Search

Abstract To explore the differences and relationships between the available SARS-CoV-2 strains and predict the potential evolutionary direction of these strains, we employ the hierarchical clustering analysis to investigate the evolutionary relationships between the SARS-CoV-2 strains utilizing the genomic sequences collected in China till January 7, 2023. We encode the sequences of the existing SARS-CoV-2 strains into numerical data through k-mer algorithm, then propose four methods to select the representative sample from each type of strains to comprise the dataset for clustering analysis. Three hierarchical clustering algorithms named Ward-Euclidean, Ward-Jaccard, and Average-Euclidean are introduced through combing the Euclidean and Jaccard distance with the Ward and Average linkage clustering algorithms embedded in the OriginPro software. Experimental results reveal that BF.28, BE.1.1.1, BA.5.3, and BA.5.6.4 strains exhibit distinct characteristics which are not observed in other types of SARS-CoV-2 strains, suggesting their being the majority potential sources which the future SARS-CoV-2 strains’ evolution from. Moreover, BA.2.75, CH.1.1, BA.2, BA.5.1.3, BF.7, and B.1.1.214 strains demonstrate enhanced abilities in terms of immune evasion, transmissibility, and pathogenicity. Hence, closely monitoring the evolutionary trends of these strains is crucial to mitigate their impact on public health and society as far as possible.

Abstract Vehicle trajectory data underpins various applications in intelligent transportation systems, such as traffic surveillance, traffic prediction, and traffic control. Traditional vehicle trajectory datasets, recorded by GPS devices or single cameras, are often biased towards specific vehicles (e.g., taxis) or incomplete (typically

Abstract MAVS is an adapter protein involved in RIG-I-like receptor (RLR) signaling in mitochondria, peroxisomes, and mitochondria-associated ER membranes (MAMs). However, the role of MAVS in glucose metabolism and RLR signaling cross-regulation and how these signaling pathways are coordinated among these organelles have not been defined. This study reports that RLR action drives a switch from glycolysis to the pentose phosphate pathway (PPP) and the hexosamine biosynthesis pathway (HBP) through MAVS. We show that peroxisomal MAVS is responsible for glucose flux shift into PPP and type III interferon (IFN) expression, whereas MAMs-located MAVS is responsible for glucose flux shift into HBP and type I IFN expression. Mechanistically, peroxisomal MAVS interacts with G6PD and the MAVS signalosome forms at peroxisomes by recruiting TNF receptor-associated factor 6 (TRAF6) and interferon regulatory factor 1 (IRF1). By contrast, MAMs-located MAVS interact with glutamine-fructose-6-phosphate transaminase, and the MAVS signalosome forms at MAMs by recruiting TRAF6 and TRAF2. Our findings suggest that MAVS mediates the interaction of RLR signaling and glucose metabolism.

The fabrication of singly dispersed metal cluster catalysts with atomic-level control of dopants is a long-standing challenge. Here, the authors report a strategy for the synthesis of a precisely doped single cluster catalyst which shows exceptional activity for electrochemical dinitrogen reduction.

Controllable synthesis of single atom catalysts with sufficiently high metal loading remains challenging due to the tendency of agglomeration. Here the authors synthesize a series of stable atomically dispersed cobalt atoms on graphene with high Co loadings via the regeneration of active sites by atomic layer deposition.

Controlled fabrication of few-atoms supported catalysts is a major challenge in the synthesis of nanomaterials. Here, the authors show a bottom-up approach to precisely synthesize platinum dimers supported on graphene, which display higher catalytic activity and stability than single atoms and nanoparticles.

Abstract AMP-activated protein kinase (AMPK) is a key sensor and regulator of glucose metabolism. Here, we demonstrated that shizukaol F, a natural compound isolated from Chloranthus japonicus, can activate AMPK and modulate glucose metabolism both in vitro and in vivo. Shizukaol F increased glucose uptake in differentiated C2C12 myotubes by stimulating glucose transporter-4 (GLUT-4) membraned translocation. Treatment of primary mouse hepatocytes with shizukaol F decreased the expression of phosphoenolpyruvate carboxykinase 2 (PEPCK), glucose-6-phosphatase (G6Pase) and suppressed hepatic gluconeogenesis. Meanwhile, a single oral dose of shizukaol F reduced gluconeogenesis in C57BL/6 J mice. Further studies indicated that shizukaol F modulates glucose metabolism mainly by AMPKa phosphorylation activity. In addition, we also found that shizukaol F depolarizes the mitochondrial membrane and inhibits respiratory complex I, which may result in AMPK activation. Our results highlight the potential value of shizukaol F as a possible treatment of metabolic syndrome.

Abstract The neutrophil-lymphocyte ratio (NLR) has been reported to be associated with prognosis in several cancers. The objective of our study was to evaluate the prognostic role of baseline NLR and change in NLR (ΔNLR) in advanced pancreatic cancer underwent chemotherapy. Between January 2010 and June 2015, 132 patients underwent chemotherapy were eligible for assessment. Based on our patients’ data, the cut-off value of NLR was 2.78 according to receiver operating characteristic curve. We observed that a high level of baseline NLR (NLR > 2.78) was a poor prognostic factor for overall survival (multivariable hazard ratio [HR] = 2.648, P 0) after 2 cycles of chemotherapy was associated with higher risk compared to ΔNLR ≤ 0 (multivariable HR = 1.894, P = 0.007). Combining both NLR and ΔNLR factors, multivariate analysis showed a significant higher risk (HR = 5.817, P

Pathogenic Yersinia species employ the Ysc-Yop type III secretion system (T3SS) encoded by a highly conserved pYV virulence plasmid to export the virulence effectors into host cells. The Ysc-Yop T3SS is tightly regulated by multiple contributing proteins that function at different levels. However, systematic transcriptional regulation analysis of Ysc-Yop T3SS is lacking and the detailed mechanism under this regulation process is still elusive. Aimed at systematically characterizing transcriptional regulations of all T3SS genes in Y. pseudotuberculosis, we amplified 97 non-coding fragments from the pYV plasmid and analyzed transcriptional responses of the T3SS genes under different growth conditions. Transcriptions of T3SS genes were induced at 37°C and genes encoding T3SS effectors were highly induced by further depletion of Ca2+. The temperature induced gene transcription process is mediated by modules encoded on the chromosome, while the Ca2+ depletion-induced process is controlled by the positive regulatory protein LcrF as well as the negative regulatory protein LcrQ. In this process, LcrQ shares the same targets with LcrF and the effect of LcrQ is dependent on the presence of LcrF. Furthermore, over-expression of LcrF showed the same phenotype as that of the lcrQ mutant strain and intracellular amount balance of LcrQ and LcrF is important in T3SS regulation. When the expression level of LcrF exceeds LcrQ, expression of the Ysc-Yop T3SS genes is activated and vice versa. Together, these data support a model in which LcrQ blocks the activation role of LcrF in regulating the transcription of T3SS genes in Yersinia.

This study is the first to demonstrate that shizukaol D, a natural compound isolated from Chloranthusjaponicus, can activate AMP- activated protein kinase (AMPK), a key sensor and regulator of intracellular energy metabolism, leading to a decrease in triglyceride and cholesterol levels in HepG2 cells. Furthermore, we found that shizukaol D induces mitochondrial dysfunction by depolarizing the mitochondrial membrane and suppressing energy production, which may result in AMPK activation. Our results provide a possible link between mitochondrial dysfunction and AMPK activation and suggest that shizukaol D might be used to treat metabolic syndrome.

Human hepatitis B virus (HBV) infection and HBV-related diseases remain a major public health problem. Individuals coinfected with its satellite hepatitis D virus (HDV) have more severe disease. Cellular entry of both viruses is mediated by HBV envelope proteins. The pre-S1 domain of the large envelope protein is a key determinant for receptor(s) binding. However, the identity of the receptor(s) is unknown. Here, by using near zero distance photo-cross-linking and tandem affinity purification, we revealed that the receptor-binding region of pre-S1 specifically interacts with sodium taurocholate cotransporting polypeptide (NTCP), a multiple transmembrane transporter predominantly expressed in the liver. Silencing NTCP inhibited HBV and HDV infection, while exogenous NTCP expression rendered nonsusceptible hepatocarcinoma cells susceptible to these viral infections. Moreover, replacing amino acids 157–165 of nonfunctional monkey NTCP with the human counterpart conferred its ability in supporting both viral infections. Our results demonstrate that NTCP is a functional receptor for HBV and HDV.

Abstract Accurate differentiation between angina with no obstructive coronary arteries (ANOCA) and mental stress-induced myocardial ischemia (MSIMI) is crucial for tailored treatment strategies, yet public data scarcity hampers understanding. Given the higher incidence of both conditions in women, this study prospectively enrolled 80 female ANOCA and 39 age-matched female controls, subjecting them to three types of mental stress tasks. ECGs were continuously monitored across Rest, Stress, and Recover stages of the mental stress tasks, with PET/CT imaging during the Stress stage to evaluate myocardial perfusion. With PET/CT serving as the gold standard for MSIMI diagnosis, 35 of the 80 ANOCA patients were diagnosed as MSIMI. Using ECG variables from different stages of mental stress tasks, we developed five machine learning models to diagnose MSIMI. The results showed that ECG data from different stages provide valuable information for MSIMI classification. Additionally, the dataset encompassed demographic details, physiological, and blood sample test results of the patients. We anticipate this new dataset will significantly push further progress in ANOCA and MSIMI research.

Abstract Archaea possess characteristic membrane-spanning lipids that are thought to contribute to the adaptation to extreme environments. However, the biosynthesis of these lipids is poorly understood. Here, we identify a radical S-adenosyl-L-methionine (SAM) enzyme that synthesizes glycerol monoalkyl glycerol tetraethers (GMGTs). The enzyme, which we name GMGT synthase (Gms), catalyzes the formation of a C(sp3)–C(sp3) linkage between the two isoprenoid chains of glycerol dialkyl glycerol tetraethers (GDGTs). This conclusion is supported by heterologous expression of gene gms from a GMGT-producing species in a methanogen, as well as demonstration of in vitro activity using purified Gms enzyme. Additionally, we show that genes encoding putative Gms homologs are present in obligate anaerobic archaea and in metagenomes obtained from oxygen-deficient environments, and appear to be absent in metagenomes from oxic settings.

Abstract Eye tracking techniques enable high-efficient, natural, and effortless human-machine interaction by detecting users’ eye movements and decoding their attention and intentions. Here, a miniature, imperceptible, and biocompatible smart contact lens is proposed for in situ eye tracking and wireless eye-machine interaction. Employing the frequency encoding strategy, the chip-free and battery-free lens successes in detecting eye movement and closure. Using a time-sequential eye tracking algorithm, the lens has a great angular accuracy of

Abstract Antibiotic-induced dysbiosis is a major risk factor for Clostridioides difficile infection (CDI), and fecal microbiota transplantation (FMT) is recommended for treating CDI. However, the underlying mechanisms remain unclear. Here, we show that Tritrichomonas musculis (T.mu), an integral member of the mouse gut commensal microbiota, reduces CDI-induced intestinal damage by inhibiting neutrophil recruitment and IL-1β secretion, while promoting Th1 cell differentiation and IFN-γ secretion, which in turn enhances goblet cell production and mucin secretion to protect the intestinal mucosa. T.mu can actively metabolize arginine, not only influencing the host’s arginine-ornithine metabolic pathway, but also shaping the metabolic environment for the microbial community in the host’s intestinal lumen. This leads to a relatively low ornithine state in the intestinal lumen in C. difficile-infected mice. These changes modulate C. difficile’s virulence and the host intestinal immune response, and thus collectively alleviating CDI. These findings strongly suggest interactions between an intestinal commensal eukaryote, a pathogenic bacterium, and the host immune system via inter-related arginine-ornithine metabolism in the regulation of pathogenesis and provide further insights for treating CDI.

Abstract High heterogeneity and complex interactions of malignant cells in breast cancer has been recognized as a driver of cancer progression and therapeutic failure. However, complete understanding of common cancer cell states and their underlying driver factors remain scarce and challenging. Here, we revealed seven consensus cancer cell states recurring cross patients by integrative analysis of single-cell RNA sequencing data of breast cancer. The distinct biological functions, the subtype-specific distribution, the potential cells of origin and the interrelation of consensus cancer cell states were systematically elucidated and validated in multiple independent datasets. We further uncovered the internal regulons and external cell components in tumor microenvironments, which contribute to the consensus cancer cell states. Using the state-specific signature, we also inferred the abundance of cells with each consensus cancer cell state by deconvolution of large breast cancer RNA-seq cohorts, revealing the association of immune-related state with better survival. Our study provides new insights for the cancer cell state composition and potential therapeutic strategies of breast cancer.

ABSTRACTBaicalein, usually obtained after the removal of 7-O-β-D-glucuronic acid from baicalin, has strong pharmacological activity. In this study, a novel strategy for efficient and eco-friendly preparation of baicalein was established by high-temperature-little-acid hydrolysis of baicalin. The effects of inorganic acids, solvents, solid–liquid ratio, HCl concentration and hydrolysis duration on the yield of baicalein were investigated by one-factor-at-a-time experiment. Then, an orthogonal experiment design was conducted for the optimal hydrolysis conditions, namely, baicalin was boiled in n-BuOH solution containing 0.50% HCl (w/v) at 130°C for 2.0 h with solid–liquid ratio at 1:25 (g/mL). In the 60-fold scale-up experiment, the yield of baicalein was achieved at 83.5% ± 6.3%, and its purity was increased from 74.2% to 98.7% after purification. Compared with reported methods, acid consumption per unit product of the newly developed strategy was approximately 80 times lower than that of conventional acid hydrolysis, and time consumption was substantially reduced. Overall, the novel strategy showed great prospects for a cleaner large-scale production of baicalein, which provides a new alternative desirable for the preparation of natural products with high efficiency and low consumption in the pharmaceutical industry.

Abstract The realization of compact and efficient broadband mid-infrared (MIR) lasers has enormous impacts in promoting MIR spectroscopy for various important applications. A number of well-designed waveguide platforms have been demonstrated for MIR supercontinuum and frequency comb generations based on cubic nonlinearities, but unfortunately third-order nonlinear response is inherently weak. Here, we propose and demonstrate for the first time a χ (2) micrometer waveguide platform based on birefringence phase matching for long-wavelength infrared (LWIR) laser generation with a high quantum efficiency. In a ZnGeP2-based waveguide platform, an octave-spanning spectrum covering 5–11 μm is generated through optical parametric generation (OPG). A quantum conversion efficiency of 74% as a new record in LWIR single-pass parametric processes is achieved. The threshold energy is measured as ~616 pJ, reduced by more than 1-order of magnitude as compared to those of MIR OPGs in bulk media. Our prototype micro-waveguide platform could be extended to other χ (2) birefringence crystals and trigger new frontiers of MIR integrated nonlinear photonics.

Relay channels capture the essence of several important communication scenarios such as sensor network and satellite communication. In this paper, first, we propose an efficient coding scheme for an additive white Gaussian noise (AWGN) relay channel in the presence of AWGN feedback, which generalizes the conventional scheme for the AWGN relay channel with noiseless feedback by introducing a lattice-based strategy to eliminate the impact of the feedback channel noise on the performance of the original scheme. Next, we further extend the proposed scheme to the multi-input single-output (MISO) fading relay channel (FRC) with noisy feedback. The key to this extension is to use a pre-coding strategy to transform the MISO channel into a single-input single-output (SISO) channel and applying a two-dimensional lattice coding strategy to deal with the feedback fading channel noise. Finally, we analyze the security performance of our proposed scheme in several cases, and the results of this paper are further illustrated by numerical examples.

Although various degradable gel materials have been developed for temporary plugging in oil fields, they often degrade too quickly in high-temperature environments. To address this issue, an unstable crosslinker was synthesized to prepare a high-temperature degradable gel. This gel does not degrade excessively fast at high temperatures. Temperature and crosslinker concentration are the primary factors influencing gel degradation time, followed by monomer and initiator concentrations. Increased temperature and decreased crosslinker concentration both reduce degradation time, which can be adjusted within the range of 90–130 °C by varying the crosslinker concentration. The molecular structure and thermal stability of the degradable gel were analyzed using FTIR, 13C NMR, and TG. Furthermore, the viscoelastic properties, compressive performance, plugging performance, and core damage performance of the gel were evaluated. Within the test range of 0.1–1000 Pa, the storage modulus is higher than the loss modulus. The gel prepared at 130 °C exhibited a compressive stress of 0.25 MPa at 50% strain. The plugging pressure of the gel in sand-filled tubes with varying permeabilities (538.2–2794.1 mD) exceeded 15 MPa while maintaining a core damage rate below 5%. SEM analysis indicated that the degradation mechanism of the gel may involve the collapse of its three-dimensional network structure due to the hydrolysis of amide groups in the crosslinker. The viscosity of the degradation liquid was below 11 mPa·s, enabling it to be brought back to the surface with the formation fluid without the need for further breaking operations.

Abstract NVS-ZP7-4 was identified as a novel chemical reagent targeting the zinc input protein ZIP7, which accounts for the zinc surge from the apparatus to the cytoplasm. Since zinc dysregulation is related to multiple diseases, in this study, we aimed to identify the anti-tumor effects of NVS-ZP7-4 and explore the molecular mechanisms of NVS-ZP7-4 in hepatocellular carcinoma (HCC) progression. We found that NVS-ZP7-4 inhibited cell viability, caused cell cycle arrest, induced apoptosis, and inhibited the proliferation, migration, and invasion of HCCLM3 and Huh7 cells. We further investigated the inhibited activation of the phosphatidylinositol 3-kinase (PI3K)/Akt pathway was involved in the antitumor effect of NVS-ZP7-4 in HCC. Furthermore, NVS-ZP7-4 inhibited HCC tumor growth in vivo. The present study demonstrated that NVS-ZP7-4 is a promising therapeutic target for HCC by regulating PI3K/AKT signaling.

Abstract The limited number of targetable tumor-specific antigens and the immunosuppressive nature of the microenvironment within solid malignancies represent major barriers to the success of chimeric antigen receptor (CAR)-T cell therapies. Here, using epithelial cell adhesion molecule (EpCAM) as a model antigen, we used alanine scanning of the complementarity-determining region to fine-tune CAR affinity. This allowed us to identify CARs that could spare primary epithelial cells while still effectively targeting EpCAMhigh tumors. Although affinity-tuned CARs showed suboptimal antitumor activity in vivo, we found that inducible secretion of interleukin-12 (IL-12), under the control of the NFAT promoter, can restore CAR activity to levels close to that of the parental CAR. This strategy was further validated with another affinity-tuned CAR specific for intercellular adhesion molecule-1 (ICAM-1). Only in affinity-tuned CAR-T cells was NFAT activity stringently controlled and restricted to tumors expressing the antigen of interest at high levels. Our study demonstrates the feasibility of specifically gearing CAR-T cells towards recognition of solid tumors by combining inducible IL-12 expression and affinity-tuned CAR.

The rapid protease degradation of peptides is currently limiting their therapeutic utility. Here, the authors report functionalised thiocarbazate scaffolds as precursors of aza-amino acids that can be integrated in peptide sequences, extending their bioavailability, and demonstrate this on FSSE/P5779 and bradykinin.

Selective activation of C–H bonds is a key challenge in organic reactions. Here, the authors achieve the selective activation of four quasi-equivalent C–H bonds, leading to the formation of N-doped graphene nanoribbons with partial corannulene motifs.

In considering Asian monsoon intensity and precipitation during glacial-interglacial transitions in Chinese Loess Plateau, a new study finds that brGDGT-DLNN method can significantly extend the temporal scale record of the EASM and is not restricted by geographic location compared with stalagmite records.

Abstract Leaf area index (LAI) is a fundamental indicator of crop growth status, timely and non-destructive estimation of LAI is of significant importance for precision agriculture. In this study, a multi-rotor UAV platform equipped with CMOS image sensors was used to capture maize canopy information, simultaneously, a total of 264 ground‐measured LAI data were collected during a 2-year field experiment. Linear regression (LR), backpropagation neural network (BPNN), and random forest (RF) algorithms were used to establish LAI estimation models, and their performances were evaluated through 500 repetitions of random sub-sampling, training, and testing. The results showed that RGB-based VIs derived from UAV digital images were strongly related to LAI, and the grain-filling stage (GS) of maize was identified as the optimal period for LAI estimation. The RF model performed best at both whole period and individual growth stages, with the highest R2 (0.71–0.88) and the lowest RMSE (0.12–0.25) on test datasets, followed by the BPNN model and LR models. In addition, a smaller 5–95% interval range of R2 and RMSE was observed in the RF model, which indicated that the RF model has good generalization ability and is able to produce reliable estimation results.

Prosapogenin A (also known as Progenin III and polyphyllin V), a secondary steroidal saponin in Dioscorea zingiberensis tubers, has more superior pharmacological activities than its primary form Protogracillin. Conventional preparation methods, such as column chromatography, and acidic hydrolysis, are of very low efficiency and limited scale due to tedious procedures and large consumption of organic solvent. This study aims to establish a convenient method for efficiently obtaining Prosapogenin A by enzymatic hydrolysis of abundant Protogracillin in the raw material. In light of the highest hydrolysis performance, β-dextranase was selected from four commercial enzymes in this application. After optimization of the conditions by the response surface methodology using Box–Behnken design, the enzymatic hydrolysis was carried out in 0.20 M HAc-NaAc buffer (pH 4.81) containing β-dextranase/Protogracillin (5.0:1, w/w), and the system was constantly kept at 56.7°C water bath for 4 h. Consequently, Protogracillin has been almost completely hydrolyzed to be Prosapogenin A and the highest yield was 96.4 ± 1.4%. The newly proposed approach is efficient and promising for conveniently obtaining Prosapogenin A and aimed to provide a laboratory-scale experimental foundation for the preparation of Prosapogenin A in industrial applications.

Abstract Accumulating evidence shows HOOK1 disordered in human malignancies. However, the clinicopathological and biological significance of HOOK1 in renal cell carcinoma (RCC) remains rarely studied. In this study, the authors demonstrate that HOOK1 is downregulated in RCC samples with predicted poorer clinical prognosis. Mechanistically, HOOK1 inhibits tumor growth and metastasis via canonical TGF‐β/ALK5/p‐Smad3 and non‐canonical TGF‐β/MEK/ERK/c‐Myc pathway. At the same time, HOOK1 inhibits RCC angiogenesis and sunitinib resistance by promoting degradation of TNFSF13B through the ubiquitin‐proteasome pathway. In addition, HOOK1 is transcriptionally regulated by nuclear factor E2F3 in VHL dependent manner. Notably, an agonist of HOOK1, meletin, is screened and it shows antitumor activity more effectively when combined with sunitinib or nivolumab than it is used alone. The findings reveal a pivotal role of HOOK1 in anti‐cancer treatment, and identify a novel therapeutic strategy for renal cell carcinoma.

Abstract Intervertebral disc degeneration (IVDD)‐induced lower back pain (LBP) is a common problem worldwide. The underlying mechanism is partially accredited to ferroptosis, based on sequencing analyses of IVDD patients from the gene expression omnibus (GEO) databases. In this study, it is shown that polydopamine nanoparticles (PDA NPs) inhibit oxidative stress‐induced ferroptosis in nucleus pulposus (NP) cells in vitro. PDA NPs scavenge reactive oxygen species (ROS), chelate Fe2+ to mitigate iron overload, and regulate the expression of iron storage proteins such as ferritin heavy chain (FHC), ferritin, and transferrin receptor (TFR). More importantly, PDA NPs co‐localize with glutathione peroxidase 4 (GPX4) around the mitochondria and suppress ubiquitin‐mediated degradation, which in turn exerts a protective function via the transformation and clearance of phospholipid hydroperoxides. PDA NPs further down‐regulate malondialdehyde (MDA) and lipid peroxide (LPO) production; thus, antagonizing ferroptosis in NP cells. Moreover, PDA NPs effectively rescue puncture‐induced degeneration in vivo by targeting ferroptosis and inhibiting GPX4 ubiquitination, resulting in the upregulation of antioxidant pathways. The findings offer a new tool to explore the underlying mechanisms and a novel treatment strategy for IVDD‐induced LBP.

The spatiotemporal patterns and shifts of net ecosystem productivity (NEP) play a pivotal role in ecological conservation and addressing climate change. For example, by quantifying the NEP information within ecosystems, we can achieve the protection and restoration of natural ecological balance. Monitoring the changes in NEP enables a more profound understanding and prediction of ecosystem alterations caused by global warming, thereby providing a scientific basis for formulating policies aimed at mitigating and adapting to climate change. The accurate prediction of NEP sheds light on the ecosystem’s response to climatic variations and aids in formulating targeted carbon sequestration policies. While traditional ecological process models provide a comprehensive approach to predicting NEP, they often require extensive experimental and empirical data, increasing research costs. In contrast, machine-learning models offer a cost-effective alternative for NEP prediction; however, the delicate balance in algorithm selection and hyperparameter tuning is frequently overlooked. In our quest for the optimal prediction model, we examined a combination of four mainstream machine-learning algorithms with four hyperparameter-optimization techniques. Our analysis identified that the backpropagation neural network combined with Bayesian optimization yielded the best performance, with an R2 of 0.68 and an MSE of 1.43. Additionally, deep-learning models showcased promising potential in NEP prediction. Selecting appropriate algorithms and executing precise hyperparameter-optimization strategies are crucial for enhancing the accuracy of NEP predictions. This approach not only improves model performance but also provides us with new tools for a deeper understanding of and response to ecosystem changes induced by climate change.

Abstract The incidence of prostate cancer (PCa) in men globally increases as the standard of living improves. Blood serum biomarker prostate‐specific antigen (PSA) detection is the gold standard assay that do not meet the requirements of early detection. Herein, a solution‐gated graphene transistor (SGGT) biosensor for the ultrasensitive and rapid quantification detection of the early prostate cancer‐relevant biomarker, miRNA‐21 is reported. The designed single‐stranded DNA (ssDNA) probes immobilized on the Au gate can hybridize effectively with the miRNA‐21 molecules targets and induce the Dirac voltage shifts of SGGT transfer curves. The limit of detection (LOD) of the sensor can reach 10−20 M without amplification and any chemical or biological labeling. The detection linear range is from 10−20 to 10−12 M. The sensor can realize real‐time detection of the miRNA‐21 molecules in less than 5 min and can well distinguish one‐mismatched miRNA‐21 molecule. The blood serum samples from the patients without RNA extraction and amplification are measured. The results demonstrated that the biosensor can well distinguish the cancer patients from the control group and has higher sensitivity (100%) than PSA detection (58.3%). Contrastingly, it can be found that the PSA level is not directly related to PCa.

Spatio-temporal evolution laws of storage coefficient and contact network of crushed rock are of great significance for the construction and utilization of underground reservoirs in coal mines. Based on discrete element method and irregular rigid block model, spatio-temporal evolution laws of storage coefficient and contact network of crushed rock under different overburden stresses are investigated and the following main conclusions are obtained: (1) The average storage coefficient and the storage coefficient at different vertical heights of the crushed rock packing system decrease exponentially as the overburden stress increases. When the overburden stress ranges from 0 to 20 MPa, the average storage coefficient decreases by 48.947%. (2) The average void radius and throat radius of water storage space decrease exponentially as the overburden stress increases. The increase in overburden stress leads to the transformation of large voids into smaller voids, causing a gradual decrease in void connectivity and a tendency towards irregular void shapes. (3) With the increase of overburden stress, the number of strong contacts in the packing system of crushed rock increases and gradually expands from the top to the bottom. The average contact force of crushed rock increases exponentially, while the coordination number increases linearly. (4) As the overburden stress increases, the majority of contact directions are concentrated within the ±30° range in the loading direction. This increase results in an enhancement of the anisotropy of the packing system structure of crushed rock.

BackgroundThe risk factors for depression in asthma are still unclear. The objective of this study was to identify the risk factors associated with depression in asthmatic individuals.MethodsWe used data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Univariate analysis and multivariate logistic regression analyses were used to identify risk factors for depression and calculate unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs).ResultsA total of 5,379 asthmatic participants were included. Of these subjects, 767 individuals had depression, and 4,612 individuals had no depression. Univariate analysis and multivariate analyses suggested that asthmatic individuals with smoking (OR 1.98, 95% CI 1.19-3.29), hypertension (OR 2.73, 95% CI 1.48-5.04), and arthritis (OR 2.83, 95% CI 1.53-5.22) were more likely to have depression. Asthmatic individuals who had more than a high school education had lower depression risk than those with less than a high school education (OR 0.55, 95% CI 0.30-0.99). Increasing age was also associated with decreased depression risk (OR 0.97, 95% CI 0.95-0.99).ConclusionsDepression was more likely in asthmatic individuals with smoking, hypertension, and arthritis and less likely in individuals with higher education and increasing age. These findings could improve the identification of target populations for effective interventions to improve the mental health of asthmatic individuals.

The Chukchi Sea has experienced significant changes under global warming in the Common Era, including the shift of primary productivity. However, modern observations are too short to fully investigate the effects of environmental changes in this area. Here, we analyzed lipid biomarkers (e.g. long-chain n-alkanes, n-alkanols, n-alkanoic acids, diols, and sterols) from a sediment core (R07) collected from the Chukchi Sea shelf to determine phytoplankton primary productivity variations and factors influencing these changes over the past 70 years. Similar trends of the abundance of terrestrial ecosystem-derived compounds (e.g. long-chain n-alkanes, n-alkanols, n-alkanoic acids, and C32 1,15-diol) indicate that terrigenous input increased from ca. 1946 towards ca. 1983 and then decreased thereafter. In comparison, biomarkers with marine origin indicate that the ratio of diatoms to dinoflagellates increased after ca. 1983 towards the core-top (ca. 2011). Concurrent changes in terrigenous input and phytoplankton community indicated a shift in water mass structure at ca. 1983 (i.e. the Alaska Coastal Water decreased and the Bering Sea Water increased), which may be attributed to the phase shift of the Arctic Oscillation and/or unsynchronized flow changes in different water masses. Owing to the different water mass properties, the change of water mass structure caused intense water mixing and the resulting high turbidity in the study area, which led to light limitation for phytoplankton growth. These conditions probably account for the reduced phytoplankton primary productivity from ca. 1983 to ca. 2000 in the general trend of increasing. The results indicate that, in addition to global warming and sea ice retreat, other factors, such as change in regional water mass structure (i.e. different water masses), may also have a significant influence on the primary productivity and the phytoplankton community in the Chukchi Sea shelf.

Drp1 is the master regulator of mitochondrial fission, which has important impact on cellular functions. Here, Yang et al identified evolutionarily conserved proteins Clueless and its homolog CLUH as key regulators of Drp1 that function via translation of Drp1 receptors MiD49 and Mff.

The cell membranes of many archaea contain characteristic membrane-spanning lipids known as glycerol dibiphytanyl glycerol tetraethers. Here, Zeng et al. identify a protein that participates in a key step of the synthesis of these lipids from diether precursors.

For this study, a new point cloud alignment method is proposed for extracting corner points and aligning them at the geometric level. It can align point clouds that have low overlap and is more robust to outliers and noise. First, planes are extracted from the raw point cloud, and the corner points are defined as the intersection of three planes. Next, graphs are constructed for subsequent point cloud registration by treating corners as vertices and sharing planes as edges. The graph-matching algorithm is then applied to determine correspondence. Finally, point clouds are registered by aligning the corresponding corner points. The proposed method was investigated by utilizing pertinent metrics on datasets with differing overlap. The results demonstrate that the proposed method can align point clouds that have low overlap, yielding an RMSE of about 0.05 cm for datasets with 90% overlap and about 0.2 cm when there is only about 10% overlap. In this situation, the other methods failed to align point clouds. In terms of time consumption, the proposed method can process a point cloud comprising 104 points in 4 s when there is high overlap. When there is low overlap, it can also process a point cloud comprising 106 points in 10 s. The contributions of this study are the definition and extraction of corner points at the geometric level, followed by the use of these corner points to register point clouds. This approach can be directly used for low-precision applications and, in addition, for coarse registration in high-precision applications.

The recently discovered class of kagome metals AV3Sb5, where A stands for K, Rb, Cs, has been shown to host a variety of exotic phases. Here, the authors report the two-fold rotational symmetry of superconductivity and signatures of an in-plane nematic electronic state in CsV3Sb5 under in-plane magnetic field.

Summary: E3 ubiquitin ligase Cbl-b is involved in the maintenance of a balance between immunity and tolerance. Mice lacking Cbl-b are highly susceptible to experimental autoimmune encephalomyelitis (EAE), a Th17-mediated autoimmune disease. However, how Cbl-b regulates Th17 cell responses remains unclear. In this study, utilizing adoptive transfer and cell type-specific Cblb knockout strains, we show that Cbl-b expression in macrophages, but not T cells or dendritic cells (DCs), restrains the generation of pathogenic Th17 cells and the development of EAE. Cbl-b inhibits IL-6 production by macrophages that is induced by signaling from CARD9-dependent C-type lectin receptor (CLR) pathways, which directs T cells to generate pathogenic Th17 cells. Therefore, our data unveil a previously unappreciated function for Cbl-b in the regulation of pathogenic Th17 responses.

Change detection (CD), as a special remote-sensing (RS) segmentation task, faces challenges, including alignment errors and illumination variation, dense small targets, and large background intraclass variance in very high-resolution (VHR) remote-sensing images. Recent methods have avoided the misjudgment caused by illumination variation and alignment errors by increasing the ability of global modeling, but the latter two problems have still not been fully addressed. In this paper, we propose a new CD model called SFCD, which increases the feature extraction capability for small targets by introducing a shifted-window (Swin) transformer. We designed a foreground-aware fusion module to use attention gates to trim low-level feature responses, enabling increased attention to the changed region compared to the background when recovering the changed region, thus reducing background interference. We evaluated our model on two CD datasets, LEVIR-CD and CDD, and obtained F1 scores of 91.78 and 97.87, respectively. The experimental results and visual interpretation show that our model outperforms several previous CD models. In addition, we adjusted the parameters and structure of the standard model to develop a lightweight version that achieves an accuracy beyond most models with only 1.55 M parameters, further validating the effectiveness of our design.

Abstract Laser heating of gold nanospheres (GNS) is increasingly prevalent in biomedical applications due to tunable optical properties that determine heating efficiency. Although many geometric parameters (i.e. size, morphology) can affect optical properties of individual GNS and their heating, no specific studies of how GNS aggregation affects heating have been carried out. We posit here that aggregation, which can occur within some biological systems, will significantly impact the optical and therefore heating properties of GNS. To address this, we employed discrete dipole approximation (DDA) simulations, Ultraviolet–Visible spectroscopy (UV–Vis) and laser calorimetry on GNS primary particles with diameters (5, 16, 30 nm) and their aggregates that contain 2 to 30 GNS particles. DDA shows that aggregation can reduce the extinction cross-section on a per particle basis by 17–28%. Experimental measurement by UV–Vis and laser calorimetry on aggregates also show up to a 25% reduction in extinction coefficient and significantly lower heating (~ 10%) compared to dispersed GNS. In addition, comparison of select aggregates shows even larger extinction cross section drops in sparse vs. dense aggregates. This work shows that GNS aggregation can change optical properties and reduce heating and provides a new framework for exploring this effect during laser heating of nanomaterial solutions.

The recent observation of superconductivity in nickelate thin films has attracted a lot of attentions. Here, authors report single particle tunneling spectra on the superconducting nickelate thin films revealing two types of gap feature with one V-shape and the other a full gap.