Characterization of the exopolysaccharide produced by Pediococcus acidilactici S1 and its effect on the gel properties of fat substitute meat mince.

Exopolysaccharide produced by lactic acid bacteria has various functions. In the present study, one anti-oxidant polysaccharide fraction, namely S1-EPS, was extracted and purified from Pediococcus acidilactici S1, and its structure and its potential effect on the gel properties of fat substitute meat mince were investigated. The results showed that S1-EPS, one of homogeneous polysaccharides, was mainly composed of Gal, Glc, and Man in molar ratio of 7.61: 15.25: 77.13 and molecular weight of 46.975 kDa. The backbone of EPS-S1 contained →2,6)-α-D-Manp-(1→，→2)-α-D-Manp-(1→,→3)-α-D-Glcp-(1 → and a small amount of→6)-ß-D-Manp-(1→. The linkages of branches in EPS-S1 were mainly composed of α-D-Manp-(1→ attached to a sugar residue →2,6)-α-D-Manp-(1→O-2 or ß-D-Galp-(1→ attached to a sugar residue →2,6)-α-D-Manp-(1→O-6. Furthermore, as S1-EPS increased, the meat minced gel pores decreased, and the surface became smooth. A remarkable inhibitory effect on the lipid oxidation of meat minced gel was found as S1-EPS concentration increased. Overall, S1-EPS was found to have substantial potential in low-fat meat products by serving as a natural, anti-oxidant, and functional additive.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

Improved multi-ancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk.

Multi-ancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. However, existing approaches fail to reflect shared genetic architectures. To solve this limitation, we present the Sum of Shared Single Effects (SuShiE) model, which leverages LD heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations, and estimate ancestry-specific expression prediction weights. We apply SuShiE to mRNA expression measured in PBMCs (n=956) and LCLs (n=814) together with plasma protein levels (n=854) from individuals of diverse ancestries in the TOPMed MESA and GENOA studies. We find SuShiE fine-maps cis-molQTLs for 16% more genes compared with baselines while prioritizing fewer variants with greater functional enrichment. SuShiE infers highly consistent cis-molQTL architectures across ancestries on average; however, we also find evidence of heterogeneity at genes with predicted loss-of-function intolerance, suggesting that environmental interactions may partially explain differences in cis-molQTL effect sizes across ancestries. Lastly, we leverage estimated cis-molQTL effect-sizes to perform individual-level TWAS and PWAS on six white blood cell-related traits in AOU Biobank individuals (n=86k), and identify 44 more genes compared with baselines, further highlighting its benefits in identifying genes relevant for complex disease risk. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.

Tunneling Proton Grotthuss Transfer Channels by Hydrophilic-Zincophobic Heterointerface Shielding for High-Performance Zn-MnO2 Batteries.

Hollandite-type manganese dioxide (α-MnO2) is recognized as a promising cathode material upon high-performance aqueous zinc-ion batteries (ZIBs) owing to the high theoretical capacities, high working potentials, unique Zn2+/H+ co-insertion chemistry, and environmental friendliness. However, its practical applications limited by Zn2+ accommodation, where the strong coulombic interaction and sluggish kinetics cause significant lattice deformation, fast capacity degradation, insufficient rate capability, and undesired interface degradation. It remains challenging to accurately modulate H+ intercalation while suppressing Zn2+ insertion for better lattice stability and electrochemical kinetics. Herein, proton Grotthuss transfer channels are first tunneled by shielding MnO2 with hydrophilic-zincophobic heterointerface, fulfilling the H+-dominating diffusion with the state-of-the-art ZIBs performance. Local atomic structure and theoretical simulation confirm that surface-engineered α-MnO2 affords to the synergy of Mn electron t2g-eg activation, oxygen vacancy enrichment, selective H+ Grotthuss transfer, and accelerated desolvation kinetics. Consequently, fortified α-MnO2 achieves prominent low current density cycle stability (≈100% capacity retention at 1 C after 400 cycles), remarkable long-lifespan cycling performance (98% capacity retention at 20 C after 12 000 cycles), and ultrafast rate performance (up to 30 C). The study exemplifies a new approach of heterointerface engineering for regulation of H+-dominating Grotthuss transfer and lattice stabilization in α-MnO2 toward reliable ZIBs.

Modular Biomimetic Strategy Enables Discovery and SAR Exploration of Oxime Macrocycles as Influenza A Virus (H1N1) Inhibitors.

Although vaccination remains the prevalent prophylactic means for controlling Influenza A virus (IAV) infections, novel structural antivirus small-molecule drugs with new mechanisms of action for treating IAV are highly desirable. Herein, we describe a modular biomimetic strategy to expeditiously achieve a new class of macrocycles featuring oxime, which might target the hemagglutinin (HA)-mediated IAV entry into the host cells. SAR analysis revealed that the size and linker of the macrocycles play an important role in improving potency. Particularly, as a 14-membered macrocyclic oxime, 37 exhibited potent inhibitory activity against IAV H1N1 with an EC50 value of 23 nM and low cytotoxicity, which alleviated cytopathic effects and protected cell survival obviously after H1N1 infection. Furthermore, 37 showed significant synergistic activity with neuraminidase inhibitor oseltamivir in vitro.

Novel insights into dimethylsulfoniopropionate cleavage by deep subseafloor fungi.

Dimethylsulfoniopropionate (DMSP), a key organic sulfur compound in marine and subseafloor sediments, is degraded by phytoplankton and bacteria, resulting in the release of the climate-active volatile gas dimethylsulfide (DMS). However, it remains unclear if dominant eukaryotic fungi in subseafloor sediments possess specific abilities and metabolic mechanisms for DMSP degradation and DMS formation. Our study provides the first evidence that fungi from coal-bearing sediments ∼2 km below the seafloor, such as Aspergillus spp., Chaetomium globosum, Cladosporium sphaerospermum, and Penicillium funiculosum, can degrade DMSP and produce DMS. In Aspergillus sydowii 29R-4-F02, which exhibited the highest DMSP-dependent DMS production rate (16.95 pmol/µg protein/min), two DMSP lyase genes, dddP and dddW, were identified. Remarkably, the dddW gene, previously observed only in bacteria, was found to be crucial for fungal DMSP cleavage. These findings not only extend the list of fungi capable of degrading DMSP, but also enhance our understanding of DMSP lyase diversity and the role of fungi in DMSP decomposition in subseafloor sedimentary ecosystems.

Elucidation of genes enhancing natural product biosynthesis through co-evolution analysis.

Streptomyces has the largest repertoire of natural product biosynthetic gene clusters (BGCs), yet developing a universal engineering strategy for each Streptomyces species is challenging. Given that some Streptomyces species have larger BGC repertoires than others, we proposed that a set of genes co-evolved with BGCs to support biosynthetic proficiency must exist in those strains, and that their identification may provide universal strategies to improve the productivity of other strains. We show here that genes co-evolved with natural product BGCs in Streptomyces can be identified by phylogenomics analysis. Among the 597 genes that co-evolved with polyketide BGCs, 11 genes in the 'coenzyme' category have been examined, including a gene cluster encoding for the cofactor pyrroloquinoline quinone. When the pqq gene cluster was engineered into 11 Streptomyces strains, it enhanced production of 16,385 metabolites, including 36 known natural products with up to 40-fold improvement and several activated silent gene clusters. This study provides an innovative engineering strategy for improving polyketide production and finding previously unidentified BGCs.

Hybrid-Driven Origami Gripper with Variable Stiffness and Finger Length.

Soft grippers due to their highly compliant material and self-adaptive structures attract more attention to safe and versatile grasping tasks compared to traditional rigid grippers. However, those flexible characteristics limit the strength and the manipulation capacity of soft grippers. In this paper, we introduce a hybrid-driven gripper design utilizing origami finger structures, to offer adjustable finger stiffness and variable grasping range. This gripper is actuated via pneumatic and cables, which allows the origami structure to be controlled precisely for contraction and extension, thus achieving different finger lengths and stiffness by adjusting the cable lengths and the input pressure. A kinematic model of the origami finger is further developed, enabling precise control of its bending angle for effective grasping of diverse objects and facilitating in-hand manipulation. Our proposed design method enriches the field of soft grippers, offering a simple yet effective approach to achieve safe, powerful, and highly adaptive grasping and in-hand manipulation capabilities.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading.

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

Total ginsenosides extend healthspan of aging Drosophila by suppressing imbalances in intestinal stem cells and microbiota.

BACKGROUND: Disruption of stem cell and microbial homeostasis accelerates the aging process. Hence, maintaining these balances effectively delays aging and alleviates the symptoms of age-related diseases. Recent research indicates that targeting endoplasmic reticulum (ER) stress and immune deficiency (IMD) signalling may play a positive role in maintaining homeostasis in aging intestinal stem cells (ISC) and microbial equilibrium. Previous research has suggested that total ginsenosides (TG) derived from Panax ginseng C. A. Meyer may exhibit potential anti-aging properties by mitigating ER stress and mediating the IMD pathway. Nevertheless, it remains unclear whether TG improve ISC and microbial homeostasis by modulating ER stress and the IMD pathway to promote healthy aging. PURPOSE: To elucidate whether TG promotes healthspan in Drosophila and its underlying molecular mechanisms, focusing on its role in regulating ER stress and the IMD pathway to maintain ISC and intestinal microbiota homeostasis. METHODS: High performance liquid chromatography was performed to detect the main saponin monomer in TG. Survival rate, gut length, barrier function, and feeding/excretion behaviour assays were used to evaluate the effects of TG on the lifespan and gut health of Drosophila. At the stem cell level, "esg-luciferase" reporter system, esg-GFP/delta stem cell fluorescent labelling, and phospho-histone H3+ mitotic activity assays were employed to determine whether TG prevented natural aging or oxidative stress-associated ISC over-proliferation in Drosophila. Immunofluorescence staining was used to detect the effects of TG on ER stress during aging. Overexpression or interference of ER stress target genes and their related c-Jun N-terminal kinase (JNK) gene was manipulated using gene editing technology to verify the molecular mechanism by which TG maintains age-related ISC proliferation homeostasis. Molecular docking and isothermal titration calorimetry were used to verify the direct interactions between TG and ER stress target genes. In addition, at the intestinal flora level, 16S rDNA sequencing was used to analyse the effect of TG on the diversity and abundance of Drosophila intestinal flora and the possible functional pathways involved. RT-qPCR was performed to determine whether TG mediated the expression of target genes in the IMD pathway. A dominant bacterial species-specific mono-association analysis were performed to verify whether the effects of TG on IMD target genes and ISC proliferation depended on the direct control of the dominant bacterial species. RESULTS: Our results suggest that administration of TG delays the decline in gut morphology and function in aging Drosophila. TG prevents age-associated ISC hyperproliferation by inhibiting ER stress IRE1-mediated JNK signaling. Furthermore, oral TG prevented aging-associated ISC and gut microbiota dysbiosis by remodelling the gut microbiota and inhibiting Acetobacter-mediated activation of IMD target genes. CONCLUSION: TG promotes healthy aging by inhibiting the excessive proliferation of ISC and alleviating intestinal microbial imbalance, thereby providing new insights for the research and development of anti-aging TG products.

Identifying atomically thin isolated-band channels for intrinsic steep-slope transistors by high-throughput study.

Developing low-power FETs holds significant importance in advancing logic circuits, especially as the feature size of MOSFETs approaches sub-10 nanometers. However, this has been restricted by the thermionic limitation of SS, which is limited to 60 mV per decade at room temperature. Herein, we proposed a strategy that utilizes 2D semiconductors with an isolated-band feature as channels to realize sub-thermionic SS in MOSFETs. Through high-throughput calculations, we established a guiding principle that combines the atomic structure and orbital interaction to identify their sub-thermionic transport potential. This guides us to screen 192 candidates from the 2D material database comprising 1608 systems. Additionally, the physical relationship between the sub-thermionic transport performances and electronic structures is further revealed, which enables us to predict 15 systems with promising device performances for low-power applications with supply voltage below 0.5 V. This work opens a new way for the low-power electronics based on 2D materials and would inspire extensive interests in the experimental exploration of intrinsic steep-slope MOSFETs.

Ammonia marine engine design for enhanced efficiency and reduced greenhouse gas emissions.

Pilot-diesel-ignition ammonia combustion engines have attracted widespread attentions from the maritime sector, but there are still bottleneck problems such as high unburned NH3 and N2O emissions as well as low thermal efficiency that need to be solved before further applications. In this study, a concept termed as in-cylinder reforming gas recirculation is initiated to simultaneously improve the thermal efficiency and reduce the unburned NH3, NOx, N2O and greenhouse gas emissions of pilot-diesel-ignition ammonia combustion engine. For this concept, one cylinder of the multi-cylinder engine operates rich of stoichiometric and the excess ammonia in the cylinder is partially decomposed into hydrogen, then the exhaust of this dedicated reforming cylinder is recirculated into the other cylinders and therefore the advantages of hydrogen-enriched combustion and exhaust gas recirculation can be combined. The results show that at 3% diesel energetic ratio and 1000 rpm, the engine can increase the indicated thermal efficiency by 15.8% and reduce the unburned NH3 by 89.3%, N2O by 91.2% compared to the base/traditional ammonia engine without the proposed method. At the same time, it is able to reduce carbon footprint by 97.0% and greenhouse gases by 94.0% compared to the traditional pure diesel mode.

Pathway Evolution Through a Bottlenecking-Debottlenecking Strategy and Machine Learning-Aided Flux Balancing.

The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L-1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

Gold-copper-doped lanthanide luminescent metal-organic backbone induced self-enhanced molecularly imprinted ECL sensors for ultra-sensitive detection of chlorpyrifos.

Herein, a self-enhanced molecularly imprinted polymer luminescence (MIP-ECL) sensing platform based on gold-copper doped Tb-MOFs (Au@Cu:Tb-MOFs) was constructed for ultra-sensitive detection of chlorpyrifos (CPF). In this work, Au@Cu:Tb-MOFs as co-reaction promoters greatly improve the ECL emission signal, while Au@Cu:Tb-MOFs were used as cathode emitters. And chlorpyrifos and 4,7-bis(thiophene-2-yl)benzo [c][1,2,5] thiadiazole were electropolymerized on electrode surface to form MIP, where this films with thiophene derivatives could greatly improve ECL signal. Notably, the introduction of MIP as recognition elements enabled specific identification of target analytes, in which molecular docking technique validated target analyte and functional monomers are tightly bound through Pi-alkyl interaction. As the concentration of CPF increases, the ECL signal gradually decreases, showing a good linear relationship in the range of 0.1-106 pg/mL with a low detection limit (LOD) of 0.029 pg/mL. Moreover, actual sample testing experiment of this method displayed a special correlation in organophosphorus detection and development potential in actual sample analysis.

Design and Control of the Magnetically Actuated Micro/Nanorobot Swarm toward Biomedical Applications.

Recently, magnetically actuated micro/nanorobots hold extensive promises in biomedical applications due to their advantages of noninvasiveness, fuel-free operation, and programmable nature. While effectively promised in various fields such as targeted delivery, most past investigations are mainly displayed in magnetic control of individual micro/nanorobots. Facing practical medical use, the micro/nanorobots are required for the development of swarm control in a closed-loop control manner. This review outlines the recent developments in magnetic micro/nanorobot swarms, including their actuating fundamentals, designs, controls, and biomedical applications. The fundamental principles and interactions involved in the formation of magnetic micro/nanorobot swarms are discussed first. The recent advances in the design of artificial and biohybrid micro/nanorobot swarms, along with the control devices and methods used for swarm manipulation, are presented. Furthermore, biomedical applications that have the potential to achieve clinical application are introduced, such as imaging-guided therapy, targeted delivery, embolization, and biofilm eradication. By addressing the potential challenges discussed toward the end of this review, magnetic micro/nanorobot swarms hold promise for clinical treatments in the future.

Two-dimensional semiconductor transistors and integrated circuits for advanced technology nodes.

This Perspective aims to provide a concise survey of current progress and outlook future directions in high-performance transistors and integrated circuits (ICs) based on 2D semiconductors.

Whole-brain spatial organization of hippocampal single-neuron projectomes.

Mapping single-neuron projections is essential for understanding brain-wide connectivity and diverse functions of the hippocampus (HIP). Here, we reconstructed 10,100 single-neuron projectomes of mouse HIP and classified 43 projectome subtypes with distinct projection patterns. The number of projection targets and axon-tip distribution depended on the soma location along HIP longitudinal and transverse axes. Many projectome subtypes were enriched in specific HIP subdomains defined by spatial transcriptomic profiles. Furthermore, we delineated comprehensive wiring diagrams for HIP neurons projecting exclusively within the HIP formation (HPF) and for those projecting to both intra- and extra-HPF targets. Bihemispheric projecting neurons generally projected to one pair of homologous targets with ipsilateral preference. These organization principles of single-neuron projectomes provide a structural basis for understanding the function of HIP neurons.

Wavelet-Inspired Multi-channel Score-based Model for Limited-angle CT Reconstruction.

Score-based generative model (SGM) has demonstrated great potential in the challenging limited-angle CT (LA-CT) reconstruction. SGM essentially models the probability density of the ground truth data and generates reconstruction results by sampling from it. Nevertheless, direct application of the existing SGM methods to LA-CT suffers multiple limitations. Firstly, the directional distribution of the artifacts attributing to the missing angles is ignored. Secondly, the different distribution properties of the artifacts in different frequency components have not been fully explored. These drawbacks would inevitably degrade the estimation of the probability density and the reconstruction results. After an in-depth analysis of these factors, this paper proposes a Wavelet-Inspired Score-based Model (WISM) for LA-CT reconstruction. Specifically, besides training a typical SGM with the original images, the proposed method additionally performs the wavelet transform and models the probability density in each wavelet component with an extra SGM. The wavelet components preserve the spatial correspondence with the original image while performing frequency decomposition, thereby keeping the directional property of the artifacts for further analysis. On the other hand, different wavelet components possess more specific contents of the original image in different frequency ranges, simplifying the probability density modeling by decomposing the overall density into component-wise ones. The resulting two SGMs in the image-domain and wavelet-domain are integrated into a unified sampling process under the guidance of the observation data, jointly generating high-quality and consistent LA-CT reconstructions. The experimental evaluation on various datasets consistently verifies the superior performance of the proposed method over the competing method.

Role of genes encoding microbial carbohydrate-active enzymes in the accumulation and dynamics of organic carbon in subtropical forest soils.

Microbial anabolism and catabolism regulate the accumulation and dynamics of soil organic carbon (SOC). However, very little attention has been paid to the role of microbial functional traits in the accumulation and dynamics of SOC in forest soils. In this study, nine forest soils were selected at three altitudes (600 m, 1200 m, and 1500 m) and three soil depths (0-15 cm, 15-30 cm, and 30-45 cm) located in Jiugong Mountain. Vertical traits of functional genes encoding microbial carbohydrate-active enzymes (CAZymes) were observed using metagenomic sequencing. Soil amino sugars were used as biomarkers to indicate microbial residue carbon (MRC). The results showed that GH1 (ß-glucosidase: 147.49 TPM) and GH3 (ß-glucosidase: 109.09 TPM) were the dominant genes for plant residue decomposition, and their abundance increased with soil depth and peaked in the deep soil at 600 m (GH1: 147.89 TPM; GH3: 109.59 TPM). The highest abundance of CAZymes for fungal and bacterial residue decomposition were GH18 (chitinase: 30.81 TPM) and GH23 (lysozyme: 58.02 TPM), respectively. The abundance of GH18 increased with soil depth, while GH23 showed the opposite trend. Moreover, MRC accumulation was significantly positively correlated with CAZymes involved in the degradation of hemicellulose (r = 0.577, p = 0.002). Compared with the soil before incubation, MRC in the topsoil at the low and middle altitudes after incubation increased by 4 % and 8 %, respectively, while MRC in the soils at 1500 m tended to decrease (p > 0.05). The mineralization capacity of SOC at 1500 m was significantly higher than that at 1200 m and 600 m (p < 0.05). Our results suggested that microbial function for degrading plant residue components, especially hemicellulose and lignin, contributed greatly to SOC accumulation and dynamics. These results were vital for understanding the roles of microbial functional traits in C cycling in forest.