Elucidating the Role of HAUSP Ubiquitin Like Domains in the Catalytic Function of USP7

Ubiquitin specific proteases (USPs) are a class of enzymes involved in myriad cellular processes. One USP of great interest due to its oncogenic properties is USP7. In normal conditions USP7 is closely regulated due to its responsibility for destabilizing the tumor suppressor, p53, through the deubiquitination of MDM2. In multiple myeloma cases, it appears the regulation of USP7 subsides, as it is largely overexpressed, leading to the inappropriate degradation of p53. Inhibition of USP7 could, therefore, prove a viable target for cancer therapy. A greater understanding of USP7’s function and structure can lead to more insight into how this enzyme could be inhibited. USP7 is composed of the TRAF, catalytic and 5 HUBL domains. Previous work has shown that the catalytic activity of USP7 is greatly reduced in the absence of the HUBL 4 and 5 (H-45) domains. However, it is unclear if the other HUBL domains have specific roles in USP7 activity. To evaluate the individual HUBL domain roles in USP7s activity, constructs containing the full length HUBL domain, as well as just H-45 truncations were obtained. Each construct was expressed in E. coli BL21 (DE3) cells and purified by chromatography. These constructs were left with their respective histidine tags in order to evaluate the kinetics of their interactions in trans with the catalytic domain using the Fortebio Octet Red 384 system. Kinetic assays using the ubiquitin rhodamine substrate showed that the histidine tagged proteins are still able to activate the catalytic domain of USP7. Optimization of the Fortebio Octet Red 384 system suggested that the catalytic domain bound nonspecifically to the Anti-Penta-His (HIS1K) obscuring the off binding rates of the HUBL protein. Further truncations of the HUBL domains including H1, H2, H3, H1-2 were successfully subcloned using recombinant cloning techniques and will be analyzed using the Octet system

Planning for autonomous vehicles : effects and optimal placement of reservation-based intersections in urban networks

Connected and autonomous vehicle (CAV) technologies can revolutionize the way we transport people and goods and may soon be publicly available, however proper planning for these technologies is crucial to their successful integration into our transportation systems. CAVs can reduce following headways and increase roadway capacity and stability, as well as allow for new, more efficient intersection controls with wireless communication capabilities. This work is twofold: (1) evaluating the traffic congestion impacts of AVs and reservation-based intersection control on real large-scale city networks in Texas using DTA and (2) developing methods to find optimal configurations of reservations and signals in a city network. The first part of this thesis evaluates CAV behavior impacts by simulating different mixed CAV and human vehicle (HV) demand scenarios. Results show improvements in network efficiency with increases in CAV penetration. Reservations were observed to perform better than signals in most scenarios. Namely, the Austin downtown network resulted in a 78% reduction in travel time. However, signals outperformed reservations in some high demand cases on arterial networks due to the reservation's first-come-first-serve (FCFS) policy allocating more capacity to local roads, resulting in arterial progression interruption and queue spillback onto close-proximity streets. The discovered paradoxical effects imply that some intersections are better suited for reservation control than others. The second part of this thesis finds and characterizes favorable mixed-configurations of reservation-based controls and signalized controls in a large city network which minimize total system travel times. As this optimization problem is bi-level and challenging, we propose three different methods to heuristically find effective mixed-configurations. The first method is an intersection ranking method uses simulation to assign a score to each intersection in a network based on localized potential benefit to system travel time under reservation control and then ranks all intersections accordingly. The second is another ranking method, however uses linear regression to predict an intersection's localized score. Finally, we present a genetic algorithm which iteratively approaches high-performing network configurations yielding minimal system travel times. We test the methods on the downtown Austin network and find configurations which are less than half controlled by reservation intersections that improve travel times beyond an all-reservation controlled network. Overall, our results show that the genetic algorithm finds the best performing configurations with the initial score-assigning ranking method performing similarly but much more efficiently. We finally find that favorable reservation placement is in consecutive chains along highly trafficked corridors.Civil, Architectural, and Environmental Engineerin

Evaluation of relationship between timing of surgery and functional outcome considering the extent of neurological deficit in patients with cauda equina syndrome secondary to lumbar disc herniation

Background: Cauda equina syndrome (CES) is a rare but severe neurological disorder most commonly due to lumbar disc herniation. The role of urgent surgery in improving the outcome of patients with CES remains controversial.Methods: In the present study retrospective evaluation of 44 patients with CES secondary to lumbar disc herniation treated at our hospital between 2009 and 2017 has been done. The patients were categorized into complete (CES-R) and incomplete (CES-I) types of CES and the relationship between timing of surgery and outcome were evaluated.Results: Out of 44 patients, 28 patients presented with CES-I and 16 patients presented with CES-R. In patients with CES-I there was statistically significant difference (p=0.0001) in all observed surgical outcome between the patients operated within 48 hrs and those operated after 48 hrs. In patients with CES-R, no correlation was found between onset of symptoms and timing of surgery as recovery was partial in all the patients except 3 who completely recovered, irrespective of their operative times. (p=0.494).Conclusions: Early diagnosis and treatment in form of emergency decompressive surgery done within 48 hours of onset of autonomic symptoms in CES-I patients can prevent further neurological damage and deterioration to CES-R. For CES-R patients operating within 48 hours made no difference to their outcome. However, necessary investigations and planned surgery by skilful surgeon should be arranged as soon as is reasonably possible for patients with CES-R.

Rescuing referral failures during automated diagnosis of domain-shifted medical images

The success of deep learning models deployed in the real world depends critically on their ability to generalize well across diverse data domains. Here, we address a fundamental challenge with selective classification during automated diagnosis with domain-shifted medical images. In this scenario, models must learn to avoid making predictions when label confidence is low, especially when tested with samples far removed from the training set (covariate shift). Such uncertain cases are typically referred to the clinician for further analysis and evaluation. Yet, we show that even state-of-the-art domain generalization approaches fail severely during referral when tested on medical images acquired from a different demographic or using a different technology. We examine two benchmark diagnostic medical imaging datasets exhibiting strong covariate shifts: i) diabetic retinopathy prediction with retinal fundus images and ii) multilabel disease prediction with chest X-ray images. We show that predictive uncertainty estimates do not generalize well under covariate shifts leading to non-monotonic referral curves, and severe drops in performance (up to 50%) at high referral rates (>70%). We evaluate novel combinations of robust generalization and post hoc referral approaches, that rescue these failures and achieve significant performance improvements, typically >10%, over baseline methods. Our study identifies a critical challenge with referral in domain-shifted medical images and finds key applications in reliable, automated disease diagnosis

Ovarian hyper stimulation syndrome in a spontaneous singleton pregnancy: a case report

Ovarian hyper stimulation syndrome (OHSS) is extremely rare in spontaneous pregnancies. Spontaneous OHSS can result from glycoprotein hormones stimulating follicle-stimulating hormone receptors (FSHR). Our case reinforces the importance of a prompt diagnosis and management in all pregnant patients presenting with acute abdomen and ovarian masses. We report a case of spontaneous singleton pregnancy at 12-week POG presented with abdominal distension and enlarged ovaries. Patient was successfully managed with supportive treatment comprise of intravenous (IV) Albumin, thromboprophylaxis, dopamine agonist and insulin sensitizer. Spontaneous OHSS should be included in the differential diagnosis of acute abdomen in pregnant women. Since spontaneous OHSS can be associated with life-threatening complications, it requires early diagnosis for successful management. The etiology should be determined in order to focus the treatment and avoid future complications.

Correlation of non-stress test with fetal outcome in term of apgar score: a prospective observation study

Background: The objectives of antepartum fetal surveillance are to prevent fetal death and avoidance of unnecessary intervention. This study using NST as a tool for routine antepartum fetal surveillance is we will be trying to catch up those fetuses who might be at risk in womb and provide prompt intervention in otherwise considered normal pregnancies without any obvious high-risk factor thus giving the best outcome in mothers.Methods: The objective of this study was to evaluate the correlation of the non-stress test with fetal outcome in pregnancies from 37-42 weeks of gestation.  This was a prospective observational study at RNT Medical college Udaipur (Rajasthan) from November 2021 to March 2022. This study included 100 normal pregnant mothers from 37 weeks to 42 weeks who were subjected to NST.Results: The parameters of poor fetal outcome like apgar score <7 at 5 minutes had increased incidences in the non-reactive group.Conclusions: This study suggests that the NST was found to be a good predictor of the healthy foetus even in normal pregnancies between 37-42 weeks of gestation and the probability of an adverse outcome such as poor Apgar score increases with a non-reactive strip

Insilico guided CRISPR-Cas driven enzyme engineering framework: An automated and efficient enzyme engineering method

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Rural Transformation in Gujarat: An Empirical Assessment through Multidimensional Indicators

Rural transformation is one of the key social and economic changes that lead to the development of rural communities and the overall growth of any country. A country like India has diversity in terms of the availability of natural resources, work culture, race, and religion for each geographical state unit with its own pace of growth and development. Gujarat is one of the high-growth states in the country, with Gross State Domestic Product (GSDP) estimates of USD 253.64 billion in FY22 with a 7% YoY increase (India Brand Equity Foundation, n.d.). However, the rural population in Gujarat fell to 57.4% in 2011 from 62.6% in the 2001 census. This paper tries to assess the rural transformation in Gujarat with multidimensional indices like agriculture, consumption, employment, education, and urbanization that focus on rural transformation with the help of district-level microdata in the broader context of the high economic growth of Gujarat

How much is needed? Patient exposure and curricular education on medical students’ LGBT cultural competency

Background: For medical students, providing exposure to and education about the lesbian, gay, bisexual, and transgender (LGBT) patient population are effective methods to increase comfort, knowledge, and confidence in caring for LGBT people. However, specific recommendations on the number of patient exposures and educational hours that relate to high LGBT cultural competency are lacking. Methods: Medical students (N = 940) at three universities across the United States completed a survey consisting of demographics, experiential variables (i.e., number of LGBT patients and LGBT hours), and the 7-point Likert LGBT-Development of Clinical Skills Scale (LGBT-DOCSS). LGBT-DOCSS scores were stratified by 1-point increments, and experiential variable means were computed per each stratification to characterize the mean LGBT patients and hours of medical students with higher scores and those with lower scores. Results: Medical students reported caring for some LGBT patients annually (M = 6.02, SD = 20.33) and receiving a low number of annual LGBT curricular hours (M = 2.22, SD = 2.85) and moderate number of annual LGBT extracurricular hours (M = 6.93, SD = 24.97). They also reported very high attitudinal awareness (M = 6.54, SD = 0.86), moderate knowledge (M = 5.73, SD = 1.01), and low clinical preparedness (M = 3.82, SD = 1.25). Medical students who cared for 35 or more LGBT patients and received 35 or more LGBT total hours reported significantly higher preparedness and knowledge. Conclusions: Medical students have shortcomings in LGBT cultural competency and limited LGBT patient exposure and education. To improve LGBT cultural competency, medical schools and accrediting bodies should consider providing medical students with at least a total of 35 LGBT patient contacts and 35 LGBT education hours (10 h of required curricular education and 25 h of supplemental education)

Using the new ICD-MM classification system for attribution of cause of maternal death: a retrospective study from a tertiary care hospital of Rajasthan

Background: Sustainable development goal 3 includes an ambitious target of reducing the global maternal mortality rate (MMR) to less than 70 per 100,000 births by 2030. Understanding the causes of and factors contributing to maternal deaths is critically important for development of interventions that reduce the global burden of maternal mortality and morbidity. The International classification of diseases-maternal mortality has proven to be easily applicable and helps clarify the cause of maternal death. Methods: Retrospective study of 100 maternal death cases was done in a tertiary medical centre of Rajasthan from December 2020 to November 2021 for determining the causes of maternal death and their classification according to ICD-MM. Results: A total of 100 maternal mortality cases were analyzed in this study for causes of death. Classification of causes of death according to WHO ICD-MM is represented in study results. Direct causes of maternal deaths were observed in 82 % cases whereas indirect causes were present in remaining 18%. Hypertensive disorders (29%), obstetric haemorrhage (27%) and pregnancy related infection (12%) constituted the major groups of direct cause of maternal deaths whereas systemic infections were the most common indirect cause (15%). During the study period, COVID-19 was attributable to 12 cases of maternal death.Conclusions: Hypertensive disorders (29%), obstetric haemorrhage (27%) and pregnancy related infection (12%) were the major causes of direct obstetric death and systemic infections (15%) was the most common cause of indirect obstetric death. All of these causes are preventable with targeted interventions