[Analysis of rare mutations associated with Thalassemia and their hematological characteristics in Chenzhou region of Hunan Province].

OBJECTIVE: To explore the distribution and hematological characteristics of rare thalassemia-associated mutations in Chenzhou region of Hunan Province with an aim to provide a basis for genetic counseling and effective prevention. METHODS: A total of 37 370 individuals enrolled from January 2015 to December 2021 were screened by routine blood test and hemoglobin electrophoresis. The genotypes were determined with high-throughput sequencing. RESULTS: A total of 8 455 thalassemia mutations (including 185 rare ones) were detected, which had involved 27 mutational types. Rare type α-Thalassemia --THAI and CD31 (AGG>AAG) have the typical microcytic hypochromic hematological features, whilst SEA-HPFH, CD14 (CTG>-TG), CD37 (TGG>TAG), -90(C>T), Codon 15 (G>A), IVS-I-128 (T>G), CD86 (GCC>GC-) and Chinese Gγ+(Aγδß)0 had typical microcytic hypochromic and ß-thalassemia-associated hematological features of elevated HbA2 or HbF. In addition, the -50（G>A）heterozygotes of ß-thalassemia had normal or slightly decreased MCV and MCH without an increase in HbA2. CONCLUSION: Various forms of thalassemia-associated mutations have been identified in the Chenzhou region of Hunan Province. Above finding has facilitated development of preventive and control strategies for thalassemia as well as birth health programs.

Ischemia and reperfusion-injured liver-derived exosomes elicit acute lung injury through miR-122-5p regulated alveolar macrophage polarization.

Acute lung injury (ALI) is a common postoperative complication, particularly in pediatric patients after liver transplantation. Hepatic ischemia-reperfusion (HIR) increases the release of exosomes (IR-Exos) in peripheral circulation. However, the role of IR-Exos in the pathogenesis of ALI induced by HIR remains unclear. Here, we explored the role of exosomes derived from the HIR-injured liver in ALI development. Intravenous injection of IR-Exos caused lung inflammation in naive rats, whereas pretreatment with an inhibitor of exosomal secretion (GW4869) attenuated HIR-related lung injury. In vivo and in vitro results show that IR-Exos promoted proinflammatory responses and M1 macrophage polarization. Furthermore, miRNA profiling of serum identified miR-122-5p as the exosomal miRNA with the highest increase in young rats with HIR compared with controls. Additionally, IR-Exos transferred miR-122-5p to macrophages and promoted proinflammatory responses and M1 phenotype polarization by targeting suppressor of cytokine signaling protein 1(SOCS-1)/nuclear factor (NF)-κB. Importantly, the pathological role of exosomal miR-122-5p in initiating lung inflammation was reversed by inhibition of miR-122-5p. Clinically, high levels of miR-122-5p were found in serum and correlated to the severity of lung injury in pediatric living-donor liver transplant recipients with ALI. Taken together, our findings reveal that IR-Exos transfer liver-specific miR-122-5p to alveolar macrophages and elicit ALI by inducing M1 macrophage polarization via the SOCS-1/NF-κB signaling pathway.

Single-cell analysis reveals the immune heterogeneity and interactions in lungs undergoing hepatic ischemia-reperfusion.

Hepatic ischemia-reperfusion IR (HIR) is an unavoidable pathophysiological process during liver transplantation, resulting in systematic sterile inflammation and remote organ injury. Acute lung injury (ALI) is a serious complication after liver transplantation with high postoperative morbidity and mortality. However, the underlying mechanism is still unclear. To assess the phenotype and plasticity of various cell types in the lung tissue microenvironment after HIR at the single-cell level, single-cell RNA sequencing (scRNA-seq) was performed using the lungs from HIR-induced mice. In our results, we identified 23 cell types in the lungs after HIR and found that this highly complex ecosystem was formed by subpopulations of bone marrow-derived cells that signaled each other and mediated inflammatory responses in different states and different intervals. We described the unique transcriptional profiles of lung cell clusters and discovered two novel cell subtypes (Tspo+Endothelial cells and Vcan+ monocytes), as well as the endothelial cell-immune cell and immune cell-T cell clusters interactome. In addition, we found that S100 calcium binding protein (S100a8/a9), specifically and highly expressed in immune cell clusters of lung tissues and exhibited detrimental effects. Finally, the cellular landscape of the lung tissues after HIR was established, highlighting the heterogeneity and cellular interactions between major immune cells in HIR-induced lungs. Our findings provided new insights into the mechanisms of HIR-induced ALI and offered potential therapeutic target to prevent ALI after liver transplantation.

Caspase 6/NR4A1/SOX9 signaling axis regulates hepatic inflammation and pyroptosis in ischemia-stressed fatty liver.

The mechanism of nonalcoholic fatty liver susceptibility to ischemia/reperfusion (IR) injury has not been fully clarified. Caspase 6 is a critical regulator in innate immunity and host defense. We aimed to characterize the specific role of Caspase 6 in IR-induced inflammatory responses in fatty livers. Human fatty liver samples were harvested from patients undergoing ischemia-related hepatectomy to evaluate Caspase 6 expression. in mice model, we generated Caspase 6-knockout (Caspase 6KO) mice to investigate cellular and molecular mechanisms of macrophage Caspase 6 in IR-stimulated fatty livers. In human liver biopsies, Caspase 6 expression was upregulated combined with enhanced serum ALT level and severe histopathological injury in ischemic fatty livers. Moreover, Caspase 6 was mainly accumulated in macrophages but not hepatocytes. Unlike in controls, the Caspase 6-deficiency attenuated liver damage and inflammation activation. Activation of macrophage NR4A1 or SOX9 in Caspase 6-deficient livers aggravated liver inflammation. Mechanistically, macrophage NR4A1 co-localized with SOX9 in the nuclear under inflammatory conditions. Specifically, SOX9 acts as a coactivator of NR4A1 to directly target S100A9 transcription. Furthermore, macrophage S100A9 ablation dampened NEK7/NLRP3-driven inflammatory response and pyroptosis in macrophages. In conclusion, our findings identify a novel role of Caspase 6 in regulating NR4A1/SOX9 interaction in response to IR-stimulated fatty liver inflammation, and provide potential therapeutic targets for the prevention of fatty liver IR injury.

Rapid and Visual Detection of Porcine Parvovirus Using an ERA-CRISPR/Cas12a System Combined With Lateral Flow Dipstick Assay.

Porcine parvovirus (PPV) is one of the important causes of pig reproductive diseases. The most prevalent methods for PPV authentication are the polymerase chain reaction (PCR), enzyme-linked immunosorbent assay, and quantitative real-time PCR. However, these procedures have downsides, such as the fact that they take a long time and require expensive equipment. As a result, a rapid, visible, and economical clinical diagnostic strategy to detect PPV is necessary. In this study, three pairs of crRNA primers were designed to recognize the VP2 gene, and an ERA-CRISPR/Cas12a system for PPV detection was successfully developed. The approach involved isothermal detection at 37°C, and the method can be used for visual inspection. The detection limit of the ERA-CRISPR/Cas12a system was 3.75 × 102 copies/µL, and no cross reactions with other porcine viruses were found. In view of the preceding, a rapid, visible, and low-cost nucleic acid testing approach for PPV has been developed using the ERA-CRISPR/Cas12a system.

Study on the Classification Method of Rice Leaf Blast Levels Based on Fusion Features and Adaptive-Weight Immune Particle Swarm Optimization Extreme Learning Machine Algorithm.

Leaf blast is a disease of rice leaves caused by the Pyricularia oryzae. It is considered a significant disease is affecting rice yield and quality and causing economic losses to food worldwide. Early detection of rice leaf blast is essential for early intervention and limiting the spread of the disease. To quickly and non-destructively classify rice leaf blast levels for accurate leaf blast detection and timely control. This study used hyperspectral imaging technology to obtain hyperspectral image data of rice leaves. The descending dimension methods got rice leaf disease characteristics of different disease classes, and the disease characteristics obtained by screening were used as model inputs to construct a model for early detection of leaf blast disease. First, three methods, ElasticNet, principal component analysis loadings (PCA loadings), and successive projections algorithm (SPA), were used to select the wavelengths of spectral features associated with leaf blast, respectively. Next, the texture features of the images were extracted using a gray level co-occurrence matrix (GLCM), and the texture features with high correlation were screened by the Pearson correlation analysis. Finally, an adaptive-weight immune particle swarm optimization extreme learning machine (AIPSO-ELM) based disease level classification method is proposed to further improve the model classification accuracy. It was also compared and analyzed with a support vector machine (SVM) and extreme learning machine (ELM). The results show that the disease level classification model constructed using a combination of spectral characteristic wavelengths and texture features is significantly better than a single disease feature in terms of classification accuracy. Among them, the model built with ElasticNet + TFs has the highest classification accuracy, with OA and Kappa greater than 90 and 87%, respectively. Meanwhile, the AIPSO-ELM proposed in this study has higher classification accuracy for leaf blast level classification than SVM and ELM classification models. In particular, the AIPSO-ELM model constructed with ElasticNet+TFs as features obtained the best classification performance, with OA and Kappa of 97.62 and 96.82%, respectively. In summary, the combination of spectral characteristic wavelength and texture features can significantly improve disease classification accuracy. At the same time, the AIPSO-ELM classification model proposed in this study has sure accuracy and stability, which can provide a reference for rice leaf blast disease detection.

Epidemiology and Evolution of Emerging Porcine Circovirus-like Viruses in Pigs with Hemorrhagic Dysentery and Diarrhea Symptoms in Central China from 2018 to 2021.

Porcine circovirus-like virus (PCLV) is a type of circular Rep-encoding single-stranded DNA virus and may be associated with the development of diarrheal symptoms in pigs. In this study, we retrospectively analyzed three years of past cases in Anhui, China, and reported a case of hemorrhagic enteritis and death in a pregnant sow possibly caused by PCLV. In addition, we analyzed the evolutionary characteristics of PCLV and found that mutation, recombination and selective pressure all played an important role in the evolution of PCLV. We identified N15D and T17S as well as L56T, T58R, K59Q, M62R, L75I and R190K mutations in two different branches, and we noted recombination events in the Rep of a group of Chinese strains. Analysis of selection pressure revealed that PCLV gained more positive selection, indicating that the virus is in a continuous evolutionary state. The PR2 plot, ENC-plot and neutrality analysis showed a greater role of natural selection than that of mutational pressure in the formation of codon usage patterns. This study is the first to identify PCLV in sows with hemorrhagic dysentery and death, and it provides new epidemiological information on PCLV infection in pigs in China.

Association between Congenital Cytomegalovirus Infection and Brain Injury in Neonates: A Meta-analysis of Cohort Studies.

OBJECTIVE: To assess association between congenital cytomegalovirus (CMV) infection and brain injury in neonates. METHODS: The literatures from inception to November 4, 2020, were searched through PubMed, Embase, Cochrane Library, and Web of Science. Heterogeneity test was conducted for each indicator and measured by I 2 statistics. If I 2 ≥ 50%, the random effects model was applied; otherwise, the fixed effects model was used. Sensitivity analysis was performed for all models. Weighed mean difference (WMD) was used as the effect size for measurement data, and risk ratio (RR) was as the effect indicator. RESULTS: A total of 13 studies, including 4,262 congenital CMV infection neonates, were enrolled in this study. Our results showed that the rate of hearing impairment (RR: 2.105, 95% CI: (1.115, 3.971), P = 0.002), sensorineural hearing loss (SNHL) (RR: 17.051, 95% CI: (6.201, 46.886), P < 0.001), and microcephaly (RR: 2.283, 95% CI: (1.325, 3.935), P =0.003) in neonates infected congenital CMV was higher than that in control group. CONCLUSION: The risks of hearing impairment, SNHL, and microcephaly in neonates during childhood may be associated with congenital CMV infection. It is necessary to establish neonatal screening programs and comprehensive diagnostic tests for patients to reduce the risk of adverse brain damage to the congenital CMV infection as early as possible and to improve the prognosis of the newborn.

Enzymatic recombinase amplification coupled with CRISPR-Cas12a for ultrasensitive, rapid, and specific Porcine circovirus 3 detection.

Porcine circovirus type 3 (PCV3) is a disease associated with porcine dermatitis and nephrotic syndrome (PDNS) that has caused significant economic losses to swine herds since its discovery in 2016. To develop a simple, on-site, rapid, and sensitive assay to combat the spread of PCV3, we optimized the CRISPR/Cas12a (also known as Cpf1) system combined with enzymatic recombinase amplification (ERA) nucleic acid amplification to diagnose PCV3. The results showed that the ERA-CRISPR/Cas12a reaction could detect PCV3 within 1 h in genomic DNA harboring a minimum of seven copies. Additionally, we confirmed no cross-reactivity with PCV2, PCV4, or other porcine viruses, revealing the good specificity of this technique. These results demonstrated the ability of ERA-CRISPR/Cas12a to detect DNA at the single-molecule level and provide a rapid, simple, ultrasensitive, one-pot point-of-care test for PCV3 and suggest its potential for a variety of nucleic acid detection applications.

[Effects of organic manure partial substitution for chemical fertilizer on the photosynthetic rate, nitrogen use efficiency and yield of rice]. / æœ‰æœºè‚¥æ›¿ä»£éƒ¨åˆ†åŒ–è‚¥å¯¹æ°´ç¨»å ‰åˆé€ŸçŽ‡ã€æ°®ç´ åˆ©ç”¨çŽ‡å’Œäº§é‡çš„å½±å“.

Rational application of organic fertilizers is an effective approach to improve soil fertility, crop yield, and zero growth of chemical fertilizer in agricultural production. The rice variety 'Shennong9816' was planted in Shenyang, Liaoning Province, under seven different treatments: zero nitrogen fertilizer (CK), low nitrogen, 150 kg·hm-2(LN), medium nitrogen, 240 kg·hm-2 (MN), high nitrogen, 330 kg·hm-2(HN), medium nitrogen with replacement of chemical N by 10% organic manure (OMN10), medium nitrogen with replacement of chemical N by 20% organic manure (OMN20), and medium nitrogen with replacement of chemical N by 30% organic manure (OMN30). The effects of different treatments on photosynthetic rate, nitrogen absorption, nitrogen use efficiency, and yield were examined and the optimal fertilization scheme was determined. The results showed that the photosynthetic rate, biomass and yield were increased with the increases of nitrogen application rate, while the nitrogen use efficiency was decreased significantly. Compared with the MN treatment, the photosynthetic rate of OMN10 and OMN20 in filling stage was increased by 22.9% and 9.9%, respectively. The yield of OMN20 was increased by 3.8% compared to that of MN. The nitrogen agronomic efficiency and physiological efficiency of OMN20 were significantly improved by 8.1% and 13.3%, respectively. Moreover, the nitrogen agronomic efficiency and physiological efficiency of OMN20 were improved by 27.2% and 37.2% compared with the HN treatment. Thus, we concluded that the organic fertilizer replacement treatment could conserve soil fertility, achieve high yield and high nitrogen use efficiency, while reduce chemical nitrogen fertilizer application. The OMN20 treatment was recommended as a fertilizer application model due to its superior performance among the seven treatments.

Acrocentric Chromosome Polymorphic Variants on Chinese Female Have Possible Association with Unexplained Recurrent Pregnancy Loss.

Recurrent pregnancy loss (RPL) occurs frequently in Chinese patients, but the causes for 40-50% RPL remain unexplained. This study aims to explore possible association between recurrent pregnancy loss and chromosome polymorphism. We performed a retrospective cohort study including a total number of 2967 Chinese patients from January in 2013 to December in 2019.These participants were divided into two groups: group I (RPL group) and group II (control group). Group I included 1791 patients who underwent RPL. Group II included 1176 individuals who underwent primary infertility. Their chromosome karyotype analyses were performed by Giemsa banding protocol. Pearson chi-squared test and Fisher's exact test were employed to evaluate the difference in frequency of chromosomal polymorphic variations between both groups. Chromosomal polymorphism occurred more frequently in RPL group compared with control group, the differences for 9qh+, inv(9), and Yqh+ between both groups were (χ2 = 6.697, p = 0.01), (χ2 = 6.242, p = 0.012), and (χ2 = 4.587, p = 0.032), respectively. The most significant difference of chromosomal polymorphism karyotype between RPL group and control group was found for acrocentric chromosome (D/G group) variants (χ2 = 30.7, p < 0.001). Moreover, the difference in frequency of D/G group variants between women and men in RPL group was remarkably significant (χ2 = 55.3, p < 0.001), and furthermore, D/G group variants occurred more frequently among women in RPL group than women in control group (χ2 = 44.3, p < 0.001). We found that acrocentric chromosomal polymorphism occurred preferentially on Chinese women with RPL. The fascinating finding provides us novel insight into the potential association of higher frequency of acrocentric chromosomal variations on Chinese women with unexplained RPL.

A Study of Nitrogen Deficiency Inversion in Rice Leaves Based on the Hyperspectral Reflectance Differential.

To achieve rapid, accurate, and non-destructive diagnoses of nitrogen deficiency in cold land japonica rice, hyperspectral data were collected from field experiments to investigate the relationship between the nitrogen (N) content and the difference in the spectral reflectance relationship and to establish the hyperspectral reflectance difference inversion model of differences in the N content of rice. In this study, the hyperspectral reflectance difference was used to invert the nitrogen deficiency of rice and provide a method for the implementation of precision fertilization without reducing the yield of chemical fertilizer. For the purpose of constructing the standard N content and standard spectral reflectance the principle of minimum fertilizer application at maximum yield was used as a reference standard, and the acquired rice leaf nitrogen content and leaf spectral reflectance were differenced from the standard N content and standard spectral reflectance to obtain N content. The difference and spectral reflectance differential were then subjected to discrete wavelet multiscale decomposition, successive projections algorithm, principal component analysis, and iteratively retaining informative variables (IRIVs); the results were treated as partial least squares (PLSR), extreme learning machine (ELM), and genetic algorithm-extreme learning machine (GA-ELM). The results of hyperspectral dimensionality reduction were used as input to establish the inverse model of N content differential in japonica rice. The results showed that the GA-ELM inversion model established by discrete wavelet multi-scale decomposition obtained the optimal results in data set modeling and training. Both the R2 of the training data set and the validation data set were above 0.68, and the root mean square errors (RMSEs) were <0.6 mg/g and were more predictive, stable, and generalizable than the PLSR and ELM predictive models.

Inversion modeling of japonica rice canopy chlorophyll content with UAV hyperspectral remote sensing.

Chlorophyll content is an important indicator of the growth status of japonica rice. The objective of this paper is to develop an inversion model that can predict japonica rice chlorophyll content by using hyperspectral image of rice canopy collected with unmanned aerial vehicle (UAV). UAV-based hyperspectral remote sensing can provide timely and cost-effective monitoring of chlorophyll content over a large region. The study was based on hyperspectral data collected at the Shenyang Agricultural College Academician Japonica Rice Experimental Base in 2018 and 2019. In order to extract the salient information embedded in the high-dimensional hyperspectral data, we first perform dimension reduction by using a successive projection algorithm (SPA). The SPA extracts the characteristic hyperspectral bands that are used as input to the inversion model. The characteristic bands extracted by SPA are 410 nm, 481 nm, 533 nm, 702 nm, and 798 nm, respectively. The inversion model is developed by using an extreme learning machine (ELM), the parameters of which are optimized by using particle swarm optimization (PSO). The PSO-ELM algorithm can accurately model the nonlinear relationship between hyperspectral data and chlorophyll content. The model achieves a coefficient of determination R2 = 0.791 and a root mean square error of RMSE = 8.215 mg/L. The model exhibits good predictive ability and can provide data support and model reference for research on nutrient diagnosis of japonica rice.

Unsupervised Bayesian learning for rice panicle segmentation with UAV images.

BACKGROUND: In this paper, an unsupervised Bayesian learning method is proposed to perform rice panicle segmentation with optical images taken by unmanned aerial vehicles (UAV) over paddy fields. Unlike existing supervised learning methods that require a large amount of labeled training data, the unsupervised learning approach detects panicle pixels in UAV images by analyzing statistical properties of pixels in an image without a training phase. Under the Bayesian framework, the distributions of pixel intensities are assumed to follow a multivariate Gaussian mixture model (GMM), with different components in the GMM corresponding to different categories, such as panicle, leaves, or background. The prevalence of each category is characterized by the weights associated with each component in the GMM. The model parameters are iteratively learned by using the Markov chain Monte Carlo (MCMC) method with Gibbs sampling, without the need of labeled training data. RESULTS: Applying the unsupervised Bayesian learning algorithm on diverse UAV images achieves an average recall, precision and F 1 score of 96.49%, 72.31%, and 82.10%, respectively. These numbers outperform existing supervised learning approaches. CONCLUSIONS: Experimental results demonstrate that the proposed method can accurately identify panicle pixels in UAV images taken under diverse conditions.

Nurr1: A vital participant in the TLR4-NF-κB signal pathway stimulated by α-synuclein in BV-2 cells.

Parkinson's disease (PD) is a multi-factorial neurodegenerative disease. Abnormal α-synuclein protein aggregate and sustained microglia activation contribute to the pathogenic processes of PD. However, the relationship between α-synuclein and microglia-mediated neuroinflammation remains unclear. We purified α-synuclein after overexpression in Escherichia coli and then used it to stimulate BV-2 cells or primary microglia cells from wild type or toll-like receptor 4 (TLR4)-defective mice. Enzyme linked immunosorbent assay (ELISA) and real-time PCR results confirmed that α-synuclein could enhance the production of tumor necrosis factor α (TNF-α) through TLR4 activation. Western blotting results confirmed the involvement of the TLR4/PI3K/AKT/GSK3ß signal pathway in the inflammatory response. Nuclear factor kappa B (NF-κB) could translocate to the nucleus, promoting the expression of TNF-α when stimulated by α-synuclein in BV-2 cells. Nurr1 suppressed the production of TNF-α via interaction with NF-κB/p65 and inhibiting its nuclear translocation. In addition, both NF-κB and Nurr1 appeared to be regulated by the TLR4-mediated signal pathway. Our work demonstrated that TLR4 recognized α-synuclein and activated downstream signaling mechanisms leading to the release of pro-inflammatory mediators that are contra-balanced by Nurr1 expression. In conclusion, Nurr1 is a novel participant in the neuroinflammation stimulated by α-synuclein, thus the regulation of Nurr1 may be a novel neuroprotective target for PD treatment.

Differentiation of renal cell carcinoma subtypes with different iodine quantification methods using single-phase contrast-enhanced dual-energy CT: areal vs. volumetric analyses.

PURPOSE: To investigate the possibility of iodine quantification during a single nephrographic phase in characterizing renal cell carcinoma (RCC) subtypes and if there is a difference between areal and volumetric iodine quantification methods. MATERIALS AND METHODS: This retrospective study included 110 patients with 113 histopathologically confirmed RCCs scanned by dual-energy CT at the nephrographic phase before surgeries. For each lesion, an areal measurement of the iodine concentration with maximum enhancement (I max enhan) and the iodine concentration with maximum area among slices (I max area), as well as a volumetric iodine concentration of the whole-tumor (I volume), were evaluated by two independent radiologists. The diagnostic performances in a single nephrographic phase for characterizing RCC subtypes were evaluated, and three iodine quantification methods were compared with each other. RESULTS: There were significant differences (clear cell vs. papillary and clear cell vs. chromophobe RCC) and no significant differences (papillary vs. chromophobe RCC) at the nephrographic phase in all three methods. The area under the receiver operating characteristic (ROC) curve (AUC) derived from the I max enhan for discriminating clear cell from papillary RCC was significantly higher than that derived from the I max area (P = 0.0357) and the I volume (P = 0.0206), and no significant differences existed among the three methods in distinguishing clear cell RCC from chromophobe RCC. The reliability of all three parameters was very high with an interclass correlation coefficient (ICC) exceeding 0.8. CONCLUSIONS: Iodine quantification in a single nephrographic phase can be used to differentiate RCC subtypes preoperatively, and the areal maximum enhancement iodine quantification would probably be the most appropriate approach.