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Background: Metal ions play vital roles in regulating various biological systems, making it essential to control the concentration of free metal ions in solutions during experimental procedures. Several software applications exist for estimating the concentration of free metals in the presence of chelators, with MaxChelator being the easily accessible choice in this domain. This work aimed at developing a Python version of the software with arbitrary precision calculations, extensive new features, and a user-friendly interface to calculate the free metal ions. Results: We introduce the open-source PyChelator web application and the Python-based Google Colaboratory notebook, PyChelator Colab. Key features aim to improve the user experience of metal chelator calculations including input in smaller units, selection among stability constants, input of user-defined constants, and convenient download of all results in Excel format. These features were implemented in Python language by employing Google Colab, facilitating the incorporation of the calculator into other Python-based pipelines and inviting the contributions from the community of Python-using scientists for further enhancements. Arbitrary-precision arithmetic was employed by using the built-in Decimal module to obtain the most accurate results and to avoid rounding errors. No notable differences were observed compared to the results obtained from the PyChelator web application. However, comparison of different sources of stability constants showed substantial differences among them. Conclusions: PyChelator is a user-friendly metal and chelator calculator that provides a platform for further development. It is provided as an interactive web application, freely available for use at https://amrutelab.github.io/PyChelator, and as a Python-based Google Colaboratory notebook at https://colab.research.google.com/github/AmruteLab/PyChelator/blob/main/PyChelator_Colab.ipynb. [ABSTRACT FROM AUTHOR]

Background: The application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates. Results: Through the development and application of simulation software, readsynth, we compare simulated metagenomic sequencing libraries with existing RMS data to assess the influence of multiple library preparation and sequencing steps on downstream analytical results. Based on read depth per position, readsynth achieved 0.79 Pearson's correlation and 0.94 Spearman's correlation to these benchmarks. Application of a novel estimation approach, fixed length taxonomic ratios, improved quantification accuracy of simulated human gut microbial communities when compared to estimates of mean or median coverage. Conclusions: We investigate the possible strengths and weaknesses of applying the RMS technique to profiling microbial communities via simulations with readsynth. The choice of restriction enzymes and size selection steps in library prep are non-trivial decisions that bias downstream profiling and quantification. The simulations investigated in this study illustrate the possible limits of preparing metagenomic libraries with a reduced representation sequencing approach, but also allow for the development of strategies for producing and handling the sequence data produced by this promising application. [ABSTRACT FROM AUTHOR]

Background: Interprofessional primary care teams (IPCTs) work together to enhance care. Despite evidence on the benefits of IPCTs, implementation remains challenging. This research aims to 1) identify and prioritize barriers and enablers, and 2) co-develop team-level strategies to support IPCT implementation in Nova Scotia, Canada. Methods: Healthcare providers and staff of IPCTs were invited to complete an online survey to identify barriers and enablers, and the degree to which each item impacted the functioning of their team. Top ranked items were identified using the sum of frequency x impact for each response. A virtual knowledge sharing event was held to identify strategies to address local barriers and enablers that impact team functioning. Results: IPCT members (n = 117), with a mix of clinic roles and experience, completed the survey. The top three enablers identified were access to technological tools to support their role, standardized processes for using the technological tools, and having a team manager to coordinate collaboration. The top three barriers were limited opportunity for daily team communication, lack of conflict resolution strategies, and lack of capacity building opportunities. IPCT members, administrators, and patients attended the knowledge sharing event (n = 33). Five strategies were identified including: 1) balancing patient needs and provider scope of practice, 2) holding regular and accessible meetings, 3) supporting team development opportunities, 4) supporting professional development, and 5) supporting involvement in non-clinical activities. Interpretation: This research contextualized evidence to further understand local perspectives and experiences of barriers and enablers to the implementation of IPCTs. The knowledge exchange event identified actionable strategies that IPCTs and healthcare administrators can tailor to support teams and care for patients. [ABSTRACT FROM AUTHOR]

Background: The results of high-throughput biology ('omic') experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features. Results: We present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access. Conclusions: OmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator [ABSTRACT FROM AUTHOR]

Background: Treatment-resistant depression (TRD) is defined by the European Medicines Agency as a lack of clinically meaningful improvement after treatment, with at least two different antidepressants. Individual, familiar, and socio-economic burden of TRD is huge. Given the lack of clear guidelines, the large variability of TRD approaches across different countries and the availability of new medications to meet the need of effective and rapid acting therapeutic strategies, it is important to understand the consensus regarding the clinical characteristics and treatment pathways of patients with TRD in Italian routine clinical practice, particularly in view of the recent availability of esketamine nasal spray. Methods: A Delphi questionnaire with 17 statements (with a 7 points Likert scale for agreement) was administered via a customized web-based platform to Italian psychiatrists with at least 5 years of experience and specific expertise in the field of depression. In the second-round physicians were asked to answer the same statements considering the interquartile range of each question as an index of their colleagues' responses. Stata 16.1 software was used for the analyses. Results: Sixty panellists, representative of the Italian territory, answered the questionnaire at the first round. For 8/17 statements more than 75% of panellists reached agreement and a high consensus as they assigned similar scores; for 4 statements the panellists assigned similar scores but in the middle of the Likert scale showing a moderate agreement with the statement, while for 5 statements there was indecision in the agreement and low consensus with the statement. Conclusions: This Delphi Panel showed that there is a wide heterogeneity in Italy in the management of TRD patients, and a compelling need of standardised strategies and treatments specifically approved for TRD. A high level of consensus and agreement was obtained about the importance of adding lithium and/or antipsychotics as augmentation therapies and in the meantime about the need for long-term maintenance therapy. A high level of consensus and agreement was equally reached for the identification of esketamine nasal spray as the best option for TRD patients and for the possibility to administrate without difficulties esketamine in a community outpatient setting, highlighting the benefit of an appropriate educational support for patients. [ABSTRACT FROM AUTHOR]

Background: Detection and counting of wheat heads are of crucial importance in the field of plant science, as they can be used for crop field management, yield prediction, and phenotype analysis. With the widespread application of computer vision technology in plant science, monitoring of automated high-throughput plant phenotyping platforms has become possible. Currently, many innovative methods and new technologies have been proposed that have made significant progress in the accuracy and robustness of wheat head recognition. Nevertheless, these methods are often built on high-performance computing devices and lack practicality. In resource-limited situations, these methods may not be effectively applied and deployed, thereby failing to meet the needs of practical applications. Results: In our recent research on maize tassels, we proposed TasselLFANet, the most advanced neural network for detecting and counting maize tassels. Building on this work, we have now developed a high-real-time lightweight neural network called WheatLFANet for wheat head detection. WheatLFANet features a more compact encoder-decoder structure and an effective multi-dimensional information mapping fusion strategy, allowing it to run efficiently on low-end devices while maintaining high accuracy and practicality. According to the evaluation report on the global wheat head detection dataset, WheatLFANet outperforms other state-of-the-art methods with an average precision AP of 0.900 and an R2 value of 0.949 between predicted values and ground truth values. Moreover, it runs significantly faster than all other methods by an order of magnitude (TasselLFANet: FPS: 61). Conclusions: Extensive experiments have shown that WheatLFANet exhibits better generalization ability than other state-of-the-art methods, and achieved a speed increase of an order of magnitude while maintaining accuracy. The success of this study demonstrates the feasibility of achieving real-time, lightweight detection of wheat heads on low-end devices, and also indicates the usefulness of simple yet powerful neural network designs. [ABSTRACT FROM AUTHOR]

Background: With the ageing population worldwide, falls are becoming a severe and growing health problem. Interprofessional multifactorial fall prevention interventions (FPIs) have effectively prevented falls in community-dwelling older adults. However, the implementation of FPIs often fails due to a lack of interprofessional collaboration. Therefore, gaining insight into the influencing factors of interprofessional collaboration in multifactorial FPI's for older adults living in the community is essential. Consequently, our aim was to provide an overview of factors influencing interprofessional collaboration in multifactorial FPIs for community-dwelling older adults. Methods: This qualitative systematic literature research was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Pubmed, CINAHL, and Embase electronic databases have been systematically searched for eligible articles, with a qualitative design. The quality was appraised using the Checklist for Qualitative Research by the Joann Briggs Institute. The findings were inductively synthesized using a meta-aggregative approach. Confidence in the synthesized findings was established using the ConQual methodology. Results: Five articles were included. Analysis of the included studies resulted in 31 influencing factors for interprofessional collaboration, which were labelled as findings. These findings were summarized in ten categories and combined into five synthesized findings. Results showed that communication, role clarity, information sharing, organization, and interprofessional aim influence interprofessional collaboration in multifactorial FPIs. Conclusions: This review provides a comprehensive summary of findings on interprofessional collaboration, specifically in the context of multifactorial FPIs. Knowledge in this area is considerably relevant given the multifactorial nature of falls, which demands an integrated, multidomain approach, including both health and social care. The results can be utilized as a fundament for developing effective implementation strategies aiming to improve interprofessional collaboration between health and social care professionals working in multifactorial FPIs in the community. [ABSTRACT FROM AUTHOR]

Background: In out-of-hours urgent care practices in Germany, physicians of different specialties care for a large number of patients, most of all unknown to them, resulting in a high workload and challenging diagnostic decision-making. As there is no common patient file, physicians have no information about patients' previous conditions or received treatments. In this setting, a digital tool for medical history taking could improve the quality of medical care. This study aims to implement and evaluate a software application (app) that takes a structured symptom-oriented medical history from patients in urgent care settings. Methods: We conduct a time-cluster-randomized trial in two out-of-hours urgent care practices in Germany for 12 consecutive months. Each week during the study defines a cluster. We will compare participants with (intervention group) and without app use (control group) prior to consultation and provision of the self-reported information for the physician. We expect the app to improve diagnostic accuracy (primary outcome), reduce physicians' perceived diagnostic uncertainty, and increase patients' satisfaction and the satisfaction with communication of both physician and patient (secondary outcomes). Discussion: While similar tools have only been subject to small-scale pilot studies surveying feasibility and usability, the present study uses a rigorous study design to measure outcomes that are directly associated with the quality of delivered care. Trial registration: The study was registered at the German Clinical Trials Register (No. DRKS00026659 registered Nov 03 2021. World Health Organization Trial Registration Data Set, https://trialsearch.who.int/Trial2.aspx? TrialID = DRKS00026659. [ABSTRACT FROM AUTHOR]

Background: Though evidence on the detrimental impact of the COVID-19 pandemic in nursing homes is vast, research focusing on general practitioners' (GP) care during the pandemic in nursing homes is still scarce. Methods: A retrospective online survey among 1,010 nursing home managers in Germany was conducted during the first wave of the COVID-19 pandemic between November 2020 and February 2021. Associations between perceived deficits in GP care (routine and acute visits) and both general and COVID-19-related characteristics of nursing homes were analysed using multiple logistic regression analyses. Results: The majority of nursing home managers reported no deficits in GP care (routine visits, 84.3%; acute visits, 92.9%). Logistic regression analyses revealed that deficits in GP care (routine visits) were significantly associated with visiting restrictions for GPs and nursing home size. Small nursing homes (1–50 residents) were significantly more likely to report deficits in GP care (routine visits) compared to medium (51–100 residents) and large nursing homes (> 100 residents). Further, deficits in GP care (acute visits) were significantly associated with dementia as a focus of care and the burden of insufficient testing for SARS-CoV-2 among residents. Moreover, visiting restrictions for GPs were significantly associated with dementia as the focus of care and the COVID-19 incidence at the federal state level. Finally, COVID-19 cases in nursing homes were significantly associated with size of nursing homes, COVID-19-incidence on the federal state level and the burden of insufficient testing capacities for SARS-CoV-2 among residents. Conclusion: We found structural factors associated with GP care deficits during the pandemic. New concepts for GP care should be implemented in pandemic preparedness plans to ensure high quality, consistent, and reliable GP care as well as effective infection prevention measures in nursing homes. [ABSTRACT FROM AUTHOR]

Background: Falls are common among adults aged 60 years and older because of physiological changes. Most falls in older adults occur most often at home. Coupled with the lack of awareness and knowledge of preventing falls, the proportion of injuries and deaths among older adults due to falls is increasing yearly. Our study developed a WeChat mini-program for urban elderly to implement teach-back health education (TBHE) that a repeated cycle process of health education, assessment, and re-education in preventing falls at home.Objectives: This study aimed to evaluate the application effect of the TBHE-based WeChat mini-program on health education knowledge for fall prevention at home for urban older adults.Design: A single-blinded, two-arm parallel-group, randomized controlled trial was conducted.Setting: Three residential communities, named Hot Spring Apartment, Hualinyuan, and Dongtang Community in Gulou District, Fuzhou, China.Participants: Participants were older adults recruited from communities in Fuzhou from January to March 2021.Methods: Fifty-nine participants agreed to participate and were assigned randomly to the intervention group (n = 29) or the control group receiving traditional health education (n = 30). Each participant in the intervention group received twice a week for a total of 8 weeks of health education interventions performed by the first author that she is intervenor according to specific themes. The trial statistician, recruiters, and participants were blinded to group allocation. The intervenor (first author) was blinded to the study hypotheses. To evaluate the effects of the intervention, we assessed participants' knowledge total score and scores of physiology and disease; drug application; mental, cognitive, and spiritual well-being; lifestyle; and house environment at baseline and 1-week post-intervention and compared scores between two groups. A two-way repeated-measures analysis of variance was conducted to examine the effects of time, group, and their interaction.Results: There was a significant difference in knowledge of house environment (p = 0.003) between the two groups. Within groups, total and five dimensions knowledge scores had a significant difference (p < 0.001). Moreover, interaction effects were significant on drug application (p = 0.012) and mental, cognitive, and spiritual well-being (p = 0.015).Conclusions: The TBHE can improve knowledge on fall prevention at home among urban older adults. The TBHE based on the WeChat mini-program could enhance the efficiency and effectiveness of being educated among urban older adults.Trial Registration: Chinese Clinical Trial Register: ChiCTR2100052946 ; reg date: 06/11/2021. [ABSTRACT FROM AUTHOR]

Background: Overall, 55% of the German population suffers from primary episodic headaches according to recent studies. Inadequate management of headache disorders is a significant medical problem. The prevalence of medication overuse headache (MOH) is about 1% with an estimated number of 800,000 people in Germany. Medication overuse (MO) and MOH are usually managed through a complex process of medication withdrawal and initiating of prophylaxis. However, patients who were successfully treated for MO or MOH have a high relapse rate in the following 2 years. Previously, continued monitoring of self-reported medication intake demonstrated lower relapse rates. The prevalence and burden of MO and MOH are high, and effective strategies to prevent the development of a relapse into MOH or de novo MOH are still missing. Therefore, the MOH trial was designed to assess the effects of combining self-reported medication intake with daily monitoring of the entered data and a personalized patient-specific medication intake feedback system in an easy-accessible app-based platform in order to prevent the development and relapse of MO(H).Methods: The MOH trial is a randomized, controlled, parallel, multicenter, prospective trial. A total of 624 migraine patients with frequent migraine attacks and 336 patients who underwent treatment for MO(H) will be randomly allocated to use either a customized app with or without individual feedback regarding their self-reported medication intake for 12 months. The primary outcome will be the proportion of patients developing MO or MOH for at least 3 consecutive months between baseline and end of study visits.Discussion: This trial will assess the effects of providing patients with feedback regarding their self-reported use of migraine medications and migraine days using a mobile software on the development or prevention of MO(H). We hypothesize that the development of MO(H) in patients with frequent episodic migraine (EM) or chronic migraine (CM) and relapse after treatment of MO(H) can be reduced by a feedback system. If this trial proves that using an app with specific and unspecific messaging to the patient is successful, this method, which is now investigated mainly in specialized headache centers, could later be extended to primary care, thus providing benefits for a broader patient group.Trial Registration: German Clinical Trials Register DRKS00025961 . Registered on 04 August 2021. [ABSTRACT FROM AUTHOR]

Background: Partnership between local government and local health districts is imperative, given their overlapping goals. However, the need for further evidence-informed actions to address health inequities remains. The effectiveness of such partnerships requires better insight into how local governments perceive partnerships with local health districts, and how well equipped and prepared they are to deal with the health equity opportunities and challenges. It was precisely for these reasons that a qualitative study was conducted by South Western Sydney Local Health District (SWSLHD) in 2016.Objective: This study aims to better understand how to improve the effectiveness of collaboration between local governments and the public health sector.Methods: Qualitative data were collected from 14 in-depth interviews with staff representing five of the local councils comprising SWSLHD. These data were then thematically analysed using inductive and deductive reasoning through the application of NVivo software.Results: While councils recognize the potential value of consulting SWSLHD, limited communication and the absence of a clearly defined process for collaboration needs to be addressed. Moreover, councils perceive knowledge gaps in relation to basic issues, such as who provides what services to whom, and how to access local-government-level data from health experts.Conclusions: The study confirms the importance of providing locally relevant public health data to help address issues of mutual concern that arise during the consultation process. Moreover, it suggests that proactive and ongoing consultation between SWSLHD and councils is critical if there is to be effective engagement, and coordinated and sustained action. The concerns raised in this study echo findings from studies from other local government settings of Victoria, South Australia and New South Wales. Thus, the study findings may be applied to other councils beyond the SWSLHD. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews are the cornerstone of evidence-based medicine. However, systematic reviews are time consuming and there is growing demand to produce evidence more quickly, while maintaining robust methods. In recent years, artificial intelligence and active-machine learning (AML) have been implemented into several SR software applications. As some of the barriers to adoption of new technologies are the challenges in set-up and how best to use these technologies, we have provided different situations and considerations for knowledge synthesis teams to consider when using artificial intelligence and AML for title and abstract screening.Methods: We retrospectively evaluated the implementation and performance of AML across a set of ten historically completed systematic reviews. Based upon the findings from this work and in consideration of the barriers we have encountered and navigated during the past 24 months in using these tools prospectively in our research, we discussed and developed a series of practical recommendations for research teams to consider in seeking to implement AML tools for citation screening into their workflow.Results: We developed a seven-step framework and provide guidance for when and how to integrate artificial intelligence and AML into the title and abstract screening process. Steps include: (1) Consulting with Knowledge user/Expert Panel; (2) Developing the search strategy; (3) Preparing your review team; (4) Preparing your database; (5) Building the initial training set; (6) Ongoing screening; and (7) Truncating screening. During Step 6 and/or 7, you may also choose to optimize your team, by shifting some members to other review stages (e.g., full-text screening, data extraction).Conclusion: Artificial intelligence and, more specifically, AML are well-developed tools for title and abstract screening and can be integrated into the screening process in several ways. Regardless of the method chosen, transparent reporting of these methods is critical for future studies evaluating artificial intelligence and AML. [ABSTRACT FROM AUTHOR]

Background: A crucial aspect of continued senior care is the early detection and management of frailty. Developing reliable and secure electronic frailty assessment tools can benefit virtual appointments, a need especially relevant in the context of the COVID-19 pandemic. An emerging effort has targeted web-based software applications to improve accessibility and usage. The objectives of this scoping review are to identify and evaluate web-based frailty assessment tools currently available and to identify challenges and opportunities for future development.Methods: We conducted a review with literature (e.g., using MEDLINE databases) and Google searches (last updated on October 10, 2021). Each of the identified web applications were assessed based on eight featured categories and assigned a rating score accordingly.Results: Twelve web-based frailty assessment applications were found, chiefly provided by the USA (50%) or European countries (41%) and focused on frailty grading and outcome prediction for specific patient groups (59%). Categories that scored well among the applications included the User Interface (2.8/3) and the Cost (2.7/3). Other categories had a mean score of 1.6/3 or lower. The least developed feature was Data Saving.Conclusions: Web-based applications represent a viable option for remote frailty assessments and multidisciplinary integrated care of older adults. Despite the available web-based frailty assessments on the Internet, many missed certain needed features for professional use in healthcare settings. This situation calls for fully comprehensive web-based applications, taking into consideration a number of key functions linking graphical user interface and functionalities, and paying special attention to secure data management. [ABSTRACT FROM AUTHOR]

Background: This study evaluating the effect of web application media in increasing the caries risk knowledge and decreasing the caries risk scores among dental students. Methods: A quasi-experimental design along with a purposive sampling technique was used in this study. A total of 361 undergraduate pre-clinical dental students from 15 universities in Indonesia were divided into two groups: intervention (n = 282) and control (n = 79). The students in the intervention group received a web application media with educational materials to independently check their caries risk, whereas those in the control group received the application without any educational materials. The students were instructed to use the web application at least once a week for 21 days and complete the pretest and posttest questionnaires and web application evaluation questionnaires. In addition, they were required to independently examine their initial and final caries risk. Results: A significant increase in the level of knowledge was observed in the intervention group, but not in the control group, after the use of the web application. Each group showed a decrease in the caries risk score, but the difference was not statistically significant before and after the use of a web application in both groups. Conclusion: These findings indicate that health promotion and education about caries risk through web application media can improve the knowledge and reduce the caries risk in dental dentistry students. [ABSTRACT FROM AUTHOR]