Objectives/Goals: Longitudinal studies capture dynamic host–environment interactions crucial to microbiome research. Commonly used mixed-effects models can struggle with small clinical samples, like many endometrial cancer studies. We will compare them to simpler fixed-effects models, aiming to develop a new fixed-effects differential abundance alternative. Methods/Study Population: Starting with simulated data for linear models with a single treatment effect, we will incrementally increase complexity to reflect real-world microbiome data. To observe conditions of misspecification, simulated data of repeated measures will be generated using different distributions, while varying parameters and inter-class correlation. In each condition, linear fixed- and mixed-effects models will be fitted 1000 times to empirically determine p-value, type 1 error rate, and power. We will increase the verisimilitude of our approach by using endometrial cancer data from our lab as a real background, while adding simulated signals. This data will be used to assess extant differential abundance models against our novel fixed-effects model. Results/Anticipated Results: Our initial findings indicate that fixed-effects models maintain control over type 1 error rates in small samples, while mixed-effects models do not perform as reliably. We are now exploring the effects of confounders on type 1 error rates and power in linear models, while our next step will evaluate generalized linear models in a differential abundance context. We expect that the fixed-effects models will continue to be as reliable as mixed-effects models, while being less computationally complex. After establishing our theoretical basis, our novel model should perform comparably to mixed-effects models on pseudo-simulated endometrial cancer data and better at small sample sizes. We will finally apply our model to real endometrial cancer data to identify microbial markers of disease predisposition. Discussion/Significance of Impact: By characterizing and improving these statistical tools, we seek to increase the robustness and power of microbiome study results (especially at small sample sizes), ultimately supporting better-informed translational research decisions. This work underscores the importance of statistical methods in advancing microbiome research.

Systematically monitoring the baseline sensitivity of troublesome weeds to herbicides is a crucial step in the early detection of their market lifespan. Florpyrauxifen-benzyl is one of the most important herbicides used in rice production throughout the world, and has been used for 5 yr in China. Barnyardgrass is one of the main targeted weed species of florpyrauxifen-benzyl. In total, 114 barnyardgrass populations were collected from rice fields in Jiangsu Province, China, and using whole-plant bioassays they were screened for susceptibility to florpyrauxifen-benzyl. The GR50 values (representing the dose that causes a 50% reduction in fresh weight of aboveground parts) of florpyrauxifen-benzyl for all populations ranged from 1.0 to 34.5 g ai ha−1, with an average of 6.8 g ai ha−1, a baseline sensitivity dose of 3.3 g ai ha−1, and a baseline sensitivity index of 34.5. Twenty-one days after treatment with florpyrauxifen-benzyl at the labeled dose (36 g ai ha−1), 90% of the barnyardgrass populations exhibited >95% reductions in fresh weight of aboveground parts. Compared with the baseline sensitivity dose, 63, 44, and 7 populations had, respectively, no resistance (55%), low resistance (39%), and moderate resistance (6%) to florpyrauxifen-benzyl. Furthermore, the GR50 distribution of barnyardgrass populations did not show a significant correlation with collection location, planting method (direct-seeding or transplanting), or rice species (Oryza sativa L. ssp. indica or ssp. japonica) at any of rice fields where seeds had been collected (P > 0.05). In conclusion, florpyrauxifen-benzyl remains effective for barnyardgrass control in rice fields despite serious resistance challenges.

Despite the important role of state-owned enterprises (SOEs) in government policy implementation, there is a lack of research on how SOEs owned by different government entities differ. We draw on an attention-based view (ABV) to understand how central government-owned (called central SOEs) and local government-owned enterprises (called local SOEs) differ in their response to digitalization, a major state objective in China in recent years. The two types of SOEs differ in the foundational feature of attention structure – the rules of the game (as embodied in their different goals, identities, and evaluation of top executives) – as well as important features such as governance structures and resources. These features can trigger more attention in central SOEs to digitalization. Given the interdependence of these features in shaping the structural distribution of attention, we further propose how governance structures and resources can influence strategic attention differently in SOEs with different rules of the game. The arguments are tested using data from all Chinese-listed manufacturing SOEs between 2009 and 2020. The study reveals different responses to national strategy between central and local SOEs due to their distinct attention structures designed by the state. It also extends the ABV and research on corporate digital transformation.

High prevalence of long COVID symptoms has emerged as a significant public health concern. This study investigated the associations between three doses of COVID-19 vaccines and the presence of any and ≥3 types of long COVID symptoms among people with a history of SARS-CoV-2 infection in Hong Kong, China. This is a secondary analysis of a cross-sectional online survey among Hong Kong adult residents conducted between June and August 2022. This analysis was based on a sub-sample of 1,542 participants with confirmed SARS-CoV-2 infection during the fifth wave of COVID-19 outbreak in Hong Kong (December 2021 to April 2022). Among the participants, 40.9% and 16.1% self-reported having any and ≥3 types of long COVID symptoms, respectively. After adjusting for significant variables related to sociodemographic characteristics, health conditions and lifestyles, and SARS-CoV-2 infection, receiving at least three doses of COVID-19 vaccines was associated with lower odds of reporting any long COVID symptoms comparing to receiving two doses (adjusted odds ratio [AOR]: 0.69, 95% CI: 0.54, 0.87, P = .002). Three doses of inactivated and mRNA vaccines had similar protective effects against long COVID symptoms. It is important to strengthen the coverage of COVID-19 vaccination booster doses, even in the post-pandemic era.

Pro-environmental behavior, including waste sorting and recycling, involves a combination of future-oriented (futureness) and other-oriented (otherness) attributes. Inspired by the perspective of intergenerational choice, this work explores whether eliciting concerns for future others could increase public support for recycling policy and recycling behavior. Study 1 consisted of an online random controlled trial and a laboratory experiment. In Study 1A (N = 400), future other-concern was primed using a static text manipulation, whereas in Study 1B (N = 192), a dynamic virtual manipulation was employed. The results showed that people in the conditions that elicited future other-concern reported greater household recycling intentions and more actual recycling behavior than those in the control conditions. Study 2A (N = 467) and Study 2B (N = 600) generalized this effect on the acceptance of the ‘Certain Time Certain Place’ waste sorting policy in China. Consistent with the intergenerational choice model, envisioning the future of subsequent generations is more impactful in gaining policy approval than merely envisioning a future time. These findings provide a new method for promoting public policy approval and recycling behavior, suggesting that people could become environmentally friendly when they are guided to consider future others.

The gas dynamics of shock-induced gas filtration through densely packed granular columns with vastly varying shock intensity and the structural parameters are numerically investigated using a coupled Eulerian–Lagrangian approach. The results shed fundamental light on the thermal effects of the shock-induced gas filtration manifested by a distinctive self-heating hot gas layer traversing the medium. The characteristics of the thermal effects in terms of the thermal intensity and uniformity are found to vary with the shock Mach number, Ms, and the filtration coefficient of the granular media, Π. As the incident shock transitions from weak to strong, and (or) the filtration coefficient increases from O(10−5) to O(104), the heating mechanisms transition between three distinct heating modes. A phase diagram of heating modes is established on the parameter space (Ms, Π), which enables us to predict the characteristics of the thermal effect in different shock-induced gas filtrations. The thermal effects markedly accelerate the pressure diffusion due to the additional heat influx when the time scale of the former is smaller than or comparable to the latter. Based on the contour map displaying the coupling degree of the thermal effects and the pressure diffusion, we identify a decoupling criterion whereby the isothermal assumption holds if only the pressure diffusion is concerned. The thermal effects may well bring about considerable thermal shocks which pose a great threat to the integrity of the solid skeleton and further reduce the overall shock resistance performance of the porous media.

Human alveolar echinococcosis is a hard-to-treat and largely untreated parasitic disease with high associated health care costs. The current antiparasitic treatment for alveolar echinococcosis relies exclusively on albendazole, which does not act parasiticidally and can induce severe adverse effects. Alternative, and most importantly, improved treatment options are urgently required. A drug repurposing strategy identified the approved antimalarial pyronaridine as a promising candidate against Echinococcus multilocularis infections. Following a 30-day oral regimen (80 mg kg−1 day−1), pyronaridine achieved an excellent therapeutic outcome in a clinically relevant hepatic alveolar echinococcosis murine model, showing a significant reduction in both metacestode size (72.0%) and counts (85.2%) compared to unmedicated infected mice, which revealed significantly more potent anti-echinococcal potency than albendazole treatment at an equal dose (metacestode size: 42.3%; counts: 4.1%). The strong parasiticidal activity of pyronaridine was further confirmed by the destructive damage to metacestode tissues observed morphologically. In addition, a screening campaign combined with computational similarity searching against an approved drug library led to the identification of pirenzepine, a gastric acid-inhibiting drug, exhibiting potent parasiticidal activity against protoscoleces and in vitro cultured small cysts, which warranted further in vivo investigation as a promising anti-echinococcal lead compound. Pyronaridine has a known drug profile and a long track record of safety, and its repurposing could translate rapidly to clinical use for human patients with alveolar echinococcosis as an alternative or salvage treatment.

Previous research has suggested a potential link between folic acid (FA) supplementary therapy and gastric ulcers (GU). To investigate this relationship further, we conducted a Mendelian randomisation (MR) analysis using data from the UK Biobank. Our analysis primarily employed inverse-variance weighted (IVW) methods, including both fixed-effect and random-effect models. To ensure the robustness of our findings, additional methods such as the simple median, the weighted median and the penalised weighted median were also applied. The MR analysis aimed to explore the causal effect of FA supplementary therapy on GU. Seven SNP at genetic loci associated with FA supplementary therapy were identified. Both the random-effect and fixed-effect IVW models indicated that genetically predicted FA supplementary therapy significantly reduced the risk of GU (OR, 0·870; 95 % CI 0·826, 0·917, P < 0·001). This result was consistent across other methods, with similar outcomes observed using the simple median (OR, 0·835; 95 % CI 0·773, 0·901, P < 0·001), the weighted median (OR, 0·854; 95 % CI 0·794, 0·919, P < 0·001) and the penalised weighted median (OR, 0·849; 95 % CI 0·789, 0·914, P < 0·001). Leave-one-out sensitivity analysis confirmed that no individual SNP significantly drove the association between FA supplementary therapy and GU. This MR study provides genetic evidence that FA supplementary therapy may decrease the risk of GU.

Artificial sweeteners are generally used and recommended to alternate added sugar for health promotion. However, the health effects of artificial sweeteners remain unclear. In this study, we included 6371 participants from the National Health and Nutrition Examination Survey with artificial sweetener intake records. Logistic regression and Cox regression were applied to explore the associations between artificial sweeteners and risks of cardiometabolic disorders and mortality. Mendelian randomisation was performed to verify the causal associations. We observed that participants with higher consumption of artificial sweeteners were more likely to be female and older and have above medium socio-economic status. After multivariable adjustment, frequent consumers presented the OR (95 % CI) for hypertension (1·52 (1·29, 1·80)), hypercholesterolaemia (1·28 (1·10, 1·50)), diabetes (3·74 (3·06, 4·57)), obesity (1·52 (1·29, 1·80)), congestive heart failure (1·89 (1·35, 2·62)) and heart attack (1·51 (1·10, 2·04)). Mendelian randomisation confirmed the increased risks of hypertension and type 2 diabetes. Moreover, an increased risk of diabetic mortality was identified in participants who had artificial sweeteners ≥ 1 daily (HR = 2·62 (1·46, 4·69), P = 0·001). Higher consumption of artificial sweeteners is associated with increased risks of cardiometabolic disorders and diabetic mortality. These results suggest that using artificial sweeteners as sugar substitutes may not be beneficial.

Shark vertebrae and their centra (vertebral bodies) are high-performance structures able to survive millions of cycles of high amplitude strain despite lacking a repair mechanism for accumulating damage. Shark centra consist of mineralized cartilage, a biocomposite of bioapatite (bAp), and collagen, and the nanocrystalline bAp's contribution to functionality remains largely uninvestigated. Using the multiple detector energy-dispersive diffraction (EDD) system at 6-BM-B, the Advanced Photon Source, and 3D tomographic sampling, the 3D functionality of entire centra were probed. Immersion in ethanol vs phosphate-buffered saline produces only small changes in bAp d-spacing within a great hammerhead centrum. EDD mapping under in situ loading was performed an entire blue shark centrum, and 3D maps of bAp strain showed the two structural zones of the centrum, the corpus calcareum and intermedialia, contained opposite-signed strains approaching 0.5%, and application of ~8% nominal strain did not alter these strain magnitudes and their spatial distribution.

In an isolate-free graph G, a subset S of vertices is a semitotal dominating set of G if it is a dominating set of G and every vertex in S is within distance 2 of another vertex of S. The semitotal domination number of G, denoted by $\gamma _{t2}(G)$, is the minimum cardinality of a semitotal dominating set in G. Goddard, Henning and McPillan [‘Semitotal domination in graphs’, Utilitas Math. 94 (2014), 67–81] characterised the trees and graphs of minimum degree 2 with semitotal domination number half their order. In this paper, we characterise all graphs whose semitotal domination number is half their order.

This study investigates the impact of molecular thermal fluctuations on compressible decaying isotropic turbulence using the unified stochastic particle (USP) method, encompassing both two-dimensional (2-D) and three-dimensional (3-D) scenarios. The findings reveal that the turbulent spectra of velocity and thermodynamic variables follow the wavenumber (k) scaling law of ${k}^{(d-1)}$ for different spatial dimensions $d$ within the high wavenumber range, indicating the impact of thermal fluctuations on small-scale turbulent statistics. With the application of Helmholtz decomposition, it is found that the thermal fluctuation spectra of solenoidal and compressible velocity components (${\boldsymbol {u}}_{s}$ and ${\boldsymbol {u}}_{c}$) follow an energy ratio of 1 : 1 for 2-D cases, while the ratio changes to 2 : 1 for 3-D cases. Comparisons between 3-D turbulent spectra obtained through USP simulations and direct numerical simulations of the Navier–Stokes equations demonstrate that thermal fluctuations dominate the spectra at length scales comparable to the Kolmogorov length scale. Additionally, the effect of thermal fluctuations on the spectrum of ${\boldsymbol {u}}_{c}$ is significantly influenced by variations in the turbulent Mach number. We further study the impact of thermal fluctuations on the predictability of turbulence. With initial differences caused by thermal fluctuations, different flow realizations display significant disparities in velocity and thermodynamic fields at larger scales after a certain period of time, which can be characterized by ‘inverse error cascades’. Moreover, the results suggest a strong correlation between the predictabilities of thermodynamic fields and the predictability of ${\boldsymbol {u}}_{c}$.

Trauma is a significant health issue that not only leads to immediate death in many cases but also causes severe complications, such as sepsis, thrombosis, haemorrhage, acute respiratory distress syndrome and traumatic brain injury, among trauma patients. Target protein identification technology is a vital technique in the field of biomedical research, enabling the study of biomolecular interactions, drug discovery and disease treatment. It plays a crucial role in identifying key protein targets associated with specific diseases or biological processes, facilitating further research, drug design and the development of treatment strategies. The application of target protein technology in biomarker detection enables the timely identification of newly emerging infections and complications in trauma patients, facilitating expeditious medical interventions and leading to reduced post-trauma mortality rates and improved patient prognoses. This review provides an overview of the current applications of target protein identification technology in trauma-related complications and provides a brief overview of the current target protein identification technology, with the aim of reducing post-trauma mortality, improving diagnostic efficiency and prognostic outcomes for patients.

A new species of Moniliformis, M. tupaia n. sp. is described using integrated morphological methods (light and scanning electron microscopy) and molecular techniques (sequencing and analysing the nuclear 18S, ITS, 28S regions and mitochondrial cox1 and cox2 genes), based on specimens collected from the intestine of the northern tree shrew Tupaia belangeri chinensis Anderson (Scandentia: Tupaiidae) in China. Phylogenetic analyses show that M. tupaia n. sp. is a sister to M. moniliformis in the genus Moniliformis, and also challenge the systematic status of Nephridiacanthus major. Moniliformis tupaia n. sp. represents the third Moniliformis species reported from China.

Obesity is an important characteristic manifestation of metabolic syndrome (MetS), and body roundness index (BRI) is one of the anthropometric indicators associated with obesity. However, studies on the relationship between BRI and MetS risk are limited. We aimed to explore the relationship between baseline BRI and MetS in the USA population. Our study used data from the National Health and Nutrition Examination Survey from 1999 to 2018, ultimately enrolling and analysing 47 303 participants. Data-driven tertiles were used to categorise BRI levels, and multivariate logistic regression models were fitted to investigate the association of BRI with MetS in adults. In addition, receiver operating characteristic curve analysis was used to assess the ability of BRI to predict MetS. The distribution of BRI was different across ethnic groups with a gradual decrease in the proportion of non-Hispanic Whites and other races. In addition, BRI was significantly associated with traditional cardiovascular risk factors. Univariate regression analysis indicated BRI to be a moderate risk factor for MetS, and multivariate logistic regression analysis found that BRI remained an independent risk factor for MetS. After adjusting for confounding variables, a non-linear relationship was found between BRI levels and the prevalence of MetS. More importantly, BRI predicted MetS with the largest AUC among anthropometric measures. In summary, elevated baseline BRI levels are independently associated with the development of MetS, and baseline BRI may assist in identifying patients at risk for MetS, leading to early and optimal treatment to improve their outcomes.

In an isolate-free graph G, a subset S of vertices is a semitotal dominating set of G if it is a dominating set of G and every vertex in S is within distance 2 of another vertex of S. The semitotal domination number of G, denoted by $\gamma _{t2}(G)$, is the minimum cardinality of a semitotal dominating set in G. Using edge weighting functions on semitotal dominating sets, we prove that if $G\neq N_2$ is a connected claw-free graph of order $n\geq 6$ with minimum degree $\delta (G)\geq 3$, then $\gamma _{t2}(G)\leq \frac{4}{11}n$ and this bound is sharp, disproving the conjecture proposed by Zhu et al. [‘Semitotal domination in claw-free cubic graphs’, Graphs Combin. 33(5) (2017), 1119–1130].