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A PENTEC review of childhood cancer survivors who received brain radiation therapy (RT) was performed to develop models that aid in developing dose constraints for RT-associated central nervous system (CNS) morbidities.
The morbidity and mortality of patients requiring mechanical ventilation for coronavirus disease 2019 (COVID-19) pneumonia is considerable. We studied the use of whole-lung low-dose radiation therapy (LDRT) in this patient cohort.
Primary mediastinal B cell lymphoma (PMBCL) is a highly curable subtype of non-Hodgkin lymphoma that is diagnosed predominantly in adolescents and young adults. Consequently, long-term treatment-related morbidity is critical to consider when devising treatment strategies that include different chemoimmunotherapy strategies with or without radiation therapy. Furthermore, adaptive approaches using the end-of-chemotherapy (EOC) positron emission tomography (PET)/computed tomography (CT) scanning may help to determine which patients may benefit from additional therapies. We aimed to develop evidence-based guidelines for treating these patients.
Epigenetic age acceleration (EAA) is robustly linked with mortality and morbidity. This study examined risk factors of EAA and its association with overall survival (OS), progression-free survival (PFS), and quality of life (QOL) in patients with head and neck cancer (HNC) receiving radiation therapy.
Radiation therapy plays an important role in the multidisciplinary management of breast cancer. Recent years have seen improvements in breast cancer survival and a greater appreciation of potential long-term morbidity associated with the dose and volume of irradiated organs. Proton therapy reduces the dose to nontarget structures while optimizing target coverage. However, there remain additional financial costs associated with proton therapy, despite reductions over time, and studies have yet to demonstrate that protons improve upon the treatment outcomes achieved with photon radiation therapy. There remains considerable heterogeneity in proton patient selection and techniques, and the rapid technological advances in the field have the potential to affect evidence evaluation, given the long latency period for breast cancer radiation therapy recurrence and late effects. In this consensus statement, we assess the data available to the radiation oncology community of proton therapy for breast cancer, provide expert consensus recommendations on indications and technique, and highlight ongoing trials’ cost-effectiveness analyses and key areas for future research.
The purpose was to evaluate patient- and treatment-related risk factors for physician-assessed and patient-reported gastrointestinal (GI) symptoms after radio(chemo)therapy and image guided adaptive brachytherapy in locally advanced cervical cancer.
Total body irradiation (TBI) is a common myeloablative preparative regimen used in acute myeloid and lymphoblastic leukemia patients before allogenic hematopoietic stem cell transplantation (HSCT). The inefficient clearance of tumor cells and radiation-induced toxicity to normal tissues is attributed to relapse and morbidity in a significant fraction of patients. Developing biomarkers that indicate an individual's physiological response to radiation will allow personalized treatment and follow-up. We investigated the utility of circulating microRNA150-5p (miR150) for evaluation of radiation dose response.
Breast cancer has been identified as the most common malignant tumors among women and the morbidity of breast cancer is still increasing rapidly. MEX3A possesses important functions in the regulation of mRNAs and may be involved in a variety of human diseases including cancer, whose relationship with breast cancer is still not clear. In this study, MEX3A was identified as a potential promotor in breast cancer, whose expression was strongly higher in breast cancer tissues than normal tissues. The in vitro experiments showed that MEX3A is capable of promoting the development of breast cancer through stimulating cell proliferation, inhibiting cell apoptosis, arresting cell cycle and promoting cell migration. The functions of MEX3A were also verified in vivo. Furthermore, a combination of genechip analysis and Ingenuity pathway analysis (IPA) identified PIK3CA as a potential downstream target of MEX3A, knockdown of which executes similar inhibitory effects on breast cancer and could alleviate MEX3A-induced progression of breast cancer. In conclusion, our study unveiled, as the first time, MEX3A as a tumor promotor for breast cancer, whose function was carried out probably through the regulation of PIK3CA.
Purpose: Prospective data are lacking on long-term morbidity of inguinal lymphadenectomy including the influence of extent of surgery, use of radiotherapy, and patient factors. The aim of this study is to evaluate the effects of these factors on patient outcome, quality of life (QOL), regional symptoms, and limb volumes after inguinal or ilio-inguinal lymphadenectomy for melanoma. Methods: Analysis of the subgroup of patients with inguinal lymph node field relapse of melanoma, treated by inguinal or ilio-inguinal lymphadenectomy in the ANZMTG/TROG randomized trial of adjuvant radiotherapy versus observation. Results: Sixty-nine patients, 46 having undergone inguinal and 23 ilio-inguinal lymphadenectomy, with median follow-up of 73 months were analyzed. Mean limb volume increased rapidly after surgery (7% by 3 months) and continued to increase for at least another 18 months. Patients with body mass index (BMI) ≥ 25 kg/m{sup 2} had greater limb volume increase than normal-weight patients (13.3% versus 6.9%, P = 0.030). QOL improved over the first 18 months, but despite initial improvement, regional symptoms persisted long term. Type of surgery (inguinal or ilio-inguinal lymphadenectomy) had no demonstrably significant effect on limb volume (9.9% versus 13.4%, P = 0.35), QOL (P = 0.68), or regional symptoms (P = 0.65). There was no difference in overall survival between inguinal and ilio-inguinal lymphadenectomy [hazard ratio (HR) 0.75, 95% confidence interval (CI) 0.40–1.40, P = 0.43]. Conclusions: Inguinal lymphadenectomy for melanoma is a potentially morbid procedure with significant increases in limb volume. Patients report reasonable QOL but may have ongoing regional symptoms. Overweight/obesity is associated with poorer QOL, increased limb volume, and regional symptoms.
The National Predictive Modeling Tool Initiative (NPMTI) is a multi-year program to develop research-based “tools” to forecast incidences of diseases and mycotoxins affecting U.S. crops. The overall goals of NPMTI are to: (1) ensure crop sustainability and crop quality; (2) provide climate change resilience; (3) improve soil health; (4) monitor pathogens and microbial diversity in the environment, but not limited to crop residues, soils, and air; (5) improve disease management thereby reducing yield losses; (6) increase precision of in-season disease management tactics; and (7) increase precision of pesticide use.
Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate. In particular, we use Bayesian symbolic regression to automatically learn the closed-form mathematical models that most parsimoniously describe incidence. We develop and validate our models using COVID-19 incidence values for nine different countries, confirming their ability to accurately predict daily incidence. Remarkably, despite the differences in epidemic trajectories and dynamics across countries, we find that a single model for all countries offers a more parsimonious description and is more predictive of actual incidence compared to separate models for each country. Our results show the potential to accurately model incidence in real-time using closed-form mathematical models, providing a valuable tool for public health decision-makers.
Healthcare Professionals Working in Schools (HPWS) are responsible for providing health services to students and play a role in providing education to prevent illnesses, including tickborne diseases (TBD). Providing TBD education to children has been shown to increase prevention behaviors and knowledge of TBD symptoms, but little is known regarding the current state of TBD awareness among HPWS. In spring 2019 we conducted a cross-sectional knowledge, attitudes, and practices (KAP) survey of HPWS in two states with a high incidence of Lyme disease (LD) to inform design of TBD prevention programs. The survey queried general knowledge of TBDs, school practices regarding TBDs, and availability of TBD resources. Overall, higher confidence, experience, risk perception, prior training on TBD, and more years employed as a HPWS were independently associated with knowledge of LD transmission, symptoms, and correct tick removal practices. State and local health departments should consider prioritizing engagement with HPWS to provide educational opportunities about tickborne diseases.
Infectious disease modeling and forecasting have played a key role in helping assess and respond to epidemics and pandemics. Recent work has leveraged data on disease peak infection and peak hospital incidence to fit compartmental models for the purpose of forecasting and describing the dynamics of a disease outbreak. Incorporating these data can greatly stabilize a compartmental model fit on early observations, where slight perturbations in the data may lead to model fits that forecast wildly unrealistic peak infection. We introduce a new method for incorporating historic data on the value and time of peak incidence of hospitalization into the fit for a Susceptible-Infectious-Recovered (SIR) model by formulating the relationship between an SIR model’s starting parameters and peak incidence as a system of two equations that can be solved computationally. We demonstrate how to calculate SIR parameter estimates – which describe disease dynamics such as transmission and recovery rates – using this method, and determine that there is a noticeable loss in accuracy whenever prevalence data is misspecified as incidence data. To exhibit the modeling potential, we update the Dirichlet-Beta State Space modeling framework to use hospital incidence data, as this framework was previously formulated to incorporate only data on total infections. This approach is assessed for practicality in terms of accuracy and speed of computation via simulation.
Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective electronic health record (EHR) cohort study of 2,391,006 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 76 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28–120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There were significant associations between a diagnosis of any psychiatric disease and five categories of PASC-AMs with odds ratios highest for neurological, cardiovascular, and constitutional PASC-AMs with odds ratios of 1.31, 1.29, and 1.23 respectively. Secondary analysis revealed that the proportions of 50 individual clinical features significantly differed between patients diagnosed with different psychiatric diseases. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings.
The global incidence of the sexually transmitted disease gonorrhea is expected to rise due to the spread of Neisseria gonorrhoeae strains with decreased susceptibility to extended-spectrum cephalosporins (ESCs). ESC resistance is conferred by mosaic variants of penicillin-binding protein 2 (PBP2) that have diminished capacity to form acylated adducts with cephalosporins. To elucidate the molecular mechanisms of ESC resistance, we conducted a biochemical and high-resolution structural analysis of PBP2 variants derived from the decreased-susceptibility N. gonorrhoeae strain 35/02 and ESC-resistant strain H041. Our data reveal that mutations both lower affinity of PBP2 for ceftriaxone and restrict conformational changes that normally accompany acylation. Specifically, we observe that a G545S substitution hinders rotation of the β3 strand necessary to form the oxyanion hole for acylation and also traps ceftriaxone in a noncanonical configuration. In addition, F504L and N512Y substitutions appear to prevent bending of the β3–β4 loop that is required to contact the R1 group of ceftriaxone in the active site. Other mutations also appear to act by reducing flexibility in the protein. Overall, our findings reveal that restriction of protein dynamics in PBP2 underpins the ESC resistance of N. gonorrhoeae.
Coccidioidomycosis, or Valley fever, is an infectious disease caused by inhaling Coccidioides fungal spores. Incidence has risen in recent years, and it is believed the endemic region for Coccidioides is expanding in response to climate change. While Valley fever case data can help us understand trends in disease risk, using case data as a proxy for Coccidioides endemicity is not ideal because case data suffers from imperfect detection, including false positives (e.g., travel-related cases reported outside of endemic area) and false negatives (e.g., misdiagnosis or underreporting). Here we proposed a Bayesian, spatio-temporal occupancy model to relate monthly, county-level presence/absence data on Valley fever cases to latent endemicity of Coccidioides, accounting for imperfect detection. We used our model to estimate endemicity in the western United States. We estimated high probability of endemicity in southern California, Arizona, and New Mexico, but also in regions without mandated reporting, including western Texas, eastern Colorado, and southeastern Washington. We also quantified spatio-temporal variability in detectability of Valley fever, given an area is endemic to Coccidioides. We estimated an inverse relationship between lagged 3- and 9-month precipitation and case detection, and a positive association with agriculture. This work can help inform public health surveillance needs and identify areas that would benefit from mandatory case reporting.
The aim of the study was to determine (1) the rate at which rescreening former Department of Energy site workers identifies noncommunicable chronic diseases and (2) the development of comorbid conditions. Incidence and prevalence of hypertension, diabetes, reduced kidney function, and peripheral neuropathy at both initial and return screenings were calculated. Risk ratio of chronic disease development at return screening based on the presence of other conditions at initial screening were estimated with generalized linear regression. Prevalence of reduced kidney function was 19% at initial examination and 30% at return examination. The screening program was responsible for identifying 81% of reduced kidney function cases. Similar findings were present for the other chronic conditions examined. As a result, former worker health surveillance programs help identify significant health conditions among DOE workers, subcontractors, and visitors. Longitudinal screening of participants detects additional chronic conditions.
Tick-borne diseases are a growing public health concern in the United States, with cases rising steadily each year. Lyme borreliosis, or Lyme disease, remains the most prevalent, affecting approximately 476,000 individuals annually. Human-driven changes in climate and ecosystems have expanded the habitat of pathogen-carrying ticks, facilitating the spread of these infections. Additionally, increased instances of tick-borne diseases transmission through human tissues have been reported. Despite ongoing efforts to manage these infections, their incidence continues to rise. To develop effective control measures against these diseases and prevent the transmission of tick-borne infections through human and animal tissues, it is very important to develop detection assays and understand the transmission mechanisms of tick-borne infections. In this study, we provide detailed descriptions and visual references for larval and nymphal tick feeding on mice, focusing on the transmission and acquisition ofBorrelia burgdorferi(sensu stricto). These methodologies can be applied to study other tick-borne diseases, tick vectorial capacity, and tick biology, aiding in the development of detection strategies to combat these infections.