The demand for separating and analysing rare target cells is increasing dramatically for vital applications such as cancer treatment and cell-based therapies. However, there remains a grand challenge for high-throughput and label-free segregation of lesion cells with similar sizes. Cancer cells with different invasiveness usually manifest distinct deformability. In this work, we employ a hydrogel microparticle system with similar sizes but varied stiffness to mimic cancer cells and examine in situ their deformation and focusing under microfluidic flow. We first demonstrate the similar focusing behaviour of hydrogel microparticles and cancer cells in confined flow that is dominated by deformability-induced lateral migration. The deformation, orientation and focusing position of hydrogel microparticles in microfluidic flow under different Reynolds numbers are then systematically observed and measured using a high-speed camera. Linear correlations of the Taylor deformation and tilt angle of hydrogel microparticles with the capillary number are revealed, consistent with theoretical predictions. Detailed analysis of the dependence of particle focusing on the flow rate and particle stiffness enables us to identify a linear scaling between the equilibrium focusing position and the major axis of the deformed microparticles, which is uniquely determined by the capillary number. Our findings provide insights into the focusing and dynamics of soft beads, such as cells and hydrogel microparticles, under confined flow, and pave the way for applications including the separation and identification of circulating tumour cells, drug delivery and controlled drug release.

Spin coating is the process of generating a uniform coating film on a substrate by centrifugal forces during rotation. In the framework of lubrication theory, we investigate the axisymmetric film evolution and contact-line dynamics in spin coating on a partially wetting substrate. The contact-line singularity is regularized by imposing a Navier slip model. The interface morphology and the contact-line movement are obtained by numerical solution and asymptotic analysis of the lubrication equation. The results show that the evolution of the liquid film can be classified into two modes, depending on the rotational speed. At lower speeds, the film eventually reaches an equilibrium state, and we provide a theoretical description of how the equilibrium state can be approached through matched asymptotic expansions. At higher speeds, the film exhibits two or three distinct regions: a uniform thinning film in the central region, an annular ridge near the contact line, and a possible Landau–Levich–Derjaguin-type (LLD-type) film in between that has not been reported previously. In particular, the LLD-type film occurs only at speeds slightly higher than the critical value for the existence of the equilibrium state, and leads to the decoupling of the uniform film and the ridge. It is found that the evolution of the ridge can be well described by a two-dimensional quasi-steady analysis. As a result, the ridge volume approaches a constant and cannot be neglected to predict the variation of the contact-line radius. The long-time behaviours of the film thickness and the contact radius agree with derived asymptotic solutions.

In laser systems requiring a flat-top distribution of beam intensity, beam smoothing is a critical technology for enhancing laser energy deposition onto the focal spot. The continuous phase modulator (CPM) is a key component in beam smoothing, as it introduces high-frequency continuous phase modulation across the laser beam profile. However, the presence of the CPM makes it challenging to measure and correct the wavefront aberration of the input laser beam effectively, leading to unwanted beam intensity distribution and bringing difficulty to the design of the CPM. To address this issue, we propose a deep learning enabled robust wavefront sensing (DLWS) method to achieve effective wavefront measurement and active aberration correction, thereby facilitating active beam smoothing using the CPM. The experimental results show that the average wavefront reconstruction error of the DLWS method is 0.04 μm in the root mean square, while the Shack–Hartmann wavefront sensor reconstruction error is 0.17 μm.

In this paper, we propose a novel and highly effective variational Bayesian expectation maximization-maximization (VBEM-M) inference method for log-linear cognitive diagnostic model (CDM). In the implementation of the variational Bayesian approach for the saturated log-linear CDM, the conditional variational posteriors of the parameters that need to be derived are in the same distributional family as the priors, the VBEM-M algorithm overcomes this problem. Our algorithm can directly estimate the item parameters and the latent attribute-mastery pattern simultaneously. In contrast, Yamaguchi and Okada’s (2020a) variational Bayesian algorithm requires a transformation step to obtain the item parameters for the log-linear cognitive diagnostic model (LCDM). We conducted multiple simulation studies to assess the performance of the VBEM-M algorithm in terms of parameter recovery, execution time, and convergence rate. Furthermore, we conducted a series of comparative studies on the accuracy of parameter estimation for the DINA model and the saturated LCDM, focusing on the VBEM-M, VB, expectation-maximization, and Markov chain Monte Carlo algorithms. The results indicated that our method can obtain more stable and accurate estimates, especially for the small sample sizes. Finally, we demonstrated the utility of the proposed algorithm using two real datasets.

When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allows efficient and accurate estimation of multilevel IRT models, we argue that a two-stage divide-and-conquer strategy still has its unique advantages. Within the two-stage framework, three methods that take into account heteroscedastic measurement errors of the dependent variable in stage II analysis are introduced; they are the closed-form marginal MLE, the expectation maximization algorithm, and the moment estimation method. They are compared to the naïve two-stage estimation and the one-stage MCMC estimation. A simulation study is conducted to compare the five methods in terms of model parameter recovery and their standard error estimation. The pros and cons of each method are also discussed to provide guidelines for practitioners. Finally, a real data example is given to illustrate the applications of various methods using the National Educational Longitudinal Survey data (NELS 88).

A high-energy pulsed vacuum ultraviolet (VUV) solid-state laser at 177 nm with high peak power by the sixth harmonic of a neodymium-doped yttrium aluminum garnet (Nd:YAG) amplifier in a KBe2BO3F2 prism-coupled device was demonstrated. The ultraviolet (UV) pump laser is a 352 ps pulsed, spatial top-hat super-Gaussian beam at 355 nm. A high energy of a 7.12 mJ VUV laser at 177 nm is obtained with a pulse width of 255 ps, indicating a peak power of 28 MW, and the conversion efficiency is 9.42% from 355 to 177 nm. The measured results fitted well with the theoretical prediction. It is the highest pulse energy and highest peak power ever reported in the VUV range for any solid-state lasers. The high-energy, high-peak-power, and high-spatial-uniformity VUV laser is of great interest for ultra-fine machining and particle-size measurements using UV in-line Fraunhofer holography diagnostics.

This study aimed to develop a predictive tool for identifying individuals with high antibody titers crucial for recruiting COVID-19 convalescent plasma (CCP) donors and to assess the quality and storage changes of CCP. A convenience sample of 110 plasma donors was recruited, of which 75 met the study criteria. Using univariate logistic regression and random forest, 6 significant factors were identified, leading to the development of a nomogram. Receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA) evaluated the nomogram’s discrimination, calibration, and clinical utility. The nomogram indicated that females aged 18 to 26, blood type O, receiving 1 to 2 COVID-19 vaccine doses, experiencing 2 symptoms during infection, and donating plasma 41 to 150 days after symptom onset had higher likelihoods of high antibody titres. Nomogram’s AUC was 0.853 with good calibration. DCA showed clinical benefit within 9% ~ 90% thresholds. CCP quality was qualified, with stable antibody titres over 6 months (P > 0.05). These findings highlight developing predictive tools to identify suitable CCP donors and emphasize the stability of CCP quality over time, suggesting its potential for long-term storage.

Femtosecond oscillators with gigahertz (GHz) repetition rate are appealing sources for spectroscopic applications benefiting from the individually accessible and high-power comb line. The mode mismatch between the potent pump laser diode (LD) and the incredibly small laser cavity, however, limits the average output power of existing GHz Kerr-lens mode-locked (KLM) oscillators to tens of milliwatts. Here, we present a novel method that solves the difficulty and permits high average power LD-pumped KLM oscillators at GHz repetition rate. We propose a numerical simulation method to guide the realization of Kerr-lens mode-locking and comprehend the dynamics of the Kerr-lens mode-locking process. As a proof-of-principle demonstration, an LD-pumped Yb:KGW oscillator with up to 6.17-W average power and 184-fs pulse duration at 1.6-GHz repetition rate is conducted. The simulation had a good agreement with the experimental results. The cost-effective, compact and powerful laser source opens up new possibilities for research and industrial applications.

Accurately converting satellite instantaneous evapotranspiration (λETi) over time to daily evapotranspiration (λETd) is crucial for estimating regional evapotranspiration from remote sensing satellites, which plays an important role in effective water resource management. In this study, four upscaling methods based on the principle of energy balance, including the evaporative fraction method (Eva-f method), revised evaporative fraction method (R-Eva-f method), crop coefficient method (Kc-ET0 method) and direct canopy resistance method (Direct-rc method), were validated based on the measured data of the Bowen ratio energy balance system (BREB) in maize fields in northwestern (NW) and northeastern (NE) China (semi-arid and semi-humid continental climate regions) from 2021 to 2023. Results indicated that Eva-f and R-Eva-f methods were superior to Kc-ET0 and Direct-rc methods in both climatic regions and performed better between 10:00 and 11:00, with mean absolute errors (MAE) and coefficient of efficiency (ɛ) reaching <10 W/m2 and > 0.91, respectively. Comprehensive evaluation of the optimal upscaling time using global performance indicators (GPI) showed that the Eva-f method had the highest GPI of 0.59 at 12:00 for the NW, while the R-Eva-f method had the highest GPI of 1.18 at 11:00 for the NE. As a result, the Eva-f approach is recommended as the best way for upscaling evapotranspiration in NW, with 12:00 being the ideal upscaling time. The R-Eva-f method is the optimum upscaling method for the Northeast area, with an ideal upscaling time of 11:00. The comprehensive results of this study could be useful for converting λETi to λETd.

Weedy rice (Oryza sativa f. spontanea Auct. ex Backer) is a troublesome annual weed from the Gramineae family and infests rice (Oryza sativa L.) fields globally, with a notable presence in China. However, limited information is available regarding the effects of diverse environmental factors on its germination and emergence. A better understanding of the seed biology and ecology of weedy rice is crucial for developing effective weed management strategies. Experiments were conducted to evaluate the effects of temperature, light, soil burial depth, wheat (Triticum aestivum L.) crop residue amount, salt stress, osmotic stress, and radiant heat on the germination and seedling emergence of weedy rice. Weedy rice exhibited robust germination (>98%) when exposed to varying day/night temperatures (20/15 to 35/30 C) and remained unaffected by light conditions. Seedling emergence was not influenced within the top 5-cm soil layer, where 100% of the seedlings emerged. However, emergence decreased as the soil burial depth increased, eventually resulting in no emergence from a burial depth of 11 cm. The soil burial depth required for 50% of the maximum emergence was 8.3 cm. Seedling emergence ranged from 97% to 100% across different amounts of the wheat straw residue cover (0 to 10,000 kg ha−1). The sodium chloride concentration and osmotic potential required for 50% were 230.8 mM and −0.5 MPa, respectively. No germination was observed when weedy rice seeds were exposed to >110 C pretreatment (radiant heat for 5 min), indicating that residue burning could reduce infestation of weedy rice. The insights gained from this study contribute valuable knowledge to enhance the integrated management of weedy rice in China.

Dietary n-3 PUFA may have potential benefits in preventing peptic ulcer disease (PUD). However, data from observational epidemiological studies are limited. Thus, we conducted a Mendelian randomisation analysis to reveal the causal impact of n-3 PUFA on PUD. Genetic variants strongly associated with plasma levels of total or individual n-3 PUFA including plant-derived α-linolenic acid and marine-derived EPA, DPA and DHA were enrolled as instrumental variables. Effect size estimates of the n-3 PUFA-associated genetic variants with PUD were evaluated using data from the UK biobank. Per one sd increase in the level of total n-3 PUFA in plasma was significantly associated with a lower risk of PUD (OR = 0·91; 95 % CI 0·85, 0·99; P = 0·020). The OR were 0·81 (95 % CI 0·67, 0·97) for EPA, 0·72 (95 % CI 0·58, 0·91) for DPA and 0·87 (95 % CI 0·80, 0·94) for DHA. Genetically predicted α-linolenic acid levels in plasma had no significant association with the risk of PUD (OR = 5·41; 95 % CI 0·70, 41·7). Genetically predicted plasma levels of n-3 PUFA were inversely associated with the risk of PUD, especially marine-based n-3 PUFA. Such findings may have offered an effective and feasible strategy for the primary prevention of PUD.

A simplified configuration was developed to facilitate the mode transition process within an over-under Turbine-Based Combined Cycle (TBCC) inlet. Leveraging dynamic mesh technology, an unsteady numerical simulation of the mode transition was conducted, emphasising the flow characteristics of the mode transition and the impact of key similarity criteria numbers. The findings indicate that at an incoming Mach number of 2.0, the mode transition is paired with a continuous alteration in the capture mass flow of the high-speed duct. This continual change instigates the inlet unstarting, with subsequent flow characteristics being contingent on the historical effect, exhibiting a degree of hysteresis characteristics. When the scale effect is considered, it is observed that a larger model scale results in higher Reynolds (Re) and Strouhal (St) numbers. This directly contributes to a notable delay in the unstart moment, a decrease in the unstart interval, and an enlargement of the hysteresis loop. An examination of control variables reveals that the Re number marginally influences mode transition characteristics, while the St number’s effect constitutes approximately 90% of the scale effect. This conclusively demonstrates that the St number is the predominant similarity criterion number in the mode transition process.

This study investigated the impact of diallyl disulfide (DADS) on oxidative stress induced by hydrogen peroxide (H2O2) in ovine rumen epithelial cells (RECs). Initially, the effects of DADS were evaluated on cellular reactive oxygen species (ROS) levels, antioxidant capacity in RECs were estimated. Then, RNA-seq analysis was conducted in DADS-treated and untreated cells to analyze the differential gene expression, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, the effects of DADS on Kelch-like ECH associated protein 1/the nuclear factor erythroid 2-related factor 2 (Keap1/Nrf2) signaling pathway in RECs were evaluated. Results showed that DADS remarkably enhanced superoxide dismutase (SOD) activity and total antioxidant capacity (T-AOC) (P < 0.05) while reducing ROS and malonaldehyde production (P < 0.05) in H2O2-treated RECs. Transcriptomic analysis revealed that DADS might influence glutathione synthesis through cysteine and methionine metabolism, thereby affecting the transcription of genes involved in immunity and oxidative stress. The DADS treatment resulted in increased nuclear translocation of Nrf2 and upregulation of mRNA and protein levels of quinone oxidoreductase 1, heme oxygenase 1, and Nrf2. The Nrf2-specific inhibitor nullified the protective effects of DADS on malonaldehyde formation induced by H2O2 and decreased T-AOC and SOD activities. In conclusion, DADS demonstrated the ability to alleviate oxidative stress in RECs by promoting antioxidative capacity through the Keap1/Nrf2 signaling pathway.

The discovery that blazars dominate the extra-galactic $\gamma$-ray sky is a triumph in the Fermi era. However, the exact location of $\gamma$-ray emission region still remains in debate. Low-synchrotron-peaked blazars (LSPs) are estimated to produce high-energy radiation through the external Compton process, thus their emission regions are closely related to the external photon fields. We employed the seed factor approach proposed by Georganopoulos et al. It directly matches the observed seed factor of each LSP with the characteristic seed factors of external photon fields to locate the $\gamma$-ray emission region. A sample of 1 138 LSPs with peak frequencies and peak luminosities was adopted to plot a histogram distribution of observed seed factors. We also collected some spectral energy distributions (SEDs) of historical flare states to investigate the variation of $\gamma$-ray emission region. Those SEDs were fitted by both quadratic and cubic functions using the Markov-chain Monte Carlo method. Furthermore, we derived some physical parameters of blazars and compared them with the constraint of internal $\gamma\gamma$-absorption. We find that dusty torus dominates the soft photon fields of LSPs and most $\gamma$-ray emission regions of LSPs are located at 1–10 pc. The soft photon fields could also transition from dusty torus to broad line region and cosmic microwave background in different flare states. Our results suggest that the cubic function is better than the quadratic function to fit the SEDs.

Studies on obesity and risk factors from a life-course perspective among residents in the Tibet Plateau with recent economic growth and increasing obesity are important and urgently needed. The birth cohort in this area provides a unique opportunity to examine the association between maternal dietary practice and neonatal obesity. The study aims to detect the prevalence of obesity among neonates, associated with maternal diet and other factors, supporting life-course strategies for obesity control. A cohort of pregnant women was enrolled in Tibet Plateau and followed till childbirth. Dietary practice during pregnancy was assessed using the Chinese FFQ – Tibet Plateau version, food items and other variables were associated with the risk for obesity of neonates followed by logistic regression, classification and regression trees (CART) and random forest. Of the total 1226 mother–neonate pairs, 40·5 % were Tibetan and 5·4 % of neonates with obesity. Consuming fruits as a protective factor for obesity of neonates with OR (95 % CI) = 0·61 (0·43, 0·87) from logistic regression; as well as OR = 0·20 (0·12, 0·35) for consuming fruits (≥ weekly) from CART. Removing fruit consumption to avoid overshadowing effects of other factors, the following were influential from CART: maternal education (more than middle school, OR = 0·22 (0·13, 0·37)) and consumption of Tibetan food (daily, OR = 3·44 (2·08, 5·69). Obesity among neonates is prevalent in the study population. Promoting healthy diets during pregnancy and strengthening maternal education should be part of the life-course strategies for obesity control.

This experiment aimed to investigate the impacts of tributyrin (TB) dietary supplementation on serum biochemical indices and meat quality characteristics of longissimus thoracis et lumborum (LTL) muscle of lambs after weaning. Thirty healthy Small-Tailed Han female lambs (27.5 ± 4.1 kg; mean ± standard deviation) were randomly assigned to five treatments: basal diet (1) without TB, (2) with 0.5 g/kg TB, (3) with 1.0 g/kg TB, (4) with 2.0 g/kg TB or (5) with 4.0 g/kg TB. Each treatment consisted of six lambs, and the lambs were weaned on d 90 and were raised until d 165. Results showed that supplementing TB significantly promoted serum immunoglobulin concentrations of lambs such as immunoglobulins G, A and M. Besides, TB significantly increased muscle ether extract content, intermuscular fat length, pH value and redness but decreased lightness, drip loss and shear force. In addition, TB significantly elevated inosine-5ʹ-phosphate content and upregulated the relative expressions of genes related to lipid metabolism such as SREBP-1C, SCD, PPARγ, FAS and LPL. The mostly important, TB significantly enhanced essential amino acids (EAAs) and conjugated linoleic acids contents of the LTL muscle, despite it decreased total unsaturated fatty acids level. In conclusion, supplementing TB not only could promote the healthy status of weaned lambs via promoting serum immunity but also may improve nutritional quality of LTL muscle by improving EAA and conjugated linoleic acid contents.

The absorption and distribution of radiocarbon-labeled urea at the ultratrace level were investigated with a 14C-AMS biotracer method. The radiopharmaceutical concentrations in the plasma, heart, liver, spleen, lung, kidney, stomach, brain, bladder, muscle, testis, and fat of rats after oral administration of 14C urea at ultratrace doses were determined by AMS, and the concentration-time curves in plasma and tissues and pharmacokinetic distribution data were obtained. This study provides an analytical method for the pharmacokinetic parameters and tissue distribution of exogenous urea in rats at ultratrace doses and explores the feasibility of evaluation and long-term tracking of ultratrace doses of drugs with AMS.

Machine learning methods have been used in identifying omics markers for a variety of phenotypes. We aimed to examine whether a supervised machine learning algorithm can improve identification of alcohol-associated transcriptomic markers. In this study, we analysed array-based, whole-blood derived expression data for 17 873 gene transcripts in 5508 Framingham Heart Study participants. By using the Boruta algorithm, a supervised random forest (RF)-based feature selection method, we selected twenty-five alcohol-associated transcripts. In a testing set (30 % of entire study participants), AUC (area under the receiver operating characteristics curve) of these twenty-five transcripts were 0·73, 0·69 and 0·66 for non-drinkers v. moderate drinkers, non-drinkers v. heavy drinkers and moderate drinkers v. heavy drinkers, respectively. The AUC of the selected transcripts by the Boruta method were comparable to those identified using conventional linear regression models, for example, AUC of 1958 transcripts identified by conventional linear regression models (false discovery rate < 0·2) were 0·74, 0·66 and 0·65, respectively. With Bonferroni correction for the twenty-five Boruta method-selected transcripts and three CVD risk factors (i.e. at P < 6·7e-4), we observed thirteen transcripts were associated with obesity, three transcripts with type 2 diabetes and one transcript with hypertension. For example, we observed that alcohol consumption was inversely associated with the expression of DOCK4, IL4R, and SORT1, and DOCK4 and SORT1 were positively associated with obesity, and IL4R was inversely associated with hypertension. In conclusion, using a supervised machine learning method, the RF-based Boruta algorithm, we identified novel alcohol-associated gene transcripts.