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[Introduction] With the advancement of the "dual carbon" goals and the introduction of new energy allocation and storage policies in various regions, there is a need to further clarify the role of distributed energy storage in the new types of distribution networks and the configuration of associated energy storage system. [Method] This paper began by summarizing the configuration requirements of the distributed energy storage systems for the new distribution networks, and further considered the structure of distributed photovoltaic energy storage system according to different application needs. To maximize the economic aspect of configuring energy storage, in conjunction with the policy requirements for energy allocation and storage in various regions, the paper clarified the methods for configuring distributed energy storage systems and summarized the commonly used algorithms for determining the location and capacity. Based on this, research suggestions were proposed. [Result] Proper configuration of energy storage should be based on clear demands, selecting the appropriate topology and offering a configuration plan that is optimized by comprehensively considering indicators such as power supply stability, security, and economic efficiency of the distribution network. [Conclusion] Distributed energy storage technology is the key aspect of the new distribution networks and an essential means to ensure the safe and stable operation of distribution networks. To harness its full potential, further research into its optimal configuration and related control technologies is necessary.

It is an established and already accomplished fact that probability-based methodologies (or probability/statistical distributions) play the roles of imperative tools in illustrating and describing applied phenomena. Paying attention to these previous facts, this paper considers the evolution of a new probability distribution. Thus, the main achievement of this paper leads to a new probability distribution as a result of combining the exponentiated exponential model with a tangent-based stratagem. The new model is called the tangent exponentiated exponential (TEE) distribution. For the TEE distribution, certain distributional properties and estimators of the model parameters are derived mathematically. The appraisal of the estimators of the TEE distribution is accomplished through a simulation study. Moreover, the applicability and virtuoso of the TEE distribution are exemplified via two data sets, which are taken from the music engineering (named Data 1) and reliability sector (named Data 2). By considering the p-value and three other important statistical tests/methods as diagnostic tools, we find that the TEE distribution is the most useful and optimal model for Data 1 and Data 2 compared to certain candidate probability distributions.

Targeted protein degradation (TPD) represented by proteolysis targeting chimeras (PROTACs) marks a significant stride in drug discovery. A plethora of innovative technologies inspired by PROTAC have not only revolutionized the landscape of TPD but have the potential to unlock functionalities beyond degradation. Non-small-molecule-based approaches play an irreplaceable role in this field. A wide variety of agents spanning a broad chemical spectrum, including peptides, nucleic acids, antibodies, and even vaccines, which not only prove instrumental in overcoming the constraints of conventional small molecule entities but also provided rapidly renewing paradigms. Herein we summarize the burgeoning non-small molecule technological platforms inspired by PROTACs, including three major trajectories, to provide insights for the design strategies based on novel paradigms.

Summary: Although autosomal-dominant inheritance is believed an important cause of familial clustering Alzheimer’s disease (FAD), it covers only a small proportion of FAD incidence, and so we investigated epigenetic memory as an alternative mechanism to contribute for intergenerational AD pathogenesis. Our data in vivo showed that mys-2 of Caenorhabditis elegans that encodes a putative MYST acetyltransferase responsible for H4K16 acetylation modulated AD occurrence. The phenotypic improvements in the parent generation caused by mys-2 disfunction were passed to their progeny due to epigenetic memory, which resulted in similar H4K16ac levels among the candidate target genes of MYS-2 and similar gene expression patterns of the AD-related pathways. Furthermore, the ROS/CDK-5/ATM pathway functioned as an upstream activator of MYS-2. Our study indicated that MYS-2/MOF could be inherited intergenerationally via epigenetic mechanisms in C. elegans and mammalian cell of AD model, providing a new insight into our understanding of the etiology and inheritance of FAD.

Yttria-stabilized zirconia (YSZ), which exhibits a tetragonal phase, finds widespread application in the realm of high-temperature solid electrolytes. In the context of this research endeavor, a concerted effort was undertaken to procure a stable and controlled tetragonal phase structure within 5 mol% yttria-stabilized zirconia (5 YSZ) by modulating the precipitation rate of YSZ sols in three distinct precipitation environments, namely acidic (AC), near to neutral (NE), and alkaline (AL) conditions. Through the characterization of 5 YSZ compounds synthesized in these various environments, encompassing an assessment of their elemental composition, phase structure, local structure, and microscale morphology, it was discerned that under acidic conditions, the product exhibited non-uniform elemental distribution, pronounced agglomeration, and an abundance of hydroxyl groups, all of which proved detrimental to the stability of the tetragonal phase, resulting in the presence of 40.63% monoclinic phase. Conversely, under alkaline conditions, substantial agglomeration and hydroxyl group presence were also noted, with 34.7% monoclinic phase in the product. In stark contrast, under the condition which is near to neutral, the product demonstrated uniform elemental distribution, excellent dispersion characteristics, and a virtual absence of hydroxyl groups. The tetragonal phase structure remained stable and homogeneous, with almost negligible monoclinic phase content. Subsequent ceramic processing resulted in the highest attainable density (99.7%), coupled with the highest ionic conductivity at 850 °C (35.2 mS/cm). This study underscores that pH control during coprecipitation reactions stands as a robust and effective methodology for achieving a stable tetragonal phase structure.

Automatic detection of mechanical failure is an essential technology in the fourth industrial revolution, which involves artificial-intelligence-based factory automation. The primary challenge in encoder-based machine sound anomaly detection lies in ensuring high-quality reconstruction of feature maps, as this directly impacts the precise definition of reconstruction error thresholds for normal and abnormal sound feature maps. This study proposes an improved deep convolutional generative adversarial network combined with the GANomaly method to introduce a unique anomaly detection model. This model leverages a residual deep convolutional generative adversarial network with an integrated attention mechanism as the generator and a multi-scale, multi-layer convolutional neural network as the discriminator to address the issue of information loss in reconstruction feature maps with increasing network depth, enhancing model generalization capabilities. The proposed approach introduces custom hyperparameters and tailored loss functions, utilizing Wasserstein distance to measure sample differences and promote model convergence. Researching the DCASE Challenge 2023 Task 2 development dataset, improvements are observed in experimental metrics such as AUC and pAUC, demonstrating the superiority of the model. We also analyze aspects such as feature map quality, parameter settings, and experimental ablation, and compare with other state-of-the-art methods to showcase the contributions of our model.

Ratiometric fluorescent films with high amine sensitivity and stability were developed to monitor the freshness of beef and pork. Fluorescein isothiocyanate (FITC) and red carbon quantum dots (R-CQD) were used as the amine-responsive indicator and internal reference, respectively. The electrospun films prepared by immobilizing FITC and R-CQD complex (F-R) into polyvinylidene fluoride (PVDF) under 35 %, 55 % and 75 % of relative humidity (RH) were named F-R@PVDF-1, F-R@PVDF-2 and F-R@PVDF-3, respectively. In comparison, the F-R@PVDF-2 film exhibited the highest sensitivity to trimethylamine (TMA), demonstrating a limit of detection (LOD) value of 1.59 μM, and meanwhile high stability during storage with ΔE value of 1.99 after 14 days of storage at 4 °C. The F-R@PVDF-2 film also showed a significant fluorescent red-to-brown color change during meat freshness monitoring at 4 °C. Conclusively, this study reported a new ratiometric fluorescent film that can be used to track the freshness of meats in food packaging.

Although an alarming rate of global biodiversity loss is occurring, the effects of belowground microbial diversity on soil functioning still remain uncertain and debated across numbers of experiments data. In this context, we synthesize and evaluate the impacts of microbial diversity loss on soil ecosystem functioning from published literatures, and elaborate the probable mechanisms of the different response in terms of soil general and specific functions. The results showed that the loss of microbial diversity decreases both specific (e.g. pollutant degradation, methane metabolism, pathogen control) and general functions (e.g. C and N mineralization, soil respiration, biomass production), indicating that functional redundancy may be overestimated, even for general functions. The processes that drive the link between microbial diversity and ecosystem processes are influenced by environmental factors in the soil (e.g. nutrient condition, pollution stress, moisture content). However, high functional diversity and stability are crucial in explaining the maintenance of soil ecosystem function under the scenario of global biodiversity declining, which involves the process of genotypic/phenotypic functional traits and diversity effects. In summary, our review has implications for an improved understanding regarding the relationship between diversity and general/specific functions, with suggestions for the future research provided.

Summary: Background: The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods: In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Findings: In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64–73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953–0.998) to 0.992 (0.982–1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908–1.000]) surpassed that of two junior pathologists (0.862 [0.746–0.939], P = 0.023; 0.879 [0.767–0.950], P = 0.041) by 10–12% and showed no difference to that of two senior pathologists (both 0.983 [0.908–1.000], both P > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P = 0.041) to the level of senior pathologists (both P > 0.99), and substantially reduced the four pathologists’ slide reviewing time (−31%, P

Summary: Background: Urine cytology is an important non-invasive examination for urothelial carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence (AI) can enhance the sensitivity of urine cytology and help avoid unnecessary endoscopy. Methods: In this multicentre diagnostic study, consecutive patients who underwent liquid-based urine cytology examinations at four hospitals in China were included for model development and validation. Patients who declined surgery and lacked associated histopathology results, those diagnosed with rare subtype tumours of the urinary tract, or had low-quality images were excluded from the study. All liquid-based cytology slides were scanned into whole-slide images (WSIs) at 40 × magnification and the WSI-labels were derived from the corresponding histopathology results. The Precision Urine Cytology AI Solution (PUCAS) was composed of three distinct stages (patch extraction, features extraction, and classification diagnosis) and was trained to identify important WSI features associated with UC diagnosis. The diagnostic sensitivity was mainly used to validate the performance of PUCAS in retrospective and prospective validation cohorts. This study is registered with the ChiCTR, ChiCTR2300073192. Findings: Between January 1, 2018 and October 31, 2022, 2641 patients were retrospectively recruited in the training cohort, and 2335 in retrospective validation cohorts; 400 eligible patients were enrolled in the prospective validation cohort between July 7, 2023 and September 15, 2023. The sensitivity of PUCAS ranged from 0.922 (95% CI: 0.811–0.978) to 1.000 (0.782–1.000) in retrospective validation cohorts, and was 0.896 (0.837–0.939) in prospective validation cohort. The PUCAS model also exhibited a good performance in detecting malignancy within atypical urothelial cells cases, with a sensitivity of over 0.84. In the recurrence detection scenario, PUCAS could reduce 57.5% of endoscopy use with a negative predictive value of 96.4%. Interpretation: PUCAS may help to improve the sensitivity of urine cytology, reduce misdiagnoses of UC, avoid unnecessary endoscopy, and reduce the clinical burden in resource-limited areas. The further validation in other countries is needed. Funding: National Natural Science Foundation of China; Key Program of the National Natural Science Foundation of China; the National Science Foundation for Distinguished Young Scholars; the Science and Technology Planning Project of Guangdong Province; the National Key Research and Development Programme of China; Guangdong Provincial Clinical Research Centre for Urological Diseases.

To explore the regulatory mechanism of endogenous hormones in the synthesis of anthocyanins in Anoectochilus roxburghii (Wall.) Lindl (A. roxburghii) under different light intensities, this study used metabolomics and transcriptomics techniques to identify the key genes and transcription factors involved in anthocyanin biosynthesis. We also analyzed the changes in and correlations between plant endogenous hormones and anthocyanin metabolites under different light intensities. The results indicate that light intensity significantly affects the levels of anthocyanin glycosides and endogenous hormones in leaves. A total of 38 anthocyanin-related differential metabolites were identified. Under 75% light transmittance (T3 treatment), the leaves exhibited the highest anthocyanin content and differentially expressed genes such as chalcone synthase (CHS), flavonol synthase (FLS), and flavonoid 3′-monooxygenase (F3′H) exhibited the highest expression levels. Additionally, 13 transcription factors were found to have regulatory relationships with 7 enzyme genes, with 11 possessing cis-elements responsive to plant hormones. The expression of six genes and two transcription factors was validated using qRT-PCR, with the results agreeing with those obtained using RNA sequencing. This study revealed that by modulating endogenous hormones and transcription factors, light intensity plays a pivotal role in regulating anthocyanin glycoside synthesis in A. roxburghii leaves. These findings provide insights into the molecular mechanisms underlying light-induced changes in leaf coloration and contribute to our knowledge of plant secondary metabolite regulation caused by environmental factors.

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in adults. The standard treatment achieves a median overall survival for GBM patients of only 15 months. Hence, novel therapies based on an increased understanding of the mechanistic underpinnings of GBM are desperately needed. In this study, we show that elevated expression of 28S rRNA (cytosine‐C(5))‐methyltransferase NSUN5, which methylates cytosine 3782 of 28S rRNA in GBM cells, is strongly associated with the poor survival of GBM patients. Moreover, we demonstrate that overexpression of NSUN5 increases protein synthesis in GBM cells. NSUN5 knockdown decreased protein synthesis, cell proliferation, sphere formation, migration, and resistance to temozolomide in GBM cell lines. NSUN5 knockdown also decreased the number and size of GBM neurospheres in vitro. As a corollary, mice harboring U251 tumors wherein NSUN5 was knocked down survived longer than mice harboring control tumors. Taken together, our results suggest that NSUN5 plays a protumorigenic role in GBM by enabling the enhanced protein synthesis requisite for tumor progression. Accordingly, NSUN5 may be a hitherto unappreciated target for the treatment of GBM.

Abstract Chloride channels (CLCs) transport anion across membrane to regulate ion homeostasis and acidification of intracellular organelles, and are divided into anion channels and anion/proton antiporters. Arabidopsis thaliana CLCa (AtCLCa) transporter localizes to the tonoplast which imports NO3 − and to a less extent Cl− from cytoplasm. The activity of AtCLCa and many other CLCs is regulated by nucleotides and phospholipids, however, the molecular mechanism remains unclear. Here we determine the cryo-EM structures of AtCLCa bound with NO3 − and Cl−, respectively. Both structures are captured in ATP and PI(4,5)P2 bound conformation. Structural and electrophysiological analyses reveal a previously unidentified N-terminal β-hairpin that is stabilized by ATP binding to block the anion transport pathway, thereby inhibiting the AtCLCa activity. While AMP loses the inhibition capacity due to lack of the β/γ- phosphates required for β-hairpin stabilization. This well explains how AtCLCa senses the ATP/AMP status to regulate the physiological nitrogen-carbon balance. Our data further show that PI(4,5)P2 or PI(3,5)P2 binds to the AtCLCa dimer interface and occupies the proton-exit pathway, which may help to understand the inhibition of AtCLCa by phospholipids to facilitate guard cell vacuole acidification and stomatal closure. In a word, our work suggests the regulatory mechanism of AtCLCa by nucleotides and phospholipids under certain physiological scenarios and provides new insights for future study of CLCs.

In this work, a gelatin/chia mucilage (GN/CM) composite coating material doped with Lactococcus lactis (LS) was developed for strawberry preservation applications. The results of the scanning electron microscope and Fourier transform infrared spectroscopy stated that the enhanced molecular interaction between the CM and GN matrix strengthened the density and compactness of the GN film. Antifungal results indicated that the addition of LS significantly (p < 0.05) improved the ability of the GN coating to inhibit the growth of Botrytis cinerea (inhibition percentage = 62.0 ± 4.6%). Adding CM significantly (p < 0.05) decreased the water vapour permeability and oxygen permeability of the GN coating by 32.7 ± 4.0% and 15.76 ± 1.89%, respectively. In addition, the incorporated CM also significantly (p < 0.05) improved the LS viability and elongation at break of the film by 13.11 ± 2.05% and 42.58 ± 1.21%, respectively. The GN/CM/LS composite coating material also exhibited an excellent washability. The results of this study indicated that the developed GN/CM/LS coating could be used as a novel active material for strawberry preservation.

Abstract Developing low-cadmium (Cd) rice cultivars has emerged as a promising avenue for food safety in Cd-contaminated farmlands. The root-associated microbiomes of rice have been shown to enhance rice growth and alleviate Cd stress. However, the microbial taxon-specific Cd resistance mechanisms underlying different Cd accumulation characteristics between different rice cultivars remain largely unknown. This study compared low-Cd cultivar XS14 and hybrid rice cultivar YY17 for Cd accumulation with five soil amendments. The results showed that XS14 was characterized by more variable community structures and stable co-occurrence networks in the soil-root continuum compared to YY17. The stronger stochastic processes in assembly of the XS14 (~25%) rhizosphere community than that of YY17 (~12%) suggested XS14 may have higher resistance to changes in soil properties. Microbial co-occurrence networks and machine learning models jointly identified keystone indicator microbiota, such as Desulfobacteria in XS14 and Nitrospiraceae in YY17. Meanwhile, genes involved in sulfur cycling and nitrogen cycling were observed among the root-associated microbiome of these two cultivars, respectively. Microbiomes in the rhizosphere and root of XS14 showed a higher diversity in functioning, with the significant enrichment of functional genes related to amino acid and carbohydrate transport and metabolism, and sulfur cycling. Our findings revealed differences and similarities in the microbial communities associated with two rice cultivars, as well as bacterial biomarkers predictive of Cd-accumulation capacity. Thus, we provide new insights into taxon-specific recruitment strategies of two rice cultivars under Cd stress and highlight the utility of biomarkers in offering clues for enhancing crop resilience to Cd stresses in the future.

Accurate assessment of dough kneading is pivotal in pasta processing, where both under-kneading and over-kneading can detrimentally impact dough quality. This study proposes an innovative approach utilizing a cost-effective current sensor to ascertain the optimal kneading time for dough. Throughout the kneading process, the dough’s tensile resistance gradually increases, reflecting the evolution of properties such as the gluten network. This leads to a discernible ascending phase in dough quality, evident through an increase in the load current of the mixing machine, succeeded by a subsequent decline beyond a certain threshold. The identification of this peak point enables the achievement of optimal dough consistency, thereby enhancing the overall quality of both the dough and subsequent pasta products. After the final product quality assessment, this novel method promises to be a valuable tool in optimizing pasta processing and ensuring consistent product quality.

As a traditional Chinese dish cutting technology process, Gaidao artificially create cuts embedded in the food surface by cutting through it with knife, a process that currently plays an important role in the beef marinating process. And different Gaidao processes directly affect the beef marination flavour and marination efficiency. This study is the first to propose the use of Hyperspectral imaging technology (HSI) combined with finite element analysis to investigate the effect of Gaidao process on the quality of marinated beef. The study was carried out by collecting spectral information of beef marinated with different sucrose concentrations and combining various pre-processing methods and algorithms such as PLS, BiPLS, iPLS, and SiPLS to establish a quantitative model of sucrose concentration in beef, and finally optimizing parameters such as the length, position and number of Gaidao by Finite Element Analysis (FEA), which showed that when marinated with 1.0 mol/m³ sucrose solution, the concentration of sucrose in all tissues in the Gaidao steak reached 0.8 mol/m³ and above, which greatly improved the diffusion effect of the marinade. This work provides new ideas and methods to optimize the beef marinade Gaidao process, which has important practical value and research significance.

Power supply for IGBT drive circuit of HVDC circuit breaker is a great challenge in practical engineering. At present, most of the HVDC circuit breakers rely on external power sources. This paper proposes a self-powered hybrid HVDC circuit breaker. The HVDC circuit breaker consists of an ultra-fast mechanical disconnector (UFD), a load commutation switch (LCS) and a main circuit breaker (MB). The LCS and the MB are formed by series connection of enhanced half-bridge sub-modules (EHBSMs). By this design, the energy stored in the EHBSM capacitor can be used for IGBT triggering. Thus, the self-powered function of the HVDC circuit breaker is realized. Three operation modes of the HVDC circuit breaker, including the star-up mode, the steady-state operation mode and the DC fault handling mode are analysed in detail. Finally, a four-terminal HVDC model is constructed in PSCAD simulation software. The simulation results verify the feasibility and effectiveness of the self-powered HVDC circuit breaker.

Abstract Safety concerns on the deep neural networks (DNNs) have been raised when they are applied to critical sectors. In this paper, we define safety risks by requesting the alignment of network’s decision with human perception. To enable a general methodology for quantifying safety risks, we define a generic safety property and instantiate it to express various safety risks. For the quantification of risks, we take the maximum radius of safe norm balls, in which no safety risk exists. The computation of the maximum safe radius is reduced to the computation of their respective Lipschitz metrics—the quantities to be computed. In addition to the known adversarial example, reachability example, and invariant example, in this paper, we identify a new class of risk—uncertainty example—on which humans can tell easily, but the network is unsure. We develop an algorithm, inspired by derivative-free optimization techniques and accelerated by tensor-based parallelization on GPUs, to support an efficient computation of the metrics. We perform evaluations on several benchmark neural networks, including ACSC-Xu, MNIST, CIFAR-10, and ImageNet networks. The experiments show that our method can achieve competitive performance on safety quantification in terms of the tightness and the efficiency of computation. Importantly, as a generic approach, our method can work with a broad class of safety risks and without restrictions on the structure of neural networks.

In this study, a composite film was created with the dual goal of prolonging pork shelf life and showing freshness. Hydrogel materials as solid base films were selected from gelatin (G), sodium alginate (SA) and carboxymethyl cellulose (CMC) based on their antioxidant activity, water vapor permeability, mechanical properties, as well as their stability, antimicrobial activity, and freshness, which indicates effectiveness when combined with anthocyanins. Furthermore, the effects of several concentrations of red cabbage anthocyanin (R) (3%, 6%, 12%, and 24%) on freshness indicators and bacteriostasis were investigated. The antimicrobial activity of the composite films was evaluated against Escherichia coli, Bacillus subtilis, and Staphylococcus aureus. Likewise, the freshness indicates effectiveness was evaluated for NH3. Considering the mechanical properties, antibacterial ability, freshness indicator effect, and stability of the composite film, CS film combined with 12% R was selected to prepare a dual-functional intelligent film for pork freshness indicator and preservation. By thoroughly investigating the effect of composite film on pork conservation and combining with it KNN, the discriminative model of pork freshness grade was established and the recognition rate of the prediction set was up to 93.3%. These results indicated that CSR film can be used for the creation of active food packaging materials.

This study comparatively analyzed the geological, geochemical, reservoir, and gas-bearing characteristics of the lower Cambrian marine shale in the Middle and Lower Yangtze regions. The main factors controlling the gas-bearing properties of the shales were identified, and the favorable and unfavorable conditions for shale gas accumulation are discussed. The results show that the organic carbon contents and thermal evolution degree of the organic matter in the lower Cambrian marine shale in the Lower Yangtze area were higher than those generally found in the Middle Yangtze area. The brittle mineral composition of the Middle Yangtze area was typically low silicon and high calcium, whereas the Lower Yangtze area was characterized by high silicon and low calcium. The development of micropores in the Lower Yangtze area was poorer than in the Middle Yangtze area, with the organic pores being particularly underdeveloped. The adsorption capacity of shale in the Lower Yangtze area was obviously higher than in the Middle Yangtze area. It was considered that the organic carbon content, thermal evolution degree, and molecular structure of kerogen were the main factors that controlled the adsorption properties of the shale. In addition, the Lower Yangtze area suffered a stronger tectonic transformation and frequent magmatic activity, and the preservation conditions were inferior to those in the Middle Yangtze area.

Abstract Objective Esophageal cancer, one of the most common cancers in the upper digestive tract and is one of the leading cancer-related mortality worldwide. Accumulating studies found that Ginsenoside compound K (CK) has significantly anti-tumor effects, especially in the suppression of proliferation, migration, as well as invasion in various human cancers. While the effects of Ginsenoside CK in esophageal cancer have not been well studied. In our present study, we aim to explore the functions and mechanisms of Ginsenoside CK in the progression of esophageal cancer cells (Eca109). Methods Cell Counting Kit-8 (CCK-8), wound healing, transwell and flow cytometry assays were applied to analyze the effects of Ginsenoside CK in the progression of Eca109 cell, western blot assay was used to investigate the potential downstream signaling pathway after Ginsenoside CK treatment. Results Our study found that Ginsenoside CK can suppress cell proliferation, migration and invasion of Eca109 cell. Furthermore, the flow cytometry showed that Ginsenoside CK increased of apoptosis rates in Eca109 cell. The western blot results indicated that Ginsenoside CK decreased the expression of VEGF-A, P-Pi3k and P-Akt proteins. Moreover, the knockdown of VEGF-A gene could suppress cell proliferation, migration, invasion and induce apoptosis in Eca109 cell, and the expression of P-Pi3k and P-Akt proteins were significantly downregulated. Conclusions Our study suggests that Ginsenoside CK inhibits the proliferation, migration, invasion, and induced apoptosis of Eca109 cell by blocking VEGF-A/Pi3k/Akt signaling pathway.

Abstract This study aimed to use bioinformatics methods to characterize epigenetic changes in terms of micro-RNA(miRNA) expression and DNA methylation during adipogenesis. The mRNA and miRNA expression microarray and DNA methylation dataset were obtained from the GEO database. Differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs) and differentially methylated probes (DMPs) were filtered using the limma package. The R language cluster profile package was used for functional and enrichment analysis. A protein–protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. The Connection map (CMap) website tool was used to screen potential therapeutic drugs for adipogenesis. When comparing the early and late stages of adipogenesis, 111 low miRNA targeted upregulated genes and 64 high miRNA targeted downregulated genes were obtained, as well as 663 low-methylated high-expressed genes and 237 high-methylated low-expressed genes. In addition, 41 genes (24 upregulated and 17 downregulated) were simultaneously regulated by abnormal miRNA changes and DNA methylation. Ten chemicals were identified as putative therapeutics for adipogenesis. In addition, among the dual-regulated genes identified, CANX, HNRNPA1, MCL1, and PPIF may play key roles in the epigenetic regulation of adipogenesis and may serve as aberrant methylation or miRNA targeting biomarkers.

This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.

Advancements in drilling technology are pivotal to optimizing the production and sustainability of oil and gas wells. One of the emerging innovations is the application of a specialized fluid known as “Fuzzy-ball” fluid. This paper comprehensively reviews the historical evolution and advancements in the utilization of fuzzy-ball fluid in drilling and well-repair processes. Fuzzy-ball fluid has been discovered to bolster a formation’s pressure-bearing capabilities and systematically augment resistance against oil, gas, and water flow. These attributes have been instrumental in the phased integration of fuzzy-ball fluid into procedures aiming to enhance production in oil and gas wells. This paper bridges the knowledge gap in the industry regarding the application of fuzzy-ball fluid, thereby circumventing the challenges of inadequate understanding and suboptimal designs. However, the study acknowledges the potential limitation of information loss despite the extensive data collection from diverse sources, such as articles, patents, and reports. As a future direction, this paper emphasizes the need for a more encompassing and critical evaluation of fuzzy-ball fluid’s performance and applications. This will enable a more informed decision-making process, fostering the expanded use and understanding of this fluid’s mechanism within the industry.

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.

Abstract Background Text Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc. In recent years, a large number of deep learning neural networks have been applied to TM, and have refreshed benchmarks of TM repeatedly. Among the deep learning neural networks, convolutional neural network (CNN) is one of the most popular networks, which suffers from difficulties in dealing with small samples and keeping relative structures of features. In this paper, we propose a novel deep learning architecture based on capsule network for TM, called CapsTM, where capsule network is a new type of neural network architecture proposed to address some of the short comings of CNN and shows great potential in many tasks. Methods CapsTM is a five-layer neural network, including an input layer, a representation layer, an aggregation layer, a capsule layer and a prediction layer. In CapsTM, two pieces of text are first individually converted into sequences of embeddings and are further transformed by a highway network in the input layer. Then, Bidirectional Long Short-Term Memory (BiLSTM) is used to represent each piece of text and attention-based interaction matrix is used to represent interactive information of the two pieces of text in the representation layer. Subsequently, the two kinds of representations are fused together by BiLSTM in the aggregation layer, and are further represented with capsules (vectors) in the capsule layer. Finally, the prediction layer is a connected network used for classification. CapsTM is an extension of ESIM by adding a capsule layer before the prediction layer. Results We construct a corpus of Chinese medical question matching, which contains 36,360 question pairs. This corpus is randomly split into three parts: a training set of 32,360 question pairs, a development set of 2000 question pairs and a test set of 2000 question pairs. On this corpus, we conduct a series of experiments to evaluate the proposed CapsTM and compare it with other state-of-the-art methods. CapsTM achieves the highest F-score of 0.8666. Conclusion The experimental results demonstrate that CapsTM is effective for Chinese medical question matching and outperforms other state-of-the-art methods for comparison.

The aversive behavior of Caenorhabditis elegans is an important strategy that increases their survival under pathogen infection, and the molecular mechanisms underlying this behavior have been described. However, whether this defensive response occurs in plant-parasitic nematodes (PPNs), which have quite different life cycles and genomic sequences from the model nematode, against biocontrol microbes and affects interspecific interactions in ecological environments remains unclear. Here, we showed that Meloidogyne incognita, one of the most common PPNs, engaged in lawn-leaving behavior in response to biocontrol bacteria such as Bacillus nematocida B16 and B. thuringiensis Bt79. Genomic analysis revealed that the key genes responsible for the aversive behavior of C. elegans, such as serotonin-and TGF-β-related genes in canonical signaling pathways, were homologous to those of M. incognita, and the similarity between these sequences ranged from 30% to 67%. Knockdown of the homologous genes impaired avoidance of M. incognita to varying degrees. Calcium ion imaging showed that the repulsive response requires the involvement of the multiple amphid neurons of M. incognita. In situ hybridization specifically localized Mi-tph-1 of the serotonin pathway to ADF/NSM neurons and Mi-dbl-1 of the TGF-β pathway to AVA neurons. Our data suggested that the repulsive response induced by different biocontrol bacteria strongly suppresses the invasion of tomato host plants by M. incognita. Overall, our study is the first to clarify the pathogen-induced repulsive response of M. incognita and elucidate its underlying molecular mechanisms. Our findings provide new insights into interspecific interactions among biocontrol bacteria, PPNs, and host plants.

Under partial shading conditions (PSCs), photovoltaic (PV) generation systems exhibit multiple local and a single global maximum power point. Consequently, global maximum power point tracking (GMPPT) is required to improve the performance of PV systems in such scenarios. This paper comparatively studies and evaluates the tracking performance of modern heuristic-optimization-based GMPPT techniques. Monte Carlo method is used to statistically analyze different methods. Simulation and experimental results indicate that many of the algorithms have difficulties in balancing the explorative and exploitative searching behaviors. Therefore, we propose a variable vortex search (VVS), which is capable of improving the performance of GMPPT by using a variable step size and deterministic starting points. This paper will aid researchers and practical engineers to gain a thorough understanding on how to use modern heuristic algorithms for maximum power out of PV systems. Furthermore, it offers a comprehensive guidance on how to perform efficiently GMPPT in the PV systems under PSCs.

Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes’ (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC).Methods: We employed bioinformatics and statistical knowledge to examine the transcriptome data of HCC patients in the TCGA and GEO databases, with the goal of constructing a multigene predictive model. Then, we separated the patients into high- and low-risk groups based on the score. The model’s dependability was determined using principal components analysis (PCA), survival analysis, independent prognostic analysis, and receiver operating characteristic (ROC) analysis. Following that, we examined the clinical correlations, pharmacological treatment sensitivity, immune checkpoint expression, and immunological correlations between patients in high and low risk groups. Finally, we evaluated the variations in gene expression between high- and low-risk groups and further analyzed the network core genes using protein-protein interaction network analysis.Results: Prognostic models were built using eight genes (OPTN, ATG12, CSNK2A2, MFN1, PGAM5, SQSTM1, TOMM22, TOMM5). During validation, the prognostic model demonstrated high reliability, indicating that it could accurately predict the prognosis of HCC patients. Additionally, we discovered that typical HCC treatment medicines had varying impacts on patients classified as high or low risk, and that individuals classified as high risk are more likely to fail immunotherapy. Additionally, the high-risk group expressed more immunological checkpoints. The immunological status of patients in different risk categories varies as well, and patients with a high-risk score have a diminished ability to fight cancer. Finally, PPI analysis identified ten related genes with potential for research.Conclusion: Our prognostic model had good and reliable predictive ability, as well as clinical diagnosis and treatment guiding significance. Eight prognostic MRGs and ten network core genes merited further investigation.

Gene Set Analysis (GSA) is one of the most commonly used strategies to analyze omics data. Hundreds of GSA-related papers have been published, giving birth to a GSA field in Bioinformatics studies. However, as the field grows, it is becoming more difficult to obtain a clear view of all available methods, resources, and their quality. In this paper, we introduce a web platform called “GSA Central” which, as its name indicates, acts as a focal point to centralize GSA information and tools useful to beginners, average users, and experts in the GSA field. “GSA Central” contains five different resources: A Galaxy instance containing GSA tools (“Galaxy-GSA”), a portal to educational material (“GSA Classroom”), a comprehensive database of articles (“GSARefDB”), a set of benchmarking tools (“GSA BenchmarKING”), and a blog (“GSA Blog”). We expect that “GSA Central” will become a useful resource for users looking for introductory learning, state-of-the-art updates, method/tool selection guidelines and insights, tool usage, tool integration under a Galaxy environment, tool design, and tool validation/benchmarking. Moreover, we expect this kind of platform to become an example of a “thematic platform” containing all the resources that people in the field might need, an approach that could be extended to other bioinformatics topics or scientific fields.

The suitability of five apple varieties (Ralls, Qinguan, Fuji, Delicious, and Cattle) for fresh-cut processing was compared based on the evaluation of weight loss, firmness, color, titratable acid (TA), polyphenoloxidase (PPO) activity and peroxidase (POD) activity, and the impact of pulsed electronic field (PEF) on fresh-cut apples’ quality was explored. The results showed that the changes to Delicious apples in terms of the color parameter, firmness, and weight loss were comparable to or lower than the other samples, while the TA content was higher than the other samples during storage. Therefore, Delicious was selected for the study of the effects of PEF on fresh-cut apples. By measuring the physicochemical properties and microbiological characteristics within 10 days of storage, it was found that the PPO and POD activity of apples treated with PEF at 3 kV/cm on the 10th day decreased the most, with 44.61% and 36.48% decreases, respectively. In addition, apples treated with 5 kV/cm showed the greatest decrease in malondialdehyde (MDA) content and the number of microorganisms, 63.98%, and 9.17%, respectively. In general, the PEF-treated apples retained a high level of quality. These results suggested that PEF treatment is a promising technology for extending the storage period of fresh-cut apples.

Abstract Background Small intestine duplication cysts (SIDCs) are rare congenital anatomical abnormalities of the digestive tract and a rare cause of hematochezia. Case presentation We describe an adult female presented with recurrent hematochezia. The routine gastric endoscope and colonic endoscope showed no positive findings. Abdominal CT scan indicated intussusception due to the "doughnut" sign, but the patient had no typical symptoms. Two subsequent capsule endoscopes revealed a protruding lesion with bleeding in the distal ileum. Surgical resection was performed and revealed a case of SIDC measuring 6 * 2 cm located inside the ileum cavity. The patient remained symptom-free throughout a 7-year follow-up period. Conclusion SIDCs located inside the enteric cavity can easily be misdiagnosed as intussusception by routine radiologic examinations.

The generation mechanism of abiogenic alkane gas and whether the gas has industrial values are the focus of international attention. CH4 generated by Fischer–Tropsch synthesis is an important constitutent of abiogenic alkane gas. The study on the components, isotopic compositions, and crust-mantle mixing model indicates that, the alkane gas from the Qingshen gas field in the Songliao Basin is contributed by abiogenic alkane gas from Fischer–Tropsch synthesis, besides the mantle-derived abiogenic alkane gas. The authors have selected the endmembers of typical biogenic and abiogenic gases and conducted mixed source calculation. The abiogenic alkane gas accounts for over 60 × 109 m3 in the proven reserves of the gas field, in which the amount of CH4 generated by Fischer–Tropsch synthesis exceeds 9.6 × 109 m3. The calculation results indicate that, abiogenic alkane gas under organic–inorganic interactions can form commercial accumulations. Since typical biogenic gas is predominant in conventional gas pools, and high- to over-mature coal-derived gas displays a certain similarity with abiogenic alkane gas, the typical characteristics of abiogenic gas is concealed. Therefore, abiogenic alkane gas generated by organic–inorganic interactions may exist widely in petroliferous basins, and its contribution to gas pools may be underestimated previously.

There is increasingly valued attention on whether the matter and energy carried in the deep fluids can significantly change the hydrocarbon (HC) generation of low-mature source rocks. Previous studies suggest that the upward movement of deep fluids to sedimentary basins will change the HC generation evolution mode of low-mature source rocks, and the matter and energy carried by the fluid will transform the evolution process as transient events. However, there is a lack of quantitative evaluation of the specific changes of gaseous HC generation in the process of modification. In this study, the effect of deep fluids on HC generation and evolution of low maturity source rocks were quantitatively studied through simulation experiments of the gold tube closed system. We quantitatively selected hydrogen and catalysts (ZnCl2 and MoS2) to conduct catalytic hydrogenation of kerogen and explore the quantitative effects of deep fluids on HC generation in low-mature source rocks. Through the experimental results, it is found that catalytic hydrogenation has significant changes in a HC generation transformation of organic matter (OM). With the increase of catalytic hydrogenation reaction intensity, the maximum gaseous HC generation yield is 3.16–3.24 times that of the control groups without hydrogenation. In the relatively low-temperature stage (

This article conforms to a recent trend of developing an energy-efficient Spiking Neural Network (SNN), which takes advantage of the sophisticated training regime of Convolutional Neural Network (CNN) and converts a well-trained CNN to an SNN. We observe that the existing CNN-to-SNN conversion algorithms may keep a certain amount of residual current in the spiking neurons in SNN, and the residual current may cause significant accuracy loss when inference time is short. To deal with this, we propose a unified framework to equalize the output of the convolutional or dense layer in CNN and the accumulated current in SNN, and maximally align the spiking rate of a neuron with its corresponding charge. This framework enables us to design a novel explicit current control (ECC) method for the CNN-to-SNN conversion which considers multiple objectives at the same time during the conversion, including accuracy, latency, and energy efficiency. We conduct an extensive set of experiments on different neural network architectures, e.g., VGG, ResNet, and DenseNet, to evaluate the resulting SNNs. The benchmark datasets include not only the image datasets such as CIFAR-10/100 and ImageNet but also the Dynamic Vision Sensor (DVS) image datasets such as DVS-CIFAR-10. The experimental results show the superior performance of our ECC method over the state-of-the-art.

Ginsenosides, as the most important constituents of ginseng, have been extensively investigated in cancer chemoprevention and therapeutics. Among the ginsenosides, Compound K (CK), a rare protopanaxadiol type of ginsenoside, has been most broadly used for cancer treatment due to its high anticancer bioactivity. However, the functional mechanism of CK in cancer is not well known. This review describes the structure, transformation and pharmacological activity of CK and discusses the functional mechanisms of CK and its metabolites, which regulate signaling pathways related to tumor growth and metastasis. CK inhibits tumor growth by inducing tumor apoptosis and tumor cell differentiation, regulates the tumor microenvironment by suppressing tumor angiogenesis-related proteins, and downregulates the roles of immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs). There is currently much research on the potential development of CK as a new strategy when administered alone or in combination with other compounds.

The transition metal-based layered double hydroxides (LDHs) for high-performance supercapacitor applications were synthesized by the double hydrolysis dropping method. We found that the dropping sequence of the cation and anion solutions has a strong influence on the microstructural and electrochemical properties of LDHs. The NiAl LDHs obtained by dropping the Ni2+ solution into the AlO2- solution have obvious layered structures with a particle size of the order of micrometers. They are different from those LDHs prepared by the conventional double hydrolysis method and hydrothermal method. The specific capacity of the NiAl LDHs is about 615 C g−1 at 0.5 A g−1, which is almost twice that of the sample synthesized by the traditional double hydrolysis method (339 C g−1). It is indicated that the performance of the NiAl LDHs is improved by the dropping method. Moreover, an excellent cyclic stability of 83.3% capacitance retention after 1000 cycles at 3 A g−1 was achieved. In addition, the trimetallic NiCoAl LDHs have been synthesized successfully by the dropping method. The results showed that the addition of Co effectively enhanced the electrochemical properties of LDHs. The optimal NiCoAl LDHs display an excellent specific capacity of 990 C g−1 at 0.5 A g−1. This work offers an efficient and facile route, without hydrothermal treatment or adscititious alkali sources, to fabricating LDHs for boosting energy storage capabilities.

Gas of hydrogen is combustible and has been regarded as one of the important form of clean energy. With the increasing environmental concerns caused by the continues and high dependence on fossil fuels, more attention is being paid to the research on hydrogen exploration. However, only limited understanding about the geological, genetic as well as distribution characteristics of hydrogen gas has been addressed. In this paper, the formation and enrichment mechanisms of hydrogen gas under different geological conditions were compared, results showed that reservoirs of high-content hydrogen gas may develop in rift system and the front edge of plate subduction zone. By further summarizing the distribution of hydrogen gas in different tectonic members, it is concluded that the plate collision zone and subduction zone and their peripheries controlling the distribution of the development of high-content hydrogen gas and thus the petroliferous basins developed in these tectonic positions have good natural gas preservation conditions, hence are promising for the preservation of high-content hydrogen gas.

Abstract Objective To retrospectively analyze the clinical efficacy of PFNA combined with a cerclage wire in the treatment of 52 patients with unstable subtrochanteric fracture of the femur and to analyze the biomechanical effect of ligature on a fracture model. Methods In this study, 52 patients with unstable subtrochanteric fractures were treated in our orthopedic trauma center from June 2013 to July 2018. The Seinsheimer type IV fracture model was established using the patient’s CT data, and the joint surface of the distal femoral condyle and the external condyle were restrained. The femoral head was used as the loading point, and a force of 500 N was applied vertically along the long axis of the femoral shaft. Results All 52 patients were followed up for 12 to 37 months, with an average of 18.07 ± 4.38 months. According to the Sanders hip function score, 28 cases were excellent (55–60 points), 22 cases were good (45–54 points), and 2 cases were poor (35–44 points), with an excellent and good rate of 96.15%. Postoperative deep vein thrombosis occurred in 3 cases, and fracture nonunion occurred in 1 case. No infection, loose fracture of internal fixation or hip varus deformity occurred. The finite element analysis indicated that the displacement of the whole model decreased slightly and the relative sliding of the fracture block decreased, but the maximum stress of the femur increased after the addition of the cerclage wire. Conclusion The treatment of unstable subtrochanteric fracture of the femur with PFNA combined with cerclage wire has the advantages of simple operation, satisfactory reduction of fracture, stable fixation, and good recovery of limb function. The finite element analysis suggested that the biomechanical strength fixation was enhanced after the addition of cerclage wire. However, the local stress concentration of the tie may increase the risk of failure.

Hydrogen is an attractive, clean, sustainable energy source primarily produced via industry. At present, most reviews on hydrogen mainly focus on the preparation and storage of hydrogen, while the development and utilization of natural hydrogen will greatly reduce its cost. Natural hydrogen has been discovered in many geological environments. Therefore, based on extensive literature research, in this study, the distribution and sources of natural hydrogen were systematically sorted, and the identification method and occurrence state of natural hydrogen were examined and summarized. The results of this research show that hydrogen has been discovered in oceanic spreading centers, transform faults, passive margins, convergent margins, and intraplate settings. The primary sources of the hydrogen include alterations in Fe(II)-containing rocks, the radiolysis of water, degassed magma, and the reaction of water- and silica-containing rocks during the mechanical fracturing. Hydrogen can appear in free gas, it can be adsorbed and trapped in inclusions. Currently, natural hydrogen exploration is in its infancy. This systematic review helps to understand the origin, distribution, and occurrence pattern of natural hydrogen. In addition, it facilitates the exploration and development of natural hydrogen deposits, thus enabling the production of low-cost hydrogen.

A ratiometric fluorescent sensor with hydrogen sulfide (H2S) and methanthiol (CH3SH) sensitivity was developed to real-time monitor beef freshness. A silicon quantum dots (SiQD) and silver nanoclusters (AgNC) complex, namely SiQD-AgNC, was used as the dual emission fluorescence materials. Due to the fluorescence resonance energy transfer (FRET) effect between SiQD and AgNC, when the fluorescence of AgNC (610 nm) was quenched by H2S or CH3SH, the fluorescence of SiQD (468 nm) recovered, resulting in an increase of the fluorescent intensity ratio (I468/I610). I468/I610 showed a linear relationship with the H2S concentration within the concentration range of 1.125–17 μM, with a limit of detection (LOD) value of 53.6 nM. Meanwhile, I468/I610 presented two linear relationships with the CH3SH concentration within the concentration range of 1.125–17 μM and 23.375–38.25 μM, respectively, with a LOD value of 56.5 nM. The SiQD-AgNC complex was coated on a polyvinylidene fluoride (PVDF) film to form a portable SiQD-AgNC/PVDF film sensor. This film showed purplish red-to-cyan color changes in response to H2S and CH3SH, with LOD values of 224 nM and 233 nM to H2S and CH3SH, respectively. When the film was used to monitor beef freshness at 4 °C, its fluorescent color gradually changed from purplish red to cyan. Hence, this study presented a new ratiometric fluorescent sensor for intelligent food packaging.

The leaf of Perilla frutescens (L.) Britt (PF) has been reported to negatively affect adipocyte formation, inhibit body-fat formation, and lower body weight. However, its effect on adipocyte browning remains unknown. Thus, the mechanism of PF in promoting adipocyte browning was investigated. The ingredients of PF were acquired from the online database and filtered with oral bioavailability and drug-likeness criteria. The browning-related target genes were obtained from the Gene Card database. A Venn diagram was employed to obtain the overlapped genes that may play a part in PF promoting adipocyte browning, and an enrichment was analysis conducted based on these overlapped genes. A total of 17 active ingredients of PF were filtered, which may regulate intracellular receptor-signaling pathways, the activation of protein kinase activity, and other pathways through 56 targets. In vitro validation showed that PF promotes mitochondrial biogenesis and upregulates brite adipocyte-related gene expression. The browning effect of PF can be mediated by the p38 MAPK pathway as well as PI3K-AKT pathway. The study revealed that PF could promote adipocyte browning through multitargets and multipathways. An in vitro study validated that the browning effect of PF can be mediated by both the P38 MAPK pathway and the PI3K-AKT pathway.

High-stability bi-layer films were prepared by incorporating anthocyanin-loaded liposomes into carrageenan and agar (A-CBAL) for non-destructive shrimp freshness monitoring. The encapsulation efficiency of the anthocyanin-loaded liposomes increased from 36.06% to 46.99% with an increasing ratio of lecithin. The water vapor transmission (WVP) of the A-CBAL films, with a value of 2.32 × 10−7 g · m−1 · h−1 · pa−1, was lower than that of the film with free anthocyanins (A-CBA). The exudation rate of the A-CBA film reached 100% at pH 7 and pH 9 after 50 min, while the A-CBAL films slowed down to a value lower than 45%. The encapsulation of anthocyanins slightly decreased the ammonia sensitivity. Finally, the bi-layer films with liposomes successfully monitored shrimp freshness with visible color changes to the naked eye. These results indicated that films with anthocyanin-loaded liposomes have potential applications in high-humidity environments.

The study was proposed to investigate the effects of pulsed pressure curing on the beef absorption of the curing solution, cooking loss, moisture content, centrifugal loss, salt content, sensory attributes, texture, microstructures and volatile compounds. Curing methods include the following four treatments: (1) control group 1—static curing (SC); (2) control group 2—vacuum curing (VC); (3) control group 3—pressurized curing (PC); and (4) treatment group—pulsed pressure curing (PPC). The acquired results revealed that pulsed pressure curing significantly boosts the curing efficiency and moisture content, decreases cooking loss in beef, brightens meat color, and enhances texture compared to static curing, vacuum curing, and pressurized curing. Additionally, centrifugal losses were not impaired, and sensory findings revealed that PPC significantly improved the saltiness of beef. TPA results showed that the springiness and cohesiveness of PPC were greatly increased, and hardness and chewiness were significantly reduced. Moreover, PPC significantly reduced the content of 1-octen-3-ol and 1-hexanol. Scanning electron microscopy (SEM) images documented that pulsed pressure curing can effectively increase the tenderness of beef. This study demonstrates that processed meat product efficiency and sensory attributes should be taken into account when selecting a curing technique, and the PPC technique has an advantage in both areas.

Salmonella enteritidis (SE) is an important factor causing foodborne disease, and electrochemical sensors have drawn much attention for SE prevention and detection due to their many advantages. A renewable electrochemical sensor using specially designed locked nucleic acids (LNA) as linkers for the detection of SE was proposed to improve the reusability and reproducibility of biosensors. One end of the LNA was designed as an anchor to attach to modified electrodes through the sulfhydryl group; the other end was used to match with a short segment of SE aptamers, which will allow for the convenient renewal of occupied aptamers by raising the temperature. Results revealed that the manufactured biosensor had good stability, reproducibility, and selectivity in addition to a linear range of 6 × 101–6 × 105 CFU/mL and a limit of detection (LOD) of 20.704 CFU/mL. The recovery rate of SE for the real sample varied from 98.84% to 134.82% without exceeding 16.27% in the relative standard deviation (RSD). The proposed biosensor appears to be a promising tool for foodborne pathogen detection.

BackgroundThe Coronavirus 2019 (COVID-19) outbreak has led to a considerable proportion of adverse psychological symptoms in different subpopulations. This study aimed to investigate the status of anxiety and depression and their associated factors in the adult, working-age population in Mainland China at the early remission stage of the COVID-19 pandemic.MethodsAn online study was conducted among 1,863 participants in 29 provinces in Mainland China from March 23 to 31, 2020. Their mental health was evaluated by the generalized anxiety disorder scale (GAD-7) and the patient health questionnaire (PHQ-9). Descriptive analysis, Chi-square, and multiple logistic regressions were applied.ResultsAbout 44.5% of the participants had anxiety, 49.2% had depression, and 37.9% showed a combination of depression and anxiety. Around 83.7% of the participants claimed that the pandemic had a negative impact on their medical needs, which was the primary predictor of mental health, the degree of impact being positively related to the prevalence of anxiety and depression. More chronic diseases, moderate to bad self-rated health, severe perceived infection risk, and younger age group were the common risk factors for anxiety and depression. Having no children, unemployment, and a college-level educational background were associated with higher anxiety prevalence, whereas unmarried participants were correlated with higher depression prevalence.ConclusionThe working-age population showed a relatively high risk of anxiety and depression in Mainland China at the early remission stage of the pandemic. To improve medical services capacity for routine and delayed medical service needs should be a part of policy-makers’ priority agenda during this period of crisis.

This study aims to use bioinformatics methods to determine the epigenetic changes in microRNA expression and DNA methylation caused by cigarette smoking. The data of mRNA, miRNA expression, and methylation microarray were obtained from the GEO database to filter differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and methylated CpG probes (DMPs) through the limma package. The R clusterProfile package was used for functional annotation and enrichment analysis. The protein-protein interaction (PPI) network was constructed by the String database and visualized in Cytoscape software. Starbase database was employed to predict lncRNA and CirRNA based on the sequence of miRNA, and to establish a regulatory network of ceRNA. By overlapping DEG and DEM, 107 down-miRNA-targeted up-regulated genes and 65 up-miRNA-target down-regulated genes were obtained, which were mainly enriched in autophagy signaling pathways and protein ubiquitination pathways, respectively. In addition, 324 genes with low methylation and high expression and 204 genes with high methylation and low expression were respectively related to the degeneration of the nervous system and the function of the cardiovascular system. Interestingly, 43 genes were up-regulated under the dual regulation of reduced miRNA and hypomethylation, while 14 genes were down-regulated under the dual regulation of increased miRNA and hypermethylation. Ten chemicals have been identified as putative therapeutic agents for pathological conditions caused by smoking. In addition, among these genes, HSPA4, GRB2, PRKCA, and BCL2L1 could play a fundamental role in related diseases caused by smoking and may be used as the biomarkers for precise diagnosis and targets for future therapies of smoking-related diseases.