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The sulfur microbial diet (SMD), a dietary pattern associated with 43 sulfur-metabolizing bacteria, may influence gut microbiota composition and contribute to aging process through gut-produced hydrogen sulfide (H2S). We aimed to explore the association between SMD and biological age acceleration, using the cross-sectional study included 71,579 individuals from the UK Biobank. The SMD score was calculated by multiplying β-coefficients by corresponding serving sizes and summing them, based on dietary data collected using the Oxford WebQ, a 24-hour dietary assessment tool. Biological age (BA) was assessed using Klemerae-Doubal (KDM) and PhenoAge methods. The difference between BA and chronological age refers to the age acceleration (AgeAccel), termed “KDMAccel” and “PhenoAgeAccel”. Generalized linear regression was performed. Mediation analyses were used to investigate underlying mediators including body mass index (BMI) and serum aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio. Following adjustment for multiple variables, a positive association was observed between consuming a dietary pattern with a higher SMD score and both KDMAccel (βQ4vsQ1 = 0.35, 95%CI = 0.27 to 0.44, P<0.001) and PhenoAgeAccel (βQ4vsQ1 = 0.32, 95%CI = 0.23 to 0.41, P<0.001). Each 1-standard deviation increase in SMD score was positively associated with the acceleration of biological age by 7.90% for KDMAccel (P<0.001) and 7.80% for PhenoAgeAccel (P<0.001). BMI and AST/ALT mediated the association. The stratified analysis revealed stronger accelerated aging impacts in males and smokers. Our study indicated a higher SMD score is associated with elevated markers of biological aging, supporting the potential utility of gut microbiota-targeted dietary interventions in attenuating the aging process.
Depression has been linked to disruptions in resting-state networks (RSNs). However, inconsistent findings on RSN disruptions, with variations in reported connectivity within and between RSNs, complicate the understanding of the neurobiological mechanisms underlying depression.
Methods
A systematic literature search of PubMed and Web of Science identified studies that employed resting-state functional magnetic resonance imaging (fMRI) to explore RSN changes in depression. Studies using seed-based functional connectivity analysis or independent component analysis were included, and coordinate-based meta-analyses were performed to evaluate alterations in RSN connectivity both within and between networks.
Results
A total of 58 studies were included, comprising 2321 patients with depression and 2197 healthy controls. The meta-analysis revealed significant alterations in RSN connectivity, both within and between networks, in patients with depression compared with healthy controls. Specifically, within-network changes included both increased and decreased connectivity in the default mode network (DMN) and increased connectivity in the frontoparietal network (FPN). Between-network findings showed increased DMN–FPN and limbic network (LN)–DMN connectivity, decreased DMN–somatomotor network and LN–FPN connectivity, and varied ventral attention network (VAN)–dorsal attentional network (DAN) connectivity. Additionally, a positive correlation was found between illness duration and increased connectivity between the VAN and DAN.
Conclusions
These findings not only provide a comprehensive characterization of RSN disruptions in depression but also enhance our understanding of the neurobiological mechanisms underlying depression.
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.
Calorie restriction plays a role in reducing food intake and weight gain, and improving health and lifespan. We hypothesized that calorie restriction would affect body weight (BW), serum indices, gut microbiota, metabolites and short-chain fatty acids of finishing pigs. Castrated male (Landrace × Yorkshire) pigs (86.13 ± 3.50 kg) were randomly assigned into two groups indicated as control (Con) and calorie restriction (CR) (eight pigs/group), respectively. Pigs in the Con group consumed feed ad libitum, whereas pigs in the CR group were fed 70% of the amount of feed in the Con group. The trial lasted for 38 days. Blood and colonic contents were collected for serum parameters, and microbiota and metabolome analysis, respectively. Main effects were tested by Student’s t-test. We found that for finishing pigs, calorie restriction reduced the cumulative food intake, BW gain, serum total cholesterol, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, alanine aminotransferase and aspartate aminotransferase levels. Calorie restriction did not change the α and β diversity of intestinal microbiota. However, calorie restriction significantly increased the abundance of Romboutsia and unclassified_c_Bacilli, and significantly reduced the abundance of Lachnospiraceae_XPB1014_group, Candidatus_Saccharimonas, Escherichia-–Shigella and Gastranaerophilales. Calorie restriction also simultaneously changed the structure of intestinal metabolites and increased the concentration of isobutyric acid, isovaleric acid and valeric acid. In conclusion, calorie restriction may affect metabolism, reduce obesity and improve intestinal microbiota, which may be a healthy diet treatment that can reduce obesity and improve metabolism.
We report on an experimental study in which Lagrangian tracking is applied to millions of microscopic particles floating on the free surface of turbulent water. We leverage a large jet-stirred zero-mean-flow apparatus, where the Reynolds number is sufficiently high for an inertial range to emerge while the surface deformation remains minimal. Two-point statistics reveal specific features of the flow, deviating from the classic description derived for incompressible turbulence. The magnitude of the relative velocity is strongly intermittent, especially at small separations, leading to anomalous scaling of the second-order structure functions in the dissipative range. This is driven by the divergent component of the flow, leading to fast approaching/separation rates of nearby particles. The Lagrangian relative velocity shows strong persistence of the initial state, such that the ballistic pair separation extends to the inertial range of time delays. Based on these observations, we propose a classification of particle pairs based on their initial separation rate. When this is much smaller than the relative velocity prescribed by inertial scaling (which is the case for the majority of the observed particle pairs), the relative velocity transitions to a diffusive growth and the Richardson–Obukhov super-diffusive dispersion is recovered.
Broad-spectrum antimicrobials are commonly used without indication and contribute to antimicrobial resistance (AMR). We implemented a syndrome-based stewardship intervention in a community hospital that targeted common infectious syndromes and antipseudomonal beta-lactam (APBL) use. Our intervention successfully reduced AMR, C. difficile rates, use of APBLs, and cost.
This paper explores the potential causal relationship between political orientation and education investment by using panel data from 21 OECD countries from 1970 to 2020 and utilizing estimators that address endogeneity (i.e. 2SLS, System GMM, and Lewbel 2SLS). In particular, using communist influence as a physical instrument for political orientation, we find a positive impact of the right political orientation on education investment, and the impact of the left orientation is negative. The positive impact from the right orientation is also stronger than the negative impact from the left. Moreover, these core results are robust to alternative measures of political orientation and education investment, alternative estimators that address endogeneity, and the moderation effect of innovation.
Trilobite moulting behaviour has been extensively investigated. However, exuviae in eodiscid trilobites are poorly known. Here, we report two eodiscid trilobite specimens, Tsunyidiscus niutitangensis and Tsunyidiscus sp., showing Somersault configuration from the Niutitang Formation and Mingxinsi Formation of South China, respectively (Cambrian Series 2, Stage 3). The arrangements of the exoskeletons indicate that the two specimens are the slightly disturbed and undisturbed exuviae. The impression of the lower cephalic unit (LCU) displays the rostral plate in Tsunyidiscus niutitangensis. The exuviae showing the LCU inverted anteriorly under the trunk. The opening of the facial and rostral sutures would have allowed the emergence of the post-ecdysial trilobite with the partial enrolment of exoskeleton. Moreover, our discovery indicates a Somersault configuration which employed the facial and rostral sutures to create an anterior exuvial gape that also exists in eodiscid trilobites besides redlichiid trilobites, corynexochid trilobites and ptychopariid trilobites during the Cambrian.
Real-time gait trajectory planning is challenging for legged robots walking on unknown terrain. In this paper, to realize a more efficient and faster motion control of a quadrupedal robot, we propose an optimized gait planning generator (GPG) based on the decision tree (DT) and random forest (RF) model of the robot leg workspace. First, the framework of this embedded GPG and some of the modules associated with it are illustrated. Aiming at the leg workspace model described by DT and RF used in GPG, this paper introduces in detail how to collect the original data needed for training the model and puts forward an Interpolation Labeling with Dilation and Erosion (ILDE) data processing algorithm. After the DT and RF models are trained, we preliminarily evaluate their performance. We then present how these models can be used to predict the location relation between a spatial point and the leg workspace based on its distributional features. The DT model takes only 0.00011 s to process a sample, while the RF model can give the prediction probability. As a complement, the PID inverse kinematic model used in GPG is also mentioned. Finally, the optimized GPG is tested during a real-time single-leg trajectory planning experiment and an unknown terrain recognition simulation of a virtual quadrupedal robot. According to the test results, the GPG shows a remarkable rapidity for processing large-scale data in the gait trajectory planning tasks, and the results can prove it has an application value for quadruped robot control.
The impact of hepatitis B virus (HBV) infection on clinical outcomes of coronavirus disease 2019 (COVID-19) remains unclear. The aim of this study is to explore this impact. For this systematic review and meta-analysis, we searched PubMed, Web of Science, Embase, Cochrane library, China National Knowledge Infrastructure (CKNI), China Science and Technology Journal Database (VIP), and Wan Fang database for articles between 1 January 2020 and 1 February 2023. We used the Newcastle–Ottawa Quality Assessment to evaluate the study’s quality. A random-effects meta-analysis was performed utilising the rates of severe/critical illness and death in COVID-19 patients with and without HBV infection. Eighteen studies with a total of 40,502 participants met the inclusion criteria. The meta-analysis showed that compared to those without HBV infection, COVID-19 patients with HBV were at increased risk of mortality (OR = 1.65, I2 = 58%, and 95% CI 1.08–2.53) and severity (OR = 1.90, I2 = 44%, and 95% CI 1.62–2.24). The region and gender may influence the outcomes of COVID-19 patients with HBV infection, but it requires more global data to confirm. In conclusion, HBV infection is significantly linked to an increased risk of severity and mortality in COVID-19.
Given the rising burden of palliative care and the limited human resources for its facilitation in China, volunteers are becoming increasingly indispensable. In particular, there is a high demand for volunteers who can serve as spiritual caregivers. However, a volunteer’s ability to provide good spiritual care in a palliative setting may be influenced by their attitude toward palliative care. To uncover the current state of spiritual caregiving in palliative settings in China and insights into best practices for its improvement, this study measured spiritual care competence and identified its influencing factors and explored its relationship with attitudes toward palliative care among volunteers. Notably, this study is the first to consider spiritual care competence alongside attitudes toward palliative care.
Methods
A descriptive cross-sectional study using online survey methods was conducted with 385 volunteers in Shanghai, China. Data were collected using a structured questionnaire.
Results
Volunteers demonstrated relatively low levels of spiritual care competence (58.50 ± 10.92). Statistically significant correlations were found between spiritual care competence and the following variables: age, educational background, marital status, religious beliefs, occupational status, and relevant training and practical experience. Attitude toward palliative care significantly correlated with spiritual care competence (r = 0.49, p < 0.001).
Significance of results
To continually improve volunteers’ spiritual care competence, diversified education and training programs about spiritual care should be designed for different kinds of volunteers; moreover, because attitude toward palliative care significantly impacted spiritual care competence, such programs should encourage positive attitudes toward palliative care.
3D object detection using point cloud is an essential task for autonomous driving. With the development of infrastructures, roadside perception can extend the view range of the autonomous vehicles through communication technology. Computation time and power consumption are two main concerns when deploying object detection tasks, and a light-weighted detection model applied in an embedded system is a convenient solution for both roadside and vehicleside. In this study, a 3D Point cLoud Object deTection (PLOT) network is proposed to reduce heavy computing and ensure real-time object detection performance in an embedded system. First, a bird’s eye view representation of the point cloud is calculated using pillar-based encoding method. Then a cross-stage partial network-based backbone and a feature pyramid network-based neck are implemented to generate the high-dimensional feature map. Finally, a multioutput head using a shared convolutional layer is attached to predict classes, bounding boxes, and the orientations of the objects at the same time. Extensive experiments using the Waymo Open Dataset and our own dataset are conducted to demonstrate the accuracy and efficiency of the proposed method.
Patients with cirrhosis experience worse health-related quality of life (HRQoL), and attempts are warranted further exploration of modifiable factors to improve HRQoL. Data on the impact of malnutrition risk on HRQoL among cirrhosis are limited; thus, we aimed to strengthen understanding by clarifying the relationship between nutritional status and low HRQoL in patients with decompensated cirrhosis. Consecutive inpatients with cirrhosis attending our department within a tertiary hospital were studied. Generic health profiles and malnutrition risk were evaluated by the EuroQol-5D (EQ-5D) and Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) score, respectively. Multiple linear regression analysis was used to determine association of malnutrition risk with low HRQoL. In this cohort of 364 patients with median age of 64 years and 49·5 % male, 55·5 % of the study population reported impairment pertinent to HRQoL in at least one dimension in terms of the EQ-5D. Moreover, malnutrition risk (RFH-NPT score: β coefficient = −0·114, P = 0·038) was proved to be independently associated with poor HRQoL in multiple analysis, after adjustment for significant variables like age, BMI and markers of decompensation. Notably, we found that health dimensions representing physical function (i.e. mobility, self-care and usual activities) are substantially affected, while malnourished patients reported less frequencies of complaints in other domain such as anxiety/depression. In conclusion, the risk of malnutrition assessed by the RFH-NPT score is independently associated with low HRQoL. It is operational to improve HRQoL by identifying patients at high malnutrition risk and providing timely nutrition treatment.
The mitochondrial genome provides important information for phylogenetic analysis and an understanding of evolutionary origin. In this study, the mitochondrial genomes of Ilisha elongata and Setipinna tenuifilis were sequenced, which are typical circular vertebrate mitochondrial genomes composed of 16,770 and 16,805 bp, respectively. The mitogenomes of I. elongata and S. tenuifilis include 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA), two ribosomal RNA (rRNA) genes and one control region (CR). Both two species' genome compositions were highly A + T biased and exhibited positive AT-skews and negative GC-skews. The genetic distance and Ka/Ks ratio analyses indicated that 13 PCGs were affected by purifying selection and the selection pressures were different from certain deep-sea fishes, which were most likely due to the difference in their living environment. Results of phylogenetic analysis support close relationships among Chirocentridae, Denticipitidae, Clupeidae, Engraulidae and Pristigasteridae based on the nucleotide and amino acid sequences of 13 PCGs. Within Clupeoidei, I. elongata and S. tenuifilis were most closely related to the family Pristigasteridae and Engraulidae, respectively. These results will help to better understand the evolutionary position of Clupeiformes and provide a reference for further phylogenetic research on Clupeiformes species.
Persistent psychological distress associated with the coronavirus disease 2019 (COVID-19) pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults.
Methods
Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist in the period of community-level outbreaks, and for follow-up distress evaluation again 1 year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses.
Results
The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress.
Conclusions
Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from the corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges.
Fibronectin type III domain-containing protein 5 (FNDC5) is a transmembrane protein and the precursor of irisin, which serves as a systemic exerkine/myokine with multiple origins. Since its discovery in 2012, this hormone-like polypeptide has rapidly evolved to a component significantly involved in a gamut of metabolic dysregulations and various liver diseases. After a decade of extensive investigation on FNDC5/irisin, we are still surrounded by lots of open questions regarding its diagnostic and therapeutic values. In this review, we first concentrated on the structure–function relationship of FNDC5/irisin. Next, we comprehensively summarised the current knowledge and research findings regarding pathogenic roles/therapeutic applications of FNDC5/irisin in the context of non-alcoholic fatty liver disease, fibrosis, liver injury due to multiple detrimental insults, hepatic malignancy and intrahepatic cholestasis of pregnancy. Moreover, the prominent molecules involved in the underlying mechanisms and signalling pathways were highlighted. As a result, emerging evidence reveals FNDC5/irisin may act as a proxy for diagnosing liver disease pathology, a sensitive biomarker for assessing damage severity, a predisposing factor for surveilling illness progression and a treatment option with protective/preventive impact, all of which are highly dependent on disease grading and contextually pathological features.
The Democratic Republic of the Congo (DRC) has one of the highest levels of child undernutrition globally; however, little information exists on the underlying socio-economic inequalities resulting in undernutrition. This study aims to examine the differences in the nutritional statuses of children across different wealth quintiles and explores the association between malnutrition in children and related factors.
Design:
We utilised the 2018 Multiple Indicator Cluster Survey data. We estimated the prevalence of malnutrition across all twenty-six provinces. The study used the WHO 2006 child growth standards to measure stunting, underweight and wasting. We employed a mixed-effect linear model to analyse the association between nutritional status and healthcare accessibility, domestic sanitation, and socio-demographic factors.
Setting:
Twenty-six provinces in the DRC.
Participants:
21 477 children under 5 years of age and 21 828 women of childbearing age in the DRC.
Results:
The national prevalence of underweight, stunting and wasting was found to be 23·33 %, 42·05 % and 5·66 %, respectively. Household wealth and mother’s education level were significantly positively associated with the nutritional statuses of children. Among households in the lowest wealth quintile, residence in urban areas was a protective factor against undernutrition.
Conclusion:
The findings of this study indicate considerable socio-economic inequalities in the nutritional statuses of children under 5 years of age in the DRC, highlighting the need for nutrition promotion as part of maternal and child healthcare. Interventions and policies should include improving nutrition education for less-educated mothers, in particular, in the central provinces of the DRC.
We extend Savage et al.'s music and social bonding hypothesis by examining it in the context of Chinese music. First, top-down functions such as music as political instrument should receive more attention. Second, solo performance can serve as important cues for social identity. Third, a right match between the tones in lyrics and music contributes also to social bonding.
Saetaspongia so far cannot be confidently assigned to any class-level crown group. Clarifying its phylogenetic position requires new information provided by more detailed studies of previously described and/or new material. Some sponge fossils with the typical skeletal architecture of Saetaspongia have recently been recognized in the Cambrian (Stage 4) Balang Biota of Guizhou, China, including S. jianhensis new species and S. cf. S. densa. The new taxon is characterized by the following features: spicules are fine monaxons and are inclined to be loosely to densely arranged into plumose arrays; skeleton is composed primarily of one major plumose bundle, with an uncertain number (perhaps two) of small plumose arrays; and primary skeleton is occasionally interspersed with some irregularly oriented individual spicules. An additional specimen consisting of large monaxons, with plumose structures and overlying irregular coarse monaxons, closely fits the description and illustrations of previously described S. cf. S. densa. By combining information from previous studies and the present research, fossil evidence indicates that the plumose architecture is a critical feature diagnostic of Saetaspongia and that there are no hexactine-based spicules in this genus. The new material from the Balang Biota further supports the notion that Saetaspongia has a protomonaxonid rather than a hexactinellid affinity. Fossil evidence suggests that Saetaspongia had a wide biogeographic distribution during the early Cambrian and the stratigraphic distribution of this genus extends up to Stage 4.
Real-time localization is an important mission for self-driving cars and it is difficult to achieve precise pose information in dynamic environments. In this paper, a novel localization method is proposed to estimate the pose of self-driving cars using a 3D-LiDAR sensor. First, the multi-frame curb features and laser intensity features are extracted. Meanwhile, based on the high-precision curb map generated offline, obstacles on road are detected using region segmentation methods and their features are removed. Furthermore, a map-matching method is proposed to match the features to the map, a robust iterative closest point algorithm is utilized to deal with curb features along with a probability search method dealing with intensity features. Finally, two separate Kalman filters are used to fuse the low-cost global positioning systems and map-matching results. Both offline and online experiments are carried out in dynamic environments and the results demonstrate the accuracy and robustness of the proposed method.