Unraveling trends in schistosomiasis: deep learning insights into national control programs in China.

Objectives: To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. Methods: We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). Results: The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease. Conclusion: The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Epidemiological features and prognosis for primary gastrointestinal follicular lymphoma.

Primary gastrointestinal follicular lymphoma (PGI-FL) is a rare extra-nodal lymphoma. Its epidemiology and prognosis remain unclear. We performed a retrospective analysis of eligible patients with 1648 PGI-FL and 34 892 nodal FL (N-FL) in the Surveillance, Epidemiology and End Results (SEER) database. The age-adjusted average annual incidence of PGI-FL was 0.111/100000. The median overall survival (OS) for PGI-FL and N-FL patients was 207 and 165 months respectively. The 5-year diffuse large B-cell lymphoma (DLBCL) transformation rates were 2.1% and 2.6% respectively. Age, sex, grade, Ann Arbor stage, primary site and radiation were independent prognostic factors (p < 0.05). Nomograms were constructed to predict 1-, 5- and 10-year OS and disease-specific survival (DSS). The receiver operating characteristic curves and calibration plots showed the established nomograms had robust and accurate performance. Patients were classified into three risk groups according to nomogram score. In conclusion, the incidence of PGI-FL has increased over the past 40 years, and PGI-FL has a better prognosis and a lower DLBCL transformation rate than N-FL. The nomograms were developed and validated as an individualized tool to predict survival. Patients were divided into three risk groups to assist clinicians in identifying high-risk patients and choosing the optimal individualized treatments.

Upland rice genomic signatures of adaptation to drought resistance and navigation to molecular design breeding.

Upland rice is a distinctive drought-aerobic ecotype of cultivated rice highly resistant to drought stress. However, the genetic and genomic basis for the drought-aerobic adaptation of upland rice remains largely unclear due to the lack of genomic resources. In this study, we identified 25 typical upland rice accessions and assembled a high-quality genome of one of the typical upland rice varieties, IRAT109, comprising 384 Mb with a contig N50 of 19.6 Mb. Phylogenetic analysis revealed upland and lowland rice have distinct ecotype differentiation within the japonica subgroup. Comparative genomic analyses revealed that adaptive differentiation of lowland and upland rice is likely attributable to the natural variation of many genes in promoter regions, formation of specific genes in upland rice, and expansion of gene families. We revealed differentiated gene expression patterns in the leaves and roots of the two ecotypes and found that lignin synthesis mediated by the phenylpropane pathway plays an important role in the adaptive differentiation of upland and lowland rice. We identified 28 selective sweeps that occurred during domestication and validated that the qRT9 gene in selective regions can positively regulate drought resistance in rice. Eighty key genes closely associated with drought resistance were appraised for their appreciable potential in drought resistance breeding. Our study enhances the understanding of the adaptation of upland rice and provides a genome navigation map of drought resistance breeding, which will facilitate the breeding of drought-resistant rice and the "blue revolution" in agriculture.

Influence of urbanization on schistosomiasis infection risk in Anhui Province based on sixteen year's longitudinal surveillance data: a spatio-temporal modelling study.

BACKGROUND: Urbanization greatly affects the natural and social environment of human existence and may have a multifactoral impact on parasitic diseases. Schistosomiasis, a common parasitic disease transmitted by the snail Oncomelania hupensis, is mainly found in areas with population aggregations along rivers and lakes where snails live. Previous studies have suggested that factors related to urbanization may influence the infection risk of schistosomiasis, but this association remains unclear. This study aimed to analyse the effect of urbanization on schistosomiasis infection risk from a spatial and temporal perspective in the endemic areas along the Yangtze River Basin in China. METHODS: County-level schistosomiasis surveillance data and natural environmental factor data covering the whole Anhui Province were collected. The urbanization level was characterized based on night-time light data from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and the National Polar-Orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). The geographically and temporally weighted regression model (GTWR) was used to quantify the influence of urbanization on schistosomiasis infection risk with the other potential risk factors controlled. The regression coefficient of urbanization was tested for significance (α = 0.05), and the influence of urbanization on schistosomiasis infection risk was analysed over time and across space based on significant regression coefficients. Variables studied included climate, soil, vegetation, hydrology and topography. RESULTS: The mean regression coefficient for urbanization (0.167) is second only to the leached soil area (0.300), which shows that the urbanization is the most important influence factors for schistosomiasis infection risk besides leached soil area. The other important variables are distance to the nearest water source (0.165), mean minimum temperature (0.130), broadleaf forest area (0.105), amount of precipitation (0.073), surface temperature (0.066), soil bulk density (0.037) and grassland area (0.031). The influence of urbanization on schistosomiasis infection risk showed a decreasing trend year by year. During the study period, the significant coefficient of urbanization level increased from - 0.205 to - 0.131. CONCLUSIONS: The influence of urbanization on schistosomiasis infection has spatio-temporal heterogeneous. The urbanization does reduce the risk of schistosomiasis infection to some extend, but the strength of this influence decreases with increasing urbanization. Additionally, the effect of urbanization on schistosomiasis infection risk was greater than previous reported natural environmental factors. This study provides scientific basis for understanding the influence of urbanization on schistosomiasis, and also provides the feasible research methods for other similar studies to answer the issue about the impact of urbanization on disease risk.

Immune inhibitory receptor-mediated immune response, metabolic adaptation, and clinical characterization in patients with COVID-19.

Immune inhibitory receptors (IRs) play a critical role in the regulation of immune responses to various respiratory viral infections. However, in coronavirus disease 2019 (COVID-19), the roles of these IRs in immune modulation, metabolic reprogramming, and clinical characterization remain to be determined. Through consensus clustering analysis of IR transcription in the peripheral blood of patients with COVID-19, we identified two distinct IR patterns in patients with COVID-19, which were named IR_cluster1 and IR_cluster2. Compared to IR_cluster1 patients, IR_cluster2 patients with lower expressions of immune inhibitory receptors presented with a suppressed immune response, lower nutrient metabolism, and worse clinical manifestations or prognosis. Considering the critical influence of the integrated regulation of multiple IRs on disease severity, we established a scoring system named IRscore, which was based on principal component analysis, to evaluate the combined effect of multiple IRs on the disease status of individual patients with COVID-19. Similar to IR_cluster2 patients, patients with high IRscores had longer hospital-free days at day 45, required ICU admission and mechanical ventilatory support, and presented higher Charlson comorbidity index and SOFA scores. A high IRscore was also linked to acute infection phase and absence of drug intervention. Our investigation comprehensively elucidates the potential role of IR patterns in regulating the immune response, modulating metabolic processes, and shaping clinical manifestations of COVID-19. All of this evidence suggests the essential role of prognostic stratification and biomarker screening based on IR patterns in the clinical management and drug development of future emerging infectious diseases such as COVID-19.

The prognostic index PRIMA-PI combined with Ki67 as a better predictor of progression of disease within 24 months in follicular lymphoma.

Background: Progression of disease within 24 months (POD24) is a risk factor for poor survival in follicular lymphoma (FL), and there is currently no optimal prognostic model to accurately predict patients with early disease progression. How to combine traditional prognostic models with new indicators to establish a new prediction system, to predict the early progression of FL patients more accurately is a future research direction. Methods: This study retrospectively analyzed patients with newly diagnosed FL patients in Shanxi Provincial Cancer Hospital from January 2015 to December 2020. Data from patients undergoing immunohistochemical detection (IHC) were analyzed using χ2 test and multivariate Logistic regression. Also, we built a nomogram model based on the results of LASSO regression analysis of POD24, which was validated in both the training set and validation set, and additional external validation was performed using a dataset (n = 74) from another center, Tianjin Cancer Hospital. Results: The multivariate Logistic regression results suggest that high-risk PRIMA-PI group, Ki-67 high expression represent risk factors for POD24 (P<0.05). Next, PRIMA-PI and Ki67 were combined to build a new model, namely, PRIMA-PIC to reclassify high and low-risk groups. The result showed that the new clinical prediction model constructed by PRIMA-PI with ki67 has a high sensitivity to the prediction of POD24. Compared to PRIMA-PI, PRIMA-PIC also has better discrimination in predicting patient's progression-free survival (PFS) and overall survival (OS). In addition, we built nomogram models based on the results of LASSO regression (histological grading, NK cell percentage, PRIMA-PIC risk group) in the training set, which were validated using internal validation set and external validation set, we found that C-index and calibration curve showed good performance. Conclusion: As such, the new predictive model-based nomogram established by PRIMA-PI and Ki67 could well predict the risk of POD24 in FL patients, which boasts clinical practical value.

Integrative genomic and transcriptomic analysis reveals genetic alterations associated with the early progression of follicular lymphoma.

Follicular lymphoma (FL), the most common indolent lymphoma, is a clinically and genetically heterogeneous disease. However, the prognostic value of driver gene mutations and copy number alterations has not been systematically assessed. Here, we analysed the clinical-biological features of 415 FL patients to identify variables associated with disease progression within 24 months of first-line therapy (POD24). Patients with B symptoms, elevated lactate dehydrogenase and ß2-microglobulin levels, unfavourable baseline haemoglobin levels, advanced stage, and high-risk FL International Prognostic Index (FLIPI) scores had an increased risk of POD24, with FLIPI being the most important factor in logistic regression. HIST1H1D, identified as a driver mutation, was correlated with POD24. Gains of 6p22.2 (HIST1H1D) and 18q21.33 (BCL2) and loss of 1p36.13 (NBPF1) predicted POD24 independent of FLIPI. Gene expression profiling of FL samples showed that the POD24 cohort was significantly enriched in the inflammatory response (mediated by interferon and tumour necrosis factor), cell cycle regulation (transcription, replication and proliferation) sets and PI3K-AKT-mTOR signalling. This result was further validated with transcriptome-wide information provided by RNA-seq at single-cell resolution. Our study, performed on a large cohort of FL patients, highlights the importance of distinctive genetic alterations and gene expression relevant to disease diagnosis and early progression.

Impacts of sample ratio and size on the performance of random forest model to predict the potential distribution of snail habitats.

Few studies have considered the impacts of sample size and sample ratio of presence and absence points on the results of random forest (RF) testing. We applied this technique for the prediction of the spatial distribution of snail habitats based on a total of 15,000 sample points (5,000 presence samples and 10,000 control points). RF models were built using seven different sample ratios (1:1, 1:2, 1:3, 1:4, 2:1, 3:1, and 4:1) and the optimal ratio was identified via the Area Under the Curve (AUC) statistic. The impact of sample size was compared by RF models under the optimal ratio and the optimal sample size. When the sample size was small, the sampling ratios of 1:1, 1:2 and 1:3 were significantly better than the sample ratios of 4:1 and 3:1 at all four levels of sample sizes (p<0.01) and there was no significant difference among the ratios of 1:1, 1:2 and 1:3 (p>0.05). The sample ratio of 1:2 appeared to be optimal for a relatively large sample size with the lowest quartile deviation. In addition, increasing the sample size produced a higher AUC and a smaller slope and the most suitable sample size found in this study was 2400 (AUC=0.96). This study provides a feasible idea to select an appropriate sample size and sample ratio for ecological niche modelling (ENM) and also provides a scientific basis for the selection of samples to accurately identify and predict snail habitat distributions.

Clinical features and outcomes of patients with follicular lymphoma: A real-world study of 926 patients in China.

Background: The data about the clinical features and outcomes of Chinese patients with follicular lymphoma (FL) are limited. Here, we conducted a retrospective study to explore the initial treatment strategies and clinical outcomes of Chinese patients with FL in the real world. Method: This study included FL patients who were newly diagnosed in Tianjin Medical University Cancer Institute and Hospital from March 2002 to August 2020. Results: A total of 926 FL patients were enrolled. The median age was 54 years old, and the majority of the Chinese FL patients had advanced-stage disease and Eastern Cooperative Oncology Group(ECOG) <1 but less frequently infiltrated bone marrow. After a median of 38-month follow-up, the 5-year progressive-free survival (PFS) and overall survival (OS) of grade1-3a were 57.8% and 88.7%, respectively, which both are similar to those reported in previous Chinese and Western studies. The co-existence at diagnosis of FL and diffuse large B-cell lymphoma (DLBCL) components (FL/DLBCL) was associated with poor outcomes. The FL grades and proportion of DLBCL component in FL/DLBCL did not have an impact on PFS and OS. The most common regimen with great efficacy and risk-benefit was RCHOP-like followed by R maintenance regimen. The 5-year cumulative hazard of histological transformation (HT) was 4.7% (95% CI, 3.5-5.9); median time to transformation was 23.5 months (range, 2-146 months) after diagnosis. Three-year survival following transformation was 55% (95% CI, 40-70). Patients with stage III-IV, elevated ß2 microglobulin (ß2-MG), and B symptoms seemed to be more prone to progress within 24 months of frontline therapy (POD24). The FLIPI-2 showed the highest specificity to predict POD24, reflecting the prediction of correctly classifying as low-risk patients, but the FLIPI had the highest sensitivity to predict the risk of progression for critical patients. Conclusions: We revealed the clinical characteristics and outcomes of FL patients in the real world in China, which may provide novel data on prognostic factors and primary treatment of FL, applicable to routine clinical practice.

Risk factors for POD24 in patients with previously untreated follicular lymphoma: a systematic review and meta-analysis.

Progression of disease within 24 months (POD24) is strongly associated with a poor outcome in patients with follicular lymphoma (FL). Our study aimed to identify the potential risk factors for POD24 in patients with FL. Medline, EMBASE and the Cochrane Library were systematically searched from the earliest record to September 2020. Studies investigating the prognostic factors for POD24 in patients with newly diagnosed grade 1-3a FL were included. Among 10,014 pieces of literature, a total of 90 studies investigating 82 risk factors were included for qualitative analysis. Meta-analyses were performed in 31 studies with 11 factors. Results showed that elevated sIL-2R, ß2m and LDH, total metabolic tumour volume > 510 cm3, vitamin D < 20 ng/mL, grade 3a and lymphoma-associated macrophages/high-power field ≥ 15 were significantly associated with an increased risk of POD24. No significant association was found between POD24 and the ALC/AMC ratio, sex, T effector signature or EZH2 genetic alteration. Additionally, minimal residual disease, Ki-67, PD-1 and TP53 were analysed narratively. Overall, this is the first study that comprehensively analysed the prognostic factors associated with POD24 in FL patients. We have confirmed the significance value of several common prognostic factors as well as others not commonly included in clinical study, helping to construct an integrated and more efficient model.

Screening of Adverse Prognostic Factors and Construction of Prognostic Index in Previously Untreated Concurrent Follicular Lymphoma and Diffuse Large B-Cell Lymphoma.

Objective: Concurrent follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) (defined as FL/DLBCL) have been considered an important pathological feature in cell lymphoma. However, clinicopathological information and prognostic factors in these cases are scarce. The aim of this study was to construct a prediction index to compare with traditional prognostic models. Methods: Retrospectively enrolled, previously untreated FL/DLBCL (n = 121) patients, as well as those with pure FL 1-3a (n = 471), were assessed. De novo DLBCL (n = 529) were used as controls. Kaplan-Meier curves were plotted to compare the outcomes among the three groups. Multivariate analysis identified risk factors associated with overall survival (OS) in FL/DLBCL patients. A clinicopathological prognosis index (CPPI) was developed to predict OS based on the Cox proportional hazards model. Results: The outcomes of FL/DLBCL patients were intermediate between pure FL 1-3a and de novo DLBCL patients, with a 5-year PFS of 70%, 59%, and 48% (P < 0.05) and 5-year OS of 80%, 70% and 60% (P < 0.05), respectively. Cox regression analysis showed that the prognostic factors of OS for FL/DLBCL patients included FL grade, cell of origin, and Ann Arbor stage. A nomogram and clinicopathological prognostic index (CPPI) were developed to predict the OS for FL/DLBCL patients based on these factors. The area under the curve (AUC) of the CPPI for 3- and 5-year OS prediction was 0.782 and 0.860, respectively. This was superior to that of the International Prognostic Index (IPI), Follicular Lymphoma International Prognostic Index (FLIPI), and FLIPI2 in the 0.540-0.819 (P < 0.01) range. Conclusions: A valid OS estimation in FL/DLBCL patients, using the recommended CPPI, may be useful in routine clinical practice.

m6A-Regulator Expression Signatures Identify a Subset of Follicular Lymphoma Harboring an Exhausted Tumor Microenvironment.

The role of N6-methyladenosine (m6A) modification in tumor microenvironment has rarely been explored in follicular lymphoma (FL). To examine the role of m6A modification in biological behavior, especially the immune landscape of FL, we utilized the Gene Expression Omnibus database to determine the expression signatures of m6A-regulators by unsupervised clustering, and then condense into a risk score, which was validated in an external cohort from the Tianjin Medical University Cancer Institute and Hospital. Finally, 16 m6A-regulators in 351 FL patients were evaluated and two m6A clusters were identified, characterized by differences in prognosis and biological behaviors. The m6A score was further developed based on 20-genes to quantify the m6A-regulator expression signature in each patient with FL. The low m6A score was associated with inferior prognosis of patients, with a median survival time of 8.84 (95% confidence interval [CI]: 7.251-10.429) years, which was remarkably shorter than that of patients with high m6A scores (15.73 years, 95% CI: 11.729-19.731; p<0.0001). Genes like TNFRSF14, CREBBP, and CARD11 were shown to be more often mutated in the low m6A group. This group was enriched with immune/inflammatory response but along with the abundant infiltration of exhausted T cells and the upregulated PD-1 and PD-L1 expression. Finally, we verified the m6A score could predict the response to anti-PD-L1 antibodies in an immunotherapy cohort. To conclude, the m6A score recognizes a section of FL patients harboring an exhausted tumor microenvironment and may help guide more effective immunotherapy strategies for patients with FL.

A comparison of modelling the spatio-temporal pattern of disease: a case study of schistosomiasis japonica in Anhui Province, China.

The construction of spatio-temporal models can be either descriptive or dynamic. In this study we aim to evaluate the differences in model fitting between a descriptive model and a dynamic model of the transmission for intestinal schistosomiasis caused by Schistosoma japonicum in Guichi, Anhui Province, China. The parasitological data at the village level from 1991 to 2014 were obtained by cross-sectional surveys. We used the fixed rank kriging (FRK) model, a descriptive model, and the integro-differential equation (IDE) model, a dynamic model, to explore the space-time changes of schistosomiasis japonica. In both models, the average daily precipitation and the normalized difference vegetation index are significantly positively associated with schistosomiasis japonica prevalence, while the distance to water bodies, the hours of daylight and the land surface temperature at daytime were significantly negatively associated. The overall root mean square prediction error of the IDE and FRK models was 0.0035 and 0.0054, respectively, and the correlation reflected by Pearson's correlation coefficient between the predicted and observed values for the IDE model (0.71; p<0.01) was larger than that for the FRK model (0.53; p=0.02). The IDE model fits better in capturing the geographic variation of schistosomiasis japonica. Dynamic spatio-temporal models have the advantage of quantifying the process of disease transmission and may provide more accurate predictions.

Bayesian maximum entropy-based prediction of the spatiotemporal risk of schistosomiasis in Anhui Province, China.

BACKGROUND: "Schistosomiasis" is a highly recurrent parasitic disease that affects a wide range of areas and a large number of people worldwide. In China, schistosomiasis has seriously affected the life and safety of the people and restricted the economic development. Schistosomiasis is mainly distributed along the Yangtze River and in southern China. Anhui Province is located in the Yangtze River Basin of China, with dense water system, frequent floods and widespread distribution of Oncomelania hupensis that is the only intermediate host of schistosomiasis, a large number of cattle, sheep and other livestock, which makes it difficult to control schistosomiasis. It is of great significance to monitor and analyze spatiotemporal risk of schistosomiasis in Anhui Province, China. We compared and analyzed the optimal spatiotemporal interpolation model based on the data of schistosomiasis in Anhui Province, China and the spatiotemporal pattern of schistosomiasis risk was analyzed. METHODS: In this study, the root-mean-square-error (RMSE) and absolute residual (AR) indicators were used to compare the accuracy of Bayesian maximum entropy (BME), spatiotemporal Kriging (STKriging) and geographical and temporal weighted regression (GTWR) models for predicting the spatiotemporal risk of schistosomiasis in Anhui Province, China. RESULTS: The results showed that (1) daytime land surface temperature, mean minimum temperature, normalized difference vegetation index, soil moisture, soil bulk density and urbanization were significant factors affecting the risk of schistosomiasis; (2) the spatiotemporal distribution trends of schistosomiasis predicted by the three methods were basically consistent with the actual trends, but the prediction accuracy of BME was higher than that of STKriging and GTWR, indicating that BME predicted the prevalence of schistosomiasis more accurately; and (3) schistosomiasis in Anhui Province had a spatial autocorrelation within 20 km and a temporal correlation within 10 years when applying the optimal model BME. CONCLUSIONS: This study suggests that BME exhibited the highest interpolation accuracy among the three spatiotemporal interpolation methods, which could enhance the risk prediction model of infectious diseases thereby providing scientific support for government decision making.

Fotemustine-based therapy in combination with rituximab as a first-line induction chemotherapy followed by WBRT for newly diagnosed primary central nervous system lymphoma: a prospective phase II trial.

OBJECTIVE: This study aimed to evaluate the safety, efficacy, and feasibility of the rituximab, fotemustine, pemetrexed, and dexamethasone (R-FPD) regimen followed by whole-brain radiotherapy (WBRT) for patients with primary central nervous system lymphoma (PCNSL). METHODS: A prospective, single-center phase II clinical trial was conducted. Patients with PCNSL newly diagnosed at the First Affiliated Hospital of Zhengzhou University between July 2018 and July 2020 were studied. The R-FPD regimen consisted of rituximab (375 mg/m2 i.v. on D0), fotemustine (100 mg/m2 i.v. on D1), pemetrexed (600 mg/m2 i.v. on D1), and dexamethasone (40 mg i.v. on D1-5). Patients 60 years or younger who showed a complete response (CR) were treated with 23.4 Gy of WBRT after the end of chemotherapy; those older than 60 years with CR were treated with a wait-and-see approach; and those who did not show CR after the 4th cycle of chemotherapy were given salvage WBRT 30 Gy + local tumor field irradiation up to 45 Gy, regardless of age. RESULTS: A total of 30 patients were included. After 2 cycles, the objective response rate (ORR) was 96.5% (28/29, 1 CR, 27 PR, 0 SD, and 1 PD). After 4 cycles, the ORR was 73.1% (19/26, 11 CR, 8 PR, 4 SD, and 3 PD). After WBRT, the ORR was 90.9% (10/11, 7 CR, 3 PR, and 1 SD). The grade III and IV toxicity responses were mainly leukopenia (20.0%), thrombocytopenia (23.3%), and anemia (10.0%). CONCLUSIONS: Fotemustine-based therapy in combination with rituximab chemotherapy followed by WBRT can improve outcomes, providing ORR benefits and favorable tolerability in patients newly diagnosed with PCNSL.

Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice.

Genetic basis and network studies underlying synergistic biomass accumulation of roots and shoots (SBA) are conducive for rational design of high-biomass rice breeding. In this study, association signals for root weight, shoot weight, and the ratio of root-to-shoot mass (R/S) were identified using 666 rice accessions by genome-wide association study, together with their sub-traits, root length, root thickness and shoot length. Most association signals for root weight and shoot weight did not show association with their sub-traits. Based on the results, we proposed a top-to-bottom model for SBA, i.e. root weight, shoot weight and R/S were determined by their highest priority in contributing to biomass in the regulatory pathway, followed by a lower priority pathway for their sub-traits. Owing to 37 enriched clusters with more than two association signals identified, the relationship among the six traits could be also involved in linkage and pleiotropy. Furthermore, a discrimination of pleiotropy and LD at sequencing level using the known gene OsPTR9 for root weight, R/S and root length was provided. The results of given moderate correlation between traits and their corresponding sub-traits, and moderate additive effects between a trait and the accumulation of excellent alleles corresponding to its sub-traits supported a bottom-to-top regulation model for SBA. This model depicted each lowest-order trait (root length, root thickness and shoot length) was determined by its own regulation loci, and competition among different traits, as well as the pleiotropy and LD. All above ensure the coordinated development of each trait and the accumulation of the total biomass, although the predominant genetic basis of SBA is still indistinguishable. The presentation of the above two models and evidence of this study shed light on dissecting the genetic architecture of SBA.

Comparative Transcriptomic and Proteomic Analyses Prove that IFN-λ1 is a More Potent Inducer of ISGs than IFN-α against Porcine Epidemic Diarrhea Virus in Porcine Intestinal Epithelial Cells.

Type III interferon (IFN-λ) is currently considered to be largely nonredundant to type I interferon (IFN-α) in antivirus infection, especially in epithelial cells. Previous studies reported that, compared with IFN-α, IFN-λ exhibited stronger induction of interferon-stimulated genes (ISGs) at the transcriptional level in intestinal epithelial cells and stronger inhibition of porcine epidemic diarrhea virus (PEDV). In this study, the different mechanisms of ISG upregulation induced by IFN-α and IFN-λ1 were compared at the mRNA and protein levels in the porcine intestinal epithelial cell model (IPEC-J2). It was proved that IFN-λ1 consistently exhibited stronger stimulation effects at both levels. At the mRNA level, 132 genes were significantly upregulated upon IFN-λ1 stimulation, while 42 genes upon IFN-α stimulation. At the protein level, 47 proteins were significantly upregulated upon IFN-λ1 stimulation, but only 8 proteins were upregulated upon IFN-α stimulation. The shared upregulated genes/proteins by IFN-λ1 in both transcriptional and translational omics, especially the regulation factors of ISG15, were involved in the JAK-STAT signaling pathway. Compared to IFN-α, IFN-λ1 could induce more consistent upregulation of the key ISGs (ISG15, USP18, OASL, and RSAD2) at 3-24 h postinduction as measured by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) validation. It was further confirmed through functional analysis that ISG15 and RSAD2 could inhibit PEDV infection in dose-dependent manners. This study provided solid evidence that IFN-λ1 could induce a more unique and higher ISG expression level, which exhibited anti-PEDV effects on porcine intestinal epithelial cells.

Risk prediction of two types of potential snail habitats in Anhui Province of China: Model-based approaches.

Elimination of the intermediate snail host of Schistosoma is the most effective way to control schistosomiasis and the most important first step is to accurately identify the snail habitats. Due to the substantial resources required for traditional, manual snail-searching in the field, and potential risk of miss-classification of potential snail habitats by remote sensing, more convenient and precise methods are urgently needed. Snail data (N = 15,000) from two types of snail habitats (lake/marshland and hilly areas) in Anhui Province, a typical endemic area for schistosomiasis, were collected together with 36 environmental variables covering the whole province. Twelve different models were built and evaluated with indices, such as area under the curve (AUC), Kappa, percent correctly classified (PCC), sensitivity and specificity. We found the presence-absence models performing better than those based on presence-only. However, those derived from machine-learning, especially the random forest (RF) approach were preferable with all indices above 0.90. Distance to nearest river was found to be the most important variable for the lake/marshlands, while the climatic variables were more important for the hilly endemic areas. The predicted high-risk areas for potential snail habitats of the lake/marshland type exist mainly along the Yangtze River, while those of the hilly type are dispersed in the areas south of the Yangtze River. We provide here the first comprehensive risk profile of potential snail habitats based on precise examinations revealing the true distribution and habitat type, thereby improving efficiency and accuracy of snail control including better allocation of limited health resources.

Overexpression of TIM-3 in Macrophages Aggravates Pathogenesis of Pulmonary Fibrosis in Mice.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disorder and lacks effective treatments because of unclear mechanisms. Aberrant function of alveolar macrophages is directly linked to pulmonary fibrosis. Here, we show TIM-3 (T-cell immunoglobulin domain and mucin domain-3), a key regulator of macrophage function, aggravates pulmonary fibrosis. TIM-3 mRNA of patients with IPF was analyzed based on the Gene Expression Omnibus and Array Express databases. Lung pathology and profibrotic molecules were assessed in a bleomycin (BLM)-induced pulmonary fibrosis model using wild-type (WT) and TIM-3 transgenic (TIM-3-TG) mice. Macrophage cells, RAW264.7, were then applied to investigate the effect of macrophage TIM-3 under BLM exposure in vitro. Macrophage depletion and adoptive-transfer experiments were finally performed to examine lung morphology and profibrotic molecules. TIM-3 expression was increased both in patients with IPF and in our BLM-induced mouse model. TIM-3-TG mice developed more serious pathological changes in lung tissue and higher expressions of TGF-ß1 (transforming growth factor-ß1) and IL-10 than WT mice. After BLM treatment, TGF-ß1 and IL-10 expression was significantly decreased in RAW264.7 cells after TIM-3 knock-out, whereas it was increased in TIM-3-TG peritoneal macrophages. The scores of pulmonary fibrosis in WT and TIM-3-TG mice were significantly reduced, and there was no difference between them after macrophage depletion. Furthermore, WT mice receiving adoptive macrophages from TIM-3-TG mice also had more serious lung fibrosis and increased expression of TGF-ß1 and IL-10 than those receiving macrophages from WT mice. Our findings revealed that overexpressed TIM-3 in alveolar macrophages aggravated pulmonary fibrosis.