IMP3 signatures of fallopian tube: a risk for pelvic serous cancers

BACKGROUND:Recent advances suggest fallopian tube as the main cellular source for women's pelvic serous carcinoma (PSC). In addition to TP53 mutations, many other genetic changes are involved in pelvic serous carcinogenesis. IMP3 is an oncofetal protein which has recently been observed to be overexpressed in benign-looking tubal epithelia. Such findings prompted us to examine the relationship between IMP3 over-expression, patient age and the likelihood of development of PSC.METHODS:Fallopian tubes from three groups (low-risk, high-risk, and PSC) of patients with matched ages were studied. Age was recorded in 10years intervals ranging from age 20 to older than 80. The number of IMP3 signatures (defined by 10 or more tubal secretory cells stained positively and continuously in benign appearing tubal mucosa) from both tubal fimbria and ampulla segments was measured. The data was analyzed by standard contingency table and Poisson distribution methods after age adjustment. IMP3 overexpression was also examined in serous tubal intraepithelial carcinoma and PSC.RESULTS:The positive IMP3-stained cells are mainly tubal secretory cells. The absolute number of tubal IMP3 signatures increased significantly within each age group. Age remained a significant risk factor for serous neoplasia after age adjustment. IMP3 signatures were more frequent in the patients of both high-risk and PSC groups. The presence of IMP3 signatures in tubal mucosa was significantly associated with tubal or pelvic serous carcinogenesis (p<0.001).CONCLUSIONS:The findings suggest that tubal secretory cells with IMP3 signatures showing growth advantage could potentially serve as a latent precancer biomarker for tubal or pelvic serous carcinomas in women.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

Specific gene module pair-based target identification and drug discovery

Identification of the biological targets of a compound is of paramount importance for the exploration of the mechanism of action of drugs and for the development of novel drugs. A concept of the Connectivity Map (CMap) was previously proposed to connect genes, drugs, and disease states based on the common gene-expression signatures. For a new query compound, the CMap-based method can infer its potential targets by searching similar drugs with known targets (reference drugs) and measuring the similarities into their specific transcriptional responses between the query compound and those reference drugs. However, the available methods are often inefficient due to the requirement of the reference drugs as a medium to link the query agent and targets. Here, we developed a general procedure to extract target-induced consensus gene modules from the transcriptional profiles induced by the treatment of perturbagens of a target. A specific transcriptional gene module pair (GMP) was automatically identified for each target and could be used as a direct target signature. Based on the GMPs, we built the target network and identified some target gene clusters with similar biological mechanisms. Moreover, a gene module pair-based target identification (GMPTI) approach was proposed to predict novel compound–target interactions. Using this method, we have discovered novel inhibitors for three PI3K pathway proteins PI3Kα/β/δ, including PU-H71, alvespimycin, reversine, astemizole, raloxifene HCl, and tamoxifen

Evaluation of the Effectiveness of Clinical Pharmacists’ Consultation in the Treatment of Infectious Diseases: A Single-Arm, Prospective Cohort Study

Background: With the implementation of Antimicrobial Stewardship Program, clinical pharmacists’ consultation (CPC) for infectious diseases (ID) is gradually adopted by many hospitals in China. We conducted a cohort study to evaluate the effectiveness of CPC in ID treatment on patient outcomes and potential determinants.Methods: Based on a registry database, a prospective cohort study was conducted in Guizhou Provincial People’s Hospital. The main exposure factor was whether clinician adopted the suggestion from clinical pharmacist. The outcome was effective response rate (ERR) of ID patients. The variables associated with the outcome (e.g., age, gender, severity of infection, liver function, and kidney function) were also prospectively recorded. A multilevel model was performed to analyze the factors related to ERR.Results: A total of 733 ID inpatients were included in the final analysis according to the predesigned inclusion and exclusion criteria. The proportion of clinical pharmacists’ suggestions adopted by clinicians and ERR were 88.13 and 69.03%, respectively. Significant data aggregation (P &lt; 0.05) for individuals at the level of department was observed. According to the two-level variance component model, liver dysfunction (Adjusted Odds Ratio (AOR) = 0.649, 95%Credible Interval (CI): 0.432–0.976), severity of infection (AOR = 0.602, 95%CI: 0.464–0.781), and adopting the suggestion from pharmacist (AOR = 1.738, 95%CI: 1.028–2.940) had significant association with ERR.Conclusion: Our study suggests that the effect of CPC on ID treatment is significant. The policy/decision makers or hospital managers should be cognizant of the critical value of clinical pharmacists in ID treatment

Development of a core outcome set for cardiovascular diabetology: a methodological framework

BackgroundCardiovascular diabetology is an emergent field focusing on all aspects of diabetes/cardiovascular interrelationship and metabolic syndrome. High-quality evidence needs to be provided to determine the efficacy and safety of interventions in cardiovascular diabetology. The heterogeneity of outcomes among trials limits the comparison of results, and some outcomes are not always meaningful to end-users. The cardiovascular diabetology core outcome set (COS) study aims to develop a COS of interventions for cardiovascular diabetology. In this paper, we introduce the methodological framework for developing the COS.MethodsThe COS development will include the following steps: (a) establish the COS groups of stakeholders, including international steering committee, Delphi survey group, and consensus meeting group; (b) systematic reviews of outcomes used in trials of cardiovascular diabetology; (c) semistructured interview of stakeholders for outcomes of cardiovascular diabetology; (d) generate a list of candidate outcomes and determine the original outcome pool; (e) Delphi survey with stakeholders of cardiovascular diabetology to select potential core outcomes; and (f) review and endorse the cardiovascular diabetology COS by expert consensus meeting.ConclusionsThis current study reports the methodological framework to develop a COS in cardiovascular diabetology and will provide evidence for the future development of COS in cardiovascular diabetology

Вихретоковый анизотропный термоэлектрический первичный преобразователь лучистого потока

Представлена оригинальная конструкция первичного преобразователя лучистого потока, который может служить основой для создания приемника неселективного излучения с повышенной чувствительностью

Problem-Based mHealth Literacy Scale (PB-mHLS): Development and Validation

BackgroundMobile devices have greatly facilitated the use of digital health resources, particularly during the COVID-19 pandemic. Mobile health (mHealth) has become a common and important way to monitor and improve health conditions for people from different social classes. The ability to utilize mHealth affects its effectiveness; therefore, the widespread application of mHealth technologies calls for an instrument that can accurately measure health literacy in the era of mobile media. ObjectiveWe aimed to (1) identify the components of mHealth literacy for ordinary users and (2) develop a systematic scale for appropriately measuring individuals’ self-perceived mHealth literacy through a problem-based framework. MethodsWe conducted an exploratory study involving in-depth interviews and observations (15 participants) in January 2020 and used exploratory factor analysis and confirmatory factor analysis to identify the components of mHealth literacy and develop an item pool. In February 2020, we conducted a pilot survey with 148 participants to explore the factor structures of items identified during the exploratory study. Subsequently, 2 surveys were administrated using quota sampling. The first survey (conducted in Guangdong, China) collected 552 responses during March 2020; we assessed composite reliability, convergent validity, and discriminant validity. The second survey (conducted in China nationwide) collected 433 responses during October 2021; we assessed criterion-related validity using structural equation modeling. ResultsWe identified 78 items during the exploratory study. The final scale—the Problem-Based mHealth Literacy Scale—consists of 33 items that reflect 8 domains of mHealth literacy. The first web-based survey suggested that mHealth literacy consists of 8 factors (ie, subscales), namely, mHealth desire, mobile phone operational skills, acquiring mHealth information, acquiring mHealth services, understanding of medical terms, mobile-based patient–doctor communication, evaluating mHealth information, and mHealth decision-making. These factors were found to be reliable (composite reliability >0.7), with good convergent validity (average variance extracted >0.5) and discriminant validity (square root of average variance extracted are greater than the correlation coefficients between factors). The findings also revealed that these 8 factors should be grouped under a second-order factor model (χ2/df=2.701; comparative fit index 0.921; root mean square error of approximation 0.056; target coefficient 0.831). The second survey revealed that mHealth use had a significant impact (β=0.43, P<.001) on mHealth literacy and that mHealth literacy had a significant impact (β=0.23, P<.001) on health prevention behavior. ConclusionsThis study revealed the distinctiveness of mHealth literacy by placing mHealth needs, the ability to understand medical terms, and the skills in patient–doctor interactions in the foreground. The Problem-Based mHealth Literacy Scale is a useful instrument for comprehensively measuring individuals’ mHealth literacy and extends the concept of health literacy to the context of mobile communication