Adamsenmcmahan1315

To report the outcomes of gonioscopy-assisted transluminal trabeculotomy (GATT) for juvenile-onset primary open-angle glaucoma (JOAG).

A consecutive case series of JOAG patients who underwent GATT was reviewed with follow-up period of up to 18 months. Intraocular pressure (IOP), number of glaucoma medications and success rate were compared between eyes with and without prior glaucoma surgery, and between mild-to-moderate and severe cases defined based on Humphrey Visual Field mean deviation.

In total, 59 eyes of 48 patients were included. Overall, IOP was reduced from 26.5 ± 9.0 mmHg on 3.7 ± 0.9 medications preoperatively to 14.7 ± 3.0 mmHg on 0.7 ± 1.2 medications at 12 months and to 14.1 ± 2.3 mmHg on 0.4 ± 0.8 medications at 18 months postoperatively (P < 0.001). The complete and qualified success rates were 70.8% and 81.2% at 12 months, and 58.6% and 81.2% at 18 months, respectively. Eyes with and without prior glaucoma surgery did not differ significantly in terms of postoperative IOP, glaucoma medication and success rate. In addition, GATT was effective for both mild-to-moderate and severe cases; the latter achieved a surgical success of 79.1%.

GATT is effective for JOAG. In particular, this case series suggests that GATT is promising in treating severe JOAG and those with prior glaucoma surgery.

GATT is effective for JOAG. In particular, this case series suggests that GATT is promising in treating severe JOAG and those with prior glaucoma surgery.We report experiments on crystallization of highly undercooled forsterite melt droplets under atmospheric and sub-atmospheric pressure conditions. Experiments have been conducted under non-contact conditions using the principles of aero-dynamic levitation. Real time dynamics of solidification, along with the transient evolution of surface textures, have been recorded using high speed camera for three cooling rates. These images have been matched with the time-tagged temperature data to understand the effect of pressure conditions and cooling rates on the crystallization dynamics. Compared to normal pressure, relatively higher levels of undercooling could be achieved under sub-atmospheric conditions. Results showed a strong dependence of surface textures on pressure conditions. For any externally employed cooling rate, relatively small length scale morphological textures were observed under sub-atmospheric conditions, in comparison to those achieved under ambient conditions. The observed trends have been explained on the basis of influence of pressure conditions on recalescence phenomenon and the rate at which latent heat of crystallization gets dissipated from the volume of the molten droplet. Sub-atmospheric experiments have also been performed to reproduce one of the classical chondrule textures, namely the rim + dendrite double structure. Possible formation conditions of this double structure have been discussed vis-à-vis those reported in the limited literature. To the best of our knowledge, the reported study is one of the first attempts to reproduce chondrules-like textures from highly undercooled forsterite melt droplets under sub-atmospheric non-contact conditions.The number of critically ill patients has increased globally along with the rise in emergency visits. this website Mortality prediction for critical patients is vital for emergency care, which affects the distribution of emergency resources. Traditional scoring systems are designed for all emergency patients using a classic mathematical method, but risk factors in critically ill patients have complex interactions, so traditional scoring cannot as readily apply to them. As an accurate model for predicting the mortality of emergency department critically ill patients is lacking, this study's objective was to develop a scoring system using machine learning optimized for the unique case of critical patients in emergency departments. We conducted a retrospective cohort study in a tertiary medical center in Beijing, China. Patients over 16 years old were included if they were alive when they entered the emergency department intensive care unit system from February 2015 and December 2015. Mortality up to 7 days after admission into the emergency department was considered as the primary outcome, and 1624 cases were included to derive the models. Prospective factors included previous diseases, physiologic parameters, and laboratory results. Several machine learning tools were built for 7-day mortality using these factors, for which their predictive accuracy (sensitivity and specificity) was evaluated by area under the curve (AUC). The AUCs were 0.794, 0.840, 0.849 and 0.822 respectively, for the SVM, GBDT, XGBoost and logistic regression model. In comparison with the SAPS 3 model (AUC = 0.826), the discriminatory capability of the newer machine learning methods, XGBoost in particular, is demonstrated to be more reliable for predicting outcomes for emergency department intensive care unit patients.The human brain organoids derived from pluripotent cells are a new class of three-dimensional tissue systems that recapitulates several neural epithelial aspects. Brain organoids have already helped efficient modeling of crucial elements of brain development and disorders. Brain organoids' suitability in modeling glioma has started to emerge, offering another usefulness of brain organoids in disease modeling. Although the current state-of-the organoids mostly reflect the immature state of the brain, with their vast cell diversity, human brain-like cytoarchitecture, feasibility in culturing, handling, imaging, and tractability can offer enormous potential in reflecting the glioma invasion, integration, and interaction with different neuronal cell types. Here, we summarize the current trend of employing brain organoids in glioma modeling and discuss the immediate challenges. Solving them might lay a foundation for using brain organoids as a pre-clinical 3D substrate to dissect the glioma invasion mechanisms in detail.Ileal epithelial cell apoptosis and the local microbiota modulate the effects of oxaliplatin against proximal colon cancer by modulating tumor immunosurveillance. Here, we identified an ileal immune profile associated with the prognosis of colon cancer and responses to chemotherapy. The whole immune ileal transcriptome was upregulated in poor-prognosis patients with proximal colon cancer, while the colonic immunity of healthy and neoplastic areas was downregulated (except for the Th17 fingerprint) in such patients. Similar observations were made across experimental models of implanted and spontaneous murine colon cancer, showing a relationship between carcinogenesis and ileal inflammation. Conversely, oxaliplatin-based chemotherapy could restore a favorable, attenuated ileal immune fingerprint in responders. These results suggest that chemotherapy inversely shapes the immune profile of the ileum-tumor axis, influencing clinical outcome.