Hypothalamic neuropeptides play essential roles in regulating energy and body weight balance. Energy imbalance and obesity have been linked to hypothalamic signaling defects in regulating neuropeptide genes; however, it is unknown whether dysregulation of neuropeptide exocytosis could be critically involved. This study discovered that synaptotagmin-4, an atypical modulator of synaptic exocytosis, is expressed most abundantly in oxytocin neurons of the hypothalamus. Synaptotagmin-4 negatively regulates oxytocin exocytosis, and dietary obesity is associated with increased vesicle binding of synaptotagmin-4 and thus enhanced negative regulation of oxytocin release. Overexpressing synaptotagmin-4 in hypothalamic oxytocin neurons and centrally antagonizing oxytocin in mice are similarly obesogenic. Synaptotagmin-4 inhibition prevents against dietary obesity by normalizing oxytocin release and energy balance under chronic nutritional excess. In conclusion, the negative regulation of synaptotagmin-4 on oxytocin release represents a hypothalamic basis of neuropeptide exocytosis in controlling obesity and related diseases.

Study design: A systematic review. Background: The number of traumatic spinal cord injury (TSCI) reports grows annually, especially in China and Korea. The epidemiological characteristics of TSCI in Asia differ from those in other countries. Thus, we compiled epidemiological factors from Asia to compare with those from other countries. Method: We searched articles published in any language between January 1980 to December 2011 using the terms "spinal cord injury", "traumatic spinal cord injury", "epidemiology", and "Asia". The articles were reviewed for information regarding TSCI incidence, total cases, case criteria, case source, causes of injury, male/female ratio, mean age, prospective or retrospective, neurological level of injury, extent of injury, and America Spinal Injury Association Impairment Scale (AIS)/grade. Results: Epidemiological data were extracted from 39 reports in the published literature that met the inclusion criteria. Only two studies reported prevalence rates. Incidence rates ranged from 12.06 to 61.6 per million. The average age ranged from 26.8 to 56.6 years old. Men were at higher risk than women. Motor vehicle collisions (MVCs) and falls were the main causes of TSCI. However, several countries reported war wounds as the major cause. The neurological level and extent of injury were mixed, and most patients were categorized as AIS/Frankel grade A. Conclusion: TSCI is an important public health problem and a major cause of paralysis. We must understand the epidemiology to implement appropriate preventative measures. Asian epidemiology is different from that in other regions, so intervention measures must be established according to population-specific characteristics.

Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR is trained for real-time image quality assessment, lesion detection and grading using 466,247 fundus images from 121,342 patients with diabetes. Evaluation is performed on a local dataset with 200,136 fundus images from 52,004 patients and three external datasets with a total of 209,322 images. The area under the receiver operating characteristic curves for detecting microaneurysms, cotton-wool spots, hard exudates and hemorrhages are 0.901, 0.941, 0.954 and 0.967, respectively. The grading of diabetic retinopathy as mild, moderate, severe and proliferative achieves area under the curves of 0.943, 0.955, 0.960 and 0.972, respectively. In external validations, the area under the curves for grading range from 0.916 to 0.970, which further supports the system is efficient for diabetic retinopathy grading.

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Timely detection and treatment of microaneurysms is a critical step to prevent the development of vision-threatening eye diseases such as diabetic retinopathy. However, detecting microaneurysms in fundus images is a highly challenging task due to the low image contrast, misleading cues of other red lesions, and the large variation of imaging conditions. Existing methods tend to fail in face of the large intra-class variation and small inter-class variations for microaneurysm detection in fundus images. Recently, hybrid text/image mining computer-aided diagnosis systems have emerged to offer a promise of bridging the semantic gap between images and diagnostic information. In this paper, we focus on developing an interleaved deep mining technique to cope intelligently with the unbalanced microaneurysm detection problem. Specifically, we present a clinical report guided multi-sieving convolutional neural network, which leverages a small amount of supervised information in clinical reports to identify the potential microaneurysm regions via the image-to-text mapping in the feature space. These potential microaneurysm regions are then interleaved with fundus image information for multi-sieving deep mining in a highly unbalanced classification problem. Critically, the clinical reports are employed to bridge the semantic gap between low-level image features and high-level diagnostic information. We build an efficient microaneurysm detection framework based on the hybrid text/image interleaving and validate its performance on challenging clinical data sets acquired from diabetic retinopathy patients. Extensive evaluations are carried out in terms of fundus detection and classification. Experimental results show that our framework achieves 99.7% precision and 87.8% recall, comparing favorably with the state-of-the-art algorithms. Integration of expert domain knowledge and image information demonstrates the feasibility of reducing the difficulty of training classifiers under extremely unbalanced data distributions.

Hyperglycemia was a strong risk factor for diabetic retinopathy. In pre-diabetic subjects, diabetic retinopathy was also associated with hypertension and obesity.

Vitamin D deficiency is an independent risk factor for diabetic retinopathy and sight-threatening diabetic retinopathy. The prevalence of sight-threatening diabetic retinopathy doubles when the serum 25-hydroxyvitamin D level is < 15.57 ng/ml.

The platelet is considered as an accessible and valuable tool to study mitochondrial function, owing to its greater content of fully functional mitochondria compared with other metabolically active organelles. Different lines of studies have demonstrated that mitochondria in platelets have function far more than thrombogenesis regulation, and beyond hemostasis, platelet mitochondrial dysfunction has also been used for studying mitochondrial-related diseases. In this review, the interplay between platelet mitochondrial dysfunction and oxidative stress, mitochondrial DNA lesions, electron transfer chain impairments, mitochondrial apoptosis and mitophagy has been outlined. Meanwhile, considerable efforts have been made towards understanding the role of platelet mitochondrial dysfunction in human diseases, such as diabetes mellitus, sepsis and neurodegenerative disorders. Alongside this, we have also articulated our perspectives on the development of potential biomarkers of platelet mitochondrial dysfunction in mitochondrial-related diseases.