Risk of congenital anomalies associated with antithyroid treatment during pregnancy: a meta-analysis

To evaluate the association of either propylthiouracil or methimazole treatment for hyperthyroidism during pregnancy with congenital malformations, relevant studies were identified by searching Medline, PubMed, the Cochrane Library and EMBASE. We intended to include randomized controlled trials, but no such trials were identified. Thus, we included cohort studies and case-control studies in this meta-analysis. A total of 7 studies were included in the meta-analyses. The results revealed an increased risk of birth defects among the group of pregnant women with hyperthyroidism treated with methimazole compared with the control group (odds ratio 1.76, 95% confidence interval 1.47-2.10) or the non-exposed group (odds ratio 1.71, 95% confidence interval 1.39-2.10). A maternal shift between methimazole and propylthiouracil was associated with an increased odds ratio of birth defects (odds ratio 1.88, 95% confidence interval 1.27-2.77). An equal risk of birth defects was observed between the group of pregnant women with hyperthyroidism treated with propylthiouracil and the non-exposed group (odds ratio 1.18, 95% confidence interval 0.97-1.42). There was only a slight trend towards an increased risk of congenital malformations in infants whose mothers were treated with propylthiouracil compared with in infants whose mothers were healthy controls (odds ratio 1.29, 95% confidence interval 1.07-1.55). The children of women receiving methimazole treatment showed an increased risk of adverse fetal outcomes relative to those of mothers receiving propylthiouracil treatment. We found that propylthiouracil was a safer choice for treating pregnant women with hyperthyroidism according to the risk of birth defects but that a shift between methimazole and propylthiouracil failed to provide protection against birth defects

On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID

The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there is an increasing demand for the automatic interpretation of these images. In this context, the benchmark datasets serve as essential prerequisites for developing and testing intelligent interpretation algorithms. After reviewing existing benchmark datasets in the research community of RS image interpretation, this article discusses the problem of how to efficiently prepare a suitable benchmark dataset for RS image interpretation. Specifically, we first analyze the current challenges of developing intelligent algorithms for RS image interpretation with bibliometric investigations. We then present the general guidances on creating benchmark datasets in efficient manners. Following the presented guidances, we also provide an example on building RS image dataset, i.e., Million-AID, a new large-scale benchmark dataset containing a million instances for RS image scene classification. Several challenges and perspectives in RS image annotation are finally discussed to facilitate the research in benchmark dataset construction. We do hope this paper will provide the RS community an overall perspective on constructing large-scale and practical image datasets for further research, especially data-driven ones

Paracrine GABA and insulin regulate pancreatic alpha cell proliferation in a mouse model of type 1 diabetes

Aims/hypothesis: This study aimed to elucidate the mechanism of increased proliferation of alpha cells in recent-onset type 1 diabetes. Pancreatic beta cells express GAD and produce γ-aminobutyric acid (GABA), which inhibits alpha cell secretion of glucagon. We explored the roles of GABA in alpha cell proliferation in conditions corresponding to type 1 diabetes in a mouse model and in vitro. Methods: Type 1 diabetes was induced by injecting the mice with streptozotocin (STZ). Some of the STZ-injected mice were treated with GABA (10 mg/kg daily) for 12 days. Isolated pancreatic islets were treated with STZ or STZ together with GABA for 2 days. The effects of GABA treatment on STZ-induced alpha cell proliferation in vivo and in vitro were assessed. The effect of muscimol, a GABA receptor agonist, on αTC1-6 cell proliferation was also examined. Results: STZ injection substantially decreased levels of GAD, GABA and insulin in pancreatic beta cells 12 h after injection; this was followed by an upsurge of phosphorylated mechanistic target of rapamycin (p-mTOR) in the alpha cells at day 1, and a significant increase in alpha cell mass at day 3. Treating STZ-injected mice with GABA largely restored the immunodetectable levels of insulin and GAD in the beta cells and significantly decreased the number of aldehyde dehydrogenase 1 family, member A3 (ALDH1a3)-positive cells, alpha cell mass and hyperglucagonaemia. STZ treatment also increased alpha cell proliferation in isolated islets, which was reversed by co-treatment with GABA. Muscimol, together with insulin, significantly lowered the level of cytosolic Ca2+ and p-mTOR, and decreased the proliferation rate of αTC1-6 cells. Conclusions/interpretation: GABA signalling critically controls the alpha cell population in pancreatic islets. Low intraislet GABA may contribute to alpha cell hyperplasia in early type 1 diabetes

Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events

Scene Dynamic Recovery (SDR) by inverting distorted Rolling Shutter (RS) images to an undistorted high frame-rate Global Shutter (GS) video is a severely ill-posed problem, particularly when prior knowledge about camera/object motions is unavailable. Commonly used artificial assumptions on motion linearity and data-specific characteristics, regarding the temporal dynamics information embedded in the RS scanlines, are prone to producing sub-optimal solutions in real-world scenarios. To address this challenge, we propose an event-based RS2GS framework within a self-supervised learning paradigm that leverages the extremely high temporal resolution of event cameras to provide accurate inter/intra-frame information. % In this paper, we propose to leverage the event camera to provide inter/intra-frame information as the emitted events have an extremely high temporal resolution and learn an event-based RS2GS network within a self-supervised learning framework, where real-world events and RS images can be exploited to alleviate the performance degradation caused by the domain gap between the synthesized and real data. Specifically, an Event-based Inter/intra-frame Compensator (E-IC) is proposed to predict the per-pixel dynamic between arbitrary time intervals, including the temporal transition and spatial translation. Exploring connections in terms of RS-RS, RS-GS, and GS-RS, we explicitly formulate mutual constraints with the proposed E-IC, resulting in supervisions without ground-truth GS images. Extensive evaluations over synthetic and real datasets demonstrate that the proposed method achieves state-of-the-art and shows remarkable performance for event-based RS2GS inversion in real-world scenarios. The dataset and code are available at https://w3un.github.io/selfunroll/

Newton-Cartan Gravity and Torsion

We compare the gauging of the Bargmann algebra, for the case of arbitrary torsion, with the result that one obtains from a null-reduction of General Relativity. Whereas the two procedures lead to the same result for Newton-Cartan geometry with arbitrary torsion, the null-reduction of the Einstein equations necessarily leads to Newton-Cartan gravity with zero torsion. We show, for three space-time dimensions, how Newton-Cartan gravity with arbitrary torsion can be obtained by starting from a Schroedinger field theory with dynamical exponent z=2 for a complex compensating scalar and next coupling this field theory to a z=2 Schroedinger geometry with arbitrary torsion. The latter theory can be obtained from either a gauging of the Schroedinger algebra, for arbitrary torsion, or from a null-reduction of conformal gravity.Comment: 21 page

Clinicopathological features and CCT2 and PDIA2 expression in gallbladder squamous/adenosquamous carcinoma and gallbladder adenocarcinoma

BACKGROUND: Gallbladder cancer (GBC) is a relatively uncommon carcinoma among gastrointestinal cancers and usually has a rather poor prognosis. The most common subtype of GBC is adenocarcinoma (AC), which accounts for about 90% of GBC. Squamous carcinoma/adenosquamous carcinoma (SC/ASC) are comparatively rare histopathological subtypes of GBC. The clinicopathological features and biological behaviors of SC/ASC have not been well-characterized. No molecular biomarkers are currently available for predicting the progression, metastasis, and prognosis of the SC/ASC subtype of GBC. METHODS: We examined the expression levels of CCT2 and PDIA3 by immunohistochemistry (IHC) staining in human GBC tissue samples collected from 46 patients with SC/ASC and evaluated the clinicopathological significance of both CCT2 and PDIA3 expression in the SC/ASC subtypes of GBC by Kaplan-Meier analysis and multivariate Cox regression analysis. For comparison, we included specimens from 80 AC patients in our study to investigate the specificity of CCT2 and PDIA3 expression in GBC subtypes. RESULTS: We found that the positive expression of CCT2 and PDIA3 was significantly associated with clinicopathological features of both SC/ASC and AC specimens, including high TNM stage and lymph node metastasis. Univariate analysis revealed that the two-year survival rate was significantly lower for patients with positive expression of CCT2 and PDIA3 than for those with negative expression. Multivariate analysis also indicated that the positive expression of CCT2 and PDIA3 was negatively correlated with poor postoperative patient survival and positively correlated with high mortality. CONCLUSIONS: Our study suggests that positive expression of CCT2 or PDIA3 is associated with tumor progression and the clinical behavior of gallbladder carcinoma. Therefore, CCT2 and PDIA3 could be potentially important diagnostic and prognostic biomarkers for both SC/ASC and AC subtypes of GBC

利培酮合并舒眠胶囊治疗精神分裂症的疗效及对患者糖、脂代谢的影响

Objective: To explore the curative effect and influence on glucose and lipid metabolism of risperidone with Shu Mian capsules in patients with schizophrenia .Methods: 128patients with chronic schizophrenia were randomly divided into the combined group (crisperidone combined with shu mian capsules group) and the single group (risperidone group ), each group was assessed the positive and negative syndrome scale (PANSS),the body mass index (BMI ) was measured and the blood glucose and blood lipid were detected before treatment and after 2,4,8 weekends respectively. After 4,8 weeks ,both the two groups were assessed by Wesconsin card sorting test ( WCST) curative effect and their cognitive function was evaluated .Results: The reacting time in the two groups were of no significantly difference , but compared with condition before treatment, cognitive function of the patients with schizophrenia was improved and their level of total cholesterol was significantly increased (P < 0.05) in the combined group. BMI, blood glucose and blood lipid were significantly increased in single group after 8weeks’ treatment (P < 0.05 or P < 0.01). Conclusion: Shu Mian capsules can lower negative symptoms and improve cognitive function of schizophrenia ,and the dverse reactions is mild. With therapeutic dose range, risperidone in combined group or single group can make equal reacting time, curative effect and affecting blood lipid metabolism in patients with schizophrenia. Single group shows more obvious influence on blood sugat and blood fat metabolismcan.目的  探讨利培酮合并舒眠胶囊治疗慢性精神分裂症的疗效及对患者糖、脂代谢的影响。方法  128例精神分裂症患者采用系统随机分为联合组（利培酮合并舒眠胶囊组）和单用组（利培酮组）。每组各64例分别于治疗前及治疗2、4、8周末采用阳性与阴性症状量表（PANSS）进行评分，并检测体质量指数（BMI）、血糖及血脂；4、8周末评价认知能力及疗效。结果  联合组和单用组起效时间比较差异无统计学意义；联合组能部分改善精神分裂症患者的认知能力，与治疗前相比8周未联合组总胆固醇明显增高（P＜0.05）；单用组BMI、血糖、总胆固醇和甘油三酯明显增高（P＜0.05 或P＜0.01）。结论  舒眠胶囊对精神分裂症阴性症状和认知功能有一定改善作用，不良反应轻微。利培酮治疗精神分裂症的剂量范围内联合组和单用组起效时间相当，但均可影响脂代谢；单用组对血糖、血脂代谢的影响更明显。 

Mutation of SLC35D3 causes metabolic syndrome by impairing dopamine signaling in striatal D1 neurons

We thank Dr. Ya-Qin Feng from Shanxi Medical University, Dr. Tian-Yun Gao from Nanjing University and Dr. Yan-Hong Xue from Institute of Biophysics (CAS) for technical assistance in this study. We are very thankful to Drs. Richard T. Swank and Xiao-Jiang Li for their critical reading of this manuscript and invaluable advice. Funding: This work was partially supported by grants from National Basic Research Program of China (2013CB530605; 2014CB942803), from National Natural Science Foundation of China 1230046; 31071252; 81101182) and from Chinese Academy of Sciences (KSCX2-EW-R-05, KJZD-EW-L08). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD