Effectiveness and safety of glucagon-like peptide 1 receptor agonists in patients with type 2 diabetes: evidence from a retrospective real-world study.

Introduction: Global phase III clinical trials have shown superior hypoglycemic efficacy to insulin and other oral hypoglycemic agents. However, there is a scarcity of real-world data comparing different glucagon-like peptide 1 receptor agonist (GLP-1RA) directly. This study aimed to assess the safety and effectiveness of various GLP-1RA in treating type 2 diabetes mellitus (T2DM) in a real-world clinical setting and identify predictive factors for favorable treatment outcomes. Methods: This was a retrospective, single-center, real-world study. The changes in HbA1c, fasting plasma glucose (FPG), body weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), and the percentage of participants who achieved HbA1c of <7%, 7%-8%, and ≥ 8% after GLP-1RA treatment was analyzed. The clinical factors that affect the effectiveness of GLP-1RA were analyzed. Results: At baseline, the 249 participants had a mean baseline HbA1c of 8.7 ± 1.1%. After at least three months of follow-up, the change in HbA1c was -0.89 ± 1.3% from baseline. Dulaglutide exerted a more significant hypoglycemic effect than immediate-release exenatide. The percentage of participants who achieved HbA1c<7% was substantial, from 6.0% at baseline to 28.9%. Average body weight decreased by 2.02 ± 3.8 kg compared to baseline. After GLP-1RA treatment, the reduction in SBP was 2.4 ± 7.1 mmHg from baseline. A shorter duration of diabetes and a higher baseline HbA1c level were more likely to achieve a good response in blood glucose reduction. Conclusions: This study provided real-world evidence showing that GLP-1RA significantly improved HbA1c, body weight, and SBP. The results can inform the decision-making about GLP-1RA treatment in daily clinical practice.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders.

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

Evolution of SARS-CoV-2 Viral Mutations in Individuals with Prolonged Infections.

OBJECTIVE: The world has been faced with the repeat rise of SARS-CoV-2 variants since late 2020, including Alpha, Beta, Gamma, Delta, and the latest simultaneous emergence of far-flung spawn of Omicron sub-lineages in different parts of the globe. This has brought us the challenge of determining what factor(s) have been the selective force behind these immune evasive and therapy resistant mutations. It is very possible that such variants evolved in limited host individuals with prolonged infections, or from a localized community of patients. METHODS: This study surveys the GISAID time capsule of mutations found in viral genomes from patients with prolonged same lineage viral infections. We analyzed 288 SARS-CoV-2 genomes representing 113 patients who had same lineage viral genomes in two or more samples stored in GISAID. RESULTS: Of these, thirty-five (30.9%) of the 113 patients developed mutations during their infections. Samples from patients whose viral genomes showed nucleotide changes(s) (n=35) versus those that showed no change (n=78) had a statistically significant difference (p=2.121x10-4) in duration of infection by a median of 13 days (range 0-109 days) versus 6 days (range 0-72 days), respectively. Five highly recognizable variant-defining mutations with immune evasion properties were identified in 5 cases infected by the B.1 lineages in late 2020 and early 2021. CONCLUSION: This suggests the duration of infection is a contributing factor that gives rise to mutations, but not the sole factor, and individual host conditions may play a critical role in driving viral evolution.

Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster ( Crassostrea ariakensis).

Glycogen serves as the principal energy reserve for metabolic processes in aquatic shellfish and substantially contributes to the flavor and quality of oysters. The Jinjiang oyster ( Crassostrea ariakensis) is an economically and ecologically important species in China. In the present study, RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) were performed to investigate gene expression and chromatin accessibility variations in oysters with different glycogen contents. Analysis identified 9 483 differentially expressed genes (DEGs) and 7 215 genes with significantly differential chromatin accessibility (DCAGs) were obtained, with an overlap of 2 600 genes between them. Notably, a significant proportion of these genes were enriched in pathways related to glycogen metabolism, including "Glycogen metabolic process" and "Starch and sucrose metabolism". In addition, genome-wide association study (GWAS) identified 526 single nucleotide polymorphism (SNP) loci associated with glycogen content. These loci corresponded to 241 genes, 63 of which were categorized as both DEGs and DCAGs. This study enriches basic research data and provides insights into the molecular mechanisms underlying the regulation of glycogen metabolism in C. ariakensis.

Immunological dynamic characteristics in acute myeloid leukemia predict the long-term outcomes and graft-versus host-disease occurrences post-transplantation.

To investigate the relationship between immune dynamic and graft-versus-host-disease (GVHD) risk, 111 initial diagnostic acute myeloid leukemia patients were reviewed. The flow cytometry data of 12 major lymphocyte subsets in bone marrow (BM) from 60 transplant patients at four different time points were analyzed. Additionally, 90 immune subsets in peripheral blood (PB) of 11 post-transplantation on day 100 were reviewed. Our results demonstrated that transplant patients had longer OS compared to non-transplant patients (P < 0.001). Among transplant patients, those who developed GVHD showed longer OS than those without GVHD (P < 0.05). URD donors and CMV-negative status donors were associated with improved OS in transplant patients (P < 0.05). Importantly, we observed a decreased Th/Tc ratio in BM at initial diagnostic in patients with GVHD compared to those without GVHD (P = 0.034). Receiver operating characteristic analysis indicated that a low Th/Tc ratio predicted an increased risk of GVHD with a sensitivity of 44.44% and specificity of 87.50%. Moreover, an increased T/NK ratio in BM of post-induction chemotherapy was found to be associated with GVHD, with a sensitivity of 75.76% and specificity of 65.22%. Additionally, we observed a decreased percentage of NK1 (CD56-CD16+NK) in PB on day 100 post-transplantation in the GVHD group (P < 0.05). These three indicators exhibit promising potential as specific and useful biomarkers for predicting GVHD. These findings provide valuable insights for the early identification and management of GVHD risk, thereby facilitating the possibility of improving patient outcomes.

Cytogenetically Cryptic Acute Promyelocytic Leukemia: A Diagnostic Challenge.

Cytogenetically cryptic acute promyelocytic leukemia (APL) is rare, characterized by typical clinical and morphological features, but lacks t(15;17)(q24;q21)/PML::RARA translocation seen in conventional karyotyping or FISH. The prompt diagnosis and treatment of APL are critical due to life-threatening complications associated with this disease. However, cryptic APL cases remain a diagnostic challenge that could mislead the appropriate treatment. We describe four cryptic APL cases and review reported cases in the literature. Reverse transcriptase polymerase chain reaction (RT-PCR) is the most efficient diagnostic modality to detect these cases, and alternative methods are also discussed. This study highlights the importance of using parallel testing methods to diagnose cryptic APL cases accurately and effectively.

Three-dimensional model construction and wind simulation of different tree species in farmland shelter.

Protective forests are the ecological barriers of oases in arid sand areas and can effectively prevent and control wind and sand hazards. The structural characteristics of individual trees, as the basic unit of protective forests, are the key factors affecting the protective benefits. With the typical leafless tree species of Ulan Buh Desert oasis, i.e., Populus alba var. pyramidalis, Populus nigra var. thevestina, and Populus popularis, as the research objects, and by using the ground-based LiDAR and through computational fluid dynamics (CFD), we fully explored the structural characteristics of individual trees and their surrounding aerodynamic characteristics on the basis of real 3D models. We further established the relationship between structural parameters of individual trees and wind field index. The results showed that combining AdQSM and MeshLab to build tree models had high accuracy. The wind field around the individual trees could be roughly divided into six regions, including the attenuation zone of the windward side of the plant, the acceleration zone at the top of the plant, the eddy zone, the calm zone, the transition zone, and the recovery zone of leeward side of the plant. The pressure field around individual trees showed a gradual change of high pressure on the windward side to low pressure on the leeward side. Horizontally, in the range of 20% to 50% reduction in relative wind speed, the effective protection distances were 0.21H-1.51H, 0.20H-0.91H, and 0.25H-1.64H (H was the corresponding tree height) for P. alba var. pyramidalis, P. nigra var. thevestina, and P. popularis, corresponding to effective protection areas of 18-294, 15-227, and 18-261 m2, respectively. The maximum wind speed decay rate in the vertical direction was at 0.3H height for P. alba var. pyramidalis and P. popularis, and was reflected at 0.5H height for P. nigra var. thevestina. The correlation and stepwise regression analysis of the single tree structure parameters with the wind field indicators clearly indicated that optical porosity and volume porosity dominated the protection effect. Among the wind field factors, the best regression models related to the porous coefficient were screened for three factors, including diameter at breast height, tree surface area, and optical porosity. The regression variables screened for effective protection distance and effective protection area differed among the classes.

Patient-Specific Targeting of the T-Cell Receptor Variable Region as a Therapeutic Strategy in Clonal T-Cell Diseases.

PURPOSE: Targeted therapeutics are a goal of medicine. Methods for targeting T-cell lymphoma lack specificity for the malignant cell, leading to elimination of healthy cells. The T-cell receptor (TCR) is designed for antigen recognition. T-cell malignancies expand from a single clone that expresses one of 48 TCR variable beta (Vß) genes, providing a distinct therapeutic target. We hypothesized that a mAb that is exclusive to a specific Vß would eliminate the malignant clone while having minimal effects on healthy T cells. EXPERIMENTAL DESIGN: We identified a patient with large granular T-cell leukemia and sequenced his circulating T-cell population, 95% of which expressed Vß13.3. We developed a panel of anti-Vß13.3 antibodies to test for binding and elimination of the malignant T-cell clone. RESULTS: Therapeutic antibody candidates bound the malignant clone with high affinity. Antibodies killed engineered cell lines expressing the patient TCR Vß13.3 by antibody-dependent cellular cytotoxicity and TCR-mediated activation-induced cell death, and exhibited specific killing of patient malignant T cells in combination with exogenous natural killer cells. EL4 cells expressing the patient's TCR Vß13.3 were also killed by antibody administration in an in vivo murine model. CONCLUSIONS: This approach serves as an outline for development of therapeutics that can treat clonal T-cell-based malignancies and potentially other T-cell-mediated diseases. See related commentary by Varma and Diefenbach, p. 4024.

Assessment on the declining degree of farmland shelter forest in a desert oasis based on LiDAR and hyperspectrum imagery.

We examined the growth decline and health status of farmland protective forest belt (Populus alba var. pyramidalis and Populus simonii shelterbelts) in Ulanbuh Desert Oasis by using airborne hyperspectral and ground-based LiDAR to collect the hyperspectral images and point cloud data of the whole forest belt respectively. Through correlation analysis and stepwise regression analysis, we constructed the evaluation model of the decline degree of farmland protection forest with the spectral differential value, vegetation index, and forest structure parameters as independent variables and the tree canopy dead branch index of the field survey as dependent variables. We further tested the accuracy of the model. The results showed that the evaluation accuracy of the decline degree of P. alba var. pyramidalis and P. simonii by LiDAR method was better than that by hyperspectral method, and that the evaluation accuracy of the combined LiDAR and hyperspectral method was the highest. Using the LiDAR method, hyperspectral method, the combined method, the optimal model of P. alba var. pyramidalis was all light gradient boosting machine model, with the overall classification accuracy being 0.75, 0.68, 0.80, and Kappa coefficient being 0.58, 0.43, 0.66, respectively. The optimal model of P. simonii was random forest model, random forest model, and multilayer perceptron model, with the overall classification accuracy being 0.76, 0.62, 0.81, and Kappa coefficient being 0.60, 0.34, 0.71, respectively. This research method could accurately check and monitor the decline of plantations.

Construction of 3D sheet-packed hierarchical MoS2/BiOBr heterostructures with remarkably enhanced photocatalytic performance for tetracycline and levofloxacin degradation.

In this paper, MoS2 nanosheets were prepared and deposited on BiOBr microflowers through deposition-hydrothermal strategy. MoS2 exhibited a string of nanosheets with wrinkled layer outlook, and MoS2/BiOBr composites displayed a micro-flower morphology with the diameter of 2-3 µm. Visible-light harvesting performance was significantly improved in the region of 400-600 nm for MoS2/BiOBr. The obtained MoS2/BiOBr samples exhibited tremendous enhanced catalytic activity, which could degrade 92.96% of tetracycline and 90.31% of levofloxacin within 70 min. The photo-generated holes and ⋅OH radicals played the dominant roles in the whole photocatalytic decomposition process. Based on the analysis of DRS, BET, PL, and electrochemical results, the remarkably improved photocatalytic performance may be ascribed to the synergistic effect of strong visible-light harvesting ability, enhanced BET surface area, and faster separation or transfer efficiency of photo-generated charges.

Phylogenetic analyses of 41 Y-STRs and machine learning-based haplogroup prediction in the Qingdao Han population from Shandong province, Eastern China.

BACKGROUND: Known for its rich history and culture, Qingdao is a typical symbol of Chinese maritime culture. Its unique genetic landscape has aroused interest among geneticists and forensic scientists. However, the genetic landscape of Qingdao has never been uncovered. AIM: This investigation intends to provide light on Qingdao's paternal genetic diversity and its evolutionary connections to other Han subgroups. SUBJECTS AND METHODS: The genetic polymorphisms of 41 Y-chromosomal short tandem repeat (STR) loci in the Qingdao Han were investigated using SureID® PathFinder Plus Kit. Phylogenetic studies were performed using genotype data from 52 East Asian groups at 23 common Y-STR loci. A multidimensional scaling plot and cladogram were constructed. Linear Discriminant Analysis (LDA) was carried out for predicting categories among the Han people. The k-nearest neighbour (kNN) algorithm was utilised to designate Y-SNP haplogroups for each haplotype. RESULTS: The Qingdao Han were genetically far from the Tibeto-Burman populations and close with the Han people from northern China. LDA indicated a deep integration among the present-day Han people. By the kNN model, the predicted O2a2 and O2a1 were shown to be the predominant Y-SNP haplogroups. CONCLUSIONS: This study would be helpful for reconstructing the patrilineal history in China and establishing a more comprehensive Y-STR database.

Upregulation of KLF14 expression attenuates kidney fibrosis by inducing PPARα-mediated fatty acid oxidation.

Tubulointerstitial fibrosis (TIF) is essential during the development of end-stage kidney disease (ESKD) and is associated with the impairment of fatty acid oxidation (FAO). Kruppel-like factor 14 (KLF14) is an important gene in lipid metabolism, but its role in TIF remains unknown. TGF-ß-stimulated HK-2 cells and mouse unilateral ureteral obstruction (UUO) were used as renal fibrosis models. The role of KLF14 in the process of renal fibrosis was verified by gene knockout mice, genetic or pharmacological interference in animal model and cell model respectively. In the current study, we found that KLF14 expression increased after activation of the TGF-ß signaling pathway during TIF. In KLF14-/- mice, more severe fibrosis was observed after unilateral ureteral obstruction (UUO) was induced. In human HK2 cells, knockdown of KLF14 led to more severe fibrosis induced by TGF-ß1, while overexpression of KLF14 partially attenuated this process. Specifically, KLF14 deficiency decreased mitochondrial FAO activity, resulting in lipid accumulation. Thus, the energy supply to the cells was insufficient, finally resulting in TIF. We further proved that KLF14 could target peroxisome proliferator activated receptor alpha (PPARα) as a transcriptional activator. This study identified the upregulation of KLF14 expression in response to kidney stress during the process of fibrosis. Upon TIF, the activated TGF-ß signaling pathway can enhance KLF14 expression, while the upregulation of KLF14 expression can decrease the degree of TIF by improving FAO activity in tubular epithelial cells and recovering the energy supply mediated by PPARα.

A mixed blessing for liver transplantation patients - Rapamycin.

BACKGROUND: Liver transplantation (LT) is an effective treatment option for end-stage liver disease. Mammalian target of rapamycin (mTOR) inhibitors, such as rapamycin, are widely used post LT. DATA SOURCES: In this review, we focused on the anti-cancer activities and metabolic side effects of rapamycin after LT. The literature available on PubMed for the period of January 1999-September 2022 was reviewed. The key words were rapamycin, sirolimus, liver transplantation, hepatocellular carcinoma, diabetes, and lipid metabolism disorder. RESULTS: Rapamycin has shown excellent effects and is safer than other immunosuppressive regimens. It has exhibited excellent anti-cancer activity and has the potential in preventing hepatocellular carcinoma (HCC) recurrence post LT. Rapamycin is closely related to two long-term complications after LT, diabetes and lipid metabolism disorders. CONCLUSIONS: Rapamycin prevents HCC recurrence post LT in some patients, but it also induces metabolic disorders. Reasonable use of rapamycin benefits the liver recipients.

Programmable Thermo-Responsive Actuation of Hydrogels via Light-Guided Surface Growth of Active Layers on Shape Memory Substrates.

Hydrogel shape memory and actuating functionalities are heavily pursued and have found great potential in various application fields. However, their combination for more flexible and complicated morphing behaviors is still challenging. Herein, it is reported that by controlling the light-initiated polymerization of active hydrogel layers on shape memory hydrogel substrates, advanced morphing behaviors based on programmable hydrogel shapes and actuating trajectories are realized. The formation and photo-reduction-induced dissociation of Fe3+ -carboxylate coordination endow the hydrogel substrates with the shape memory functionality. The photo-reduced Fe2+ ions can diffuse from the substrates into the monomer solutions to initiate the polymerization of the thermally responsive active layers, whose actuating temperatures and amplitudes can be facially tuned by controlling their thicknesses and compositions. One potential application, a shape-programmable 3D hook that can lift an object with a specific shape, is also unveiled. The demonstrated strategy is extendable to other hydrogel systems to realize more versatile and complicated actuating behaviors.

Prognostic implication of early posttransplant hypercholesterolemia in liver transplantation for patients with hepatocellular carcinoma.

BACKGROUND: Hyperlipidemia is a common complication after liver transplantation (LT) and develops mostly in the early posttransplant period. Recently, some studies have reported a positive correlation between hyperlipidemia and favorable prognosis in patients with hepatocellular carcinoma (HCC) undergoing hepatectomy. This study aimed to evaluate the possibility of predicting prognosis in HCC patients receiving LT by early posttransplant dyslipidemia. METHODS: From January 2015 to December 2017, a total of 806 HCC patients from China Liver Transplant Registry database were retrospectively enrolled. The prognostic relevance of early posttransplant hypertriglyceridemia or hypercholesterolemia was examined using survival analysis, and subgroup analysis was implemented based on LT criteria. RESULTS: Early posttransplant hypercholesterolemia (EPHC) was independently inversely associated with the risk of recurrence [hazard ratio (HR) = 0.630; P = 0.022], but was not significantly correlated with the mortality. However, early posttransplant hypertriglyceridemia was not related to prognosis. Intriguingly, with further classification, we found that borderline EPHC (B-EPHC), instead of significant EPHC, was a predictor of lower risk for both recurrence (HR = 0.504; P = 0.006) and mortality (HR = 0.511; P = 0.023). Compared with non-EPHC patients, B-EPHC patients achieved significantly superior 1-year and 3-year tumor-free survival (89.6% and 83.7% vs. 83.8% and 72.7% respectively; P = 0.023), and 1-year and 3-year overall survival (95.8% and 84.8% vs. 94.6% and 77.6% respectively; P = 0.039). In the subgroup analysis, B-EPHC remained an independent predictor of better prognosis in patients beyond Milan criteria and those within Hangzhou criteria; whereas there was no significant relationship between B-EPHC and prognosis in patients within Milan criteria and those beyond Hangzhou criteria. More interestingly, patients beyond Milan criteria but within Hangzhou criteria were identified as the crucial subpopulation who benefited from B-EPHC (recurrence HR = 0.306, P = 0.011; mortality HR = 0.325, P = 0.031). CONCLUSIONS: B-EPHC could assist transplant teams in dynamically evaluating prognosis after LT for HCC as a postoperative non-oncological biomarker, especially in patients beyond Milan criteria but within Hangzhou criteria.

Investigation of insecticidal activity of two Rhododendron species on stored-product insects.

This study was designed to investigate the insecticidal activity of the essential oils (EOs) and extracts from Rhododendron rufum and Rhododendron przewalskii. The EOs were extracted from the leaves of R. Rufum and R. przewalskii by hydro-distillation and their chemical components were analyzed by gas chromatography-mass spectrometry (GC-MS). The repellency, contact toxicity and antifeedant activity of the EOs and extracts were evaluated against Sitophilus oryzae and Tribolium castaneum along with those of their main components. A total of nine compounds were identified from the EO of R. Rufum, and the most abundant component was myristicin (79.72%). The EO of R. Rufum exhibited repellent activities at different levels and its main compound myristicin showed contact toxicity and repellent effects against S. oryzae and T. castaneum. Meanwhile, by bioassay-guided fractionation, four compounds with strong antifeedant activities against T. castaneum, 24-methylenecycloartanyl-2'E, 4'Z-tetradecadienoate (1), methyl thyrsiflorin B acetate (2), friedelin (3) and Excoecarin R1 methyl ester (4) were separated and identified from the ethanol extract of R. przewalskii for the first time. Considering the significant anti-insect activities, the EOs and extracts of R. Rufum and R. przewalskii might be used in integrated pest strategies, establishing a good perspective for the comprehensive use of natural plant resources of Rhododendron genus.

[Germplasm resource evaluation of Chrysanthemi Indici Flos based on color and chemical components].

This study explored the correlation between color and chemical components of Chrysanthemi Indici Flos(CIF), aiming at providing a reference for its procurement, evaluation, and breeding. Colorimeter and ultra-performance liquid chromatograph(UPLC) were used to determine the color(lightness-shade chromaticity value L~*, red-green chromaticity value a~*, yellow-blue chromati-city value b~*) and chemical components(cynaroside, linarin, luteolin, apigenin, and chlorogenic acid) of 84 CIF germplasms, respectively. Diversity analysis, correlation analysis, regression analysis, and cluster analysis were performed. The results showed that the color and chemical components of CIF were diversified. Chlorogenic acid was in significantly positive correlation with L~* and b~* and significantly negative correlation with a~*. Cynaroside and grey relational grade γ_i of chemical components were in significantly po-sitive correlation with b~* and L~*, respectively, whereas linarin, luteolin, and apigenin had no significant correlation with L~*, a~*, or b~*. The 84 CIF germplasms were clustered into 4 clades. In addition, germplasms in clade Ⅲ had higher γ_i and total color value(E~*_(ab)) than those in other clades, with the best quality and color, and a germplasm with the highest quality, bright yellow color, and highest content of linarin was screened out in this clade. Thus, CIF with bright yellow color had high content of cymaroside and chlorogenic acid and thereby high quality. In summary, the color can be used to quickly predict the quality of CIF. Our results provided data for the evaluation of CIF quality by color and a reference for its procurement and breeding.

Toxicity Effects and Mechanisms of MgO Nanoparticles on the Oomycete Pathogen Phytophthora infestans and Its Host Solanum tuberosum.

Engineered nanoparticles have recently been used for innovation in agricultural disease management. However, both the toxicity effects and mechanisms of nanoparticles in target pathogens and their host plants are still largely unknown. Here, we found that magnesium oxide nanoparticles (MgO NPs) could protect potatoes against Phytophthora infestans (P. infestans) at a low dosage (50 µg/mL). Through scanning electron microscopy observation, antioxidant enzymes activity measurement, and gene transcriptome analysis, we found that the cell surfaces of P. infestans were destroyed, endogenous superoxide dismutase continuously remained in a higher active state, oxidoreductase activity-related gene ontology (GO) terms were enriched with upregulation, and transporter-activity related GO terms and six essential metabolism-related pathways were enriched with downregulation in P. infestans after 30 min MgO NPs treatment, whereas only 89 genes were changed without enriched GO and pathways terms, and no change in antioxidant activities and phenylalnine ammonialyase in potato appeared at 6 h post-MgO NPs treatment. Only the "plant hormone signal transduction pathway" was enriched with upregulation under differential expression analysis in potatoes. In conclusion, cell surface distortion, continuous oxidative stress, and inhibitions of membrane transport activity and metabolic pathways were toxic mechanisms of Mg ONPs in P. infestans, and the "plant hormone signal transduction pathway" was potentially regulated by Mg-ONPs without obviously harmful effects on potato after Mg ONPs exposure.

Interpretation of genotype-environment-sowing date/plant density interaction in sorghum [Sorghum bicolor (L.) Moench] in early mature regions of China.

Sorghum [Sorghum bicolor (L.) Moench] is an important crop for food security in semiarid and arid regions due to its high tolerance to abiotic and biotic stresses and its good performance in marginal lands with relatively low fertility. To deeply understand the interrelationship among sorghum genotype, environment, sowing dates, and densities in the spring sowing early maturing (SSEM) areas of China, and to provide a basis for specifying scientific and reasonable cultural practices, a two-year field experiment was conducted with six popular varieties at six locations. Combined ANOVA showed that the yield difference between years was significant (P<0.05); the yield differences among locations, varieties, sowing dates, and densities were all highly significant (P<0.01). The variety effect was mainly influenced by location, year, sowing dates and their interactions. The sowing effect was mainly influenced by the location, year, variety and their interactions The plant density effect was significantly influenced by location and location-year interaction. Of the contributions of various test factors to yield variance, the location was the largest one (38.18%), followed by variety (12.31%), sowing date (1.53%), density (0.54%), and year (0.09%), with all these single factors accounting for 52.65%. The total contribution of all two-factor interactions accounted for 14.24%, among which the greatest contributor was location-hybrid interaction (8.07%). The total contribution of all three-factor interactions accounted for 14.58%, of which year-location-hybrid interaction was the largest contributor (9.02%). Sowing dates significantly affected model of sorghum growth and development, especially during the late period. The key climatic factors affecting yield were different among the six locations. Weather factors during the grain filling stages contributed much more than those during the early stage to grain yield. Mid-maturing varieties are recommended other than early maturing varieties for the SSEM areas even when late sowing occurs. Sowing as early as possible is recommended for areas with very short frost-free period (Harbin, Tongliao, and Datong). Proper delayed sowing is recommended for areas with a relative long frost-free period (Gongzhuling, Baicheng and Zhangjiakou). This research will provide a conducive reference for sorghum production in similar areas.

Assessing the factors influencing the performance of machine learning for classifying haplogroups from Y-STR haplotypes.

Two distinct genetic markers, single nucleotide polymorphisms (Y-SNPs) and short tandem repeats (Y-STRs), exist simultaneously in the non-recombining portion of the Y chromosome. Because of their different rates of mutation, Y-STRs and Y-SNPs play distinct roles in forensic and evolutionary genetics. Current approaches to infer haplogroup status rely on genotyping lots of Y-SNP loci. Given the relationship between haplotype and haplogroup of a Y chromosome, a cost-effective strategy of Y-STRs typing had an advantage in haplogroup prediction. Many machine learning algorithms have sprung up for assigning a Y-STR haplotype to a haplogroup. However, a series of issues must be solved before the using of machine learning method in practice. Thus, the k-nearest neighbor (kNN) classifier was built respectively based on different situations in this study. We assessed different factors which may influence the performance of the kNN prediction model for classifying haplogroups. The training set was based on a diverse ground-truth data set comprising Y-STR haplotypes and corresponding Y-SNP haplogroups. Our results showed that combining different levels of haplogroups into the observations or transracial prediction was impractical. Moreover, using more slow mutation Y-STR loci in the category is good for promoting classification accuracy. The preconditions for an effective and accurate haplogroup assignment by the kNN classifier were revealed.