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.

UNASSIGNED: 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.
UNASSIGNED: To meet the objectives of this study, 100 wheat genotypes were tested hydroponically in 0 (control) and 15 dS m-1 salt solutions.
UNASSIGNED: 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 (h2b) 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. D2 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.

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.

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.
BACKGROUND: Open Science Framework; www.osf.io/27d5m.
UNASSIGNED: DERR1-10.2196/56933.

UNASSIGNED: 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.
UNASSIGNED: A data mining analysis was conducted with the objective of determining the most effective acupoint combinations and selection for CTS.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: The evidence-based acupoint selection and combinations of acupuncture therapy for carpal tunnel syndrome were provided by the findings of this study.

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.

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.

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.

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.

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.