ABSTRACT
A prospective cohort study was conducted to assess the prognostic significance of heart rate variability (HRV) measured by the HRV Camera application in predicting major adverse cardiovascular events (MACE) and all-cause mortality within 3 months after percutaneous coronary intervention (PCI). Of 101 patients, 25 developed MACE and 6 died. Low HRV (SDNN and rMSSD) is associated with increased MACE (p < 0.001 and p = 0.014, respectively) and all-cause mortality rates (p = 0.025 and p = 0.032, respectively). Our study concludes that HRV measured by smartphone applications has significant potential as predictive indicators of MACE and all-cause mortality after PCI, particularly SDNN.
ABSTRACT
Verticillium dahliae, a fungal pathogen that affects more than 200 plant species, including tomatoes, requires specific proteins for its early steps in plant infection. One such crucial protein, VdPBP1, exhibits high expression in the presence of tomato roots. Its 313-amino acid C-terminal section restores adhesion in nonadhesive Saccharomyces cerevisiae strains. To uncover its role, we employed a combination of bioinformatics, genetics, and morphological analyses. Our findings underscore the importance of VdPBP1 in fungal growth and pathogenesis. Bioinformatic analysis revealed that the VdPBP1 gene consists of four exons and three introns, encoding a 952-codon reading frame. The protein features a 9aaTAD domain, LsmAD, and PAB1 DNA-binding sites, as well as potential nuclear localization and transmembrane helix signals. Notably, the deletion of a 1.1 kb fragment at the gene's third end impedes microsclerotia formation and reduces pathogenicity. Mutants exhibit reduced growth and slower aerial mycelial development compared to the wild type. The VdPBP1 deletion strain does not induce disease symptoms in tomato plants. Furthermore, VdPBP1 deletion correlates with downregulated microsclerotia formation-related genes, and promoter analysis reveals regulatory elements, including sites for Rfx1, Mig1, and Ste12 proteins. Understanding the regulation and target genes of VdPBP1 holds promise for managing Verticillium wilt disease and related fungal pathogens.
ABSTRACT
We study opinion dynamics on complex social networks where each individual holding a binary opinion on a certain subject may change her/his mind to match the opinion of the majority. Two rules of interactions between individuals, termed as classic majority and influence majority rules, respectively, are imposed on the social networks. The former rule allows each individual to adopt an opinion following a simple majority of her/his immediate neighbors, while the latter one lets each individual calculate the influence of each opinion and choose to follow the more influential one. In this calculation, the influences of different opinions are counted as the sum of the influences of their respective opinion holders in neighborhood area, where the influence of each individual is conveniently estimated as the number of social connections s/he has. Our study reveals that in densely-connected social networks, all individuals tend to converge to having a single global consensus. In sparsely-connected networks, however, the systems may exhibit rich properties where coexistence of different opinions, and more interestingly, multiple steady states of coexistence can be observed. Further studies reveal that low-degree and high-degree nodes may play different roles in formulating the final steady state, including multi-steady states, of the systems under different opinion evolution rules. Such observations would help understand the complex dynamics of opinion evolution and coexistence in social systems.
Subject(s)
Attitude , Social Networking , Models, StatisticalABSTRACT
AIM: The aim of this study was to evaluate the rates and types of drug prescription and administration errors in one pediatric nephrology ward, comparing two dispensing schemes: the first one defined as handwritten prescription plus ward stock distribution system (WSDS), and the second one as computerized prescription plus unit dose drug dispensing system (UDDDS). METHOD: Data were collected over an 8-week period, from 1 February to 31 March 1999. Two fifth-year pharmacy students photocopied prescription and administration documents on the ward each day, under the supervision of a senior pharmacist. The medical record analysis was used to compare the prescription with the administration report. Prescribing and administration medication errors were classified according to the American Society of Health-System Pharmacists. RESULTS: Prescribing errors: overall, for both dispensing schemes, a total of 511 prescriptions, resulting in 4532 prescribed drugs (an average of 9 drugs per prescription) were prescribed. The total prescription error rate was 20.7% (937 of 4532), resulting in 1.9 errors per patient per day. The computerized prescription error rate was 10.6% (419 of 3943), the handwritten prescription error rate was 87.9% (518 of 589). This difference was very significant (P < 0.0001). ADMINISTRATION ERRORS: The total opportunity of administration errors was 4589 (sum of administered and omitted drugs). The total administration error rate was 23.5% (1077 of 4589) including wrong administration time, and 11.7% (538 of 4589) excluding administration time. The administration error rate, including administration associated with time errors, was only 22.5% (888 of 3943) for computerized prescription + UDDDS, compared with 29.3% (189 of 646) for handwritten prescriptions plus WSDS (P < 0.001). Excluding administration associated with time errors, the administration error rates were 9.7% and 24.3%, respectively (P < 0.0001). CONCLUSION: The drug prescription and administration error rates were significantly decreased using computerized prescription plus UDDDS as compared with handwritten prescription plus WSDS in a pediatric unit (even with potential biases taken into account).
