Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS.

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Fabrication of Hollow and Hierarchical CuO Micro-Nano Cubes Wrapped by Reduced Graphene Oxide as a Prospective Anode for SIBs.

In this study, hollow and hierarchical CuO micro-nano cubes wrapped by reduced graphene oxide (H-CuO MNCs@rGO) were designed and successfully fabricated via a novel three-step wet-chemical method. Benefiting from its unique hollow and hierarchical micro-nano structures, H-CuO MNCs@rGO exhibited significantly enhanced electrochemical Na+ storage performance when utilized as anode material for sodium-ion batteries (SIBs). Specifically, H-CuO MNCs@rGO demonstrated a specific capacity of 380.9 mAh g-1 in the initial reversible cycle and a capacity retention of 218.9 mAh g-1 after 150 cycles at a current density of 300 mA g-1. Furthermore, through the dominant pseudocapacitive behavior, an optimized rate capability of 221.2 mAh g-1 at 800 mA g-1 can be obtained for H-CuO MNCs@rGO. The comprehensive Na+ storage properties of H-CuO MNCs@rGO obviously exceeded those of hollow CuO cubes (H-CuO MNCs) and bulk CuO anodes. Such enhanced Na+ storage performances of H-CuO MNCs@rGO can be attributed to its reasonable hollow and hierarchical micro-nano structures, which provide abundant redox active sites, shorten Na+ migration pathway, buffer volume expansion, and improve electronic/ionic conductivity during sodiation/desodiation process. Our strategy provides a facile and innovative approach for the design of CuO with rational micro-nano structure as a high-performance anode for SIBs, which would also be a guiding way for tailoring transition metal oxides in other scalable and functional applications.

Chromone-deferiprone hybrids as novel MAO-B inhibitors and iron chelators for the treatment of Alzheimer's disease.

A series of chromone-deferiprone hybrids were designed, synthesized, and evaluated as inhibitors of human monoamine oxidase B (hMAO-B) with iron-chelating activity for the treatment of Alzheimer's disease (AD). The majority exhibited moderate inhibitory activity towards hMAO-B and potent iron-chelating properties. Particularly, compound 25c demonstrated remarkable selectivity against hMAO-B with an IC50 value of 1.58 µM and potent iron-chelating ability (pFe3+ = 18.79) comparable to that of deferiprone (pFe3+ = 17.90). Molecular modeling and kinetic studies showed that 25c functions as a non-competitive hMAO-B inhibitor. According to the predicted results, compound 25c can penetrate the blood-brain barrier (BBB). Additionally, it has been proved to display significant antioxidant activity and the ability to inhibit neuronal ferroptosis. More importantly, compound 25c reduced the cognitive impairment induced by scopolamine and showed significant non-toxicity in short-term toxicity assays. In summary, compound 25c was identified as a potential anti-AD agent with hMAO-B inhibitory, iron-chelating and anti-ferroptosis activities.

Anisotropic sensing based on single ReS2flake for VOCs discrimination.

Selective and sensitive detection of volatile organic compounds (VOCs) holds paramount importance in real-world applications. This study proposes an innovative approach utilizing a single ReS2field-effect transistor (FET) characterized by distinct in-plane anisotropy, specifically tailored for VOC recognition. The unique responses of ReS2, endowed with robust in-plane anisotropic properties, demonstrate significant difference along thea-axis andb-axis directions when exposed to four kinds of VOCs: acetone, methanol, ethanol, and IPA. Remarkably, the responses of ReS2were significantly magnified under ultraviolet (UV) illumination, particularly in the case of acetone, where the response amplified by 10-15 times and the detection limit decreasing from 70 to 4 ppm compared to the dark conditions. Exploiting the discernible variances in responses along thea-axis andb-axis under both UV and dark conditions, the data points of acetone, ethanol, methanol and IPA gases were clearly separated in the principal component space without any overlap through principal component analysis, indicating that the single ReS2FET has a high ability to distinguish various gas species. The exploration of anisotropic sensing materials and light excitation strategies can be applied to a broad range of sensing platforms based on two-dimensional materials for practical applications.

Crystallization and electrochemical properties of KxV2O5 nano-ribbons obtained via a solvothermal process as a promising cathode for PIBs.

In this research, a series of K+-intercalated quasi-1D vanadium-based nano-ribbons (KxV2O5 NRs) were synthesized via a facile solvothermal method. The solvation and reductive effects of vanadium oxide precursors (V2O5 powder) on the crystallization and growth of KxV2O5 NRs were studied. Besides, post-heat treatment was performed to improve the crystallinity of KxV2O5 NRs. These KxV2O5 NRs were adopted as active cathodes for potassium-ion batteries (PIBs), whose K+ storage properties were systematically evaluated using various electrochemical methods. The relationship among the morphology, crystallinity, working voltage window and electrochemical reversible K+ storage performance of KxV2O5 NRs was studied and established. Results reveal that KxV2O5-HG, which was prepared via a solvothermal reaction involving a solvation process (using H2O2) and a proper reducing condition (proper dose of glucose) with V2O5 powder as the raw material, would be more beneficial for the reversible storage of K+ when used as the cathode for PIBs compared to other contrast samples. In addition, the enhanced crystallinity and slightly broadened working voltage window of KxV2O5-HG could hinder its long-term cycling stability upon repeated K+ insertions/extractions.

Adversarial multi-task underwater acoustic target recognition: Toward robustness against various influential factors.

Underwater acoustic target recognition based on passive sonar faces numerous challenges in practical maritime applications. One of the main challenges lies in the susceptibility of signal characteristics to diverse environmental conditions and data acquisition configurations, which can lead to instability in recognition systems. While significant efforts have been dedicated to addressing these influential factors in other domains of underwater acoustics, they are often neglected in the field of underwater acoustic target recognition. To overcome this limitation, this study designs auxiliary tasks that model influential factors (e.g., source range, water column depth, or wind speed) based on available annotations and adopts a multi-task framework to connect these factors to the recognition task. Furthermore, we integrate an adversarial learning mechanism into the multi-task framework to prompt the model to extract representations that are robust against influential factors. Through extensive experiments and analyses on the ShipsEar dataset, our proposed adversarial multi-task model demonstrates its capacity to effectively model the influential factors and achieve state-of-the-art performance on the 12-class recognition task.

Advancing robust underwater acoustic target recognition through multitask learning and multi-gate mixture of experts.

Underwater acoustic target recognition has emerged as a prominent research area within the field of underwater acoustics. However, the current availability of authentic underwater acoustic signal recordings remains limited, which hinders data-driven acoustic recognition models from learning robust patterns of targets from a limited set of intricate underwater signals, thereby compromising their stability in practical applications. To overcome these limitations, this study proposes a recognition framework called M3 (multitask, multi-gate, multi-expert) to enhance the model's ability to capture robust patterns by making it aware of the inherent properties of targets. In this framework, an auxiliary task that focuses on target properties, such as estimating target size, is designed. The auxiliary task then shares parameters with the recognition task to realize multitask learning. This paradigm allows the model to concentrate on shared information across tasks and identify robust patterns of targets in a regularized manner, thus, enhancing the model's generalization ability. Moreover, M3 incorporates multi-expert and multi-gate mechanisms, allowing for the allocation of distinct parameter spaces to various underwater signals. This enables the model to process intricate signal patterns in a fine-grained and differentiated manner. To evaluate the effectiveness of M3, extensive experiments were implemented on the ShipsEar underwater ship-radiated noise dataset. The results substantiate that M3 has the ability to outperform the most advanced single-task recognition models, thereby achieving the state-of-the-art performance.

Improving the microbiological safety and quality of aquatic products using nonthermal processing.

Spoilage and deterioration of aquatic products during storage are inevitable, posing significant challenges to their suitability for consumption and the sustainability of the aquatic products supply chain. Research on the nonthermal processing of fruit juices, probiotics, dairy products, and meat has demonstrated positive outcomes in preserving quality. This review examines specific spoilage bacteria species and mechanisms for various aquatic products and discusses the principles, characteristics, and applications of six nonthermal processing methods for bacterial inhibition to maintain microbiological safety and physicochemical quality. The primary spoilage bacteria groups differ among fish, crustaceans, and shellfish based on storage conditions and durations. Four metabolic pathways utilized by spoilage microorganisms-peptides and amino acids, nitrogen compounds, nucleotides, and carbohydrates-are crucial in explaining spoilage. Nonthermal processing techniques, such as ultrahigh pressure, irradiation, magnetic/electric fields, plasma, and ultrasound, can inactivate microorganisms, thereby enhancing microbiological safety, physicochemical quality, and shelf life. Future research may integrate nonthermal processing with other technologies (e.g., modified atmosphere packaging and omics) to elucidate mechanisms of spoilage and improve the storage quality of aquatic products.

Cyclooctatetraene-Embedded Carbon Nanorings.

With the prosperity of the development of carbon nanorings, certain topologically or functionally unique units-embedded carbon nanorings have sprung up in the past decade. Herein, we report the facile and efficient synthesis of three cyclooctatetraene-embedded carbon nanorings (COTCNRs) that contain three (COTCNR1 and COTCNR2) and four (COTCNR3) COT units in a one-pot Yamamoto coupling. These nanorings feature hoop-shaped segments of Gyroid (G-), Diamond (D-), and Primitive (P-) type carbon schwarzites. The conformations of the trimeric nanorings COTCNR1 and COTCNR2 are shape-persistent, whereas the tetrameric COTCNR3 possesses a flexible carbon skeleton which undergoes conformational changes upon forming host-guest complexes with fullerenes (C60 and C70), whose co-crystals may potentially serve as fullerene-based semiconducting supramolecular wires with electrical conductivities on the order of 10-7 S cm-1 (for C60⊂COTCNR3) and 10-8 S cm-1 (for C70⊂COTCNR3) under ambient conditions. This research not only describes highly efficient one-step syntheses of three cyclooctatetraene-embedded carbon nanorings which feature hoop-shaped segments of distinctive topological carbon schwarzites, but also demonstrates the potential application in electronics of the one-dimensional fullerene arrays secured by COTCNR3.

Helicobacter pylori-induced fibroblast-derived Serpin E1 promotes gastric cancer growth and peritoneal dissemination through p38 MAPK/VEGFA-mediated angiogenesis.

BACKGROUND: Fibroblasts, especially cancer-associated fibroblasts (CAFs), represent the predominant stromal cell population in the tumor microenvironment and have an important function in tumorigenesis by interacting with tumor cells. However, their interaction remains elusive in an inflammatory tumor microenvironment induced by Helicobacter pylori (H. pylori). METHODS: The expression of Serpin family E member 1 (Serpin E1) was measured in fibroblasts with or without H. pylori infection, and primary gastric cancer (GC) cells. Serpin E1 knockdown and overexpression fibroblasts were generated using Serpin E1 siRNA or lentivirus carrying Serpin E1. Co-culture models of fibroblasts and GC cells or human umbilical vein endothelial cells (HUVECs) were established with direct contact or the Transwell system. In vitro functional experiments and in vivo tumorigenesis assay were employed to study the malignant behaviors of GC cells interacting with fibroblasts. ELISA was used for quantifying the levels of Serpin E1 and VEGFA in the culture supernatant. The tube formation capacity of HUVECs was assessed using a tube formation assay. Recombinant human Serpin E1 (recSerpin E1), anti-Serpin E1 antibody, and a MAPK pathway inhibitor were utilized to treat HUVECs for elucidating the underlying molecular mechanisms. RESULTS: Serpin E1 was predominantly expressed in gastric CAFs. H. pylori infection significantly enhanced the expression and secretion of Serpin E1 by CAFs. Both fibroblast-derived Serpin E1 and recSerpin E1 enhanced the growth, invasion, and migration of GC cells, along with increased VEGFA expression and tube formation in HUVECs. Furthermore, the co-inoculation of GC cells and fibroblasts overexpressing Serpin E1 triggered the expression of Serpin E1 in cancer cells, which facilitated together xenograft tumor growth and peritoneal dissemination of GC cells in nude mice, with an increased expression of Ki67, Serpin E1, CD31 and/or VEGFA. These processes may be mediated by Serpin E1-induced migration and p38 MAPK/VEGFA-mediated angiogenesis of HUVECs. CONCLUSION: H. pylori infection induces Serpin E1 expression in fibroblasts, subsequently triggering its expression in GC cells through their interaction. Serpin E1 derived from these cells promotes the migration and p38 MAPK/VEGFA-mediated angiogenesis of HUVECs, thereby facilitating GC growth and peritoneal metastasis. Targeting Serpin E1 signaling is a potential therapy strategy for H. pylori-induced GC.

Assessing the causal association of pregnancy complications with diabetes and cardiovascular disease.

Background: To the best of our knowledge, numerous observational studies have linked pregnancy complications to increased risks of diabetes and cardiovascular disease (CVD), causal evidence remains lacking. Our aim was to estimate the association of adverse pregnancy outcomes with diabetes and cardiovascular diseases. Methods: A two-sample Mendelian randomization (MR) analysis was employed, which is not subject to potential reverse causality. Data for pregnancy complications were obtained from the FinnGen consortium. For primary analysis, outcome data on diabetes, related traits, stroke, and coronary heart disease (CHD) were extracted from the GWAS Catalog, MAGIC, MEGASTROKE, and CARDIoGRAMplusC4D consortium. The MAGIC and UKB consortium datasets were used for replication and meta-analysis. Causal effects were appraised using inverse variance weighted (IVW), weighted median (WM), and MR-Egger. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out (LOO) analysis and the funnel plot. Results: Genetically predicted gestational diabetes mellitus (GDM) was causally associated with an increased diabetes risk (OR=1.01, 95% CI=1-1.01, P<0.0001), yet correlated with lower 2-hour post-challenge glucose levels (OR=0.89, 95% CI=0.82-0.97, P=0.006). Genetic liability for pregnancy with abortive outcomes indicated decreased fasting insulin levels (OR=0.97, 95% CI=0.95-0.99, P=0.02), but potentially elevated glycated hemoglobin levels (OR=1.02, 95% CI=1.01-1.04, P=0.01). Additionally, hypertensive disorders in pregnancy was tentatively linked to increased risks of stroke (OR=1.11, 95% CI=1.04-1.18, P=0.002) and CHD (OR=1.3, 95% CI=1.2-1.4, P=3.11E-11). Gestational hypertension might have a potential causal association with CHD (OR=1.11, 95% CI=1.01-1.22, P=0.04). No causal associations were observed between preterm birth and diabetes, stroke, or CHD. Conclusion: The findings of this study provide genetic evidence that gestational diabetes, pregnancy with abortive outcomes, and hypertensive disorders in pregnancy may serve as early indicators for metabolic and cardiovascular risks. These insights are pivotal for the development of targeted screening and preventive strategies.

Association of circulating minerals and vitamins with pregnancy complications: a Mendelian randomization study.

Background: Though considerable studies suggesting connections between micronutrients and pregnancy complications, current evidence remains inconsistent and lacks causative confirmation. Our study aimed to explore the causal links between them with a two-sample Mendelian randomization (MR) analysis. Methods: Genome-wide association studies (GWAS) data for circulating micronutrients were sourced from GWAS Catalog consortium and PubMed, while data for pregnancy outcomes, including gestational diabetes mellitus (GDM), gestational hypertension (GH), spontaneous abortion (SA), preterm birth (PTB), and stillbirth (SB), were retrieved from the UK Biobank and FinnGen consortia. Causal effects were appraised using inverse variance weighted (IVW), weighted median (WM), and MR-Egger, followed by sensitivity analyses and meta-analysis for validation. Results: Genetically predicted higher vitamin E (OR = 0.993, 95% CI 0.987-0.998; p = 0.005) levels were inversely associated with SA risk. Consistent results were obtained in meta-analysis (OR = 0.99, 95% CI 0.99-1.00; p = 0.005). Besides, a potential positive causality between genetic predisposition to vitamin B12 and SB was identified in both IVW (OR = 0.974, 95% CI 0.953-0.996; p = 0.018) and WM analysis (OR = 0.965, 95% CI 0.939-0.993; p = 0.013). However, no causal relationships were observed between other analyzed circulating micronutrients and pregnancy complications. Conclusion: This study offers compelling evidence of causal associations between circulating levels of vitamins E, B12 and the risk of SA and SB, respectively. These findings are pivotal for pregnancy complications screening and prevention, potentially guiding clinical practice and public health policies toward targeted nutritional interventions.

Uplift of the Tibetan Plateau driven by mantle delamination from the overriding plate.

The geodynamic evolution of the Tibetan Plateau remains highly debated. Any model of its evolution must explain the plateau's growth as constrained by palaeo-altitude studies, the spatio-temporal distribution of magmatic activity, and the lithospheric mantle removal inferred from seismic velocity anomalies in the underlying mantle. Several conflicting models have been proposed, but none of these explains the first-order topographic, magmatic and seismic features self-consistently. Here we propose and test numerically an evolutionary model of the plateau that involves gradual peeling of the lithospheric mantle from the overriding plate and consequent mantle and crustal melting and uplift. We show that this model successfully reproduces the successive surface uplift of the plateau to more than 4 km above sea level and is consistent with the observed migration of magmatism and geometry of the lithosphere-asthenosphere boundary resulting from subduction of the Indian plate and delamination of the mantle lithosphere of the Eurasian plate. These comparisons indicate that mantle delamination from the overriding plate is the driving force behind the uplift of the Tibetan Plateau and, potentially, orogenic plateaus more generally.

Clinical rules of Acupoint selection for cancer pain opioid-induced constipation based on journal literature data mining: A systematic review.

Objective: To analyse and summarise the regularity of acupoint selection in the treatment of opioid-induced constipation (OIC) in patients with cancer pain using a data mining technique and provide a reference for clinical practice and more valuable treatment options. Methods: The acupoint prescription database for the treatment of OIC-related cancer pain was established by searching the relevant literature on randomised controlled trials involving acupoint therapy for OIC-related cancer pain in seven major databases, including the China National Knowledge Infrastructure, Wanfang and VIP Chinese scientific journal databases, from database establishment to December 31, 2022. The main therapeutic measures of acupoint prescription, frequency of acupoint use and its subordinate meridians and subordinate sites were then analysed. Through systematic clustering and association rule analysis, the core acupoint prescriptions and most commonly used acupoint compatibility of acupoint therapy for OIC-related cancer pain were obtained. Results: A total of 649 articles were retrieved, with 72 articles included after screening. The treatment measures were found to be mainly acupoint applications involving 28 acupoints, with a total frequency of 234. The three most frequently used acupoints were Shenque, Tianshu and Zusanli. The number of points used in the Foot-Yangming stomach meridian was the highest. Commonly used acupoints were mainly distributed in the abdomen. The compatibility of two commonly used acupoints was obtained through systematic clustering. Through association rule analysis, it was found that in the compatibility of acupoints, the strongest correlation was between Tianshu and Zusanli, and their frequency of application was the highest. Conclusion: Tianshu and Zusanli are the core acupoints for acupoint therapy in the treatment of OIC-related cancer pain, and the Shangjuxu-Zhigou-Zusanli, Qihai-Guanyuan and Zhongwan-Tianshu acupoints exhibit the highest compatibility. This study provides a reference for the clinical acupoint selection programme of acupuncture and moxibustion in the treatment of OIC-related cancer pain.

Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning.

Weakly supervised point cloud semantic segmentation methods that require 1% or fewer labels with the aim of realizing almost the same performance as fully supervised approaches have recently attracted extensive research attention. A typical solution in this framework is to use self-training or pseudo-labeling to mine the supervision from the point cloud itself while ignoring the critical information from images. In fact, cameras widely exist in LiDAR scenarios, and this complementary information seems to be highly important for 3D applications. In this paper, we propose a novel cross-modality weakly supervised method for 3D segmentation that incorporates complementary information from unlabeled images. We design a dual-branch network equipped with an active labeling strategy to maximize the power of tiny parts of labels and to directly realize 2D-to-3D knowledge transfer. Afterward, we establish a cross-modal self-training framework, which iterates between parameter updating and pseudolabel estimation. In the training phase, we propose cross-modal association learning to mine complementary supervision from images by reinforcing the cycle consistency between 3D points and 2D superpixels. In the pseudolabel estimation phase, a pseudolabel self-rectification mechanism is derived to filter noisy labels, thus providing more accurate labels for the networks to be fully trained. The extensive experimental results demonstrate that our method even outperforms the state-of-the-art fully supervised competitors with less than 1% actively selected annotations.

CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection.

Mirror detection is a challenging task since mirrors do not possess a consistent visual appearance. Even the Segment Anything Model (SAM), which boasts superior zero-shot performance, cannot accurately detect the position of mirrors. Existing methods determine the position of the mirror under hypothetical conditions, such as the correspondence between objects inside and outside the mirror, and the semantic association between the mirror and surrounding objects. However, these assumptions do not apply to all scenarios. For instance, there may be no corresponding real objects to the reflected objects in the scene, or it may be challenging to extract meaningful semantic associations in complex scenes. On the other hand, humans can easily recognize mirrors through the specular texture caused by materials. To mine mirror features in more general scenes, we propose a Cross-Space-Frequency Window Transformer (CSFwinformer) to extract spatial and frequency features for texture analysis. Specifically, we design a Spatial-Frequency Window Alignment module (SFWA) to calculate spatial-frequency feature affinities and learn the difference between mirror and non-mirror textures. We then propose a Dilated Window Attention (DWA) to extract global features to complement the limitation of window alignment. Besides, we propose a Cross-Modality Context Contrast module (CMCC) to fuse cross-modality features and global features, which enables information flow between different windows to take full advantage of cross-modality information. Extensive experiments show that our method performs favorably against state-of-the-art methods on three mirror detection benchmarks and significantly improved SAM performance on mirror detection. The code is available at https://github.com/wangsen99/CSFwinformer.

17ß-Estradiol protects female rats from bilateral oophorectomy-induced nonalcoholic fatty liver disease induced by improving linoleic acid metabolism alteration and gut microbiota disturbance.

After surgical or natural menopause, women face a high risk of nonalcoholic fatty liver disease (NAFLD), which can be diminished by hormone replacement therapy (HRT). The gut microbiota is subject to modulation by various physiological changes and the progression of diseases. This microbial ecosystem coexists symbiotically with the host, playing pivotal roles in immune maturation, microbial defense mechanisms, and metabolic functions essential for nutritional and hormone homeostasis. E2 supplementation effectively prevented the development of NAFLD after bilateral oophorectomy (OVX) in female rats. The changes in the gut microbiota such as abnormal biosynthetic metabolism of fatty acids caused by OVX were partially restored by E2 supplementation. The combination of liver transcriptomics and metabolomics analysis revealed that linoleic acid (LA) metabolism, a pivotal pathway in fatty acids metabolism was mainly manipulated during the induction and treatment of NAFLD. Further correlation analysis indicated that the gut microbes were associated with abnormal serum indicators and different LA metabolites. These metabolites are also closely related to serum indicators of NAFLD. An in vitro study verified that LA is an inducer of hepatic steatosis. The changes in transcription in the LA metabolism pathway could be normalized by E2 treatment. The metabolic perturbations of LA may directly and secondhand impact the development of NAFLD in postmenopausal individuals. This research focused on the sex-specific pathophysiology and treatment of NAFLD, providing more evidence for HRT and calling for the multitiered management of NAFLD.

Regulation of intracellular process by two-component systems: Exploring the mechanism of plasmid-mediated conjugative transfer.

Plasmid-mediated conjugative transfer facilitates the dissemination of antibiotic resistance, yet the comprehensive regulatory mechanisms governing this process remain elusive. Herein, we established pure bacteria and activated sludge conjugation system to investigate the regulatory mechanisms of conjugative transfer, leveraging metformin as an exogenous agent. Transcriptomic analysis unveiled that substantial upregulation of genes associated with the two-component system (e.g., AcrB/AcrA, EnvZ/Omp, and CpxA/CpxR) upon exposure to metformin. Furthermore, downstream regulators of the two-component system, including reactive oxygen species (ROS), cytoplasmic membrane permeability, and adenosine triphosphate (ATP) production, were enhanced by 1.7, 1.4 and 1.1 times, respectively, compared to the control group under 0.1 mg/L metformin exposure. Moreover, flow sorting and high-throughput sequencing revealed increased microbial community diversity among transconjugants in activated sludge systems. Notably, the antibacterial potential of human pathogenic bacteria (e.g., Bacteroides, Escherichia-Shigella, and Lactobacillus) was augmented, posing a potential threat to human health. Our findings shed light on the spread of antibiotic resistance bacteria and assess the ecological risks associated with plasmid-mediated conjugative transfer in wastewater treatment systems.

PIG: Prompt Images Guidance for Night-Time Scene Parsing.

Night-time scene parsing aims to extract pixel-level semantic information in night images, aiding downstream tasks in understanding scene object distribution. Due to limited labeled night image datasets, unsupervised domain adaptation (UDA) has become the predominant method for studying night scenes. UDA typically relies on paired day-night image pairs to guide adaptation, but this approach hampers dataset construction and restricts generalization across night scenes in different datasets. Moreover, UDA, focusing on network architecture and training strategies, faces difficulties in handling classes with few domain similarities. In this paper, we leverage Prompt Images Guidance (PIG) to enhance UDA with supplementary night knowledge. We propose a Night-Focused Network (NFNet) to learn night-specific features from both target domain images and prompt images. To generate high-quality pseudo-labels, we propose Pseudo-label Fusion via Domain Similarity Guidance (FDSG). Classes with fewer domain similarities are predicted by NFNet, which excels in parsing night features, while classes with more domain similarities are predicted by UDA, which has rich labeled semantics. Additionally, we propose two data augmentation strategies: the Prompt Mixture Strategy (PMS) and the Alternate Mask Strategy (AMS), aimed at mitigating the overfitting of the NFNet to a few prompt images. We conduct extensive experiments on four night-time datasets: NightCity, NightCity+, Dark Zurich, and ACDC. The results indicate that utilizing PIG can enhance the parsing accuracy of UDA. The code is available at https://github.com/qiurui4shu/PIG.

3D-Printed Origami Actuators for a Multianimal-Inspired Soft Robot with Amphibious Locomotion and Tongue Hunting.

The field of soft robotics is rapidly evolving, and there is a growing interest in developing soft robots with bioinspired features for use in various applications. This research presented the design and development of 3D-printed origami actuators for a soft robot with amphibious locomotion and tongue hunting capabilities. Two different types of programmable origami actuators were designed and manufactured, namely Z-shaped and twist tower actuators. In addition, two actuator variations were developed based on the Z-shaped actuator, including the pelvic fin and the coiling/uncoiling types. The Z-shaped actuators were used for the rear legs to facilitate the locomotion of the water-like frogs. Meanwhile, the twisted tower actuators were used for the rotation joints in the forelegs and for locomotion on land. The pelvic fin actuator was developed to imitate the land locomotion of the mudskipper, and the coiling/uncoiling actuator was designed for tongue hunting motion. The origami actuators and soft robot prototype were tested through a series of experiments, which showed that the robot was capable of efficiently moving in water and on land and performing tongue hunting motions. Our results demonstrate the effectiveness of these actuators in producing the desired motions and provide insights into the potential of applying 3D-printed origami actuators in the development of soft robots with bioinspired features.