IAnimal: a cross-species omics knowledgebase for animals.

With the exponential growth of multi-omics data, its integration and utilization have brought unprecedented opportunities for the interpretation of gene regulation mechanisms and the comprehensive analyses of biological systems. IAnimal (https://ianimal.pro/), a cross-species, multi-omics knowledgebase, was developed to improve the utilization of massive public data and simplify the integration of multi-omics information to mine the genetic mechanisms of objective traits. Currently, IAnimal provides 61 191 individual omics data of genome (WGS), transcriptome (RNA-Seq), epigenome (ChIP-Seq, ATAC-Seq) and genome annotation information for 21 species, such as mice, pigs, cattle, chickens, and macaques. The scale of its total clean data has reached 846.46 TB. To better understand the biological significance of omics information, a deep learning model for IAnimal was built based on BioBERT and AutoNER to mine 'gene' and 'trait' entities from 2 794 237 abstracts, which has practical significance for comprehending how each omics layer regulates genes to affect traits. By means of user-friendly web interfaces, flexible data application programming interfaces, and abundant functional modules, IAnimal enables users to easily query, mine, and visualize characteristics in various omics, and to infer how genes play biological roles under the influence of various omics layers.

Advancements in fertility preservation strategies for pediatric male cancer patients: a review of cryopreservation and transplantation of immature testicular tissue.

Recently, there has been increasing emphasis on the gonadotoxic effects of cancer therapy in prepubertal boys. As advances in oncology treatments continue to enhance survival rates for prepubertal boys, the need for preserving their functional testicular tissue for future reproduction becomes increasingly vital. Therefore, we explore cutting-edge strategies in fertility preservation, focusing on the cryopreservation and transplantation of immature testicular tissue as a promising avenue. The evolution of cryopreservation techniques, from controlled slow freezing to more recent advancements in vitrification, with an assessment of their strengths and limitations was exhibited. Detailed analysis of cryoprotectants, exposure times, and protocols underscores their impact on immature testicular tissue viability. In transplantation strategy, studies have revealed that the scrotal site may be the preferred location for immature testicular tissue grafting in both autotransplantation and xenotransplantation scenarios. Moreover, the use of biomaterial scaffolds during graft transplantation has shown promise in enhancing graft survival and stimulating spermatogenesis in immature testicular tissue over time. This comprehensive review provides a holistic approach to optimize the preservation strategy of human immature testicular tissue in the future.

Effect of metformin on gut microbiota imbalance in patients with T2DM, and the value of probiotic supplementation.

PURPOSE: To investigate the effect of metformin on gut microbiota imbalance in patients with type 2 diabetes mellitus (T2DM), and the value of probiotic supplementation. METHODS: A total of 84 newly diagnosed T2DM patients were randomly divided into probiotics group, metformin group, and control group, with 28 patients in each group. The blood glucose control, islet function, gut microbiota, and inflammatory factors were compared between three groups. RESULTS: After 3 months of treatment, fasting plasma glucose (FPG), 2-h postprandial plasma glucose (2-h PG), and glycosylated hemoglobin A1c (HbA1c) were evidently decreased in both probiotics and metformin groups (P < 0.05) and were lower than that in the control group prior to treatment. Besides, FPG, 2-h PG, and HbA1c were lower in the metformin group than that in the control group. FPG, 2-h PG, and HbA1c were further lower in the probiotic group than in the metformin group (P < 0.05). Fasting insulin (FINS) and islet ß cell (HOMA-ß) -function were dramatically increased in the same group (P < 0.05), while insulin-resistant islet ß cells (HOMA-IR) were significantly lower in the same group (P < 0.05); FINS and HOMA-ß were significantly higher, while HOMA-IR was significantly lower (P < 0.05) in both groups than in the control group prior to treatment. HOMA-IR was also lower in the probiotic group than in the metformin group after treatment (P < 0.05); the number of lactobacilli and bifidobacteria increased (P < 0.05) in both probiotic and metformin groups than in the control group prior to treatment, and the number of Enterobacteriaceae and Enterococcus was lower in the control group prior to treatment (P < 0.05). In addition, the number of lactobacilli and bifidobacteria was higher and the number of enterobacteria and enterococci was lower in the probiotic group than that in the metformin group after treatment, and the differences were statistically significant (P < 0.05). Lipopolysaccharide (LPS), interleukin 6 (IL-6), and C-reactive protein (CRP) levels were lower in both probiotic and metformin groups (P < 0.05). The serum LPS, IL-6, and CRP levels were lower in both probiotic and metformin groups, compared to the control group prior to the treatment (P < 0.05). CONCLUSION: Metformin while treating T2DM assists in improving the imbalance of gut microbiota.

Pretreatment of septic tank wastewater by packed anaerobic baffled reactor: Pollutant degradation and microbial community succession in different compartments.

Anaerobic baffled reactor (ABR) is widely used in rural sewage treatment due to its unique structure, strong impact load resistance, and low energy consumption. However, there is a lack of research on pollutant degradation patterns and microbial community succession patterns in each compartment of ABR. In this study, a packed anaerobic baffled reactor (PABR) was constructed. The effects of T and HRT on the pollutant removal performance of PABR were investigated, and the pollutant degradation and microbial community succession in different compartments of PABR were studied. The results show that the removal rates of COD, NH4+-N, and TN of PABR can reach 85.54 ± 1.08%, 16.94 ± 1.01%, and 5.64 ± 1.18% respectively, and PABR has a good pollutant removal effect. With the extension of HRT, the COD removal rate of PABR increases steadily, and the NH4+-N and TN removal rate of PABR increases to a certain extent. The recommended HRT is 72 h. T has a significant impact on the COD removal effect of PABR. The increase of T in a certain range is conducive to the removal of pollutants by PABR. The COD removal rate of PABR decreases gradually along the flow direction, and the removal of organic matter is mainly concentrated in the first compartment. PABR has good removal capacity for CODss and better nitrogen removal capacity compared with traditional ABR. The richness and diversity of the microbial community in PABR increased gradually along the flow direction. The bacterial species in each compartment were similar but the proportion was different, showing the characteristics of multi-stage and separated phase operation. This study provides a new reference for the application of ABR in rural sewage treatment.

Ultra-Reliable Deep-Reinforcement-Learning-Based Intelligent Downlink Scheduling for 5G New Radio-Vehicle to Infrastructure Scenarios.

Higher standards for reliability and efficiency apply to the connection between vehicle terminals and infrastructure by the fifth-generation mobile communication technology (5G). A vehicle-to-infrastructure system uses a communication system called NR-V2I (New Radio-Vehicle to Infrastructure), which uses Link Adaptation (LA) technology to communicate in constantly changing V2I to increase the efficacy and reliability of V2I information transmission. This paper proposes a Double Deep Q-learning (DDQL) LA scheduling algorithm for optimizing the modulation and coding scheme (MCS) of autonomous driving vehicles in V2I communication. The problem with the Doppler shift and complex fast time-varying channels reducing the reliability of information transmission in V2I scenarios is that they make it less likely that the information will be transmitted accurately. Schedules for autonomous vehicles using Space Division Multiplexing (SDM) and MCS are used in V2I communications. To address the issue of Deep Q-learning (DQL) overestimation in the Q-Network learning process, the approach integrates Deep Neural Network (DNN) and Double Q-Network (DDQN). The findings of this study demonstrate that the suggested algorithm can adapt to complex channel environments with varying vehicle speeds in V2I scenarios and by choosing the best scheduling scheme for V2I road information transmission using a combination of MCS. SDM not only increases the accuracy of the transmission of road safety information but also helps to foster cooperation and communication between vehicle terminals to realize cooperative driving.

Cyclic hexadepsipeptides from the fermentation of Fusarium sp. DCJ-A and their cytotoxic activities.

Beauvercin H (1), a new cyclic hexadepsipeptide, and two known ones (2 and 3) were isolated from the EtOH extract of the solid culture of Fusarium sp. Their structures were elucidated by spectroscopic analysis, including extensive 1D and 2D NMR techniques, as well as comparison with literature values. Additionally, compounds 1-3 were tested for their cytotoxic activities. The results showed that all isolated compounds exhibited cytotoxic activities against five human cancer cell lines with IC50 values ranging from 1.379 to 13.12 µM.

Multi-Modal Representation via Contrastive Learning with Attention Bottleneck Fusion and Attentive Statistics Features.

The integration of information from multiple modalities is a highly active area of research. Previous techniques have predominantly focused on fusing shallow features or high-level representations generated by deep unimodal networks, which only capture a subset of the hierarchical relationships across modalities. However, previous methods are often limited to exploiting the fine-grained statistical features inherent in multimodal data. This paper proposes an approach that densely integrates representations by computing image features' means and standard deviations. The global statistics of features afford a holistic perspective, capturing the overarching distribution and trends inherent in the data, thereby facilitating enhanced comprehension and characterization of multimodal data. We also leverage a Transformer-based fusion encoder to effectively capture global variations in multimodal features. To further enhance the learning process, we incorporate a contrastive loss function that encourages the discovery of shared information across different modalities. To validate the effectiveness of our approach, we conduct experiments on three widely used multimodal sentiment analysis datasets. The results demonstrate the efficacy of our proposed method, achieving significant performance improvements compared to existing approaches.

Convolutional Models with Multi-Feature Fusion for Effective Link Prediction in Knowledge Graph Embedding.

Link prediction remains paramount in knowledge graph embedding (KGE), aiming to discern obscured or non-manifest relationships within a given knowledge graph (KG). Despite the critical nature of this endeavor, contemporary methodologies grapple with notable constraints, predominantly in terms of computational overhead and the intricacy of encapsulating multifaceted relationships. This paper introduces a sophisticated approach that amalgamates convolutional operators with pertinent graph structural information. By meticulously integrating information pertinent to entities and their immediate relational neighbors, we enhance the performance of the convolutional model, culminating in an averaged embedding ensuing from the convolution across entities and their proximal nodes. Significantly, our methodology presents a distinctive avenue, facilitating the inclusion of edge-specific data into the convolutional model's input, thus endowing users with the latitude to calibrate the model's architecture and parameters congruent with their specific dataset. Empirical evaluations underscore the ascendancy of our proposition over extant convolution-based link prediction benchmarks, particularly evident across the FB15k, WN18, and YAGO3-10 datasets. The primary objective of this research lies in forging KGE link prediction methodologies imbued with heightened efficiency and adeptness, thereby addressing salient challenges inherent to real-world applications.

High glucose stimulating ECM remodeling and an inflammatory phenotype in the IPFP via upregulation of MFAP5 expression.

Extracellular matrix (ECM) remodeling and inflammation in the infrapatellar fat pad (IPFP) are associated with cartilage degeneration and the severity of osteoarthritis (OA). Diabetes is associated with the progression of OA. However, it is still unclear whether diabetes can promote osteoarthritis by targeting the IPFP. In this study, we established a high-fat diet/streptozotocin (HFD/STZ)-induced diabetes mouse model. We found that fibrosis and inflammation were more severe in the IPFP in diabetic mice. Transcriptomic profiling showed that MFAP5 expression was upregulated in IPFPs collected from diabetic mice compared to IPFPs collected from normal mice. We identified that Pdgfrα(+) progenitors were the primary source of MFAP5 in the IPFP under diabetic conditions. In addition, high glucose promoted the expression of MFAP5 in Pdgfrα(+) progenitors by stimulating the translocation of Yap1. Overexpression of MFAP5 in Pdgfrα(+) progenitors promoted fibrogenic differentiation and the production of IL-6. Knocking down the expression of MFAP5 efficiently prevented fibrosis and decreased the level of IL-6 in the IPFP and attenuated cartilage degeneration. Together, these results suggest that MFAP5 may be a potential novel therapeutic target for the treatment of diabetes-induced OA.

The Unique CO Activation Effects for Boosting NH3 Selective Catalytic Oxidation over CuOx-CeO2.

Slip NH3 is a priority pollutant of concern to be removed in various flue gases with NOx and CO after denitrification using NH3-SCR or NH3-SNCR, and the simultaneous catalytic removal of NH3 and CO has become one of the new topics in the deep treatment of such flue gases. Synergistic catalytic oxidation of CO and NH3 appears to be a promising method but still has many challenges. Due to the competition for active oxidizing species, CO was supposed to hinder the NH3 selective catalytic oxidation (NH3-SCO). However, it is first found that CO could significantly promote NH3-SCO over the CuOx-CeO2 catalyst. The NH3 conversion rates increased linearly with CO concentrations in the range of 180-300 °C. Specifically, it accelerated by 2.8 times with 10,000 ppm CO inflow at 220 °C. Mechanism studies found that the Cu-O-Ce solid solution was more active for CO oxidation, while the CuOx species facilitated the NH3 dehydrogenation and mitigated the competition of NH3 and CO, further stabilizing the promotion effects. Gaseous CO boosted the generation of active isolated oxygen atoms (Oi) by actuating the Cu+/Cu2+ redox cycle. The enriched Oi facilitated oxidation of NH3 to NO and was conducive to the NH3-SCO via the i-SCR approach. This study tapped the potential of CO for promoting simultaneous catalytic oxidation of coexisting pollutants in the flue gas.

Denitrification performance and characteristics of untreated corncob for enhanced nitrogen removal of municipal sewage with low C/N ratio.

Unpretreated corncob was applied in denitrification bio-filter (DNBF) and anoxic tank of AAO system, respectively, to treat sewage with low C/N ratio, and both two approaches achieved good denitrification performance. Although shorter HRT could effectively decrease effluent chroma and COD of corncob-DNBF, nitrogen removal efficiency declined unexpectedly. Higher internal reflux ratio was beneficial for corncob-AAO without damage to anoxic environment for denitrification, while there was no risk of effluent chroma and excessive COD. Different supplement modes could realize same denitrification effect with distinct advantages, which were higher specific denitrification rate and biomass amount, respectively. The latter mode, applying corncob at secondary treatment, was preferable for its operational stability and convenience. Stoichiometry analysis indicated the unit COD demand of AAO decreased from 5.70 to 5.04 g COD/g N after adding corncob, and the oxygen demand (or energy consumption of aeration) decreased as well. The dominant substrates decomposer in corncob-AAO altered to Kouleothrix (affiliated to phylum Chloroflexi), and the main denitrifying bacteria were unclassified_f__Methylophilaceae and Azospira. Accordingly, functional enzymes for degrading glucan, xylan and lignin and processing denitrification showed satisfying abundance in the integrated system, especially in the newly formed biofilm.

Effect of dexmedetomidine for prevention of acute kidney injury after cardiac surgery: an updated systematic review and meta-analysis.

BACKGROUND: Acute kidney injury (AKI) is a serious complication related to cardiac surgery. Several studies have been conducted to investigate the effect of dexmedetomidine administration on AKI prevention. OBJECTIVE: To assess if dexmedetomidine is associated with a protective effect of renal function after cardiac surgery. And the aim of conducting this meta-analysis is to summarize the literature and determine the clinical utility of dexmedetomidine administration in patients undergoing cardiac surgery. METHODS: PubMed, Cochrane Library, and EMBASE databases were comprehensively searched for all randomized controlled trials (RCTs) published before 1 December, 2021 that investigated the effect of dexmedetomidine on AKI prevention. RESULTS: Our analysis included 16 studies involving 2148 patients. Compared with the control group, dexmedetomidine administration significantly reduced AKI incidence (OR, 0.47; 95% CI, 0.36-0.61; p < 0.00001; I2 = 26%) and the length of stay in the intensive care unit (ICU) but did not alter mortality rate, length of stay in the hospital, and mechanical ventilation time. Furthermore, the incidence of delirium among patients treated with dexmedetomidine was significantly decreased. CONCLUSION: Dexmedetomidine administration has a positive effect on preventing AKI and postoperative delirium after cardiac surgery and significantly reduces the length of stay in the ICU.

[Determination of Dichloromethane in Blood with Headspace Gas Chromatography and Gas Chromatography-Mass Spectrometry].

Objective: To establish a method for qualitative determination of dichloromethane (DCM) in blood by gas chromatography-mass spectrometry (GC-MS) and quantitative determination of DCM in blood by headspace gas chromatography (HS-GC), and to provide reliable support for forensic examination and analysis of poisoning or deaths caused by DCM. Methods: 0.5 mL blood sample was collected, added into headspace vial with chloroform as the internal standard, and processed by heating at 65 °C and evacuation treatment. The intermediate gas in the headspace vial was analyzed by GC-MS for qualitative validation of the method and by HS-GC for quantitative validation of the method. The method was then applied in forensic case analysis. Results: Qualitative validation of the examination method by GC-MS found that the chromatographic peak and mass spectral characteristic ions were specific in samples added with DCM, and that no interference was observed in the blank negative samples. The limit of detection (LOD) was 5 µg/mL. Quantitative method validation by HS-GC found that the chromatographic peak of DCM was well separated from those of eight other volatile compounds, with the resolution>1.5 in all cases; the lower limit of quantification (LOQ) was 20 µg/mL and good linearity was shown within the range of 20 and 1000 µg/mL, R>0.999; the intra-day test precision and inter-day test precision were good (relative standard deviation, or RSD<15% for both) and test accuracy was high (relative error, or δ<15%). With the method established in the study, DCM was detected successfully in the blood of two fatal cases caused by DCM poisoning, with the blood concentration being 470 µg/mL and 915 µg/mL, respectively. Conclusion: This method is shown to be a rapid, stable and accurate approach to the qualitative and quantitative forensic and toxicological analysis of DCM in blood in DCM poisoning cases or deaths caused by DCM.

Production of H2S with a Novel Short-Process for the Removal of Heavy Metals in Acidic Effluents from Smelting Flue-Gas Scrubbing Systems.

Direct sulfidation using a high concentration of H2S (HC-H2S) has shown potential for heavy metals removal in various acidic effluents. However, the lack of a smooth method for producing HC-H2S is a critical challenge. Herein, a novel short-process hydrolysis method was developed for the on-site production of HC-H2S. Near-perfect 100% efficiency and selectivity were obtained via CS2 hydrolysis over the ZrO2-based catalyst. Meanwhile, no apparent residual sulfur/sulfate poisoning was detected, which guaranteed long-term operation. The coexistence of CO2 in the products had a negligible effect on the complete hydrolysis of CS2. H2S production followed a sequential hydrolysis pathway, with the reactions for CS2 adsorption and dissociation being the rate-determining steps. The energy balance indicated that HC-H2S production was a mildly exothermic reaction, and the heat energy could be maintained at self-balance with approximately 80% heat recovery. The batch sulfidation efficiencies for As(III), Hg(II), Pb(II), and Cd(II) removal were over 99.9%, following the solubilities (Ksp) of the corresponding metal sulfides. CO2 in the mixed gas produced by CS2 hydrolysis did not affect heavy metals sulfidation due to the presence of abundant H+. Finally, a pilot-scale experiment successfully demonstrated the practical effects. Therefore, this novel on-site HC-H2S production method adequately achieved heavy metals removal requirements in acidic effluents.

Autosomal recessive Alport syndrome caused by a novel COL4A4 compound heterozygous mutation: A case report.

AIM: Autosomal dominant inheritance of Alport syndrome (AS) is very rare, and only a few unrelated families have been found with COL4A3 or COL4A4 gene mutations. Therefore, we aimed to explore the COL4A4 gene mutation spectrum in autosomal recessive Alport syndrome (ARAS). MATERIALS AND METHODS: Blood samples of the proband and his parents were sent to the Institute of Rare Diseases at the West China Hospital of Sichuan University for genetic testing. The analyzed genes were COL4A3-5. The chip capture high-throughput sequencing method was adopted. The data analysis process of high-throughput sequencing was applied for data analysis. RESULTS: A 26-year-old female patient (proband) was diagnosed with AS. The results of genetic analysis and comparison between the proband's genetic information and her parents' showed that the proband carried a compound heterozygous mutation c.4758_4760delCCC (p.1586_1587del) and c.4333+3A>G in the COL4A4 gene; the nonframeshift mutation c.4758_4760delCCC (p.1586_1587del) was inherited from her mother, and the splice site mutation c.4333+3A>G was inherited from her father, suggesting that COL4A4 gene variants caused ARAS in this patient. CONCLUSION: The novel mutation found in this patient enriches the mutation spectrum of ARAS caused by the COL4A4 gene.

Extracellular Amylase Is Required for Full Virulence and Regulated by the Global Posttranscriptional Regulator RsmA in Xanthomonas campestris Pathovar campestris.

As with many phytopathogenic bacteria, the virulence of Xanthomonas campestris pv. campestris, the causal agent of black rot disease in cruciferous plants, relies on secretion of a suite of extracellular enzymes that includes cellulase (endoglucanase), pectinase, protease, and amylase. Although the role in virulence of a number of these enzymes has been assessed, the contribution of amylase to X. campestris pv. campestris virulence has yet to be established. In this work, we investigated both the role of extracellular amylase in X. campestris pv. campestris virulence and the control of its expression. Deletion of XC3487 (here renamed amyAXcc), a putative amylase-encoding gene from the genome of X. campestris pv. campestris strain 8004, resulted in a complete loss of extracellular amylase activity and significant reduction in virulence. The extracellular amylase activity and virulence of the amyAXcc mutant could be restored to the wild-type level by expressing amyAXcc in trans. These results demonstrated that amyAXcc is responsible for the extracellular amylase activity of X. campestris pv. campestris and indicated that extracellular amylase plays an important role in X. campestris pv. campestris virulence. We also found that the expression of amyAXcc is strongly induced by starch and requires activation by the global posttranscriptional regulator RsmA. RsmA binds specifically to the 5'-untranslated region of amyAXcc transcripts, suggesting that RsmA regulates amyAXcc directly at the posttranscriptional level. Unexpectedly, in addition to posttranscriptional regulation, the use of a transcriptional reporter demonstrated that RsmA also regulates amyAXcc expression at the transcriptional level, possibly by an indirect mechanism.

Exenatide Twice Daily Plus Glargine Versus Aspart 70/30 Twice Daily in Patients With Type 2 Diabetes With Inadequate Glycemic Control on Premixed Human Insulin and Metformin.

OBJECTIVE: Many patients with type 2 diabetes treated with premixed insulin gradually have inadequate glycemic control and switch to a basal-bolus regimen, which raises some concerns for weight gain and increased hypoglycemic risk. Switching to combination use of glp-1 agonist and basal insulin may be an alternative option. METHODS: After a 12-week premixed human insulin 70/30 dosage optimization period, 200 patients with HbA1c of 7.0% to 10.0% were randomized into 24-week treatment groups with exenatide twice a day plus glargine or with aspart 70/30 twice a day. RESULTS: After 24 weeks, the patients receiving exenatide plus glargine (n = 90) had improved HbA1c control compared with those receiving aspart 70/30 (n = 90) (least squares mean change: ‒0.59 vs ‒0.13%; difference [95% CI]: ‒0.45 [‒0.74 to ‒0.17]) in the full analysis set population. Weight decreased 3.5 kg with exenatide and decreased 0.4 kg with aspart 70/30 (P < .001). The insulin dose was reduced 10.7 units/day (95% CI, ‒12.2 to ‒9.2 units; P < .001) with exenatide, and increased 9.7 units/day (95% CI, 8.2 to 11.2 units; P < .001) with aspart 70/30. The most common adverse events were gastrointestinal adverse effects in the exenatide group (nausea [21%], vomiting [16%], diarrhea [13%]). The incidence of hypoglycemia was similar in 2 groups (27% for exenatide and 38% for aspart 70/30; P = .1). CONCLUSION: In premixed human insulin‒treated patients with type 2 diabetes with inadequate glycemic control, switching to exenatide twice a day plus glargine was superior to aspart 70/30 twice a day for glycemic and weight control.

Multi-Level and Multi-Scale Feature Aggregation Network for Semantic Segmentation in Vehicle-Mounted Scenes.

The main challenges of semantic segmentation in vehicle-mounted scenes are object scale variation and trading off model accuracy and efficiency. Lightweight backbone networks for semantic segmentation usually extract single-scale features layer-by-layer only by using a fixed receptive field. Most modern real-time semantic segmentation networks heavily compromise spatial details when encoding semantics, and sacrifice accuracy for speed. Many improving strategies adopt dilated convolution and add a sub-network, in which either intensive computation or redundant parameters are brought. We propose a multi-level and multi-scale feature aggregation network (MMFANet). A spatial pyramid module is designed by cascading dilated convolutions with different receptive fields to extract multi-scale features layer-by-layer. Subseqently, a lightweight backbone network is built by reducing the feature channel capacity of the module. To improve the accuracy of our network, we design two additional modules to separately capture spatial details and high-level semantics from the backbone network without significantly increasing the computation cost. Comprehensive experimental results show that our model achieves 79.3% MIoU on the Cityscapes test dataset at a speed of 58.5 FPS, and it is more accurate than SwiftNet (75.5% MIoU). Furthermore, the number of parameters of our model is at least 53.38% less than that of other state-of-the-art models.

Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System.

6G vehicle-to-everything (V2X) communication will be combined with vehicle automatic driving technology and play an important role in automatic driving. However, in 6G V2X systems, vehicle users have the characteristics of high-speed movement. Therefore, how to provide stable and reliable wireless link quality and improve channel gain has become a problem that must be solved. To solve this problem, a new multi-user scheduling algorithm based on block diagonalization (BD) precoding for 6G ultra-massive multiple-input multiple-output (MIMO) systems is proposed in this paper. The algorithm takes advantage of the sensitive nature of BD precoding to channel correlation, uses the Pearson coefficient after matrix vectorization to measure the channel correlation between users, defines the scheduling factor to measure the channel quality according to the user noise enhancement factor, and jointly considers the influence of the correlation between user channels and channel quality, ensuring the selection of high-quality channels while minimizing channel correlation. Simulation results show that compared with the multi-user scheduling algorithm based on subspace correlation, condition number, and geometric angle, the proposed algorithm can obtain higher user channel gain, effectively reduce the system bit error rate, and can be applied to 6G V2X communication.

Aberrant Kank1 expression regulates YAP to promote apoptosis and inhibit proliferation in OSCC.

The kidney ankyrin repeat-containing protein 1 (Kank1) gene is one of the most important members of the KANK family. Kank1 has hybridity deletion and promoter methylation in the cancer tissues of the brain, lung, kidney and the corresponding cell lines, leading to downregulation of the gene expression. Meanwhile, Kank1 also plays a key role in the occurrence and development of various types of tumors, suggesting that Kank1 may be an anti-oncogene. However, its role and the potential mechanisms in the Oral Squamous Cell Carcinoma (OSCC) remain unclear. We examined the expression of Kank1 in OSCC tissues and explored its clinical significance. In addition, we investigated the effects of Kank1 on the biological behavior of OSCC cells and their specific molecular mechanisms. We found that Kank1 was poorly expressed in OSCC tissues and it is correlated with the OSCC stage and the patient's poor prognosis. By overexpression of Kank1, we found that the proliferation ability of the OSCC cells decreased both in vitro and in vivo, the proportion of apoptotic cells increased, and the mitochondrial transmembrane potential decreased. In terms of the molecular mechanism, we confirmed that Kank1 could inhibit the occurrence of OSCC by regulating Yap to inhibit the proliferation and promote apoptosis of the OSCC cells. Moreover, it was found that the overexpression of YAP reversed those effects caused by Kank1 overexpression on the OSCC cells. In conclusion, the research indicated that Kank1 might play an anti-oncogenic role in OSCC and it could be considered to be a target for the diagnosis and the treatment of OSCC.