Project description:SARS-CoV-2 has infected nearly 3.7 million and killed 61,722 Californians, as of May 22, 2021. Non-pharmaceutical interventions have been instrumental in mitigating the spread of the coronavirus. However, as we ease restrictions, widespread implementation of COVID-19 vaccines is essential to prevent its resurgence. In this work, we addressed the adequacy and deficiency of vaccine uptake within California and the possibility and severity of resurgence of COVID-19 as restrictions are lifted given the current vaccination rates. We implemented a real-time Bayesian data assimilation approach to provide projections of incident cases and deaths in California following the reopening of its economy on June 15, 2021. We implemented scenarios that vary vaccine uptake prior to reopening, and transmission rates and effective population sizes following the reopening. For comparison purposes, we adopted a baseline scenario using the current vaccination rates, which projects a total 11,429 cases and 429 deaths in a 15-day period after reopening. We used posterior estimates based on CA historical data to provide realistic model parameters after reopening. When the transmission rate is increased after reopening, we projected an increase in cases by 21.8% and deaths by 4.4% above the baseline after reopening. When the effective population is increased after reopening, we observed an increase in cases by 51.8% and deaths by 12.3% above baseline. A 30% reduction in vaccine uptake alone has the potential to increase cases and deaths by 35% and 21.6%, respectively. Conversely, increasing vaccine uptake by 30% could decrease cases and deaths by 26.1% and 17.9%, respectively. As California unfolds its plan to reopen its economy on June 15, 2021, it is critical that social distancing and public behavior changes continue to be promoted, particularly in communities with low vaccine uptake. The Centers for Disease Control and Prevention (CDC) recommendation to ease mask-wearing for fully vaccinated individuals despite major inequities in vaccine uptake in counties across the state highlights some of the logistical challenges that society faces as we enthusiastically phase out of this pandemic.
Project description:Background: To develop a tool for assessing normalcy of the thoracic aorta (TA) by echocardiography, based on either a linear regression model (Z-score), or a machine learning technique, namely one-class support vector machine (OC-SVM) (Q-score). Methods: TA diameters were measured in 1112 prospectively enrolled healthy subjects, aging 5 to 89 years. Considering sex, age and body surface area we developed two calculators based on the traditional Z-score and the novel Q-score. The calculators were compared in 198 adults with TA > 40 mm, and in 466 patients affected by either Marfan syndrome or bicuspid aortic valve (BAV). Results: Q-score attained a better Area Under the Curve (0.989; 95% CI 0.984-0.993, sensitivity = 97.5%, specificity = 95.4%) than Z-score (0.955; 95% CI 0.942-0.967, sensitivity = 81.3%, specificity = 93.3%; p < 0.0001) in patients with TA > 40 mm. The prevalence of TA dilatation in Marfan and BAV patients was higher as Z-score > 2 than as Q-score < 4% (73.4% vs. 50.09%, p < 0.00001). Conclusions: Q-score is a novel tool for assessing TA normalcy based on a model requiring less assumptions about the distribution of the relevant variables. Notably, diameters do not need to depend linearly on anthropometric measurements. Additionally, Q-score can capture the joint distribution of these variables with all four diameters simultaneously, thus accounting for the overall aortic shape. This approach results in a lower rate of predicted TA abnormalcy in patients at risk of TA aneurysm. Further prognostic studies will be necessary for assessing the relative effectiveness of Q-score versus Z-score.
Project description:PurposeThe coronavirus disease 2019 (COVID-19) outbreak has significantly impacted the diagnosis and treatment of breast cancer. Our study investigated the change in diagnosis and treatment of breast cancer with the progress of COVID-19 pandemic.Materials and methodsThe study group comprised 6,514 recently diagnosed breast cancer patients between January 1, 2019, and February 28, 2021. The patients were divided into two groups: pre-COVID-19 period (3,182; January 2019 to December 2019) and COVID-19 pandemic period (3,332; January 2020 to February 2021). Clinicopathological information related to the first treatment after breast cancer diagnosis was retrospectively collected and analyzed in the two groups.ResultsAmong the 6,514 breast cancer patients, 3,182 were in the pre-COVID-19 period and 3,332 were in the COVID-19 pandemic period. According to our evaluation, the least breast cancer diagnosis (21.8%) was seen in the first quarter of 2020. The diagnosis increased gradually except for the fourth quarter in 2020. While early-stage breast cancer was diagnosed 1,601 (48.1%) during the COVID-19 pandemic (p=0.001), the number of surgical treatments increased 4.6% (p < 0.001), and the treatment time was slightly shorter 2 days (p=0.001). The breast cancer subtype distribution was not statistically different between the pre-COVID-19 and COVID-19 period groups.ConclusionIn the early stages of the pandemic, the number of breast cancer cases temporarily decreased; however, they stabilized soon, and no significant differences could be identified in the diagnosis and treatment when compared to the period before the pandemic.
Project description:The novel coronavirus, severe acute respiratory coronavirus 2 (SARS-CoV-2), pandemic has delivered a profound and negative impact on the United States. The suspension of elective surgeries including arthroplasty will have a lasting effect on all stakeholders including patients, physicians, and healthcare organizations within the US healthcare system. Resumption of elective hip and knee arthroplasty will need to be carefully focused. The purpose of this work is to address potential strategies, concerns, and regulatory barriers in restarting elective hip and knee arthroplasty in the United States.
Project description:After the first lockdown, Italian dentists resumed their practice while handling several challenges. Reducing contagion risk by complying with the stringent measures recommended by the Italian Ministry of Health for dental activity while also balancing patient needs was a difficult task. This work aims to understand the procedures that were adopted in the second phase of the COVID-19 pandemic (5 May-30 September 2020) and the dentists' expectations and concerns about returning to normalcy. A national survey with 38 questions was conducted from November 2020 to January 2021 and comparisons were performed among the five main Italian geographic areas. Located mainly in northwest Italy, 1028 dentists were included in the survey. About 83% of the Italian dentists fully restarted their activities after the lockdown. The resumption was significantly marked in North Italy and the Center than in the South (p < 0.01). Over 80% adopted the recommended precautional guidelines, modifying them according to the specific dental treatment executed. Fifty percent of dentists were confident in returning to normalcy after the COVID-19 crisis. Many precautions adopted during the pandemic will be continued, especially in South Italy and the Islands (p < 0.01). Italian dentists reported excellent autonomous organizational skills and the maintaining of high-quality precautions during the reopening phase.
Project description:Extracellular vesicles (EVs) offer a vehicle for diagnostic and therapeutic utility. EVs carry bioactive cargo and an accrued interest in their characterization has emerged. Efforts at identifying EV-enriched protein or RNA led to a surprising realization that EVs are excessively heterogeneous in nature. This diversity is originally attributed to vesicle sizes but it is becoming evident that different classes of EVs vehiculate distinct molecular cargos. Therefore, one of the current challenges in EV research is their selective isolation in quantities sufficient for efficient downstream analyses. Many protocols have been developed; however, reproducibility between research groups can be difficult to reach and inter-studies analyses of data from different isolation protocols are unmanageable. Therefore, there is an unmet need to optimize and standardize methods and protocols for the isolation and purification of EVs. This review focuses on the diverse techniques and protocols used over the years to isolate and purify EVs with a special emphasis on their adequacy for proteomics applications. By combining recent advances in specific isolation methods that yield superior quality of EV preparations and mass spectrometry techniques, the field is now prepared for transformative advancements in establishing distinct categorization and cargo identification of subpopulations based on EV surface markers.
Project description:Our limited understanding of the biological impact of the whole spectrum of early breast lesions together with a lack of accurate molecular-based risk criteria for the diagnosis and assignment of prognostic significance to biopsy findings presents an important problem in the clinical management of patients harboring precancerous breast lesions. As a result, there is a need to identify biomarkers that can better determine the outcome of early breast lesions by identifying subpopulations of cells in breast premalignant disease that are at high-risk of progression to invasive disease. A first step towards achieving this goal will be to define the molecular phenotypes of the various cell types and precursors - generated by the stem cell hierarchy - that are present in normal and benign conditions of the breast. To date there have been very few systematic proteomic studies aimed at characterizing the phenotypes of the different cell subpopulations present in normal human mammary tissue, partly due to the formidable heterogeneity of mammary tissue, but also due to limitations of the current proteomic technologies. Work in our laboratories has attempted to address in a systematic fashion some of these limitations and here we present our efforts to search for biomarkers using normal fresh tissue from non-neoplastic breast samples. From the data generated by the 2D gel-based proteomic profiling we were able to compile a protein database of normal human breast epithelial tissue that was used to support the biomarker discovery program. We review and present new data on the putative cell-progenitor marker cytokeratin 15 (CK15), and describe a novel marker, dihydropyriminidase-related protein 3 (DRP3) that in combination with CK15 and other well known proteins were used to define molecular phenotypes of normal human breast epithelial cells and their progenitors in resting acini, lactating alveoli, and large collecting ducts of the nipple. Preliminary results are also presented concerning DRP3 positive usual ductal hyperplasias (UDHs) and on single cell layer columnar cells (CCCs). At least two bona fide biomarkers of undifferentiated ER?/PgR negative luminal cells emerged from these studies, CK15 and c-KIT, which in combination with transformation markers may lead to the establishment of a protein signature able to identify breast precancerous at risk of progressing to invasive disease.
Project description:A considerable number of adopted animals are returned to animal shelters post-adoption which can be stressful for both the animal and the owner. In this retrospective analysis of 23,932 animal records from a US shelter, we identified animal characteristics associated with the likelihood of return, key return reasons, and outcomes post-return for dogs and cats. Binary logistic regression models were used to describe the likelihood of return, return reason and outcome based on intake age, intake type, sex, breed and return frequency. Behavioral issues and incompatibility with existing pets were the most common return reasons. Age and breed group (dogs only) predicted the likelihood of return, return reason and post-adoption return outcome. Adult dogs had the greatest odds of post-adoption return (OR 3.40, 95% CI 2.88-4.01) and post-return euthanasia (OR 3.94, 95% CI 2.04-7.59). Toy and terrier breeds were 65% and 35% less likely to be returned compared with herding breeds. Pit bull-type breeds were more likely to be returned multiple times (X2 = 18.11, p = 0.01) and euthanized post-return (OR 2.60, 95% CI 1.47-4.61). Our findings highlight the importance of animal behavior in the retention of newly adopted animals and provide useful direction for allocation of resources and future adoption counselling and post-adoption support services.
Project description:The inhibition of return effect in perception refers to the observation that one is slower to re-attend a location that was attended right before, compared to a location that was not attended right before. Johnson et al. (2013, Psych. Sc., 24, 1104-1112, doi:10.1177/0956797612466414) observed a similar inhibitory effect for an attended item in working memory, which the authors referred to as an inhibition-of-return-like effect. However, testing an inhibition of return effect requires attention to be disengaged from the attended item, before testing whether participants are slower to return to said item. This was assumed but not experimentally manipulated in the paradigm by Johnson and colleagues. In the current study, we investigated whether an inhibition of return effect can be observed in working memory when attention is experimentally disengaged from the attended item before measuring whether responses are slower for the item in question. Participants were indeed slower to respond to a memory probe that matched the item that was attended right before, compared to a memory probe that matched the item that was not attended right before. Thus, our test with more experimental control did result in an inhibition of return effect in working memory.