Comprehensive analysis of the immune implication of EPHX4 gene in laryngeal squamous cell carcinoma.

OBJECTIVES: The role of Epoxide Hydrolase-4 (EPHX4), a member of epoxide hydrolase family, has not been investigated in cancer. The purpose of this article is to explore the application value of EPHX4 in laryngeal cancer and its relationship with immune infiltration. METHODS: We observed that EPHX4 expression and its survival assays in laryngeal cancer specimens based on The Cancer Genome Atlas (TCGA) cohorts. We also analyzed the correlation between immune cell infiltration levels and EPHX4 gene copy number in laryngeal cancer. Finally, we conducted in vitro assay to evaluate the functions of EPHX4 in laryngeal cancer cell line. RESULTS: EPHX4 is highly expressed in laryngeal cancer specimens and has a poor prognosis. EPHX4 related immune cell analysis showed that it participated in NK Natural killer cell mediated cytotoxicity. Finally, Cell experiments indicate that EPHX4 could promote laryngeal cancer cell line proliferation, colony formation and invasion. CONCLUSIONS: Our research results suggest that EPHX4 may be a potential immunotherapy target for laryngeal cancer. The nominated immune signature is a helpful and promising prognostic indicator in laryngeal cancer. LEVELS OF EVIDENCE: Level 3.

Effect of Asymmetry on the Contact Time of Droplet Impact on Superhydrophobic Cylindrical Surfaces.

Reducing the contact time during the droplet impact on the surface is crucial for anti-icing, self-cleaning, and heat transfer optimization applications. This study aims to minimize the contact time by modifying the surface curvature to create an asymmetric impact process. Our experiments showed that the increase in Weber numbers (We) and the decrease in the ratio of surface diameter to droplet diameter (D*) intensify the asymmetry of the impact process, yielding four distinct rebound modes. Low asymmetry observes the liquid retract toward the central point (Rebound Modes 1 and 2), whereas high asymmetry yields a wing-like rebound (Rebound Modes 3 and 4). In Rebound Mode 1, increased asymmetry would lead to more extended contact due to the prolonged waiting period. Conversely, the reduction in contact time in Rebound Mode 2 occurs due to increased asymmetry with no waiting period. For Rebound Modes 3 and 4, the retraction time could be divided into three stages, generated by two liquid detachment modes from the surface. Analysis reveals that an increased asymmetry would reduce the retraction time during the first stage but prolong it during the third stage, with no significant effects on the second. Four correlations, each pertaining to a distinct impact mode, are proposed based on these analyses to describe the contact time concerning We and D* for droplets impacting a superhydrophobic cylindrical surface.

LORF9 of Marek's disease virus is involved in the early cytolytic replication of B lymphocytes and can act as a target for gene deletion vaccine development.

IMPORTANCE: Marek's disease virus (MDV) is a highly infectious and oncogenic virus that can induce severe T cell lymphomas in chickens. MDV encodes more than 100 genes, most of which have unknown functions. This work indicated that the LORF9 gene is necessary for MDV early cytolytic replication in B lymphocytes. In addition, we have found that the LORF9 deletion mutant has a comparative immunological protective effect with CVI988/Rispens vaccine strain against very virulent MDV challenge. This is a significant discovery that LORF9 can be exploited as a possible target for the development of an MDV gene deletion vaccine.

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau.

Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Establishment and characterization of a novel indirect ELISA method based on ASFV antigenic epitope-associated recombinant protein.

African Swine Fever (ASF) is an acute and highly lethal disease in pigs caused by African Swine Fever Virus (ASFV). Viral proteins have been commonly used as antigenic targets for the development of ASF diagnostic methods. However, the prokaryotic expression of viral proteins has deficiencies such as instability, insolubility, and high cost in eukaryotic situations. This study screened and verified ASFV-encoded p72, p54, and p30 protein antigenic epitopes. Subsequently, a novel antigenic epitope-associated recombinant protein was designed based on an ideal structural protein and expressed in Escherichia coli (E. coli). Western blot analysis indicated that the recombinant protein could specifically react with the monoclonal antibody (mAb) of p72 and polyclonal antibodies of p54 and p30, respectively. Next, an ASF indirect ELISA (iELISA) method was established based on the recombinant protein, which has no specific reaction with sera of other important pig viral diseases. Meanwhile, it shows a sensitivity to detecting dilutions of ASF-positive reference serum up to 1:6400. The clinical sample detection results showed a high coincidence rate of 98 % with a commercial competition ELISA kit. In conclusion, we established a novel specific, and sensitive ASF serologic detection method that opens new avenues for ASF serodiagnostic method development.

Research Progress of Nanomaterials in Chemotherapy of Osteosarcoma.

Osteosarcoma (OS) is a common malignant bone tumor that occurs mostly in children and adolescents. At present, surgery after chemotherapy or postoperative adjuvant chemotherapy is the main treatment plan. However, the efficacy of chemotherapeutic drugs is limited by the occurrence of chemotherapeutic resistance, toxicity to normal cells, poor pharmacokinetic performance, and drug delivery failure. The delivery of chemotherapy drugs to the bone to treat OS may fail for a variety of reasons, such as a lack of selectivity for OS cells, initial sudden release, short-term release, and the presence of biological barriers (such as the blood-bone marrow barrier). Nanomaterials are new materials with at least one dimension on the nanometer scale (1-100 nm) in three-dimensional space. These materials have the ability to penetrate biological barriers and can accumulate preferentially in tumor cells. Studies have shown that the effective combination of nanomaterials and traditional chemotherapy can significantly improve the therapeutic effect. Therefore, this article reviews the latest research progress on the use of nanomaterials in OS chemotherapy.

An Intracellular Epitope of ASFV CD2v Protein Elicits Humoral and Cellular Immune Responses.

The African swine fever virus (ASFV) causes high mortality in domestic pigs. ASFV encodes an important protein target for subunit vaccine development, CD2v, but its most effective immunological regions are not known. Herein, we generated a monoclonal antibody (mAb) named IF3 by immunizing mice against the intracellular region of the CD2v protein (CD2v-IR). 1F3 specifically recognized CD2v, which is expressed transiently in transfected Sf9 cells and also in inactivated ASFV-infected porcine alveolar macrophage (PAM) cells. The epitope recognized by 1F3 is 264EPSPREP270, which is highly conserved in ASFV genotypes. Immunization of mice with this epitope elicited an increased IgG response, including IgG1 and IgG2a subtypes, and also increased CD8+ T cells and cytokine expression. Overall, these results indicate that this epitope induces both humoral and cellular immune responses that may be used for ASFV-related subunit vaccine design and development.

Effect of Natural Aging on Cold Forming Performance of 2219 Aluminum Alloy.

To facilitate the manufacturing of the thin-walled components of 2219 aluminum alloy, the quenching-forming-aging (Q-F-A) process has been increasingly utilized. However, natural aging (NA) after quenching significantly affects the cold forming performance of this alloy. In this study, experiments are conducted to investigate the effect of NA time on the cold forming performance of 2219 aluminum alloy. The results indicate that NA can weaken the Portevin-Le Chatelier (PLC) effect, thereby reducing its influence on the cold forming performance of the alloy. The PLC effect becomes indistinct when the aging time reaches 2 years. The yield strength of 2219 aluminum alloy increases monotonically with aging time, while the elongation first increases rapidly and then decreases. After an aging time of 2 years, the yield strength increases by 28.6% from that of newly quenched alloys. The strain hardening index and hardening coefficient indicate that short-term NA (less than 4 days) increases the work hardening rate, while long-term NA reduces it. Microstructural analysis shows that the strengthening effect of NA on 2219 aluminum alloy is mainly due to the growth of G.P. zones and the precipitation of θ″ phases. The NA precipitation behavior can also cause the aggregation of solute atoms and weaken the PLC effect.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests.

Introduction: Conductance-photosynthesis (Gs-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (Gs) and transpiration (Tc) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (gsu and gsh) and maximum LUE (ϵmsu and ϵmsh) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in Tc estimation errors, as it contradicts field observations. Methods: In this study, the measured flux data from three temperate deciduous broadleaved forests (DBF) FLUXNET sites were adopted, and the key parameters of LUE and Ball-Berry models for sunlit and shaded leaves were calibrated within the entire growing season and each season, respectively. Then, the estimations of gross primary production (GPP) and Tc were compared between the two schemes of parameterization: (1) entire growing season-based fixed parameters (EGS) and (2) season-specific dynamic parameters (SEA). Results: Our results show a cyclical variability of ϵmsu across the sites, with the highest value during the summer and the lowest during the spring. A similar pattern was found for gsu and gsh, which showed a decrease in summer and a slight increase in both spring and autumn. Furthermore, the SEA model (i.e., the dynamic parameterization) better simulated GPP, with a reduction in root mean square error (RMSE) of about 8.0 ± 1.1% and an improvement in correlation coefficient (r) of 3.7 ± 1.5%, relative to the EGS model. Meanwhile, the SEA scheme reduced Tc simulation errors in terms of RMSE by 3.7 ± 4.4%. Discussion: These findings provide a greater understanding of the seasonality of plant functional traits, and help to improve simulations of seasonal carbon and water fluxes in temperate forests.

Climate change unequally affects nitrogen use and losses in global croplands.

Maintaining food production while reducing agricultural nitrogen pollution is a grand challenge under global climate change. Yet, the response of global agricultural nitrogen uses and losses to climate change on the temporal and spatial scales has not been fully characterized. Here, using historical data for 1961-2018 from over 150 countries, we show that global warming leads to small temporal but substantial spatial impacts on cropland nitrogen use and losses. Yield and nitrogen use efficiency increase in 29% and 56% of countries, respectively, whereas they reduce in the remaining countries compared with the situation without global warming in 2018. Precipitation and farm size changes would further intensify the spatial variations of nitrogen use and losses globally, but managing farm size could increase the global cropland nitrogen use efficiency to over 70% by 2100. Our results reveal the importance of reducing global inequalities of agricultural nitrogen use and losses to sustain global agriculture production and reduce agricultural pollution.

Research Progress of Long Non-coding RNAs in Spinal Cord Injury.

Spinal cord injury (SCI) can result in a partial or complete loss of motor and sensory function below the injured segment, which has a significant impact on patients' quality of life and places a significant social burden on them. Long non-coding RNA (LncRNA) is a 200-1000 bp non-coding RNA that has been shown to have a key regulatory role in the progression of a variety of neurological illnesses. Many studies have demonstrated that differentially expressed LncRNAs following spinal cord injury can participate in inflammatory damage, apoptosis, and nerve healing by functioning as competitive endogenous RNA (ceRNA); at the same time, it has a significant regulatory effect on sequelae such neuropathic pain. As a result, we believe that LncRNAs could be useful as a molecular regulatory target in the diagnosis, treatment, and prognosis of spinal cord injury.

A New Technique of Achilles Tendon Rupture Repaired by Double Transverse Mini-incision to Avoid Sural Nerve Injury: A Consecutive Retrospective Study.

OBJECTIVE: Percutaneous suture is a classic technique used in Achilles tendon repair. However, the complication rates surrounding the sural nerve remain relatively high. Modified percutaneous repair technology can effectively avoid these complications; however, the surgical procedure is complicated. Hence, the present study was conducted to describe a redesigned repair technique for the Achilles tendon able to avoid sural nerve injury and reduce the complexity of the procedure. METHODS: Data of patients with acute primary Achilles tendon rupture at our hospital from January 2019 to May 2020 were included. Subjects with expectations for surgical scarring underwent a minimally invasive-combined percutaneous puncture technique. The surgical time, requirement for conversion to other technologies, and length of postoperative hospitalization were investigated to assess efficacy. The American Orthopedic Foot & Ankle Society (AOFAS) score and the Arner-Lindholm scale (A-L scale) were used to assess postoperative clinical outcomes (> 24 months). During the 2-year follow-up, MRI was performed to observe the healing of the Achilles tendon. In addition, subjective satisfaction with surgical scar healing was recorded. RESULTS: Twenty consecutive subjects with an average follow-up of 28.3 ± 4.5 months (range, 24-41) met the inclusion criteria. None of the 20 enrolled patients required a converted surgical approach. The mean surgical time was 26.9 ± 6.47 min (range, 20-44). None of the patients experienced dysesthesia or anesthesia around the sural nerve. No signs of postoperative infections were observed. MRI data showed that the wounds of the Achilles tendon healed completely in all the subjects. The AOFAS score increased from 55.6 ± 11.07 (range, 28-71) preoperatively to 97.8 ± 3.34 (range, 87-100) at the last follow-up. The A-L scale showed that 90% of the subjects (n = 18) presented as excellent and 10% of the subjects (n = 2) presented as good, with an excellent/good rate of 100%. Moreover, subjects' satisfaction for surgical scars was 9.1 ± 0.78 (upper limit, 10). CONCLUSIONS: The results indicate that this technique can achieve good postoperative function, a small surgical incision, and high scar satisfaction. In addition, this technique should be widely used in suturing Achilles tendon ruptures.

Infection phase-dependent dynamics of the viral and host N6-methyladenosine epitranscriptome in the lifecycle of an oncogenic virus in vivo.

Dynamic alteration of the epitranscriptome exerts regulatory effects on the lifecycle of oncogenic viruses in vitro. However, little is known about these effects in vivo because of the general lack of suitable animal infection models of these viruses. Using a model of rapid-onset Marek's disease lymphoma in chickens, we investigated changes in viral and host messenger RNA (mRNA) N6-methyladenosine (m6 A) modification during Marek's disease virus (MDV) infection in vivo. We found that the expression of major epitranscriptomic proteins varies among viral infection phases, reprogramming both the viral and the host epitranscriptomes. Specifically, the methyltransferase-like 3 (METTL3)/14 complex was suppressed during the lytic and reactivation phases of the MDV lifecycle, whereas its expression was increased during the latent phase and in MDV-induced tumors. METTL3/14 overexpression inhibits, whereas METTL3/14 knockdown enhances, MDV gene expression and replication. These findings reveal the dynamic features of the mRNA m6 A modification program during viral replication in vivo, especially in relation to key pathways involved in tumorigenesis.

Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications.

Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant-climate interactions. The correct representation of vegetation phenology is important for models to accurately simulate the exchange of carbon, water, and energy between the vegetated land surface and the atmosphere. Remote sensing has advanced the monitoring of vegetation phenology by providing spatially and temporally continuous data that together with conventional ground observations offers a unique contribution to our knowledge about the environmental impact on ecosystems as well as the ecological adaptations and feedback to global climate change. Land surface phenology (LSP) is defined as the use of satellites to monitor seasonal dynamics in vegetated land surfaces and to estimate phenological transition dates. LSP, as an interdisciplinary subject among remote sensing, ecology, and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, here we summarize the recent advances in LSP and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of the global LSP research field.

Applying machine learning to construct braking emission model for real-world road driving.

Brake emissions from vehicles are increasing as the number of vehicles increases. However, current research on brake emissions, particularly the intensity and characteristics of emissions under real road conditions, is significantly inadequate compared to exhaust emissions. To this end, a dataset of 600 (200 unique real-world braking events simulated using three types of brake pads) real-world braking events (called brake pad segments) was constructed and a mapping function between the average brake emission intensity of PM2.5 from the segments and the segment features was established by five algorithms (multiple linear regression (MLR) and four machine learning algorithms). Based on the five algorithms, the importance of the different features of the fragments was discussed and brake energy intensity (BEI) and metal content (MC) of the brake pad emissions were identified as the most significant factors affecting brake emissions and used as the final modeling features. Among the five algorithms, categorical boosting (CatBoost) had the best prediction performance, with a mean R2 and RMSE of 0.83 and 0.039 respectively for the tenfold cross-validation. In addition, the CatBoost-based model was further compared with the MOVES model to demonstrate its applicability. The CatBoost-based model has better prediction performance than the MOVES model. The MOVES model overpredicts brake fragment emissions for urban roads and underpredicts brake fragment emissions for motorways. Furthermore, the CatBoost-based model was interpreted and visualized by an individual conditional expectation (ICE) plot to break the machine learning "black box", with BEI and MC showing nonlinear monotonic increasing relationships with braking emissions. ICE plot also provides viable technical solutions for controlling brake emissions in the future. Both avoiding aggressive braking driving behavior (e.g., the application of smart transportation technologies) and using brake pads with less metal content (e.g., using ceramic brake pads) can effectively reduce brake emissions. The construction of a machine learning-based brake emission model and the white-boxing of its model provide excellent insights for the future detailed assessment and control of brake emissions.

Quantifying the influences of climate change and human activities on the grassland in the Southwest Transboundary Basin, China.

The Southwest Transboundary Basin (STB), which contains a part of the Tibetan Plateau and Southwest China, covers a large area of grassland that has been experiencing significant climate change (Cc) and human activities (Ha). However, variabilities of the grasslands and respective contributions of the drivers have not been fully understood. In this study, we quantitatively investigated the influences of Cc and Ha on the grasslands from 1982 to 2015 across the STB, using residual analysis, trend analysis, and partial correlation analysis. Particularly, vapor pressure deficit (VPD), which is increasingly paid attention to in current studies, was included in our analysis as a critical driver of alpine grasslands. Additionally, a new method, pure climate-induced grassland pixel, which combined the coefficient of variation, was proposed to significantly improve the pixel purity with higher coefficient correlation and lower error and bias. Results show that changes in the climate play an important role in the grassland coverage of STB during 1982-1999 and 2000-2015, while Ha only had a relatively weak negative impact on grassland during 2000-2015, mainly in the Lancang River Basin. Specifically, the grasslands showed an increasing trend in 1982-1999, dominated by climate change with a contribution rate of 80.87%. Temperature had the greatest contribution, followed by VPD and precipitation in this period. On the contrary, the grasslands showed a decreasing trend in 2000-2015, dominated by both Cc and Ha with the contributions of 53.16% and 46.84%, respectively. The findings of this study provide a valuable reference for future ecological restoration in other similar alpine regions.

Deletion of miR-M8 and miR-M13 eliminates the bursa atrophy induced by Marek's disease virus infection.

Marek's disease (MD) is a neoplastic disease of chickens caused by an avian alphaherpesvirus, Marek's disease virus (MDV, also known as Gallid alphaherpesvirus 2 [GaHV2]). A total of 14 microRNA (miRNA) precursors and 26 mature miRNAs have been identified in MDV genome, which were grouped in three distinct clusters. In recent years, our studies revealed the role of MDV encoded cluster 3 miRNAs (or miR-M8-M10) and the specific function of its three members, miR-M6, miR-M7 and miR-M10, in regulating MDV replication and pathogenesis. In this study, we characterized the unique function of the other two members, miR-M8 and miR-M13, in cluster 3 miRNAs. Our results show that miR-M8 and miR-M13 are not important for MDV plaque formation and genome replication in vitro. Animal experiment results show that deletion of miR-M8-5p and miR-M13-5p eliminates the bursa atrophy, but not thymus atrophy, of MDV inoculated chickens. In addition, we found that the survival curve and MD incidences were not affected by disruption of miR-M8 and miR-M13. Taken together, this study uncovers the unique role of miR-M8 and miR-M13 in MDV replication and pathogenesis, which filled the gap in the research of MDV encoded miRNAs.

Molecular Epidemiology and Pathogenic Characterization of Novel Chicken Infectious Anemia Viruses in Henan Province of China.

Chicken infectious anemia (CIA) is an immunosuppressive disease caused by the chicken infectious anemia virus (CIAV) resulting in heavy economic losses once an outbreak is established. This study conducted a systematic analysis of the epidemiology and pathology of CIA in Henan province, China. A total of 437 clinical tissue samples and 120 poultry disease-related live attenuated vaccines were collected during 2017-2020; of which 45 were positive for CIAV nucleic acid, with a positive rate of 8.08%. Our results showed that genome sequence similarity among a total of 12 CIAV isolates was high, and ranged from 97.1 to 99.3%, and their similarity to the vaccine strains Cux-1 and Del-Ros ranged from 97.8 to 98.6%. However, There were mutations in the locus of the major capsid proteins VP1, VP2, and VP3 among all isolates. The subsequent sequence analysis indicated that the isolates of HN-4 and HN-8 showed genetic recombination and follow up animal experiments revealed that HN-4 might be a pathogenic strain. Our results reveal that both field infection and non-CIAV vaccines contamination promote the epidemiology of CIAV in China and some dominant epidemic viruses have undergone recombination and evolution. This study provides important information to help with the prevention and control of CIAV in the poultry industry.

Non-Coding RNA Regulatory Network in Ischemic Stroke.

Stroke is a worldwide public health problem that has caused a substantial economic burden to families and society. Despite recent major advances, there is still a need for more timely, effective diagnosis and treatment methods for acute ischemic stroke. Non-coding RNAs (ncRNAs), which widely exist in the human body, do not encode proteins. Instead, these mediate various cellular processes as functional regulatory molecules from the RNA level. Each ncRNA node in organisms is not isolated but constitutes a complex regulatory network, regulating multiple molecular targets and triggering specific physiological or pathological reactions, leading to different outcomes. Abundant studies have proclaimed the impact of ncRNAs in ischemic stroke, which may enlighten new inspirations for diagnosing and treating ischemic stroke. This paper outlines the current understanding of the ncRNA regulatory network and reviews the recent evidence for the contribution of ncRNAs in the experimental ischemic stroke model.

Super-learner model realizes the transient prediction of CO2 and NOx of diesel trucks: Model development, evaluation and interpretation.

The transient simulation of CO2 and NOX from motor vehicles has essential applications in evaluating vehicular greenhouse gas emissions and pollutant emissions. However, accurately estimating vehicular transient emissions is challenging due to the heterogeneity between different vehicles and the continuous upgrading of vehicle exhaust purification technology. To accurately characterize the transient emissions of motor vehicles, a Super-learner model is used to build CO2 and NOx transient emission models. The actual onboard test data of 9 China VI N2 vehicles were used to train the model, and the test data of another China VI N2 vehicle were selected for further robustness verification. There were significant differences in the emissions between the vehicles, but the constructed transient model could capture the common law of transient emissions from China VI N2 vehicles. The R2 values of CO2 and NOx emission in the test data of the validation vehicle were 0.71 and 0.82, respectively. In addition, to further prove the model's robustness, the training data were synchronously modelled based on the Moves-method. The Super-learner model has a smaller RMSE on the validation set than the model based on the Moves-method, indicating that the Super-learner model has more transient simulation advantages. The marginal contributions of the model characteristics to the model results were analysed by SHapley Additive exPlanation (SHAP) value interpretation, and the marginal contributions of different pollutant characteristic parameters varied. Therefore, when establishing transient models of different pollutants, the selection of the model parameters demands considering the generation and purification process of different pollutants. The present work provides novel insights into the parameter selection, construction, and interpretation of the transient vehicle emission model.