GluA3 subunits are required for appropriate assembly of AMPAR GluA2 and GluA4 subunits on cochlear afferent synapses and for presynaptic ribbon modiolar-pillar morphology

Cochlear sound encoding depends on α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs), but reliance on specific pore-forming subunits is unknown. With 5-week-old male C57BL/6

Knowledge, anxiety levels and attitudes of infertile couples towards COVID-19 and its impact on self-funded fertility treatment : a cross-sectional questionnaire survey

Acknowledgement We thank the couples who were willing to participate in the study. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.Peer reviewedPublisher PD

Significant benefits of AIP testing and clinical screening in familial isolated and young-onset pituitary tumors

Context Germline mutations in the aryl hydrocarbon receptor-interacting protein (AIP) gene are responsible for a subset of familial isolated pituitary adenoma (FIPA) cases and sporadic pituitary neuroendocrine tumors (PitNETs). Objective To compare prospectively diagnosed AIP mutation-positive (AIPmut) PitNET patients with clinically presenting patients and to compare the clinical characteristics of AIPmut and AIPneg PitNET patients. Design 12-year prospective, observational study. Participants & Setting We studied probands and family members of FIPA kindreds and sporadic patients with disease onset ≤18 years or macroadenomas with onset ≤30 years (n = 1477). This was a collaborative study conducted at referral centers for pituitary diseases. Interventions & Outcome AIP testing and clinical screening for pituitary disease. Comparison of characteristics of prospectively diagnosed (n = 22) vs clinically presenting AIPmut PitNET patients (n = 145), and AIPmut (n = 167) vs AIPneg PitNET patients (n = 1310). Results Prospectively diagnosed AIPmut PitNET patients had smaller lesions with less suprasellar extension or cavernous sinus invasion and required fewer treatments with fewer operations and no radiotherapy compared with clinically presenting cases; there were fewer cases with active disease and hypopituitarism at last follow-up. When comparing AIPmut and AIPneg cases, AIPmut patients were more often males, younger, more often had GH excess, pituitary apoplexy, suprasellar extension, and more patients required multimodal therapy, including radiotherapy. AIPmut patients (n = 136) with GH excess were taller than AIPneg counterparts (n = 650). Conclusions Prospectively diagnosed AIPmut patients show better outcomes than clinically presenting cases, demonstrating the benefits of genetic and clinical screening. AIP-related pituitary disease has a wide spectrum ranging from aggressively growing lesions to stable or indolent disease course

Simulation of Daily Rainfall from Concurrent Meteorological Parameters over Core Monsoon Region of India: A Novel Approach

In the present work, daily rainfall is simulated over the core monsoon region of India by using a feedforward multilayer perceptron (MLP) model. Daily rainfall is found to be optimally dependent on four concurrent meteorological parameters, namely, geopotential height, specific humidity, zonal, and meridional wind at 1000 mb, 925 mb, 850 mb, and 700 mb pressure levels during 00, 06, 12, and 18 Greenwich Mean Time (GMT). The architecture of the optimized feedforward MLP model consists of 64 nodes in the input layer, 10 nodes in the hidden layer, and 1 node in the output layer. The results from the model are compared with the 3B42 (version 7) rainfall product. In terms of root mean square error (rmse) and correlation coefficient (cc), the model is performing better compared to the satellite-derived 3B42 rainfall product, whereas in terms of bias, the performance of the 3B42 product is better compared to the model. The weight matrices of the feedforward MLP model are estimated at a particular location (22.5°N, 82.5°E). These weight matrices are able to simulate daily rainfall at neighbourhood locations also with reasonably good accuracy with cc in the range of 0.41 to 0.55. The performance of the model improves in case of an aerial average of daily rainfall with significantly enhanced cc (0.72). The model is able to capture monthly and intraseasonal variation of rainfall with reasonably good accuracy, with cc of 0.88 and 0.68, respectively. The simulation model has a limitation that it is not able to simulate extreme high rainfall events (>60 mm/day). Overall, the developed model is performing reasonably well. This approach has a potential to be used as a rain parameterization scheme in the dynamical atmospheric and coupled models to simulate daily rainfall. Nevertheless, the present approach can also be used for multistep prediction of rainfall