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There is a dearth of studies that examine the association between poorer hearing and change in cerebral white matter (WM) microstructure.

To examine the association of poorer hearing with baseline and change in WM microstructure among older adults.

This was a prospective cohort study that evaluated speech-in-noise, pure-tone audiometry, and WM microstructure, as measured by mean diffusivity (MD) and fractional anisotropy (FA), both of which were evaluated by diffusion tensor imaging (DTI) in 17 WM regions. Data were collected between October 2012 and December 2018 and analyzed between March 2019 and August 2019 with a mean follow-up time of 1.7 years. The study evaluated responses to the Baltimore Longitudinal Study of Aging among 356 cognitively normal adults who had at least 1 hearing assessment and DTI session. Excluded were those with baseline cognitive impairment, stroke, head injuries, Parkinson disease, and/or bipolar disorder.

Peripheral auditory function was measured by pure-tone average in t associated with longitudinal MD increases (β = 0.031; 95% CI, 0.010-0.052) and FA declines (β = -1.624; 95% CI, -2.511 to -0.738) in the uncinate fasciculus.

Findings of this cohort study suggest that poorer hearing is related to change in integrity of specific WM regions involved with auditory processing.
Findings of this cohort study suggest that poorer hearing is related to change in integrity of specific WM regions involved with auditory processing.
Mucinous cystic neoplasm of the liver is characterized by neoplastic mucinous and/or biliary epithelium surrounded by ovarian-type stroma. Immunohistochemical studies have shown that the ovarian-type stroma expresses estrogen receptor, suggesting potential hormonal responsiveness. The molecular biology of mucinous cystic neoplasm of the liver remains poorly studied.

Transcriptome sequencing and immunohistochemistry were performed on a series of mucinous cystic neoplasms.

Mucinous cystic neoplasm of the liver exhibited significantly increased RNA expression of ovarian stromal markers WT1, PR, and ER2 and sex cord stromal markers SF-1, inhibin-α, and calretinin compared with nonneoplastic liver. Immunohistochemistry confirmed the RNA-level data. Evidence for sex hormone biosynthesis was identified by significant overexpression of multiple estrogen biosynthetic enzymes. Expression of 17β-hydroxysteroid dehydrogenase 1 was confirmed immunohistochemically. Pathway analysis also identified significant upregulation of the hedgehog and Wnt pathways and significant downregulation of T-helper 1 and T-helper 2 pathways.

Mucinous cystic neoplasm of the liver recapitulates ovarian stroma at the morphologic, DNA, RNA, and protein levels. These data support the concept that this tumor likely arises from ectopic primitive gonadal tissue and/or stromal cells with capacity to transdifferentiate to ovarian cortical cells.
Mucinous cystic neoplasm of the liver recapitulates ovarian stroma at the morphologic, DNA, RNA, and protein levels. These data support the concept that this tumor likely arises from ectopic primitive gonadal tissue and/or stromal cells with capacity to transdifferentiate to ovarian cortical cells.
During the outbreak, billions of people were eager to get information about COVID-19 through social media. Social media can not only deliver reliable information to the public but can in turn reflect changes in the public's psychological status. Insight into the public's hotspots of concern and mental status through media background tools contributes to the formulation of public health policies and the clarification of epidemic development mode.

WeChat is the largest social media in China. Taking the recovery period of COVID-19 in China, for example, we collected WeChat Index data and analyzed the public's concern about the course of COVID-19 and the restoration of emotional tendency through keywords search.

With the gradual control of the COVID-19 in China, the public psychological status changes from negative to neutral, accompanied by a weakening of negative emotions and an increase in positive emotions. Every obvious inflection point of improvement in social operation is reflected in the increase of public attention and the relaxation of lifestyle.

Social media can be used to monitor the public psychological status and the development mode and trend of infection in one country during a pandemic.
Social media can be used to monitor the public psychological status and the development mode and trend of infection in one country during a pandemic.
Screening for diabetic retinopathy is recommended for children with type 1 diabetes (T1D) and type 2 diabetes (T2D), yet screening rates remain low. this website Point-of-care diabetic retinopathy screening using autonomous artificial intelligence (AI) has become available, providing immediate results in the clinic setting, but the cost-effectiveness of this strategy compared with standard examination is unknown.

To assess the cost-effectiveness of detecting and treating diabetic retinopathy and its sequelae among children with T1D and T2D using AI diabetic retinopathy screening vs standard screening by an eye care professional (ECP).

In this economic evaluation, parameter estimates were obtained from the literature from 1994 to 2019 and assessed from March 2019 to January 2020. Parameters included out-of-pocket cost for autonomous AI screening, ophthalmology visits, and treating diabetic retinopathy; probability of undergoing standard retinal examination; relative odds of undergoing screening; and sensitivity, specutonomous AI systems is effective and cost saving for children with diabetes and their caregivers at recommended adherence rates.
These results suggest that point-of-care diabetic retinopathy screening using autonomous AI systems is effective and cost saving for children with diabetes and their caregivers at recommended adherence rates.
Recent studies have demonstrated the successful application of artificial intelligence (AI) for automated retinal disease diagnostics but have not addressed a fundamental challenge for deep learning systems the current need for large, criterion standard-annotated retinal data sets for training. Low-shot learning algorithms, aiming to learn from a relatively low number of training data, may be beneficial for clinical situations involving rare retinal diseases or when addressing potential bias resulting from data that may not adequately represent certain groups for training, such as individuals older than 85 years.

To evaluate whether low-shot deep learning methods are beneficial when using small training data sets for automated retinal diagnostics.

This cross-sectional study, conducted from July 1, 2019, to June 21, 2020, compared different diabetic retinopathy classification algorithms, traditional and low-shot, for 2-class designations (diabetic retinopathy warranting referral vs not warranting referral).
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