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How psychotic symptoms, depressive symptoms, cognitive deficits, and functional impairment may interact with one another in schizophrenia or bipolar disorder is unclear.
Methods
This study explored these interactions in a discovery sample of 339 Chinese, of whom 146 had first-episode schizophrenia and 193 had bipolar disorder. Psychotic symptoms were assessed using the Positive and Negative Symptom Scale; depressive symptoms, using the Hamilton Depression Rating Scale; cognitive deficits, using tests of processing speed, executive function, and logical memory; and functional impairment, using clinical assessments. Network models connecting the four types of variables were developed and compared between men and women and between disorders. Potential causal relationships among the variables were explored through directed acyclic graphing. The results in the discovery sample were compared to those obtained for a validation sample of 235 Chinese, of whom 138 had chronic schizophrenia and 97 had bipolar disorder.
Results
In the discovery and validation cohorts, schizophrenia and bipolar disorder showed similar networks of associations, in which the central hubs included ‘disorganized’ symptoms, depressive symptoms, and deficits in processing speed during the digital symbol substitution test. Directed acyclic graphing suggested that disorganized symptoms were upstream drivers of cognitive impairment and functional decline, while core depressive symptoms (e.g. low mood) drove somatic and anxiety symptoms.
Conclusions
Our study advocates for transdiagnostic, network-informed strategies prioritizing the mitigation of disorganization and depressive symptoms to disrupt symptom cascades and improve functional outcomes in schizophrenia and bipolar disorder.
The existing intelligent optimization algorithms face challenges related to premature convergence in the synthesis of array antennas, resulting in low solution accuracy and a tendency to get stuck in local optima. In this paper, a logistic chaos and spiral flight dandelion optimizer (LSDO) algorithm is applied to sparse antenna array synthesis with constraints. To optimize the positions of the array elements and reduce sidelobe levels, the logistic chaotic mapping is employed for population initialization, which generates a diverse and uniformly distributed initial population. Additionally, the dandelion optimizer (DO) algorithms utilize a spiral flight strategy to enhance local exploitation capability and escape from the local optimum of the sidelobe level. For algorithm performance, numerical experimental results show the stability and robustness of the LSDO algorithm. For the optimization of planar sparse arrays, the LSDO algorithm significantly outperforms conventional optimization methods, achieving a peak sidelobe level (PSLL) reduction of 15.5% for DO, 9% for PSO, and 14.56% for IWO. These results confirm the effectiveness and superiority of the proposed algorithm.
Little is known regarding the shared genetic architecture underlying the phenotypic associations between depression and preterm birth (PTB). We aim to investigate the genetic overlap and causality of depression with PTB.
Methods
Leveraging summary statistics from the largest genome-wide association studies for broad depression (Ntotal = 807,533), major depression (Ntotal = 173,005), bipolar disorder (Ntotal = 414,466), and PTB (Ntotal = 226,330), we conducted a large-scale genome-wide cross-trait analysis to assess global and local genetic correlations, identify pleiotropic loci, and infer potential causal relationships
Results
Positive genetic correlations were observed between PTB and broad depression (rg = 0.242), major depression (rg = 0.236), and bipolar disorder (rg = 0.133) using the linkage disequilibrium score regression, which were further verified by the genetic covariance analyzer. Local genetic correlation was identified at chromosome 11q22.3 (harbors NCAM1-TTC12-ANKK1-DRD2) for PTB with depression. Cross-trait meta-analysis identified two loci shared between PTB and broad depression, two loci shared with major depression, and five loci shared with bipolar disorder, among which three were novel (rs7813444, rs3132948 and rs9273363). Mendelian randomization demonstrated a significantly increased risk of PTB for genetic liability to broad depression (odds ratio [OR]=1.30; 95% confidence interval [CI]: 1.11-1.52) and major depression (OR=1.27; 95%CI: 1.08-1.49), and the estimates remained significant across the sensitivity analyses.
Conclusions
Our findings demonstrate an intrinsic link underlying depression and PTB and shed novel light on the biological mechanisms, highlighting an important role of early screening and effective intervention of depression in PTB prevention, and may provide novel treatment strategies for both diseases.
Previous studies highlighted the health benefits of coffee and tea, but they only focused on the comparisons between different consumptions. Consequently, the association estimate lacked a clear interpretation, as the substitution of beverages and distribution of doses were not explicitly prescribed. We focused on the ‘relative association’ to ascertain the optimal consumption strategy (including total intake and optimal allocation strategy) for coffee, tea and plain water associated with decreased mortality. Self-reported coffee, tea and plain water intake were used from the UK Biobank. Within a compositional data analysis framework, a multivariate Cox model was used to assess the relative associations after adjusting for a range of potential confounders. The lower mortality risk was observed with at least approximately 7–8 drinks/d of total consumption. When the total intake > 4 drinks/d, substituting plain water with coffee or tea was linked to reduced mortality; nevertheless, the benefit was not seen for ≤ 4 drinks/d. Besides, a balanced consumption of coffee and tea (roughly a ratio of 2:3) associated with the lowest hazard ratios of 0·55 (95 % CI 0·47, 0·64) for all-cause mortality, 0·59 (95 % CI 0·48, 0·72) for cancer mortality, 0·69 (95 % CI 0·49, 0·99) for CVD mortality, 0·28 (95 % CI 0·15, 0·52) for respiratory disease mortality and 0·35 (95 % CI 0·15, 0·82) for digestive disease mortality than other combinations. These results highlight the importance of the rational combination of coffee, tea and plain water, with particular emphasis on ensuring adequate total intake, offering more comprehensive and explicit guidance for individuals.
Saccharum barberi is regarded as a sugarcane germ plasm resource of potential value. Tissue culture serves multiple purposes in breeding-related research for sugarcane. The response to tissue culture varies considerably among sugarcane genotypes; however, the influence of genetic differences on the tissue culture performance of S. barberi had not been previously investigated. This study evaluated the genotypic variation in tissue culture response among six accessions of S. barberi. Seven parameters were assessed to determine the tissue culture performance: callus induction frequency (CIF), embryogenic callus ratio, embryogenic callus induction frequency, callus regeneration frequency, callus regeneration coefficient, overall regeneration frequency (ORF) and overall regeneration coefficient (ORC). Significant variations (P < 0.05) were observed among the S. barberi genotypes for all parameters. The broad-sense heritability ranged from 80.77% to 93.10%, indicating that genetic differences were the primary source of genotypic variation. ORF exhibited the highest diversity among the parameters, with a genotypic coefficient of variation up to 70.06%. Pansahi was identified as the most amenable genotype to tissue culture, demonstrating superior performance in both callus induction and plant regeneration. CIFs at different induction periods were strongly positively correlated with both ORF and ORC, particularly during the first week, suggesting that CIF may serve as a promising early predictor of overall regeneration competence. This study is the first to report the effect of genotypic variation on callus induction and plant regeneration of S. barberi, and the findings will be valuable for future research involving tissue culture in this species.
Objectives: Data on primary care antibiotic prescription practices for children in Southeast Asia, which are essential for policy, quality improvement and patient safety, are lacking. We aimed to describe this gap and to benchmark prescription practices against international standards. Methods: Antibiotic prescriptions for children (age <18 years) who visited six public primary care clinics in Singapore between 2018 and 2021 were extracted and categorized according to the World Health Organization Access, Watch, Reserve (WHO AWaRe) classification. Quality indicators from the European Surveillance of Antimicrobial Consumption Network (ESAC- Net) and National Institute for Health and Care Excellence (NICE) guidelines were used as a measure of appropriateness of antibiotic prescribing. Descriptive statistics and T-test was used to compare prescription rates pre- and post-COVID-19 pandemic. Results: 19,325 and 20,692 oral and topical antibiotics were prescribed for 831,669 visits, with a prescription rate of 2.3% and 2.5% respectively. Mean antibiotic prescriptions fell significantly post-pandemic (2020–2021), compared to pre-pandemic numbers (1062.8 to 604.5 prescriptions per month) (p <0.001). The majority (95.8%) of prescriptions belonged to the Access group. Watch group antibiotics constituted 6.1% of the total antibiotics prescribed for respiratory conditions (n = 562). While prescriptions were low (4.1%) and well within EASC-Net quality indicator limits of 0-20% for respiratory infections, prescriptions for otitis media were significantly high (56.6%). Approximately 1 in 2 children received antibiotics as recommended by NICE guidelines for both respiratory infections (n=4,622, 51.5%) and otitis media (n=204, 51.8%). Conclusions: Primary care antibiotic prescriptions for children in Singapore decreased post- COVID-19. However, high rates of otitis media prescriptions and only 50% appropriateness for respiratory infections and otitis media emphasize the need for targeted improvements in these areas.
This qualitative study aimed to explore the lived experiences, challenges, and perceptions of nurses regarding disaster preparedness in non–first-tier (inland) cities in China. Building upon our previous quantitative findings, we sought to understand the psychological, professional, and organizational factors that influence nurses’ disaster response capabilities in resource-limited settings.
Methods
A descriptive phenomenological approach was employed. Semistructured in-depth interviews were conducted with 12 nurses from four comprehensive hospitals at or above the second level in Yongcheng City, Henan Province, China, between September and December 2023. Participants were purposively selected based on their involvement in disaster response activities. Interviews were audio-recorded, transcribed verbatim, and analyzed using Colaizzi’s 7-step method.
Results
Five major themes emerged from the analysis: (1) Psychological Stress and Emotional Adaptation, (2) Disaster Emergency Response Capacity and Management, (3) Communication and Collaboration, (4) Challenges in Disaster Nursing Capacity Development, and (5) Impact of Disaster Relief Participation. Key findings revealed that nurses experienced significant psychological pressure during disaster response, struggled with limited specialized training opportunities, faced challenges in team coordination, and identified institutional barriers to disaster preparedness enhancement. Despite these challenges, participants demonstrated strong professional commitment and developed personal coping strategies.
Conclusions
This study provides critical insights into the lived experiences of nurses during disaster response in Chinese non–first-tier cities. The findings highlight the need for systematic psychological support mechanisms, specialized disaster nursing training programs tailored to local contexts, enhanced interhospital collaboration networks, and stronger institutional commitment to disaster preparedness. These insights complement our previous quantitative findings and offer a comprehensive foundation for developing targeted interventions to enhance disaster nursing capabilities in resource-limited settings.
Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network.
Methods:
We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit.
Results:
The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility.
Conclusion:
This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.
Phase change materials (PCMs) hold considerable promise for thermal energy storage applications. However, designing a PCM system to meet a specific performance presents a formidable challenge, given the intricate influence of multiple factors on the performance. To address this challenge, we hereby develop a theoretical framework that elucidates the melting process of PCMs. By integrating stability analysis with theoretical modelling, we derive a transition criterion to demarcate different melting regimes, and subsequently formulate the melting curve that uniquely characterises the performance of an exemplary PCM system. This theoretical melting curve captures the key trends observed in experimental and numerical data across a broad parameter space, establishing a convenient and quantitative relationship between design parameters and system performance. Furthermore, we demonstrate the versatility of the theoretical framework across diverse configurations. Overall, our findings deepen the understanding of thermo-hydrodynamics in melting PCMs, thereby facilitating the evaluation, design and enhancement of PCM systems.
Compelling evidence claims that gut microbial dysbiosis may be causally associated with major depressive disorder (MDD), with a particular focus on Alistipes. However, little is known about the potential microbiota–gut–brain axis mechanisms by which Alistipes exerts its pathogenic effects in MDD.
Methods
We collected data from 16S rDNA amplicon sequencing, untargeted metabolomics, and multimodal brain magnetic resonance imaging from 111 MDD patients and 102 healthy controls. We used multistage linked analyses, including group comparisons, correlation analyses, and mediation analyses, to explore the relationships between the gut microbiome (Alistipes), fecal metabolome, brain imaging, and behaviors in MDD.
Results
Gut microbiome analysis demonstrated that MDD patients had a higher abundance of Alistipes relative to controls. Partial least squares regression revealed that the increased Alistipes was significantly associated with fecal metabolome in MDD, involving a range of metabolites mainly enriched for amino acid, vitamin B, and bile acid metabolism pathways. Correlation analyses showed that the Alistipes-related metabolites were associated with a wide array of brain imaging measures involving gray matter morphology, spontaneous brain function, and white matter integrity, among which the brain functional measures were, in turn, associated with affective symptoms (anxiety and anhedonia) and cognition (sustained attention) in MDD. Of more importance, further mediation analyses identified multiple significant mediation pathways where the brain functional measures in the visual cortex mediated the associations of metabolites with behavioral deficits.
Conclusion
Our findings provide a proof of concept that Alistipes and its related metabolites play a critical role in the pathophysiology of MDD through the microbiota–gut–brain axis.
A dual-beam platform is developed for all-optical Thomson/Compton scattering, with versatile parameter tuning capabilities including electron energy, radiation energy, radiation polarization, etc. By integrating this platform with a 200 TW Ti:sapphire laser system, we demonstrate the generation of inverse Compton scattering X-/gamma-rays with tunable energies ranging from tens of keV to MeV. The polarization of X-/gamma-rays is manipulated by adjusting the polarization of the scattering laser. In the near future, by combining this platform with multi-PW laser facilities, our goal is to explore the transition from nonlinear Thomson scattering to nonlinear Compton scattering, ultimately verifying theories related to strong-field quantum electrodynamics effects induced by extreme scattering.
Triceps skinfold thickness (TSF) is a surrogate marker of subcutaneous fat. Evidence is limited about the association of sex-specific TSF with the risk of all-cause mortality among maintenance haemodialysis (MHD) patients. We aimed to investigate the longitudinal relationship of TSF with all-cause mortality among MHD patients. A multicenter prospective cohort study was performed on 1034 patients undergoing MHD. The primary outcome was all-cause mortality. The median (interquartile range) of TSF was 9·7 (6·3–13·3 mm) in males and 12·7 (10·0–18·0 mm) in females. Over a median follow-up of 4·4 years (interquartile range, 2·4–7·9 years), there were 548 (53·0 %) deaths. When TSF was assessed as sex-specific quartiles, compared with those in quartile 1, the adjusted hazard ratio (HR) (95 % CI) of all-cause mortality in quartile 2, quartile 3 and quartile 4 was 0·93 (0·73, 1·19), 0·75 (0·58, 0·97) and 0·69 (0·52, 0·92), respectively (P for trend = 0·005). Moreover, when analysed by sex, increased TSF (≥9·7 mm for males and ≥18 mm for females) was significantly associated with a reduced risk of all-cause mortality (quartile 3–4 v. quartile 1–2; HR, 0·70; 95 % CI: 0·55, 0·90 in males; quartile 4 v. quartile 1–3; HR, 0·69; 95 % CI: 0·48, 1·00 in females). In conclusion, high TSF was significantly associated with a lower risk of all-cause mortality in MHD patients.
This paper presents an investigation of the secondary saturation characteristics of a HfTe2 saturable absorber. Pulse energies of 5.85 and 7.4 mJ were demonstrated with a high-order Hermite–Gaussian (HG) laser and a vortex laser, respectively, using alexandrite as the gain medium. To the best of our knowledge, these are the highest pulse energies directly generated with HG and vortex lasers. To broaden the applications of high-energy pulsed HG and vortex lasers, wavelength tuning in the region of 40 nm was achieved using an etalon.
This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.
Knowledge of the critical periods of crop–weed competition is crucial for designing weed management strategies in cropping systems. In the Lower Yangtze Valley, China, field experiments were conducted in 2011 and 2012 to study the effect of interference from mixed natural weed populations on cotton growth and yield and to determine the critical period for weed control (CPWC) in direct-seeded cotton. Two treatments were applied: allowing weeds to infest the crop or keeping plots weed-free for increasing periods (0, 1, 2, 4, 6, 8, 10, 12, 14, and 20 wk) after crop emergence. The results show that mixed natural weed infestations led to 35- to 55-cm shorter cotton plants with stem diameters 10 to 13 mm smaller throughout the season, fitting well with modified Gompertz and logistic models, respectively. Season-long competition with weeds reduced the number of fruit branches per plant by 65% to 82%, decreasing boll number per plant by 86% to 96% and single boll weight by approximately 24%. Weed-free seed cotton yields ranged from 2,900 to 3,130 kg ha−1, while yield loss increased with the duration of weed infestation, reaching up to 83% to 96% compared with permanent weed-free plots. Modified Gompertz and logistic models were used to analyze the impact of increasing weed control duration and weed interference on relative seed cotton yield (percentage of season-long weed-free cotton), respectively. Based on a 5% yield loss threshold, the CPWC was found to be from 145 to 994 growing degree days (GDD), corresponding to 14 to 85 d after emergence (DAE). These findings emphasize the importance of implementing effective weed control measures from 14 to 85 DAE in the Lower Yangtze Valley to prevent crop losses exceeding a 5% yield loss threshold.
Machine learning has already shown promising potential in tiled-aperture coherent beam combining (CBC) to achieve versatile advanced applications. By sampling the spatially separated laser array before the combiner and detuning the optical path delays, deep learning techniques are incorporated into filled-aperture CBC to achieve single-step phase control. The neural network is trained with far-field diffractive patterns at the defocus plane to establish one-to-one phase-intensity mapping, and the phase prediction accuracy is significantly enhanced thanks to the strategies of sin-cos loss function and two-layer output of the phase vector that are adopted to resolve the phase discontinuity issue. The results indicate that the trained network can predict phases with improved accuracy, and phase-locking of nine-channel filled-aperture CBC has been numerically demonstrated in a single step with a residual phase of λ/70. To the best of our knowledge, this is the first time that machine learning has been made feasible in filled-aperture CBC laser systems.
Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] is a dominant weed species occurring in rice (Oryza sativa L.) fields across China. Metamifop, a common herbicide, is frequently applied to control E. crus-galli and other grassy weeds in rice fields. Herein, HS01, an E. crus-galli population suspected to be resistant (R) to metamifop, was collected from Hanshan County in Anhui Province, China. Whole-plant dose–response testing revealed that, compared with the susceptible (S) population FD03, HS01 had developed high-level resistance to metamifop with a resistance index (RI) of 11.76 and showed cross-resistance to cyhalofop-butyl (RI = 9.33), fenoxaprop-P-ethyl (RI = 5.80) and clethodim (RI = 3.24). Gene sequencing revealed a Cys-2088-Arg mutation in the ACCase 1,5 allele of all the R plants, while ACCase gene overexpression was not involved in the resistance. Molecular docking indicated that the less-negative binding energies might be the main reason for the resistance of HS01 to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides. A derived cleaved amplified polymorphic sequence (dCAPS) method was developed for the rapid identification of the Cys-to-Arg mutation in the ACCase gene at codon position 2088 in E. crus-galli. Additionally, pretreatment with the cytochrome P450 inhibitor piperonyl butoxide or the glutathione S-transferase inhibitor 4-chloro-7-nitrobenzoxadiazole had no significant effects (P > 0.05) on the resistance of HS01 to metamifop. To our knowledge, this is the first report of a Cys-2088-Arg mutation in E. crus-galli ACCase that confers cross-resistance to ACCase-inhibiting herbicides.
The Early-Middle Jurassic impression/compression macroflora and the palynoflora from the Qaidam Basin in the northeastern Qinghai-Xizang (Tibetan) Plateau have been well studied; however, fossil wood from this region has not been previously documented systematically. Here, we describe an anatomically well-preserved fossil wood specimen from the Lower Jurassic Huoshaoshan Formation at the Dameigou section in northern Qinghai Province, northwestern China. This fossil exhibits typical Metapodocarpoxylon Dupéron-Laudoueneix et Pons anatomy with usually araucarian radial tracheid pits and variable cross-field pits, representing a new record for Metapodocarpoxylon in the Qaidam Basin. This discovery indicates that trees with this type of wood anatomy were not confined to northern Gondwana but also grew in more northerly regions in Laurasia. The wood displays distinct growth rings, with abundant, well-formed earlywood and narrow latewood. This observation, along with previous interpretations based on macroflora, palynoflora and sedimentological data, suggests that a warm and humid climate with mild seasonality prevailed in the region during the Early Jurassic.
Drawing upon research on the visual complexity effect and Dual Coding Theory, this research examined the influence of character properties and the role of individual learner differences in Chinese character acquisition. The participants included 248 Chinese-speaking children in grades 1 through 3 in Taiwan. The study extended the scope of previous research by concurrently examining two types of cognitive processing: activation of verbal codes with nonverbal codes (activation of word form) and activation of nonverbal codes with verbal codes (activation of meaning). Results revealed the asymmetry in the two types of cognitive processing. Regarding the influence of character properties, while characters with less visual complexity and with radical presence are generally more acquirable, the interaction between these two properties was only present in the activation of meaning but not the activation of word form. Individual differences contributing to character acquisition did not mirror each other in the two directions of cognitive processing either. The contribution of radical awareness and visual skills remained the same across grade levels in the activation of meaning but varied with grades and the properties of the characters in the activation of word form. The methodological and theoretical contributions of the study were discussed.