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Abstract N6‐methyladenosine (m6A) is the most abundant modification of RNA in eukaryotic cells. Previous studies have shown that m6A is pivotal in diverse diseases especially cancer. m6A corelates with the initiation, progression, resistance, invasion, and metastasis of cancer. However, despite these insights, a comprehensive understanding of its specific roles and mechanisms within the complex landscape of cancer is still elusive. This review begins by outlining the key regulatory proteins of m6A modification and their posttranslational modifications (PTMs), as well as the role in chromatin accessibility and transcriptional activity within cancer cells. Additionally, it highlights that m6A modifications impact cancer progression by modulating programmed cell death mechanisms and affecting the tumor microenvironment through various cancer‐associated immune cells. Furthermore, the review discusses how microorganisms can induce enduring epigenetic changes and oncogenic effect in microorganism‐associated cancers by altering m6A modifications. Last, it delves into the role of m6A modification in cancer immunotherapy, encompassing RNA therapy, immune checkpoint blockade, cytokine therapy, adoptive cell transfer therapy, and direct targeting of m6A regulators. Overall, this review clarifies the multifaceted role of m6A modification in cancer and explores targeted therapies aimed at manipulating m6A modification, aiming to advance cancer research and improve patient outcomes.

According to the latest consensus, many traditional diseases are considered metabolic diseases, such as cancer, type 2 diabetes, obesity, and cardiovascular disease. Currently, metabolic diseases are increasingly prevalent because of the ever-improving living standards and have become the leading threat to human health. Multiple therapy methods have been applied to treat these diseases, which improves the quality of life of many patients, but the overall effect is still unsatisfactory. Therefore, intensive research on the metabolic process and the pathogenesis of metabolic diseases is imperative. N6-methyladenosine (m6A) is an important modification of eukaryotic RNAs. It is a critical regulator of gene expression that is involved in different cellular functions and physiological processes. Many studies have indicated that m6A modification regulates the development of many metabolic processes and metabolic diseases. In this review, we summarized recent studies on the role of m6A modification in different metabolic processes and metabolic diseases. Additionally, we highlighted the potential m6A-targeted therapy for metabolic diseases, expecting to facilitate m6A-targeted strategies in the treatment of metabolic diseases.

Summary: The efficacy of COVID-19 vaccination relies on the induction of neutralizing antibodies, which can vary among vaccine recipients. In this study, we investigated the potential factors affecting the neutralizing antibody response by combining plasma and urine proteomics and gut microbiota analysis. We found that activation of the LXR/FXR pathway in plasma was associated with the production of ACE2-RBD-inhibiting antibodies, while urine proteins related to complement system, acute phase response signaling, LXR/FXR, and STAT3 pathways were correlated with neutralizing antibody production. Moreover, we observed a correlation between the gut microbiota and plasma and urine proteins, as well as the vaccination response. Based on the above data, we built a predictive model for vaccination response (AUC = 0.85). Our study provides insights into characteristic plasma and urine proteins and gut microbiota associated with the ACE2-RBD-inhibiting antibodies, which could benefit our understanding of the host response to COVID-19 vaccination.

M6A is essential for tumor occurrence and progression. The expression patterns of m6A regulators differ in various kinds of tumors. Transcriptomic expression statistics together with clinical data from a database were analyzed to distinguish patients with digestive tract tumors. Based on the expression patterns of diverse m6A regulators, patients were divided into several clusters. Survival analysis suggested significant differences in patient prognosis among the m6A clusters. The results showed overlapping of m6A expression patterns with energy metabolism and nucleotide metabolism. Functional analyses imply that m6A modifications in tumor cells probably drive metabolic reprogramming to sustain rapid proliferation of cancer cells. Our analysis highlights the m6A risk characterizes various kinds of metabolic features and predicts chemotherapy sensitivity in digestive tract tumors, providing evidence for m6A regulators as markers to predict patient outcomes.

We propose a novel method for estimating the permeability of heterogeneous sandstones based on the nuclear magnetic resonance (NMR) data with multiple echo spacings. The decaying curves and their corresponding spectra are obtained for different echo spacings to investigate the relaxation property, the diffusion term, and the signal loss contributed by higher echo spacing. Moreover, an empirical model is developed to correlate permeability with the differential decay rate. The result shows that the geometric transversal relaxation time is positively related to echo spacing, which disobeys the traditional cognition. Moreover, the absolute value of the differential decay rate is positively correlated with the echo spacing and exhibits a power law behavior. More interestingly, it is observed that the permeability diminishes in a power law behavior with respect to fitting parameters. This marks the first attempt to establish a relationship between the permeability and NMR data with different echo spacings, which is hopeful to be extended to other complex reservoirs with the availability of multiple echo spacing data.

Background The Rhizophoraceae family comprises crucial mangrove plants that inhabit intertidal environments. In China, eight Rhizophoraceae mangrove species exist. Although complete chloroplast (Cp) genomes of four Rhizophoraceae mangrove plants have been reported, the Cp genomes of the remaining four species remain unclear, impeding a comprehensive understanding of the evolutionary history of this family. Methods Illumina high-throughput sequencing was employed to obtain the DNA sequences of Rhizophoraceae species. Cp genomes were assembled by NOVOPlasty and annotated using CpGAVAS software. Phylogenetic and divergence time analyses were conducted using MEGA and BEAST 2 software. Results Four novel Cp genomes of Rhizophoraceae mangrove species (Bruguiera sexangula, Bruguiera gymnorrhiza, Bruguiera × rhynchopetala and Rhizophora apiculata) were successfully assembled. The four Cp genomes ranged in length from 163,310 to 164,560 bp, with gene numbers varying from 124 to 128. The average nucleotide diversity (Pi) value of the eight Rhizophoraceae Cp genomes was 0.00596. Phylogenetic trees constructed based on the complete Cp genomes supported the monophyletic origin of Rhizophoraceae. Divergence time estimation based on the Cp genomes of representative species from Malpighiales showed that the origin of Rhizophoraceae occurred at approximately 58.54–50.02 million years ago (Mya). The divergence time within the genus Rhizophora (∼4.51 Mya) was much earlier than the divergence time within the genus Bruguiera (∼1.41 Mya), suggesting recent speciation processes in these genera. Our data provides new insights into phylogenetic relationship and evolutionary history of Rhizophoraceae mangrove plants.

To efficiently develop deep shale gas in southern Sichuan Basin, under the guidance of “extreme utilization” theory, a basic idea and solutions for deep shale gas development are put forward and applied in practice. In view of multiple influencing factors of shale gas development, low single-well production and marginal profit of wells in this region, the basic idea is to establish “transparent geological body” of the block in concern, evaluate the factors affecting shale gas development through integrated geological-engineering research and optimize the shale gas development of wells in their whole life cycle to balance the relationship between production objectives and development costs. The solutions are as follows: (1) calculate the gold target index and pinpoint the location of horizontal well drilling target, and shale reservoirs are depicted accurately by geophysical and other means to build underground transparent geological body; (2) optimize the drilling and completion process, improve the adaptability of key tools by cooling, reducing density and optimizing the performance of drilling fluid, the “man-made gas reservoir” is built by comprehensively considering the characteristics of in-situ stress and fractures after the development well is drilled; (3) through efficient management, establishment of learning curve and optimization of drainage and production regime, the development quality and efficiency of the well are improved across its whole life cycle, to fulfil “extreme utilization” development of shale gas. The practice shows that the estimated ultimate recovery of single wells in southern Sichuan Basin increase by 10%-20% than last year.

Root microbiota have a significant effect on plant health. However, the role of root microbiota in the resistance of Rhododendron against root rot is not known. In this study, we employed amplicon 16S and ITS sequencing to investigate the bacterial and fungal communities associated with four distinct niches (bulk soil, rhizosphere, rhizoplane, and endosphere) of both healthy and diseased Rhododendron plants in the Baili Rhododendron nature reserve in China. The amplicon data analysis identified 182 bacterial genera and 141 fungal genera that were impacted by root rot across all niches. Specifically, the rhizoplane appeared to exert a selective gating effect, resulting in a reduction in the complexity of bacterial communities, but not fungal communities, in wild Rhododendron delavayi Franch roots. Nevertheless, the stress induced by root rot led to alterations in the root microbiota and compromised the gating function of the rhizoplane, thereby significantly increasing the complexity of the bacterial community within the plant root. In the root tissue following root rot outbreak, the relative abundance of the pathogenic species Pezicula brunnea and Diaporthe helianthi was enriched by as much as 6.13% and 1.71%, respectively. These findings provide novel insights into the contribution of enrichment of root-associated microbiota to wild plant hosts under the disease stress of root rot. The root rot-causing pathogenic fungi may interact with beneficial bacteria and induce plants to send out “cry for help” signals, which may encourage the specific assembly of microbiota. In the Rhododendron delavayi Franch root microbiota, we found 23 potentially beneficial microbes. Notably, certain beneficial bacteria, such as Sporolactobacillus and Stenotrophomonas, were found to accumulate in the rhizoplane and endosphere under root rot disease stress. Overall, our results lend support to our hypothesis that Rhododendron recruits protective microbes as a strategy to suppress root rot outbreaks. Future endeavors in isolating beneficial microbes capable of mitigating root rot have the potential to enhance plant resilience against root diseases.

The nuclear magnetic resonance (NMR) response is known to deviate from the true value for the volcanic reservoirs, particularly when the pore throat size is ultralow. Consequently, the related petrophysical parameters such as porosity, permeability, and pore size distribution from NMR measurements are greatly influenced. An empirical method to correct the NMR calibrated porosity for the tight volcanic rocks is proposed after comprehensive investigations of influential factors combined with mineralogical and petrophysical analyses. The laboratory result indicates that the relative porosity deviation is negatively correlated with the geometric mean of the transversal relaxation time (T2) but positively correlated with the clay content. Moreover, both the paramagnetic materials, such as the manganese (Mn) content, and the diamagnetic materials, such as the magnesium (Mg) content, contribute to the NMR relaxation intensity reduction but with different mechanisms. The NMR calibrated porosity can be compensated through multiple regressions with these controlling factors, which can be generalized to other tight volcanic reservoirs.

This paper adopts the tail-event driven network (TENET) framework to explore the connectedness and systemic risk of the banking industry along the Belt and Road (B&R) based on weekly returns of 377 publicly-listed banks from 2014 to 2019. We conduct the connectedness analysis from four levels (i.e., system, region, country and institution) and identify the systemic risk contribution of banks. We find that the dynamic total connectedness reached its peak during the outbreak of the abnormal fluctuations of Chinese stock market in 2015-2016 and its trough during the Brexit vote, and subsequently experienced several periodic fluctuations at a relatively high position. In the B&R banking system, the intra-regional tail risk spillovers are remarkably stronger than the inter-regional tail risk spillovers during the post-crisis period. In addition, the panel regressions estimated by the least squares dummy variable model show that the cross-border merger and acquisitions (M&As) and the merchandise trade export are important drivers for the tail-connectedness across the B&R countries. Our study provides regulators with insightful implications on the systemic risk supervision of the B&R banking industry.

The shales in the 2nd Member of Permian Shanxi Formation (Shan2 Member) at the Daning-Jixian block at the eastern margin of the Ordos Basin were deposited in a marine–continental transitional environment. The Shan23 sub-member, which is the target interval for transitional shale gas exploration and development in China, is characterized by substantial shale thickness, few and thin interlayers. This interval, however, has been rarely investigated for reservoir characteristics, especially the controlling factors of high-quality reservoirs. In this paper, the reservoir characteristics and main controlling factors of high-quality reservoirs in Shan23 in the Daning-Jixian block were systematically discussed by organic geochemical analysis, mineral compositional analysis, and microscopic reservoir characterization. The results indicate that the lagoon facies shale interval in the upper part of the Shan23 sub-member has a high total organic carbon (TOC) content, a high brittle mineral content, and high BET surface area and BJH pore volume values, indicating that this is the sweet spot for shale gas exploration and development. Pore space in the Shan23 sub-member shale is dominated by clay mineral intercrystalline pores (76.9%), which also contains organic matter pores (18.7%). The SEM observations reveal that the mineral components are different in pore size distribution (PSD) and the organic matter pores and calcite dissolved pores are mainly in meso-scale, the pores in clay minerals and quartz are in meso- and macro-scale, while the pores in feldspar and pyrite exhibit a wide and uniform size distribution. The single-factor analysis shows that the clay mineral content is the dominant factor controlling pore development in the Shan23 sub-member transitional shales, the TOC content has a certain effect on pore development, and the kerogen type has no discernible effect on pore development.

Abstract Background Gastric cancer (GC) is one of the most pernicious tumors that seriously harm human healthcare. GC metastasis is one of the prime cause of failed cancer treatment, but correlation between N6-methyladenosine (m6A) and GC metastasis was less reported. Methods Methylated RNA immunoprecipitation sequencing (MeRIP-seq) of GC tissues was conducted. Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry (IHC) were taken to determine the expression of ALKBH5 in GC tissues and cell lines. RNA-seq together with MeRIP-qRT-PCR was used to screen the target gene of ALKBH5. RNA pulldown, mass spectrometry and RNA immunoprecipitation (RIP) were used to search the “reader” protein of target gene. The mechanism was also validated via a tail vein injection method for lung metastasis model. Results Decreased expression of ALKBH5 was detected in GC samples, and it was correlated with clinical tumor distal metastasis and lymph node metastasis. ALKBH5 interference promoted metastasis of GC cells and this effect was closely related to the demethylase activity of ALKBH5. PKMYT1, as a downstream target of ALKBH5, promoted invasion and migration in GC. Caused by ALKBH5 knockdown or its demethylase activity mutation, upregulated expression of PKMYT1 indicated that ALKBH5 modulates expression of PKMYT1 in an m6A-dependent manner. IGF2BP3 helped stabilize the mRNA stability of PKMYT1 via its m6A modification site. Conclusions This study established an ALKBH5-PKMYT1-IGF2BP3 regulation system in metastasis, representing a new therapeutic target for GC metastasis.

Abstract With the development of blue laser endoscopy (BLE) technique, it's often used to diagnose early gastric cancer (EGC) by the morphological changes of blood vessels through BLE. However, EGC is still not obvious to identify, resulting in a high rate of missed diagnosis. Molecular imaging can show the changes in early tumors at molecular level, which provides a possibility for diagnosing EGC. Therefore, developing a probe that visually monitors blood vessels of EGC under BLE is particularly necessary. Herein, a bis‐pyrene (BP) based nanoprobe (BP‐FFVLK‐(PEG)‐RGD, M1) is designed, which can target angiogenesis and self‐assemble into fibers in situ, resulting in stable and long‐term retention in tumor. Moreover, M1 probe can emit yellow‐green fluorescence for imaging under BLE. M1 probe is confirmed to steadily remain in tumor for up to 96 hours in mice transplanted subcutaneously. In addition, the M1 probe is able to target angiogenesis for molecular imaging of isolated human gastric cancer tissue under BLE. Finally, M1 probe i.v. injected into primary gastric cancer model rabbits successfully highlighted the tumor site under BLE, which is confirmed by pathological analysis. It's the first time to develop a probe for diagnosing EGC by visualizing angiogenesis under BLE, showing great clinical significance.

Detecting pump-and-dump schemes involving cryptoassets with high-frequency data is challenging due to imbalanced datasets and the early occurrence of unusual trading volumes. To address these issues, we propose constructing synthetic balanced datasets using resampling methods and flagging a pump-and-dump from the moment of public announcement up to 60 min beforehand. We validated our proposals using data from Pumpolymp and the CryptoCurrency eXchange Trading Library to identify 351 pump signals relative to the Binance crypto exchange in 2021 and 2022. We found that the most effective approach was using the original imbalanced dataset with pump-and-dumps flagged 60 min in advance, together with a random forest model with data segmented into 30-s chunks and regressors computed with a moving window of 1 h. Our analysis revealed that a better balance between sensitivity and specificity could be achieved by simply selecting an appropriate probability threshold, such as setting the threshold close to the observed prevalence in the original dataset. Resampling methods were useful in some cases, but threshold-independent measures were not affected. Moreover, detecting pump-and-dumps in real-time involves high-dimensional data, and the use of resampling methods to build synthetic datasets can be time-consuming, making them less practical.

Transitional shale gas, rich in resources, is expected to be a practical contributor to the increase in shale gas reserves and production in China. Its exploration prospect has been demonstrated by several wells in the Daning-Jixian block on the eastern margin of the Ordos Basin. In this paper, the Lower Permian Shanxi Formation (P1s) and Taiyuan Formation (P1t) in the eastern margin of Ordos Basin were compared for organic geochemical parameters, revealing that the overflow fan + lagoon combination (OLC) of the third sub-member of the second member of Shanxi Formation (P1s23) and the marine + lagoon combination (MLC) of the first member of Taiyuan Formation (P1t1) are the most favorable shale gas intervals. The two intervals were comparatively analyzed with respect to mineral composition, brittleness, caprocks, and preservation conditions. It is found that the OLC of P1s23 has a similar porosity to and much lower permeability than the MLC of P1t1 (or MLC1) and a BET surface area of 10–15 m2/g, which is smaller than the MLC1 (15–20 m2/g). Moreover, OLC has a brittle mineral content equivalent to MLC1 but a brittleness index of 33.73–62.36 (avg. 49.86), smaller than MLC1 (53.34–58.27, or avg. 55.85). OLC contains sandstones at both the roof and floor, with a higher permeability than shale in the interval, which cannot serve as good physical seals. In contrast, MLC1 contains limestones with lower permeability at the roof and floor, which, together with the overlying coal seams, have hydrocarbon generation capacity and can physically seal the MLC1 shale but also fill it with hydrocarbons, making MLC1 have higher gas content and superior for shale gas exploration than the OLC shale. Due to the multi-lithologies developed in transitional facies, besides the organic matter enrichment, and reservoir characteristics, it is necessary to find a suitable lithological combination to ensure the gas in shale can be better preserved and retained.

Pore and pore network evolution of shale is critical for the evaluation the pore system in shale gas reservoirs. Thermal maturation effect acts as an indispensable role in porosity evolution. In this paper, high-temperature and high-pressure in-situ thermal simulation experiments were conducted to investigate the process and controlling factors of pore evolution in marine-continental transitional shale. Multiple methods, including scanning electron microscopy (SEM), X-ray diffraction, helium porosimetry and low-pressure N2 and CO2 adsorption were used to investigate the evolution of mineral composition and pore structure at different stages of thermal maturity. The results showed that type III organic matter (OM) generated petroleum with the thermal maturity increasing. The total organic carbon (TOC) decreased by 13.3% when temperature reached 607°C. At the same time, it produced numerous organic and mineral pores during hydrocarbon generation. Besides, some changes in mineral composition have occurred, especially in illite (from 11% to 31%) and kaolinite (from 89% to 69%). In general, it can divide into 3 stages (maturity, high maturity and over maturity) for shale pore system evolution with the thermal maturity increasing. In the low maturity period, large amounts of pyrolytic bitumen and oil generated to fill the pores, causing the pore system to diminish; in the high maturity period, a large number of pores were generated when oil is cracked into gas, resulting in a rapid expansion of the pore system; in the over-maturity period, the cracking of pyrolysis and hydrocarbon slowed down, allowing the pore system to stabilize. Shale pore evolution is primarily controlled by the thermal evolution of OM, and the conversion of inorganic minerals contributes less to pore evolution compared to organic matter. The high maturity period (1.2% < Ro < 2.0%) was the period when extensive pyrolysis and hydrocarbon generated in the Shanxi Formation shale, which contributed mostly for the pores generation and accumulation of shale gas.

Despite the recent great achievements in speech emotion recognition (SER) with the development of deep learning, the performance of SER systems depends strongly on the amount of labeled data available for training. Obtaining sufficient annotated data, however, is often extremely time consuming and costly and sometimes even prohibitive because of privacy and ethical concerns. To address this issue, this article proposes the semisupervised generative adversarial network (SSGAN) for SER to capture underlying knowledge from both labeled and unlabeled data. The SSGAN is derived from a GAN, but the discriminator of the SSGAN can not only classify its input samples as real or fake but also distinguish their emotional class if they are real. Thus, the distribution of realistic inputs can be learned to encourage label information sharing between labeled and unlabeled data. This article proposes two advanced methods, i.e., the smoothed SSGAN (SSSGAN) and the virtual smoothed SSGAN (VSSSGAN), which, respectively, smooth the data distribution of the SSGAN via adversarial training (AT) and virtual adversarial training (VAT). The SSSGAN smooths the conditional label distribution given inputs using labeled examples, while the VSSSGAN smooths the conditional label distribution without label information (“virtual” labels). To evaluate the effectiveness of the proposed methods, four publicly available and frequently used corpora are selected to conduct experiments in intradomain and interdomain situations. The results illustrate that the proposed methods are superior to the state-of-the-art methods. Specifically, in experimental settings with mismatched and semimismatched unlabeled training sets, the SSSGAN and VSSSGAN are more robust than the SSGAN because of the distributional smoothness.

ObjectiveMindfulness-based interventions have been widely demonstrated to be effective in reducing stress, alleviating mood disorders, and improving quality of life; however, the underlying mechanisms remained to be fully understood. Along with the advanced research in the microbiota-gut-brain axis, this study aimed to explore the impact of gut microbiota on the effectiveness and responsiveness to mindfulness-based cognitive therapy (MBCT) among high trait anxiety populations.DesignA standard MBCT was performed among 21 young adults with high trait anxiety. A total of 29 healthy controls were matched for age and sex. The differences in gut microbiota between the two groups were compared. The changes in fecal microbiota and psychological indicators were also investigated before and after the intervention.ResultsCompared with healthy controls, we found markedly decreased bacterial diversity and distinctive clusters among high trait anxiety populations, with significant overgrowth of bacteria such as Streptococcus, Blautia, and Romboutsia, and a decrease in genera such as Faecalibacterium, Coprococcus_3, and Lachnoclostridium. Moreover, MBCT attenuated trait anxiety and depression, improved mindfulness and resilience, and increased the similarity of gut microbiota to that of healthy controls. Notably, a high presence of intestinal Subdoligranulum pre-MBCT was associated with increased responsiveness to MBCT. Decreases in Subdoligranulum post-MBCT were indicative of ameliorated trait anxiety. The tryptophan metabolism pathways were significantly over-represented among high responders compared to low responders.ConclusionThe significantly increased diversity post-MBCT added evidence to gut-brain communication and highlighted the utility of mycobiota-focused strategies for promoting the effectiveness and responsiveness of the MBCT to improve trait anxiety.Clinical Trial Registrationchictr.org.cn, ChiCTR1900028389.

The use of vision for the recognition of water targets is easily influenced by reflections and ripples, resulting in misidentification. This paper proposed a detection method based on the fusion of 3D point clouds and visual information to detect and locate water surface targets. The point clouds help to reduce the impact of ripples and reflections, and the recognition accuracy is enhanced by visual information. This method consists of three steps: Firstly, the water surface target is detected using the CornerNet-Lite network, and then the candidate target box and camera detection confidence are determined. Secondly, the 3D point cloud is projected onto the two-dimensional pixel plane, and the confidence of LiDAR detection is calculated based on the ratio between the projected area of the point clouds and the pixel area of the bounding box. The target confidence is calculated with the camera detection and LiDAR detection confidence, and the water surface target is determined by combining the detection thresholds. Finally, the bounding box is used to determine the 3D point clouds of the target and estimate its 3D coordinates. The experiment results showed this method reduced the misidentification rate and had 15.5% higher accuracy compared with traditional CornerNet-Lite network. By combining the depth information from LiDAR, the position of the target relative to the detection coordinate system origin could be accurately estimated.

Abstract Although long noncoding RNAs (lncRNAs) do not have protein coding capacities, they are involved in the pathogenesis of many types of cancers, including hepatocellular carcinoma, cervical cancer, and gastric cancer. Notably, the roles of lncRNAs are vital in nearly every aspect of tumor biology. Long non‐coding small nucleolar RNA host genes (lnc‐SNHGs) are abnormally expressed in multiple cancers, including urologic neoplasms, respiratory tumors, and digestive cancers, and play vital roles in these cancers. These host genes could participate in tumorigenesis by regulating proliferation, migration, invasion and apoptosis of tumor cells. This review focuses on the overview of the roles that lnc‐SNHGs play in the formation and progression of digestive cancers.

Male infertility is a widespread health problem affecting approximately 6%–8% of the male population, and hypoxia may be a causative factor. In mammals, two types of hypoxia are known, including environmental and pathological hypoxia. Studies looking at the effects of hypoxia on male infertility have linked both types of hypoxia to poor sperm quality and pregnancy outcomes. Hypoxia damages testicular seminiferous tubule directly, leading to the disorder of seminiferous epithelium and shedding of spermatogenic cells. Hypoxia can also disrupt the balance between oxidative phosphorylation and glycolysis of spermatogenic cells, resulting in impaired self-renewal and differentiation of spermatogonia, and failure of meiosis. In addition, hypoxia disrupts the secretion of reproductive hormones, causing spermatogenic arrest and erectile dysfunction. The possible mechanisms involved in hypoxia on male reproductive toxicity mainly include excessive ROS mediated oxidative stress, HIF-1α mediated germ cell apoptosis and proliferation inhibition, systematic inflammation and epigenetic changes. In this review, we discuss the correlations between hypoxia and male infertility based on epidemiological, clinical and animal studies and enumerate the hypoxic factors causing male infertility in detail. Demonstration of the causal association between hypoxia and male infertility will provide more options for the treatment of male infertility

The porous and low-permeability characteristics of a shale gas reservoir determine its high gas storage efficiency, which is manifested in the extremely high breakthrough pressure of shale. Therefore, the accurate calculation of breakthrough pressure is of great significance to the study of shale gas preservation conditions. Based on a systematic analysis of a low-field NMR experiment on marine shales of the Longmaxi Formation in the Sichuan Basin, a shale gas breakthrough pressure determination technique different from conventional methods is proposed. The conventional methods have low calculation accuracy and are a tedious and time-consuming process, while low-field NMR technique is less time-consuming and of high accuracy. Firstly, the NMR T2 spectrum of shale core sample in different states is measured through low-field NMR experiment. The NMR T2 spectra of sample in water-saturated state and dry state are combined to model the mathematical relationship between shale gas breakthrough pressure and NMR T2 spectrum. It is found that the gas breakthrough pressure is power-exponentially related to the geometric mean of NMR T2 spectrum and positively related to the proportion of micropores. Accordingly, the shale gas breakthrough pressure is quickly and accurately calculated using continuous NMR logging data and then the sealing capacity of the shale caprocks is evaluated, providing basic parameters for analyzing unconventional hydrocarbon accumulation, preservation and migration. This technique has been successfully applied with actual data to evaluate the sealing capacity of shale caprock in a shale gas well in the Sichuan Basin. It can provide a good basis for the evaluation and characterization of shale oil and gas reservoirs.

Abstract Background Hepatitis B virus (HBV) infection is a major public health problem in China. Over a decade has passed since the last National Hepatitis Seroepidemiological Survey was conducted in 2006. The lack of updated data on hepatitis B in China makes assessing the current prevalence and burden of the disease inadequate. In response to the above situation, a systematic review and meta-analysis was conducted to provide a better understanding of hepatitis B epidemiology in the general population of China. Methods A systematic search was conducted in international databases (Medline through PubMed, EMBASE, Cochrane, Web of Science) and national databases (CBM, CNKI, WanFang Data) to retrieve primary studies published between January 1, 2013 and December 31, 2017. The pooled prevalence of HBV infection and 95% confidence intervals were calculated. Quality assessment, heterogeneity testing and publication bias assessment were also performed. Results Of the 27 studies included in the meta-analysis, the pooled estimated prevalence of HBV infection in the general population of China from 2013 to 2017 was 6.89% (95% CI:5.84–7.95%), which could be extrapolated to an estimated population of 84 million living with HBsAg in 2018. The prevalence of HBV infection in males was higher than that in females (5.88% vs 5.05%), and rural areas had a higher prevalence than urban areas (5.86% vs 3.29%). The highest prevalence of HBV infection was reported in Western provinces (8.92, 95% CI: 7.19–10.64%). In adults older than 20 years, the prevalence of HBV infection was approximately 7%, which was higher than that in children. Conclusion The prevalence of HBV infection in the general population of China was classified as higher intermediate prevalence (5–7.99%), of which more than 90% of the HBV infection population included adults older than 20 years. The blocking of mother-to-infant hepatitis B transmission and plans involving timely birth dose of hepatitis B vaccine within 24 h should be implemented. Additionally, improving the quality of life and survival rate of the infected population through antiviral therapy and high-risk adult vaccination will be the priority of our future work. Moreover, various control measures should be implemented in different provinces across China.

High human telomerase reverse transcriptase (hTERT) expression is related to severe Colorectal Cancer (CRC) progression and negatively related to CRC patient survival. Previous studies have revealed that hTERT can reduce cancer cellular reactive oxygen species (ROS) levels and accelerate cancer progression; however, the mechanism remains poorly understood. NFE2-related factor 2 (NRF2) is a molecule that plays a significant role in regulating cellular ROS homeostasis, but whether there is a correlation between hTERT and NRF2 remains unclear. Here, we showed that hTERT increases CRC proliferation and migration by inducing NRF2 upregulation. We further found that hTERT increases NRF2 expression at both the mRNA and protein levels. Our data also revealed that hTERT primarily upregulates NRF2 by increasing NRF2 promoter activity rather than by regulating NRF2 mRNA or protein stability. Using DNA pull-down/MS analysis, we found that hTERT can recruit YBX1 to upregulate NRF2 promoter activity. We also found that hTERT/YBX1 may localize to the P2 region of the NRF2 promoter. Taken together, our results demonstrate that hTERT facilitates CRC proliferation and migration by upregulating NRF2 expression through the recruitment of the transcription factor YBX1 to activate the NRF2 promoter. These results provide a new theoretical basis for CRC treatment.

M6A is the most prevalent modification among epigenetics. M6A occurs on different sites of RNA and exerts important functions in specific circumstances, such as mRNA splicing, stability, nuclear export, translation or damage response. Different aspects of the concrete machinery of m6A modification have been studied, including its writing, erasing and reading capabilities. The molecular and biological functions of the m6A modification and enzymes, as well as their functions in different cancers have been substantially published. The present review summarizes these findings and provides clear description of the problems involved. The probable roles of m6A modification may acts on other cancers, suggesting that it may be a treatment target for these cancers.

Generative adversarial networks (GANs), which are a promising type of deep generative network, have recently drawn considerable attention and made impressive progress. However, GAN models suffer from the well-known problem of mode collapse. This study focuses on this challenge and introduces a new model design, called the encoded multi-agent generative adversarial network (E-MGAN), which tackles the mode collapse problem by introducing the variational latent representations learned from a variable auto-encoder (VAE) to a multi-agent GAN. The variational latent representations are extracted from training data to replace the random noise input of the general multi-agent GANs. The generator in E-MGAN employs multiple generators and is penalized by a classifier. This integration guarantees that the proposed model not only enhances the quality of generated samples but also improves the diversity of generated samples to avoid the mode collapse problem. Moreover, extensive experiments are conducted on both a synthetic dataset and two large-scale real-world datasets. The generated samples are visualized for qualitative evaluation. The inception score (IS) and Fréchet inception distance (FID) are adopted to measure the performance of the model for quantitative assessment. The results confirmed that the proposed model achieves outstanding performances compared to other state-of-the-art GAN variants.

The research of robotic autonomous radioactivity detection or radioactive source search plays an important role in the monitoring and disposal of nuclear safety and biological safety. In this paper, a method for autonomously searching for radioactive sources through mobile robots was proposed. In the method, by using a partially observable Markov decision process (POMDP), the search of autonomous unknown radioactive sources was realized according to a series of radiation information measured by mobile robot. First, the factors affecting the accuracy of radiation measurement during the robot’s movement were analyzed. Based on these factors, the behavior set of POMDP was designed. Secondly, the parameters of the radioactive source were estimated in the Bayesian framework. In addition, through the reward strategy, autonomous navigation of the robot to the position of the radiation source was achieved. The search algorithm was simulated and tested, and the TurtleBot robot platform was used to conduct a real search experiment on the radio source Cs-137 with an activity of 37 MBq indoors. The experimental results showed the effectiveness of the method. Additionally, from the experiments, it could been seen that the robot was affected by the linear velocity, angular velocity, positioning accuracy and the number of measurements in the process of autonomous search for the radioactive source. The proposed mobile robot autonomous search method can be applied to the search for lost radioactive sources, as well as for the leakage of substances (nuclear or chemical) in nuclear power plants and chemical plants.

The integration of 6G networks with emerging key technologies such as blockchain, artificial intelligence, and digital twins continues to improve. However, it carries many issues with security threats and challenges of 6G networks. In this article, we analyzed the security issues of 6G networks and presented some possible solutions. First, we discussed the developments of mobile communication technology, the research motivation of 6G networks, the comparison of Key Performance Indicators (KPIs) between 5G/6G networks, and the key technologies of 6G networks. Next, security threats in the 6G network were analyzed concerning architecture, major visions and related applications. This was followed by solutions to security issues in applying key technologies for 6G networks. We also presented the application of AI in solving 6G network security problems. Firstly, we illustrated the impact of AI on 6G networks from two aspects: AI promotes the construction of 6G networks, and AI brings security threats to 6G networks. Then, we demonstrated that AI can assist 6G networks in solving security problems in many ways. Lastly, the is summarized, and the future directions in this area are proposed. [ABSTRACT FROM AUTHOR]

Aims: Soybean root rot, caused by Fusarium oxysporum, leads to significant economic and financial losses to the soybean processing industry globally. In the study, we aimed to explore a biocontrol agent to combat F. oxysporum infection in soybean. Methods and Results: From soybean rhizosphere soil, 48 strains were isolated. Among them, the strain DR11 exhibited the highest inhibition rate of 72.27%. Morphological, physiological, biochemical, and 16S rDNA identification revealed that the strain DR11 was Klebsiella grimontii DR11. Strain DR11 could inhibit the growth of F. oxysporum and spore formation and alter the mycelial morphology. At 5.0 × 106 CFU mL−1, pH 7, and 30°C, it exhibited the highest inhibitory rate (72.27%). Moreover, it could decrease the activity of cell-wall-degrading enzymes of F. oxysporum. Simultaneously, the activities of defense-related enzymes and content of malondialdehyde in soybean plants were increased after treatment with strain DR11. In addition, strain DR11 could form aggregates to form biofilm and adsorb on the surface of soybean roots. It inhibited F. oxysporum growth on soybean seedlings, with an inhibitory effect of 62.71%. Conclusion: Klebsiella grimontii DR11 had a strong inhibitory effect on F. oxysporum and could be used as a biocontrol agent to combat F. oxysporum infection in soybean. [ABSTRACT FROM AUTHOR]