Accurately predicting neurosyphilis prior to a lumbar puncture (LP) is critical for the prompt management of neurosyphilis. However, a valid and reliable model for this purpose is still lacking. This study aimed to develop a nomogram for the accurate identification of neurosyphilis in patients with syphilis. The training cohort included 9,504 syphilis patients who underwent initial neurosyphilis evaluation between 2009 and 2020, while the validation cohort comprised 526 patients whose data were prospectively collected from January 2021 to September 2021. Neurosyphilis was observed in 35.8% (3,400/9,504) of the training cohort and 37.6% (198/526) of the validation cohort. The nomogram incorporated factors such as age, male gender, neurological and psychiatric symptoms, serum RPR, a mucous plaque of the larynx and nose, a history of other STD infections, and co-diabetes. The model exhibited good performance with concordance indexes of 0.84 (95% CI, 0.83–0.85) and 0.82 (95% CI, 0.78–0.86) in the training and validation cohorts, respectively, along with well-fitted calibration curves. This study developed a precise nomogram to predict neurosyphilis risk in syphilis patients, with potential implications for early detection prior to an LP.

An online pattern recognition method of lower limb movements is proposed based on the personalized surface electromyography (sEMG) signals, and the corresponding experimental researches are performed in the rehabilitation training. Further, a wireless wearable acquisition instrument is used. Based on this instrument, a host computer for the personal online recognition and real-time control of rehabilitation training is developed. Three time-domain features and two features in the nonlinear dynamics are selected as the joint set of the characteristic values for the sEMG signals. Then a particle swarm optimization (PSO) algorithm is used to optimize the feature channels, and a k-nearest neighbor (KNN) algorithm and the extreme learning machine (ELM) algorithm are combined to classify and recognize individual sample data. Based on the multi-pose lower limb rehabilitation robot, the real-time motion recognition and the corresponding rehabilitation training are carried out by using the online personalized classifier. The experimental results of eight subjects indicate that it takes only 6 min to build an online personalized classifier for the four types of the lower limb movements. The recognition between switches of different rehabilitation training movements is timely and accurate, with an average recognition accuracy of more than 95%. These results demonstrate that this system has a strong practicability.

This paper proposes a low-divergence method to generate inhomogeneous and anisotropic turbulence. Based on the idea of correlation reconstruction, the proposed method uses the Cholesky decomposition matrix to re-establish turbulence correlation functions. This is in contrast with the time-consuming procedure used in conventional methods to solve eigenvalues and eigenvectors in each location required by coordinate transformation, thereby reducing the computational complexity and improving the efficiency of synthetic turbulence generation. The proposed method is based on the classical spectrum-based method that is widely used to generate homogeneous and isotropic turbulence. By adjusting the generation strategy of specific random vectors, inhomogeneous and anisotropic turbulence with a relatively low divergence level can be obtained in practice, with almost no additional computational burden. Two versions of the proposed method are presented: the inverter and shifter versions. Both the versions are highly efficient, easy to implement, and compatible with high-performance computing. This method is also suitable for providing high-quality initial or boundary conditions for scale-resolving turbulence simulations with large grid numbers (such as direct numerical simulations or large eddy simulations); it can be rapidly implemented using various open-source computational fluid dynamics codes or common commercial software.

Post-event rumination (PER) has been seen as a key element in the persistence of social anxiety (disorder). Studies on PER-targeted intervention, e.g., cognitive restructuring (CR), has, however, received little attention in adults, not yet in youth. In addition, previous research showed that, compared to interaction, participants reported higher levels of PER after speech task. The main aim of the present study was to investigate the effect of CR targeting PER among socially anxious (Chinese) adolescents and also to compare the intervention effect between speech and interaction situations. The present study recruited a sample of 73 high socially anxious adolescents aged 12–16 years and then randomly assigned them into speech (n = 37) or interaction (n = 36) group, without control group. PER and social anxiety (SA) were measured before and after CR. Analysis of Covariance (ANCOVA) results showed that adolescents’ PER and SA symptoms were significantly improved with intervention with moderate to high effect size. Furthermore, the decrease in PER could significantly predict the improvement of SA. However, the intervention effect showed no difference between groups. Although no control group was included, one-session CR still showed its potential to improve participants’ PER and SA. Limitations and future directions were discussed.

The development of high-brightness X-ray free electron lasers (XFELs), such as hard X-ray self-seeding free electron lasers and XFEL oscillators (XFELOs), brings a severe challenge to the crystal monochromator due to a strong non-uniform thermal load. The distortion caused by spatial temperature gradients can severely affect the optical performance of crystals. Therefore, this paper presents a model to estimate the performance of non-uniform thermally distorted crystals. The model not only takes into account thermal strain, slope error and incident angle deviation, but also considers temperature-dependent factors such as the Debye–Waller factor and electric susceptibility. Our investigation indicates that the Debye–Waller factor reduces the height and bandwidth of rocking curves, and the impact of the electric susceptibility is tiny. The proposed model can describe the distortion of the reflectivity and transmissivity curves of non-uniform thermally loaded crystals and can be applied in the design of crystal monochromators, crystal splitters, crystal compressors and XFELOs.

This paper presents a gait optimization method to generate the locomotion pattern for biped and discuss its stability. The main contribution of this paper is a newly proposed energy-based stability criterion, which permits the dynamic stable walking and could be straight-forwardly generalized to different locomotion scenarios and biped robots. The gait optimization problem is formulated subject to the constraints of the whole-body dynamics and kinematics. The constraints are established based on the modelling of bipedal hybrid dynamical systems. Following the whole-body modelling, the system energy is acquired and then applied to create the stability criterion. The optimization objective is also established on the system energy. The gait optimization is solved by being converted to a large-scale programming problem, where the transcription accuracy is improved via the spectral method. To further reduce the dimensionality of the large-scale problem, the whole-body dynamics is re-constructed. The generalization of the optimized gait is improved by the design of feedback control. The optimization examples demonstrate that the stability criterion naturally leads to a cyclic biped locomotion, though the periodicity was not previously imposed. Two simulation cases, level ground walking and slope walking, verify the generalization of the stability criterion and feedback control. The stability analyses are carried out by investigating the motions of centre of gravity and centre of pressure. It is revealed that if the tracked speed is above 0.3 m/s or the biped accelerates/climbs the slope, the stability criterion accomplishes the dynamic stable walking, where zero moment point criterion is not strictly complied.

The association between time-restricted eating (TRE) and the risk of non-alcoholic fatty liver disease (NAFLD) is less studied. Moreover, whether the association is independent of physical exercise or diet quality or quantity is uncertain. In this nationwide cross-sectional study of 3813 participants, the timing of food intakes was recorded by 24-h recalls; NAFLD was defined through vibration-controlled transient elastography in the absence of other causes of chronic liver disease. OR and 95 % CI were estimated using logistic regression. Participants with daily eating window of ≤ 8 h had lower odds of NAFLD (OR = 0·70, 95 % CI: 0·52, 0·93), compared with those with ≥ 10 h window. Early (05.00–15.00) and late TRE (11.00–21.00) showed inverse associations with NAFLD prevalence without statistical heterogeneity (Pheterogeneity = 0·649) with OR of 0·73 (95 % CI: 0·36, 1·47) and 0·61 (95 % CI: 0·44, 0·84), respectively. Such inverse association seemed stronger in participants with lower energy intake (OR = 0·58, 95 % CI: 0·38, 0·89, Pinteraction = 0·020). There are no statistical differences in the TRE-NAFLD associations according to physical activity (Pinteraction = 0·390) or diet quality (Pinteraction = 0·110). TRE might be associated with lower likelihood of NAFLD. Such inverse association is independent of physical activity and diet quality and appears stronger in individuals consuming lower energy. Given the potential misclassification of TRE based on one- or two-day recall in the analysis, epidemiological studies with validated methods for measuring the habitual timing of dietary intake are warranted.

Whether starchy and non-starchy vegetables have distinct impacts on health remains unknown. We prospectively investigated the intake of starchy and non-starchy vegetables in relation to mortality risk in a nationwide cohort. Diet was assessed using 24-h dietary recalls. Deaths were identified via the record linkage to the National Death Index. Hazard ratios (HR) and 95 % CI were calculated using Cox regression. During a median follow-up of 7·8 years, 4904 deaths were documented among 40 074 participants aged 18 years or older. Compared to those with no consumption, participants with daily consumption of ≥ 1 serving of non-starchy vegetables had a lower risk of mortality (HR = 0·76, 95 % CI 0·66, 0·88, Ptrend = 0·001). Dark-green and deep-yellow vegetables (HR = 0·79, 95 % CI 0·63, 0·99, Ptrend = 0·023) and other non-starchy vegetables (HR = 0·80, 95 % CI 0·70, 0·92, Ptrend = 0·004) showed similar results. Total starchy vegetable intake exhibited a marginally weak inverse association with mortality risk (HR = 0·89, 95 % CI 0·80, 1·00, Ptrend = 0·048), while potatoes showed a null association (HR = 0·93, 95 % CI 0·82, 1·06, Ptrend = 0·186). Restricted cubic spline analysis suggested a linear dose–response relationship between vegetable intake and death risk, with a plateau at over 300 and 200 g/d for total and non-starchy vegetables, respectively. Compared with starchy vegetables, non-starchy vegetables might be more beneficial to health, although both showed a protective association with mortality risk. The risk reduction in mortality plateaued at approximately 200 g/d for non-starchy vegetables and 300 g/d for total vegetables.

A droplet impinging on a superhydrophobic substrate in an electric field is an important process in droplet manipulation and electrostatic spraying. Here, the entire impinging dynamic of the droplet in a vertical electric field is studied by a visualization experiment and numerical simulation with OpenFOAM. We investigate the effect of an electrostatic force on droplet impact in depth, where four ejection modes and three rebound modes are found experimentally. In particular, the filamentous ejecting phenomenon occurs after a droplet impinging on a superhydrophobic substrate is first discovered. In the numerical simulation, the strong coupling between the dynamic distribution of the interface electric charge and the evolution of the droplet profile can lead to different ejection modes, and the different ejection behaviours are caused by the combined effects of electrostatic pressure, capillary pressure, dynamic pressure and static pressure on the droplet apex. A charge scaling law for the ejection droplets is proposed. Furthermore, a set of theoretical models is established, which can successfully predict the threshold electric capillary number for different droplet ejection modes. The results reveal some important characteristics for a droplet impinging on a superhydrophobic surface in an electric field, which could facilitate the design of electrically operated droplet equipment and guide the safe and stable operation of the device.

Although immune checkpoint inhibitors (ICIs) have produced remarkable responses in non-small cell lung cancer (NSCLC) patients, receivers still have a relatively low response rate. Initial response assessment by conventional imaging and evaluation criteria is often unable to identify whether patients can achieve durable clinical benefit from ICIs. Overall, there are sparse effective biomarkers identified to screen NSCLC patients responding to this therapy. A lot of studies have reported that patients with specific gene mutations may benefit from or resist to immunotherapy. However, the single gene mutation may be not effective enough to predict the benefit from immunotherapy for patients. With the advancement in sequencing technology, further studies indicate that many mutations often co-occur and suggest a drastic transformation of tumour microenvironment phenotype. Moreover, co-mutation events have been reported to synergise to activate or suppress signalling pathways of anti-tumour immune response, which also indicates a potential target for combining intervention. Thus, the different mutation profile (especially co-mutation) of patients may be an important concern for predicting or promoting the efficacy of ICIs. However, there is a lack of comprehensive knowledge of this field until now. Therefore, in this study, we reviewed and elaborated the value of cancer mutation profile in predicting the efficacy of immunotherapy and analysed the underlying mechanisms, to provide an alternative way for screening dominant groups, and thereby, optimising individualised therapy for NSCLC patients.

Nutritional Risk Screening index is a standard tool to assess nutritional risk, but epidemiological data are scarce on controlling nutritional status (CONUT) as a prognostic marker in acute haemorrhagic stroke (AHS). We aimed to explore whether the CONUT may predict a 3-month functional outcome in AHS. In total, 349 Chinese patients with incident AHS were consecutively recruited, and their malnutrition risks were determined using a high CONUT score of ≥ 2. The cohort patients were divided into high-CONUT (≥ 2) and low-CONUT (< 2) groups, and primary outcomes were a poor functional prognosis defined as the modified Rankin Scale (mRS) score of ≥ 3 at post-discharge for 3 months. Odds ratios (OR) with 95 % confidence intervals (CI) for the poor functional prognosis at post-discharge were estimated by using a logistic analysis with additional adjustments for unbalanced variables between the high-CONUT and low-CONUT groups. A total of 328 patients (60·38 ± 12·83 years; 66·77 % male) completed the mRS assessment at post-discharge for 3 months, with 172 patients at malnutrition risk at admission and 104 patients with a poor prognosis. The levels of total cholesterol and total lymphocyte counts were significantly lower in high-CONUT patients than low-CONUT patients (P = 0·012 and < 0·001, respectively). At 3-month post discharge, there was a greater risk for the poor outcome in the high-CONUT compared with the low-CONUT patients at admission (OR: 2·32, 95 % CI: 1·28, 4·17). High-CONUT scores independently predict a 3-month poor prognosis in AHS, which helps to identify those who need additional nutritional managements.

Shifts in the maternal gut microbiota have been implicated in the development of gestational diabetes mellitus (GDM). Understanding the interaction between gut microbiota and host glucose metabolism will provide a new target of prediction and treatment. In this nested case-control study, we aimed to investigate the causal effects of gut microbiota from GDM patients on the glucose metabolism of germ-free (GF) mice. Stool and peripheral blood samples, as well as clinical information, were collected from 45 GDM patients and 45 healthy controls (matched by age and prepregnancy body mass index (BMI)) in the first and second trimester. Gut microbiota profiles were explored by next-generation sequencing of the 16S rRNA gene, and inflammatory factors in peripheral blood were analyzed by enzyme-linked immunosorbent assay. Fecal samples from GDM and non-GDM donors were transferred to GF mice. The gut microbiota of women with GDM showed reduced richness, specifically decreased Bacteroides and Akkermansia, as well as increased Faecalibacterium. The relative abundance of Akkermansia was negatively associated with blood glucose levels, and the relative abundance of Faecalibacterium was positively related to inflammatory factor concentrations. The transfer of fecal microbiota from GDM and non-GDM donors to GF mice resulted in different gut microbiota colonization patterns, and hyperglycemia was induced in mice that received GDM donor microbiota. These results suggested that the shifting pattern of gut microbiota in GDM patients contributed to disease pathogenesis.

Acute haemorrhagic conjunctivitis is a highly contagious eye disease, the prediction of acute haemorrhagic conjunctivitis is very important to prevent and grasp its development trend. We use the exponential smoothing model and the seasonal autoregressive integrated moving average (SARIMA) model to analyse and predict. The monthly incidence data from 2004 to 2017 were used to fit two models, the actual incidence of acute haemorrhagic conjunctivitis in 2018 was used to validate the model. Finally, the prediction effect of exponential smoothing is best, the mean square error and the mean absolute percentage error were 0.0152 and 0.1871, respectively. In addition, the incidence of acute haemorrhagic conjunctivitis in Chongqing had a seasonal trend characteristic, with the peak period from June to September each year.

The aim of the present study was to investigate the effects of dietary Zn level on growth performance, Zn bioaccumulation, antioxidant capacity and innate immunity in juvenile mud crabs (Scylla paramamosain). Six semi-purified diets were formulated to contain dietary Zn levels of 44·5, 56·9, 68·5, 97·3, 155·6 or 254·7 mg/kg. Dietary Zn level significantly influenced percentage weight gain (PWG), with the highest observed in crabs fed the diet containing 97·3 mg/kg Zn. Tissue Zn concentrations significantly increased as dietary Zn levels increased from 44·5 to 254·7 mg/kg. Retention of Zn in hepatopancreas increased with dietary Zn levels up to 68·5 mg/kg and then significantly decreased. Moreover, inadequate dietary Zn (44·5 and 56·9 mg/kg) reduced antioxidation markers including total superoxide dismutase (SOD) and Cu/Zn SOD activities and total antioxidant level. Crabs fed the diet with 44·5 mg/kg Zn also showed significantly lower expression of genes involved in antioxidant status, such as Cu/Zn SOD, glutathione peroxidase, catalase and thioredoxin than those fed diets containing 68·5 and 97·3 mg/kg Zn. The highest activities of phenoloxidase and alkaline phosphatase were recorded in crabs fed the diets containing 68·5 and 97·3 mg/kg Zn. Expression levels of prophenoloxidase and toll-like receptor 2 were higher in crabs fed the 97·3 mg/kg Zn diet compared with crabs fed the other diets. Based on PWG alone, the optimal dietary Zn level was estimated to be 82·9 mg/kg, with 68·5 to 97·3 mg/kg recommended for maintaining optimal Zn bioaccumulation, oxidation resistance and innate immune response of juvenile mud crabs.