A cosmid-based genomic library of Serratia marcescens N28b was introduced into Escherichia coli DH5alpha, and clones were screened for serum resistance. One clone was found resistant to serum, to bacteriocin 28b, and to bacteriophages TuIa and TuIb. This clone also showed O antigen in its lipopolysaccharide. Subcloning and sequencing experiments showed that a 2,124-bp DNA fragment containing the rmlD and wbbL genes was responsible for the observed phenotypes. On the basis of amino acid similarity, we suggest that the 288-residue RmlD protein is a dTDP-L-rhamnose synthase. Plasmid pJT102, containing only the wbbL gene, was able to induce O16-antigen production and serum resistance in E. coli DH5alpha. These results suggest that the 282-residue WbbL protein is a rhamnosyltransferase able to complement the rJb-50 mutation in E. coli K-12 derivatives, despite the low level of amino acid identity between WbbL and the E. coli rhamnosyltransferase (24.80%). S. marcescens N28b rmlD and wbbL mutants were constructed by mobilization of suicide plasmids containing a portion of rmlD or wbbL. These insertion mutants were unable to produce O antigen; since strain N28b produces O4 antigen, these results suggest that both genes are involved in O4-antigen biosynthesis.

Background: Ensuring access to accurate and verified information is essential for effective patient treatment and diagnosis. Although health workers rely on the internet for clinical data, there is a need for a more streamlined approach. Objective: This systematic review aims to assess the current state of artificial intelligence (AI) and natural language processing (NLP) techniques in health care to identify their potential use in electronic health records and automated information searches. Methods: A search was conducted in the PubMed, Embase, ScienceDirect, Scopus, and Web of Science online databases for articles published between January 2000 and April 2023. The only inclusion criteria were (1) original research articles and studies on the application of AI-based medical clinical decision support using NLP techniques and (2) publications in English. A Critical Appraisal Skills Programme tool was used to assess the quality of the studies. Results: The search yielded 707 articles, from which 26 studies were included (24 original articles and 2 systematic reviews). Of the evaluated articles, 21 (81%) explained the use of NLP as a source of data collection, 18 (69%) used electronic health records as a data source, and a further 8 (31%) were based on clinical data. Only 5 (19%) of the articles showed the use of combined strategies for NLP to obtain clinical data. In total, 16 (62%) articles presented stand-alone data review algorithms. Other studies (n=9, 35%) showed that the clinical decision support system alternative was also a way of displaying the information obtained for immediate clinical use. Conclusions: The use of NLP engines can effectively improve clinical decision systems’ accuracy, while biphasic tools combining AI algorithms and human criteria may optimize clinical diagnosis and treatment flows. Trial Registration: PROSPERO CRD42022373386; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=373386

Objectives:While most studies have focused on analyzing the results of telemedicine use, it is crucial to consider the determinants of its use to fully understand the issue. This article aims to provide evidence on the determinants of telemedicine use in clinical practice.Methods:The survey targeted a total population of 398 medical professionals from a healthcare institution in Spain. The study sample was formed by the ninety-three primary care physicians who responded. Using an extended Technology Acceptance Model and microdata for the ninety-six physicians, binary logistic regression analysis was carried out.Results:The analysis performed confirmed the model's goodness-of-fit, which allowed 48.1 percent of the dependent variable's variance to be explained. The outcomes revealed that the physicians at the healthcare institution placed greater importance on telemedicine's potential to reduce costs, and on its usefulness to the medical profession. The perception of medical information security and confidentiality and the patients’ predisposition toward telemedicine were the second explanatory factors in order of importance. A third set of moderating effects would appear to corroborate the importance of the physicians’ own opinions.Conclusions:These results have revealed the need for a dynamic approach to the design of telemedicine use, especially when it targets a variety of end-users. Hence, the importance of conducting studies before using telemedicine, and attempting to identify which of the above-mentioned predictors exert an influence and how.

We conducted a systematic review of the literature on the use of mobile phones for weight loss. A total of 43 studies were identified on obese or overweight adults, aged 18 years or over. After review, ten articles met the inclusion criteria. There were 19–534 participants per study. Participants were from European, Asian and North American regions. The mean body mass index (BMI) of the subjects varied from 22 to 36 kg/m². Two studies used text messaging or multimedia messaging. All the other studies used mobile-phone apps or web-based programmes that could be accessed from mobile phones as a part of a weight-loss intervention or for evaluating their potential for use and their acceptance. Most studies lasted 2–4 months and the maximum duration was 1 year. All but two studies showed reductions in the participants’ bodyweight, BMI, waist circumference and body fat in the various interventions. There appeared to be a proportional relationship between weight loss and programme use. The programmes most benefited those who took a pro-active approach to everyday problems. Frequent self-recording of weight seemed to be important, as was the personalisation of the intervention (counselling and individualized feedback). Finally, a social support system acted as a motivational tool.

Unhealthy diet and physical inactivity—major risk factors for the main non-communicable diseases—can be addressed by mobile health applications. Using an evidence-based systematic review design, we analysed studies on mobile applications to foster physical activity to determine whether they met the objective of increasing adults’ physical activity. A bibliographic search was conducted in October 2020 using PubMed, Cochrane Library Plus, Biomed Central, Psychology Database, and SpringerLink, retrieving 191 articles. After titles and abstracts were reviewed, 149 articles were excluded, leaving 42 articles for a full-text review, of which 14 met the inclusion criteria. Despite differences in study duration, design, and variables, 13 of the 14 studies reported that applications were effective in increasing physical activity and healthy habits as dietary behaviour. However, further longer-term studies with larger samples are needed to confirm the effectiveness of mobile health applications in increasing physical activity.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet