Faculty Bibliography

OBJECTIVES/OBJECTIVE:This study investigates the prevalence of the use of reusable menstrual materials in LMICs, examines differences in prevalence between countries and areas, and identifies individual and country-level factors associated with their use. METHODS:Data from Multiple Indicator Cluster surveys conducted between 2017 and 2020 in LMICs were used. Prevalence estimates and 95% CIs were calculated for overall, rural, and urban areas. Multivariable logistic regression was used to identify individual and country-level factors associated with the use of reusable menstrual materials. RESULTS:The study included 42 surveys from LMICs, with 1653850 weighted women and girls aged 15-49 years. The overall prevalence of the use of reusable menstrual materials was 12.1% (95% CI 12.1-12.2), with significant variation between and within countries, ranging from 0.5% (0.3-0.8) in Serbia to 97.2% (96.5-97.9) in Sao Tome and Principe. The prevalence was higher in rural areas (23.9% [23.8-24.0]) than in urban areas (6.2% [6.2-6.2]), with significant differences between most countries. Use of reusable menstrual materials was associated with lower education levels, being married, low economic status, living in Asia and Africa, living in countries with lower GDP, living in rural areas, and limited availability of private places to wash menstrual materials. The prevalence of the use of reusable menstrual materials had an inverse linear relationship with the country's GDP. CONCLUSIONS:The study found that the use of reusable menstrual materials is more prevalent among women and girls in rural areas, those with lower education levels, lower economic status, and those living in countries with lower GDP. Given these disparities, policies and initiatives targeted at improving menstrual health in LMICs should focus on socioeconomically disadvantaged groups to ensure they have access to safe and appropriate menstrual materials.

The small island nations, territories, and states dotting the Pacific are among the most disproportionately affected populations worldwide in the face of climate change. Sea level rise coupled with increased tropical storms contribute to seawater incursion, flooding, personal injury, trauma, and death. They face an existential threat due to the consequences of global warming, specifically ice melt resulting in sea level rise, repercussions for which they are not historically culpable. Along with these environmental threats, Pacific Island communities are further burdened with high rates of adverse health conditions such as diabetes and obesity yet have limited healthcare resources due to minimal economic development. The Republic of the Marshall Islands (RMI) has one of the highest amputation rates worldwide due to advanced diabetes from lifestyle factors, limited healthcare infrastructure, financial disparities, and a culturally based hesitancy to seek medical attention, all of which lead to an increased incidence of diabetic complications. Challenges posed by non-communicable chronic diseases include diabetes and infectious diseases like tuberculosis, hepatitis, malaria, and Zika. Just as crucial to the narrative of the Marshallese people is a fundamental indigenous knowledge of their surroundings and an inseparable relationship to the environment, aquatic animals, and communities around them, denoting a holistic living system. Though the outlook is precarious, solutions centering on lifestyle interventions that are informed by Indigenous cultural strengths can provide a responsive framework and a ray of hope, offering potential solutions to these two. This short perspective highlights the RMI as a case study of the challenges the Pacific Island nations bear, from a legacy of annexation to the modern threat of climate change, compounded by health disparities.

In 2022, 1 in 8 people in the world were living with obesity, and lifestyle interventions that include diet, exercise, and behavioral modification have been the foundation for management of obesity. Recently, pharmacologic therapies have been developed for management of obesity, the newest of these being glucagon-like peptide 1 receptor agonists. With the development of new pharmacologic options, the American Gastroenterological Association developed a guideline in 2022 to provide evidence-based recommendations for the pharmacologic management of obesity in adults and recommended, for adults with obesity or overweight with weight-related complications who have had an inadequate response to lifestyle interventions, adding pharmacologic agents to lifestyle interventions over continuing lifestyle interventions alone. In this article, 2 experts review the available evidence to answer the following questions: How effective are lifestyle interventions for the treatment of obesity? How effective are pharmacologic interventions for the treatment of obesity? Given these options, how do you engage in a shared decision-making discussion to develop a mutually agreed-on treatment plan?

In the present work, phytoconstituents from Citrus limon are computationally tested against SARS-CoV-2 target protein such as Mpro - (5R82.pdb), Spike - (6YZ5.pdb) &RdRp - (7BTF.pdb) for COVID-19. Docking was done by glide model, QikProp was performed by in silico ADMET screening & Prime MM-GB/SA modules were used to define binding energy. When compared with approved COVID-19 drugs such as Remdesivir, Ritonavir, Lopinavir, and Hydroxychloroquine, plant-based constituents such as Quercetin, Rutoside, Naringin, Eriocitrin, and Hesperidin. bind with significant G-scores to the active SARS-CoV-2 place. The constituents Rutoside and Eriocitrin were studied in each MD simulation in 100 ns against 3 proteins 5R82.pdb, 6YZ5.pdb and 7BTF.pdb.We performed an assay with significant natural compounds from contacts and in silico results (Rutin, Eriocitrin, Naringin, Hesperidin) using 3CL protease assay kit (B.11529 Omicron variant). This kit contained 3CL inhibitor GC376 as Control. The IC₅₀ value of the test compound was found to be Rutin -17.50 μM, Eriocitrin-37.91 μM, Naringin-39.58 μM, Hesperidine-140.20 μM, the standard inhibitory concentration of GC376 was 38.64 μM. The phytoconstituents showed important interactions with SARS-CoV-2 targets, and potential modifications could be beneficial for future development.

OBJECTIVE:The Woven EndoBridge (WEB) device was approved to treat wide-necked bifurcation aneurysms. The device is designed as an intrasaccular flow disruptor covering aneurysm widths up to 10 mm. Although prior studies combined all aneurysm sizes, it is known that aneurysms behave differently in response to endovascular treatment based on their size. Therefore, the authors' objective was to identify ideal middle cerebral artery (MCA) aneurysm width and neck sizes most suitable for WEB treatment. METHODS:The WorldWideWEB consortium is a large multicenter retrospective database that analyzes intracranial aneurysms treated with the WEB device. In this study, all unruptured MCA bifurcation aneurysms with available measurements were included. Cutoff values based on aneurysm width and neck in relation to aneurysm occlusion status were measured using the receiver operating characteristic (ROC) curve. Propensity score matching (PSM) was then used to compare treatment outcomes between aneurysms smaller and larger than the cutoff value for both width and neck size. RESULTS:The ideal cutoff values for MCA bifurcation aneurysm width and neck were 6.1 mm and 4.6 mm, respectively. On PSM, 87 matched pairs were compared based on width size (≤ 6.1 mm and > 6.1 mm), and 77 matched pairs were compared based on neck size (≤ 4.6 mm and > 4.6 mm). There was a significant difference in adequate aneurysm occlusion between aneurysms smaller and larger than those cutoff values for both widths (93% vs 76%, p = 0.0017) and neck sizes (90% vs 70%, p = 0.0026). The retreatment rate was also significantly higher for larger aneurysms in both parameters. CONCLUSIONS:This study shows that MCA bifurcation aneurysms ≤ 6.1 mm in width and ≤ 4.6 mm in neck size are significantly better candidates for WEB treatment, leading to improved occlusion status and reduced retreatment rate, which are important considerations when using WEB devices.

The RAS family GTPases are the most frequently mutated oncogene family in human cancers. Activating mutations in either of the three RAS isoforms (HRAS, KRAS, or NRAS) are found in nearly 20% of all human tumors with NRAS mutated in ~25% of melanomas. Despite remarkable advancements in therapies targeted against mutant KRAS, NRAS-specific pharmacologics are lacking. Thus, development of inhibitors of NRAS would address a critical unmet need to treating primary tumors harboring NRAS mutations as well as BRAF-mutant melanomas, which frequently develop resistance to clinically approved BRAF inhibitors through NRAS mutation. Building upon our previous studies with the monobody NS1 that recognizes HRAS and KRAS but not NRAS, here we report the development of a monobody that specifically binds to both GDP and GTP-bound states of NRAS and inhibits NRAS-mediated signaling in a mutation-agnostic manner. Further, this monobody can be formatted into a genetically encoded NRAS-specific degrader. Our study highlights the feasibility of developing NRAS selective inhibitors for therapeutic efforts.

Those undergoing pregnancy are often excluded from clinical drug trials due to the risk that participation would pose. However, they often require pharmaceuticals to manage health conditions that, if gone untreated, could harm themselves or the fetus. This can mean that such individuals take one or more pharmaceuticals during pregnancy, many of which have unknown reproductive effects. Machine learning models have been used to successfully predict a number of reproductive toxicological outcomes for pharmaceuticals, including transplacental transfer, US Food and Drug Administration safety rating, and drug interactions. Models use quantitative chemical and structural features of active compounds to make predictions concerning the outcome of interest using computational algorithms. Results from these models can be a potential source of valuable information for pregnant people and their medical providers when making decisions regarding therapeutic drug use. This review summarizes current machine learning applications to make predictions about risk and toxicity of medication use during pregnancy. Our review of the recent literature revealed that machine learning quantitative structure-activity relationship models can be used successfully to predict the transplacental transfer and the US Food and Drug Administration pregnancy safety category of pharmaceuticals; such models have also been employed to predict drug interactions, though not specifically during pregnancy. This latter topic is a potential area for future research. In this review, no single algorithm or descriptor-calculation software emerged as the most widely used, and their performances depend on a variety of factors, including outcome of interest and combination of such algorithms and software.

INTRODUCTION/BACKGROUND:Autonomy during residency is crucial to the training and development of competent surgeons. An essential component of this process is the 'teaching assistant (TA)' case, an indispensable opportunity for residents to gain confidence and hone intraoperative skills. However, high-quality data on the volume and diversity of cases that graduates perform are scarce. METHODS:A retrospective analysis was performed from publicly collected data of operative case logs from general surgery residents graduating from ACGME-accredited programs from 2006 to 2023. Data on the median overall number of surgeon chief and TA cases were retrieved. Collected data were organized based on sub-specialties. The Mann-Kendall trend test was used to investigate trends in TA cases and surgeon chief operative volume. RESULTS:Between 2007 and 2023, the surgeon chief cases gradually increased from 229 to 274 (19.6 ​% increase; τ ​= ​0.610, p ​= ​0.001). There was a concurrent 72.7 ​% increase in TA cases from a median of 22-38 (τ ​= ​0.574, p ​= ​0.001). Surgeon chief (283 per resident) and TA cases (43 per resident) peaked in 2018-2019 and 2016-2017. The uptrend in TA cases was associated with the significant increase in colorectal (τ ​= ​0.559, p ​= ​0.001), general surgery-other (τ ​= ​0.404, p ​= ​0.018), and hepatopancreaticobiliary (HPB) (τ ​= ​0.596, p ​= ​0.001) subspecialties. Trauma and vascular surgery did not change significantly. With respect to total chief cases, general surgery-other (τ ​= ​0.956, p=<0.001), HPB (τ ​= ​0.713, p=<0.001) and colorectal (τ ​= ​0.522, p ​= ​0.004) volume increased. There was no significant change in trauma and foregut volume, while the volume of endocrine (τ ​= ​-0.485, p ​= ​0.006) and vascular surgery (τ ​= ​0.603, p ​= ​0.001) dropped significantly. The procedural category with the highest chief and TA volume was 'colorectal tract - large intestine.' Most procedural categories (53.49 ​%) retained a median of 0 teaching cases. No chief cases were logged for the specialties generally not considered part of general surgery (genitourinary, nervous system, orthopedics, and gynecology), although a median of 1 surgeon chief genitourinary case was recorded from 2018 to 2023. CONCLUSIONS:Over the past seventeen years, there has been a gradual uptrend in the number of surgeon chief and TA cases. While this is a positive indicator of improved autonomy, further research must focus on strategies to improve resident autonomy to train well-rounded surgeons safely.