On Tanzania’s Precipitation Climatology, Variability, and Future Projection

We investigate historical and projected precipitation in Tanzania using observational and climate model data. Precipitation in Tanzania is highly variable in both space and time due to topographical variations, coastal influences, and the presence of lakes. Annual and seasonal precipitation trend analyses from 1961 to 2016 show maximum rainfall decline in Tanzania during the long rainy season in the fall (March–May), and an increasing precipitation trend in northwestern Tanzania during the short rainy season in the spring (September–November). Empirical orthogonal function (EOF) analysis applied to Tanzania’s precipitation patterns shows a stronger correlation with warmer temperatures in the western Indian Ocean than with the eastern-central Pacific Ocean. Years with decreasing precipitation in Tanzania appear to correspond with increasing sea surface temperatures (SST) in the Indian Ocean, suggesting that the Indian Ocean Dipole (IOD) may have a greater effect on rainfall variability in Tanzania than the El Niño-Southern Oscillation (ENSO) does. Overall, the climate model ensemble projects increasing precipitation trend in Tanzania that is opposite with the historical decrease in precipitation. This observed drying trend also contradicts a slightly increasing precipitation trend from climate models for the same historical time period, reflecting challenges faced by modern climate models in representing Tanzania’s precipitation

The Role of PKR/eIF2α Signaling Pathway in Prognosis of Non-Small Cell Lung Cancer

In this study, we investigated whether PKR protein expression is correlated with mRNA levels and also evaluated molecular biomarkers that are associated with PKR, such as phosphorylated PKR (p-PKR) and phosphorylated eIF2α (p-eIF2α).We determined the levels of PKR protein expression and mRNA in 36 fresh primary lung tumor tissues by using Western blot analysis and real-time reverse-transcriptase PCR (RT-PCR), respectively. We used tissue microarrays for immunohistochemical evaluation of the expression of p-PKR and p-eIF2α proteins. We demonstrated that PKR mRNA levels are significantly correlated with PKR protein levels (Spearman's rho = 0.55, p<0.001), suggesting that PKR protein levels in tumor samples are regulated by PKR mRNA. We also observed that the patients with high p-PKR or p-eIF2α expression had a significantly longer median survival than those with little or no p-PKR or p-eIF2α expression (p = 0.03 and p = 0.032, respectively). We further evaluated the prognostic effect of combined expression of p-PKR plus PKR and p-eIF2α plus PKR and found that both combinations were strong independent prognostic markers for overall patient survival on stage I and all stage patients.Our findings suggest that PKR protein expression may controlled by transcription level. Combined expression levels of PKR and p-PKR or p-eIF2α can be new markers for predicting the prognosis of patients with NSCLC

Specific human leukocyte antigen DQ influence on expression of antiislet autoantibodies and progression to type 1 diabetes

Human leukocyte antigen (HLA) DQ haplotypes have the strongest genetic association with type 1 diabetes (T1DM) risk. OBJECTIVE: The objective of the study was to analyze whether HLA DQ alleles influence the development of antiislet autoantibodies, the progression to T1DM among autoantibody-positive relatives, or both. DESIGN: The Diabetes Prevention Trial-1 screened more than 90,000 nondiabetic relatives of patients for cytoplasmic islet-cell autoantibody (ICA) expression between 1994 and 2002. SETTING: The study was conducted in the general community. PARTICIPANTS: The Diabetes Prevention Trial-1 found 2817 ICA-positive relatives who were tested for biochemical autoantibodies (GAD65, ICA512, and insulin) and HLA-DQ haplotypes, and 2796 of them were followed up for progression to diabetes for up to 8 yr (median, 3.6 yr). MAIN OUTCOME MEASURE: Progression to T1DM was measured. RESULTS: High-risk DQ haplotypes and genotypes were associated with a higher percentage of relatives expressing multiple biochemical autoantibodies and higher T1DM risk (e.g., respectively, 59 and 36% at 5 yr for carriers of the DQA1*0301-DQB1*0302/DQA1*0501-DQB1*0201 genotype). The number of autoantibodies expressed significantly increased T1DM risk and across different DQ genotypes, autoantibody positivity directly correlated with diabetes risk. However, multivariate analyses indicated that the influence of most genotypes on T1DM risk was not independent from autoantibody expression, with the possible exception of DQA1*0102-DQB1*0602. Specific genotypic combinations conferred 5-yr diabetes risks significantly lower (e.g. 7%-DQA1*0201-DQB1*0201/DQA1*0501-DQB1*0201 and 14%-DQA1*0301-DQB1*0301/DQA1*0501-DQB1*0201) than when those haplotypes were found in other combinations. CONCLUSION: HLA DQ alleles determine autoantibody expression, which is correlated with diabetes progression. Among autoantibody-positive relatives, most HLA DQ genotypes did not further influence T1DM risk

Prevalence of cardiovascular disease and risk factors in a rural district of Beijing, China: a population-based survey of 58,308 residents

Abstract Background Cardiovascular disease (CVD) is the leading cause of global disease burden. Although stroke was thought to be more prevalent than coronary heart disease (CHD) in Chinese, the epidemic pattern might have been changed in some rural areas nowadays. This study was to estimate up-to-date prevalence of CVD and its risk factors in rural communities of Fangshan District, Beijing, China. Methods A cross-sectional population survey was carried out by stratified cluster sampling. A total of 58,308 rural residents aged over 40 years were surveyed by face-to-face interview and physical examination during 2008 and 2010. The standardized prevalence was calculated according to adult sample data of China's 5th Population Census in 2000, and the adjusted prevalence odds ratio (POR) was calculated for the association of CHD/stroke with its cardiovascular risk factors in multivariate logistic regression models. Results Age- and sex-standardized prevalence was 5.6% for CHD (5.2% in males and 5.9% in females), higher than the counterpart of 3.7% (4.7% in males and 2.6% in females) for stroke. Compared with previous studies, higher prevalence of 7.7%, 47.2%, 53.3% in males and 8.2%, 44.8%, 60.7% in females for diabetes, hypertension and overweight/obesity were presented accordingly. Moreover, adjusted POR (95% confidence interval) of diabetes, obesity, stage 1 and stage 2 hypertension for CHD as 2.51 (2.29 to 2.75), 1.53 (1.38 to 1.70), 1.13 (1.02 to 1.26) and 1.35 (1.20 to 1.52), and for stroke as 2.24 (1.98 to 2.52), 1.25 (1.09 to 1.44), 1.44 (1.25 to 1.66) and 1.70 (1.46 to 1.98) were shown respectively in the multivariate logistic regression models. Conclusions High prevalence of CVD and probably changed epidemic pattern in rural communities of Beijing, together with the prevalent cardiovascular risk factors and population aging, might cause public health challenges in rural Chinese population

Etiologic Diagnosis of Lower Respiratory Tract Bacterial Infections Using Sputum Samples and Quantitative Loop-Mediated Isothermal Amplification

Etiologic diagnoses of lower respiratory tract infections (LRTI) have been relying primarily on bacterial cultures that often fail to return useful results in time. Although DNA-based assays are more sensitive than bacterial cultures in detecting pathogens, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. Here we report a nationwide cohort study on 2986 suspected LRTI patients across P. R. China. We compared the performance of a DNA-based assay qLAMP (quantitative Loop-mediated isothermal AMPlification) with that of standard bacterial cultures in detecting a panel of eight common respiratory bacterial pathogens from sputum samples. Our qLAMP assay detects the panel of pathogens in 1047(69.28%) patients from 1533 qualified patients at the end. We found that the bacterial titer quantified based on qLAMP is a predictor of probability that the bacterium in the sample can be detected in culture assay. The relatedness of the two assays fits a logistic regression curve. We used a piecewise linear function to define breakpoints where latent pathogen abruptly change its competitive relationship with others in the panel. These breakpoints, where pathogens start to propagate abnormally, are used as cutoffs to eliminate the influence of contaminations from normal flora. With help of the cutoffs derived from statistical analysis, we are able to identify causative pathogens in 750 (48.92%) patients from qualified patients. In conclusion, qLAMP is a reliable method in quantifying bacterial titer. Despite the fact that there are always latent bacteria contaminated in sputum samples, we can identify causative pathogens based on cutoffs derived from statistical analysis of competitive relationship

Bioinformatics in China: A Personal Perspective

Biochemical Research MethodsMathematical &amp; Computational BiologySCI(E)PubMed3EDITORIAL MATERIAL4e1000020

Ecological filtering shapes the impacts of agricultural deforestation on biodiversity

Funding: This project was funded by the National Natural Science Foundation of China (Grants 32122057 and 3198810 to FH) and the Ministry of Science and Technology of China (Grant 2022YFF0802300 to FH), and received further support from Tsinghua University Initiative Scientific Research Program (Grant 20223080017 to LY).The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of 10 functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability—proxied by drier and more seasonal climates under a greater disturbance regime—and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a previously largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.Peer reviewe

Pharmacokinetics and Exposure–Response Analyses of Daratumumab in Combination Therapy Regimens for Patients with Multiple Myeloma

Introduction: Daratumumab, a human IgG monoclonal antibody targeting CD38, has demonstrated activity as monotherapy and in combination with standard-of-care regimens in multiple myeloma. Population pharmacokinetic analyses were conducted to determine the pharmacokinetics of intravenous daratumumab in combination therapy versus monotherapy, evaluate the effect of patient- and disease-related covariates on drug disposition, and examine the relationships between daratumumab exposure and efficacy/safety outcomes. Methods: Four clinical studies of daratumumab in combination with lenalidomide/dexamethasone (POLLUX and GEN503); bortezomib/dexamethasone (CASTOR); pomalidomide/dexamethasone, bortezomib/thalidomide/dexamethasone, and bortezomib/melphalan/prednisone (EQUULEUS) were included in the analysis. Using various dosing schedules, the majority of patients (684/694) received daratumumab at a dose of 16 mg/kg. In GEN503, daratumumab was administered at a dose of 2 mg/kg (n = 3), 4 mg/kg (n = 3), 8 mg/kg (n = 4), and 16 mg/kg (n = 34). A total of 650 patients in EQUULEUS (n = 128), POLLUX (n = 282), and CASTOR (n = 240) received daratumumab 16 mg/kg. The exposure–efficacy and exposure–safety relationships examined progression-free survival (PFS) and selected adverse events (infusion-related reactions; thrombocytopenia, anemia, neutropenia, lymphopenia, and infections), respectively. Results: Pharmacokinetic profiles of daratumumab were similar between monotherapy and combination therapy. Covariate analysis identified no clinically important effects on daratumumab exposure, and no dose adjustments were recommended on the basis of these factors. Maximal clinical benefit on PFS was achieved for the majority of patients (approximately 75%) at the 16 mg/kg dose. No apparent relationship was observed between daratumumab exposure and selected adverse events. Conclusion: These data support the recommended 16 mg/kg dose of daratumumab and the respective dosing schedules in the POLLUX and CASTOR pivotal studies. Funding: Janssen Research & Development

P27Kip1, regulated by glycogen synthase kinase-3β, results in HMBA-induced differentiation of human gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Gastric cancer is the second most common cause of global cancer-related mortality. Although dedifferentiation predicts poor prognosis in gastric cancer, the molecular mechanism underlying dedifferentiation, which could provide fundamental insights into tumor development and progression, has yet to be elucidated. Furthermore, the molecular mechanism underlying the effects of hexamethylene bisacetamide (HMBA), a recently discovered differentiation inducer, requires investigation and there are no reported studies concerning the effect of HMBA on gastric cancer.</p> <p>Methods</p> <p>Based on the results of FACS analysis, the levels of proteins involved in the cell cycle or apoptosis were determined using western blotting after single treatments and sequential combinations of HMBA and LiCl. GSK-3β and proton pump were investigated by western blotting after up-regulating Akt expression by Ad-Akt infection. To investigate the effects of HMBA on protein localization and the activities of GSK-3β, CDK2 and CDK4, kinase assays, immunoprecipitation and western blotting were performed. In addition, northern blotting and RNase protection assays were carried out to determine the functional concentration of HMBA.</p> <p>Results</p> <p>HMBA increased p27Kip1 expression and induced cell cycle arrest associated with gastric epithelial cell differentiation. In addition, treating gastric-derived cells with HMBA induced G0/G1 arrest and up-regulation of the proton pump, a marker of gastric cancer differentiation. Moreover, treatment with HMBA increased the expression and activity of GSK-3β in the nucleus but not the cytosol. HMBA decreased CDK2 activity and induced p27Kip1 expression, which could be rescued by inhibition of GSK-3β. Furthermore, HMBA increased p27Kip1 binding to CDK2, and this was abolished by GSK-3β inhibition.</p> <p>Conclusions</p> <p>The results presented herein suggest that GSK-3β functions by regulating p27Kip1 assembly with CDK2, thereby playing a critical role in G0/G1 arrest associated with HMBA-induced gastric epithelial cell differentiation.</p