Clinical Disease Prevention Research Articles

Influencing factors of particle deposition in the human nasal cavity.

To review the existing literature on the application of computational fluid dynamics methods to study nasal particle deposition and to summarize and analyze the factors affecting nasal particle deposition in order to provide theoretical references for the development of future transnasal drug delivery devices and the prevention of respiratory-related diseases. PubMed and CNKI databases. A search of all current literature (up to and including February 2023) was conducted. Search terms related to the topic of factors influencing nasal particle deposition were identified, and queries were conducted to identify relevant articles. Both the properties of the particles themselves and the environmental conditions external to the particles can affect particle deposition in the nasal cavity, with particle deposition showing a positive correlation with particle size, particle density, and airflow velocity, with increasing subject age leading to a decrease in deposition, and with the relationship between airflow temperature and humidity still requiring more research to further explore. With the popularity of computational fluid dynamics, more and more scholars have applied computational fluid dynamics technology to explore the influence of different parameters on particle deposition. By summarizing and analyzing the influence law of various factors on deposition, it can provide a theoretical basis for the future development and application of transnasal drug delivery devices and the prevention of respiratory-related diseases, which makes a significant contribution to the optimization of clinical disease prevention and treatment. NA.

Biofilm formation and associated gene expression changes in Cronobacter from cereal related samples in China

Cronobacter is an important foodborne pathogen that can cause severe neonatal meningitis, necrotizing enterocolitis, and bacteremia. Currently, there is limited knowledge of biofilm formation in Cronobacter. In the present study, biofilm formation ability and associated gene expression changes in Cronobacter from cereal related samples was carried out systematically. Our results from 307 Cronobacter isolates analyzed for 48 h showed strong biofilm-forming ability in 14 strains (4.6%), moderate in 47 strains (15.3%), weak in 142 strains (46.2%), and no such ability in the remaining 104 strains (33.9%). Further studies on five strains with strong biofilm-forming ability showed that maximum biofilm formation in Cronobacter occurred after 24 h of cultivation, reaching a peak around 48 h–72 h, reducing gradually thereafter. Kyoto encyclopedia of genes and genomes (KEGG) analysis revealed that differentially expressed genes (DEGs) involved in flagellar assembly, oxidative phosphorylation, ribosome, photosynthesis, O-Antigen nucleotide sugar biosynthesis, citrate cycle (tricarboxylic acid cycle, TCA) and bacterial chemotaxis were enriched in biofilm forming cells. The genes involved these enrichment pathways were mostly downregulated when compared to planktonic cells. Several transcriptional regulator genes such as csrA and bolA, and the cell surface composition regulator gene glgS were significantly upregulated. 12 of 13 (92.3%) selected genes was found to be in agreement with the RNA-Seq of planktonic and biofilm cells by Quantitative real-time PCR analysis, thus increasing confidence in our data. Our research lays a sound theoretical basis for further studies on mechanisms regulating biofilm formation and provides a foundation for development of new food safety measures, clinical disease prevention and control.

Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities

BackgroundSystematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations.MethodsHybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014–2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture. Setting:19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems. Participants: any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic. Methods: A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter. Outcomes: provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations. Measures: patient and provider surveys and EMR data.ResultsOne thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%).ConclusionsSystematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health.Trial registrationClinicaltrials.gov number NCT01956773, registered 10/8/2013.

A visual detection of human immunodeficiency virus gene using ratiometric method enabled by phenol red and target-induced catalytic hairpin assembly

Relying on the specific coordination of Ag+ and mismatched cytosine-cytosine (C–C), the high-efficiency inhibition of urease by Ag+ ion, and the rapid and sensitive response of phenol red to pH, a sensitive ratiometric sensor has been designed for visual detection of human immunodeficiency virus gene (HIV DNA). This sensor utilizes the HIV DNA to initiate catalytic hairpin assembly (CHA) process, releasing Ag+ to inhibit subsequent urease-catalyzed urea hydrolysis and prevent the pH of the solution from rising. The CHA process and the absorbance ratio of phenol red at different wavelengths (A559/A432) amplify the signal, allowing the sensor to detect HIV DNA from 10 to 130 nM in a sensitive and highly selective manner with a low detection limit of 7.8 nM. In addition, this sensor can visually distinguish different concentrations of HIV DNA within a certain range and possesses a good recovery in 1% of serum samples, which will provide new ideas for biosensor design, dipstick test, blood test, and other clinical disease prevention.

Non-invasive reconstruction of dynamic myocardial transmembrane potential with graph-based total variation constraints.

Non-invasive reconstruction of electrophysiological activity in the heart is of great significance for clinical disease prevention and surgical treatment. The distribution of transmembrane potential (TMP) in three-dimensional myocardium can help us diagnose heart diseases such as myocardial ischemia and ectopic pacing. However, the problem of solving TMP is ill-posed, and appropriate constraints need to be added. The existing state-of-art method total variation minimisation only takes advantage of the local similarity in space, which has the problem of over-smoothing, and fails to take into account the relationship among frames in the dynamic TMP sequence. In this work, the authors introduce a novel regularisation method called graph-based total variation to make up for the above shortcomings. The graph structure takes the TMP value of a time sequence on each heart node as the criterion to establish the similarity relationship among the heart. Two sets of phantom experiments were set to verify the superiority of the proposed method over the traditional constraints: infarct scar reconstruction and activation wavefront reconstruction. In addition, experiments with ten real premature ventricular contractions patient data were used to demonstrate the accuracy of the authors’ method in clinical applications.

Electrochemical-photoelectrochemical dual-mode sensing platform based on advanced Cu9S8/polypyrrole/ZIF-67 heterojunction nanohybrid for the robust and selective detection of hydrogen sulfide

The detection of hydrogen sulfide by sensing platform is desirable but highly challenged in a single-response mode due to the obstacle of low precision. In this work, a novel dual-mode electrochemical - photoelectrochemical (PEC) sensor based on Cu9S8/polypyrrole/ZIF-67 (Cu9S8/PPy/ZIF-67) nanohybrid as a double signal probe was designed for highly selective detection of hydrogen sulfide. Interestingly, the as-prepared nanohybrid with excellent peroxidase - mimicking activities show remarkable electrocatalytical activity for hydrogen sulfide oxidation by using amperometric i-t. Importantly, another mode of PEC sensing platform was also constructed based on the increase of photocurrent of the modified photoactive electrodes in response to the in-situ generation of cobalt sulfide and oxidation of hydrogen sulfide. This nanohybrid-based dual-signal transduction mode hydrogen sulfide sensor provides a highly selective and relatively wide linear range for real-time tracking hydrogen sulfide levels, which will open a new pathway in bio-sensing system, clinical disease prevention and diagnosis.

Large Cohort Data Based Group or Community Disease Prevention Design Strategy: Strong Heart Study.

Background and ObjectiveA multitude of large cohort studies have data on incidence rates and predictors of various chronic diseases. However, approaches for utilization of these costly collected data and translation of these valuable results to inform and guide clinical disease prevention practice are not well developed. In this paper we proposed a novel conceptual group/community disease prevention design strategy based on large cohort study data.Methods and ResultsThe data from participants (n = 3516; 2056 women) aged 45 to 74 years and the diabetes risk prediction model from Strong Heart Study were used. The Strong Heart Study is a population-based cohort study of cardiovascular disease and its risk factors in American Indians. A conceptual group/community disease prevention design strategy based on large cohort data was initiated. The application of the proposed strategy for group diabetes prevention was illustrated.DiscussionThe strategy may provide reasonable solutions to the prevention design issues. These issues include complex associations of a disease with its combined and correlated risk factors, individual differences, choosing intervention risk factors and setting their appropriate, attainable, gradual and adaptive goal levels for different subgroups, and assessing effectiveness of the prevention program.ConclusionsThe strategy and methods shown in the illustration example can be analogously adopted and applied for other diseases preventions. The proposed strategy for a target group/community in a population provides a way to translate and apply epidemiological study results to clinical disease prevention practice.

Large Cohort Data Based Cost-Effective Disease Prevention Design Strategy: Strong Heart Study.

Background and Objective:A multitude of large cohort studies have collected data on incidence and covariates/risk factors of various chronic diseases. However, approaches for utilization of these large data and translation of the valuable results to inform and guide clinical disease prevention practice are not well developed. In this paper, we proposed, based on large cohort study data, a novel conceptual cost-effective disease prevention design strategy for a target group when it is not affordable to include everyone in the target group for intervention.Methods and Results:Data from American Indian participants (n = 3516; 2056 women) aged 45 – 74 years in the Strong Heart Study, the diabetes risk prediction model from the study, a utility function, and regression models were used. A conceptual cost-effective disease prevention design strategy based on large cohort data was initiated. The application of the proposed strategy for diabetes prevention was illustrated.Discussion:The strategy may provide reasonable solutions to address cost-effective prevention design issues. These issues include complex associations of a disease with its significant risk factors, cost-effectively selecting individuals at high risk of developing disease to undergo intervention, individual differences in health conditions, choosing intervention risk factors and setting their appropriate, attainable, gradual and adaptive goal levels for different subgroups, and assessing effectiveness of the prevention program.Conclusions:The strategy and methods shown in the illustrative example can also be analogously adopted and applied to other diseases preventions. The proposed strategy provides a way to translate and apply epidemiological study results to clinical disease prevention practice.

An Intelligible Risk Stratification Model Based on Pairwise and Size Constrained Kmeans.

Having a system to stratify individuals according to risk is key to clinical disease prevention. This allows individuals identified at different risk tiers to benefit from further investigation and intervention. But the same risk score estimated for two different persons does not mean they need the same further investigation or represent the similarity health condition between two persons. Meanwhile, users still do not know a prior what most of the risk tiers are, and how many tiers should be found in risk stratification. In this paper, the proposed pairwise and size constrained Kmeans (PSCKmeans) method simultaneously integrates the limited supervised information and the size constraints to screen the high-risk population based on similarity measurement, and gets a feasible and balanced stratification solution to avoid cluster with few points. Results on China Health and Nutrition Survey public dataset and follow-up dataset show that the proposed PSCKmeans method can naturally grade the risk of diabetes into four tiers, and achieve 73.8%, 85.1%, and 0.95% sensitivity, specificity, and ratio of minimum to expected on testing data. The proposed method compares favorably with eight previous semisupervised clustering methods; it demonstrates that semisupervised clustering by unifying multiple forms of constraints can guide a good partition that is more relevant for the domain and find new categories through prior knowledge. Finally, this risk stratification model can provide a tool for risk stratification of clinical disease and be used for further intervention for people with similar health condition.

Serotype Distribution and Antimicrobial Resistance of Streptococcus pneumoniae Isolates Causing Invasive Diseases from Shenzhen Children’s Hospital

ObjectiveTo provide guidance for clinical disease prevention and treatment, this study examined the epidemiology, antibiotic susceptibility, and serotype distribution of Streptococcus pneumoniae (S. pneumoniae) associated with invasive pneumococcal diseases (IPDs) among children less than 14 years of age in Shenzhen, China.Materials and MethodsAll the clinical strains were isolated from children less than 14 years old from January 2009 to August 2012. The serotypes and antibiotic resistance of strains of S. pneumoniae were determined using the capsular swelling method and the E-test.ResultsA total of 89 strains were isolated and 87 isolates were included. The five prevailing serotypes were 19F (28.7%), 14 (16.1%), 23F (11.5%), 19A (9.2%) and 6B (6.9%). The most common sequence types (ST) were ST271 (21.8%), ST876 (18.4%), ST320 (8.0%) and ST81 (6.9%) which were mainly related to 19F, 14, 19A and 23F, respectively. The potential coverage by 7-, 10-, and 13-valent pneumococcal conjugate vaccine were 77.0%, 77.0%, and 89.7%, respectively. Among the 87 isolates investigated, 11.5% were resistant to penicillin, and for meningitis isolates, the resistance rate was 100%. Multi-drug resistance (MDR) was exhibited by 49 (56.3%) isolates. Eighty-four isolates were resistance to erythromycin, among which, 56 (66.7%) carried the ermB gene alone and 28 (33.3%) expressed both the ermB and mefA/E genes.ConclusionsThe potential coverage of PCV13 is higher than PCV7 and PCV10 because high rates of serotypes 19A and 6A in Shenzhen. The clinical treatment of IPD needs a higher drug concentration of antibiotics. Continued surveillance of the antimicrobial susceptibility and serotypes distribution of IPD isolates may be necessary.

Serotypes and Patterns of Antibiotic Resistance in Strains Causing Invasive Pneumococcal Disease in Children Less than 5 Years of Age

ObjectiveThe serotypes and patterns of antibiotic resistance of Streptococcus pneumoniae (S. pneumoniae) strains that cause invasive pneumococcal disease (IPD) in infants were analyzed to provide guidance for clinical disease prevention and treatment.MethodsThe clinical features of confirmed IPD were evaluated in 61 patients, less than 5 years of age, who were admitted to our hospital between January 2009 and December 2011. The serotypes and antibiotic resistance of strains of S.pneumoniae were determined using the capsular swelling method and the E-test.ResultsA total of 61 invasive strains were isolated. The serotype distribution of those isolates were 19A (41.0%), 14 (19.7%), 19F (11.5%), 23F (9.8%), 8 (4.9%), 9V (4.9%), 1 (3.3%), and 4, 6B, and 20 (each 1.6%). The percentage of S. pneumoniae strains resistant to erythromycin, clindamycin, and cotrimoxazole were 100%, 86.9%, and 100%, respectively. The percentage of S. pneumoniae strains resistant to penicillin, amoxicillin/clavulanic acid, cefuroxime, ceftriaxone, cefotaxime, cefepime, and meropenem were 42.6%, 18.0%, 82.0%, 18.0%, 13.1%, 13.1%, and 36.1%, respectively. The percentage of multidrug-resistant strains was 95.6%. Strains of all serotypes isolated in this study were highly resistant to erythromycin, cotrimoxazole, and clindamycin. Strains with serotype 19A had the highest rates of resistance.ConclusionsSerotype 19A strains were most frequently isolated from children with IPD treated in our hospital. The strains causing IPD are highly resistant to antibiotics.

A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease

The ɛ4 allele of the apolipoprotein E (APOE) gene is currently the strongest and most highly replicated genetic factor for risk and age of onset of late-onset Alzheimer's disease (LOAD). Using phylogenetic analysis, we have identified a polymorphic poly-T variant, rs10524523, in the translocase of outer mitochondrial membrane 40 homolog (TOMM40) gene that provides greatly increased precision in the estimation of age of LOAD onset for APOE ɛ3 carriers. In two independent clinical cohorts, longer lengths of rs10524523 are associated with a higher risk for LOAD. For APOE ɛ3/4 patients who developed LOAD after 60 years of age, individuals with long poly-T repeats linked to APOE ɛ3 develop LOAD on an average of 7 years earlier than individuals with shorter poly-T repeats linked to APOE ɛ3 (70.5±1.2 years versus 77.6±2.1 years, P=0.02, n=34). Independent mutation events at rs10524523 that occurred during Caucasian evolution have given rise to multiple categories of poly-T length variants at this locus. On replication, these results will have clinical utility for predictive risk estimates for LOAD and for enabling clinical disease prevention studies. In addition, these results show the effective use of a phylogenetic approach for analysis of haplotypes of polymorphisms, including structural polymorphisms, which contribute to complex diseases.

Multilevel modelling of hospitalisations for recurrent diarrhoeal disease in Aboriginal and non‐Aboriginal infants and young children in Western Australia

A multilevel proportional hazards model was used to determine the prognostic factors affecting hospitalisations for recurrent diarrhoeal disease in infants and young children. All infants born in 1996 who had index gastroenteritis admission to Western Australian (WA) hospitals during their first year of life were included in our study cohort (n = 486). There were 618 hospital admissions for infectious diarrhoea over the 6-year follow-up period. Aboriginal children stayed significantly longer in hospital than their non-Aboriginal peers, and comorbidities such as dehydration, gastrointestinal sugar intolerance, failure to thrive, iron deficiency anaemia and certain infections (genitourinary, scabies and/or otitis media) were all significantly associated with the delayed discharge of patients. Substantial variations among patients (variance = 0.660) and between health service regions of WA (variance = 0.296) were found. Over 30% of the total variation could be attributed to the heterogeneity between health districts. For any two patients in the same health district, the within-region (intraclass) correlation was estimated to be 0.309. In the absence of detailed socio-demographic data, application of the standard survival procedure may lead to incorrect inferences due to regional clustering and repeated observations on individuals. By accounting for latent patient and regional effects, the multilevel analysis clearly confirmed the high burden of infectious diarrhoea among Aboriginal infants and children, and their much longer hospital stays. Coexisting morbidities contributed to the prolonged and recurrent hospitalisations. Findings of this epidemiological study indicated the need of multifaceted clinical disease prevention and hygiene promotion strategies to control the disease.

Probiotics and prebiotics: Where are we going?Edited by Gerald W. Tannock. 341 pp. $180. Caister Academic Press, Norfolk, United Kingdom, 2002. ISBN 0-9542464-1-1. Web address for ordering: www.caister.com

Intestinal microflora and probiotic therapy have attracted increasing attention, both in the scientific community, where it is stimulating promising new research, as well as in the consumer market, where food and dietary supplements comprise a growing portion of the self-care health market. As our understanding of the interactions between gut microflora and their host advances, the potential impact of probiotics and prebiotics on human health will develop accordingly. Written by authoritative experts, Probiotics and Prebiotics: Where Are We Going? provides an historical perspective on intestinal microflora and probiotic use, and highlights future directions. The breadth of this reference is impressive, spanning from discussions on genomics of probiotic organisms to reviews on clinical disease prevention with prebiotics. In the initial chapter, the author provides a thorough historical perspective on concepts related to intestinal microecology dating back to Elie Metchnikoff (1845–1916), now considered the inventor of probiotics. The uniqueness of human gut microflora, and the prinicipal of homeostasis, which accounts for the transient nature of probiotic colonization, are major points of emphasis. Brief single sentence synopses at the completion of each section provide useful “take-home” points. Following the introductory chapter, the next several sections cover current techniques involved in identification of intestinal microorganisms, including PCR-based denaturing gradient gel electrophoresis (DGGE), fluorescent in situ hybridization, and terminal-restriction fragment length polymorphism (T-RFLP). The depth to which these technologies are discussed may be useful to those involved in hands-on microbiologic investigation but is clearly beyond the scope of those without such a background. Additional chapters address the role of prebiotics, a much more recent development in dietary intervention, as regulators of the gut ecosystem. Specifically discussed are the established and putative effects of prebiotics on health, including anti-colon cancer properties, lipid-lowering action, improved calcium bioavailability, and enhanced resistance to invading pathogens. The topic of “targeted prebiotics” selectively fermented by particular species of Bifidobacterium and Lactobacillus is introduced as a consideration for several varied applications. Also reviewed are manufacturing technologies for the production of functional carbohydrates, perhaps somewhat beyond the scope of a reference intending to cover the role of gut microflora in health and disease. The text also addresses the influence of the gut microflora on the development of the immune system, specifically as it relates to inflammatory bowel diseases (IBD) and atopic disorders. A thorough summary of in vitro and in vivo data investigating possible therapeutic mechanisms, as well as the clinical efficacy of probiotic microorganisms relevant to inflammatory bowel diseases serves as an excellent resource. Even the infectious etiology theory of Crohn’s disease is touched upon, via a brief overview of data regarding possible disease-initiating and perpetuating microorgansisms. Appropriately, an entire chapter is devoted to the evidence supporting a protective role of microbial colonization against the development of allergic/atopic diseases, and includes a brief look at the epidemiologic basis of the Hygeine Hypothesis. In the final chapter, the expanding role of functional genomics and genetic characterization of particular microorganisms was introduced as a critical means to unequivocally define their contributions to human health. This multifaceted text, which covers topics ranging from intestinal bacteriology identification techniques to the role of probiotic therapy in IBD, will appeal to a wide audience, from microbiologists to food scientists. Clinical gastroenterologists, however, may find the extensive portion of this text devoted to gut microbiology of limited applicability. Bottom Line: A comprehensive review of a timely subject, but with only a few chapters of clinical relevance to gastroenterology practice.