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Seasonal yield forecasts are important to support agricultural development programs and can contribute to improved food security in developing countries. Despite their importance, no operational forecasting system on sub-national level is yet in place in Tanzania. We develop a statistical maize yield forecast based on regional yield statistics in Tanzania and climatic predictors, covering the period 2009-2019. We forecast both yield anomalies and absolute yields at the sub-national scale about 6 weeks before the harvest. The forecasted yield anomalies (absolute yields) have a median Nash-Sutcliffe efficiency coefficient of 0.72 (0.79) in the out-of-sample cross validation, which corresponds to a median root mean squared error of 0.13 t/ha for absolute yields. In addition, we perform an out-of-sample variable selection and produce completely independent yield forecasts for the harvest year 2019. Our study is potentially applicable to other countries with short time series of yield data and inaccessible or low quality weather data due to the usage of only global climate data and a strict and transparent assessment of the forecasting skill.In other species characterized to date, aging, as a function of reproductive potential, results in the breakdown of proteaostasis and a decreased capacity to mount responses by the heat shock response (HSR) and other proteostatic network pathways. Our understanding of the maintenance of stress pathways, such as the HSR, in honey bees, and in the reproductive queen in particular, is incomplete. Based on the findings in other species showing an inverse relationship between reproductive potential and HSR function, one might predict that that HSR function would be lost in the reproductive queens. see more However, as queens possess an atypical uncoupling of the reproduction-maintenance trade-off typically found in solitary organisms, HSR maintenance might also be expected. Here we demonstrate that reproductive potential does not cause loss of HSR performance in honey bees as queens induce target gene expression to levels comparable to those induced in attendant worker bees. Maintenance of HSR function with advent of reproductive potential is unique among invertebrates studied to date and provides a potential model for examining the molecular mechanisms regulating the uncoupling of the reproduction-maintenance trade-off in queen bees, with important consequences for understanding how stresses impact different types of individuals in honey bee colonies.A brain tumor is an uncontrolled growth of cancerous cells in the brain. Accurate segmentation and classification of tumors are critical for subsequent prognosis and treatment planning. This work proposes context aware deep learning for brain tumor segmentation, subtype classification, and overall survival prediction using structural multimodal magnetic resonance images (mMRI). We first propose a 3D context aware deep learning, that considers uncertainty of tumor location in the radiology mMRI image sub-regions, to obtain tumor segmentation. We then apply a regular 3D convolutional neural network (CNN) on the tumor segments to achieve tumor subtype classification. Finally, we perform survival prediction using a hybrid method of deep learning and machine learning. To evaluate the performance, we apply the proposed methods to the Multimodal Brain Tumor Segmentation Challenge 2019 (BraTS 2019) dataset for tumor segmentation and overall survival prediction, and to the dataset of the Computational Precision Medicine Radiology-Pathology (CPM-RadPath) Challenge on Brain Tumor Classification 2019 for tumor classification. We also perform an extensive performance evaluation based on popular evaluation metrics, such as Dice score coefficient, Hausdorff distance at percentile 95 (HD95), classification accuracy, and mean square error. The results suggest that the proposed method offers robust tumor segmentation and survival prediction, respectively. Furthermore, the tumor classification results in this work is ranked at second place in the testing phase of the 2019 CPM-RadPath global challenge.Increasing evidence has confirmed that immunoglobulins (Igs) can be expressed in non-B cells. Our previous work demonstrated that mesangial cells and podocytes express IgA and IgG, respectively. The aim of this work was to reveal whether proximal tubular epithelial cells (PTECs) express Igs. High-throughput single-cell RNA sequencing (scRNA-seq) detected Igs in a small number of PTECs, and then we combined nested PCR with Sanger sequencing to detect the transcripts and characterize the repertoires of Igs in PTECs. We sorted PTECs from the normal renal cortex of two patients with renal cancer by FACS and further confirmed their identify by LRP2 gene expression. Only the transcripts of the IgG heavy chain were successfully amplified in 91/111 single PTECs. We cloned and sequenced 469 VHDJH transcripts from 91 single PTECs and found that PTEC-derived IgG exhibited classic VHDJH rearrangements with nucleotide additions at the junctions and somatic hypermutations. Compared with B cell-derived IgG, PTEC-derived IgG displayed less diversity of VHDJH rearrangements, predominant VH1-24/DH2-15/JH4 sequences, biased VH1 usage, centralized VH gene segment location at the 3' end of the genome and non-Gaussian distribution of the CDR3 length. These results demonstrate that PTECs can express a distinct IgG repertoire that may have implications for their role in the renal tubular epithelial-mesenchymal transition.Procrastination is a self-regulatory problem of voluntarily and destructively delaying intended and necessary or personally important tasks. Previous studies showed that procrastination is associated with executive dysfunctions that seem to be particularly strong in punishing contexts. In the present event-related potential (ERP) study a monetary version of the parametric Go/No-Go task was performed by high and low academic procrastinators to verify the influence of motivational context (reward vs. punishment expectation) and task difficulty (easy vs. hard) on procrastination-related executive dysfunctions. The results revealed increased post-error slowing along with reduced P300 and error-related negativity (ERN) amplitudes in high (vs. low) procrastination participants-effects that indicate impaired attention and error-related processing in this group. This pattern of results did not differ as a function of task difficulty and motivation condition. However, when the task got more difficult executive attention deficits became even more apparent at the behavioral level in high procrastinators, as indexed by increased reaction time variability.

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