Alterations in microbial communities and antibiotic resistance genes pre- and post-sludge bulking in a wastewater treatment plant.

Sludge bulking is a common issue in wastewater treatment plants (WWTPs) that can disrupt microbial communities and potentially impact the abundance and spread of antibiotic resistance genes (ARGs) within treatment systems. This study employed high-throughput 16S rRNA gene sequencing and metagenomic sequencing to examine the changes in microbial communities and ARGs in a WWTP during non-bulking and bulking periods. The results indicated that bacterial diversity decreased in bulking sludge while maintaining a high removal efficiency of conventional pollutants.

Cr3a, a candidate gene conferring fruit cracking resistance, was fine-mapped in an introgression line of Solanum lycopersicum L.

In the cultivation and production of tomato (Solanum lycopersicum L.), fruit cracking is a prevalent and detrimental issue that significantly impacts the esthetic quality and commercial value of the fruit. The complexity of the trait has resulted in a slow advancement in research aimed at identifying genes that influence tomato fruit cracking and the underlying regulatory mechanisms.

Screening for Resistant Germplasms and Quantitative Trait Locus Mapping of Resistance to Tomato Chlorosis Virus.

Tomato chlorosis virus (ToCV) is an emerging plant virus that poses a substantial threat to the cultivation of economically vital vegetable crops, particularly tomato (). Despite its substantial impact on crop yield, resistant or tolerant tomato germplasms have not been well documented, and the genetic basis of resistance to ToCV remains poorly understood. In this study, two wild accessions that were immune to ToCV and five accessions that were highly resistant to ToCV were identified from 58 tomato accessions.

Machine Learning-Driven Mass Discovery and High-Throughput Screening of Fluoroether-Based Electrolytes for High-Stability Lithium Metal Batteries.

Developing novel fluoroether electrolytes with high-voltage stability is an effective strategy to improve the performance of lithium metal batteries (LMB). However, the vast chemical space of fluoroether is underexplored due to the absence of effective tools to evaluate the potential used in high-voltage LMB. Herein, a framework was developed in combination of Voting ensemble algorithms and graph convolution neural network (GCNN), allowing the fast assessment of oxidative stability of non-aqueous liquid electrolytes, synthesizability of solvents as well as the solvation ability of them to dissolve lithium salts.

Lignin and Peptide Promote the Abundance and Activity of Arsenic Methylation Microbes in Paddy Soils.

Rice physiological straighthead disease is induced by microbially mediated arsenic methylation and usually regionally distributed in paddy soils. However, the biogeochemical mechanism underlying the geographic distribution of microbial communities harboring methylating genes () remains unclear. Herein, we revealed significant ( = 0.

Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.

With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited availability of colonoscopy images due to regulatory restrictions and privacy concerns. In this paper, we propose a method for rendering high-fidelity 3D colon models and synthesizing diversified colonoscopy images with abnormalities such as polyps, bleeding, and ulcers, which can be used to train deep learning models.

Arsenic Reduces Methane Emissions from Paddy Soils: Insights from Continental Investigation and Laboratory Incubations.

Arsenic (As) contamination and methane (CH) emissions co-occur in rice paddies. However, how As impacts CH production, oxidation, and emission dynamics is unknown. Here, we investigated the abundances and activities of CH-cycling microbes from 132 paddy soils with different As concentrations across continental China using metagenomics and the reverse transcription polymerase chain reaction.

Study on Structural Design and Motion Characteristics of Magnetic Helical Soft Microrobots with Drug-Carrying Function.

Magnetic soft microrobots have a wide range of applications in targeted drug therapy, cell manipulation, and other aspects. Currently, the research on magnetic soft microrobots is still in the exploratory stage, and most of the research focuses on a single helical structure, which has limited space to perform drug-carrying tasks efficiently and cannot satisfy specific medical goals in terms of propulsion speed. Therefore, balancing the motion speed and drug-carrying performance is a current challenge to overcome.

Organic fertilization co-selects genetically linked antibiotic and metal(loid) resistance genes in global soil microbiome.

Antibiotic resistance genes (ARGs) and metal(loid) resistance genes (MRGs) coexist in organic fertilized agroecosystems based on their correlations in abundance, yet evidence for the genetic linkage of ARG-MRGs co-selected by organic fertilization remains elusive. Here, an analysis of 511 global agricultural soil metagenomes reveals that organic fertilization correlates with a threefold increase in the number of diverse types of ARG-MRG-carrying contigs (AMCCs) in the microbiome (63 types) compared to non-organic fertilized soils (22 types). Metatranscriptomic data indicates increased expression of AMCCs under higher arsenic stress, with co-regulation of the ARG-MRG pairs.

Super-resolution segmentation network for inner-ear tissue segmentation.

Cochlear implants (CIs) are considered the standard-of-care treatment for profound sensory-based hearing loss. Several groups have proposed computational models of the cochlea in order to study the neural activation patterns in response to CI stimulation. However, most of the current implementations either rely on high-resolution histological images that cannot be customized for CI users or CT images that lack the spatial resolution to show cochlear structures.

Protocol for building a user-friendly temperature control system to support microscopes, microfluidic chambers, and custom incubators.

Biological experiments require precise temperature control, necessitating an integrated adjustable temperature system for instruments such as microscopes, microfluidic chambers, or custom incubators. We present a protocol for building a user-friendly temperature control system suitable for both in vitro and in vivo assays. We describe steps for preparing materials, assembling the printed circuit board and enclosure, and fine-tuning the heating algorithm for accuracy.

Rapid and sensitive determination of Piroxicam by N-doped carbon dots prepared by plant soot.

Piroxicam (PX) as a nonsteroidal anti-inflammatory drug (NSAID) can be effectively used for anti-inflammatory and analgesia. However, overdoses may induce side effects such as gastrointestinal ulcers and headaches. Therefore, the assay of piroxicam has considerable significance.

EIF4A3-induced circZFAND6 promotes breast cancer proliferation and metastasis through the miR-647/FASN axis.

Aims: Circular RNAs (circRNAs) are important regulators in breast cancer progression. However, the underlying mechanism of circRNAs functions in breast cancer remain largely unclear.

Main Methods: To investigate the circRNAs expression pattern in breast cancer, high-throughput circRNA microarray assay was used.

Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation.

A common problem with segmentation of medical images using neural networks is the difficulty to obtain a significant number of pixel-level annotated data for training. To address this issue, we proposed a semi-supervised segmentation network based on contrastive learning. In contrast to the previous state-of-the-art, we introduce Min-Max Similarity (MMS), a contrastive learning form of dual-view training by employing classifiers and projectors to build all-negative, and positive and negative feature pairs, respectively, to formulate the learning as solving a MMS problem.

High stretchable and self-healing nanocellulose-poly(acrylic acid) composite hydrogels for sustainable CO shutoff.

The injection of CO into oil reservoirs to enhance oil recovery (EOR) has become a widely accepted and effective technical method, which, however, remains subject to the gas channeling caused by the reservoir fractures. Herein, this work developed a novel plugging gel combining excellent mechanical properties, fatigue resistance, elastic and self-healing properties for the CO shutoff purpose. This gel consisting of grafted nanocellulose and polymer network was synthesized via a free-radical polymerization, and reinforced by using Fe to cross-link the two networks.

A Bifunctional Fluorescence Probe Based on AIE-ICT Strategy for Visual Detection of Cu/Co in Complex Matrix.

A novel fluorescence chemical sensor-based probe 1-{[(E)-(2-aminophenyl)azanylidene]methyl}naphthalen-2-ol (AMN) was designed and synthesized, which performed a "naked eye" detection ability toward Cu and Co based on aggregation-induced emission (AIE) fluorescence strategy. It has sensitive detection ability for Cu and Co. In addition, the color changed from yellow-green to orange under the sunlight, realizing the rapid identification of Cu/Co, which has the potential of on-site visual detection under the "naked eye".

Occurrence of OCPs & PCBs and their effects on multitrophic biological communities in riparian groundwater of the Beiluo River, China.

Persistent Organic Pollutants (POPs) may exert adverse effects on human and ecosystem health. However, as an ecologically fragile zone with strong interaction between river and groundwater, the POPs pollution in the riparian zone has received little attention. The goal of this research is to examine the concentrations, spatial distribution, potential ecological risks, and biological effects of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in the riparian groundwater of the Beiluo River, China.

Surface deformation tracking in monocular laparoscopic video.

Image-guided surgery has been proven to enhance the accuracy and safety of minimally invasive surgery (MIS). Nonrigid deformation tracking of soft tissue is one of the main challenges in image-guided MIS owing to the existence of tissue deformation, homogeneous texture, smoke and instrument occlusion, etc. In this paper, we proposed a piecewise affine deformation model-based nonrigid deformation tracking method.

Fast Prediction of Lipophilicity of Organofluorine Molecules: Deep Learning-Derived Polarity Characters and Experimental Tests.

Fast and accurate estimation of lipophilicity for organofluorine molecules is in great demand for accelerating drug and materials discovery. A lipophilicity data set of organofluorine molecules (OFL data set), containing 1907 samples, is constructed through density functional theory (DFT) calculations and experimental measurements. An efficient and interpretable model, called PoLogP, is developed to predict the -octanol/water partition coefficient, log , of organofluorine molecules on the basis of the descriptors of polarization, which is a combination of polarity descriptors, including the molecular polarity index and molecular polarizability (α), and hydrogen bond (HBs) index, consisting of the number of donors () and acceptors ( and ).

Molecular partition coefficient from machine learning with polarization and entropy embedded atom-centered symmetry functions.

Efficient prediction of the partition coefficient (log ) between polar and non-polar phases could shorten the cycle of drug and materials design. In this work, a descriptor, named 〈 - ACSFs〉, is proposed to take the explicit polarization effects in the polar phase and the conformation ensemble of energetic and entropic significance in the non-polar phase into consideration. The polarization effects are involved by embedding the partial charge directly derived from force fields or quantum chemistry calculations into the atom-centered symmetry functions (ACSFs), together with the entropy effects, which are averaged according to the Boltzmann distribution of different conformations taken from the similarity matrix.

Real-time biomechanical modelling of the liver using LightGBM model.

Background: Accurate and real-time biomechanical modelling of the liver is a major challenge in computer-assisted surgery. Finite element method is often used to predict the deformation of organs for its high modelling accuracy. However, its high computation cost hinders its application in real time, such as virtual surgery simulations.