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Current preclinical imaging of intestine in animal models cannot reveal intestinal dynamics in awake condition. Here the authors report a Transillumination Intestine Projection (TIP) imaging system for free-moving mice, and showed the intestine dynamics in conscious animal in natural physiological states.

The inactive X chromosome (Xi) has an atypical structure, with global loss of TADs, A/B compartments and formation of mega-domains. Here the authors show that the non-canonical SMC family protein, SmcHD1, important for developmental gene silencing on Xi, antagonises TAD formation and compartmentalization on the Xi in a transcription independent way.

This paper proposes a segmentation-based global optimization method for depth estimation. Firstly, for obtaining accurate matching cost, the original local stereo matching approach based on self-adapting matching window is integrated with two matching cost optimization strategies aiming at handling both borders and occlusion regions. Secondly, we employ a comprehensive smooth term to satisfy diverse smoothness request in real scene. Thirdly, a selective segmentation term is used for enforcing the plane trend constraints selectively on the corresponding segments to further improve the accuracy of depth results from object level. Experiments on the Middlebury image pairs show that the proposed global optimization approach is considerably competitive with other state-of-the-art matching approaches.

Abstract Globally, breast cancer continues to be the leading cause of cancer-related incidence and mortality among females. Research has shown that sleep patterns significantly influence tumor onset and progression. In this research, the association was examined through the application of a two-sample Mendelian randomization (MR) approach. For the analysis of seven sleep patterns, genetic tools were sourced from both the UK Biobank and 23andMe, including morning/evening person (chronotype) n = 177,604, morning person (chronotype) n = 248,094, daytime dozing/sleepiness n = 193,472, getting up in the morning n = 193,717, and sleeplessness n = 193,987; sleep duration n = 192,810; and nap during the day n = 166,853. The Breast Cancer Association Consortium (BCAC) supplied genome-wide association studies (GWAS) data, including 133,384 breast cancer cases and 113,789 controls, alongside subtype-specific data with 106,278 cases and 91,477 controls. We discovered that chronotype encompasses both morning and evening types contributes to the risk of overall breast cancer. While daytime dozing and morning person (chronotype) are linked to a lower risk of breast cancer in general, In subtype-specific analyses, morning person (chronotype) was negatively associated with luminal B, HER2-negative-like, and daytime dozing was negatively correlated with luminal A-like, luminal B-like, and HER2-enriched-like. The study corroborates that chronotype is a danger element for breast cancer, aligning with previous observational findings. The association between being a morning person (chronotype) or having daytime dozing and a decreased risk of breast cancer underscores the significance of sleep patterns in formulating strategies for cancer prevention.

Abstract The Span-based model can effectively capture the complex entity structure in the text, thus becoming the mainstream model for nested named entity recognition (Nested NER) tasks. However, traditional Span-based models decode each entity span independently. They do not consider the semantic connections between spans or the entities’ positional information, which limits their performance. To address these issues, we propose a Bi-Directional Context-Aware Network (Bi-DCAN) for the Nested NER. Specifically, we first design a new span-level semantic relation model. Then, the Bi-DCAN is implemented to capture this semantic relationship. Furthermore, we incorporate Rotary Position Embedding into the bi-affine mechanism to capture the relative positional information between the head and tail tokens, enabling the model to more accurately determine the position of each entity. Experimental results show that compared to the latest model Diffusion-NER, our model reduces 20M parameters and increases the F1 scores by 0.24 and 0.09 on the ACE2005 and GENIA datasets respectively, which proves that our model has an excellent ability to recognise nested entities.

Abstract Bridged chiral biaryls are axially chiral compounds with a medium-sized ring connecting the two arenes. Compared with plentiful methods for the enantioselective synthesis of biaryl compounds, synthetic approaches for this subclass of bridged atropisomers are limited. Here we show an atroposelective synthesis of 1,3-diaxial bridged eight-membered terphenyl atropisomers through an Co/SPDO (spirocyclic pyrrolidine oxazoline)-catalyzed aerobic oxidative coupling/desymmetrization reaction of prochiral phenols. This catalytic desymmetric process is enabled by combination of an earth-abundant Co(OAc)2 and a unique SPDO ligand in the presence of DABCO (1,4-diaza[2.2.2]bicyclooctane). An array of diaxial bridged terphenyls embedded in an azocane can be accessed in high yields (up to 99%) with excellent enantio- (>99% ee) and diastereoselectivities (>20:1 dr).

Abstract Capsaicin derivatives with thiourea structure (CDTS) is highly noteworthy owing to its higher analgesic potency in rodent models and higher agonism in vitro. However, the direct synthesis of CDTS remains t one or more shortcomings. In this study, we present reported a green, facile, and practical synthetic method of capsaicin derivatives with thiourea structure is developed by using an automated synthetic system, leading to a series of capsaicin derivatives with various electronic properties and functionalities in good to excellent yields.

Abstract Exfoliation of 2D non‐Van der Waals (non‐vdW) semiconductor nanoplates (NPs) from inorganic analogs presents many challenges ahead for further exploring of their advanced applications on account of the strong bonding energies. In this study, the exfoliation of ultrathin 2D non‐vdW chromium sulfide (2D Cr2S3) by means of a combined facile liquid‐phase exfoliation (LPE) method is successfully demonstrated. The morphology and structure of the 2D Cr2S3 material are systematically examined. Magnetic studies show an obvious temperature‐dependent uncompensated antiferromagnetic behavior of 2D Cr2S3. The material is further loaded on TiO2 nanorod arrays to form an S‐scheme heterojunction. Experimental measurements and density functional theory (DFT) calculations confirm that the formed TiO2@Cr2S3 S‐scheme heterojunction facilitates the separation and transmission of photo‐induced electron/hole pairs, resulting in a significantly enhanced photocatalytic activity in the visible region.

Abstract To ensure compositional consistency while mitigating potential immunogenicity for stem cell therapy, synthetic scaffolds have emerged as compelling alternatives to native extracellular matrix (ECM). Substantial progress has been made in emulating specific natural traits featuring consistent chemical compositions and physical structures. However, recapitulating the dynamic responsiveness of the native ECM involving chemical transitions and physical remodeling during differentiation, remains a challenging endeavor. Here, the creation of adaptive scaffolds is demonstrated through sequential protein‐instructed molecular assembly, utilizing stage‐specific proteins, and incorporating in situ assembly technique. The procedure is commenced by introducing a dual‐targeting peptide at the onset of stem cell differentiation. In response to highly expressed integrins and heparan sulfate proteoglycans (HSPGs) on human mesenchymal stem cell (hMSC), the peptides assembled in situ, creating customized extracellular scaffolds that adhered to hMSCs promoting osteoblast differentiation. As the expression of alkaline phosphatase (ALP) and collagen (COL‐1) increased in osteoblasts, an additional peptide is introduced that interacts with ALP, initiating peptide assembly and facilitating calcium phosphate (CaP) deposition. The growth and entanglement of peptide assemblies with collagen fibers efficiently incorporated CaP into the network resulting in an adaptive biphasic scaffold that enhanced healing of bone injuries.

Abstract Pain, a comorbidity of anxiety disorders, causes substantial clinical, social, and economic burdens. Emerging evidence suggests that propofol, the most commonly used general anesthetic, may regulate psychological disorders; however, its role in pain‐associated anxiety is not yet described. This study investigates the therapeutic potential of a single dose of propofol (100 mg kg−1) in alleviating pain‐associated anxiety and examines the underlying neural mechanisms. In acute and chronic pain models, propofol decreased anxiety‐like behaviors in the elevated plus maze (EPM) and open field (OF) tests. Propofol also reduced the serum levels of stress‐related hormones including corticosterone, corticotropin‐releasing hormone (CRH), and norepinephrine. Fiber photometry recordings indicated that the calcium signaling activity of CRH neurons in the paraventricular nucleus (PVNCRH) is reduced after propofol treatment. Interestingly, artificially activating PVNCRH neurons through chemogenetics interfered with the anxiety‐reducing effects of propofol. Electrophysiological recordings indicated that propofol decreases the activity of PVNCRH neurons by increasing spontaneous inhibitory postsynaptic currents (sIPSCs). Further, reducing the levels of γ‐aminobutyric acid type A receptor β3 (GABAAβ3) subunits in PVNCRH neurons diminished the anxiety‐relieving effects of propofol. In conclusion, this study provides a mechanistic and preclinical rationale to treat pain‐associated anxiety‐like behaviors using a single dose of propofol.

Abstract Plasma membrane lysis is an effective anticancer strategy, which mostly relying on soluble molecular membranolytic agents. However, nanomaterial-based membranolytic agents has been largely unexplored. Herein, we introduce a mesoporous membranolytic nanoperforators (MLNPs) via a nano- and molecular-scale multi-patterning strategy, featuring a spiky surface topography (nanoscale patterning) and molecular-level periodicity in the spikes with a benzene-bridged organosilica composition (molecular-scale patterning), which cooperatively endow an intrinsic membranolytic activity. Computational modelling reveals a nanospike-mediated multivalent perforation behaviour, i.e., multiple spikes induce nonlinearly enlarged membrane pores compared to a single spike, and that benzene groups aligned parallelly to a phospholipid molecule show considerably higher binding energy than other alignments, underpinning the importance of molecular ordering in phospholipid extraction for membranolysis. Finally, the antitumour activity of MLNPs is demonstrated in female Balb/c mouse models. This work demonstrates assembly of organosilica based bioactive nanostructures, enabling new understandings on nano-/molecular patterns co-governed nano-bio interaction.

Abstract The Gabija system is a newly discovered bacterial immune system that consists of GajA and GajB. Here we report the cryo-EM structure of the Gabija complex from Bacillus cereus VD045 at 3.6 Å, which provides the direct evidence of interactions between GajA and GajB. The Gabija complex is an octameric ring structure with four GajA and four GajB. GajA is an OLD nucleases family protein, while GajB belongs to the SF1 helicases. The Gabija complex has sequence-specific DNA nuclease activity and prefers circular rather than linear DNA as substrate, its activity is more sensitive to concentrations change of nucleotides compared to GajA alone. Our data suggest a mechanism of Gabija immunity: the nuclease activity of Gabija complex is inhibited under physiological conditions, while it is activated by depletion of NTP and dNTP upon the replication and transcription of invading phages and cleave the circular DNA to prevent phage DNA replication.

Abstract Chemical C–N coupling from CO2 and NO3 –, driven by renewable electricity, toward urea synthesis is an appealing alternative for Bosch–Meiser urea production. However, the unmatched kinetics in CO2 and NO3 – reduction reactions and the complexity of C- and N-species involved in the co-reduction render the challenge of C–N coupling, leading to the low urea yield rate and Faradaic efficiency. Here, we report a single-atom copper-alloyed Pd catalyst (Pd4Cu1) that can achieve highly efficient C–N coupling toward urea electrosynthesis. The reduction kinetics of CO2 and NO3 – is regulated and matched by steering Cu doping level and Pd4Cu1/FeNi(OH)2 interface. Charge-polarized Pdδ–-Cuδ+ dual-sites stabilize the key *CO and *NH2 intermediates to promote C–N coupling. The synthesized Pd4Cu1-FeNi(OH)2 composite catalyst achieves a urea yield rate of 436.9 mmol gcat. –1 h–1 and Faradaic efficiency of 66.4%, as well as a long cycling stability of 1000 h. In-situ spectroscopic results and theoretical calculation reveal that atomically dispersed Cu in Pd lattice promotes the deep reduction of NO3 – to *NH2, and the Pd-Cu dual-sites lower the energy barrier of the pivotal C–N coupling between *NH2 and *CO.

Abstract In face-to-face communication, multimodal cues such as prosody, gestures, and mouth movements can play a crucial role in language processing. While several studies have addressed how these cues contribute to native (L1) language processing, their impact on non-native (L2) comprehension is largely unknown. Comprehension of naturalistic language by L2 comprehenders may be supported by the presence of (at least some) multimodal cues, as these provide correlated and convergent information that may aid linguistic processing. However, it is also the case that multimodal cues may be less used by L2 comprehenders because linguistic processing is more demanding than for L1 comprehenders, leaving more limited resources for the processing of multimodal cues. In this study, we investigated how L2 comprehenders use multimodal cues in naturalistic stimuli (while participants watched videos of a speaker), as measured by electrophysiological responses (N400) to words, and whether there are differences between L1 and L2 comprehenders. We found that prosody, gestures, and informative mouth movements each reduced the N400 in L2, indexing easier comprehension. Nevertheless, L2 participants showed weaker effects for each cue compared to L1 comprehenders, with the exception of meaningful gestures and informative mouth movements. These results show that L2 comprehenders focus on specific multimodal cues – meaningful gestures that support meaningful interpretation and mouth movements that enhance the acoustic signal – while using multimodal cues to a lesser extent than L1 comprehenders overall.

Radar jamming recognition is a key step in electronic countermeasures, and accurate and sufficient labeled samples are essential for supervised learning-based recognition methods. However, in real practice, collected radar jamming samples often have weak labels (i.e., noisy-labeled or unlabeled ones), which degrade recognition performance. Additionally, recognition performance is hindered by limitations in capturing the global features of radar jamming. The Transformer (TR) has advantages in modeling long-range relationships. Therefore, a weakly supervised Transformer is proposed to address the issues of performance degradation under weak supervision. Specifically, complementary label (CL) TR, called RadarCL-TR, is proposed to improve radar jamming recognition accuracy with noisy samples. CL learning and a cleansing module are successively utilized to detect and remove potentially noisy samples. Thus, the adverse influence of noisy samples is mitigated. Additionally, semi-supervised learning (SSL) TR, called RadarSSL-PL-TR, is proposed to boost recognition performance under unlabeled samples via pseudo labels (PLs). Network generalization is improved by training with pseudo-labeling unlabeled samples. Moreover, the RadarSSL-PL-S-TR is proposed to further promote recognition performance, where a selection module identifies reliable pseudo-labeling samples. The experimental results show that the proposed RadarCL-TR and RadarSSL-PL-S-TR outperform comparison methods in recognition accuracy by at least 7.07% and 6.17% with noisy and unlabeled samples, respectively.

Background and objectiveThe measurement of portal venous pressure (PVP) has been extensively studied, primarily through indirect methods. However, the potential of ultrasound-guided percutaneous transhepatic PVP measurement as a direct method has been largely unexplored. This study aimed to investigate the accuracy, safety, and feasibility of this approach.MethodsIn vitro, the experiment aimed to select a needle that could accurately transmit pressure, had a small inner diameter and was suitable for liver puncture, and performed on 20 healthy New Zealand white rabbits. An ultrasound-guided percutaneous transhepatic portal vein puncture was undertaken to measure PVP. Additionally, free hepatic venous pressure (FHVP) and wedged hepatic venous pressure (WHVP) were measured under digital subtraction angiography (DSA). The correlation between the two methods was assessed. Enroll study participants from October 18, 2023 to November 11, 2023 with written informed consent. Five patients were measured the PVP under ultrasound guidance before surgery to determine the feasibility of this measurement method.ResultsThere was no significant difference in the results obtained using 9 different types of needles (P > 0.05). This demonstrated a great repeatability (P < 0.05). The 22G chiba needle with small inner diameter, allowing for accurate pressure transmission and suitable for liver puncture, was utilized for percutaneous transhepatic PVP measurement. There were positive correlations between PVP and HVPG (r = 0.881), PVP and WHVP (r = 0.709), HVPG and WHVP (r = 0.729), IVCP and FHVP (r = 0.572). The PVP was accurately and safely measured in 5 patients with segmental hepatectomy. No complications could be identified during postoperative ultrasound.ConclusionPercutaneous transhepatic portal venous puncture under ultrasound guidance is accurate, safe and feasible to measure portal venous pressure.Clinical trial registration numberThis study has been registered in the Chinese Clinical Trial Registry with registration number ChiCTR2300076751.

Abstract Mitochondrial apoptosis is strictly controlled by BCL-2 family proteins through a subtle network of protein interactions. The tumor suppressor protein p53 triggers transcription-independent apoptosis through direct interactions with BCL-2 family proteins, but the molecular mechanism is not well understood. In this study, we present three crystal structures of p53-DBD in complex with the anti-apoptotic protein BCL-2 at resolutions of 2.3–2.7 Å. The structures show that two loops of p53-DBD penetrate directly into the BH3-binding pocket of BCL-2. Structure-based mutations at the interface impair the p53/BCL-2 interaction. Specifically, the binding sites for p53 and the pro-apoptotic protein Bax in the BCL-2 pocket are mostly identical. In addition, formation of the p53/BCL-2 complex is negatively correlated with the formation of BCL-2 complexes with pro-apoptotic BCL-2 family members. Defects in the p53/BCL-2 interaction attenuate p53-mediated cell apoptosis. Overall, our study provides a structural basis for the interaction between p53 and BCL-2, and suggests a molecular mechanism by which p53 regulates transcription-independent apoptosis by antagonizing the interaction of BCL-2 with pro-apoptotic BCL-2 family members.

Abstract This study aimed to estimate the healthcare costs of kidney transplantation compared with dialysis using a propensity score approach to handle potential treatment selection bias. We included 693 adult wait-listed patients who started renal replacement therapy between 1998 and 2012 in Region Skåne and Stockholm County Council in Sweden. Healthcare costs were measured as annual and monthly healthcare expenditures. In order to match the data structure of the kidney transplantation group, a hypothetical kidney transplant date of persons with dialysis were generated for each dialysis patient using the one-to-one nearest-neighbour propensity score matching method. Applying propensity score matching and inverse probability-weighted regression adjustment models, the potential outcome means and average treatment effect were estimated. The estimated healthcare costs in the first year after kidney transplantation were €57,278 (95% confidence interval (CI) €54,467–60,088) and €47,775 (95% CI €44,313–51,238) for kidney transplantation and dialysis, respectively. Thus, kidney transplantation leads to higher healthcare costs in the first year by €9,502 (p = 0.066) compared to dialysis. In the following two years, kidney transplantation is cost saving [€36,342 (p

Abstract Provide reference data on which EQ-5D-3L value set should be used with Chinese patients with chronic kidney disease (CKD); assess differences in health-related quality of life (HRQoL) based on the use of the Chinese (from 2014 and 2018), the UK, and the Japanese value sets; and examine differences in utility scores for key preventive influencing factors. Data from 373 patients with CKD recruited for a cross-sectional multicenter HRQoL survey were used. Differences among utility scores based on the four value sets were determined using Wilcoxon signed rank test. Intra-class correlation coefficient (ICCs) and Bland–Altman plots were used to evaluate consistency among utility scores and Tobit regression model was used to analyze the influencing factors of utility scores. There were significant differences between utility scores based on the four value sets, with the Chinese 2018 value set yielding the highest utility (0.957). ICCs between the value sets for China 2014, the UK, and Japan were all greater than 0.9, whereas the ICCs between the value sets for China 2018 and the other three were all less than 0.7. The influencing factors of utility scores included CKD stages, age, education level, city, and primary renal disease. This was the first study to report findings on the health utility of patients with CKD based on the two Chinese EQ-5D-3L value sets. Overall, the Chinese value sets performed similarly to the other two value sets (UK and Japan) commonly used in the Chinese population; however, value sets for different countries were not interchangeable. In Chinese contexts, the two value sets for China were recommended and the choice of which one should consider whether the value set of choice was established with a sample that is consistent with the targeted population.

Oncidium, an important tropical orchid, has high ornamental value due to its specific color and occupies a significant market position for the worldwide flower. Transcriptome analysis of flower and leaf color formation provides new sources for producing novel Oncidium hybridum cultivars. We sequenced 12 samples of flowers (yellow and white) and leaves (striped and regular) of O. hybridum and assembled 381,136 and 453,566 unigene sequences from RNA-seq data, respectively. Among unigenes, 662 and 1,324 differentially expressed genes were identified in flower and leaf samples, respectively. Gene ontology and pathway enrichment showed that secondary metabolite biosynthetic pathways were responsible for flower and leaf color formation. It was determined that UGT75C1, E2.4.1.115, CCD7, E2.1.1.76, and CCoAOMT are involved in regulating flower color, and UGT75C1, LHCB, UGT, RP-L18Ae, and ABCB1 play crucial roles in regulating leaf color. Kyoto Encyclopedia of Genes and Genomes analysis revealed that UGT75C1 was significantly enriched in the anthocyanin biosynthetic pathway, showing effects on flower and leaf colors. This study was the first detailed analysis of the molecular mechanisms of O. hybridum flower and leaf colors, and the results advanced the understanding of the genetic basis of flower and leaf colors; they also provided additional support for improving commercial value and producing novel cultivars of O. hybridum.

Summary: Dysregulated lipid metabolism occurs in pathological processes characterized by cell proliferation and migration. Nonetheless, the mechanism of increased mitochondrial lipid oxidation is poorly appreciated in diabetic cardiac fibrosis, which is accompanied by enhanced fibroblast proliferation and migration. Herein, increased WTAP expression promotes cardiac fibroblast proliferation and migration, contributing to diabetic cardiac fibrosis. Knockdown of WTAP suppresses mitochondrial lipid oxidation, fibroblast proliferation and migration to ameliorate diabetic cardiac fibrosis. Mechanistically, WTAP-mediated m6A methylation of AR induced its degradation, dependent on YTHDF2. Additionally, AR directly interacts with mitochondrial lipid oxidation enzyme Decr1; overexpression of AR-suppressed Decr1-mediates mitochondrial lipid oxidation, inhibiting cardiac fibroblast proliferation and migration. Knockdown of AR produced the opposite effect. Clinically, increased WTAP and YTHDF2 levels correlate with decreased AR expression in human DCM heart tissue. We describe a mechanism wherein WTAP boosts higher mitochondrial lipid oxidation, cardiac fibroblast proliferation, and migration by enhancing AR methylation in a YTHDF2-dependent manner.

This study presenting the cryo-EM structure of human SNAPc in complex with U6-1 PSE, significantly enforces our understanding of the mechanism of the SNAPc assembly, the PSE-specific recognition by SNAPc and the PIC assembly on U6 snRNA promoter.

The aryl hydrocarbon receptor (AHR) plays important roles in regulating xenobiotic metabolism, cellular differentiation, and immunity. Here, the authors present multiple crystal structures of the Drosophila AHR PAS-B domain, providing insights into the mechanism of AHR ligand binding

Abstract Fetal aberrant right subclavian artery (ARSA) is a relatively common sonographic finding. Congenital heart disease (CHD) is the most common structural abnormality in patients with ARSA. We aimed to assess the prevalence of genetic abnormalities, particularly sequence variants, in fetuses with CHD and ARSA. By clinical phenotyping and genomic sequencing, we retrospectively reviewed all fetuses with a prenatal diagnosis of CHD combined with ARSA at a single center. As a result, we identified 30 fetuses with ARSA combined with CHD, with conotruncal anomalies being the most common (n = 12, 40%), followed by left ventricular outflow tract obstruction (n = 6, 20%) and atrioventricular septal defects (n = 6, 20%). Overall, 18 (60%) cases had a genetic diagnosis. Copy number variation sequencing analysis identified six (20%) fetuses with aneuploidy and seven (23%) with pathogenic copy-number variants. Whole-exome sequencing (WES) analysis of the remaining 17 cases revealed diagnostic genetic variants in five (29%) cases, indicating that the diagnostic yield of WES for the entire cohort was 17% (5/30). Our findings reveal the high burden of genetic abnormalities in fetal CHD with ARSA. Single-gene disorders contribute substantially to the genetic etiology of fetal CHD with ARSA.

Abstract Pyrimidine catabolism is implicated in hepatic steatosis. Dihydropyrimidine dehydrogenase (DPYD) is an enzyme responsible for uracil and thymine catabolism, and DPYD human genetic variability affects clinically observed toxicity following 5-Fluorouracil administration. In an in vitro model of fatty acid-induced steatosis, the pharmacologic inhibition of DPYD resulted in protection from lipid accumulation. Additionally, a gain-of-function mutation of DPYD, created through clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR-Cas9) engineering, led to an increased lipid burden, which was associated with altered mitochondrial functionality in a hepatocarcionma cell line. The studies presented herein describe a novel role for DPYD in hepatocyte metabolic regulation as a modulator of hepatic steatosis.

Engineering peptide assembly that controls integrin ligand presentation on the molecular level possesses by far the highest ligand density, expanding the perspective of ligand-density-dependent modulation.

Land carbon fluxes play a critical role in ecosystems, and acquiring a comprehensive global database of carbon fluxes is essential for understanding the Earth’s carbon cycle. The primary methods of obtaining the spatial distribution of land carbon fluxes include utilizing machine learning models based on in situ measurements, estimating through satellite remote sensing, and simulating ecosystem models. Recently, an innovative machine learning product known as the Global Carbon Flux Dataset (GCFD) has been released. In this study, we assessed the reliability of the GCFD by comparing it with existing data products, including two machine learning products (FLUXCOM and NIES (National Institute for Environmental Studies)), two ecosystem model products (TRENDY and EC-LUE (eddy covariance–light use efficiency model)), and one remote sensing product (Global Land Surface Satellite), on both site and global scales. Our findings indicate that, in terms of average absolute difference, the spatial distribution of the GCFD is most similar to the NIES product, albeit with slightly larger discrepancies compared to the other two types of products. When using site observations as the benchmark, gross primary production (GPP), respiration of ecosystem (RECO), and net ecosystem exchange of machine learning products exhibit higher R2 (ranging from 0.57 to 0.85, 0.53–0.79, and 0.31–0.70, respectively) compared to model products and remote sensing products. Furthermore, we analyzed the spatial and temporal distribution characteristics of carbon fluxes in various regions. The results demonstrate an upward trend in both GPP and RECO over the past two decades, while NEE exhibits an opposite trend. This trend is particularly pronounced in tropical regions, where higher GPP is observed in tropical, subtropical, and oceanic climate zones. Additionally, two remote sensing variables that influence changes in carbon fluxes, i.e., fraction absorbed photosynthetically active radiation and leaf area index, exhibit relatively consistent spatial and temporal characteristics. Overall, our study can provide valuable insights into different types of carbon flux products and contribute to understanding the general features of global carbon fluxes.

Chemical warfare agents (CWAs) have brought great threats to human life and social stability, and it is critical to investigate protective materials. MOF (metal–organic framework) gels are a class with an extended MOF architecture that are mainly formed using metal–ligand coordination as an effective force to drive gelation, and these gels combine the unique characteristics of MOFs and organic gel materials. They have the advantages of a hierarchically porous structure, a large specific surface area, machinable block structures and rich metal active sites, which inherently meet the requirements for adsorption and catalytic detoxification of CWAs. A series of advances have been made in the adsorption and catalytic detoxification of MOF gels as chemical warfare agents; however, overall, they are still in their infancy. This review briefly introduces the latest advances in MOF gels, including pure MOF gels and MOF composite gels, and discusses the application of MOF gels in the adsorption and catalytic detoxification of CWAs. Meanwhile, the influence of microstructures (pore structures, metal active site, etc.) on the detoxification performance of protective materials is also discussed, which is of great significance in the exploration of high-efficiency protective materials. Finally, the review looks ahead to next priorities. Hopefully, this review can inspire more and more researchers to enrich the performance of MOF gels for applications in chemical protection and other purification and detoxification processes.

Single sodium-ion solid electrolyte that meets the requirements of practical applications is difficult to design. Here, the authors show how kinetic stability via the creation of a self-passivating solid electrolyte interphase allows a homogenous glass solid electrolyte to exhibit remarkable electrochemical stability with sodium metal.

In the developing central nervous system, oligodendrocyte precursor cells (OPCs) differentiate into oligodendrocytes, which form myelin around axons. Oligodendrocytes and myelin are essential for the function of the central nervous system, as evidenced by the severe neurological symptoms that arise in demyelinating diseases such as multiple sclerosis and leukodystrophy. Although many cell-intrinsic mechanisms that regulate oligodendrocyte development and myelination have been reported, it remains unclear whether interactions among oligodendrocyte-lineage cells (OPCs and oligodendrocytes) affect oligodendrocyte development and myelination. Here, we show that blocking vesicle-associated membrane protein (VAMP) 1/2/3-dependent exocytosis from oligodendrocyte-lineage cells impairs oligodendrocyte development, myelination, and motor behavior in mice. Adding oligodendrocyte-lineage cell-secreted molecules to secretion-deficient OPC cultures partially restores the morphological maturation of oligodendrocytes. Moreover, we identified L-type prostaglandin D synthase as an oligodendrocyte-lineage cell-secreted protein that promotes oligodendrocyte development and myelination in vivo. These findings reveal a novel autocrine/paracrine loop model for the regulation of oligodendrocyte and myelin development.

ObjectiveTo investigate the effect of aerobic exercise on five dimensions of physical self-worth, exercise capacity, physical condition, physical attractiveness, and physical quality in body self-esteem of Chinese college students.MethodsBy searching PubMed, Web of Science, Cochrane Library, CNIK database, VIP database, WANFANG database platform, we searched for the subject terms or keywords "body self-esteem", "Chinese college students", "Systematic evaluation", "Aerobic exercise", "Exercise intervention", "Meta-Analysis". The search method was a combination of subject terms and keywords and title, and the search period was from database creation to The search was conducted from database creation to May 2022. A total of 3221 articles were searched, and 9 articles were included in the study through repeated screening. Risk of bias was assessed with Cochrane and the quality of studies in the literature was assessed using Grade pro software. The outcome indicators of the included literature were analysed using review manager 5.4 software and StataMP 17.0 software.ResultsNine papers including 1613 subjects were included. results of Meta-analysis showed that aerobic exercise was effective in improving physical self-worth (WMD = 1.46, 95% CI: 1.08-1.83, pConclusionAerobic exercise can effectively improve the body self-esteem of Chinese college students. In exercise, male students pursue is athletic ability and physical fitness, and female students pursue is the sense of physical self-worth and physical attractiveness. Aerobic exercise has a greater increase in body self-esteem for obese or Obese college students. Aerobics and physical dance are the most cost-effective for improving body self-esteem. Medium-intensity relative to low-intensity exercise was effective for body self-esteem intervention. A single exercise session of 90 minutes was more effective than a single 30-minute session in boosting body self-esteem, and the overall intervention duration of 16 weeks was more effective than 10 weeks.

Effective condition monitoring and fault diagnosis of bearings can not only maximize the life of rolling bearings and prevent unexpected shutdowns caused by equipment failures but also eliminate unnecessary costs and waste caused by excessive maintenance. However, the existing deep-learning-based bearing fault diagnosis models have the following defects. First of all, these models have a large demand for fault data. Second, the previous models only consider that single-scale features are generally less effective in diagnosing bearing faults. Therefore, we designed a bearing fault data collection platform based on the Industrial Internet of Things, which is used to collect bearing status data from sensors in real time and feed it back into the diagnostic model. On the basis of this platform, we propose a bearing fault diagnosis model based on deep generative models with multiscale features (DGMMFs) to solve the above problems. The DGMMF model is a multiclassification model, which can directly output the abnormal type of the bearing. Specifically, the DGMMF model uses 4 different variational autoencoder models to augment the bearing data and integrates features of different scales. Compared with single-scale features, these multiscale features contain more information and can perform better. Finally, we conducted a large number of related experiments on the real bearing fault datasets and verified the effectiveness of the DGMMF model using multiple evaluation metrics. The DGMMF model has achieved the highest value under all metrics, among which the value of precision is 0.926, the value of recall is 0.924, the value of accuracy is 0.926, and the value of F1 score is 0.925.

Though the brain was long characterized as an immune-privileged organ, findings in recent years have shown extensive communications between the brain and peripheral immune cells. We now know that alterations in the peripheral immune system can affect the behavioral outputs of the central nervous system, but we do not know which brain cells are affected by the presence of peripheral immune cells. Glial cells including microglia, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells (OPCs) are critical for the development and function of the central nervous system. In a wide range of neurological and psychiatric diseases, the glial cell state is influenced by infiltrating peripheral lymphocytes. However, it remains largely unclear whether the development of the molecular phenotypes of glial cells in the healthy brain is regulated by lymphocytes. To answer this question, we acutely purified each type of glial cell from immunodeficient Rag2-/- mice. Interestingly, we found that the transcriptomes of microglia, astrocytes, and OPCs developed normally in Rag2-/- mice without reliance on lymphocytes. In contrast, there are modest transcriptome differences between the oligodendrocytes from Rag2-/- and control mice. Furthermore, the subcellular localization of the RNA-binding protein Quaking, is altered in oligodendrocytes. These results demonstrate that the molecular attributes of glial cells develop largely without influence from lymphocytes and highlight potential interactions between lymphocytes and oligodendrocytes.

Chemical composition of sediments is often used to evaluate paleoclimate condition, provenance, tectonic setting, depositional condition, and paleoproductivity. However, the validity of these proxies has long been questioned. The comprehensive use of organic and inorganic multi-indicators in combination when interpreting issues related to terrestrial shales should be advocated. The paleodepositional environment, origin of organic matter (OM) and factor controlling OM accumulation in the Early Jurassic Badaowan (J1b) and Sangonghe (J1s) as well as Middle Jurassic Xishanyao (J2x) lacustrine shales in the East Fukang Sag are reassessed by using organic geochemical characteristics of the OM. Some previous knowledge is updated, and some knowledge is further supported by more evidence. The typical clay-rich shale developed under a lacustrine sedimental environment, and the thermal maturity of these organic-rich shales has entered the oil window and formed economic hydrocarbon potential for the tight-oil and shale-oil reservoirs. The paleoclimate conditions of the study area were warm and humid from the Early to Middle Jurassic periods but were colder and drier after the Middle Jurassic period. The salinity of the water column ranged from freshwater to brackish conditions. The J2x Formation was deposited under oxic conditions, while J1b and J1s formations developed under suboxic and reducing environmental conditions. The J2x Formation OM mainly derived from higher plants was deposited in a terrestrial environment,while the OM of J1b and J1s formations was a mixed OM derived from higher plants and bacteria with little algae deposited under bay/estuary environments alternated with terrestrial environments. It is effective to reflect the paleoclimate by element index and judge the salinity by the updated element thresholds, but it is not effective to evaluate the paleoredox conditions by common elemental ratios and to evaluate the paleoproductivity by Ba in the study area.

Restoring vegetation on waste dumps is imperative because soil erosion heavily impacts these areas and creates erosion micro-topographies, including bare slopes, rills, ephemeral gullies, and deposit bodies. These micro-topographies may affect seedling emergence by forming special micro-habitats, although the mechanism is vague. This study determined the substrate chemical (i.e., pH and electrical conductivity) and physical (i.e., capillary porosity, capillary water content, and mechanical composition) properties of different micro-topographies. In addition, the temporal dynamics of micro-climates (i.e., air temperature and air humidity), substrate hydrothermal conditions (i.e., substrate temperature and water content), and seedling emergence were investigated. Redundancy analysis (RDA), random forest (RF), and receiver operating characteristic (ROC) curve analysis were then used to identify the main factors affecting seedling emergence and clarify the relationships among the environmental conditions. Our results demonstrate that seedling densities in the rill, ephemeral gully, and deposit body were 1.78 times, 3.42 times, and 3.97 times higher than those on the bare slope, respectively. More species were found in the rill, ephemeral gully, and deposit body (Artemisia annua, Salsola collina, Setaria viridis, and Tribulus terrestris) than on the bare slope (Salsola collina). The main factors affecting seedling emergence were air humidity, substrate temperature, and substrate water content. The mechanical composition may have affected substrate water content during the initial stage of seedling emergence and substrate temperature during the entire period. We demonstrate that the ephemeral gully and deposit body may provide micro-habitats with a lower substrate temperature and higher substrate water content, which are favorable to seedling emergence, thus guiding vegetation restoration on waste dumps or other disturbed areas.

The Upper Ordovician Wufeng to Lower Silurian Longmaxi Formation has a good material basis for marine shale gas development, and the structural preservation condition is the key factor to control the rich and integrated shale gas reservoirs in the Wuxi area of Chongqing City, China. Based on the seismic-structural interpretation data, combined with the regional structural background and drilling effect, the structural deformation characteristics and shale gas structural preservation conditions are comprehensively analyzed in the study area. The Wuxi area is located at the structural junction of the Sichuan Basin and southern Dabashan along with strong structural deformations. Seven rows of NW to near EW structural belts are mainly developed. The fold styles and fault development degrees of different structural belts are different, and the difference in the structural preservation conditions of shale gas is also obvious. The study results reveal that the shale gas structure preservation conditions of the Wufeng−Longmaxi Formation in the Wuxi area are overall poor and only locally better. The structure preservation conditions for shale gas enrichment and accumulation are divided into four grades, such as the good Class I area, the general Class II area, the poor Class III area, and the very poor Class IV area. Among them, the Heiloumen structural zone and Huangcaoping buried structural zone nearby the Sichuan Basin have good preservation conditions and are classified as the good Class I preservation area. The macroscopic preservation type of shale gas in the Wufeng−Longmaxi Formation of the Wuxi area belongs to the complex structural preservation of the basin margin. Three structural preservation modes of shale gas in the study area have also been confirmed, including the lost destruction type, lost residual type, and trap preservation type. The trap preservation type is more conducive to the preservation of shale gas, which is the most favorable structural mode for shale gas exploration.

Abstract To provide an effective risk assessment of water inrush for coal mine safety production, a BP neural network prediction method for water inrush based on principal component analysis and deep confidence network optimization was proposed. Because deep belief network (DBN) is disadvantaged by a long training time when establishing a high-dimensional data classification model, the principal component analysis (PCA) method is used to reduce the dimensionality of many factors affecting the water inrush of the coal seam floor, thus reducing the number of variables of the research object, redundancy and the difficulty of feature extraction and shortening the training time of the model. Then, a DBN network was used to extract secondary features from the processed nonlinear data, and a more abstract high-level representation was formed by combining low-level features to find the expression of the nonlinear relationship between the characteristics of water in bursts. Finally, a prediction model was established to predict the water inrush in coal mines. The superiority of this method was verified by comparing the prediction of the actual working face with the actual situation in typical mining areas of North China. The prediction accuracy of coal mine water inrush obtained by this algorithm is 94%, while the prediction accuracy of traditional BP algorithm is 70%, and the prediction accuracy of SVM algorithm is 88%.

Abstract Novel modalities such as PROTAC and RNAi have the ability to inadvertently alter the abundance of endogenous proteins. Currently available in vitro secondary pharmacology assays, which evaluate off-target binding or activity of small molecules, do not fully assess the off-target effects of PROTAC and are not applicable to RNAi. To address this gap, we developed a proteomics-based platform to comprehensively evaluate the abundance of off-target proteins. First, we selected off-target proteins using genetics and pharmacology evidence. This process yielded 2813 proteins, which we refer to as the “selected off-target proteome” (SOTP). An iterative algorithm was then used to identify four human cell lines out of 932. The 4 cell lines collectively expressed ~ 80% of the SOTP based on transcriptome data. Second, we used mass spectrometry to quantify the intracellular and extracellular proteins from the selected cell lines. Among over 10,000 quantifiable proteins identified, 1828 were part of the predefined SOTP. The SOTP was designed to be easily modified or expanded, owing to the rational selection process developed and the label free LC–MS/MS approach chosen. This versatility inherent to our platform is essential to design fit-for-purpose studies that can address the dynamic questions faced in investigative toxicology.

Astrocytes are important players in brain development, homeostasis, and disease. Here, the authors compare the transcriptional profiles of human and mouse astrocytes. They report species-specific susceptibility to oxidative stress and response to hypoxic and inflammatory conditions.

Abstract Infants who are small for gestational age (SGA) are at increased risk of neonatal and infant death, non-communicable diseases and growth retardation. However, the epidemiological characteristics of SGA remain unclear. We aim to explore the prevalence of SGA and to examine its socioeconomic associations by using data from 21 cities. 10,515,494 single live birth records between 2014 and 2019 from the Guangdong Women and Children Health Information System were included in the study. Descriptive statistical methods were used to analyze the prevalence trend of SGA and its distribution. We also analyze the associations between the prevalence of SGA and per-capita GDP. The prevalence of SGA in Guangdong Province from the years 2014–2019 was 13.17%, 12.96%, 11.96%, 12.72%, 11.45%, 11.30% respectively, and the overall prevalence was 12.28%. The prevalence of term SGA infants in Guangdong Province was 12.50%, which was much higher than that of preterm SGA (7.71%). There was a significant negative correlation between the SGA prevalence and per-capita GDP in 21 cities of Guangdong Province. The level of economic development may affect the prevalence of SGA. The prevalence of SGA in full term infants is significantly higher than in premature infants, suggesting that most SGA infants may be born at a later gestational age.

The structure of human tumor suppressor p53 in complex with the antiapoptotic protein BCL-xL reveals the basis of the p53–BCL-xL interaction and provides insight into the mechanisms of p53-mediated mitochondrial apoptosis.

Abstract Space radiation consists of energetic protons and other heavier ions. During the International Space Station program, chromosome aberrations in lymphocytes of astronauts have been analyzed to estimate received biological doses of space radiation. More specifically, pre-flight blood samples were exposed ex vivo to varying doses of gamma rays, while post-flight blood samples were collected shortly and several months after landing. Here, in a study of 43 crew-missions, we investigated whether individual radiosensitivity, as determined by the ex vivo dose–response of the pre-flight chromosome aberration rate (CAR), contributes to the prediction of the post-flight CAR incurred from the radiation exposure during missions. Random-effects Poisson regression was used to estimate subject-specific radiosensitivities from the preflight dose–response data, which were in turn used to predict post-flight CAR and subject-specific relative biological effectiveness (RBEs) between space radiation and gamma radiation. Covariates age, gender were also considered. Results indicate that there is predictive value in background CAR as well as radiosensitivity determined preflight for explaining individual differences in post-flight CAR over and above that which could be explained by BFO dose alone. The in vivo RBE for space radiation was estimated to be approximately 3 relative to the ex vivo dose response to gamma irradiation. In addition, pre-flight radiosensitivity tended to be higher for individuals having a higher background CAR, suggesting that individuals with greater radiosensitivity can be more sensitive to other environmental stressors encountered in daily life. We also noted that both background CAR and radiosensitivity tend to increase with age, although both are highly variable. Finally, we observed no significant difference between the observed CAR shortly after mission and at > 6 months post-mission.

Anterior vaginal prolapse (AVP), the most common form of pelvic organ prolapse, has deleterious effects on women’s health. Here the authors employ single-cell RNA-seq to construct a transcriptomic atlas of vaginal wall cells from AVP patients, and find that extracellular matrix dysregulation and immune reaction are associated with AVP.

Determination of the dominant factors which affect soil moisture (SM) predictions for drought analysis is an essential step to assess the reliability of the prediction results. However, artificial intelligence (AI) based drought modelling only provides prediction results without the physical interpretation of the models. Here, we propose an explainable AI (XAI) framework to reveal the modelling of SM drought events. Random forest based site-specific SM prediction models were developed using the data from 30 sites, covering 8 vegetation types. The unity of multiply XAI tools was applied to interpret the site-models both globally (generally) and locally. Globally, the models were interpreted using two methods: permutation importance and accumulated local effect (ALE). On the other hand, for each drought event, the models were interpreted locally via Shapley additive explanations (SHAP), local interpretable model-agnostic explanation (LIME) and individual conditional expectation (ICE) methods. Globally, the dominant features for SM predictions were identified as soil temperature, atmospheric aridity, time variables and latent heat flux. But through local interpretations of the drought events, SM showed a greater reliance on soil temperature, atmospheric aridity and latent heat flux at grass sites, with higher correlation to the time-dependent parameters at the sites located in forests. The temporal variation of the feature which effects the drought events was also demonstrated. The interpretation could shed light on how predictions are made and could promote the application of AI techniques in drought prediction, which may be useful for irrigation and water resource management.

Soil moisture (SM) has significant impacts on the Earth’s energy and water cycle system. Remote sensing, such as the Soil Moisture Active Passive (SMAP) mission, has delivered valuable estimations of global surface soil moisture. However, it has a 2~3 days revisit time leading to gaps between SMAP areas. To achieve accurate and comprehensive real-time forecast of SM, we propose a spatial–temporal deep learning model based on the Convolutional Gated Recursive Units with Data Integration (DI_ConvGRU) to capture the spatial and temporal variation in SM simultaneously by modeling the influence of adjacent SM values in space and time. Experiments show that the DI_ConvGRU outperforms the ConvGRU with Linear Interpolation (interp_ConvGRU) and the Long Short-Term Memory with Data Integration (DI_LSTM). The best performance (Bias = 0.0132 m3/m3, ubRMSE = 0.022 m3/m3, R = 0.977) has been achieved through the use of spatial–temporal deep learning model and Data Integration term. In comparison with interp_ConvGRU and DI_LSTM, DI_ConvGRU has improved the model performance in 74.88% and 68.99% of the regions according to RMSE, respectively. The predictability of SM depends highly on SM memory characteristics. DI_ConvGRU can provide accurate spatial–temporal forecast for SM with missing data, making them potentially useful for applications such as filling observational gaps in satellite data.

Environmental abiotic stresses limit plant growth, development, and reproduction. This study aims to reveal the response of Brassica napus to salt stress. Here, transcriptomics, metabolomics, and proteomics analysis were performed on 15 Brassica napus leave samples treated with salt at different times. Through functional enrichment analyzing the differentially expressed genes (DEGs), differential metabolites (DMs) and differentially expressed proteins (DEPs), the key factors that dominate Brassica napus response to salt stress were identified. The results showed that the two key hormones responding to salt stress were Abscisic acid (ABA) and jasmonic acid (JA). Salt stress for 24h is an important milestone. Brassica napus adjusted multiple pathways at 24h to avoid over-response to salt stress and cause energy consumption. The increased expression in BnPP2C is tangible evidence. In response to salt stress, JA and ABA work together to reduce the damage caused by salt stress in Brassica napus. The increased expression of all BnJAZs after salt stress highlighted the function of JA that cannot be ignored responding to salt stress. In addition, some metabolites, such as N-acetyl-5-hydroxytryptamine, L-Cysteine and L-(+)-Arginine, play a critical role in maintaining the balance of ROS. Proteins like catalase-3, cysteine desulfurase, HSP90 and P450_97A3 were the most critical differential proteins in response to salt stress. These findings of this study provide data support for Brassica napus breeding.

Vaginal microbiota (VMB) is associated with changes in Human papilloma virus (HPV) status, which consequently influences the risk of cervical cancer. This association was often confounded by personal risk factors. This pilot research aimed to explore the relationship between vaginal microbiota, personal risk factors and their interactions with HPV status conversion to identify the vaginal microbiota that was associated with HPV clearance under heterogeneous personal risk factors. A total of 38 women participated by self-collecting a cervicovaginal mucus (CVM) sample that was sent for metagenomics sequencing. Most of the participants also filled in personal risk factors questionnaire through an eHealth platform and authorized the use of their previous HPV genotyping results stored in this eHealth platform. Based on the two HPV results, the participants were grouped into three cohorts, namely HPV negative, HPV persistent infection, and HPV status conversion. The relative abundance of VMB and personal factors were compared among these three cohorts. A correlation investigation was performed between VMB and the significant personal factors to characterize a robustness of the panel for HPV status change using R programming. At baseline, 12 participants were HPV-negative, and 22 were HPV-positive. Within one year, 18 women remained HPV-positive, 12 were HPV-negative and 4 participants showed HPV clearance. The factors in the eHealth questionnaire were systematically evaluated which identified several factors significantly associated with persistent HPV infection, including age, salary, history of reproductive tract infection, and the total number of sexual partners. Concurrent vaginal microbiome samples suggest that a candidate biomarker panel consisting of Lactobacillus gasseri, Streptococcus agalactiae, and Timona prevotella bacteria, which may be associated with HPV clearance. This pilot study indicates a stable HPV status-related vaginal microbe environment. To establish a robust biomarker panel for clinical use, larger cohorts will be recruited into follow-up studies.

Early time series classification (ETSC) is crucial for real-world time-sensitive applications. This task aims to classify time series data with least timestamps at the desired accuracy. Early methods used fixed-length time series to train the deep models, and then quit the classification process by setting specific exiting rules. However, these methods may not adapt to the length variation of flow data in ETSC. Recent advances have proposed end-to-end frameworks, which leveraged the Recurrent Neural Networks to handle the varied-length problems, and the exiting subnets for early quitting. Unfortunately, the conflict between the classification and early exiting objectives is not fully considered. To handle these problems, we decouple the ETSC task into the varied-length TSC task and the early exiting task. First, to enhance the adaptive capacity of classification subnets to the data length variation, a feature augmentation module based on random length truncation is proposed. Then, to handle the conflict between classification and early exiting, the gradients of these two tasks are projected into a unified direction. Experimental results on 12 public datasets demonstrate the promising performance of our proposed method.