The COVID-19 pandemic has had a profound impact on the mental health of healthcare workers (HCWs). We aimed to identify the factors associated with depression among HCWs during the pandemic. We conducted literature search using eight electronic databases up to July 27 2022. Observational studies with more than 200 participants investigating correlates of depression in HCWs after COVID-19 outbreak were included. We used fixed- and random-effects models to pool odds ratios (ORs) across studies, and Cochran's chi-squared test and I2 statistics to assess study heterogeneity. Publication bias was evaluated by funnel plots. Thirty-five studies involving 44,362 HCWs met the inclusion criteria. Female (OR=1.50, 95% CI [1.23,1.84]), single (OR=1.36, 95% CI [1.21,1.54]), nurse (OR=1.69, 95% CI [1.28,2.25]), history of mental diseases (OR=2.53, 95% CI [1.78,3.58]), frontline (OR=1.79, 95% CI [1.38,2.32]), health anxiety due to COVID-19 (OR=1.88, 95% CI [1.29,2.76]), working in isolation wards (OR=1.98, 95% CI [1.38,2.84]), and insufficient personal protective equipment (OR=1.49, 95% CI [1.33,1.67]) were associated with increased risk of depression. Instead, HCWs with a positive professional prospect (OR=0.34, 95% CI [0.24,0.49]) were less likely to be depressed. This meta-analysis provides up-to-date evidence on the factors linked to depression among HCWs during the COVID-19 pandemic. Given the persistent threats posed by COVID-19, early screening is crucial for the intervention and prevention of depression in HCWs.

The benefits of branched-chain amino acid (BCAA) administration after hepatic intervention in patients with liver diseases remain unclear. We conducted a systematic review and meta-analysis to evaluate the effects of BCAA on patients undergoing hepatectomy, trans-arterial embolisation and radiofrequency ablation. Relevant randomised controlled trials (RCT) were obtained from PubMed, EMBASE and Cochrane Library databases. A meta-analysis was performed to calculate the pooled effect size by using random-effects models. The primary outcomes were survival and tumour recurrence. The secondary outcomes were hospital stay, nutrition status, biochemistry profile, complication rate of liver treatment and adverse effect of BCAA supplementation. In total, eleven RCT involving 750 patients were included. Our meta-analysis showed no significant difference in the rates of tumour recurrence and overall survival between the BCAA and control groups. However, the pooled estimate showed that BCAA supplementation in patients undergoing hepatic intervention significantly increased serum albumin (mean difference (MD): 0·11 g/dl, 95 % CI: 0·02, 0·20; 5 RCT) at 6 months and cholinesterase level (MD: 50·00 U/L, 95 % CI: 21·08, 78·92; 1 RCT) at 12 months and reduced ascites incidence (risk ratio: 0·39, 95 % CI: 0·21, 0·71; 4 RCT) at 12 months compared with the control group. Additionally, BCAA administration significantly increased body weight at 6 months and 12 months and increased arm circumference at 12 months. In conclusion, BCAA supplementation significantly improved the liver function, reduced the incidence of ascites and increased body weight and arm circumference. Thus, BCAA supplementation may beneficial for selected patients undergoing liver intervention.

SARS-CoV-2 rapidly spreads among humans via social networks, with social mixing and network characteristics potentially facilitating transmission. However, limited data on topological structural features has hindered in-depth studies. Existing research is based on snapshot analyses, preventing temporal investigations of network changes. Comparing network characteristics over time offers additional insights into transmission dynamics. We examined confirmed COVID-19 patients from an eastern Chinese province, analyzing social mixing and network characteristics using transmission network topology before and after widespread interventions. Between the two time periods, the percentage of singleton networks increased from 38.9$ \% $ to 62.8$ \% $$ (p<0.001) $; the average shortest path length decreased from 1.53 to 1.14 $ (p<0.001) $; the average betweenness reduced from 0.65 to 0.11$ (p<0.001) $; the average cluster size dropped from 4.05 to 2.72 $ (p=0.004) $; and the out-degree had a slight but nonsignificant decline from 0.75 to 0.63 $ (p=0.099). $ Results show that nonpharmaceutical interventions effectively disrupted transmission networks, preventing further disease spread. Additionally, we found that the networks’ dynamic structure provided more information than solely examining infection curves after applying descriptive and agent-based modeling approaches. In summary, we investigated social mixing and network characteristics of COVID-19 patients during different pandemic stages, revealing transmission network heterogeneities.

Environment-induced epigenetics are involved in diapause regulation, but the molecular mechanism that epigenetically couples nutrient metabolism to diapause regulation remains unclear. In this study, we paid special attention to the significant differences in the level of N6-adenosine methylation (m6A) of dihydroxyacetone phosphate acyltransferase (DHAPAT) and phosphatidate phosphatase (PAP) genes in the lipid metabolism pathway of the bivoltine silkworm (Bombyx mori) strain Qiufeng developed from eggs incubated at a normal temperature (QFHT, diapause egg producer) compared to those from eggs incubated at a low temperature (QFLT, non-diapause egg producer). We knocked down DHAPAT in the pupal stage of the QFLT group, resulting in the non-diapause destined eggs becoming diapausing eggs. In the PAP knockdown group, the colour of the non-diapause destined eggs changed from light yellow to pink 3 days after oviposition, but they hatched as normal. Moreover, we validated that YTHDF3 binds to m6A-modified DHAPAT and PAP mRNAs to promote their stability and translation. These results suggest that RNA m6A methylation participates in the diapause regulation of silkworm by changing the expression levels of DHAPAT and PAP and reveal that m6A epigenetic modification can be combined with a lipid metabolism signal pathway to participate in the regulation of insect diapause traits, which provides a clearer image for exploring the physiological basis of insect diapause.

We examined the effect of an antimicrobial stewardship program (ASP), procalcitonin testing and rapid blood-culture identification on hospital mortality in a prospective quality improvement project in critically ill septic adults. Secondarily, we have reported antimicrobial guideline concordance, acceptance of ASP interventions, and antimicrobial and health-resource utilization.

A high-load counter-rotating compressor is optimised based on the method of coupling aerodynamic optimisation technology and computational fluid dynamics, and the flow structures in the passage are analysed and evaluated by vorticity dynamics diagnosis. The results show that the aerodynamic performance of optimised compressor are obviously improved at both design point and off-design point. By comparing the distribution characteristics of vorticity dynamics parameters on the blade surface before and after the optimisation, it is found that BVF (boundary vorticity flux) and circumferential vorticity can effectively capture high flow loss regions such as shock waves and secondary flow in the passage. In addition, the BEF (Boundary enstrophy flux) diagnosis method based on the theory of boundary enstrophy flux is developed, which expands the application scenario of the boundary vorticity dynamics diagnosis method. The change of vorticity dynamics parameters shows blade geometric parameters’ influence on the passage’s viscous flow field, which provides a theoretical basis for the aerodynamic optimisation design.

Menaquinone-7 (MK-7), a multipotent vitamin K2, possesses a wide range of biological activities, a precise curative effect and excellent safety. A simple and rapid LC-APCI-MS/MS method for the determination of MK-7 in human plasma with single liquid–liquid extraction (LLE) extraction and 4·5-min analysis time has been developed and validated. Four per cent bovine serum albumin (BSA) was used as surrogate matrix for standard curves and endogenous baseline subtraction. This method was reproducible and reliable and was used to analyse of MK-7 in human plasma. The endogenous circadian rhythm and bioavailability of MK-7 were investigated in two randomised single-dose, open, one-way clinical trials (Study I and Study II). A total of five healthy male subjects were enrolled in Study I and 12 healthy male subjects in Study II. Single-dose (1 mg) of MK-7 was given to each subject under fasting condition, and all eligible subjects were given a restricting VK2 diet for 4 d prior to drug administration and during the trial. The experiment results of Study I demonstrated that endogenous MK-7 has no circadian rhythm in individuals. Both studies showed MK-7 are absorbed with peak plasma concentrations at about 6 h after intake and has a very long half-life time.

My 5 moments (M5M) was used less frequently among cleaning staff members, suggesting that a poor compliance score in this group may not indicate deficient handwashing. This quasi-experimental study compared hand hygiene compliance (HHC), hand hygiene (HH) moments, and HH time distribution in the control group (no HH intervention; n = 21), case group 1 (normal M5M intervention; n = 26), case group 2 (extensive novel six moments (NSM) training; n = 24), and case group 3 (refined NSM training; n = 18). The intervention’s effect was evaluated after 3 months. The HHC gap among the four groups gradually increased in the second intervention month (control group, 31.43%; case group 1, 38.74%; case group 2, 40.19%; case group 3, 52.21%; p < 0.05). After the intervention period, the HHC of case groups 2 and 3 improved significantly from the baseline (23.85% vs. 59.22%, 27.41% vs. 83.62%, respectively; p < 0.05). ‘After transferring medical waste from the site’ had the highest HHC in case group 3, 90.72% (95% confidence interval, 0.1926–0.3967). HH peak hours were from 6 AM to 9 AM and 2 PM to 3 PM. The study showed that the implementation of an NSM practice can serve as an HHC monitoring indicator and direct relevant training interventions to improve HH among hospital cleaning staff.

Sleep apnea is one of the most common sleep disorders. The consequences of undiagnosed sleep apnea can be very serious, increasing the risk of high blood pressure, heart disease, stroke, and Alzheimer’s disease over a long period of time. However, many people are often unaware of their condition. The gold standard for diagnosing sleep apnea is nighttime polysomnography monitoring in a specialized sleep laboratory. However, these diagnoses are expensive and the number of beds is limited, and there is insufficient monitoring in terms of time dimension. Existing methods for automated detection use no more than three physiological signals, but all other signals are also associated with the patient’s sleep. In addition, the limited amount of medical real annotation data, especially abnormal samples, lead to weak model generalization capability. The gap between model generalization capability and medical field needs still exists. In this paper, we propose a method for integrating medical interpretation rules into a long short-term memory neural network based on self-attention with multichannel respiratory signals as input. We obtain attention weights through a token-level attention mechanism and then extract key rules of medical interpretation to assist the weights, improving model generalization and reducing the dependence on data volume. Compared with the best prediction performance of existing methods, the average improvements of our method in accuracy, precision, and f1-score are 3.26%, 7.03%, and 1.78%, respectively. The algorithm tested the performance of our model on the Sleep Heart Health Study data set and found that the model outperformed existing methods and could help physicians make decisions in their practices.

Post-acceleration of protons in helical coil targets driven by intense, ultrashort laser pulses can enhance ion energy by utilizing the transient current from the targets’ self-discharge. The acceleration length of protons can exceed a few millimeters, and the acceleration gradient is of the order of GeV/m. How to ensure the synchronization between the accelerating electric field and the protons is a crucial problem for efficient post-acceleration. In this paper, we study how the electric field mismatch induced by current dispersion affects the synchronous acceleration of protons. We propose a scheme using a two-stage helical coil to control the current dispersion. With optimized parameters, the energy gain of protons is increased by four times. Proton energy is expected to reach 45 MeV using a hundreds-of-terawatts laser, or more than 100 MeV using a petawatt laser, by controlling the current dispersion.

Customer preference modelling has been widely used to aid engineering design decisions on the selection and configuration of design attributes. Recently, network analysis approaches, such as the exponential random graph model (ERGM), have been increasingly used in this field. While the ERGM-based approach has the new capability of modelling the effects of interactions and interdependencies (e.g., social relationships among customers) on customers’ decisions via network structures (e.g., using triangles to model peer influence), existing research can only model customers’ consideration decisions, and it cannot predict individual customer’s choices, as what the traditional utility-based discrete choice models (DCMs) do. However, the ability to make choice predictions is essential to predicting market demand, which forms the basis of decision-based design (DBD). This paper fills this gap by developing a novel ERGM-based approach for choice prediction. This is the first time that a network-based model can explicitly compute the probability of an alternative being chosen from a choice set. Using a large-scale customer-revealed choice database, this research studies the customer preferences estimated from the ERGM-based choice models with and without network structures and evaluates their predictive performance of market demand, benchmarking the multinomial logit (MNL) model, a traditional DCM. The results show that the proposed ERGM-based choice modelling achieves higher accuracy in predicting both individual choice behaviours and market share ranking than the MNL model, which is mathematically equivalent to ERGM when no network structures are included. The insights obtained from this study further extend the DBD framework by allowing explicit modelling of interactions among entities (i.e., customers and products) using network representations.

The phase summation effect in sum-frequency mixing process is utilized to avoid a nonlinearity obstacle in the power scaling of single-frequency visible or ultraviolet lasers. Two single-frequency fundamental lasers are spectrally broadened by phase modulation to suppress stimulated Brillouin scattering in fiber amplifier and achieve higher power. After sum-frequency mixing in a nonlinear optical crystal, the upconverted laser returns to single frequency due to phase summation, when the phase modulations on two fundamental lasers have a similar amplitude but opposite sign. The method was experimentally proved in a Raman fiber amplifier-based laser system, which generated a power-scalable sideband-free single-frequency 590 nm laser. The proposal manifests the importance of phase operation in wave-mixing processes for precision laser technology.

Although a coaxial compound helicopter can takeoff without propeller in the normal condition, the distance should be as short as possible for obstacle avoidance when the vehicle operates in a confined area with heavy loads. Therefore, a suitable propeller control is required to improve the takeoff performance while the total power consumption is no more than the available power. The path is predicted by applying trajectory optimisation. Several varying takeoff parameters, including attitude, liftoff speed and obstacle height, are considered for optimum global performance. Three path indicators are proposed. Apart from typical distance and pilot workload, path sensitivity is quantified based on deviation from takeoff parameter variation. Results indicated that low propeller thrust at hover and moderate allocation on the propeller through flight is recommended. The aircraft achieves significantly improved takeoff performance compared to flight with pure rotors while maintaining the maximum takeoff weight. The distance is shortened by 12.6%, and the longitudinal pilot workload is alleviated by 9.8% and 7.3% from mean and maximum power frequency aspects. Besides, the path is less sensitive to takeoff parameter variations, such as speed, altitude and height.

Coastal eutrophication and hypoxia remain a persistent environmental crisis despite the great efforts to reduce nutrient loading and mitigate associated environmental damages. Symptoms of this crisis have appeared to spread rapidly, reaching developing countries in Asia with emergences in Southern America and Africa. The pace of changes and the underlying drivers remain not so clear. To address the gap, we review the up-to-date status and mechanisms of eutrophication and hypoxia in global coastal oceans, upon which we examine the trajectories of changes over the 40 years or longer in six model coastal systems with varying socio-economic development statuses and different levels and histories of eutrophication. Although these coastal systems share common features of eutrophication, site-specific characteristics are also substantial, depending on the regional environmental setting and level of social-economic development along with policy implementation and management. Nevertheless, ecosystem recovery generally needs greater reduction in pressures compared to that initiated degradation and becomes less feasible to achieve past norms with a longer time anthropogenic pressures on the ecosystems. While the qualitative causality between drivers and consequences is well established, quantitative attribution of these drivers to eutrophication and hypoxia remains difficult especially when we consider the social economic drivers because the changes in coastal ecosystems are subject to multiple influences and the cause–effect relationship is often non-linear. Such relationships are further complicated by climate changes that have been accelerating over the past few decades. The knowledge gaps that limit our quantitative and mechanistic understanding of the human-coastal ocean nexus are identified, which is essential for science-based policy making. Recognizing lessons from past management practices, we advocate for a better, more efficient indexing system of coastal eutrophication and an advanced regional earth system modeling framework with optimal modules of human dimensions to facilitate the development and evaluation of effective policy and restoration actions.