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In cold regions, the dynamic compressive strength (DCS) of rock damaged by freeze-thaw weathering significantly influences the stability of rock engineering. Nevertheless, testing the dynamic strength under freeze-thaw weathering conditions is often both time-consuming and expensive. Therefore, this study considers the effect of characteristic impedance on DCS and aims to quickly determine the DCS of frozen-thawed rocks through the application of machine-learning techniques. Initially, a database of DCS for frozen-thawed rocks, comprising 216 rock specimens, was compiled. Three external load parameters (freeze-thaw cycle number, confining pressure, and impact pressure) and two rock parameters (characteristic impedance and porosity) were selected as input variables, with DCS as the predicted target. This research optimized the kernel scale, penalty factor, and insensitive loss coefficient of the support vector regression (SVR) model using five swarm intelligent optimization algorithms, leading to the development of five hybrid models. In addition, a statistical DCS prediction equation using multiple linear regression techniques was developed. The performance of the prediction models was comprehensively evaluated using two error indexes and two trend indexes. A sensitivity analysis based on the cosine amplitude method has also been conducted. The results demonstrate that the proposed hybrid SVR-based models consistently provided accurate DCS predictions. Among these models, the SVR model optimized with the chameleon swarm algorithm exhibited the best performance, with metrics indicating its effectiveness, including root mean square error (RMSE) = 3.9675, mean absolute error (MAE) = 2.9673, coefficient of determination (R2) = 0.98631, and variance accounted for (VAF) = 98.634. This suggests that the chameleon swarm algorithm yielded the most optimal results for enhancing SVR models. Notably, impact pressure and characteristic impedance emerged as the two most influential parameters in DCS prediction. This research is anticipated to serve as a reliable reference for estimating the DCS of rocks subjected to freeze-thaw weathering.

Abstract Biochar-based sulfidized nano-sized zero-valent iron (SNZVI/BC) can effectively immobilize cadmium (Cd) in contaminated paddy soils. However, the synergistic effects between biochar and SNZVI on Cd immobilization, as well as the underlying mechanisms remain unclear. Herein, a soil microcosm incubation experiment was performed to investigate the immobilization performance of SNZVI/BC towards Cd in the contaminated paddy soil. Results indicated that the addition of SNZVI/BC at a dosage of 3% significantly lessened the concentration of available Cd in the contaminated soil from 14.9 (without addition) to 9.9 mg kg−1 with an immobilization efficiency of 33.3%, indicating a synergistic effect. The sequential extraction results indicated that the proportion of the residual Cd in the contaminated soil increased from 8.1 to 10.3%, manifesting the transformation of the unstable Cd fractions to the steadier specie after application of SNZVI/BC. Also, the addition of SNZVI/BC increased soil pH, organic matter, and dissolved organic carbon, which significantly altered the bacterial community in the soil, enriching the relative abundances of functional microbes (e.g., Bacillus, Clostridium, and Desulfosporosinus). These functional microorganisms further facilitated the generation of ammonium, nitrate, and ferrous iron in the contaminated paddy soil, enhancing nutrients’ availability. The direct interaction between SNZVI/BC and Cd2+, the altered soil physicochemical properties, and the responded bacterial community played important roles in Cd immobilization in the contaminated soil. Overall, the biochar-based SNZVI is a promising candidate for the effective immobilization of Cd and the improvement of nutrients’ availability in the contaminated paddy soil. Graphical Abstract

BackgroundCardiac lipid metabolism reprogramming is recognized as a critical pathological factor in the progression of chronic heart failure (CHF). The therapeutic potential of digilanid C and electroacupuncture stimulation (ES) in enhancing lipid metabolism and cardiac function has been established. However, the optimal synergistic regulatory strategies of these interventions on cardiac lipid metabolism have yet to be elucidated.MethodsThis study aimed to comprehensively evaluate the impact of a digilanid C-ES combination on cardiac steatosis remodeling in CHF. Assessments were conducted across various dimensions, including myocardial oxygen consumption, mitochondrial function, and lipid metabolism. Additionally, we sought to uncover the underlying neuromolecular mechanisms.ResultsOur findings, at both molecular and morphological levels, indicated that the synergistic application of digilanid C and ES significantly inhibited myocardial fibrosis and steatosis. This combination therapy facilitated the repair of cardiac neuro-vascular uncoupling and induced a reprogramming of lipid metabolism. Notably, the digilanid C-ES combination ameliorated cardiomyocyte apoptosis and enhanced mitochondrial biogenesis in CHF, leading to a restructured energy supply pattern. Cardiac immunofluorescence analyses revealed the aggregation of cardiac glial cells (CGCs) at sites of abnormal neurovascular coupling, a response to cardiac lipid degeneration. This was accompanied by a marked reduction in the abnormally elevated expression of interleukin 6 (IL-6) and glutamatergic signaling, which correlated with the severity of cardiac steatosis and the aberrant activation of CGCs. The combined therapy was found to activate the Janus kinase 1 (JAK1)/signal transducer and activator of transcription 3 (STAT3) pathway, effectively attenuated lipid accumulation and over-recruitment of CGCs and deprivation of glutamatergic nerves.ConclusionThese findings underscore the potential of digilanid C and ES combination therapy as a novel approach to modulate the complex interplay between neurovascular dynamics and metabolic dysregulation in CHF.

Abstract Dual-parameter pressure-temperature sensors are widely employed in personal health monitoring and robots to detect external signals. Herein, we develop a flexible composite dual-parameter pressure-temperature sensor based on three-dimensional (3D) spiral thermoelectric Bi2Te3 films. The film has a (000l) texture and good flexibility, exhibiting a maximum Seebeck coefficient of −181 μV K–1 and piezoresistance gauge factor of approximately −9.2. The device demonstrates a record-high temperature-sensing performance with a high sensing sensitivity (−426.4 μV K−1) and rapid response time (~0.95 s), which are better than those observed in most previous studies. In addition, owing to the piezoresistive effect in the Bi2Te3 film, the 3D-spiral deviceexhibits significant pressure-response properties with a pressure-sensing sensitivity of 120 Pa–1. This innovative approach achieves high-performance dual-parameter sensing using one kind of material with high flexibility, providing insight into the design and fabrication of many applications, such as e-skin.

Tissue-resident memory T (TRM) cells infiltrating solid tumors could influence tumor progression and the response to immune therapies. However, the proportion and prognostic value of TRM cells in the bone marrow (BM) of patients with acute myeloid leukemia (AML) are unclear. In this study, we used flow cytometry to assay the phenotype of 49 BM samples from patients newly diagnosed with AML (ND-AML). We found that the BM CD8+ effector memory (TEM) cells highly expressed CD69 (CD8+ TRM-like T cells), and their percentage was significantly increased in patients with ND-AML compared with that in healthy individuals (HI). The high percentage of CD8+ TRM-like subset was associated with poor overall survival in our ND-AML cohort. The Kaplan–Meier Plotter database verified a significantly reduced survival rate among patients with high expression of CD8+ TRM-like T cell characteristic genes (CD8A, CD69, and TOX), especially the M4 and M5 subtypes. Phenotypic analysis revealed that the BM CD8+ TRM-like subpopulation exhibited exhausted T cell characteristics, but its high expression of CD27 and CD28 and low expression of CD57 suggested its high proliferative potential. The single-cell proteogenomic dataset confirmed the existence of TRM-like CD8+ T cells in the BM of patients with AML and verified the high expression of immune checkpoints and costimulatory molecules. In conclusion, we found that the accumulation of BM CD8+ TRM-like cells could be an immune-related survival prediction marker for patients with AML.

Our comprehensive review plunges into the cutting-edge advancements of polymeric microneedle drug delivery systems, underscoring their transformative potential in the realm of transdermal drug administration. Our scrutiny centers on the substrate materials pivotal for microneedle construction and the core properties that dictate their efficacy. We delve into the distinctive interplay between microneedles and dermal layers, underscoring the mechanisms by which this synergy enhances drug absorption and precision targeting. Moreover, we examine the acupoint–target organ–ganglion nexus, an innovative strategy that steers drug concentration to specific targets, offering a paradigm for precision medicine. A thorough analysis of the clinical applications of polymeric microneedle systems is presented, highlighting their adaptability and impact across a spectrum of therapeutic domains. This review also accentuates the systems’ promise to bolster patient compliance, attributed to their minimally invasive and painless mode of drug delivery. We present forward-looking strategies aimed at optimizing stimulation sites to amplify therapeutic benefits. The anticipation is set for the introduction of superior biocompatible materials with advanced mechanical properties, customizing microneedles to cater to specialized clinical demands. In parallel, we deliberate on safety strategies aimed at boosting drug loading capacities and solidifying the efficacy of microneedle-based therapeutics. In summation, this review accentuates the pivotal role of polymeric microneedle technology in contemporary healthcare, charting a course for future investigative endeavors and developmental strides within this burgeoning field.

Exploring species diversity along elevational gradients is important for understanding the underlying mechanisms. Our study focused on analyzing the species diversity of fungal communities and their subcommunities at different trophic and taxonomic levels across three high mountains of the Korean Peninsula, each situated in a different climatic zone. Using high-throughput sequencing, we aimed to assess fungal diversity patterns and investigate the primary environmental factors influencing fungal diversity. Our results indicate that soil fungal diversity exhibits different elevational distribution patterns on different mountains, highlighting the combined effects of climate, soil properties, and geographic topology. Notably, the total and available phosphorus contents in the soil emerged as key determinants in explaining the differences in diversity attributed to soil properties. Despite the varied responses of fungal diversity to elevational gradients among different trophic guilds and taxonomic levels, their primary environmental determinants remained remarkably consistent. In particular, total and available phosphorus contents showed significant correlations with the diversity of the majority of the trophic guilds and taxonomic levels. Our study reveals the absence of a uniform diversity pattern along elevational gradients, underscoring the general sensitivity of fungi to soil conditions. By enriching our understanding of fungal diversity dynamics, this research enhances our comprehension of the formation and maintenance of elevational fungal diversity and the response of microbial communities in mountain ecosystems to climate change. This study provides valuable insights for future ecological studies of similar biotic communities.

PurposeTo explore white matter network topological properties changes in middle-aged and elderly patients with functional constipation (Functional Constipation, FC) by diffusion tensor imaging (DTI), and to evaluate the correlation between the abnormal changes and clinical data.Methods29 FC patients and 31 age- and sex-matched healthy controls (HC) were recruited. Magnetic resonance imaging and clinical data were collected. The white matter network changes in FC patients were analyzed using deterministic fiber tracking methods, graph theory algorithms, and partial correlation analysis with clinical data.ResultsThe nodal clustering coefficient and nodal local efficiency of FC patients in the right orbital inferior frontal gyrus, right medial superior frontal gyrus, right rectus muscle, right hippocampus, left paracentral lobule and left temporal pole, and the nodal clustering coefficient in right orbital superior frontal gyrus, left cuneus lobe and right superior occipital gyrus, the nodal local efficiency in the right medial and paracingulate gyrus, right precuneus and right dorsolateral superior frontal gyrus of FC patients are lower than that of HC. The nodal local efficiency and clustering coefficient of FC patients in left hippocampus, left amygdala, right parietal inferior limbic angular gyrus and right angular gyrus, the nodal local efficiency in the right fusiform gyrus, left supplementary motor cortex and the nodal efficiency in the left lateral temporal gyrus and right orbital middle frontal gyrus (ORBmid.R) of FC patients are higher than that of HC. The nodal efficiency of ORBmid.R in FC was positively correlated with the Patient Assessment of Constipation quality of life questionnaire (PAC-QoL).ConclusionMiddle-aged and elderly FC patients have differences in the nodal level properties in the limbic system, supplementary motor cortex, and default mode network brain regions, and the nodal efficiency of ORBmid.R was positively correlated with the PAC-QoL score, revealing that FC may be related to the abnormal processing of visceral sensorimotor in ORBmid.R and providing potential imaging diagnostic markers and therapeutic targets for middle-aged and elderly FC patients.

IntroductionParkinson’s disease (PD) remains one kind of a complex, progressive neurodegenerative disease. Levodopa and dopamine agonists as widely utilized PD therapeutics have not shown significant positive long-term outcomes. Emerging evidences indicate that electroacupuncture (EA) have potential effects on the therapy of nervous system disorders, particularly PD, but its specific underlying mechanism(s) remains poorly understood, leading to the great challenge of clinical application and management. Previous study has shown that acupuncture ameliorates PD motor symptoms and dopaminergic neuron damage by modulating intestinal dysbiosis, but its intermediate pathway has not been sufficiently investigated.MethodsA rat model of PD was induced using rotenone. The therapeutic effect of EA on PD was assessed using the pole and rotarod tests and immunohistostaining for tyrosine hydroxylase (TH) in the substantia nigra (SN) of brain. The role of gut microbiota was explored using 16S rRNA gene sequencing and metabonomic analysis. PICRUSt2 analysis, lipidomic analysis, LPS and inflammatory factor assays were used for subsequent exploration and validation. Correlation analysis was used to identify the key bacteria that EA regulates lipid metabolism to improve PD.ResultsThe present study firstly reappeared the effects of EA on protecting motor function and dopaminergic neurons and modulation of gut microbial dysbiosis in rotenone-induced PD rat model. EA improved motor dysfunction (via the pole and rotarod tests) and protected TH+ neurons in PD rats. EA increased the abundance of beneficial bacteria such as Lactobacillus, Dubosiella and Bifidobacterium and decreased the abundance of Escherichia-Shigella and Morganella belonging to Pseudomonadota, suggesting that the modulation of gut microbiota by EA improving the symptoms of PD motility via alleviating LPS-induced inflammatory response and oxidative stress, which was also validated by various aspects such as microbial gene functional analysis, fecal metabolomics analysis, LPS and inflammatory factor assays and SNpc lipidomics analysis. Moreover, correlation analyses also verified strong correlations of Escherichia-Shigella and Morganella with motor symptoms and SNpc lipid peroxidation, explicating targets and intermediate pathways through which EA improve PD exercise symptom.ConclusionOur results indicate that the improvement of motor function in PD model by EA may be mediated in part by restoring the gut microbiota, which intermediate processes involve circulating endotoxins and inflammatory mediators, SNpc oxidative stress and lipid peroxidation. The gut-microbiome - brain axis may be a potential mechanism of EA treatment for the PD.

Si-based anode materials have a relatively high theoretical specific capacity and low operating voltage, greatly enhancing the energy density of rechargeable lithium-ion batteries (LIBs). However, their practical application is seriously hindered by the instability of active particles and anode electrodes caused by the huge swelling during cycling. How to maintain the stability of the charge transfer network and interface structure of Si particles is full of challenges. To address this issue, we have developed a novel Si@Fe3O4/AC/CNR anode by in-situ growing one-dimensional high elastic carbon nano-ribbons to wrap Si nanoparticles. This special structure can construct fast channels of electron transport and lithium ion diffusion, and stabilize the surface structure of Si nanoparticles during cycling. With these promising architectural features, the Si@Fe3O4/AC/CNR composite possesses a high specific capacity of 1279.4 mAh/g at 0.5 A/g, and a superior cycling life with 80 % capacity retention after 700 cycles. Even at a high current density of 20.0 A/g, the composite still delivers a capacity of 621.2 mAh/g. The facile synthetic approach and high performance of Si@Fe3O4/AC/CNR anodes provide practical insight into advanced anode materials with large volume expansion for high-energy-density LIBs.

Abstract Aiming at the output current distortion problem in the low frequency operation of permanent magnet synchronous motor (PMSM) drive system of modular multilevel converter (MMC), the essential relationship between the output current distortion and the injected components is analyzed in this paper. A current harmonic suppression method combining feedforward and feedback compensation is proposed. Firstly, the feedback control method is applied to transform the MMC three‐phase output current into the dq rotating coordinate system at fundamental frequency ω. The harmonics of the AC terms to be suppressed are filtered out. The dominant fundamental frequency component turned into the DC term is retained. Then combined with feedforward control, the control performance of the system is improved. Secondly, the deadbeat predictive current control is improved by introducing an integral link in it. System disturbances caused by parameter changes can be compensated in real time. The design of the control system is simplified and the static error is reduced. Meanwhile, the system has the advantages of small torque pulsation and fast speed response. Finally, the PMSM drive system model of the 11‐level MMC is built in MATLAB/Simulink. The correctness and effectiveness of the proposed suppression method are verified.

Abstract Over the decades, the integrated modeling (IM) environment for magnetically confined fusion has evolved from a single, isolated, proprietary numerical computing software to an open, flexible platform emphasizing sharing, communication, and workflow. This development direction is consistent with the FAIR4RS principles put forward by the scientific community in recent years. In this article, we describe how the FAIR4RS principles were put into practice during the development of the IM management tool FyDev for the Experimental Advanced Superconducting Tokamak (EAST). FyDev integrates the process of building, deploying, and invoking research software, automating the entire process. FyDev can also assign a unique ID for each software, convert the software ID to a Python module, and encapsulate a package management tool to enhance the software building process, ensuring consistency throughout the entire phase of the research software find, access, use, and invocation in a uniform contextual environment.

Abstract While multiple external stimuli (e.g., temperature, light, pressure) have been reported to regulate gas adsorption, limited studies have been conducted on controlling molecular admission in nanopores through the application of electric fields (E-field). Here we show gas adsorption capacity and selectivity in zeolite molecular sieves can be regulated by an external E-field. Through E-field pre-activation during degassing, several zeolites exhibited enhanced CO2 adsorption and decreased CH4 and N2 adsorptions, improving the CO2/CH4 and CO2/N2 separation selectivity by at least 25%. The enhanced separation performance of the zeolites pre-activated by E-field was maintained in multiple adsorption/desorption cycles. Powder X-ray diffraction analysis and ab initio computational studies revealed that the cation relocation and framework expansion induced by the E-field accounted for the changes in gas adsorption capacities. These findings demonstrate a regulation approach to sharpen the molecular sieving capability by E-fields and open new avenues for carbon capture and molecular separations.

Surface-enhanced Raman scattering (SERS) provides an alternative rapid detection method for pesticide residues in food, but fenvalerate possesses poor affinity to the novel metal substrate, thus restricting its analysis. To break this bottleneck, a SERS-active platform with an Ag/rGO composite structure was engineered using a facile method for fenvalerate detection. Ag nanoparticles with a 60 nm diameter can grow evenly on the top and bottom of rGO layers under intense ultrasonic oscillation, and rGO in hybrid material acts as an ideal hotspot holder between the gaps of Ag nanoparticles, not only allowing the interaction area to be enhanced both electromagnetically and chemically but also enabling the capture and enrichment of fenvalerate pesticide molecules into the “hotspot” area to improve detection sensitivity. Ag/rGO composite substrate possesses superior SERS performance with an ultralow detectable concentration of 4-aminothiophenol (10−10 M) and good reproducibility, endowing the material with a better enhancement effect than pure Ag nanoparticles. When used as the SERS substrate for fenvalerate detection, Ag/rGO composite material showed excellent performance in both experiments and theoretical calculation, with the limit of detection (LOD) of fenvalerate being as low as 1.69 × 10−5 mg/kg and a detection model with an R2 of 99.2%, demonstrating its exciting potential as a SERS substrate for pesticides detection.

Abstract Drug resistance and poor treatment response are major obstacles to the effective treatment of acute myeloid leukemia (AML). A deeper understanding of the mechanisms regulating drug resistance and response genes in AML is therefore urgently needed. Our previous research has highlighted the important role of nuclear factor E2-related factor 2 (NRF2) in AML, where it plays a critical role in detoxifying reactive oxygen species and influencing sensitivity to chemotherapy. In this study, we identify a core set of direct NRF2 targets that are involved in ferroptosis, a novel form of cell death. Of particular interest, we find that glutathione peroxidase 4 (GPX4) is a key ferroptosis gene that is consistently upregulated in AML, and high expression of GPX4 is associated with poor prognosis for AML patients. Importantly, simultaneous inhibition of NRF2 with ML385 and GPX4 with FIN56 or RSL3 synergistically targets AML cells, triggering ferroptosis. Treatment with ML385 + FIN56/RSL3 resulted in a marked reduction in NRF2 and GPX4 expression. Furthermore, NRF2 knockdown enhanced the sensitivity of AML cells to the ferroptosis inducers. Taken together, our results suggest that combination therapy targeting both NRF2 and GPX4 may represent a promising approach for the treatment of AML.

Previous research has indicated that natural landscapes exhibit a greater capacity for ameliorating negative emotional states in individuals when compared to urban landscapes. Nevertheless, significant scientific inquiries, such as the uniformity of the rejuvenating effect across distinct categories of natural landscapes on college students and the choice of the optimal plant community for achieving the most potent restorative effect, remain unexplored. This study aimed to address these questions by selecting four plant communities (single-layer grassland, single-layer woodland, tree-grass composite woodland, tree-shrub-grass composite woodland) and using an electroencephalography method to capture the neuroelectric activity of the participants in combination with the Positive and Negative Affect Schedule score to explore the effects of plant community types on emotional recovery. The results showed that all four plant communities significantly increased positive emotions and significantly reduced negative emotions. There was no significant difference in the recovery effect of positive emotions among the four plant community types, but there was a significant difference in the recovery effect of negative emotions. The effect of tree-shrub-grass composite woodland on the negative emotion recovery effect is the best; the EEG results found that the alpha wave amplitude induced by the tree-shrub-grass composite woodland was significantly higher than that of the other three groups of plant communities, and the EEG and behavioral results were consistent. The results show that the tree-shrub-grass composite woodland has the best restoration effect and has stronger planning and design significance.

Background: Pathological progression from non-alcoholic fatty liver disease (NAFLD) to liver fibrosis (LF) to hepatocellular carcinoma (HCC) is a common dynamic state in many patients. Curcumin, a dietary supplement derived from the turmeric family, is expected to specifically inhibit the development of this progression. However, there is a lack of convincing evidence.Methods: The studies published until June 2023 were searched in PubMed, Web of Science, Embase, and the Cochrane Library databases. The SYstematic Review Center for Laboratory animal Experimentation (SYRCLE) approach was used to evaluate the certainty of evidence. StataSE (version 15.1) and Origin 2021 software programs were used to analyze the critical indicators.Results: Fifty-two studies involving 792 animals were included, and three disease models were reported. Curcumin demonstrates a significant improvement in key indicators across the stages of NAFLD, liver fibrosis, and HCC. We conducted a detailed analysis of common inflammatory markers IL-1β, IL-6, and TNF-α, which traverse the entire disease process. The research results reveal that curcumin effectively hinders disease progression at each stage by suppressing inflammation. Curcumin exerted hepatoprotective effects in the dose range from 100 to 400 mg/kg and treatment duration from 4 to 10 weeks. The mechanistic analysis reveals that curcumin primarily exerts its hepatoprotective effects by modulating multiple signaling pathways, including TLR4/NF-κB, Keap1/Nrf2, Bax/Bcl-2/Caspase 3, and TGF-β/Smad3.Conclusion: In summary, curcumin has shown promising therapeutic effects during the overall progression of NAFLD–LF–HCC. It inhibited the pathological progression by synergistic mechanisms related to multiple pathways, including anti-inflammatory, antioxidant, and apoptosis regulation.

Summary: Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p

This paper reports a two-step method for preparing a metal-organic framework (MOF) MIL-101 (Fe) based substrate with high sensitivity and stability for surface-enhanced Raman scattering (SERS) analysis. Firstly, MIL-101 (Fe) nanoparticles were synthesized using a traditional solvothermal method. Next, gold nanoparticles (AuNPs) were produced through a reduction method, and the AuNPs/MIL-101 (Fe) composite substrate was created by combining MIL-101 (Fe) with AuNPs. The adsorption capacity of the substrate and its SERS activity after multiple cleaning were tested. Using Rhodamine 6 G (R6G) as the probe molecule, the substrate's detection capability reached 10-8 M, with a relative standard deviation (RSD) of approximately 13.15%, indicating excellent SERS performance and uniformity. The ideal detection capability for sulfapyridine using the composite matrix can be as low as 10-6 M. This proposed substrate is convenient and efficient, holding great potential for the rapid and sensitive detection of antibiotic residues and other environmental pollutants.

Surface ground motion produced by underground blasts is significantly influenced by near-surface geological conditions. However, near-surface low-propagation velocity layers were always ignored in past analyses of ground motions due to their thin thickness. With the rising concern about surface ground motions produced by the ascendant scale and frequentness of underground excavation and mining, close attention is gradually paid to ground blast vibrations. Therefore, systemic experiments were conducted and took seven months in an underground mine to clarify the variation of motion from underground rock to surface ground. The attenuation of surface ground peak particle velocities (PPVs) is compared to that in underground rock, and horizontal amplitudes are compared to vertical amplitudes. Differences between bedrock and surface ground vibrations are analyzed to illustrate the site effect of near-surface lower-propagation velocity layers. One-dimensional site response analysis is employed to quantify the influence of different geological profiles on surface ground vibrations. The experimental data and site response analysis allowed the following conclusions: (1) geological site effects mainly produce decreasing dominant frequency (DF) of surface ground vibrations; (2) the site amplification effect of blast vibration needs to be characterized by peak particle displacement (PPD); (3) shear waves (S-waves) begin to dominate and surface Rayleigh waves (R-waves) develop as blast-induced ground vibrations travel upward through rock and lower-velocity layers to the surface. The comparison of response relative displacement to a critical value is best to assess the potential for cracking on surface structures.

Abstract Trip data that records each vehicle’s trip activity on the road network describes the operation of urban traffic from the individual perspective, and it is extremely valuable for transportation research. However, restricted by data privacy, the trip data of individual-level cannot be opened for all researchers, while the need for it is very urgent. In this paper, we produce a city-scale synthetic individual-level vehicle trip dataset by generating for each individual based on the historical trip data, where the availability and trip data privacy protection are balanced. Privacy protection inevitably affects the availability of data. Therefore, we have conducted numerous experiments to demonstrate the performance and reliability of the synthetic data in different dimensions and at different granularities to help users properly judge the tasks it can perform. The result shows that the synthetic data is consistent with the real data (i.e., historical data) on the aggregated level and reasonable from the individual perspective.

An up-and-coming concept that seeks to transform how students learn about and study complex systems, as well as how industrial workers are trained, metaverse technology is characterized in this context by its use in virtual simulation and analysis. In this work, a virtual environment is created that duplicates real-world situations and enables immersive and interactive learning in the educational metaverse. For this purpose, we built a digital twin of the Nanyang Technological University (NTU) campus as a foundation, called NTUniverse. It is designed as an educational metaverse in which various academic and analytical applications are digitized as 3D content embedded within this virtual campus. The approach to digitally twinning educational systems and embedding them within virtual campuses enables remote and collaborative learning as well as professional technical skills training. It also makes feasible the analysis of abstract concepts, complicated structures, dynamic processes, and sensitive industrial procedures virtually, which is otherwise challenging if not impossible to perform in the real world. The work offers important insights into the behaviors and interactions of systems in the metaverse by evaluating design choices and user interests. NTUniverse is an attempt to explore a novel approach that addresses remote education and training challenges. Three efforts with NTUniverse will be discussed in this work, including (1) digitalization of the NTU campus; (2) campus train modelling and simulation; and (3) science, technology, engineering and mathematics education.

Nine tea cultivars planted in Enshi were selected and processed into “Lichuan black tea”. Sensory evaluation showed that cultivar had the greatest influence on taste and aroma quality, including sweetness, umami and concentration of taste, as well as sweet and floral fragrances of aroma. The non-volatile and volatile components were identified by UPLC-Q-TOF/MS and GC–MS, and PCA analysis showed good separation between cultivars, which could cause the difference in quality. Baiyaqilan, Meizhan and Echa 10 had a floral aroma, with obvious difference in their aromatic composition from other cultivars. Moreover, Echa 10 also had a strong sweet aroma. The key aroma components in Echa 10 (with the largest cultivation area) were further investigated by GC-O-MS combined with odor activity value (OAV) analysis, included β-damascenone, phenylethylaldehyde, nonenal, geraniol, linalool, jasmonone, (E)-2-nonenal, β-cyclocitral, (E)-β-ocimene, methyl salicylate, β-ionone, 2,6,10,10-tetramethyl-1-oxaspiro[4.5]dec-6-ene, citral, β-myrcene, nerol, phenethyl alcohol, benzaldehyde, hexanal, nonanoic acid, and jasmin lactone.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with an increased risk of cardiovascular diseases (CVDs), putatively via inflammasome activation. We pursued an inflammatory gene modifier scan for CHIP-associated CVD risk among 424,651 UK Biobank participants. We identified CHIP using whole-exome sequencing data of blood DNA and modeled as a composite, considering all driver genes together, as well as separately for common drivers (DNMT3A, TET2, ASXL1, and JAK2). We developed predicted gene expression scores for 26 inflammasome-related genes and assessed how they modify CHIP-associated CVD risk. We identified IL1RAP as a potential key molecule for CHIP-associated CVD risk across genes and increased AIM2 gene expression leading to heightened JAK2- and ASXL1-associated CVD risk. We show that CRISPR-induced Asxl1-mutated murine macrophages had a particularly heightened inflammatory response to AIM2 agonism, associated with an increased DNA damage response, as well as increased IL-10 secretion, mirroring a CVD-protective effect of IL10 expression in ASXL1 CHIP. Our study supports the role of inflammasomes in CHIP-associated CVD and provides evidence to support gene-specific strategies to address CHIP-associated CVD risk.

Sodium in the coals of West China has received persistent attention due to its high contents and severe pollutions’ problems during coal utilization. A total of seven drill samples of the Jurassic coals from Tatuo coalfield, Qinghai Province, were collected and analysed using optical microscopy, scanning electron microscopy in conjunction with energy-dispersive X-ray spectrometry, X-ray powder diffraction, inductively coupled plasma mass spectrometry and X-ray fluorescence spectrometry. The results indicate that the Tatuo coal is of lower-high ash, medium volatile matter and ultra-low sulphur bituminous coal. Tatuo coal contains much more Na 2 O (> 2%), and belongs to high-sodium coal. The maceral index and element ratios of Sr/Cu, Fe/Mn and Sr/Ba showed that Tatuo coal was formed in a terrestrial peat swamp environment. The minerals in Tatuo coal, including clay minerals and halite, quartz, gypsum and rutile, are mainly concentrated in the bottom and top parts of the coal seam. Combined with scanning electron microscopy in conjunction with energy-dispersive X-ray spectrometry and optical microscope characteristics, the sodium could be carried into the peat/coal after the peat formation by basin fluids. The East Kunlun orogenic belt may be the main source of these minerals.

Knowledge Distillation (KD) is designed to train smaller student models using a larger pretrained teacher model. However, in decentralized data systems such as blockchain, privacy concerns may arise, making the data inaccessible. To address this issue, Data-Free KD (DFKD) methods have been proposed, which extract prior knowledge from teacher networks and use it to synthesize data for KD. Previous DFKD methods faced challenges due to the large search space of data generation. Recently, deep generative models (DGMs) have been proposed to learn data distribution using deep networks, which provides an efficient way to reduce the search space by generating a set of pseudo data. In this paper, we explore the performance of KD trained using pseudo samples generated by pretrained DGMs and find that the correlation with image quality is not always positive. Based on this observation, we propose a new DFKD framework called Generative Knowledge Distillation (GenKD) that reduces the search space by constructing a prior distribution modeled by DGMs for their power of likelihood estimation. Specifically, we use energy-based models (EBM) to generate data from the Maximum Likelihood Estimation (MLE) of the EBM and gradients from downstream KD tasks by policy gradient. We then train the student model using the pretrained teacher model and pseudo samples. We also implement our GenKD framework on several widely-used benchmarks, including CIFAR100, CIFAR10, and SVHN. Our experiments demonstrate that we can generate high-quality pseudo samples quantitatively and qualitatively using GenKD. Additionally, the top-1 accuracy of the student network can approach state-of-the-art (SOTA) DFKD methods trained using fewer pseudo samples and less generation time.

Measurement(s) speed Technology Type(s) Interpolation Imputation Technique Sample Characteristic - Location Xuancheng City Prefecture

Abstract Background Transversus abdominis plane (TAP) block can provide effective analgesia for abdominal surgery. However, it was questionable whether TAP had additional effect in the context of multimodal analgesia (MMA). Therefore, this study aimed to assess the additional analgesic effect of preoperative TAP block when added to MMA protocol in open gynecological surgery. Methods In this prospective, randomized-controlled trial, 64 patients scheduled for open gynecological surgery were randomized to receive preoperative TAP block (Study group, n = 32) or placebo (Control group, n = 32) in addition to MMA protocol comprising dexamethasone, acetaminophen, flurbiprofen and celecoxib, and rescued morphine analgesia. The primary outcome was rescued morphine within 24 h after surgery. Secondary outcomes included pain scores, adverse effects, quality of recovery measured by 40-item quality of recovery questionnaire score (QoR-40) at 24 h, and quality of life measured with short-form health survey (SF − 36) on postoperative day (POD) 30. Results The Study group had less rescued morphine than the control group within 24 h [5 (2–9) vs. 8.5 (5–12.8) mg, P = 0.013]. The Study group had lower pain scores at 1 h [3 (2–4) vs. 4 (3–5), P = 0.007], 2 h [3 (2–4) vs. 3.5 (3–5), P = 0.010] and 6 h [3 (2–3) vs. 3 (2.3–4), P = 0.028], lower incidence of nausea at 48 h (25.8% vs. 50%, P = 0.039), and higher satisfaction score [10 (10–10) vs. 10 (8–10), P = 0.041]. The SF-36 bodily pain score on POD 30 was higher in the Study group (59 ± 13 vs. 49 ± 16, P = 0.023). Conclusions Preoperative TAP block had additional analgesic effect for open gynecological surgery when used as part of multimodal analgesia. Rescued morphine within 24 h was significantly reduced and the SF-36 bodily pain dimension at 30 days after surgery was significantly improved. Trial registration www.chictr.org.cn (ChiCTR2000040343, on Nov 28 2020).

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous and aggressive tumor with high mortality and unfavorable prognosis. Numerous long non-coding RNAs (lncRNAs) have been confirmed to exert pivotal parts in cancers. Nevertheless, the functions of most lncRNAs in HNSCC need deeper exploration. Our present research tried to clarify the biological role of TM4SF19 antisense RNA 1 (TM4SF19-AS1) and investigate its regulatory mechanism in HNSCC. RT-qPCR analysis was done to test TM4SF19-AS1 expression and identify the up-regulation of TM4SF19-AS1 in HNSCC cells. Loss-of-function assays were also involved, and the data implied that TM4SF19-AS1 knockdown hampered the proliferation, migration, invasion, along with epithelial-mesenchymal transition (EMT) of HNSCC cells. In vivo assays revealed TM4SF19-AS1 depletion restrained HNSCC tumor growth. Additionally, mechanism experiments were implemented to uncover the underlying regulatory mechanism of TM4SF19-AS1 in HNSCC cells. It turned out that TM4SF19-AS1 modulated laminin subunit gamma 1 (LAMC1) expression via sequestering microRNA-153-3p (miR-153-3p) and recruiting heterogeneous nuclear ribonucleoprotein C (HNRNPC) protein. Rescue assays confirmed that TM4SF19-AS1 contributed to HNSCC cell malignant behaviors via up-regulating LAMC1. To summarize, TM4SF19-AS1 played an oncogenic role in HNSCC cells, signifying TM4SF19-AS1 may have the potential to be used as a novel molecular target for HNSCC diagnosis.

Abstract Tensor completion has gained considerable research interest in recent years and has been frequently applied to image restoration. This type of method basically employs the low‐rank nature of images, implicitly requiring that the whole picture is of globally consistent features. As a result, existing tensor completion algorithms often give reasonably good performance if the target image has only random pixel‐level missing. Unfortunately, pixel‐level missing is very rare in practice and it is often wanted to restore an image with irregular hole‐shaped missing, such as removing electricity poles from landscape photos or irrelevant people from tourist photos. This task is extremely difficult for traditional low‐rank based tensor completion methods. To overcome this drawback, a Contour Information regularized Tensor RIng Completion (CITRIC) method is proposed for practical image restoration. Meanwhile, the contour information regularization is used to capture significant local features, whereas the low‐rank tensor ring structure is utilized to capture as much global information as possible. The alternating direction method of multipliers (ADMM) is adopted to optimize the cost function. Extensive experimental results using real‐world images show that CITRIC is more practical than existing methods and can restore real‐world images with irregular hole‐shaped missing.

Abstract Sustained expression of programmed cell death receptor-1 (PD-1) is correlated with the exhaustion of T cells, and blockade of the PD-1 pathway is an effective immunotherapeutic strategy for treating various cancers. However, response rates are limited, and many patients do not achieve durable responses. Thus, it is important to seek additional strategies that can improve anticancer immunity. Here, we report that the bromodomain and extraterminal domain (BET) inhibitor JQ1 inhibits PD-1 expression in Jurkat T cells, primary T cells, and T-cell exhaustion models. Furthermore, JQ1 dramatically impaired the expression of PD-1 and T-cell immunoglobulin mucin-domain-containing-3 (Tim-3) and promoted the secretion of cytokines in T cells from patients with acute myeloid leukemia (AML). In line with that, BET inhibitor-treated CD19-CAR T and CD123-CAR T cells have enhanced anti-leukemia potency and resistant to exhaustion. Mechanistically, BRD4 binds to the NFAT2 and PDCD1 (encoding PD-1) promoters, and NFAT2 binds to the PDCD1 and HAVCR2 (encoding Tim-3) promoters. JQ1-treated T cells showed downregulated NFAT2, PD-1, and Tim-3 expression. In addition, BET inhibitor suppressed programmed death-ligand 1 (PD-L1) expression and cell growth in AML cell lines and in primary AML cells. We also demonstrated that JQ1 treatment led to inhibition of leukemia progression, reduced T-cell PD-1/Tim-3 expression, and prolonged survival in MLL-AF9 AML mouse model and Nalm6 (B-cell acute lymphoblastic leukemia cell)-bearing mouse leukemia model. Taken together, BET inhibition improved anti-leukemia immunity by regulating PD-1/PD-L1 expression, and also directly suppressed AML cells, which provides novel insights on the multiple effects of BET inhibition for cancer therapy.

Most studies of the genetics of the metabolome have been done in individuals of European descent. Here, the authors integrate genomics and metabolomics in Black individuals, highlighting the value of whole genome sequencing in diverse populations and linking circulating metabolites to human disease.

Background High and low birth weight are independently associated with increased cardiovascular disease risk in adulthood. Clonal hematopoiesis of indeterminate potential (CHIP), the age‐related clonal expansion of hematopoietic cells with preleukemic somatic mutations, predicts incident cardiovascular disease independent of traditional cardiovascular risk factors. Whether birth weight predicts development of CHIP later in life is unknown. Methods and Results A total of 221 047 adults enrolled in the UK Biobank with whole exome sequences and self‐reported birth weight were analyzed. Of those, 22 030 (11.5%) had low (4.0 kg). CHIP prevalence was higher among participants with low (6.0%, P=0.049) and high (6.3%, P

Characterized by the accumulation of somatic mutations in blood cell lineages, clonal hematopoiesis of indeterminate potential (CHIP) is frequent in aging and involves the expansion of mutated hematopoietic stem and progenitor cells (HSC/Ps) that leads to an increased risk of hematologic malignancy. However, the risk factors that contribute to CHIP-associated clonal hematopoiesis (CH) are poorly understood. Obesity induces a proinflammatory state and fatty bone marrow (FBM), which may influence CHIP-associated pathologies. We analyzed exome sequencing and clinical data for 47,466 individuals with validated CHIP in the UK Biobank. CHIP was present in 5.8% of the study population and was associated with a significant increase in the waist-to-hip ratio (WHR). Mouse models of obesity and CHIP driven by heterozygosity of Tet2, Dnmt3a, Asxl1, and Jak2 resulted in exacerbated expansion of mutant HSC/Ps due in part to excessive inflammation. Our results show that obesity is highly associated with CHIP and that a proinflammatory state could potentiate the progression of CHIP to more significant hematologic neoplasia. The calcium channel blockers nifedipine and SKF-96365, either alone or in combination with metformin, MCC950, or anakinra (IL-1 receptor antagonist), suppressed the growth of mutant CHIP cells and partially restored normal hematopoiesis. Targeting CHIP-mutant cells with these drugs could be a potential therapeutic approach to treat CH and its associated abnormalities in individuals with obesity.

This study delved into the aroma characteristics of “Qingxiang” oolong tea, analyzing six different cultivars and their processing modes. The findings showed that both cultivars and processing modes have a significant impact on the oolong tea aroma system. The study identified 18 terpenoid volatiles (VTs), 11 amino-acid-derived volatiles (AADVs), 15 fatty-acid-derived volatiles (FADVs), 3 carotenoid-derived volatiles (CDVs), and 10 other compounds in oolong tea that differentiate it from green and black tea. The turn-over stage was found to be the primary processing stage for oolong tea aroma formation. Molecular sensory analysis revealed that the “fresh” odor attribute is the basis for its aroma, while “floral and fruity” fragrances are its aroma characteristics. The perception of oolong tea as “fresh” and “floral and fruity” is influenced by the interactions of its aroma components. These findings provide a new basis for breed improvement and process enhancement in oolong tea production.

This study fristly investigated the taste quality formation and leaf conducting tissue changes in six types of Chinese tea (green, black, oolong, yellow, white, and dark) made from Mingke No.1 variety. Non-targeted metabolomics showed the vital manufacturing processes (green tea-de-enzyming, black tea-fermenting, oolong tea-turning-over, yellow tea-yellowing, white tea-withering, and dark tea-pile-fermenting) were highly related to their unique taste formation, due to different fermentation degree in these processes. After drying, the retained phenolics, theanine, caffeine, and other substances significantly impacted each tea taste quality formation. Meanwhile, the tea leaf conducting tissue structure was significantly influenced by high processing temperature, and the change of its inner diameter was related to moisture loss during tea processing, as indicated by its significant different Raman characteristic peaks (mainly cellulose and lignin) in each key process. This study provides a reference for process optimization to improve tea quality.

One of the main challenges in developing effective control strategies for the magnetic control system in tokamaks has been the difficulty in obtaining the last closed-flux surface (LCFS) evolution results from control commands. We have developed a data-driven model that combines a predictive model and a surrogate model for physics simulation programs. This model is capable of predicting the LCFS without relying on physical simulation codes. Addressing the data characteristics of LCFS, we have proposed a specialized discretization approach to achieve dimensionality reduction. Furthermore, we have excluding the control references, the model can be seamlessly integrated into the control system, providing real-time LCFS prediction. Following comprehensive testing and multifaceted evaluation, our model has demonstrated highly satisfactory results of 95% or above, meeting practical requirements.

A non-targeted metabolomics approach and sensory evaluation, coupled with multivariate statistical analysis, systematically uncover the impact of the rolling time on the quality parameters of black tea. GC-MS analysis reveals that a moderate extension of rolling time favorably contributes to the accumulation of characteristic aroma components in black tea. The volatile components reach their highest concentration in black tea samples processed during an 80-min rolling period. UHPLC-Q-TOF/MS analysis demonstrates a substantial decrease in the contents of catechins and flavonoids with an increase in rolling time. Simultaneously, the production of theaflavins, coupled with the degradation of green bitterness volatiles (GBVs), significantly contributes to the formation of endogenous aroma components in black tea. These findings underscore the close relationship between rolling time control and black tea quality, emphasizing that a moderate extension of the rolling time fosters the development of improved black tea flavor quality. The comprehensive quality evaluation indicates that the optimal duration is 80 min. However, the initial 0 to 20 min of rolling is a crucial phase for the genesis and transformation of black tea quality. This study offers valuable insights into the influence of rolling time on black tea quality, potentially enhancing future studies of rolling technology. It provides theoretical guidelines for optimizing the processing of Gongfu black tea.

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.

Introduction: Based on the green economic growth theory and the background of comprehensive promotion of high-quality development, the article evaluates and analyzes the dynamic evolution, convergence mechanism and influencing factors of Green Total Factor Productivity (GTFP) growth in 19 major urban agglomerations.Methods: By using the SBM-GML model method, the paper aims to study the existence of differences in green economic operation in urban agglomerations.Results: (1) The GTFP of Chinese urban agglomerations is in an effective state driven by technological progress, and the core driving role of technical efficiency has not been fully exploited, the constraints and limitations of resources, energy and environment on the space of high-quality development of urban agglomerations still exist. (2) There is no δ convergence in the GTFP growth of urban agglomerations, but there is a trend of β convergence, the pattern of coordinated regional development is gradually forming. (3) The eastern urban agglomerations show the competitiveness of green development and spatial convergence rate of GTFP growth better than other regions, and even present a synergistic development situation. (4) Industrial structure and financial service level have positive effects on GTFP growth of urban agglomerations, while business environment and capital deepening level have negative effects on them.Discussion: The research aims to provide reference for decision making to comprehensively promote regional synergistic development strategy in urban agglomerations of mainland China.

Constructed wetlands (CWs) are artificial systems that use natural processes to treat wastewater containing organic pollutants. This approach has been widely applied in both developing and developed countries worldwide, providing a cost-effective method for industrial wastewater treatment and the improvement of environmental water quality. However, due to the large organic carbon inputs, CWs is produced in varying amounts of CH4 and have the potential to become an important contributor to global climate change. Subsequently, research on the mitigation of CH4 emissions by CWs is key to achieving sustainable, low-carbon dependency wastewater treatment systems. This review evaluates the current research on CH4 emissions from CWs through bibliometric analysis, summarizing the reported mechanisms of CH4 generation, transfer and oxidation in CWs. Furthermore, the important environmental factors driving CH4 generation in CW systems are summarized, including: temperature, water table position, oxidation reduction potential, and the effects of CW characteristics such as wetland type, plant species composition, substrate type, CW-coupled microbial fuel cell, oxygen supply, available carbon source, and salinity. This review provides guidance and novel perspectives for sustainable and effective CW management, as well as for future studies on CH4 reduction in CWs.

This study employs a supervised learning method to predict the tunnel boring machine (TBM) penetration rate (PR) with high accuracy. To this end, the extreme gradient boosting (XGBoost) model is optimized based on two swarm intelligence algorithms, i.e., the sparrow search algorithm (SSA) and the whale optimization algorithm (WOA). Three other machine learning models, including random forest (RF), support vector machine (SVM), and artificial neural network (ANN) models, are also developed as the drawback. A database created in Shenzhen (China), comprising 503 entries and featuring 10 input variables and 1 output variable, was utilized to train and test the prediction models. The model development results indicate that the use of SSA and WOA has the potential to improve the XGBoost model performance in predicting the TBM performance. The performance evaluation results show that the proposed WOA-XGBoost model has achieved the most satisfactory performance by resulting in the most reliable prediction accuracy of the four performance indices. This research serves as a compelling illustration of how combined approaches, such as supervised learning methods and swarm intelligence algorithms, can enhance TBM prediction performance and can provide a reference when solving other related engineering problems.

Tea polysaccharide (TPS) is a bioactive compound extracted from tea. It has raised great interest among researchers due to its bioactivity. However, few studies focused on the diversity of TPS in its compositions and antioxidant activity. This study collected 140 different tea varieties from four tea germplasm gardens in China, and their TPSs in tea shoots were extracted. The extraction efficiency, composition contents, including neutral sugar, uronic acid, protein, and tea polyphenols, and the scavenging abilities of hydroxyl radical (·OH) and superoxide radical (O2-·) of 140 TPSs were determined and analyzed. The results showed significant differences in the compositions and antioxidant activities of TPS extracted from different tea varieties. By applying hierarchical clustering analysis (HCA), we selected nine tea varieties with high TPS extraction efficiency and 26 kinds of TPS with high antioxidant capacity.

BackgroundThe enteric nervous system (ENS) plays a central role in developing Parkinson's disease (PD) constipation, and the regulation of the ENS may be a key component in treating PD constipation. Electroacupuncture (EA) can effectively treat constipation symptoms in PD, but research on its specific mechanisms, especially in terms of ENS, is relatively lacking. Therefore, we investigated whether EA at ST25 promotes the restoration of ENS structure and colonic motor function in the rotenone-induced PD constipation rat model.MethodsIn this study, we evaluated constipation symptoms by stool characteristics, excretion and water volume, and whole gut transit time and observed colonic motility regulation through colonic motion detection and pathological changes in the colonic myenteric nervous plexus by transmission electron microscopy and immunofluorescence staining.ResultsEA significantly improved the constipation symptoms and positively adjusted the colonic motility in rotenone-induced PD constipation rats. At the same time, EA reversed the rotenone-induced colonic myenteric nervous plexus injury and regulated the ratio of inhibitory and excitatory neurotransmitters.ConclusionOur results indicate that EA treatment of PD constipation may be mediated through the adjustment of ENS.

Serum urate concentration can be studied in large datasets to find genetic and epigenetic loci that may be related to cardiometabolic traits. Here the authors identify and replicate 100 urate-associated CpGs, which provide insights into urate GWAS loci and shared CpGs of urate and cardiometabolic traits.

Many genetic loci have been identified to be associated with kidney disease, but the molecular mechanisms are not well understood. Here, the authors perform epigenome-wide association studies on kidney function measures to identify epigenetic marks and pathways involved in kidney function.

Abstract Nematodes play vital roles in soil ecosystems. To understand how their communities and coexistence patterns change along the elevation as well as to determine the best explanatory factors underlying these changes, we investigated free‐living soil nematodes on Mt. Halla, South Korea, using an amplicon sequencing approach targeting the 18S rRNA gene. Our results showed that there was significant variation in the community diversity and composition of soil nematodes in relation to elevation. The network interactions between soil nematodes were more intensive at the lower elevations. Climatic variables were responsible explaining the elevational variation in community composition and co‐occurrence pattern of the nematode community. Our study indicated that climatic factors served as the critical environmental filter that influenced not only the community structure but also the potential associations of soil nematodes in the mountain ecosystem of Mt. Halla. These findings enhance the understanding of the community structure and co‐occurrence network patterns and mechanisms of soil nematode along elevation, and the response of soil nematodes to climate change on the vertical scale of mountain ecosystems.

In this study, the effects of different sun withering degrees (75% (CK), 69% (S69), 66% (S66), 63% (S63), and 60% (S60) water content in the withered leaves) on black tea sensory quality were investigated by means of sensory evaluation plus metabolomics analysis. Sensory evaluation results showed higher sensory quality scores for the black tea in S69–S66, due to better freshness, sweeter taste, and a sweet and even floral and fruity aroma. Additionally, 65 non-volatile components were identified using Ultra Performance Liquid Chromatography-Quadrupole-Time of Flight-Mass Spectrometry (UPLC-Q-TOF/MS). Among them, the content increase of amino acids and theaflavins was found to promote the freshness and sweetness of black tea. The aroma of tea was analyzed using combined Solvent Assisted Flavor Evaporation-Gas Chromatography-Mass Spectrometry (SAFE-GC-MS) and Headspace-Solid Phase Micro Extract-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS), and 180 volatiles were identified, including 38 variable importance in projection (VIP) > 1 (p < 0.05) and 25 Odor Activity Value (OAV) > 1 volatiles. Statistical analysis revealed 11 volatiles as potential major aroma differential metabolites in black tea with a different sun withering degree, such as volatile terpenoids (linalool, geraniol, (E)-citral, and β-myrcene), amino-acid-derived volatiles (benzeneethanol, benzeneacetaldehyde, and methyl salicylate), carotenoid-derived volatiles (jasmone and β-damascenone), and fatty-acid-derived volatiles ((Z)-3-hexen-1-ol and (E)-2-hexenal). Among them, volatile terpenoids and amino acid derived volatiles mainly contributed to the floral and fruity aroma quality of sun-withered black tea.

The quality of traditional sunlight-dried orange black tea can be affected by weather variations, leading to its quality instability. This study investigated the feasibility of replacing sunlight drying with a new hot-air drying method in orange black tea production. The hot-air-dried orange black tea showed better sensory quality than the traditional outdoor-sunlight-dried tea, with a harmonious fruity aroma and sweet–mellow taste. The content of polyphenols and other quality components in the peel and tea leaves was significantly higher after hot-air drying than after sunlight drying. GC-MS analysis showed that the total number of volatile components of hot-air-dried tea (3103.46 μg/g) was higher than that of sunlight-dried tea (3019.19 μg/g). Compared with sunlight-dried orange black tea, the hot-air-dried orange black tea showed higher total antioxidant capacity, with an increase of 21.5% (FRAP), 7.5% (DPPH), and 17.4% (ABTS), as well as an increase of 38.1% and 36.3% in the inhibitory capacity on α-glucosidase and α-amylase activities. Further analysis of the effects of different drying temperatures (40, 45, 50, and 60 °C) on the quality of orange black tea showed that the tea quality gradually decreased with the increase in drying temperature, with the most obvious decrease in the quality of orange black tea at the drying temperature of 60 °C. Low-temperature (40 °C) dried tea had better aroma coordination, higher fruit flavor, greater sweet–mellow taste, and higher retention of functional active substances in orange peel and black tea. In summary, compared with traditional sunlight drying, the hot-air drying method could reduce the drying time from 90 h to 20 h and improve the sensory quality and functional activity of orange black tea, suggesting it can replace the traditional sunlight drying process. This work is significant for improving the quality of orange black tea in practical production.