The human gut microbiota refers to a diverse community of microorganisms that symbiotically exist in the human intestinal system. Altered microbial communities have been linked to many human pathologies. However, there is a lack of rapid and efficient methods to assess gut microbiota signatures in practice. To address this, we established an appraisal system containing 45 quantitative real-time polymerase chain reaction (qPCR) assays targeting gut core microbes with high prevalence and/or abundance in the population. Through comparative genomic analysis, we selected novel species-specific genetic markers and primers for 31 of the 45 core microbes with no previously reported specific primers or whose primers needed improvement in specificity. We comprehensively evaluated the performance of the qPCR assays and demonstrated that they showed good sensitivity, selectivity, and quantitative linearity for each target. The limit of detection ranged from 0.1 to 1.0 pg/µL for the genomic DNA of these targets. We also demonstrated the high consistency (Pearson\'s r = 0.8688, P < 0.0001) between the qPCR method and metagenomics next-generation sequencing (mNGS) method in analyzing the abundance of selected bacteria in 22 human fecal samples. Moreover, we quantified the dynamic changes (over 8 weeks) of these core microbes in 14 individuals using qPCR, and considerable stability was demonstrated in most participants, albeit with significant individual differences. Overall, this study enables the simple and rapid quantification of 45 core microbes in the human gut, providing a promising tool to understand the role of gut core microbiota in human health and disease. KEY POINTS: • A panel of original qPCR assays was developed to quantify human gut core microbes. • The qPCR assays were evaluated and compared with mNGS using real fecal samples. • This method was used to dynamically profile the gut core microbiota in individuals.

Intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA) is an innovative approach for investigating inequalities, including intersectional inequalities in health, disease, psychosocial, socioeconomic, and other outcomes. I-MAIHDA and related MAIHDA approaches have conceptual and methodological advantages over conventional single-level regression analysis. By enabling the study of inequalities produced by numerous interlocking systems of marginalization and oppression, and by addressing many of the limitations of studying interactions in conventional analyses, intersectional MAIHDA provides a valuable analytical tool in social epidemiology, health psychology, precision medicine and public health, environmental justice, and beyond. The approach allows for estimation of average differences between intersectional strata (stratum inequalities), in-depth exploration of interaction effects, as well as decomposition of the total individual variation (heterogeneity) in individual outcomes within and between strata. Specific advice for conducting and interpreting MAIHDA models has been scattered across a burgeoning literature. We consolidate this knowledge into an accessible conceptual and applied tutorial for studying both continuous and binary individual outcomes. We emphasize I-MAIHDA in our illustration, however this tutorial is also informative for understanding related approaches, such as multicategorical MAIHDA, which has been proposed for use in clinical research and beyond. The tutorial will support readers who wish to perform their own analyses and those interested in expanding their understanding of the approach. To demonstrate the methodology, we provide step-by-step analytical advice and present an illustrative health application using simulated data. We provide the data and syntax to replicate all our analyses.

Anthocyanins, a subclass of flavonoids known for their vibrant colors and health-promoting properties, are pivotal in the nutritional science and food industry. This review article delves into the analytical methodologies for anthocyanin detection and quantification in food matrices, comparing quantitative and topical techniques. Quantitative methods, including High-performance Liquid Chromatography (HPLC) and Mass Spectrometry (MS), offer precise quantification and profiling of individual anthocyanins but require sample destruction, limiting their use in continuous quality control. Topical approaches, such as Near-infrared Spectroscopy (NIR) and hyperspectral imaging, provide rapid, in situ analysis without compromising sample integrity, ideal for on-site food quality assessment. The review highlights the advancements in chromatographic techniques, particularly Ultra-high-performance Liquid Chromatography (UHPLC) coupled with modern detectors, enhancing resolution and speed in anthocyanin analysis. It also emphasizes the growing importance of topical techniques in the food industry for their efficiency and minimal sample preparation. By examining the strengths and limitations of both analytical realms, this article aims to shed light on current challenges and prospective advancements, providing insights into future research directions for improving anthocyanin analysis in foods.

The technology acceptance model (TAM) has not been applied beyond the technological context, despite its widespread applications. This study extends the TAM to consumer goods and validates the conceptualised consumer goods acceptance model (CGAM) using tea-to-go as a proxy for consumer goods. An exploratory research approach based on a quota sample is used to adjust and test the CGAM, showing that the adjusted CGAM and its measures are reliable and valid, thus supporting the hypothesis that extending the TAM to a non-technological context is possible. The results are discussed in light of the data collection, which is based on a cross-sectional setting, assuming consumers\' knowledge of the good and forcing answers based on assumptions. The results show that despite major changes to the exogenous variables, the difference in variance levels between perceived usefulness (PU) and perceived ease of use (PEOU) is in accordance with TAM 3. Thus, PU is the strongest predictor of behavioural intention (BI), supporting the choice of constructs influencing PU. This also indicates that usefulness outweighs ease of use. The findings demonstrate that each variable category has a favourable influence on PU and PEOU. Specifically, cognitive instrumental processes (CIP) and value-related aspects (VRA) are significant predictors of PU, whereas CIP is the most critical driver, highlighting that consumer actions are driven by factors correlated with lifestyle, trends, and price. VRA_1 had the strongest impact on PU, accentuating the high potential of functional ingredients, such as vitamins. Furthermore, the results show that the anchor variables have a stronger impact on PEOU than the adjustment variables, emphasising the importance of enjoyment and indulgence in consumer goods, especially tea-to-go. These findings show that the empirically tested and adjusted CGAM provides a solid basis for measuring the acceptance of consumer goods and identifying key drivers.

BACKGROUND: Social pensions, social assistance systems for older people in rural areas, have been put into place in many nations and have positively impacted health. The long-term health consequences of social pension programs in China are uncertain. The aim of this study is to evaluate the long-term health consequences of the new rural social pension (NRSP) for the rural older people in China.
METHODS: Based on the 2011 and 2018 China Health and Retirement Longitudinal Study, we compared the scores on eight Health-Related Quality of Life (HRQoL) subscales of the rural older people before and after participation in the NRSP. The propensity score matching and difference-in-difference methods were used in data analysis. We also conducted a heterogeneity analysis for subgroups with different characteristics and pension enrolment times.
RESULTS: The NRSP significantly enhanced scores on physical functioning, role-physical, and self-rated mental health of old rural participants by 1.90 (p < 0.01), 2.05 (p < 0.01), and 2.93 (p < 0.05), respectively. After excluding newly enrolled individuals, the beneficial health effects of the NRSP remained significant. There were no significant changes due to NRSP in the other five scores on the HRQoL subscale of the rural older people. The NRSP had more health benefits for older people in underdeveloped areas without formal schooling.
CONCLUSIONS: The NRSP reduced health disparities and had long-term benefits on the physical and mental health of the rural older people. We suggest continuously expanding the NRSP throughout rural China and further improving the social support system to enhance the overall quality of life of the rural older people. Comparable social pension programs aimed at underprivileged groups could also be conducted in other low- or middle-income nations.

暂无摘要。

\'Open Science\' advocates for open access to scientific research, as well as sharing data, analysis plans and code in order to enable replication of results. However, these requirements typically fail to account for methodological differences between quantitative and qualitative research, and serious ethical problems are raised by the suggestion that full qualitative datasets can or should be published alongside qualitative research papers. Aside from important ethical concerns, the idea of sharing qualitative data in order to enable replication is conceptually at odds with the underpinnings on most qualitative methodologies, which highlight the importance of the unique interpretative function of the researcher. The question of whether secondary analysis of qualitative data is acceptable is key, and in this commentary we argue that there are good conceptual, ethical and economic reasons to consider how funders, researchers and publishers can make better use of existing data.

Researchers in behavioral sciences are often interested in longitudinal behavior change outcomes and the mechanisms that influence changes in these outcomes over time. The statistical models that are typically implemented to address these research questions do not allow for investigation of mechanisms of dynamic change over time. However, latent change score models allow for dynamic change (not just linear or exponential change) over time and have flexibility in parameter constraints that other longitudinal models do not have. Developmental researchers also frequently utilize mediation analyses to investigate mechanisms of influence in longitudinal research implemented in path analytic or latent growth curve models. In this article, we provide three examples of how mediation can be tested in the latent change score framework by combining aspects of traditional mediation models with latent change score models of repeated measures outcomes (and mediators and predictors) with more than two timepoints. We also provide the Mplus syntax to complete these analyses and practical considerations of latent change score mediation (LCSM) models.

It is unknown how co-rumination, or perseverating on problems or feelings with another person, unfolds in the daily lives of romantic couples. Using a variance decomposition procedure on data from a 14-day dyadic diary, we assessed how much variance in co-rumination was attributable to temporally stable and varying factors, as well as whether co-rumination is better measured as a couple-level or individual-level process. Within-person, within-couple fluctuations in co-rumination contributed most (~33%) to the total variance and summary scores based on these fluctuations were reliable. Stable between-couple differences accounted for ~14% of the total variance and could also be reliably assessed. However, within-couple agreement in co-rumination was low, such that the reliability at the level of within-couple change was inadequate. Research is needed to understand these divergent perceptions of co-rumination and potential downstream consequences. We conclude by considering how these results inform theory and can be applied to similar dyadic constructs.

Assessment of coupling between transtibial sockets and users is historically based on clinicians\' observations and experience, but can be inaccurate and unreliable. Therefore, we present a proof of concept, for five out of six possible degrees of freedom coupling metric system for a socket, using motion analysis calibrated on a 3D printed limb substitute. The method is compatible with any socket suspension method and does not require prior modifications to the socket. Calibration trials were used to locate the axis of rotation of the knee joint referenced against a marker cluster on the thigh; this allowed for the identification of the limb during test trials despite the entire residuum being obscured from view by the socket. The error in the technique was found to be within 0.7 mm in displacement and 0.7 degrees in rotation, based on the control data. Dynamic testing showed the Inter Quartile Range (IQR) of inter time step variance was <0.5 mm/deg for all metrics. The method can form a basis for objective socket evaluation, improve clinical practice and the quality of life for amputees.