseline, week 4 and week 12 after the initiation of treatment. The primary outcome will be the American College of Rheumatology 20% improvement criteria (ACR20) attainment rate among patients at week 12 after treatment. Every adverse event will be reported. Ethics and dissemination: This study has been approved by the Ethics Committee of the first affiliated Hospital of Guangzhou University of traditional Chinese Medicine (NO.K-2023-009). The results of the study will be published in national and international peer-reviewed journals and at scientific conferences. The researchers will inform participants and other RA patients of the results through health education. Clinical Trial Registration: https://www.chictr.org.cn/index.html, identifier ChiCTR2300076073.

Model-based characterization of the equilibrium dynamics of transcription initiation and promoter-proximal pausing in human cells.

In metazoans, both transcription initiation and the escape of RNA polymerase (RNAP) from promoter-proximal pausing are key rate-limiting steps in gene expression. These processes play out at physically proximal sites on the DNA template and appear to influence one another through steric interactions. Here, we examine the dynamics of these processes using a combination of statistical modeling, simulation, and analysis of real nascent RNA sequencing data. We develop a simple probabilistic model that jointly describes the kinetics of transcription initiation, pause-escape, and elongation, and the generation of nascent RNA sequencing read counts under steady-state conditions. We then extend this initial model to allow for variability across cells in promoter-proximal pause site locations and steric hindrance of transcription initiation from paused RNAPs. In an extensive series of simulations, we show that this model enables accurate estimation of initiation and pause-escape rates. Furthermore, we show by simulation and analysis of real data that pause-escape is often strongly rate-limiting and that steric hindrance can dramatically reduce initiation rates. Our modeling framework is applicable to a variety of inference problems, and our software for estimation and simulation is freely available.

Extracellular polymeric substances and microbial community shift during the start-up of a single-stage partial nitritation/anammox process.

A sequencing batch reactor (SBR) was operated to investigate variations of extracellular polymeric substances (EPS) and microbial community during the start-up of the single-stage partial nitritation/anammox (SPN/A) process at intermittent aeration mode. The SPN/A system was successfully started on day 34, and the nitrogen removal efficiency and total nitrogen loading rate were 82.29% and 0.31 kg N/(m3 ·day), respectively. Furthermore, the relationship between the protein secondary structures and microbial aggregation was strongly related. The α-helix/ (ß-sheet + random coil) ratios increased obviously from 0.20 ± 0.03 to 0.23 ± 0.01, with the sludge aggregation mean size increased from 56 to 107 µm during the start-up of SPN/A. During the start-up of SPN/A, Candidatus Kuenenia was the primary anammox bacteria, whereas Nitrospira was the main functional bacteria of nitrite-oxidizing bacteria. Correlation between the microbial community and EPS components was performed. The EPS and microbial community played important roles in keeping stable nitrogen removal and the formation of sludge granules. PRACTITIONER POINTS: Intermittent aeration strategy promoted SPN/A system start-up. EPS composition and protein secondary structure were related with the sludge disintegration and aggregation. Microbial community shift existed and promoted the stability of sludge and reactor performance during SPN/A start-up.

Multimodal Image Synthesis and Editing: The Generative AI Era.

As information exists in various modalities in real world, effective interaction and fusion among multimodal information plays a key role for the creation and perception of multimodal data in computer vision and deep learning research. With superb power in modeling the interaction among multimodal information, multimodal image synthesis and editing has become a hot research topic in recent years. Instead of providing explicit guidance for network training, multimodal guidance offers intuitive and flexible means for image synthesis and editing. On the other hand, this field is also facing several challenges in alignment of multimodal features, synthesis of high-resolution images, faithful evaluation metrics, etc. In this survey, we comprehensively contextualize the advance of the recent multimodal image synthesis and editing and formulate taxonomies according to data modalities and model types. We start with an introduction to different guidance modalities in image synthesis and editing, and then describe multimodal image synthesis and editing approaches extensively according to their model types. After that, we describe benchmark datasets and evaluation metrics as well as corresponding experimental results. Finally, we provide insights about the current research challenges and possible directions for future research.

Neural Novel Actor: Learning a Generalized Animatable Neural Representation for Human Actors.

We propose a new method for learning a generalized animatable neural human representation from a sparse set of multi-view imagery of multiple persons. The learned representation can be used to synthesize novel view images of an arbitrary person and further animate them with the user's pose control. While most existing methods can either generalize to new persons or synthesize animations with user control, none of them can achieve both at the same time. We attribute this accomplishment to the employment of a 3D proxy for a shared multi-person human model, and further the warping of the spaces of different poses to a shared canonical pose space, in which we learn a neural field and predict the person- and pose-dependent deformations, as well as appearance with the features extracted from input images. To cope with the complexity of the large variations in body shapes, poses, and clothing deformations, we design our neural human model with disentangled geometry and appearance. Furthermore, we utilize the image features both at the spatial point and on the surface points of the 3D proxy for predicting person- and pose-dependent properties. Experiments show that our method significantly outperforms the state-of-the-arts on both tasks.

FEN1 inhibitor SC13 promotes CAR-T cells infiltration into solid tumours through cGAS-STING signalling pathway.

It is well known that chimeric antigen receptor T-cell immunotherapy (CAR-T-cell immunotherapy) has excellent therapeutic effect in haematological tumours, but it still faces great challenges in solid tumours, including inefficient T-cell tumour infiltration and poor functional persistence. Flap structure-specific endonuclease 1 (FEN1), highly expressed in a variety of cancer cells, plays an important role in both DNA replication and repair. Previous studies have reported that FEN1 inhibition is an effective strategy for cancer treatment. Therefore, we hypothesized whether FEN1 inhibitors combined with CAR-T-cell immunotherapy would have a stronger killing effect on solid tumours. The results showed that low dose of FEN1 inhibitors SC13 could induce an increase of double-stranded broken DNA (dsDNA) in the cytoplasm. Cytosolic dsDNA can activate the cyclic GMP-AMP synthase-stimulator of interferon gene signalling pathway and increase the secretion of chemokines. In vivo, under the action of FEN1 inhibitor SC13, more chemokines were produced at solid tumour sites, which promoted the infiltration of CAR-T cells and improved anti-tumour immunity. These findings suggest that FEN1 inhibitors could enable CAR-T cells to overcome poor T-cell infiltration and improve the treatment of solid tumours.

Qualitative and quantitative analysis of the chemical components in Yuquan capsules by using ultra-performance liquid chromatography-mass spectrometry.

The Yuquan capsules is a commonly used traditional Chinese Patent Medicine used for the treatment of diabetes mellitus. In this study, a high-throughput analytical method for identifying the chemical composition of Yuquan capsules was established for the first time by using ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry. The data obtained were subjected to fragment analysis and this was combined with UNIFI processing of natural products. One-hundred sixteen compounds were characterized from Yuquan capsules. Twelve of the bioactive compounds were quantitatively analyzed by ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry. This study was undertaken to obtain a comprehensive chemical profile analysis as well as to evaluate the overall quality of Yuquan capsules. The results will provide a reference for the quality evaluation of different Yuquan preparations. In addition, the data will enable basic pharmacodynamic research into these extensively used capsules.

A review of anammox metabolic response to environmental factors: Characteristics and mechanisms.

Anaerobic ammonium oxidation (anammox) is a promising low carbon and economic biological nitrogen removal technology. Considering the anammox technology has been easily restricted by environmental factors in practical engineering applications, therefore, it is necessary to understand the metabolic response characteristics of anammox bacteria to different environmental factors, and then guide the application of the anammox process. This review presented the latest advances of the research progress of the effects of different environmental factors on the metabolic pathway of anammox bacteria. The effects as well as mechanisms of conventional environmental factors and emerging pollutants on the anammox metabolic processes were summarized. Also, the role of quorum sensing (QS) mediating the bacteria growth, gene expression and other metabolic process in the anammox system were also reviewed. Finally, interaction and cross-feeding mechanisms of microbial communities in the anammox system were discussed. This review systematically summarized the variations of metabolic mechanism response to the external environment and cross-feeding interactions in the anammox process, which would provide an in-depth understanding for the anammox metabolic process and a comprehensive guidance for future anammox-related metabolic studies and engineering applications.

DNA-sequence and epigenomic determinants of local rates of transcription elongation.

Across all branches of life, transcription elongation is a crucial, regulated phase in gene expression. Many recent studies in eukaryotes have focused on the regulation of promoter-proximal pausing of RNA Polymerase II (Pol II), but rates of productive elongation also vary substantially throughout the gene body, both within and across genes. Here, we introduce a probabilistic model for systematically evaluating potential determinants of the local elongation rate based on nascent RNA sequencing (NRS) data. Our model is derived from a unified model for both the kinetics of Pol II movement along the DNA template and the generation of NRS read counts at steady state. It allows for a continuously variable elongation rate along the gene body, with the rate at each nucleotide defined by a generalized linear relationship with nearby genomic and epigenomic features. High-dimensional feature vectors are accommodated through a sparse-regression extension. We show with simulations that the model allows accurate detection of associated features and accurate prediction of local elongation rates. In an analysis of public PRO-seq and epigenomic data, we identify several features that are strongly associated with reductions in the local elongation rate, including DNA methylation, splice sites, RNA stem-loops, CTCF binding sites, and several histone marks, including H3K36me3 and H4K20me1. By contrast, low-complexity sequences and H3K79me2 marks are associated with increases in elongation rate. In an analysis of DNA k-mers, we find that cytosine nucleotides are strongly associated with reductions in local elongation rate, particularly when preceded by guanines and followed by adenines or thymines. Increases in elongation rate are associated with thymines and A+T-rich k-mers. These associations are generally shared across cell types, and by considering them our model is effective at predicting features of held-out PRO-seq data. Overall, our analysis is the first to permit genome-wide predictions of relative nucleotide-specific elongation rates based on complex sets of genomic and epigenomic covariates. We have made predictions available for the K562, CD14+, MCF-7, and HeLa-S3 cell types in a UCSC Genome Browser track.

Human breast milk-derived exosomes through inhibiting AT II cell apoptosis to prevent bronchopulmonary dysplasia in rat lung.

Human breast milk (HBM) effectively prevents and cures neonatal bronchopulmonary dysplasia (BPD). Exosomes are abundant in breast milk, but the function of HBM-derived exosomes (HBM-Exo) in BPD is still unclear. This study was to investigate the role and mechanism of HBM-Exo in BPD. Overall lung tissue photography and H&E staining showed that HBM-Exo improved the lung tissue structure collapse, alveolar structure disorder, alveolar septum width, alveolar number reduction and other injuries caused by high oxygen exposure. Immunohistochemical results showed that HBM-Exo improved the inhibition of cell proliferation and increased apoptosis caused by hyperoxia. qPCR and Western blot results also showed that HBM-Exo improved the expression of Type II alveolar epithelium (AT II) surface marker SPC. In vivo study, CCK8 and flow cytometry showed that HBM-Exo improved the proliferation inhibition and apoptosis of AT II cells induced by hyperoxia, qPCR and immunofluorescence also showed that HBM-Exo improved the down-regulation of SPC. Further RNA-Seq results in AT II cells showed that a total of 88 genes were significantly different between the hyperoxia and HBM-Exo with hyperoxia groups, including 24 up-regulated genes and 64 down-regulated genes. KEGG pathway analysis showed the enrichment of IL-17 signalling pathway was the most significant. Further rescue experiments showed that HBM-Exo improved AT II cell damage induced by hyperoxia through inhibiting downstream of IL-17 signalling pathway (FADD), which may be an important mechanism of HBM-Exo in the prevention and treatment of BPD. This study may provide new approach in the treatment of BPD.

Structure-Aware Long Short-Term Memory Network for 3D Cephalometric Landmark Detection.

Detecting 3D landmarks on cone-beam computed tomography (CBCT) is crucial to assessing and quantifying the anatomical abnormalities in 3D cephalometric analysis. However, the current methods are time-consuming and suffer from large biases in landmark localization, leading to unreliable diagnosis results. In this work, we propose a novel Structure-Aware Long Short-Term Memory framework (SA-LSTM) for efficient and accurate 3D landmark detection. To reduce the computational burden, SA-LSTM is designed in two stages. It first locates the coarse landmarks via heatmap regression on a down-sampled CBCT volume and then progressively refines landmarks by attentive offset regression using multi-resolution cropped patches. To boost accuracy, SA-LSTM captures global-local dependence among the cropping patches via self-attention. Specifically, a novel graph attention module implicitly encodes the landmark's global structure to rationalize the predicted position. Moreover, a novel attention-gated module recursively filters irrelevant local features and maintains high-confident local predictions for aggregating the final result. Experiments conducted on an in-house dataset and a public dataset show that our method outperforms state-of-the-art methods, achieving 1.64 mm and 2.37 mm average errors, respectively. Furthermore, our method is very efficient, taking only 0.5 seconds for inferring the whole CBCT volume of resolution 768×768×576 .

Glutamatergic receptor and neuroplasticity in depression: Implications for ketamine and rapastinel as the rapid-acting antidepressants.

PURPOSE OF REVIEW: To explore the convergent downstream pathways of ketamine and rapastinel and drive further development of identification for following generational rapid-acting antidepressants in the synaptic process. RECENT FINDINGS: Ketamine is an NMDAR antagonist and is proven effective in depression for the rapid and sustained antidepressant response, while rapastinel is an NMDAR positive allosteric modulator, producing antidepressant effects like ketamine with no severe side effects. The common antidepressant effects of ketamine and rapastinel are BDNF and mTORC1 pathway in synaptic plasticity.

Long-term effect of fulvic acid amendment on the anammox biofilm system at 15 ℃: performance, microbial community and metagenomics analysis.

The role of fulvic acid (FA) on the anammox system at 15 ℃ was investigated. After operation for 113 days, total inorganic nitrogen removal efficiency in FA amendment reactor achieved to 58.6% on average, higher than that of control group (42.1%). Anammox-related functional genes, i.e., hzo and hzs, also demonstrated higher expression level after introduction of FA. It was observed that Candidatus Kuenenia became more competitive than Candidatus Brocadia with the existence of FA at 15 ℃. Also, co-occurrence analysis showed that FA stimulated the complexity and interactive relationship of microbial communities in the anammox system. Metagenomics analysis revealed that FA introduction stimulated relative abundances of genes in central pathway of tricarboxylic acid cycle such as ACO, IDH, OGDH, SCS, FUM, and MDH. Meanwhile, metabolomics analysis revealed that metabolites related to amino sugar metabolic pathways (glucose 1-phosphate, UDP-D-glucuronate, UDP) and redox reactions (NAD+ and NADH) improved in the FA amendment reactor.

MulayCap: Multi-Layer Human Performance Capture Using a Monocular Video Camera.

We introduce MulayCap, a novel human performance capture method using a monocular video camera without the need for pre-scanning. The method uses "multi-layer" representations for geometry reconstruction and texture rendering, respectively. For geometry reconstruction, we decompose the clothed human into multiple geometry layers, namely a body mesh layer and a garment piece layer. The key technique behind is a Garment-from-Video (GfV) method for optimizing the garment shape and reconstructing the dynamic cloth to fit the input video sequence, based on a cloth simulation model which is effectively solved with gradient descent. For texture rendering, we decompose each input image frame into a shading layer and an albedo layer, and propose a method for fusing a fixed albedo map and solving for detailed garment geometry using the shading layer. Compared with existing single view human performance capture systems, our "multi-layer" approach bypasses the tedious and time consuming scanning step for obtaining a human specific mesh template. Experimental results demonstrate that MulayCap produces realistic rendering of dynamically changing details that has not been achieved in any previous monocular video camera systems. Benefiting from its fully semantic modeling, MulayCap can be applied to various important editing applications, such as cloth editing, re-targeting, relighting, and AR applications.

SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform.

Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Existing methods for 3D shape segmentation suffer from complex geometry processing and heavy computation caused by using low-level features and fragmented segmentation results due to the lack of global consideration. We present an efficient method, called SEG-MAT, based on the medial axis transform (MAT) of the input shape. Specifically, with the rich geometrical and structural information encoded in the MAT, we are able to develop a simple and principled approach to effectively identify the various types of junctions between different parts of a 3D shape. Extensive evaluations and comparisons show that our method outperforms the state-of-the-art methods in terms of segmentation quality and is also one order of magnitude faster.