Publications by authors named "K Narayana"

Cerebral angiogenesis is well appreciated in development and after injury, but the extent to which it occurs across cortical regions in normal adult mice and the underlying mechanisms are incompletely understood. Using in vivo imaging, we show that angiogenesis in anterior-medial cortical regions (retrosplenial and sensorimotor cortex) was exceptionally rare. By contrast, angiogenesis was significantly elevated in posterior-lateral regions such as visual cortex, primarily within 200 μm of the cortical surface.

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Vascular pathology is associated with cognitive impairment in diseases such as type 1 diabetes; however, how capillary flow is affected and the underlying mechanisms remain elusive. Here we show that capillaries in the diabetic mouse brain in both sexes are prone to stalling, with blocks consisting primarily of erythrocytes in branches off ascending venules. Screening for circulating inflammatory cytokines revealed persistently high levels of interleukin-10 (IL-10) in diabetic mice.

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Accurate prediction of recurrence and progression in non-muscle invasive bladder cancer (NMIBC) is essential to inform management and eligibility for clinical trials. Despite substantial interest in developing artificial intelligence (AI) applications in NMIBC, their clinical readiness remains unclear. This systematic review aimed to critically appraise AI studies predicting NMIBC outcomes, and to identify common methodological and reporting pitfalls.

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The aim of the study was to reveal the variability in soil properties influencing pigeonpea ( ) seed yield under semi-arid rainfed condition. Soils were initially classified into series level and further these series were divided into soil-phase units. For two site years , 2018-19 and 2019-20, surface soil samples from each soil-phase unit were collected before sowing of pigeonpea and subsequently crop growth parameters at critical stages were recorded.

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Article Synopsis
  • The use of artificial intelligence (AI) in the field of urology, particularly concerning urothelial cancer (UC), is becoming increasingly prominent, but comprehensive reviews synthesizing the relevant literature are limited.
  • Researchers conducted thorough literature searches and assessed the quality and bias of studies, ultimately including 227 out of 4581 identified studies that utilized AI in various areas such as image analysis, genomics, and radiomics.
  • The findings indicate a concerning high risk of bias in most studies and highlight the need for better standardization in reporting AI applications in urology to ensure more reliable and methodologically sound research outcomes.
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