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The association between milk consumption and metabolic syndrome remains inconclusive, and the data from Chinese populations are scarce. We conducted a cross-sectional study to investigate the association between milk consumption and metabolic syndrome and its components among the residents of Suzhou Industrial Park, Suzhou, China. A total of 5149 participants were included in the final analysis. A logistic regression model was applied to estimate the odds ratios (OR) and 95% confidence intervals (CIs) for the prevalence of metabolic syndrome and its components according to milk consumption. In addition, the results of our study were further meta-analyzed with other published observational studies to quantify the association between the highest versus lowest categories of milk consumption and metabolic syndrome and its components. There was no significant difference in the odds of having metabolic syndrome between milk consumers and non-milk consumers (OR 0.86, 95% CI 0.73, 1.01). However, milk consumers had lower odds of having elevated waist circumference (OR 0.78, 95% CI 0.67, 0.92), elevated triglyceride (OR 0.83, 95% CI 0.70, 0.99), and elevated blood pressure (OR 0.85, 95% CI 0.73, 0.99). When the results were pooled together with other published studies, higher milk consumption was inversely associated with the risk of metabolic syndrome (relative risk 0.80, 95% CI 0.72, 0.88) and its components (except elevated fasting blood glucose); however, these results should be treated with caution as high heterogeneity observed. In summary, the currently available evidence from observational studies suggests that higher milk consumption may be inversely associated with metabolic syndrome.
Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program.
In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC.
The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal.
The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
Fluctuation of the received signal strength (RSS) is the key performance-limiting factor for Wi-Fi indoor positioning schemes. In this study, the Manhattan distance was used in the weighted K-nearest neighbour (WKNN) algorithm to improve positioning accuracy. Reference point (RP) intervals were optimised to reduce the complexity of the system. Specifically, two new positioning schemes are proposed in this paper. Scheme 1 uses the cellular network to refine the fingerprint database, while Scheme 2 uses the cellular network positioning to locate the node a priori, then uses the Wi-Fi network to further improve accuracy. The experimental results showed that the average positioning error of Scheme 1 was 1·60 m, a reduction of 12% compared with the existing Wi-Fi fingerprinting schemes. In Scheme 2, when double cellular networks were used, RP usage was reduced by 64% and the calculating time was 0·24 s, a reduction of up to 69·5% compared with the Manhattan-WKNN algorithm. These proposed schemes are suitable for high accuracy and real-time positioning situations, respectively.
Synaptotagmin 1 (Syt1) is an abundant and important presynaptic vesicle protein that binds Ca2+ for the regulation of synaptic vesicle exocytosis. Our previous study reported its localization and function on spindle assembly in mouse oocyte meiotic maturation. The present study was designed to investigate the function of Syt1 during mouse oocyte activation and subsequent cortical granule exocytosis (CGE) using confocal microscopy, morpholinol-based knockdown and time-lapse live cell imaging. By employing live cell imaging, we first studied the dynamic process of CGE and calculated the time interval between [Ca2+]i rise and CGE after oocyte activation. We further showed that Syt1 was co-localized to cortical granules (CGs) at the oocyte cortex. After oocyte activation with SrCl2, the Syt1 distribution pattern was altered significantly, similar to the changes seen for the CGs. Knockdown of Syt1 inhibited [Ca2+]i oscillations, disrupted the F-actin distribution pattern and delayed the time of cortical reaction. In summary, as a synaptic vesicle protein and calcium sensor for exocytosis, Syt1 acts as an essential regulator in mouse oocyte activation events including the generation of Ca2+ signals and CGE.
Rational construction of Z-scheme photocatalysts and exploration of the Z-scheme charge transfer mechanism have drawn much attention in the field of CO2 reduction because of its great potential to alleviate energy crisis and environmental problems. In this study, a series of Z-scheme CdS/BiOI composites were constructed by depositing CdS nanoparticles on the surface of BiOI nanosheets. The synthesized materials were characterized comprehensively, and their photoreduction CO2 activities were evaluated. The results show that the composites exhibit higher photoreduction CO2 activity under visible light irradiation (λ > 400 nm) than pure CdS and BiOI. The yields of CO and CH4 for the optimal composite after 3 h irradiation are 3.32 and 0.54 μmol/g, respectively. The improved photocatalytic activity is attributed to Z-scheme transfer mode of the photogenerated charges in the composites. The mechanism of CO2 reduction is proposed and verified experimentally.
When the average intermolecular distance is comparable to the size of gas molecules, the Boltzmann equation, based on the dilute gas assumption, becomes invalid. The Enskog equation was developed to account for this finite size effect that makes the collision non-local and increases the collision frequency. However, it is time-consuming to solve the Enskog equation due to its complicated structure of collision operator and high dimensionality. In this work, on the basis of the Shakhov model, a gas kinetic model is proposed to simplify the Enskog equation for non-ideal monatomic dense gases. The accuracy of the proposed Shakhov–Enskog model is assessed by comparing its solutions of the normal shock wave structures with the results of the Enskog equation obtained by the fast spectral method. It is shown that the Shakhov–Enskog model is able to describe non-equilibrium flow of dense gases, when the maximum local mean free path of gas molecules is still greater than the size of a molecular diameter. The accuracy and efficiency of the present model enable simulations of non-equilibrium flow of dense gases for practical applications.
The global market requirement of ultra-fine iron powder (UFIP), with a range size of 0.1–1 μm, is more than 20,000 tons per annum. However, no low-cost nontoxic synthesis route of UFIP is known. In this study, we used the low-cost, rapid, and scalable flame aerosol synthesis (FAS) method to synthesize iron oxide nanoparticles with different size and morphology. Combining with a postreduction heat treatment process, a feasible synthesis route of UFIP which meets the commercial production criteria has been developed. By optimizing the precursor concentration and postreduction heat treatment parameters, the final particle size of UFIP can be controlled. The evolution of the microstructure, phase formation, and magnetic properties during the postreduction heat treatment are systematically investigated, and a feasible reaction model has been established. This work provides an important starting point for the facile commercial synthesis of UFIP and can be readily expanded to other pure metals.
The microbiota–gut–brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients.
We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD.
The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890.
The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.
Malnutrition and acute kidney injury (AKI) are common complications in hospitalised patients, and both increase mortality; however, the relationship between them is unknown. This is a retrospective propensity score matching study enrolling 46 549 inpatients, aimed to investigate the association between Nutritional Risk Screening 2002 (NRS-2002) and AKI and to assess the ability of NRS-2002 and AKI in predicting prognosis. In total, 37 190 (80 %) and 9359 (20 %) patients had NRS-2002 scores <3 and ≥3, respectively. Patients with NRS-2002 scores ≥3 had longer lengths of stay (12·6 (sd 7·8) v. 10·4 (sd 6·2) d, P < 0·05), higher mortality rates (9·6 v. 2·5 %, P < 0·05) and higher incidence of AKI (28 v. 16 %, P < 0·05) than patients with normal nutritional status. The NRS-2002 showed a strong association with AKI, that is, the risk of AKI changed in parallel with the score of the NRS-2002. In short- and long-term survival, patients with a lower NRS-2002 score or who did not have AKI achieved a significantly lower risk of mortality than those with a high NRS-2002 score or AKI. Univariate Cox regression analyses indicated that both the NRS-2002 and AKI were strongly related to long-term survival (AUC 0·79 and 0·71) and that the combination of the two showed better accuracy (AUC 0·80) than the individual variables. In conclusion, malnutrition can increase the risk of AKI and both AKI and malnutrition can worsen the prognosis that the undernourished patients who develop AKI yield far worse prognosis than patients with normal nutritional status.
Findings of epidemiological studies regarding the association between carrot consumption and lung cancer risk remain inconsistent. The present study aimed to summarise the current epidemiological evidence concerning carrot intake and lung cancer risk with a meta-analysis. We conducted a meta-analysis of case–control and prospective cohort studies, and searched PubMed and Embase databases from their inception to April 2018 without restriction by language. We also reviewed reference lists from included articles. Prospective cohort or case–control studies reporting OR or relative risk with the corresponding 95 % CI of the risk lung cancer for the highest compared with the lowest category of carrot intake. A total of eighteen eligible studies (seventeen case–control studies and one prospective cohort study) were included, involving 202 969 individuals and 5517 patients with lung cancer. The pooled OR of eighteen studies for lung cancer was 0·58 (95 % CI 0·45, 0·74) by comparing the highest category with the lowest category of carrot consumption. Based on subgroup analyses for the types of lung cancer, we pooled that squamous cell carcinoma (OR 0·52, 95 % CI 0·19, 1·45), small-cell carcinoma (OR 0·43, 95 % CI 0·12, 1·59), adenocarcinoma (OR 0·34, 95 % CI 0·15, 0·79), large-cell carcinoma (OR 0·40, 95 % CI 0·10, 1·57), squamous and small-cell carcinoma (OR 0·85, 95 % CI 0·45, 1·62), adenocarcinoma and large-cell carcinoma (OR 0·20, 95 % CI 0·02, 1·70) and mixed types (OR 0·61, 95 % CI 0·46, 0·81). Exclusion of any single study did not materially alter the pooled OR. Integrated epidemiological evidence from observational studies supported the hypothesis that carrot consumption may decrease the risk of lung cancer, especially for adenocarcinoma.
To explore whether and how group cognitive-behavioural therapy (GCBT) plus medication differs from medication alone for the treatment of generalised anxiety disorder (GAD).
Hundred and seventy patients were randomly assigned to the GCBT plus duloxetine (n=89) or duloxetine group (n=81). The primary outcomes were Hamilton Anxiety Scale (HAMA) response and remission rates. The explorative secondary measures included score reductions from baseline in the HAMA total, psychic, and somatic anxiety subscales (HAMA-PA, HAMA-SA), the Hamilton Depression Scale, the Severity Subscale of Clinical Global Impression Scale, Global Assessment of Functioning, and the 12-item Short-Form Health Survey. Assessments were conducted at baseline, 4-week, 8-week, and 3-month follow-up.
At 4 weeks, HAMA response (GCBT group 57.0% vs. control group 24.4%, p=0.000, Cohen’s d=0.90) and remission rates (GCBT group 21.5% vs. control group 6.2%, p=0.004; d=0.51), and most secondary outcomes (all p<0.05, d=0.36−0.77) showed that the combined therapy was superior. At 8 weeks, all the primary and secondary significant differences found at 4 weeks were maintained with smaller effect sizes (p<0.05, d=0.32−0.48). At 3-month follow-up, the combined therapy was only significantly superior in the HAMA total (p<0.045, d=0.43) and HAMA-PA score reductions (p<0.001, d=0.77). Logistic regression showed superiority of the combined therapy for HAMA response rates [odds ratio (OR)=2.12, 95% confidence interval (CI) 1.02−4.42, p=0.04] and remission rates (OR=2.80, 95% CI 1.27−6.16, p=0.01).
Compared with duloxetine alone, GCBT plus duloxetine showed significant treatment response for GAD over a shorter period of time, particularly for psychic anxiety symptoms, which may suggest that GCBT was effective in changing cognitive style.
Few of the previous studies of clinical high risk of psychosis (CHR) have explored whether outcomes other than conversion, such as poor functioning or treatment responses, are better predicted when using risk calculators. To answer this question, we compared the predictive accuracy between the outcome of conversion and poor functioning by using the NAPLS-2 risk calculator.
Three hundred CHR individuals were identified using the Chinese version of the Structured Interview for Prodromal Symptoms. Of these, 228 (76.0%) completed neurocognitive assessments at baseline and 199 (66.3%) had at least a 1-year follow-up assessment. The latter group was used in the NAPLS-2 risk calculator.
We divided the sample into two broad categories based on different outcome definitions, conversion (n = 46) v. non-conversion (n = 153) or recovery (n = 138) v. poor functioning (n = 61). Interestingly, the NAPLS-2 risk calculator showed moderate discrimination of subsequent conversion to psychosis in this sample with an area under the receiver operating characteristic curve (AUC) of 0.631 (p = 0.007). However, for discriminating poor functioning, the AUC of the model increased to 0.754 (p < 0.001).
Our results suggest that the current risk calculator was a better fit for predicting a poor functional outcome and treatment response than it was in the prediction of conversion to psychosis.
Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.
The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.
We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.
Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.
Exoskeleton robots have been widely used in many fields at present. When wearing the exoskeleton to operate, the wearer may be unconscious of the position of exoskeleton or affected by the surrounding environment, causing collision between two arms of exoskeleton or between arms and environment. The collision may result in the exoskeleton destroyed or even the wearer injured. This paper proposes a hierarchical safety control strategy for exoskeleton robots based on maximum correntropy Kalman filter and bounding box to ensure safe operation. Accurate joint angle prediction can be obtained by filtering out non-Gaussian impulsive noise using maximum correntropy criterion as evaluation criterion. Relative position relationship of the arms can be derived based on bounding box to realize hierarchical safe control. Enough experiments have been carried out, and the results validated the feasibility of the proposed method.
Major depressive disorder (MDD) is highly heterogeneous and can be classified as treatment-resistant depression (TRD) or antidepressant-responsive depression (non-TRD) based on patients' responses to antidepressant treatment. Methods for distinguishing between TRD and non-TRD are critical clinical concerns. Deficits of cortical inhibition (CI) have been reported to play an influential role in the pathophysiology of MDD. Whether TRD patients' CI is more impaired than that of non-TRD patients remains unclear.
Paired-pulse transcranial magnetic stimulation (ppTMS) was used to measure cortical inhibitory function including GABAA- and GABAB-receptor-related CI and cortical excitatory function including glutamate-receptor-related intracortical facilitation (ICF). We recruited 36 healthy controls (HC) and 36 patients with MDD (non-TRD, n = 16; TRD, n = 20). All participants received evaluations for depression severity and ppTMS examinations. Non-TRD patients received an additional ppTMS examination after 3 months of treatment with the SSRI escitalopram.
Patients with TRD exhibited reduced short-interval intracortical inhibition (SICI) and long-interval intracortical inhibition (LICI), as shown by abnormally higher estimates, than those with non-TRD or HC (F = 11.030, p < 0.001; F = 10.309, p < 0.001, respectively). After an adequate trial of escitalopram treatment, the LICI of non-TRD reduced significantly (t = − 3.628, p < 0.001), whereas the ICF remained lower than that of HC and showed no difference from pretreatment non-TRD.
TRD was characterized by relatively reduced CI, including both GABAA- and GABAB-receptor-mediated neurons while non-TRD preserved partial CI. In non-TRD, SSRIs may mainly modulate GABAB-receptor-related LICI. Our findings revealed distinguishable features of CI in antidepressant-resistant and responsive major depression.
Isolated gametes can be used to investigate fertilization mechanisms, and probe distant hybridization between different species. Pollen grains of wheat and Setaria viridis are tricellular, containing sperm cells at anthesis. Sperm from these plants were isolated by breaking open pollen grains in a osmotic solution. Wheat ovules were digested in an enzyme solution for 20 min, and then transferred to an isolation solution without enzymes to separate egg cells from ovules. The fusion of wheat egg cells with wheat and S. viridis sperm was conducted using an electro-fusion apparatus. Under suitable osmotic pressure (10% mannitol), calcium concentration of 0.001% (CaCl2·2H2O), and a 30–35 V alternating electric field for 15 s, egg cells and sperm adhered to each other and became arranged in a line. Electroporation of the plasma membrane of egg cells and sperm using a 300–500 V direct-current electric field (45 µs amplitude pulse) caused them to fuse.
Paediatric Mycoplasma pneumoniae pneumonia (MPP) is a major cause of community-acquired pneumonia in China. Data on epidemiology of paediatric MPP from China are little known. This study retrospectively collected data from June 2006 to June 2016 in Beijing Children's Hospital, Capital Medical University of North China and aims to explore the epidemiological features of paediatric MPP and severe MPP (SMPP) in North China during the past 10 years. A total of 27 498 paediatric patients with pneumonia were enrolled. Among them, 37.5% of paediatric patients had MPP. In this area, an epidemic took place every 2–3 years at the peak, and the positive rate of MPP increased during these peak years over time. The peak age of MPP was between the ages of 6 and 10 years, accounting for 75.2%, significantly more compared with other age groups (χ2 = 1384.1, P < 0.0001). The epidemics peaked in September, October and November (χ2 = 904.9, P < 0.0001). Additionally, 13.0% of MPP paediatric patients were SMPP, but over time, the rate of SMPP increased, reaching 42.6% in 2016. The mean age of paediatric patients with SMPP (6.7 ± 3.0 years old) was younger than that of patients with non-SMPP (7.4 ± 3.2 years old) (t = 3.60, P = 0.0001). The prevalence of MPP and SMPP is common in China, especially in children from 6 to 10 years old. Paediatric patients with SMPP tend to be younger than those with non-SMPP. MPP outbreaks occur every 2–3 years in North China. September, October and November are the peak months, unlike in South China. Understanding the epidemiological characteristics of paediatric MPP can contribute to timely treatment and diagnosis, and may improve the prognosis of children with SMPP.