Search

Background: The Peyronie's Disease Questionnaire (PDQ) was designed to quantitatively assess the symptoms and psychosexual consequences of Peyronie's disease but has only been validated in four languages. The aim of the study was to provide a French translation of the PDQ, to make it available to the French-speaking urology community., Methods: After a double translation of the PDQ from English into French, followed by a back translation by four expert translators, a conciliation process enabled the creation of the final French version. For each item, participants were asked to answer two sub-questions. The percentage of responses "I fully understood the question" to sub-question a) constituted the validation criterion for the translation., Results: The final French version was submitted to a series of 30 men with Peyronie's disease whose average age was 59 (±12) years. For each question, the comprehension rate was over 95%, and for 12/15 items it was 100%. For the remaining 3 items, men declared that they did not feel disturbed or bothered by the questions and none of the questions were misunderstood., Conclusion: This pilot study shows that our translation of the PDQ is valid and comprehensible by all participants, regardless of the age or level of education. This French version should be validated further in other French-speaking populations before final validation., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Arsenic is a ubiquitous toxic metalloid causing serious health problems. Speciation analysis of arsenic in human urine provides valuable insights for large-scale epidemiological studies and informs on sources of exposure as well as human metabolism. The Multi-Ethnic Study of Atherosclerosis (MESA) is a valuable cohort for assessing chronic low-moderate arsenic exposure and health effects in an ethnically diverse US population. We present a state-of-the-art arsenic speciation analysis methodology and its application to 7677 MESA spot urine samples based on high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. This method is fast, robust and detects a total of 11 individual As species at method detection limits of 0.02-0.03 μg arsenic/L urine for each individual species. Our analytical approach features excellent mean method accuracy (98%) and precision (5%) for the main arsenic species in urine (arsenobetaine, methylarsonic acid, dimethylarsinic acid, and total inorganic As); intra- (3-6%) and inter-day coefficients of variability (5-6%); column recovery (96 ± 7%); and spike recovery (97 ± 6%). The main arsenic species were detectable in ≥95% of urine samples due to the implementation of an oxidation step. Each individual minor arsenic species was detectable in ≤25% of all urines, although at least one of them was detected in almost half the participants. We identified two minor urinary arsenic species as dimethylarsinoylacetic acid and dimethylarsinoylpropionic acid, potential metabolites of seafood-related arsenicals. We observed differences in individual As species excretion by race/ethnicity, with Asian-American participants featuring 3-4 times higher concentrations compared to other participants. We also found differences by site, body mass index, smoking status, rice intake, and water arsenic levels, potentially indicating different exposures or related to individual bio-metabolism. The proposed approach is suitable for epidemiological studies and the collected data will constitute the base for future research on potential health effects of chronic low-level arsenic exposure., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Several authors report financial support was provided by National Heart Lung and Blood Institute. Several authors report financial support was provided by National Center for Advancing Translational Sciences. Several authors report financial support was provided by National Institute of Environmental Health Sciences. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this work., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: OpenAI's ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what., Objective: This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform., Methods: In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers., Results: Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349)., Conclusions: This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology., (©Oluwatobiloba Ayo-Ajibola, Ryan J Davis, Matthew E Lin, Jeffrey Riddell, Richard L Kravitz. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.08.2024.)

This study summarized the physicochemical analysis of 609 honey samples originating from the Republic of Serbia. Variations among honey samples from different botanical origins, regions of collections, and harvest years were exposed to descriptive statistics and correlation analysis that differentiated honey samples. Furthermore, most of the observed physicochemical parameters (glucose, fructose, sucrose content, 5-hydroxymethylfurfural (5-HMF) levels, acidity, and electrical conductivity) varied significantly among different types of honey, years, and regions. At the same time, no noticeable difference was found in diastase activity, moisture content, and insoluble matter. Based on the obtained results, 22 honey samples could be considered adulterated, due to the irregular content of sucrose, 5-HMF, acidity, and diastase activity. In addition, 64 honey samples were suspected to be adulterated. Adulterated and non-compliant samples present a relatively low percentage (14.1%) of the total number of investigated samples. Consequently, a considerable number of honey samples met the required standards for honey quality. Overall, these findings provide insights into compositional and quality differences among various types of honey, aiding in understanding their characteristics and potential applications.

Objectives: Soil salinity affects the growth of crop plants, leading to reduced productivity, and is a major challenge for wheat production worldwide. Various adaptations and mitigation approaches in combination with tolerant wheat genotypes can be useful for the sustainability of crop production in saline environments. However, the development of salt-tolerant wheat genotypes is one of the best and most efficient solutions for obtaining desirable yields. Considering these issues, an investigation was carried out under hydroponic nutrient culture conditions to assess the genetic variability and selection of salt-tolerant wheat genotypes by categorizing inequitable morphophysiological and genetic variability as well as multivariate analysis., Methods: To meet the objectives of this study, 100 wheat genotypes were tested hydroponically in 0 (control) and 15 dS m -1 salt solutions., Conclusion: For all the wheat genotypes grown under saline conditions, the shoot length (SL), root length (RL), shoot fresh weight (SFW), root fresh weight (RFW), total fresh weight (TFW), shoot dry weight (SDW), root dry weight (RDW), and total dry weight (TDW) decreased significantly. Furthermore, significant variation was observed among the genotypes in terms of their characteristics only under saline conditions. In the case of genetic diversity analysis, a high genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), genetic advance in the percentage of the mean (GAM) and high heritability (h 2 b) were recorded for all tested wheat genotypes based on the SDW, RDW and TDW. Correlation analysis for both genotypic and phenotypic relationships revealed strong positive correlations for TDW, SDW, TFW and SFW. Principal component analysis (PCA) revealed that TDW, TFW, SDW, and SFW were the most discriminative variables for the wheat genotypes, which was confirmed by discriminant function analysis (DFA). PCA-biplot analysis also revealed significant positive correlations between SDW and SFW and between TDW and TFW. Hierarchical cluster analysis was performed for ten clusters based on the relative performance of the genotypes, where the genotypes were characterized into salt-tolerant, medium-salt-tolerant, medium-salt-susceptible and salt-susceptible groups. Among the genotypes, G11, G25 and G29 under cluster VII were categorized as salt tolerant based on their outstanding performance in terms of characteristics only under saline conditions. D 2 analysis proved that the wheat genotypes of this cluster were highly divergent from the other cluster genotypes; as a result, these genotypes might be utilized as parents in the development of salt-tolerant wheat genotypes. The current study concluded that SDW and TDW could be employed as criteria for selecting and defining salt-tolerant genotypes during the early growth stage of wheat., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Statistical analysis is an important part of the research process. Researchers are advised to include a statistician from the moment that the study is being planned. The statistical plan informs the research process, including sample size requirements and the most robust data collection. Once the data are collected, descriptive and inferential statistical analyses are performed. The results of this analysis determine whether the findings are significant, which leads to an interpretation of the findings. The importance of the statistical plan and analysis for the researcher is self-evident. However, it is also important for the reader of published papers to have some knowledge of statistical analysis. This allows critical review of all aspects of the published manuscript. The intent of this paper is to review some basic statistical concepts and thus allow the reader to become a better consumer of the literature., (Copyright © 2024 by Daedalus Enterprises.)

Background: Atypical presentations have been increasingly recognized as a significant contributing factor to diagnostic errors in internal medicine. However, research to address associations between atypical presentations and diagnostic errors has not been evaluated due to the lack of widely applicable definitions and criteria for what is considered an atypical presentation., Objective: The aim of the study is to describe how atypical presentations are defined and measured in studies of diagnostic errors in internal medicine and use this new information to develop new criteria to identify atypical presentations at high risk for diagnostic errors., Methods: This study will follow an established framework for conducting scoping reviews. Inclusion criteria are developed according to the participants, concept, and context framework. This review will consider studies that fulfill all of the following criteria: include adult patients (participants); explore the association between atypical presentations and diagnostic errors using any definition, criteria, or measurement to identify atypical presentations and diagnostic errors (concept); and focus on internal medicine (context). Regarding the type of sources, this scoping review will consider quantitative, qualitative, and mixed methods study designs; systematic reviews; and opinion papers for inclusion. Case reports, case series, and conference abstracts will be excluded. The data will be extracted through MEDLINE, Web of Science, CINAHL, Embase, Cochrane Library, and Google Scholar searches. No limits will be applied to language, and papers indexed from database inception to December 31, 2023, will be included. Two independent reviewers (YH and RK) will conduct study selection and data extraction. The data extracted will include specific details about the patient characteristics (eg, age, sex, and disease), the definitions and measuring methods for atypical presentations and diagnostic errors, clinical settings (eg, department and outpatient or inpatient), type of evidence source, and the association between atypical presentations and diagnostic errors relevant to the review question. The extracted data will be presented in tabular format with descriptive statistics, allowing us to identify the key components or types of atypical presentations and develop new criteria to identify atypical presentations for future studies of diagnostic errors. Developing the new criteria will follow guidance for a basic qualitative content analysis with an inductive approach., Results: As of January 2024, a literature search through multiple databases is ongoing. We will complete this study by December 2024., Conclusions: This scoping review aims to provide rigorous evidence to develop new criteria to identify atypical presentations at high risk for diagnostic errors in internal medicine. Such criteria could facilitate the development of a comprehensive conceptual model to understand the associations between atypical presentations and diagnostic errors in internal medicine., Trial Registration: Open Science Framework; www.osf.io/27d5m., International Registered Report Identifier (irrid): DERR1-10.2196/56933., (©Yukinori Harada, Ren Kawamura, Masashi Yokose, Taro Shimizu, Hardeep Singh. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 25.03.2024.)

Background: Alcohol misuse is the fourth leading cause of death in the United States and a significant problem in the US military. Brief alcohol interventions can reduce negative alcohol outcomes in civilian and military populations, but additional scalable interventions are needed to reduce binge and heavy drinking. SMS text messaging interventions could address this need, but to date, no programs exist for military populations., Objective: We aimed to develop an SMS text messaging intervention to address binge and heavy drinking among Airmen in Technical Training in the US Air Force., Methods: We implemented a 2-phase, mixed methods study to develop the SMS text messaging intervention. In phase 1, a total of 149 respondents provided feedback about the persuasiveness of 49 expert-developed messages, preferences regarding message frequency, timing and days to receive messages, and suggested messages, which were qualitatively coded. In phase 2, a total of 283 respondents provided feedback about the persuasiveness of 77 new messages, including those developed through the refinement of messages from phase 1, which were coded and assessed based on the Behavior Change Technique Taxonomy (BCTT). For both phases, mean persuasiveness scores (range 1-5) were calculated and compared according to age (aged <21 or ≥21 years) and gender. Top-ranking messages from phase 2 were considered for inclusion in the final message library., Results: In phase 1, top-rated message themes were about warnings about adverse outcomes (eg, impaired judgment and financial costs), recommendations to reduce drinking, and invoking values and goals. Through qualitative coding of suggested messages, we identified themes related to warnings about adverse outcomes, recommendations, prioritizing long-term goals, team and belonging, and invoking values and goals. Respondents preferred to receive 1 to 3 messages per week (124/137, 90.5%) and to be sent messages on Friday, Saturday, and Sunday (65/142, 45.8%). In phase 2, mean scores for messages in the final message library ranged from 3.31 (SD 1.29) to 4.21 (SD 0.90). Of the top 5 highest-rated messages, 4 were categorized into 2 behavior change techniques (BCTs): valued self-identity and information about health consequences. The final message library includes 28 BCTT-informed messages across 13 BCTs, with messages having similar scores across genders. More than one-fourth (8/28, 29%) of the final messages were informed by the suggested messages from phase 1. As Airmen aged <21 years face harsher disciplinary action for alcohol consumption, the program is tailored based on the US legal drinking age., Conclusions: This study involved members from the target population throughout 2 formative stages of intervention development to design a BCTT-informed SMS text messaging intervention to reduce binge and heavy drinking, which is now being tested in an efficacy trial. The results will determine the impact of the intervention on binge drinking and alcohol consumption in the US Air Force., (©Chase A Aycock, Indika Mallawaarachchi, Xin-Qun Wang, Daniel G Cassidy, Jordan M Ellis, Robert C Klesges, G Wayne Talcott, Kara Wiseman. Originally published in JMIR Formative Research (https://formative.jmir.org), 19.03.2024.)

Background: Carpal tunnel syndrome (CTS) is the most prevalent upper limb compressive neuropathy. A considerable number of clinical trials and meta-analyses have provided evidence supporting the effectiveness of acupuncture in treating CTS. Nevertheless, the ideal choice of acupoints remains ambiguous., Objective: A data mining analysis was conducted with the objective of determining the most effective acupoint combinations and selection for CTS., Methods: A search was conducted across seven Chinese and English electronic bibliographic databases spanning from their inception to March 2023. Selected were clinical trials that evaluated the efficacy of acupuncture therapy for CTS, with or without randomised controlled methods. Data extraction mainly included acupoint prescriptions. Information such as first author, study design and study setting were also extracted. The principal outcomes comprised the clinical manifestations linked to CTS. Statistical descriptions were generated using Excel 2019. The analysis of association rules was conducted using SPSS Modeler 18.0. Using SPSS Statistics 26.0, exploratory factor analysis and cluster analysis were conducted., Results: 142 trials (including 86 RCTs and 56 non RCTs) were identified, and 193 groups of effective prescriptions involving 68 acupoints were extracted. The most frequently used acupoints were Da-ling (PC7), Nei-guan (PC6), He-gu (LI4), Wai-guan (TE5), and Yang-xi (LI5). The most frequently used meridians were the pericardial meridian and the large intestine meridian. The majority of special acupoints used were Five-shu points and Yuan-source points, with acupoints on the upper limbs being the most frequently used. The core acupoint groups were analyzed and 11 groups of association rules, 8 factors, and 5 effective cluster groups were obtained., Conclusion: The evidence-based acupoint selection and combinations of acupuncture therapy for carpal tunnel syndrome were provided by the findings of this study., Competing Interests: The authors report no conflicts of interest in this work., (© 2024 He et al.)

The alkaline comet assay is frequently used as in vivo follow-up test within different regulatory environments to characterize the DNA-damaging potential of different test items. The corresponding OECD Test guideline 489 highlights the importance of statistical analyses and historical control data (HCD) but does not provide detailed procedures. Therefore, the working group "Statistics" of the German-speaking Society for Environmental Mutation Research (GUM) collected HCD from five laboratories and >200 comet assay studies and performed several statistical analyses. Key results included that (I) observed large inter-laboratory effects argue against the use of absolute quality thresholds, (II) > 50% zero values on a slide are considered problematic, due to their influence on slide or animal summary statistics, (III) the type of summarizing measure for single-cell data (e.g., median, arithmetic and geometric mean) may lead to extreme differences in resulting animal tail intensities and study outcome in the HCD. These summarizing values increase the reliability of analysis results by better meeting statistical model assumptions, but at the cost of information loss. Furthermore, the relation between negative and positive control groups in the data set was always satisfactorily (or sufficiently) based on ratio, difference and quantile analyses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Single-case experimental designs (SCEDs) have grown in popularity in the fields such as education, psychology, medicine, and rehabilitation. Although SCEDs are valid experimental designs for determining evidence-based practices, they encounter some challenges in analyses of data. One of these challenges, missing data, is likely to be occurred frequently in SCEDs research due to repeated measurements over time. Since missing data is a critical factor that can weaken the validity and generalizability of a study, it is important to determine the characteristics of missing data in SCEDs, which are especially conducted with a small number of participants. In this regard, this study aimed to describe missing data features in SCEDs studies in detail. To accomplish this goal, 465 published SCEDs studies within the recent 5 years in six journals were included in the investigation. The overall results showed that the prevalence of missing data among SCEDs articles in at least one phase, as at least one data point, was approximately 30%. In addition, the results indicated that the missing data rates were above 10% within most studies where missing data occurred. Although missing data is so common in SCEDs research, only a handful of studies (5%) have handled missing data; however, their methods are traditional. In analyzing SCEDs data, several methods are proposed considering missing data ratios in the literature. Therefore, missing data rates determined in this study results can shed light on the analyses of SCEDs data with proper methods by improving the validity and generalizability of study results., Competing Interests: Declaration of Conflicting InterestsThe author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Knowledge-intensive service industry has become an important part of social economy, which not only promotes the innovation of modern service industry, but also promotes the upgrading and transformation of manufacturing industry. The agglomeration of knowledge-intensive service industry is not only the inevitable result of economic growth, but also the premise of sustained economic growth. Moreover, China's national economy is transforming from an industrialized economy to a service-oriented and knowledge-based economy, and the importance of knowledge-intensive service industry is increasing day by day. This paper constructs a theoretical framework of the influence of population agglomeration on the economic development of urban agglomerations. The article holds that population agglomeration promotes the economic development of urban agglomerations through the upgrading of industrial structure and the promotion of human capital. In the future, we need to focus on the similarities and differences between population agglomeration and economic development of urban agglomerations in central China, explore the factors of economic development of urban agglomerations, and provide reasonable suggestions for the government to formulate relevant economic policies. This paper, from an innovative research perspective, based on the perspective of population agglomeration, studies the path of its role in regional economic development, which can make up for this defect to some extent. Moreover, the research object has been innovated and the research method has been improved. On the basis of the above, the panel data of the Yangtze River Delta from 2012 to 2021 is selected as the research sample, the location entropy index is taken as the explanatory variable, the regional gross domestic product (GDP) is taken as the explanatory variable, and the rationality of economic theory and the significance of econometric test are considered. Finally, the data are analyzed and tested by regression. The empirical analysis of the Yangtze River Delta urban agglomeration proves the importance of knowledge-intensive service industry agglomeration to regional economic development. Finally, based on the contribution of knowledge-intensive service industry agglomeration to regional economy, the development of knowledge-intensive service industry and the promotion of industrial agglomeration are studied., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author.)

Background: Robust adverse drug event (ADE) reporting systems are crucial to monitor and identify drug safety signals, but the quantity and type of ADEs captured may vary by system characteristics., Objective: We compared ADEs reported in 2 different reporting systems in the same jurisdictions, the Patient Safety and Learning System-Adverse Drug Reaction (PSLS-ADR) and ActionADE, to understand report variation., Methods: This retrospective observational study analyzed reports entered into PSLS-ADR and ActionADE systems between December 1, 2019, and December 31, 2022. We conducted a comprehensive analysis including all events from both reporting systems to examine coverage and usage and understand the types of events captured in both systems. We calculated descriptive statistics for reporting facility type, patient demographics, serious events, and most reported drugs. We conducted a subanalysis focused on adverse drug reactions to enable direct comparisons between systems in terms of the volume and events reported. We stratified results by reporting system., Results: We performed the comprehensive analysis on 3248 ADE reports, of which 12.4% (375/3035) were reported in PSLS-ADR and 87.6% (2660/3035) were reported in ActionADE. Distribution of all events and serious events varied slightly between the 2 systems. Iohexol, gadobutrol, and empagliflozin were the most common culprit drugs (173/375, 46.2%) in PSLS-ADR, while hydrochlorothiazide, apixaban, and ramipril (308/2660, 11.6%) were common in ActionADE. We included 2728 reports in the subanalysis of adverse drug reactions, of which 12.9% (353/2728) were reported in PSLS-ADR and 86.4% (2357/2728) were reported in ActionADE. ActionADE captured 4- to 6-fold more comparable events than PSLS-ADR over this study's period., Conclusions: User-friendly and robust reporting systems are vital for pharmacovigilance and patient safety. This study highlights substantial differences in ADE data that were generated by different reporting systems. Understanding system factors that lead to varying reporting patterns can enhance ADE monitoring and should be taken into account when evaluating drug safety signals., (©Erica Y Lau, Amber Cragg, Serena S Small, Katherine Butcher, Corinne M Hohl. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 18.01.2024.)

The study shows how the statistical approach can provide information on the factors and processes that control the geochemical distribution of elements at the surface of an abandoned tailings pond. In this regard, the case study of a waste deposit resulting from the ore processing plant of Fundu Moldovei was carried out. The facility was concentrating Cu, Pb, and Zn from the polymetallic sulfide ores of the Fundu Moldovei-Leșu Ursului mining district (Romania). The statistics indicate three types of waste, showing specific properties: (i) Waste of the beach, rich in soluble fraction (14.4%) and secondary minerals (e.g., jarosite, ferricopiapite, magnesiocopiapite, pickeringite, and clay minerals). The latter and the related high contents of Al, K, Fe, Co, Ni, Cu, Pb, and Zn are controlled by the water evaporation and subsequent transient pH (2.6-3.5) of the leachates accumulated as puddles. The lower pH and scarce soluble fraction favor a rise in the Cu and Zn contents, while Al, K, Fe, and Co are noticeable at a higher pH when the soluble fraction is abundant. (ii) Waste of the upper dam slope, marked by intense oxidation and a meager occurrence of secondary minerals precipitated from highly acidic pore leachates (average pH of 2.55), namely, jarosite, ferricopiapite, magnesiocopiapite, and coquimbite. The surface waste contains more pyrite and is coarser because of the fine particle removal during rainfall. Unlike the beach waste, in the upper dam tailings, Al, K, Fe, Co, Cu, Pb, and Zn seem to relate mainly to the primary minerals (muscovite, chlorite, and pyrite). (iii) Downslope dam waste is less acidic (average pH of 3.75) than that of the upper slope; it contains secondary minerals stable at a higher pH (e.g., gypsum, apjohnite, dietrichite, clay minerals, and schwertmannite). Calcium, Mn, and Cd are more abundant in the dam waste. They originate from both primary and secondary minerals (e.g., muscovite, chlorite, gypsum, ferricopiapite, and magnesiocopiapite) and correlate with the coarser waste., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Cerebral palsy (CP) is characterized by abnormal pronunciation, posture, and movement. Clinically, CP can be categorized into various motor syndromes, including spastic hemiplegia, diplegia, quadriplegia, involuntary movement, ataxia, and mixed types. Among these, spastic CP represents over 70-80% of all CP cases. The primary objective of our study is to identify the top and core Traditional Chinese Medicine (TCM) symptoms and analysis their association rules in children with spastic cerebral palsy, thereby enhancing the theoretical foundations of TCM treatment on spastic CP., Methods: The study will be conducted on children aged 4 to 14 years with spastic CP who are undergoing treatment at Xi'an Encephalopathy Hospital Affiliated to Shaanxi University of Chinese Medicine. Basic information about the patients and their TCM symptoms will be collected on the first day of admission. This information will include age, gender, birth history, family history, disease classification, and TCM symptoms (including symptoms, tongue, and pulse). Once the data is collected, it will be exported from the electronic medical record system for further analysis. Descriptive statistics will be performed using Excel 2019, while exploratory factor analysis and cluster analysis will be conducted using SPSS Statistics 22. Additionally, association rule analysis will be carried out using SPSS Modeler 18., Results: This study will investigate the most top TCM symptoms in children with spastic CP and explore the association rules between these symptoms, mapping the presentation of spastic CP onto symptoms identified within TCM., Conclusion: Our findings will provide the distinctive characteristics of TCM symptoms in children with spastic CP, furnishing evidence-based support to clinicians and patients in making well-informed decisions collaboratively., Competing Interests: The authors report no conflicts of interest in this work., (© 2023 Wang et al.)

Background: Patients recovering from COVID-19 often experience persistent problems in their daily activities related to limitations in physical, nutritional, cognitive, and mental functioning. To date, it is unknown what treatment is needed to support patients in their recovery from COVID-19., Objective: This study aimed to evaluate the primary allied health care of patients recovering from COVID-19 at 6-month follow-up and to explore which baseline characteristics are associated with changes in the scores of outcomes between baseline and 6-month follow-up., Methods: This Dutch nationwide prospective cohort study evaluated the recovery of patients receiving primary allied health care (ie, dietitians, exercise therapists, occupational therapists, physical therapists, and speech and language therapists) after COVID-19. All treatments offered by primary allied health professionals in daily practice were part of usual care. Patient-reported outcome measures on participation, health-related quality of life, fatigue, physical functioning, and psychological well-being were assessed at baseline and at 3- and 6-month follow-up. Linear mixed model analyses were used to evaluate recovery over time, and uni- and multivariable linear regression analyses were used to examine the association between baseline characteristics and recovery., Results: A total of 1451 adult patients recovering from COVID-19 and receiving treatment from 1 or more primary allied health professionals were included. For participation (Utrecht Scale for Evaluation of Rehabilitation-Participation range 0-100), estimated mean differences of at least 2.3 points were observed at all time points. For the health-related quality of life (EuroQol Visual Analog Scale, range 0-100), the mean increase was 12.3 (95% CI 11.1-13.6) points at 6 months. Significant improvements were found for fatigue (Fatigue Severity Scale, range 1-7): the mean decrease was -0.7 (95% CI -0.8 to -0.6) points at 6 months. However, severe fatigue was reported by 742/929 (79.9%) patients after 6 months. For physical functioning (Patient-Reported Outcomes Measurement Information System-Physical Function Short Form 10b, range 13.8-61.3), the mean increase was 5.9 (95% CI 5.9-6.4) points at 6 months. Mean differences of -0.8 (95% CI -1.0 to -0.5) points for anxiety (Hospital Anxiety and Depression Scale range 0-21) and -1.6 (95% CI -1.8 to -1.3) points for depression were found after 6 months. A worse baseline score, hospital admission, and male sex were associated with greater improvement between baseline and 6-month follow-up, whereas age, the BMI, comorbidities, and smoking status were not associated with mean changes in any outcome measures., Conclusions: Patients recovering from COVID-19 who receive primary allied health care make progress in recovery but still experience many limitations in their daily activities after 6 months. Our findings provide reference values to health care providers and health care policy makers regarding what to expect from the recovery of patients who receive health care from 1 or more primary allied health professionals., Trial Registration: ClinicalTrials.gov NCT04735744; https://tinyurl.com/3vf337pn., International Registered Report Identifier (irrid): RR2-10.2340/jrm.v54.2506., (©Anne I Slotegraaf, Marissa H G Gerards, Arie C Verburg, Marian A E de van der Schueren, Hinke M Kruizenga, Maud J L Graff, Edith H C Cup, Johanna G Kalf, Antoine F Lenssen, Willemijn M Meijer, Renée A Kool, Rob A de Bie, Philip J van der Wees, Thomas J Hoogeboom, Dutch Consortium Allied Healthcare COVID-19. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.10.2023.)

In this study, due to multiple cases of dengue fever in two locations in Haikou, Hainan, several factors affecting the transmission of dengue fever in Haikou in 2019 were analyzed. It was found that dengue fever spread from two sites: a construction site, which was an epidemic site in Haikou, and the university, where only four confirmed cases were reported. Comparative analysis revealed that the important factors affecting the spread of dengue fever in Haikou were environmental hygiene status, knowledge popularization of dengue fever, educational background, medical insurance coverage and free treatment policy knowledge and active response by the government.

Background: Carpal tunnel syndrome (CTS), as the most common compression neuropathy in the upper limb, can lead to upper limb dysfunction in patients. The effectiveness of acupuncture in treating CTS has been validated based on numerous clinical trials and meta-analyses, but questions remain, such as how to select the best acupoints. Our purpose is to conduct the first data mining analysis to identify the most effective acupoint selection and combinations for treating CTS., Methods: We will search 7 electronic bibliographic databases (PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database and Chongqing VIP Database) from inception to March 2023. Clinical trials assessing the effectiveness of acupuncture therapy on the management of CTS will be selected. Reviews, protocols, animal trials, case reports, systematic reviews, and meta-analyses will be excluded. The primary outcome measure will be clinical result associated with CTS. Descriptive statistics will be performed in Excel 2019. Association rule analysis will be performed in SPSS Modeler 18.0. Exploratory factor analysis and cluster analysis will be performed in SPSS Statistics 26.0., Results: This study will investigate the most effective acupoint selection and combinations for patients with CTS., Conclusion: Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with CTS, helping clinicians and patients make a more informed decision together., Competing Interests: The authors report no conflicts of interest in this work., (© 2023 He et al.)

Background: Peyronie's disease has an impact on men's mental and physical health., Aim: We sought to translate the Peyronie's Disease Questionnaire into Danish, adapt it to the Danish cultural setting, and test it in a Danish population., Methods: Translation of the Peyronie's Disease Questionnaire was performed according to the guidelines for adapting health status measures for use in languages other than the source language by Beaton et al. The validated American Peyronie's Disease Questionnaire was developed to monitor patient symptoms after an intervention and to inspire a subsequent dialogue about physical and psychological symptoms with a healthcare provider, thereby allowing the patient and the healthcare professional to choose the best treatment. The expert committee agreed on a Danish version after cross-cultural adaptation. The Danish Peyronie's Disease Questionnaire was sent by electronic mail to a preselected group of 41 men with Peyronie's disease., Outcomes: After completing the questionnaire, 32 men participated in a video interview regarding the questionnaire and were asked to identify any problematic fields or areas open to misunderstanding., Results: The Peyronie's Disease Questionnaire underwent major modifications in light of the comments of the first 10 respondents. Thereafter, only minor changes were made until data saturation was reached after 27 of the 32 respondents had been interviewed. In 87% of respondents Peyronie's disease bothered from the last time they had intercourse, and 93% of the men experienced being bothered by having intercourse less often. Peyronie's disease made 73% of respondents feel bodily discomfort, and 88% had intercourse less often than they used to have due to Peyronie's disease., Clinical Implications: The Peyronie's Disease Questionnaire is a valuable tool in the crucial task of addressing Peyronie's disease, providing insight into the mental and sexual health problems as well as physical challenges faced by patients., Strengths and Limitations: The interviewer's modest experience in conducting interviews is believed to have been duly compensated for by continuous and accumulating learning-while-doing process because the same interviewer conducted all of the interviews and did so consecutively., Conclusions: Danish men expressed satisfaction with the questionnaire and found it valuable as a tool when visiting the doctor for the first time., (© The Author(s) 2023. Published by Oxford University Press on behalf of The International Society of Sexual Medicine.)

Rate distortion theory was developed for optimizing lossy compression of data, but it also has applications in statistics. In this paper, we illustrate how rate distortion theory can be used to analyze various datasets. The analysis involves testing, identification of outliers, choice of compression rate, calculation of optimal reconstruction points, and assigning "descriptive confidence regions" to the reconstruction points. We study four models or datasets of increasing complexity: clustering, Gaussian models, linear regression, and a dataset describing orientations of early Islamic mosques. These examples illustrate how rate distortion analysis may serve as a common framework for handling different statistical problems.

Background: Older adults have worse outcomes following hospitalization with COVID-19, but within this group there is substantial variation. Although frailty and comorbidity are key determinants of mortality, it is less clear which specific manifestations of frailty and comorbidity are associated with the worst outcomes., Objective: We aimed to identify the key comorbidities and domains of frailty that were associated with in-hospital mortality in older patients with COVID-19 using models developed for machine learning algorithms., Methods: This was a retrospective study that used the Hospital Episode Statistics administrative data set from March 1, 2020, to February 28, 2021, for hospitalized patients in England aged 65 years or older. The data set was split into separate training (70%), test (15%), and validation (15%) data sets during model development. Global frailty was assessed using the Hospital Frailty Risk Score (HFRS) and specific domains of frailty were identified using the Global Frailty Scale (GFS). Comorbidity was assessed using the Charlson Comorbidity Index (CCI). Additional features employed in the random forest algorithms included age, sex, deprivation, ethnicity, discharge month and year, geographical region, hospital trust, disease severity, and International Statistical Classification of Disease, 10th Edition codes recorded during the admission. Features were selected, preprocessed, and input into a series of random forest classification algorithms developed to identify factors strongly associated with in-hospital mortality. Two models were developed; the first model included the demographic, hospital-related, and disease-related items described above, as well as individual GFS domains and CCI items. The second model was similar to the first but replaced the GFS domains and CCI items with the HFRS as a global measure of frailty. Model performance was assessed using the area under the receiver operating characteristic (AUROC) curve and measures of model accuracy., Results: In total, 215,831 patients were included. The model using the individual GFS domains and CCI items had an AUROC curve for in-hospital mortality of 90% and a predictive accuracy of 83%. The model using the HFRS had similar performance (AUROC curve 90%, predictive accuracy 82%). The most important frailty items in the GFS were dementia/delirium, falls/fractures, and pressure ulcers/weight loss. The most important comorbidity items in the CCI were cancer, heart failure, and renal disease., Conclusions: The physical manifestations of frailty and comorbidity, particularly a history of cognitive impairment and falls, may be useful in identification of patients who need additional support during hospitalization with COVID-19., (©Johannes Heyl, Flavien Hardy, Katie Tucker, Adrian Hopper, Maria J M Marchã, Annakan V Navaratnam, Tim W R Briggs, Jeremy Yates, Jamie Day, Andrew Wheeler, Sue Eve-Jones, William K Gray. Originally published in the Interactive Journal of Medical Research (https://www.i-jmr.org/), 12.12.2022.)

Objectives: Falls in elderly patients treated in general hospitals have already been the focus of several studies. Research within psychiatric settings, however, remains limited, despite the fact that this population has a number of characteristics that could increase the fall risk. The aim of this retrospective study was to estimate the prevalence of falling in patients with a psychiatric hospital setting., Methods: A retrospective descriptive chart review of falls registered in the period July 1, 2013 until June 30, 2019 in a Belgian University Psychiatric Hospital was conducted. Data were collected from the "patient related incident report and management system" (PiMS) of the hospital. All registered falls of all hospitalized patients were included in the study., Results: During the 6-year study period an incidence of 4.4 falls per 1,000 patient days was found. Only 0.5% of the falls resulted in severe injury and none of these falls were fatal. Eighty percent of falls involved a patient over the age of 65. Only 25.0% of the elderly patients suffered physical consequences, while injuries were present in 31.4% of adults and 68.2% of young patients. The two most common causes of a fall were the health status (63.3%) and the behavior (55.1%) of the patient., Conclusion: The estimated prevalence of falls in our study was generally in line with the rates found in literature on falls in psychiatric settings. Falls in psychiatric settings occur both in younger and older patients, suggesting that all age categories deserve sufficient attention in fall prevention policies. However, more research is necessary to improve fall prevention policies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 de Smet, Carpels, Creten, De Pauw, Van Eldere, Desplenter and De Hert.)

Background: There is no current research to explain the trends in vasectomy and vasectomy reversals in the United Kingdom, leaving little understanding of the social phenomena involved., Objective: This study aimed to provide an overview of vasectomy as a main method (or primary method) of contraception and vasectomy reversals among men in the United Kingdom aged >16 years., Study Design: Descriptive statistics were generated from the National Health Service's publicly accessible datasets from 2004/2005 to 2019/2020, including data from 1,621,105 men., Results: Although men are increasing their use of contraceptive services, the number of men having vasectomies and vasectomy reversals has decreased significantly., Conclusion: The researchers propose that more rigorous techniques for capturing data are required to understand vasectomy in the United Kingdom. There is also an urgent need for research on vasectomy in the United Kingdom and globally, not only to explain the behavioral trends found in this study, but also to explain the global trend., (© 2022 The Authors.)

Background: Agile projects are statistically more likely to succeed then waterfall projects. The overall aim of this study was to explore the nursing staffs' experiences with an agile development process, from its initial requirements to the deployment of its outcome of ICT solutions aimed at supporting discharge planning., Methods: An explorative design with quantitative and qualitative methods was used. Qualitative data was collected through seven focus group interviews. Quantitative data was collected via an ICT-system, and with an evaluation form submitted by fourteen registered nurses and nine district nurses., Results: Qualitative result of the experiences with the agile development process and its outcome resulted in one theme, four categories, and ten subcategories. The theme was found to be about time and timing, namely the amount of time for the different activities and the timing of activities within and between organisations. The agile development process increased the participants' readiness for change by offering time to learn, practice, engage and reflect, and then adopt the ICT as a support to daily practice. Quantitative results showed a variated adoption of the ICT., Conclusion: There is a need for time to prepare, understand and adopt new tools, services and procedures and a need for additional time to prepare, understand and adopt the new among individuals, collectives, organizations, and sometimes even between different collectives or organizations. The agile development process offered the end-users involvement through the development process, which gave them time to change it both individually and collectively. However, there is a need for close collaboration between the development project team and management to reach an organizational change that is timely for both the individual and the collective change. When time or timing fails in the development or implementation process, there is a huge risk of non-adoption of new tools, services, or procedures or among the end-users., (© 2022. The Author(s).)

Background: Although the private household setting is considered a major driver of viral spread, only little is known about the contextual details of SARS-CoV-2 household transmission, thus hampering political decision-making., Materials and Methods: We analyzed individual case and cluster data from statutory notifications from August to November 2020 in Rhineland-Palatinate - the period preceding the second SARS-CoV-2 wave. We also conducted an into-depth survey on contextual details of household transmission in a representative sample of 149 private household clusters that had occurred during this period., Results: During the study period, 18,695 PCR-confirmed SARS-CoV-2 cases were notified, 3,642 of which occurred in 911 clusters (private households (67.3%), the workplace (7.8%), elderly homes (1.8%), others (23.2%). Demographically, clustered cases were representative of all notified cases. Two-thirds (77/113, 68%) of sample response clusters involved more than one private household. These caused on average more close contact persons (mean 13.5, ±SD 15.8) and secondary cases (3.9, ±SD 0.4) than clusters involving one household only (5.1 ± 13.8 and 2.9 ± 0.2). About one in six multi-household clusters in the private setting (13/77) followed a social gathering (e.g. birthday party). Breaches of one or more of the three major barrier concepts (mask, ventilation, and distance) were identified in most (10/13) of these social gatherings. SARS-CoV-2 clusters following social gatherings were overrepresented during the second half of the study period., Conclusion: In times of increasing infectious pressure in a given population, multi-household social gatherings appear to be an important target for reducing SARS-CoV-2 transmission., (Copyright © 2022 The British Infection Association. Published by Elsevier Ltd. All rights reserved.)

Irregular self-selection is a demonstration of active involvement in interaction. English as a foreign language (EFL) learners' talk-in-interaction is one of such cases. Yet, little research has explored when, how, and why learners implement this action. The aim of this article is to address these issues in Chinese postgraduate EFL learners' conversations from the perspective of multimodal interaction. To this end, we provide descriptive statistics and use multimodal conversation analysis to investigate the detailed process of irregular self-selection. The results show the interactional sensitivity of learners, and all the successful irregular self-selection can be divided into the following three types: turn interruption (TI), turn competition TC), and turn holding abortion (THA). Learners implement this action by using multimodal resources, including lexis, syntax, pitch reset, intensity enhancement, gaze, and so forth. However, their body movements lack diversity, causing behaviors to be constrained and inactive. The main purpose of irregular self-selection is to provide knowledge that contributes to topical development. This study reveals that Chinese postgraduate EFL learners are interactionally competent members. They are able to achieve communicative goals but in a low diversity of body movements. The findings help to understand the detailed process of speakership claiming in EFL learners' conversations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ji and Zhang.)

Background: The malaria risk analysis of multiple populations is crucial and of great importance whilst compressing limitations. However, the exponential growth in diversity and accumulation of genetic variation data obtained from malaria-infected patients through Genome-Wide Association Studies opens up unprecedented opportunities to explore the significant differences between genetic markers (risk factors), particularly in the resistance or susceptibility of populations to malaria risk. Thus, this study proposes using statistical tests to analyse large-scale genetic variation data, comprising 20,854 samples from 11 populations within three continents: Africa, Oceania, and Asia., Methods: Even though statistical tests have been utilized to conduct case-control studies since the 1950s to link risk factors to a particular disease, several challenges faced, including the choice of data (ordinal vs. non-ordinal) and test (parametric vs. non-parametric). This study overcomes these challenges by adopting the Mann-Whitney U test to analyse large-scale genetic variation data; to explore the statistical significance of markers between populations; and to further identify the highly differentiated markers., Results: The findings of this study revealed a significant difference in the genetic markers between populations (p < 0.01) in all the case groups and most control groups. However, for the highly differentiated genetic markers, a significant difference (p < 0.01) was present for most genetic markers with varying p-values between the populations in the case and control groups. Moreover, several genetic markers were observed to have very significant differences (p < 0.001) across all populations, while others exist between certain specific populations. Also, several genetic markers have no significant differences between populations., Conclusions: These findings further support that the genetic markers contribute differently between populations towards malaria resistance or susceptibility, thus showing differences in the likelihood of malaria infection. In addition, this study demonstrated the robustness of the Mann-Whitney U test in analysing genetic markers in large-scale genetic variation data, thereby indicating an alternative method to explore genetic markers in other complex diseases. The findings hold great promise for genetic markers analysis, and the pipeline emphasized in this study can fully be reproduced to analyse new data., (© 2022. The Author(s).)

The COVID-19 pandemic has severely affected healthcare delivery across the world. However, little is known about COVID-19's impact on home healthcare (HHC) services. Our study aimed to: (1) describe the changes in volume and intensity of HHC services and the crisis management policies implemented; (2) understand the responses and the experiences of HHC staff and clients. We conducted an explanatory sequential mixed methods study. First, retrospective client data (N = 43,495) from four Dutch HHC organizations was analyzed. Second, four focus group interviews were conducted for the strategic, tactical, operational, and client levels of the four HHC organizations. Our results showed that both the supply of and demand for Dutch HHC decreased considerably, especially during the first wave (March-June 2020). This was due to factors such as fear of infection, anticipation of a high demand for COVID-19-related care from the hospital sector, and lack of personal protective equipment. The top-down management style initially applied made way for a more bottom-up approach in the second wave (July 2020-January 2021). Experiences vary between levels and waves. HHC organizations need more responsive protocols to prevent such radical scaling-back of HHC in future crises, and interventions to help HHC professionals cope with crisis situations.

Genome-wide association studies (GWAS) have benefited from the advances of sequencing methods for the generation of high-density genomic data. By bridging genotype to phenotype, several genes have been associated with traits of agricultural interest. Despite this, there is still a gap between genotyping and phenotyping due to the large difference in throughput between the two disciplines. Although cutting-edge phenomics technologies are available to the community, their costs are still prohibitive at the small lab level. Semiautomated methods of investigation provide a valid alternative to generate large-scale phenotyping data able to deeply investigate the characteristics of different plant organs. Beyond automation, phenomics data management is another major constraint to consider; while bioinformatics pipelines are well-trained for releasing high-quality genomic data, fewer efforts have been done for phenotyping information. This chapter provides a guide for generating large-scale data related to the size and shape of fruits, leaves, seeds, and roots and for downstream analysis for curation and preparation of clean datasets, through removal of outliers and performing primary statistical analysis. Different steps to be carried out in the R environment will be shown for gathering the appropriate input information to use in GWAS avoiding any possible bias., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Genome-wide association studies (GWAS) are a powerful approach to dissect genotype-phenotype associations and identify causative regions. However, this power is highly influenced by the accuracy of the phenotypic data. To obtain accurate phenotypic values, the phenotyping should be achieved through multienvironment trials (METs). In order to avoid any technical errors, the required time needs to be spent on exploring, understanding, curating and adjusting the phenotypic data in each trial before combining them using an appropriate linear mixed model (LMM). The LMM is chosen to minimize as much as possible any effect that can lead to misestimation of the phenotypic values. The purpose of this chapter is to explain a series of important steps to explore and analyze data from METs used to characterize an association panel. Two datasets are used to illustrate two different scenarios., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In this study, descriptive statistics, correlation matrix, multiple regression model, and geostatistical models were used to assess the contamination of groundwater with respect to trace elements in the Lower Tano river basin, Ghana, West Africa. A total number of 48 boreholes drilled across the basin with depths ranging from 18 to 60 m were used as data sources in this study. The results of the descriptive statistics showed that the average lead, iron, and aluminium concentrations exceeded the WHO permissible limits of 0.3 mg/L, 0.01 mg/L, and 0.2 mg/L respectively. Furthermore, copper, chromium, aluminium, zinc, manganese, nickel, iron, arsenic, electrical conductivity, and total dissolved solids were found to be extreme and highly positively skewed. Even though significant correlations exist among some variables, the statistical results showed that the quality of the boreholes drilled across the basin was mainly originating from geogenic and anthropogenic sources. In addition, each pair of correlated physical parameters and trace elements in the drilled boreholes were predicted using multiple regression models. Likewise, geostatistical modelling was used to assess the spatial analysis of each pair of correlated physical parameters and trace elements in the drilled boreholes. The cross-validation results revealed kriging model, as the most precise model for the spatial distribution maps for the correlated physical parameters, and correlated trace elements concentration in the boreholes drilled across the study region. The semivariogram models showed that most of the correlated physical parameters and correlated trace elements were weak moderately and strongly spatially dependent, suggesting fewer agronomic influences. The results of the spatial analysis were consistent with the multiple regression model and the Pearson correlation matrix., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The appropriate acquisition and processing of water quality data are crucial for water resource management. As such, published articles on water quality monitoring and assessment are meant to convey essential and reliable information to water quality experts, decision-makers, researchers, students, and the public. The implication is that such information must emanate from data obtained and analysed in an up-to-date, scientifically sound manner. Thus, inappropriate data analysis and reporting techniques could yield misleading results and mar the endeavours of achieving error-free conclusions. This study utilises the findings on water quality assessment in Nigeria over the last 20 years to reveal the likely trends in water quality research regarding data collection, data analysis, and reporting for physicochemical, bacteriological parameters, and trace organics. A total of 123 Web of Science and quartile ranked (Q1-Q4) published articles involving water quality assessment in Nigeria were analysed. Results indicated shortcomings in various aspects of data analysis and reporting. Consequently, we use simulated heatmaps and graphs to illustrate preferred ways of analysing, reporting, and visualising some regularly used descriptive and inferential statistics of water quality variables. Finally, we highlight alternative approaches to the customarily applied water quality assessment methods in Nigeria and emphasise other areas of deficiency that need attention for improved water quality research., Competing Interests: The authors declare no conflict of interest., (© 2021 The Author(s).)

Pollution control is based on an exhaustive knowledge of concentration distributions. This study analyses a detailed database of NO 2 , O 3 , PM 10 and PM 2.5 in England and Wales over the period 2007-2011. Daily and annual means were considered in a 1-km spatial resolution. Histograms revealed a shape like a sawtooth. The interval was wide for NO 2 and O 3 , although with a gap, whilst the particulate matter range was narrow. Spring provided the peak for the O 3 annual cycle, whereas minima for the other pollutants were reached in summer. A trend for the annual medians of particulate matter was observed, with a minimum in the period analysed. However, the pattern was uniform for NO 2 and O 3 . Cities appeared as NO 2 hot spots and O 3 cold spots. Wales stood out as an NO 2 clean country, although with high O 3 levels. Sources or sinks of particulate matter were not observed, suggesting that more detailed analysis is required. Two NO 2 pollution axes were sometimes seen, one in the south from London to Bristol, and the second in the north, from Liverpool to Kingston Upon Hull. No annual spatial pattern was seen for the remaining pollutants beyond the contrast between cities and country sites for O 3 . Consequently, spatial analysis allows the real impact of pollutant sources be known, although it must be performed with a detailed temporal resolution in order to investigate the extension, quantity, and length of the concentrations calculated., Competing Interests: Declaration of competing interest The authors declare there is no conflict of interest regarding the publication of this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Stress is the most important proximal precipitant of depression, yet most large genome-wide association studies (GWAS) do not include stress as a variable. Here, we review how gene × environment (G × E) interaction might impede the discovery of genetic factors, discuss two examples of G × E interaction in depression and addiction, studies incorporating high-stress environments, as well as upcoming waves of genome-wide environment interaction studies (GWEIS). We discuss recent studies which have shown that genetic distributions can be affected by social factors such as migrations and socioeconomic background. These distinctions are not just academic but have practical consequences. Owing to interaction with the environment, genetic predispositions to depression should not be viewed as unmodifiable destiny. Patients may genetically differ not just in their response to drugs, as in the now well-recognised field of pharmacogenetics, but also in how they react to stressful environments and how they are affected by behavioural therapies.

This article presents the descriptive statistics of service life data of building elements, gathered through an international, European and Swiss literature review of LCA, LCC and other sources called "Real-Estate Management sources" that include building owners, banks, insurances, associations of tenants and owners, etc. Furthermore, the properties of the fitted lognormal distribution are given. The data are structured, using a hybrid decomposition (functional decomposition, according to the eBKP-H - SN506511 and material decomposition, as well). These data and the derived statistical distributions were used in a research study, in order to quantify the uncertainty and sensitivity of the LCA and LCC output, due to the variability of the building elements' service lives., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Ergene River is heavily utilized for irrigation of fields to grow the main stocks of rice, wheat, and sunflower of Turkey also exported to Europe; therefore, monitoring the river's water quality is crucial for public health. Although the river quality is routinely monitored, the evaluation of pollution based on micropollutants is limited. In this study, we measured 222 organic micropollutants in 300 samples collected from 75 different locations on the Ergene River between August 2017 and May 2018 using direct injection liquid chromatography-tandem spectrometry with optimized scheduled multiple reaction monitoring. In total, 165 micropollutants were detected at a range of concentrations between 1.90 ng/L and 1824.55 μg/L. Sixty-three chemical substances were recurrent micropollutants that were detected at least one location in all seasons. Among them, 41 chemical substances were identified as the core micropollutants of the Ergene River using data-driven clustering methods. Hexa(methoxymethyl)melamine, benzotriazoles, and benzalkonium chlorides were frequently detected core micropollutants with an industrial origin. Besides, diuron, carbendazim, and cadusafos were common pesticides in the river. Core micropollutants were further categorized based on their type of source and environmental behavior using Kurtosis of concentration and load data obtained for each micropollutant. As a result, the majority of the core micropollutants are recalcitrant chemicals either released from a specific source located upstream of the river or have urban and agricultural sources dispersed on the watershed. In this study, we assessed the current state of pollution in the Ergene River at the micropollutant level with a very high spatial resolution and developed a statistical approach to categorize micropollutants that can be used to monitor the extent of pollution and track pollution sources in the river., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This reflection presents a discussion of some common measures of variability and how they are appropriately used in descriptive and inferential statistical analyses. We argue that confidence intervals (CIs), which incorporate these measures, serve as tools to assess both clinical and statistical significance.

Estimation of hazardous air pollutants in the urban environment for maintaining public safety is a significant concern to mankind. In this paper, we have developed an efficient air quality warning system based on a low-cost and robust ground-level ozone soft sensor. The soft sensor was developed based on a novel technique of damped least squares neural network (DLSNN) with greedy backward elimination (GBE) for the estimation of hazardous ground-level ozone. Only three meteorological factors were used as input variables in the estimation of ground-level ozone and we have used weighted k-nearest neighbors (WkNN) classifier with fast response for development of air quality warning system. We have chosen the urban areas of Taiwan for this study and have analyzed seasonal variations in the ground-level ozone concentration of various cities in Taiwan as part of this work. Moreover, descriptive statistics and linear dependence of ozone concentration based on Spearman correlation coefficient, Kendall's tau coefficient, and Pearson coefficient are calculated. The proposed DLSNN/GBE method exhibited excellent performance resulting in very low mean square error (MSE), mean absolute error (MAE), and high coefficient of determination (R 2 ) compared to other traditional approaches in ozone concentration estimation. We have achieved a good fit in the determination of ozone concentration from meteorological features of atmosphere. Moreover, the excellent performance of proposed urban air quality warning system was evident from the good F1-score value of 0.952 achieved by the WkNN classifier., (Copyright © 2020 Elsevier Inc. All rights reserved.)

We discuss the validation of machine learning models, which is standard practice in determining model efficacy and generalizability. We argue that internal validation approaches, such as cross-validation and bootstrap, cannot guarantee the quality of a machine learning model due to potentially biased training data and the complexity of the validation procedure itself. For better evaluating the generalization ability of a learned model, we suggest leveraging on external data sources from elsewhere as validation datasets, namely external validation. Due to the lack of research attractions on external validation, especially a well-structured and comprehensive study, we discuss the necessity for external validation and propose two extensions of the external validation approach that may help reveal the true domain-relevant model from a candidate set. Moreover, we also suggest a procedure to check whether a set of validation datasets is valid and introduce statistical reference points for detecting external data problems., (© 2020 The Authors.)

Competing Interests: Declaration of competing interest All authors have no disclosures.

Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely studied during the patient's workup. Experimentally, bead bound antigen- antibody reactions are detected using a special multicolor flow cytometer (Luminex). Routinely for each sample, antibody responses against 96 different HLA antigen groups are measured simultaneously and a 96-dimensional immune response vector is created. Under a common experimental protocol, using unsupervised clustering algorithms, we analyzed these immune intensity vectors of anti HLA class II responses from a dataset of 1,748 patients before or after renal transplantation residing in a single country. Each patient contributes only one serum sample in the analysis. A population view of linear correlations of hierarchically ordered fluorescence intensities reveals patterns in human immune responses with striking similarities with the previously described CREGs but also brings new information on the antigenic properties of class II HLA molecules. The same analysis affirms that "public" anti-DP antigenic responses are not correlated to anti DR and anti DQ responses which tend to cluster together. Principal Component Analysis (PCA) projections also demonstrate ordering patterns clearly differentiating anti DP responses from anti DR and DQ on several orthogonal planes. We conclude that a computer vision of human alloresponse by use of several dimensionality reduction algorithms rediscovers proven patterns of immune reactivity without any a priori assumption and might prove helpful for a more accurate definition of public immunogenic antigenic structures of HLA molecules. Furthermore, the use of Eigen decomposition on the Immune Response generates new hypotheses that may guide the design of more effective patient monitoring tests., (Copyright © 2020 Vittoraki, Fylaktou, Tarassi, Tsinaris, Petasis, Gerogiannis, Kheav, Carmagnat, Lehmann, Doxiadis, Iniotaki and Theodorou.)

Moisture is one of the major causes of problems in buildings, and it can compromise their performance. Infrared thermography (IRT) is a non-destructive testing technology that can be used to assess the humidification phenomenon and, thus, prevent some of the problems caused by moisture. The images obtained by IRT reflect the thermal patterns of the surface under study and can be evaluated using a quantitative approach, which allows not only the traditional visualization of the thermal patterns but also quantification of surface temperatures and/or their differences. The relevance of this work is related to the discussion of the strengths and weaknesses of several methods to quantitatively assess the humidification phenomenon using IRT. For that purpose, the partial humidification by the bottom surface of a lightweight concrete specimen was considered as a case study. To evaluate the thermal gradients, the evolution of the thermal imaging throughout the measurement period and the definition of the areas particularly affected by moisture, a methodology that included a pre-processing phase for data reduction, followed by a data processing phase, were implemented. In the data processing, different statistical and numerical methods were tested. The results of the statistical descriptive analysis highlighted the time variation of the surface temperature, both when considering the entire specimen and when considering only specific areas. The variability of the temperatures at certain moments of the experiment could be observed in the box-plot representation. The image subtraction proved to be an interesting technique to quantify the temperature differences if the first image was used as reference. A thermal index, TI, was proposed to assess the cooling rate. The index highlighted the initial instant when the effect of moisture on the surface temperature was detectable.

Three-dimensional structure of a protein chain is determined by its amino acid interactions. One approach to the analysis of amino acid interactions refers to geometric distances of amino acid pairs in polypeptide chains. For a detailed analysis of the amino acid distances, the database with three types of amino acid distances in a set of chains was created. Web application Distances of Amino Acids has also been developed to enable scientists to explore interactions of amino acids with different properties based on distances stored in the database. Web application calculates and displays descriptive statistics and graphs of amino acid pair distances with selected properties, such as geometric distance threshold, corresponding SCOP class of proteins and secondary structure types. In addition to the analysis of pre-calculated distances stored in the database, the amino acid distances of a single protein with the specified PDB identifier can also be analyzed. The web application is available at http://andromeda.matf.bg.ac.rs/aadis&#95;dynamic/., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objective: Epidemiologic and clinical research papers often describe the study sample in the first table. If well-executed, this "Table 1" can illuminate potential threats to internal and external validity. However, little guidance exists on best practices for designing a Table 1, especially for complex study designs and analyses. We aimed to summarize and extend the literature related to reporting descriptive statistics., Study Design and Setting: In consultation with existing guidelines, we synthesized and developed reporting recommendations driven by study design and focused on transparency related to potential threats to internal and external validity., Results: We describe a basic structure for Table 1 and discuss simple modifications in terms of columns, rows, and cells to enhance a reader's ability to judge both internal and external validity. We further highlight several analytic complexities common in epidemiologic research (missing data, sample weights, clustered data, and interaction) and describe possible variations to Table 1 to maintain and add clarity about study validity in light of these issues. We discuss considerations and tradeoffs in Table 1 related to breadth and comprehensiveness vs. parsimony and reader-friendliness., Conclusion: We anticipate that our work will guide authors considering layouts for Table 1, with attention to the reader's perspective., (Copyright © 2019 Elsevier Inc. All rights reserved.)

In this paper, we propose a regression depth versus regression depth plot, hereafter RR -plot, for regression observations based on the halfspace regression depth. Areas of application of this tool include: the visualization of hypothesis tests about regression coefficients, and of the comparison between regression observations from different models, etc. Some characterization theorems are also provided to address the rationale of this RR -plot., Competing Interests: No potential conflict of interest was reported by the authors., (© 2019 Informa UK Limited, trading as Taylor & Francis Group.)

Descriptive statistics are an important part of biomedical research which is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Measures of the central tendency and dispersion are used to describe the quantitative data. For the continuous data, test of the normality is an important step for deciding the measures of central tendency and statistical methods for data analysis. When our data follow normal distribution, parametric tests otherwise nonparametric methods are used to compare the groups. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages. In the present study, we have discussed the summary measures and methods used to test the normality of the data., Competing Interests: None

This short "snippet" covers three important aspects related to statistics - the concept of variables , the importance, and practical aspects related to descriptive statistics and issues related to sampling - types of sampling and sample size estimation., Competing Interests: There are no conflicts of interest.

Statistics plays an essential role in clinical research by providing a framework for making inferences about a population of interest. In order to interpret research datasets, clinicians involved in clinical research should have an understanding of statistical methodology. This article provides a brief overview of statistical methods that are frequently used in clinical research studies. Descriptive and inferential methods, including regression modeling and propensity scores, are discussed, with focus on the rationale, assumptions, strengths, and limitations to their application., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The purpose of this study was to clarify the sleep disorders and sleep conditions among workers in a company through descriptive statistics. We analyzed the data of individuals with suspected sleep disorders based on the 1-year outpatient health insurance claim data of 2803 employees in a company in Japan. We conducted a questionnaire survey to determine the sleep condition and drug usage of the same participants. Claim data of 339 employees (12.1%) were selected for analysis, and the breakdown of diseases comprised 153 (5.5%) with sleep disorders, 149 (5.3%) with headache, 119 (4.2%) with depression and 17 (0.6%) with autonomic imbalance. We recovered 2608 questionnaire responses (93.0%) and found that 1852 subjects (71.0%) were aware of insomnia symptoms within 1 year. Our findings highlight the prevalence of sleep disorders and drug usage among workers in a company, and the conditions of these disorders, including awareness of insomnia.

The data presents the self-esteem examination of undergraduate students studying in Zabol University of Medical Sciences, Iran in 2017 and its relationship with gender. The total number of participants was 100 (49% female and 51% male). The 100 students were selected through random sampling method. The average age of participants was 21.61 years while the youngest and the oldest participants were 19 and 32 years old, respectively. The data were collected using the Coopersmith Self-Esteem Inventory (CSEI) and analyzed by descriptive statistics (frequency, mean, standard deviation, minimum and maximum) using SPSS version 22 (statistical package for Social Sciences). The detailed dataset is presented in this paper.