Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

Vaccines have revolutionised the field of medicine, eradicating and controlling many diseases. Recent pandemic vaccine successes have highlighted the accelerated pace of vaccine development and deployment. Leveraging this momentum, attention has shifted to cancer vaccines and personalised cancer vaccines, aimed at targeting individual tumour-specific abnormalities. The UK, now regarded for its vaccine capabilities, is an ideal nation for pioneering cancer vaccine trials. This article convened experts to share insights and approaches to navigate the challenges of cancer vaccine development with personalised or precision cancer vaccines, as well as fixed vaccines. Emphasising partnership and proactive strategies, this article outlines the ambition to harness national and local system capabilities in the UK; to work in collaboration with potential pharmaceutic partners; and to seize the opportunity to deliver the pace for rapid advances in cancer vaccine technology.

Computerized assessment provides rich multidimensional data including trial-by-trial accuracy and response time (RT) measures. A key question in modeling this type of data is how to incorporate RT data, for example, in aid of ability estimation in item response theory (IRT) models. To address this, we propose a joint model consisting of a two-parameter IRT model for the dichotomous item response data, a log-normal model for the continuous RT data, and a normal model for corresponding paper-and-pencil scores. Then, we reformulate and reparameterize the model to capture the relationship between the model parameters, to facilitate the prior specification, and to make the Bayesian computation more efficient. Further, we propose several new model assessment criteria based on the decomposition of deviance information criterion (DIC) the logarithm of the pseudo-marginal likelihood (LPML). The proposed criteria can quantify the improvement in the fit of one part of the multidimensional data given the other parts. Finally, we have conducted several simulation studies to examine the empirical performance of the proposed model assessment criteria and have illustrated the application of these criteria using a real dataset from a computerized educational assessment program.

Objectives: Depression is the second most prevalent mental illness among the elderly. Nonetheless, treatment- resistant depression (TRD) is prevalent among the elderly; one-third of elderly patients with major depressive disorder (MDD) who received antidepressant treatment failed to achieve remission. Although there have been several studies regarding the associations between MDD and increased mortality and suicidal risk, studies between TRD and mortality/suicidal risk in the elderly still remains limited. In this national cohort study, we examined the association between TRD, non-TRD MDD, and non-depression with all-cause mortality, accident mortality, and suicide mortality.

Methods: For this retrospective longitudinal analysis on the entire population, the National Health Insurance Research Database of Taiwan, which comprises claims data from a lifetime insurance program and provided comprehensive medical inpatient and outpatient information categorized by ICD-9-CM and ICD-10. The National Mortality Registry offered information regarding mortality resulting from all causes, natural causes, suicide, and accidents. A cohort of ≥60-year-old patients, including both those with and without MDD, was observed between January 2003 and December 2017. Individuals were classified as TRD if they had undergone aminimum of two distinct antidepressant trials within the current episode’s two-year duration and dose, as documented in the prescribing records. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated for mortality risk utilizing Cox regression models.

Results: Among those >60 years old, after adjusting with sex and comorbidities, TRD was associated with increased risk of suicide (aHR 7.4, 95% CI [5.6-9.8]; MDD without TRD 4.4 [4.1- 4.6], compared with non-MDD group). Simliar risk of accident mortality was observed among three groups (TRD aHR 1.3 [0.9-1.9]; MDD without TRD 0.9 [0.9-1.0], compared with non-MDD group). Surprisely, TRD might presented lower mortality risk of natural mortality than the non- MDD group (TRD aHR 0.8 [0.7-0.8]; MDD without TRD 0.9 [0.8-0.9], compared with non- MDD group).

Conclusions: The suicide mortality among elderly patients with TRD is higher in comparison to non-MDD patients; nevertheless, accident mortality does not appear to have increased and the natural mortality rate is reduced. The lower mortality may reflect patient selection, and the contributing factors need further evaluation.

Developing a model to describe the shock-accelerated cylindrical fluid layer with arbitrary Atwood numbers is essential for uncovering the effect of Atwood numbers on the perturbation growth. The recent model (J. Fluid Mech., vol. 969, 2023, p. A6) reveals several contributions to the instability evolution of a shock-accelerated cylindrical fluid layer but its applicability is limited to cases with an absolute value of Atwood numbers close to $1$, due to the employment of the thin-shell correction and interface coupling effect of the fluid layer in vacuum. By employing the linear stability analysis on a cylindrical fluid layer in which two interfaces separate three arbitrary-density fluids, the present work generalizes the thin-shell correction and interface coupling effect, and thus, extends the recent model to cases with arbitrary Atwood numbers. The accuracy of this extended model in describing the instability evolution of the shock-accelerated fluid layer before reshock is confirmed via direct numerical simulations. In the verification simulations, three fluid-layer configurations are considered, where the outer and intermediate fluids remain fixed and the density of the inner fluid is reduced. Moreover, the mechanisms underlying the effect of the Atwood number at the inner interface on the perturbation growth are mainly elucidated by employing the model to analyse each contribution. As the Atwood number decreases, the dominant contribution of the Richtmyer–Meshkov instability is enhanced due to the stronger waves reverberated inside the layer, leading to weakened perturbation growth at initial in-phase interfaces and enhanced perturbation growth at initial anti-phase interfaces.

Caryocaridids are a unique representative of pelagic arthropods from the Ordovician period. They are typically found as flattened carapaces in mudstones and shales. This study reports on a species of caryocaridids, Soomicaris cedarbergensis, discovered in the Lower Ordovician of northwestern Xinjiang, NW China. The species shows the rare enrolled carapaces with a preserved cuticular ultrastructure. These specimens of caryocaridids from Xinjiang are the first reported in the Yili Block, and provide the substantial evidence that the paleogeographic distribution of caryocaridid phyllocarids could extend to the Central Asian Orogenic Belt. This species existed from the late Tremadocian until the end of the Ordovician (Hirnantian), making it the longest-ranging known species of caryocaridids. The carapace cuticle of S. cedarbergensis is composed of carbonate-fluorapatite and can be divided into three mineralized lamellae: outer, middle, and inner. The outer and inner lamellae each consist of three layers that correspond to the epicuticle, exocuticle, and endocuticle of extant crustacean carapaces. Moreover, the polygonal reticulation structure of the carapace in archaeostracans appears to be similar in shape and size to the hemolymph sinuses of leptostracans. This unique ultrastructure of the carapace cuticle in caryocaridids is believed to be better suited for a pelagic lifestyle.

The global challenge of methane emissions from enteric fermentation is critical, as it contributes significantly to atmospheric greenhouse gases and represents a loss of energy that could otherwise be utilized by ruminants. With the increasing demand for dairy and meat products, finding effective methods to reduce methane production is essential. This review explores the use of advanced meta-omics techniques – including metagenomics, metatranscriptomics, metaproteomics, and metabolomics – to deepen our understanding of ruminal methane production and identify potential strategies for its mitigation. These high-throughput technologies provide comprehensive insights into the rumen microbial communities and their metabolic functions by analyzing DNA, RNA, proteins, and metabolites directly from environmental samples. Metagenomics and metatranscriptomics offer a detailed view of microbial diversity and gene expression, while metaproteomics can identify specific enzymes and proteins directly involved in methane production pathways, revealing potential targets for mitigation strategies. Integrating these meta-omics approaches allows for a holistic understanding of the microbial processes that drive methane emissions, enabling the development of more precise interventions, such as tailored dietary modifications and the use of specific inhibitors. This review underscores the importance of a multi-omics strategy in characterizing microbial roles and interactions within the rumen, which is crucial for devising effective and sustainable methods to reduce methane emissions without compromising livestock productivity.

The evolution of the water-entry cavity affects the impact load and the motion of the body. This paper adopts the Eulerian finite element method for multiphase flow for simulations of the high-speed water-entry process. The accuracy and convergence of the numerical method are verified by comparing it with the experimental data and the results of the transient cavity dynamics theory. Based on the results, the representative characteristics of the cavity are discussed from the perspective of the cavity cross-section. It is found that the asymmetry of the cavity expansion and contraction durations is related to the motion of the free surface and the closure of the cavity. The uplift of the free surface suppresses cavity expansion, while the jet generated from free surface closure accelerates cavity contraction. The duration of the contraction of the cavity near the free surface is shorter than the expansion duration due to the change in the velocity distribution caused by the free surface motion. The necking phenomenon during deep closure leads to an increase in the internal pressure of the cavity, prolonging cavity contraction near the deep closure area. This work provides new insights into the cavity dynamics in high-speed water entry.

This study investigates the impacts of the timing of an extreme cyclone that occurred in August 2012 on the sea-ice volume evolution based on the Arctic Ice Ocean Prediction System (ArcIOPS). By applying a novel cyclone removal algorithm to the atmospheric forcing during 4–12 August 2012, we superimpose the derived cyclone component onto the atmospheric forcing one month later or earlier. This study finds that although the extreme cyclone leads to strong sea-ice volume loss in all runs, large divergence occurs in sea-ice melting mechanism in response to various timing of the cyclone. The extreme cyclone occurred in August, when enhanced ice volume loss is attributed to ice bottom melt primarily and ice surface melt secondarily. If the cyclone occurs one month earlier, ice surface melt dominates ice volume loss, and earlier appearance of open water within the ice zone initiates positive ice-albedo feedback, leading to a long lasting of the cyclone-induced impacts for approximately one month, and eventually a lower September ice volume. In contrast, if the cyclone occurs one month later, ice bottom melt entirely dominates ice volume loss, and the air-open water heat flux in the ice zone tends to offset ice volume loss.

Soft drink consumption has become a highly controversial public health issue. Given the pattern of consumption in China, sugar-sweetened beverage is the main type of soft drink consumed. Due to containing high levels of fructose, a soft drink may have a deleterious effect on handgrip strength (HGS) due to oxidative stress, inflammation and insulin resistance. However, few studies show an association between soft drink consumption and HGS in adults. We aimed to investigate the association between soft drink consumption and longitudinal changes in HGS among a Chinese adult population. A longitudinal population-based cohort study (5-year follow-up, median: 3·66 years) was conducted in Tianjin, China. A total of 11 125 participants (56·7 % men) were enrolled. HGS was measured using a handheld digital dynamometer. Soft drink consumption (mainly sugar-containing carbonated beverages) was measured at baseline using a validated FFQ. ANCOVA was used to evaluate the association between soft drink consumption and annual change in HGS or weight-adjusted HGS. After adjusting for multiple confounding factors, the least square means (95 % CI) of annual change in HGS across soft drink consumption frequencies were −0·70 (–2·49, 1·09) for rarely drinks, −0·82 (–2·62, 0·97) for < 1 cup/week and −0·86 (–2·66, 0·93) for ≥ 1 cup/week (Pfor trend < 0·05). Likewise, a similar association was observed between soft drink consumption and annual change in weight-adjusted HGS. The results indicate that higher soft drink consumption was associated with faster HGS decline in Chinese adults.

The fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith) is a highly damaging invasive omnivorous pest that has developed varying degrees of resistance to commonly used insecticides. To investigate the molecular mechanisms of tolerance to tetraniliprole, spinetoram, and emamectin benzoate, the enzyme activity, synergistic effect, and RNA interference were implemented in S. frugiperda. The functions of cytochrome P450 monooxygenase (P450) in the tolerance to tetraniliprole, spinetoram, and emamectin benzoate in S. frugiperda was determined by analysing changes in detoxification metabolic enzyme activity and the effects of enzyme inhibitors on susceptibility to the three insecticides. 102 P450 genes were screened via transcriptome and genome, of which 67 P450 genes were differentially expressed in response to tetraniliprole, spinetoram, and emamectin benzoate and validated by quantitative real-time PCR. The expression patterns of CYP9A75, CYP340AA4, CYP340AX8v2, CYP340L16, CYP341B15v2, and CYP341B17v2 were analysed in different tissues and at different developmental stages in S. frugiperda. Silencing CYP340L16 significantly increased the susceptibility of S. frugiperda to tetraniliprole, spinetoram, and emamectin benzoate. Furthermore, knockdown of CYP340AX8v2, CYP9A75, and CYP341B17v2 significantly increased the sensitivity of S. frugiperda to tetraniliprole. Knockdown of CYP340AX8v2 and CYP340AA4 significantly increased mortality of S. frugiperda to spinetoram. Knockdown of CYP9A75 and CYP341B15v2 significantly increased the susceptibility of S. frugiperda to emamectin benzoate. These results may help to elucidate the mechanisms of tolerance to tetraniliprole, spinetoram and emamectin benzoate in S. frugiperda.

The classification of internet gaming disorder (IGD) as a mental condition for further study in 2013 marked the emerging recognition of potential mental health issues associated with internet and gaming addiction. The COVID-19 pandemic and the rapid growth of gaming technology have combined to increase internet gaming, resulting in unhealthy lifestyle behaviors, poor sleep quality and psychological distress. Identifying the complex interplay between internet problem use, sleep disorders and psychological distress is crucial. However, it remains unclear how physical activity and self-compassion could improve sleep quality when individuals experience IGD symptoms. The current study, therefore, examined the relationships between IGD, sleep quality, self-compassion, physical activity and psychological distress using a path analysis approach. The study, targeting young adults (N = 283), found that physical activity played a significant role in connecting the variables and supporting the overall fit of the model. The results suggest that interventions targeting individuals with IGD should focus on promoting physical activity participation and developing self-compassion. Future research should continue to investigate the effectiveness of clinical interventions that incorporate self-compassion and physical activity counseling for individuals with IGD.

Aiming at the problems of small good workspace, many singular configurations, and limited carrying capacity of non-redundant parallel mechanisms, a full-redundant drive parallel mechanism is designed and developed, and its performance evaluation, good workspace identification, and scale optimization design are studied. First, the kinematics analysis of the planar 6R parallel mechanism is completed. Then, the motion/force transmission performance evaluation index of the mechanism is established, and the singularity analysis of the mechanism is completed. Based on this, the fully redundant driving mode of the mechanism is determined, and the good transmission workspace of the mechanism in this mode is identified. Then, the mapping relationship between the performance and scale of the mechanism is established by using the space model theory, and the scale optimization of the mechanism is completed. Finally, the robot prototype is made according to the optimal scale, and the performance verification is carried out based on the research of dynamics and control strategy. The results show that the fully redundant actuation parallel mechanism obtained by design optimization has high precision and large bearing capacity. The position repeatability and position accuracy are 0.053 mm and 0.635 mm, respectively, and the load weight ratio can reach 15.83%. The research results of this paper complement and improve the performance evaluation and scale optimization system of redundantly actuated parallel mechanisms.