Brief Bioinform. 2023 Jan 11:bbac606. doi: 10.1093/bib/bbac606. Online ahead of print.

ABSTRACT

Recently, peptide-based drugs have gained unprecedented interest in discovering and developing antifungal drugs due to their high efficacy, broad-spectrum activity, low toxicity and few side effects. However, it is time-consuming and expensive to identify antifungal peptides (AFPs) experimentally. Therefore, computational methods for accurately predicting AFPs are highly required. In this work, we develop AFP-MFL, a novel deep learning model that predicts AFPs only relying on peptide sequences without using any structural information. AFP-MFL first constructs comprehensive feature profiles of AFPs, including contextual semantic information derived from a pre-trained protein language model, evolutionary information, and physicochemical properties. Subsequently, the co-attention mechanism is utilized to integrate contextual semantic information with evolutionary information and physicochemical properties separately. Extensive experiments show that AFP-MFL outperforms state-of-the-art models on four independent test datasets. Furthermore, the SHAP method is employed to explore each feature contribution to the AFPs prediction. Finally, a user-friendly web server of the proposed AFP-MFL is developed and freely accessible at http://inner.wei-group.net/AFPMFL/, which can be considered as a powerful tool for the rapid screening and identification of novel AFPs.

PMID:36631407 | DOI:10.1093/bib/bbac606

J Alzheimers Dis. 2023 Jan 3. doi: 10.3233/JAD-220832. Online ahead of print.

ABSTRACT

BACKGROUND: Loneliness has been highlighted as a risk factor for dementia. However, the nature of the relationship between loneliness and cognitive function prior to onset of dementia is unclear.

OBJECTIVE: The aim of this systematic review and meta-analysis was to examine the relationship between loneliness and cognitive function in samples screened for dementia at study commencement.

METHODS: Five electronic databases (PubMed, PsycNET, Web of Science, EBSCOhost, Scopus) were searched from inception to August 31, 2021. A narrative review and random-effects meta-analysis were conducted on studies meeting search criteria. PROSPERO registration number: CRD42020155539.

RESULTS: The sixteen studies that met inclusion criteria involved 30,267 individuals, with mean age ranging from 63.0 to 84.9 years. Studies varied in dementia screening criteria, measurement of loneliness and cognitive function, and statistical modeling approach. The narrative review indicated that loneliness was associated with poorer global cognition, episodic memory, working memory, visuospatial function, processing speed, and semantic verbal fluency. Results of the meta-analysis indicated that loneliness was negatively associated with global cognitive function (overall r = -0.08; 95% CI = -0.14, -0.02; n = 6). Due to lack of sufficient data and heterogeneity between studies, we were unable to explore associations with other cognitive domains or longitudinal associations.

CONCLUSION: Loneliness is associated with subtle impairment across multiple cognitive domains in older adults who were screened for dementia. Better characterization of this relationship will provide important information about how loneliness contributes to the clinical and pathological sequalae of AD and be informative for risk reduction and early detection strategies.

PMID:36617781 | DOI:10.3233/JAD-220832

Brain Commun. 2022 Dec 8;5(1):fcac322. doi: 10.1093/braincomms/fcac322. eCollection 2023.

ABSTRACT

The replication crisis poses important challenges to modern science. Central to this challenge is re-establishing ground truths or the most fundamental theories that serve as the bedrock to a scientific community. However, the goal to identify hypotheses with the greatest support is non-trivial given the unprecedented rate of scientific publishing. In this era of high-volume science, the goal of this study is to sample from one research community within clinical neuroscience (traumatic brain injury) and track major trends that have shaped this literature over the past 50 years. To do so, we first conduct a decade-wise (1980-2019) network analysis to examine the scientific communities that shape this literature. To establish the robustness of our findings, we utilized searches from separate search engines (Web of Science; Semantic Scholar). As a second goal, we sought to determine the most highly cited hypotheses influencing the literature in each decade. In a third goal, we then searched for any papers referring to 'replication' or efforts to reproduce findings within our >50 000 paper dataset. From this search, 550 papers were analysed to determine the frequency and nature of formal replication studies over time. Finally, to maximize transparency, we provide a detailed procedure for the creation and analysis of our dataset, including a discussion of each of our major decision points, to facilitate similar efforts in other areas of neuroscience. We found that the unparalleled rate of scientific publishing within the brain injury literature combined with the scarcity of clear hypotheses in individual publications is a challenge to both evaluating accepted findings and determining paths forward to accelerate science. Additionally, while the conversation about reproducibility has increased over the past decade, the rate of published replication studies continues to be a negligible proportion of the research. Meta-science and computational methods offer the critical opportunity to assess the state of the science and illuminate pathways forward, but ultimately there is structural change needed in the brain injury literature and perhaps others.

PMID:36601624 | PMC:PMC9806718 | DOI:10.1093/braincomms/fcac322

J Asthma. 2023 Aug;60(8):1584-1591. doi: 10.1080/02770903.2022.2164200. Epub 2023 Feb 3.

ABSTRACT

OBJECTIVES: To (1) describe primary health care utilization and (2) estimate the effect of primary care early follow-up, continuity, regularity, frequency, and long consultations on asthma hospital readmission, including secondary outcomes of emergency (ED) presentations, asthma preventer adherence, and use of rescue oral corticosteroids within 12 months.

METHODS: An Australian multi-site cohort study of 767 children aged 3-18 years admitted with asthma between 2017 and 2018, followed up for at least 12 months with outcome and primary care exposure data obtained through linked administrative datasets. We estimated the effect of primary care utilization through a modified Poisson regression adjusting for child age, asthma severity, socioeconomic status and self-reported GP characteristics.

RESULTS: The median number of general practitioner (GP) consultations, unique GPs and clinics visited was 9, 5, and 4, respectively. GP care was irregular and lacked continuity, only 152 (19.8%) children visited their usual GP on more than 60% of occasions. After adjusting for confounders, there was overall weak indication of effects due to any of the exposures. Increased frequency of GP visits was associated with reduced readmissions (4-14 visits associated with risk ratio of 0.71, 95% CI 0.50-1.00, p = 0.05) and ED presentations (>14 visits associated risk ratio 0.62, 95% CI 0.42-0.91, p = 0.02).

CONCLUSIONS: Our study demonstrates that primary care use by children with asthma is often irregular and lacking in continuity. This highlights the importance of improving accessibility, consistency in care, and streamlining discharge communication from acute health services.

PMID:36594684 | DOI:10.1080/02770903.2022.2164200

JMIR Public Health Surveill. 2022 Dec 23;8(12):e24938. doi: 10.2196/24938.

ABSTRACT

BACKGROUND: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends.

OBJECTIVE: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web forum data Prescription Drug Abuse Online Surveillance; analyzing patterns and trends of cannabis product use in the context of evolving cannabis legalization policies in the United States through analysis of Twitter and web forum data (eDrugTrends); assessing trends in the availability of novel synthetic opioids through the analysis of cryptomarket data (eDarkTrends); and analyzing COVID-19 pandemic trends in social media data related to 13 states in the United States as per Mental Health America reports.

METHODS: The domain and scope of the DAO were defined using competency questions from popular ontology methodology (101 ontology development). The 101 method includes determining the domain and scope of ontology, reusing existing knowledge, enumerating important terms in ontology, defining the classes, their properties and creating instances of the classes. The quality of the ontology was evaluated using a set of tools and best practices recognized by the semantic web community and the artificial intelligence community that engage in natural language processing.

RESULTS: The current version of the DAO comprises 315 classes, 31 relationships, and 814 instances among the classes. The ontology is flexible and can easily accommodate new concepts. The integration of the ontology with machine learning algorithms dramatically decreased the false alarm rate by adding external knowledge to the machine learning process. The ontology is recurrently updated to capture evolving concepts in different contexts and applied to analyze data related to social media and dark web marketplaces.

CONCLUSIONS: The DAO provides a powerful framework and a useful resource that can be expanded and adapted to a wide range of substance use and mental health domains to help advance big data analytics of web-based data for substance use epidemiology research.

PMID:36563032 | DOI:10.2196/24938

Health Informatics J. 2022 Oct-Dec;28(4):14604582221146720. doi: 10.1177/14604582221146720.

NO ABSTRACT

PMID:36548199 | DOI:10.1177/14604582221146720

Front Hum Neurosci. 2022 Dec 5;16:1027446. doi: 10.3389/fnhum.2022.1027446. eCollection 2022.

NO ABSTRACT

PMID:36545349 | PMC:PMC9760723 | DOI:10.3389/fnhum.2022.1027446

Schizophr Bull. 2023 Mar 15;49(2):498-506. doi: 10.1093/schbul/sbac157.

ABSTRACT

OBJECTIVES: Schizophrenia is a mental illness that presents with thought disorders including delusions and disorganized speech. Thought disorders have been regarded as a consequence of the loosening of associations between semantic concepts since the term "schizophrenia" was first coined by Bleuler. However, a mechanistic account of this cardinal disturbance in terms of functional dysconnection has been lacking. To evaluate how aberrant semantic connections are expressed through brain activity, we characterized large-scale network structures of concept representations using functional magnetic resonance imaging (fMRI).

STUDY DESIGN: We quantified various concept representations in patients' brains from fMRI activity evoked by movie scenes using encoding modeling. We then constructed semantic brain networks by evaluating the similarity of these semantic representations and conducted graph theory-based network analyses.

STUDY RESULTS: Neurotypical networks had small-world properties similar to those of natural languages, suggesting small-worldness as a universal property in semantic knowledge networks. Conversely, small-worldness was significantly reduced in networks of schizophrenia patients and was correlated with psychological measures of delusions. Patients' semantic networks were partitioned into more distinct categories and had more random within-category structures than those of controls.

CONCLUSIONS: The differences in conceptual representations manifest altered semantic clustering and associative intrusions that underlie thought disorders. This is the first study to provide pathophysiological evidence for the loosening of associations as reflected in randomization of semantic networks in schizophrenia. Our method provides a promising approach for understanding the neural basis of altered or creative inner experiences of individuals with mental illness or exceptional abilities, respectively.

PMID:36542452 | PMC:PMC10016409 | DOI:10.1093/schbul/sbac157

JMIR Med Inform. 2022 Dec 18. doi: 10.2196/43053. Online ahead of print.

NO ABSTRACT

PMID:36534739 | DOI:10.2196/43053

JMIR Med Inform. 2022 Dec 19;10(12):e42664. doi: 10.2196/42664.

NO ABSTRACT

PMID:36534448 | DOI:10.2196/42664

Biophys Rev. 2022 Dec 9:1-6. doi: 10.1007/s12551-022-01021-w. Online ahead of print.

NO ABSTRACT

PMID:36532871 | PMC:PMC9734456 | DOI:10.1007/s12551-022-01021-w

PeerJ Comput Sci. 2022 Dec 8;8:e1163. doi: 10.7717/peerj-cs.1163. eCollection 2022.

NO ABSTRACT

PMID:36532807 | PMC:PMC9748814 | DOI:10.7717/peerj-cs.1163

Front Public Health. 2022 Dec 2;10:1056575. doi: 10.3389/fpubh.2022.1056575. eCollection 2022.

NO ABSTRACT

PMID:36530722 | PMC:PMC9755165 | DOI:10.3389/fpubh.2022.1056575

Comput Biol Med. 2022 Dec 6;152:106415. doi: 10.1016/j.compbiomed.2022.106415. Online ahead of print.

NO ABSTRACT

PMID:36527782 | DOI:10.1016/j.compbiomed.2022.106415

Acc Chem Res. 2022 Dec 14. doi: 10.1021/acs.accounts.2c00617. Online ahead of print.

NO ABSTRACT

PMID:36516456 | DOI:10.1021/acs.accounts.2c00617

Cancer Epidemiol. 2023 Feb;82:102296. doi: 10.1016/j.canep.2022.102296. Epub 2022 Dec 9.

ABSTRACT

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are environmental contaminants that are potentially harmful to health. We examined if rates of selected cancers and causes of deaths were elevated in three Australian communities with local environmental contamination caused by firefighting foams containing PFAS. The affected Australian communities were Katherine in Northern Territory, Oakey in Queensland and Williamtown in New South Wales.

METHODS: All residents identified in the Medicare Enrolment File (1983-2019)-a consumer directory for Australia's universal healthcare-who ever lived in an exposure area (Katherine, Oakey and Williamtown), and a sample of those who ever lived in selected comparison areas, were linked to the Australian Cancer Database (1982-2017) and National Death Index (1980-2019). We estimated standardised incidence ratios (SIRs) for 23 cancer outcomes, four causes of death and three control outcomes, adjusting for sex, age and calendar time of diagnosis.

FINDINGS: We observed higher rates of prostate cancer (SIR=1·76, 95 % confidence interval (CI) 1·36-2·24) in Katherine; laryngeal cancer (SIR=2·71, 95 % CI 1·30-4·98), kidney cancer (SIR=1·82, 95 % CI 1·04-2·96) and coronary heart disease (CHD) mortality (SIR=1·81, 95 % CI 1·46-2·33) in Oakey; and lung cancer (SIR=1·83, 95 % CI 1·39-2·38) and CHD mortality (SIR=1·22, 95 % CI 1·01-1·47) in Williamtown. We also saw elevated SIRs for control outcomes. SIRs for all other outcomes and overall cancer were similar across exposure and comparison areas.

INTERPRETATION: There was limited evidence to support an association between living in a PFAS exposure area and risks of cancers or cause-specific deaths.

PMID:36508965 | DOI:10.1016/j.canep.2022.102296

Sci Rep. 2022 Dec 12;12(1):21459. doi: 10.1038/s41598-022-11698-4.

NO ABSTRACT

PMID:36509768 | PMC:PMC9744829 | DOI:10.1038/s41598-022-11698-4

Proc Int Conf Distrib Comput Syst. 2022 Jul;2022:1306-1309. doi: 10.1109/icdcs54860.2022.00143. Epub 2022 Oct 13.

NO ABSTRACT

PMID:36506615 | PMC:PMC9732836 | DOI:10.1109/icdcs54860.2022.00143

Med Phys. 2022 Dec 9. doi: 10.1002/mp.16105. Online ahead of print.

NO ABSTRACT

PMID:36493420 | DOI:10.1002/mp.16105

Geospat Health. 2022 Nov 29;17(2). doi: 10.4081/gh.2022.1171.

NO ABSTRACT

PMID:36468586 | DOI:10.4081/gh.2022.1171