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Little is known about the association between iodine nutrition status and bone health. The present study aimed to explore the connection between iodine nutrition status, bone metabolism parameters, and bone disease (osteopenia and osteoporosis). A cross-sectional survey was conducted involving 391, 395, and 421 adults from iodine fortification areas (IFA), iodine adequate areas (IAA), and iodine excess areas (IEA) of China. Iodine nutrition status, bone metabolism parameters and BMD were measured. Our results showed that, in IEA, the urine iodine concentrations (UIC) and serum iodine concentrations (SIC) were significantly higher than in IAA. BMD and Ca2+ levels were significantly different under different iodine nutrition levels and the BMD were negatively correlated with UIC and SIC. Univariate linear regression showed that gender, age, BMI, menopausal status, smoking status, alcohol consumption, UIC, SIC, free thyroxine, TSH, and alkaline phosphatase were associated with BMD. The prevalence of osteopenia was significantly increased in IEA, UIC ≥ 300 µg/l and SIC > 90 µg/l groups. UIC ≥ 300 µg/l and SIC > 90 µg/l were risk factors for BMD T value < –1·0 sd. In conclusion, excess iodine can not only lead to changes in bone metabolism parameters and BMD, but is also a risk factor for osteopenia and osteoporosis.
The sulphur microbial diet (SMD), a dietary pattern associated with forty-three sulphur-metabolising bacteria, may influence gut microbiota composition and contribute to ageing process through gut-produced hydrogen sulfide (H2S). We aimed to explore the association between SMD and biological age (BA) acceleration, using the cross-sectional study that included 71 579 individuals from the UK Biobank. The SMD score was calculated by multiplying β-coefficients by corresponding serving sizes and summing them, based on dietary data collected using the Oxford WebQ, a 24-hour dietary assessment tool. BA was assessed using Klemerae–Doubal (KDM) and PhenoAge methods. The difference between BA and chronological age refers to the age acceleration (AgeAccel), termed ‘KDMAccel’ and ‘PhenoAgeAccel’. Generalised linear regression was performed. Mediation analyses were used to investigate underlying mediators including BMI and serum aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio. Following adjustment for multiple variables, a positive association was observed between consuming a dietary pattern with a higher SMD score and both KDMAccel (βQ4 v. Q1 = 0·35, 95 % CI = 0·27, 0·44, P < 0·001) and PhenoAgeAccel (βQ4 v. Q1 = 0·32, 95 % CI = 0·23, 0·41, P < 0·001). Each 1-SD increase in SMD score was positively associated with the acceleration of BA by 7·90 % for KDMAccel (P < 0·001) and 7·80 % for PhenoAgeAccel (P < 0·001). BMI and AST/ALT mediated the association. The stratified analysis revealed stronger accelerated ageing impacts in males and smokers. Our study indicated a higher SMD score is associated with elevated markers of biological ageing, supporting the potential utility of gut microbiota-targeted dietary interventions in attenuating the ageing process.
The study aims were to present in vitro susceptibilities of clinical isolates from Gram-negative bacteria bloodstream infections (GNBSI) collected in China. GNBSI isolates were collected from 18 tertiary hospitals in 7 regions of China from 2018 to 2020. Minimum inhibitory concentrations were assessed using a Trek Diagnostic System. Susceptibility was determined using CLSI broth microdilution, and breakpoints were interpreted using CLSI M100 (2021). A total of 1,815 GNBSI strains were collected, with E. coli (42.4%) and Klebsiella pneumoniae (28.6%) being the most prevalent species, followed by P. aeruginosa (6.7%). Susceptibility analyses revealed low susceptibilities (<40%) of ESBL-producing E. coli and K. pneumonia to third-/fourth-generation cephalosporins, monobactamases, and fluoroquinolones. High susceptibilities to colistin (95.0%) and amikacin (81.3%) were found for K. pneumoniae, while Acinetobacter baumannii exhibited a high susceptibility (99.2%) to colistin but a low susceptibility to other antimicrobials (<27.5%). Isolates from ICUs displayed lower drug susceptibility rates of K. pneumoniae and A. baumannii than isolates from non-ICUs (all P < 0.05). Carbapenem-resistant and ESBL-producing K. pneumoniae detection was different across regions (both P < 0.05). E. coli and K. pneumoniae were major contributors to GNBSI, while A. baumannii exhibited severe drug resistance in isolates obtained from ICU departments.
The dependence of the Richtmyer–Meshkov instability (RMI) on post-shock Atwood number ($A_1$) is experimentally investigated for a heavy–light single-mode interface. We create initial interfaces with density ratios of heavy to light gases ranging from 1.73 to 34.07, and achieve the highest $|A_1|$ value reported to date for gaseous-interface experiments (0.95). For the first time, spike acceleration is observed in experiments with a heavy–light configuration. The models for the start-up, linear and weakly nonlinear evolution stages are evaluated over a wide range of $A_1$ conditions. Specifically, the models proposed by Li et al. (Phys. Fluids, vol. 36, 2024, 056104) and Wouchuk & Nishihara (Phys. Plasmas, vol. 4, 1997, 1028–1038) effectively describe the start-up and linear stages, respectively, across all cases. None of the considered nonlinear models is valid under all $A_1$ conditions. Based on the dependence of spike and bubble evolutions on $A_1$ provided by the present work and previous study (Chen et al., J. Fluid Mech., vol. 975, 2023, A29), the SEA model (Sadot et al., Phys. Rev. Lett., vol. 80, 1998, pp. 1654–1657), whose expression has clear physical meanings, is modified by revising the coefficient that governs its prediction for early-time evolution. The modified model applies to prediction of the weakly nonlinear evolution of RMI with $A_1$ ranging from −0.95 to −0.35 and from 0.30 to 0.86. Based on this model, an approximation of the critical $A_1$ for the occurrence of spike acceleration is obtained.
The rural-oriented tuition-waived medical education program in China, started in 2010, provides free medical education to students committed to serving in rural areas to address medical staff shortages. Despite its success in training and deploying graduates, retaining them post-obligation remains challenging. This study explores the mechanisms behind the turnover intentions of rural-oriented medical students in Western China, offering insights for their retention.
Methods:
Semi-structured interviews were conducted with 47 rural-oriented medical students and 30 health clinic directors in Nanning City. Interview data were analysed using grounded theory, and open, axial and selective coding was applied.
Results:
Through three levels of coding analysis, 34 tree nodes, 13 sub-categories and 3 main categories were identified from the interviews with rural-oriented medical students and health clinic directors. 3 main categories were Subjective Norms, Behavioural Attitudes, and Perceived Behavioural Control.
Conclusion:
A model of turnover intention among rural-oriented medical students was developed. This model can serve as a valuable reference for future policy optimization concerning China’s rural order-directed medical students.
Depression has been linked to disruptions in resting-state networks (RSNs). However, inconsistent findings on RSN disruptions, with variations in reported connectivity within and between RSNs, complicate the understanding of the neurobiological mechanisms underlying depression.
Methods
A systematic literature search of PubMed and Web of Science identified studies that employed resting-state functional magnetic resonance imaging (fMRI) to explore RSN changes in depression. Studies using seed-based functional connectivity analysis or independent component analysis were included, and coordinate-based meta-analyses were performed to evaluate alterations in RSN connectivity both within and between networks.
Results
A total of 58 studies were included, comprising 2321 patients with depression and 2197 healthy controls. The meta-analysis revealed significant alterations in RSN connectivity, both within and between networks, in patients with depression compared with healthy controls. Specifically, within-network changes included both increased and decreased connectivity in the default mode network (DMN) and increased connectivity in the frontoparietal network (FPN). Between-network findings showed increased DMN–FPN and limbic network (LN)–DMN connectivity, decreased DMN–somatomotor network and LN–FPN connectivity, and varied ventral attention network (VAN)–dorsal attentional network (DAN) connectivity. Additionally, a positive correlation was found between illness duration and increased connectivity between the VAN and DAN.
Conclusions
These findings not only provide a comprehensive characterization of RSN disruptions in depression but also enhance our understanding of the neurobiological mechanisms underlying depression.
Accurate characterization of high-power laser parameters, especially the near-field and far-field distributions, is crucial for inertial confinement fusion experiments. In this paper, we propose a method for computationally reconstructing the complex amplitude of high-power laser beams using modified coherent modulation imaging. This method has the advantage of being able to simultaneously calculate both the near-field (intensity and wavefront/phase) and far-field (focal-spot) distributions using the reconstructed complex amplitude. More importantly, the focal-spot distributions at different focal planes can also be calculated. To verify the feasibility, the complex amplitude optical field of the high-power pulsed laser was measured after static aberrations calibration. Experimental results also indicate that the near-field wavefront resolution of this method is higher than that of the Hartmann measurement. In addition, the far-field focal spot exhibits a higher dynamic range (176 dB) than that of traditional direct imaging (62 dB).
While the cross-sectional relationship between internet gaming disorder (IGD) and depression is well-established, whether IGD predicts future depression remains debated, and the underlying mechanisms are not fully understood. This large-scale, three-wave longitudinal study aimed to clarify the predictive role of IGD in depression and explore the mediating effects of resilience and sleep distress.
Methods
A cohort of 41,215 middle school students from Zigong City was assessed at three time points: November 2021 (T1), November 2022 (T2) and November 2023 (T3). IGD, depression, sleep distress and resilience were measured using standardized questionnaires. Multiple logistic regression was used to examine the associations between baseline IGD and both concurrent and subsequent depression. Mediation analyses were conducted with T1 IGD as the predictor, T2 sleep distress and resilience as serial mediators and T3 depression as the outcome. To test the robustness of the findings, a series of sensitivity analyses were performed. Additionally, sex differences in the mediation pathways were explored.
Results
(1) IGD was independently associated with depression at baseline (T1: adjusted odds ratio [AOR] = 4.76, 95% confidence interval [CI]: 3.79–5.98, p < 0.001), 1 year later (T2: AOR = 1.42, 95% CI: 1.16–1.74, p < 0.001) and 2 years later (T3: AOR = 1.24, 95% CI: 1.01–1.53, p = 0.042); (2) A serial multiple mediation effect of sleep distress and resilience was identified in the relationship between IGD and depression. The mediation ratio was 60.7% in the unadjusted model and 33.3% in the fully adjusted model, accounting for baseline depression, sleep distress, resilience and other covariates. The robustness of our findings was supported by various sensitivity analyses; and (3) Sex differences were observed in the mediating roles of sleep distress and resilience, with the mediation ratio being higher in boys compared to girls.
Conclusions
IGD is a significant predictor of depression in adolescents, with resilience and sleep distress serving as key mediators. Early identification and targeted interventions for IGD may help prevent depression. Intervention strategies should prioritize enhancing resilience and improving sleep quality, particularly among boys at risk.
The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.
Methods
A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.
Results
Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.
Conclusions
These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.
The manipulation of the Richtmyer–Meshkov instability growth at a heavy–light interface via successive shocks is theoretically analysed and experimentally realized in a specific shock-tube facility. An analytical model is developed to forecast the interface evolution before and after the second shock impact, and the possibilities for the amplitude evolution pattern are systematically discussed. Based on the model, the parameter conditions for each scenario are designed, and all possibilities are experimentally realized by altering the time interval between two shock impacts. These findings may enhance the understanding of how successive shocks influence hydrodynamic instabilities in practical applications.
This paper introduces a novel fiber-based picosecond burst-mode laser system capable of operating at high power and high repetition rates. A pulse-circulating fiber ring was developed as a burst generator, achieving an intra-burst repetition rate of 469 MHz without the need for a high-repetition-rate seed source. This design also allows for flexible adjustment of the number of sub-pulses, burst repetition rate and burst shape. In addition, a master oscillator power amplifier was employed to analyze the amplification characteristics of bursts. The system demonstrated a maximum average power of 606 W, with a measured sub-pulse duration of 62 ps and the highest sub-pulse peak power of 980 kW. To the best of our knowledge, this marks the highest average power obtained in burst-mode ultrafast lasers. Such a laser system holds potential for applications in precision manufacturing, high-speed imaging, high-precision ranging and other diverse domains.
The maintenance of item bank is essential for continuously implementing adaptive tests. Calibration of new items online provides an opportunity to efficiently replenish items for the operational item bank. In this study, a new optimal design for online calibration (referred to as D-c) is proposed by incorporating the idea of original D-optimal design into the reformed D-optimal design proposed by van der Linden and Ren (Psychometrika 80:263–288, 2015) (denoted as D-VR design). To deal with the dependence of design criteria on the unknown item parameters of new items, Bayesian versions of the locally optimal designs (e.g., D-c and D-VR) are put forward by adding prior information to the new items. In the simulation implementation of the locally optimal designs, five calibration sample sizes were used to obtain different levels of estimation precision for the initial item parameters, and two approaches were used to obtain the prior distributions in Bayesian optimal designs. Results showed that the D-c design performed well and retired smaller number of new items than the D-VR design at almost all levels of examinee sample size; the Bayesian version of D-c using the prior obtained from the operational items worked better than that using the default priors in BILOG-MG and PARSCALE; and Bayesian optimal designs generally outperformed locally optimal designs when the initial item parameters of the new items were poorly estimated.
This article addresses the localization problem in robotic autonomous luggage trolley collection at airports and provides a systematic evaluation of different methods to solve it. The robotic autonomous luggage trolley collection is a complex system that involves object detection, localization, motion planning and control, manipulation, etc. Among these components, effective localization is essential for the robot to employ subsequent motion planning and end-effector manipulation because it can provide a correct goal position. This article explores four popular and representative localization methods for object localization in luggage trolley collection: radio frequency identification (RFID), Keypoints, ultrawideband (UWB), and Reflectors. A qualitative evaluation framework is constructed to assess performance, encompassing Localization Accuracy, Mobile Power Supplies, Coverage Area, Cost, and Scalability. Furthermore, a series of quantitative experiments concerning Localization Accuracy and Success Rate have been conducted on a real-world robotic autonomous luggage trolley collection system. The performance of various localization methods is further analyzed based on experimental results, indicating that the Keypoints method is optimally suited for indoor environments to facilitate luggage trolley collection. Significantly, these experiment results provide a valuable reference point, extending the application of indoor localization methods across diverse scenarios. A website about this work is available at https://sites.google.com/view/localization-evaluation/.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
Microorganisms symbiotic with insects, whether permanently or temporarily, play a crucial role in the nutrition, development, reproduction, defence, and metamorphosis regulation. In some Lepidoptera, oviposition-deterrent pheromones (ODPs) on egg surface were used by pregnant females to modify the behaviour of conspecifics to avoid excessive competition for limited resources. In this study, we constructed four different Spodoptera litura groups, including, OH, OA, SH, and OA, which either feed on different hosts or grow in different environments. The 16S rDNA libraries of microbes from the egg surface of the four groups were constructed and sequenced. According to alpha and beta diversity indices, the microbes in environments and diets considerably influenced the richness, diversity, and community compositions of the microbiota on egg surfaces. The quantity of the main ODP components and the corresponding oviposition-deterrent activity among four groups were significantly differed among the four groups. The result of this study revealed that altering of microbes in environments or diets considerably changed the contents of ODP and oviposition-deterrent activity. As ODPs impart oviposition-deterrent activity towards closely related species, the findings of this study suggest that we should pay more attention to the role of symbiotic microorganisms in changing the ability of insects, especially sympatric species, to occupy the optimal niche when developing novel pest-control strategies.
The effects of reshock conditions, including the interface evolution state before reshock and the second shock intensity, on interface instability induced by two successive shocks propagating in the same direction are investigated via shock-tube experiments. It is observed that the reshock promotes the interface instability, and the post-reshock perturbation evolution relates to both the pre-reshock interface evolution state and second shock intensity. For the linear evolution of the twice-shocked interface, existing models perform poorly when either the pre-reshock interface shape effect or the secondary compression effect is pronounced, as current reduction factors fail to accurately describe these effects. Besides, the reshock-induced linear amplitude growth rate shows a non-monotonic dependence on the scaled pre-reshock amplitude, primarily due to the shape effect of the pre-reshock interface. For the post-reshock nonlinear evolution, the model proposed by Zhang & Guo (J. Fluid Mech., vol. 786, 2016, pp. 47–61) offers reasonable predictions when the second shock is weak. However, when the second shock is moderately strong, the model overestimates the bubble growth and underestimates the spike evolution under the influence of the significant secondary compression effect. Furthermore, empirical linear and nonlinear models capable of describing the dependence of the post-reshock evolution on reshock conditions are proposed based on the present experimental results and existing models.
Nano-silicon has been regarded as the most promising anode material for next-generation lithium-ion batteries (LIBs). However, the preparation of nano-silicon suffers from high cost, complex procedures, and low yield, which hinders its commercial application. In this study, porous nano-silicon with particle sizes in the range of 50–100 nm was prepared through molten salt-assisted magnesiothermic reduction using porous nano-silica derived from clay minerals as the precursor. Through combining ball milling and acid activation, the synthesised nano-silica derived from montmorillonite exhibited smaller particle sizes (below 50 nm), higher specific surface area (647 m2 g–1), and total pore volume (0.71 cm3 g–1). This unique structure greatly facilitated the conversion efficiency of silica into nano-silicon by maximising the contact area between silica and magnesium powder and optimising the diffusion kinetics of magnesium atoms. When used as anodes in LIBs, the synthesised nano-silicon materials demonstrated a high specific capacity of up to 1222 mAh g–1 and an excellent capacity retention rate of 79% after 150 cycles at a current density of 0.5 A g–1. This method provides a novel approach for the cost-effective and large-scale production of nano-silicon materials for high-performance anodes.
Five typical metal cations (i.e. Na+, K+, Ca2+, Mg2+ and Al3+) were selected as representatives to study the influence of metal cations on the dissolution and transformation of biotite. This work focussed on the mineralogical features of transformation products and phase transformation mechanisms by utilising modern spectroscopic methods and micro-beam characterisation techniques. In comparison with a control system, K+ inhibited the dissolution and transformation of biotite, leading to the generation of amorphous iron hydroxides on the biotite surface. Na+, Mg2+ and Ca2+ promoted the dissolution of biotite but inhibited its transformation into kaolinite, with the Na system producing sodium-bearing biotite, vermiculite, hematite and a small amount of kaolinite, and the Mg and Ca systems producing mainly vermiculite, chlorite and hematite. Al3+ notably accelerated the dissolution and transformation of biotite, resulting in well-crystallised kaolinite and hematite. Furthermore, metal cations changed the formation mechanism of kaolinite by altering the dissolution rate of biotite. Within the blank system, biotite dissolved slowly, with elements (i.e. Al and Si) accumulating on the biotite surface and growing epitaxially into kaolinite; whereas in the Al system, the rapid dissolution of biotite provided a large amount of Si, which combined with Al in the solution, forming kaolinite via a dissolution–recrystallisation process. In addition, the exchange reactions of metal-cation–K+ and the competitive adsorption of metal-cation–proton simultaneously constrained the dissolution process of biotite. This work offers a theoretical basis for an in-depth comprehension of the factors influencing biotite weathering and new insights into the evolution of clay minerals in terrestrial surface environments.
The influence of the SNP rs174575 (C/G) within the fatty acid desaturase 2 gene on the levels of long-chain PUFA was determined through statistical meta-analysis. Six databases were searched to retrieve the relevant literature. Original data were analysed using Stata 17·0, encompassing summary statistics, tests for heterogeneity, assessment of publication bias, subgroup analysis and sensitivity analysis. A total of ten studies were identified and grouped into twelve trials. Our results showed that individuals who carried the minor G allele of rs174575 had significantly higher dihomo-γ-linolenic acid levels (P = 0·005) and lower arachidonic acid levels (P = 0·033) than individuals who were homozygous for the major allele. The subgroup analysis revealed that the G-allele carriers of rs174575 were significantly positively correlated with linoleic acid (P = 0·002) and dihomo-γ-linolenic acid (P < 0·001) and negatively correlated with arachidonic acid (P = 0·004) in the European populations group. This particular SNP showed a potential association with higher concentrations of dihomo-γ-linolenic acid (P = 0·050) and lower concentrations of arachidonic acid (P = 0·030) within the breast milk group. This meta-analysis has been registered in the PROSPERO database (ID: CRD42023470562).
The AIMTB rapid test assay is an emerging test, which adopted a fluorescence immunochromatographic assay to measure interferon-γ (IFN-γ) production following stimulation of effector memory T cells in whole blood by mycobacterial proteins. The aim of this article was to explore the ability of AIMTB rapid test assay in detecting Mycobacterium tuberculosis (MTB) infection compared with the widely applied QuantiFERON-TB Gold Plus (QFT-Plus) test among rural doctors in China. In total, 511 participants were included in the survey. The concordance between the QFT-Plus test and the AIMTB rapid test assay was 94.47% with a Cohen’s kappa coefficient (κ) of 0.84 (95% CI, 0.79–0.90). Improved concordance between the two tests was observed in males and in participants with 26 or more years of service as rural doctors. The quantitative values of the QFT-Plus test was higher in individuals with a result of QFT-Plus-/AIMTB+ as compared to those with a result of QFT-Plus-/AIMTB- (p < 0.001). Overall, our study found that there was an excellent consistency between the AIMTB rapid test assay and the QFT-Plus test in a Chinese population. As the AIMTB rapid test assay is fast and easy to operate, it has the potential to improve latent tuberculosis infection testing and treatment at the community level in resource-limited settings.