The Efficacy and Safety Profile of Netarsudil 0.02% in Glaucoma Treatment: Real-World Outcomes

Introduction: More effective glaucoma medications are necessary as medication intolerance and non-adherence remain problematic. Netarsudil is a newly FDA-approved Rho kinase inhibitor. We hypothesize that netarsudil will safely reduce intraocular pressure (IOP) compared to baseline even while other glaucoma medications are used. Methods: This retrospective observational study was conducted on glaucoma patients seen at the Wills Eye Hospital Glaucoma Service who received netarsudil 0.02% between March and September of 2018. Intraocular pressure (IOP, via Goldmann applanation tonometry) and best corrected visual acuity (BCVA, via Snellen visual acuity charts) comparisons between baseline and 1- and 3-month follow-up visits were performed using Student’s t-tests. Results: This study included 172 eyes of 108 patients. Compared to baseline, a mean±SD decrease in IOP of 3.67±4.91 and 3.91±4.83 mmHg was noted at 1- and 3-month follow-up visits, respectively (both p\u3c0.001). No statistically significant difference in IOP change between patients on ≥3 and \u3c3 glaucoma medications at month 1 was observed (p=0.667). Conjunctival hyperemia was the most common side effect at months 1 and 3 (15.7% and 23.0% of patients, respectively). Blurred vision was reported at 1- and 3-month follow-up (5.8% and 8.0% of patients, respectively), but no significant difference in BCVA was observed (p= 0.723 and 0.611, respectively). Discussion: With a mild side effect profile, netarsudil yielded a significant IOP reduction in glaucoma patients, including significant reductions in patients on ≥3 medications. Given its efficacy and unique mechanism of action, earlier-line use of netarsudil may be considered

6-Year Experience of Outpatient Total and Completion Thyroidectomy

Outpatient thyroidectomy has become slowly accepted with various published reports predominantly examining partial or subtotal thyroidectomy. Concerns regarding the safety of outpatient total and completion thyroidectomy remain, especially in regards to vocal fold paralysis, hypocalcemia, and catastrophic hematoma. We aimed to evaluate the safety of outpatient thyroid surgery in a large cohort. We conducted a retrospective review comparing outcomes in those who underwent outpatient (n=251) versus inpatient (n= 291) completion or total thyroidectomy between February 2009 and February 2015. Outpatient completion and total thyroidectomy had lower rates of temporary hypocalcemia (6% vs. 24.4%; p\u3c 0.001) and no significant difference in rates of return to emergency department (1.2% vs. 1.4%), hematoma formation (0.8% vs. 0.7%), temporary (2% vs. 4.1%) or permanent (0.4% vs. 0.7%) vocal fold paralysis, or permanent hypocalcemia (0.4% vs. 0%) compared to the inpatient group. Outpatients requiring calcium replacement had shorter duration of postoperative calcium supplementation (44.4±59.3 days vs. 63.3 ±94.4 days; p \u3c 0.001). Our data demonstrates similar safety in outpatient and inpatient total and completion thyroidectomy

Ahmed vs Baerveldt Glaucoma Drainage Device in Uveitic Glaucoma

Introduction: Uveitis is an inflammatory eye disorder which may elevate intraocular pressure (IOP), causing sight-threatening glaucoma. Treatment of refractory uveitic glaucoma involves implantation of a glaucoma drainage device (GDD). Uveitic glaucoma has been a minority diagnosis in prior studies comparing the valved Ahmed GDD and non-valved Baerveldt GDD. Here we compare the safety and efficacy of the Ahmed and Baerveldt GDD in uveitic glaucoma. Methods: This retrospective comparative study was conducted on patients with uveitic glaucoma (≥14 years old) who underwent Ahmed or Baerveldt GDD implantation between 2006–2018 with a minimum follow-up of 3 months. Success was defined as IOP of 6-21 mmHg with (complete success) or without (qualified success) medications, with at least light perception vision and no further glaucoma surgery. Pearson Chi-squared test, independent t test, and Kaplan-Meier survival model were utilized for statistical analysis. Results: 137 eyes of 122 patients (67 Ahmed and 70 Baerveldt) were included. Baseline characteristics were comparable in both groups. The Baerveldt group experienced greater IOP reduction (60.3% vs. 44.5%), higher complete success rate (28.6% vs. 10.4%), higher complication rate (44.3% vs. 20.9%), and higher hypotony rate (10% vs. 0%) than the Ahmed group (all p values \u3c0.05). Discussion: Our results are in line with pooled analysis of previous GDD comparison studies on various types of glaucoma. For patients with uveitic glaucoma, the Baerveldt implant provided a significantly higher success rate and greater IOP reduction with fewer medications, but was associated with a higher complication rate, compared to the Ahmed implant

Educational Programs and Adaptability: A Systems Approach to Creating Adaptable Educational Programs

The IUSM Scholarly Concentrations Program is an optional four-year longitudinal program that allows students to explore interests outside the core medical curriculum. In two years, 17 concentrations were developed statewide and more than 220 students enrolled. As a part of developing a sustainable educational program, a Plan-Do-Check-Act improvement cycle is being used. This workshop will feature examples of the use of the Plan-Do-Check-Act improvement cycle during the launch and pilot a large, novel educational program that is “good enough” and builds toward sustainability and excellence while responding to large-scale systematic changes. Participants in the workshop will apply these principles to their own educational programs

WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster Images

Incorporating deep learning (DL) classification models into unmanned aerial vehicles (UAVs) can significantly augment search-and-rescue operations and disaster management efforts. In such critical situations, the UAV's ability to promptly comprehend the crisis and optimally utilize its limited power and processing resources to narrow down search areas is crucial. Therefore, developing an efficient and lightweight method for scene classification is of utmost importance. However, current approaches tend to prioritize accuracy on benchmark datasets at the expense of computational efficiency. To address this shortcoming, we introduce the Wider ATTENTION EfficientNet (WATT-EffNet), a novel method that achieves higher accuracy with a more lightweight architecture compared to the baseline EfficientNet. The WATT-EffNet leverages width-wise incremental feature modules and attention mechanisms over width-wise features to ensure the network structure remains lightweight. We evaluate our method on a UAV-based aerial disaster image classification dataset and demonstrate that it outperforms the baseline by up to 15 times in terms of classification accuracy and $38.3\%$ in terms of computing efficiency as measured by Floating Point Operations per second (FLOPs). Additionally, we conduct an ablation study to investigate the effect of varying the width of WATT-EffNet on accuracy and computational efficiency. Our code is available at \url{https://github.com/TanmDL/WATT-EffNet}.Comment: This paper is accepted in IEEE Trans. GRS

Unlocking the capabilities of explainable fewshot learning in remote sensing

Recent advancements have significantly improved the efficiency and effectiveness of deep learning methods for imagebased remote sensing tasks. However, the requirement for large amounts of labeled data can limit the applicability of deep neural networks to existing remote sensing datasets. To overcome this challenge, fewshot learning has emerged as a valuable approach for enabling learning with limited data. While previous research has evaluated the effectiveness of fewshot learning methods on satellite based datasets, little attention has been paid to exploring the applications of these methods to datasets obtained from UAVs, which are increasingly used in remote sensing studies. In this review, we provide an up to date overview of both existing and newly proposed fewshot classification techniques, along with appropriate datasets that are used for both satellite based and UAV based data. Our systematic approach demonstrates that fewshot learning can effectively adapt to the broader and more diverse perspectives that UAVbased platforms can provide. We also evaluate some SOTA fewshot approaches on a UAV disaster scene classification dataset, yielding promising results. We emphasize the importance of integrating XAI techniques like attention maps and prototype analysis to increase the transparency, accountability, and trustworthiness of fewshot models for remote sensing. Key challenges and future research directions are identified, including tailored fewshot methods for UAVs, extending to unseen tasks like segmentation, and developing optimized XAI techniques suited for fewshot remote sensing problems. This review aims to provide researchers and practitioners with an improved understanding of fewshot learnings capabilities and limitations in remote sensing, while highlighting open problems to guide future progress in efficient, reliable, and interpretable fewshot methods.Comment: Under review, once the paper is accepted, the copyright will be transferred to the corresponding journa

Effect of Co catalyst on PECVD growth of carbon nanotubes for NEMS applications

In this paper the effect of cobalt (Co) catalyst on the growth of carbon nanotubes (CNTs) was studied. CNTs were vertically grown by plasma enhanced chemical vapor deposition method (PECVD) at 700°C with various sputtered Co catalyst thicknesses. Experimental results shows that for carbon nanotube growth duration of 20 minutes, growth was only achieved with thinner catalyst layers but when the growth duration was doubled, high density of CNTS were also observed with thicker catalyst layers with taller nanotubes formed. The nucleation of the catalyst with various thicknesses was also studied as the absorption of the carbon feedstock is dependent on the initial size of the catalyst island

Functional characterization of C. elegans Y-box-binding proteins reveals tissue-specific functions and a critical role in the formation of polysomes

The cold shock domain is one of the most highly conserved motifs between bacteria and higher eukaryotes. Y-box-binding proteins represent a subfamily of cold shock domain proteins with pleiotropic functions, ranging from transcription in the nucleus to translation in the cytoplasm. These proteins have been investigated in all major model organisms except Caenorhabditis elegans. In this study, we set out to fill this gap and present a functional characterization of CEYs, the C. elegans Y-box-binding proteins. We find that, similar to other organisms, CEYs are essential for proper gametogenesis. However, we also report a novel function of these proteins in the formation of large polysomes in the soma. In the absence of the somatic CEYs, polysomes are dramatically reduced with a simultaneous increase in monosomes and disomes, which, unexpectedly, has no obvious impact on animal biology. Because transcripts that are enriched in polysomes in wild-type animals tend to be less abundant in the absence of CEYs, our findings suggest that large polysomes might depend on transcript stabilization mediated by CEY protein