Energy exchange between electron and molecular gases

Energy transfer between electron and molecular gase

Irritable Bowel Syndrome Onset after New Coronavirus Infection COVID-19

Aim. A psychometric comparison in patients with previous irritable bowel syndrome (IBS) vs. those with IBS presenting six months or later since COVID-19 infection.Materials and methods. The study included patients having had COVID-19 infection over 6 months ago and complying with Rome IV criteria (2016). The study cohort was 100 patients with gastrointestinal symptoms. Fourteen patients (cohort 1) complied with the IBS criteria, 5 males and 9 females. A comparison cohort was 40 patients with IBS verified prior to the COVID-19 pandemic (cohort 2), 12 males and 28 females. Data were obtained from the SIPSITEST 9.0 DBMS resource. The control cohort comprised 50 healthy respondents (cohort 3), 23 males and 27 females. Depression was scored with the Beck Inventory, anxiety — with Spielberger—Khanin (adapted STAI) questionnaire; childhood psychogeny has also been assessed.Results. In statistical analysis of cohort 1, mean depression, personality and reactive anxiety scores were 11 ± 2.27, 43.8 ± 1.93 and 46.7 ± 2.05, respectively. Mean values in cohort 2: personality anxiety 47.3 ± 1.46, reactive anxiety 50.7 ± 1.96 and depression 12.85 ± 1.13. With childhood psychogeny, positive answers to at least one question were reported in 9 of 14 (65%) patients in cohort 1 and 33 (82.5%) — in cohort 2. No study inter-cohort differences have been observed for personality or reactive anxiety and depression, nor for the history of childhood psychogeny.Conclusion. The new coronavirus infection entails postinfectious IBS in 6 months after COVID-19

Multidrug-resistance and presence of class 1 integrons in clinical isolates of Salmonella enterica serotype Enteritidis, circulating in Armenia

Abstract. The aim of this work was detection of class 1 integrons and their contribution to the antimicrobial resistance phenotypes in strains of   subspecies enterica serotype Enteritidis. S. Enteritidis strains (n = 29) were isolated from patients with salmonellosis at “Nork” Clinical Hospital of Infectious Diseases, Yerevan, Republic of Armenia. High prevalence of multi-drug resistance (MDR) phenotypes was revealed and isolates with MDR phenotypes which are rare in the S. Enteritidis serotype were observed. Class 1 integrons were detected in 27,6% of isolates, with the prevalence of a variable region of 1000 bp. Occurrence of the MDR phenotype was more frequent in integron-positive isolates compared to integron-negative isolates of S. Enteritidis. Further studies are necessary to reveal the genetic background of MDR phenotypes and to estimate the genetic kinship among the isolates. Our results suggest a rapid and large-scale penetration of antibiotic resistance genes into populations of S. Enteritidis, which complicates infection control. More rigorous regulations should be imposed on antibiotic use, together with a vigilant epidemiological surveillance, to prevent the emergence and spread of MDR S. Enteritidis

Esophageal lesions at irritable bowel syndrome

Aim of investigation. To study potential of рН-impedance measurement in differential diagnostics of esophageal disorders at irritable bowel syndrome (IBS).Material and methods. Overall 201 patients with IBS, diagnosed according to Rome-III criteria were investigated. Of them 52 were men, 149 — women, mean age was 41,8±9,5 years. In 70 (35%) of them (21men, 49 women, mean age — 42,3±12,0 years) heartburn, belching, epigastric dyscomfort, non-coronary retrosternal pain were present along with IBS. Methods of investigation included clinical examination, esophagogastroduodenoscopy (EGDS) colonoscopy, X-ray investigation of the upper gut, 13С-urease breath test for Helicobacter pylori, 24-hour combined intraluminal рН-impedance recording with estimation of qualitative and quantitative indicators of refluxes and index of symptom-association probability (SAP). Psychometric components were estimated as well: anxiety and depression scores, scores of alexithymia, associated symptoms, quality of life, degree of hyperventilation, index of visceral sensitivity, degree of pain by visual analog scale. The estimation of the mentioned parameters was carried out separately at IBS with esophageal symptoms (n=70) in comparison to other group of investigated patients with IBS (n=131). Statistical analysis of obtained results was carried out by Statistica 6 software.Results. In 16 (23%) patients instrumental investigation revealed esophagitis of the II–IV degree by Savary–Miller classification. Clinically 6 of them had heartburn, 1 — belching and 9 — combination of heartburn and belching; according to 13С-urease breath test 5 patients had H. pylori infection. In 49 (70%) patients at EGDS and X-ray investigation non-erosive reflux disease (NERD) was revealed. Clinical presentation in this group included heartburn in 10 cases, belching in 16 combination of heartburn and belching — in 12 and postprandial epigastric dyscomfort — 11; 13С-urease breath test was positive in 15 patients. It is noteworthy that in none of patients non-coronary retrosternal pain was associated to esophageal disorders. According to рН-impedance measurement NERD was diagnosed in 20 (33,3%) patients. Functional heartburn was diagnosed in the other 29 (41%) patients.Conclusion. Nowadays 24-hour combined рН-impedance recording is considered as the most exact method, allowing to reveal gastroesophagal refluxes. In some cases it allows to carry out differential diagnostics between NERD and functional disorders of the esophagus and the stomach in patients with IBS. Application of рН-impedance measurement allows to recommend its introduction in broad clinical practice

Situational Awareness of Influenza Activity Based on Multiple Streams of Surveillance Data Using Multivariate Dynamic Linear Model

BACKGROUND: Multiple sources of influenza surveillance data are becoming more available; however integration of these data streams for situational awareness of influenza activity is less explored. METHODS AND RESULTS: We applied multivariate time-series methods to sentinel outpatient and school absenteeism surveillance data in Hong Kong during 2004-2009. School absenteeism data and outpatient surveillance data experienced interruptions due to school holidays and changes in public health guidelines during the pandemic, including school closures and the establishment of special designated flu clinics, which in turn provided 'drop-in' fever counts surveillance data. A multivariate dynamic linear model was used to monitor influenza activity throughout epidemics based on all available data. The inferred level followed influenza activity closely at different times, while the inferred trend was less competent with low influenza activity. Correlations between inferred level and trend from the multivariate model and reference influenza activity, measured by the product of weekly laboratory influenza detection rates and weekly general practitioner influenza-like illness consultation rates, were calculated and compared with those from univariate models. Over the whole study period, there was a significantly higher correlation (rho = 0.82, p</=0.02) for the inferred trend based on the multivariate model compared to other univariate models, while the inferred trend from the multivariate model performed as well as the best univariate model in the pre-pandemic and the pandemic period. The inferred trend and level from the multivariate model was able to match, if not outperform, the best univariate model albeit with missing data plus drop-in and drop-out of different surveillance data streams. An overall influenza index combining level and trend was constructed to demonstrate another potential use of the method. CONCLUSIONS: Our results demonstrate the potential use of multiple streams of influenza surveillance data to promote situational awareness about the level and trend of seasonal and pandemic influenza activity.published_or_final_versio

Data-driven approach for creating synthetic electronic medical records

<p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p

ТРАНСПЛАНТАЦИЯ ПЕЧЕНИ У ДЕТЕЙ С БОЛЕЗНЯМИ НАКОПЛЕНИЯ ГЛИКОГЕНА: ОЦЕНКА РИСКА И НЕОБХОДИМОСТИ ЕЕ ПРОВЕДЕНИЯ

Glycogen storage diseases I, III and IV types are congenital disorders, which are commonly associated with severe liver diseases. Liver transplantation has been proposed as a treatment of choise for these disorders. While liver transplantation corrects the primary hepatic enzyme defect, the extrahepatic manifestations of glycogenoses often complicate the posttransplant management. Upon review of the English-language literature, 42 children under 18 years old were discovered to have undergone liver transplantation for complications associated with glycogenoses (18 patients with Ia type, 6 – with Ib type, one patient – with III type, 17 – with IV type). This artic- le represents the pediatric liver transplantation for complications associated with glycogenosis Ia type, analyzed posttransplant period in this recipient. Болезни накопления гликогена I, III, IV типа являются врожденными заболеваниями, которые обычно ведут к тяжелому поражению печени. Трансплантация печени является терапией выбора при данных патологиях. В то время как пересадка печени нивелирует первичный дефект фермента в печени, внепе- ченочные проявления гликогенозов порой осложняют посттрансплантационный период. В статье опи- саны данные англоязычной литературы, согласно которой 42 детям до 18 лет по поводу осложнений гликогенозов были проведены трансплантации печени (18 пациентам – в связи с гликогенозом Ia типа, шестерым – Ib, одному ребенку – III типа, 17 пациентам – по поводу гликогеноза IV типа). В работе представлено описание трансплантации печени ребенку по поводу гликогеноза Ia типа, проведен анализ посттрансплантационного периода жизни реципиента.

Optimizing Provider Recruitment for Influenza Surveillance Networks

The increasingly complex and rapid transmission dynamics of many infectious diseases necessitates the use of new, more advanced methods for surveillance, early detection, and decision-making. Here, we demonstrate that a new method for optimizing surveillance networks can improve the quality of epidemiological information produced by typical provider-based networks. Using past surveillance and Internet search data, it determines the precise locations where providers should be enrolled. When applied to redesigning the provider-based, influenza-like-illness surveillance network (ILINet) for the state of Texas, the method identifies networks that are expected to significantly outperform the existing network with far fewer providers. This optimized network avoids informational redundancies and is thereby more effective than networks designed by conventional methods and a recently published algorithm based on maximizing population coverage. We show further that Google Flu Trends data, when incorporated into a network as a virtual provider, can enhance but not replace traditional surveillance methods