Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains.

Because of the growing number of clinical antibiotic resistance cases in recent years, novel antimicrobial peptides (AMPs) may be ideal for next-generation antibiotics. This study trained a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) based on known AMPs to generate novel AMP candidates. The quality of the GAN-designed peptides was evaluated in silico, and eight of them, named GAN-pep 1-8, were selected by an AMP Artificial Intelligence (AI) classifier and synthesized for further experiments. Disc diffusion testing and minimum inhibitory concentration (MIC) determinations were used to identify the antibacterial effects of the synthesized GAN-designed peptides. Seven of the eight synthesized GAN-designed peptides displayed antibacterial activity. Additionally, GAN-pep 3 and GAN-pep 8 presented a broad spectrum of antibacterial effects and were effective against antibiotic-resistant bacteria strains, such as methicillin-resistant Staphylococcus aureus and carbapenem-resistant Pseudomonas aeruginosa. GAN-pep 3, the most promising GAN-designed peptide candidate, had low MICs against all the tested bacteria. In brief, our approach shows an efficient way to discover AMPs effective against general and antibiotic-resistant bacteria strains. In addition, such a strategy also allows other novel functional peptides to be quickly designed, identified, and synthesized for validation on the wet bench.

The individualized supervision strategy and effectiveness under the strength perspective: a pilot study for the case management model of the high-care elderly in communities.

BACKGROUND: This study tried to improve the operational efficiency and service quality of the community case management model for the High-Care Elderly in Communities in Taiwan. This study tried to assistant social workers in community care sites to establish individualized treatment planning, to empower them with flexibility to discover and utilize their own unique strengths, to reach the goal of developing community care capacity. METHODS: A case consulting model was employed in this study by providing case by case supervision service. We collected all supervision meeting records and related data as our qualitative research materials, analyzed these materials and tried to define intervention effectiveness of the individualized supervision strategy under the strength perspective applied to the case management model of the high-care elderly in communities. To find out what helps these social workers the most, and how these social workers realize and recognize their process and key to improve their service quality and work efficiency, in the way of qualitative interpretation. RESULTS: A supervision model under the perspective of strength was developed in this study, and was applied to clinical community care sites to help their social workers. The results proved that our supervision model provided an opportunity to empower and re-know themselves, re-establish their professional confidence and meaning of existence for their organization, and eventually produced positive effect to quality of service and service receiver's satisfaction improvement. The key feature that made this supervision model of the strength perspective work was to let social workers have the autonomy to interpret the challenges they face and to think possible alternative solutions creatively. CONCLUSIONS: This study showed that create a supervisee-friendly psycho-socio environment empowered these workers by increasing their resource network and taking advantage of what they still have and what they were good at, this could help these workers upgrade their level on ladders of empowerment, become an active and independent professional worker that have power and confidence to make treatment and intervention.

AI4AMP: an Antimicrobial Peptide Predictor Using Physicochemical Property-Based Encoding Method and Deep Learning.

Antimicrobial peptides (AMPs) are innate immune components that have recently stimulated considerable interest among drug developers due to their potential as antibiotic substitutes. AMPs are notable for their fundamental properties of microbial membrane structural interference and the biomedical applications of killing or suppressing microbes. New AMP candidates must be developed to oppose antibiotic resistance. However, the discovery of novel AMPs through wet-lab screening approaches is inefficient and expensive. The prediction model investigated in this study may help accelerate this process. We collected both the up-to-date AMP data set and unbiased negatives based on which the protein-encoding methods and deep learning model for AMPs were investigated. The external testing results indicated that our trained model achieved 90% precision, outperforming current methods. We implemented our model on a user-friendly web server, AI4AMP, to accurately predict the antimicrobial potential of a given protein sequence and perform proteome screening. IMPORTANCE Antimicrobial peptides (AMPs) are innate immune components that have aroused a great deal of interest among drug developers recently, as they may become a substitute for antibiotics. New candidates need to fight antibiotic resistance, while discovering novel AMPs through wet-lab screening approaches is inefficient and expensive. To accelerate the discovery of new AMPs, we both collected the up-to-date antimicrobial peptide data set and integrated the protein-encoding methods with a deep learning model. The trained model outperforms the current methods and is implemented into a user-friendly web server, AI4AMP, to accurately predict the antimicrobial properties of a given protein sequence and perform proteome screening. Author Video: An author video summary of this article is available.

Systematic Review and Meta-Analysis on Using Acupressure to Promote the Health of Older Adults.

Acupressure is noninvasive, safe, and appropriate for use among older adults. However, there remains little evidence of the common elements that contribute to the effectiveness of acupressure in promoting the health of older adults. A systematic review using meta-analysis was designed to examine the effects of acupressure on the health promotion in older adults. Studies published between 2012 and 2017 were searched for in 11 electronic databases. Acupressure was highly effective for improving sleep quality and cognitive functioning (0.85, 95% confidence interval [CI] = [0.49, 1.22]; 1.23, 95% CI = [0.88, 1.59]). A slight to moderate effect was found in alleviating constipation (0.37, 95% CI = [0.03, 0.71]), and a moderate effect was found for alleviating pain and improving quality of life (0.71, 95% CI = [0.09, 1.32]; 0.59 95% CI = [0.36, 0.82]).

Prevalence and demographic characteristics of high-need community-dwelling older adults in Taiwan.

By early screening, the high-need older adults who require multiple care needs and resources can be identified and the necessary assistance can then be provided. However, a precise definition of and related research on high-need older adults are limited. Identifying older adults with high needs is of practical urgency. This study aimed to investigate the prevalence of high-need community-dwelling older adults and to identify the characteristic differences between high-need older adults and those without high needs. This cross-sectional descriptive survey research was conducted between July and December 2018 and used a simple random sampling to select older adults aged 65 and older who had lived in the community for at least 3 months. The High-need Community-dwelling Older Adults Screening Scale was used to identify high-need older adults in the community. A total of 818 community-dwelling older adults were surveyed and the prevalence of high-need older adults was 24.1%. Those screened as high-need older adults (n = 197) were 78.58 (SD = 7.60) years old in average, mostly female, widowed or single but living with someone, had chronic illnesses (M = 2.11, SD = 1.41), an elementary school level of education and religious beliefs. Furthermore, differences were found between older adults with high needs (n = 197) and those without high needs (n = 621) where there is a significantly higher proportion of high-need older adults who were 85 years and older, being male, widowed or single, illiterate, living alone, had chronic illnesses and no religious belief. The high prevalence of high-need community-dwelling older adults highlighted the importance of screening. If community care centres are provided with a comprehensive screening tool for finding high-need older adults during home visits, this would lead to timely identification of older adults with potential needs and enhance the preventive nature of home visits.