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The heating effect of electromagnetic waves in ion cyclotron range of frequencies (ICRFs) in magnetic confinement fusion device is different in different plasma conditions. In order to evaluate the ICRF heating effect in different plasma conditions, we conducted a series of experiments and corresponding TRANSP simulations on the EAST tokamak. Both simulation and experimental results show that the effect of ICRF heating is poor at low core electron density. The decrease in electron density changes the left-handed electric field near the resonant layer, resulting in a significant decrease in the power absorbed by the hydrogen fundamental resonance. However, quite a few experiments must be performed in plasma conditions with low electron density. It is necessary to study how to make ICRF heating best in low electron density plasma. Through a series of simulation scans of the parallel refractive index (n//) of the ICRF antenna, it is concluded that the change of the ICRF antenna n// will lead to the change of the left-handed electric field, which will change the fundamental absorption of ICRF power by the hydrogen minority ions. Fully considering the coupling of ion cyclotron wave at the tokamak boundary and the absorption in the plasma core, optimizing the ICRF antenna structure and selecting appropriate parameters such as parallel refractive index, minority ion concentration, resonance layer position, plasma current and core electron temperature can ensure better heating effect in the ICRF heating experiments in the future EAST upgrade. These results have important implications for the enhancement of the auxiliary heating effect of EAST and other tokamaks.
The Chinese pangolin Manis pentadactyla is categorized as Critically Endangered on the IUCN Red List, but the development of effective conservation strategies is hindered by a lack of data on its distribution range and population dynamics. In addition, standardized survey and analysis methods are required to facilitate the sharing of results and maximize conservation effectiveness. To fill these knowledge and methodological gaps, we investigated the occurrence of pangolin burrows in the subtropical forest ecosystem of Fujian, China. We surveyed a total of 70 transects across five land-cover types within the Fujian Junzifeng National Nature Reserve and detected 87 burrows. The majority of burrows (87%) were located in mixed conifer and broadleaf forests. We used six environmental variables in a generalized linear model to examine the relationship between the occurrence of burrows and environmental factors. The average model results from the best model set showed that the distribution of burrows was significantly influenced by forest type. For effective pangolin conservation, we recommend that local conservation authorities prioritize the protection of mixed conifer and broadleaf forests. Our findings support the local conservation of the Chinese pangolin and the standardization of surveys and conservation efforts across the species’ range.
The high comorbidity of major depressive disorder (MDD), anxiety disorders (ANX), and post-traumatic stress disorder (PTSD) complicates the study of their structural neural correlates, particularly in white matter (WM) alterations. Using fractional anisotropy (FA), this meta-analysis aimed to identify both unique and shared WM characteristics for these disorders by comparing them with healthy controls (HC). The aggregated sample size across studies includes 3,661 individuals diagnosed with MDD, ANX, or PTSD and 3,140 HC participants. The whole-brain analysis revealed significant FA reductions in the corpus callosum (CC) across MDD, ANX, and PTSD, suggesting a common neurostructural alteration underlying these disorders. Further pairwise comparisons highlighted disorder-specific differences: MDD patients showed reduced FA in the middle cerebellar peduncles and bilateral superior longitudinal fasciculus II relative to ANX patients and decreased FA in the CC extending to the left anterior thalamic projections (ATPs) when compared with PTSD. In contrast, PTSD patients exhibited reduced FA in the right ATPs compared to HC. No significant FA differences were observed between ANX and PTSD or between ANX and HC. These findings provide evidence for both shared and unique WM alterations in MDD, ANX, and PTSD, reflecting the neural underpinnings of the clinical characteristics that distinguish these disorders.
This research employs an enhanced Polar Operation Limit Assessment Risk Indexing System (POLARIS) and multi-scale empirical analysis methods to quantitatively evaluate the risks in icy region navigation. It emphasises the significant influence of spatial effects and external environmental factors on maritime accidents. Findings reveal that geographical location, environmental and ice conditions are crucial contributors to accidents. The models indicate that an increase in ports, traffic volume and sea ice density directly correlates with higher accident rates. Additionally, a novel risk estimation model is introduced, offering a more accurate and conservative assessment than current standards. This research enriches the understanding of maritime accidents in icy regions, and provides a robust framework for different navigation stages and conditions. The proposed strategies and model can effectively assist shipping companies in route planning and risk management to enhance maritime safety in icy regions.
Haemonchus contortus is a parasitic nematode that causes significant economic losses in ruminant livestock worldwide. In this study, we assessed the global genetic diversity and population structure of H. contortus using mitochondrial COX1 and ribosomal ITS2 sequences retrieved from the NCBI GenBank database. In total, 324 haplotypes of the COX1 and 72 haplotypes of the ITS2 were identified. The haplotype diversity values were all higher than 0.5, and the nucleotide diversity values were higher than 0.005. The Tajima’s D value for COX1 (−1.65634) was higher than that for ITS2 (−2.60400). Fu’s Fs, Fu and Li’s D (FLD), and Fu and Li’s F (FLF) values also showed high negative values, indicating a high probability of future population growth. In addition, the high fixation index (FST) value suggests significant genetic differentiation among populations. The haplotype networks of H. contortus populations based on COX1 sequences revealed clear geographic clustering, whereas ITS2 sequences showed more haplotype admixture across regions. The results of phylogenetic analyses were consistent with the haplotype networks. These findings highlighted that H. contortus populations exhibit significant genetic variation and are undergoing rapid population expansion, with clear genetic differences across geographic regions. This study established critical baseline data for future molecular epidemiology studies, which could guide region-specific parasite surveillance and targeted control strategies, thus helping to mitigate the risk of cross-border parasite transmission and drug resistance.
This study aimed to examine the relationship between FGF19 and depressive symptoms, measured by BDI scores and investigate the moderating role of smoking.
Methods:
This study involved 156 Chinese adult males (78 smokers and 78 non-smokers) from September 2014 to January 2016. The severity of depressive symptoms was evaluated using the BDI scores. Spearman rank correlation analyses were used to investigate the relationship between CSF FGF19 levels and BDI scores. Additionally, moderation and simple slope analyses were applied to assess the moderating effect of smoking on the relationship between the two.
Results:
FGF19 levels were significantly associated with BDI scores across all participants (r = 0.26, p < 0.001). Smokers had higher CSF FGF19 levels and BDI scores compared to non-smokers (445.9 ± 272.7 pg/ml vs 229.6 ± 162.7 pg/ml, p < 0.001; 2.7 ± 3.0 vs 1.3 ± 2.4, p < 0.001). CSF FGF19 levels were positively associated with BDI scores in non-smokers (r = 0.27, p = 0.015), but no similar association was found among smokers (r = -0.11, p = 0.32). Linear regression revealed a positive correlation between FGF19 and BDI scores (β = 0.173, t = 2.161, 95% CI: 0.015- 0.331, p < 0.05), which was negatively impacted by smoking (β = -0.873, t = -4.644, 95% CI: -1.244 to -0.501, p < 0.001).
Conclusion:
These results highlight the potential role of FGF19 in individuals at risk for presence of or further development of depressive symptoms and underscore the importance of considering smoking status when examining this association.
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.
Background: We’ve adopted a novel approach that combines cellular barcoding with CRISPR/Cas-9 technology and single-cell RNA sequencing known as continuous lineage tracing to track the development, treatment and inevitable recurrence of glioblastoma. Methods: Patient derived glioma initiating cell lines were engineered with expressed DNA barcodes with CRISPR/Cas-9 targets and engrafted into NOD scid-mice. Clonal and relationships are surmised through identification of expressed barcodes, and cells were characterized by their transcriptional profiles. Phylogenetic lineage trees are created using lineage reconstructive algorithms to define cell fitness and expansion. Results: Our work has revealed a significant amount of intra-clonal cell state heterogeneity, suggesting that tumour cells engage in phenotype switching prior to therapeutic intervention. Phylogenetic lineage trees allowed us to define a gene signature of cell fitness. GBMs exist along a transcriptional gradient between undifferentiated but “high-fit” cells and terminally differentiated, “low-fit” cells, lending further evidence that these tumours consist of pools of cells that are capable of recapitulating the tumour microenvironment after treatment. Conclusions: We have successfully engineered a set of glioma initiating tumours with a novel lineage tracing technique, creating a powerful tool for real-time tracing of tumour growth through the analysis of highly detailed singe-cell RNA sequencing data with associated clonal and phylogenetic relationships.
Parental psychopathology is a known risk factor for child autistic-like traits. However, symptom-level associations and underlying mechanisms are poorly understood.
Methods
We utilized network analyses and cross-lagged panel models to investigate the specific parental psychopathology related to child autistic-like traits among 8,571 adolescents (mean age, 9.5 years at baseline), using baseline and 2-year follow-up data from the Adolescent Brain Cognitive Development study. Parental psychopathology was measured by the Adult Self Report, and child autistic-like traits were measured by three methods: the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 autism spectrum disorder (ASD) subscale, the Child Behavior Checklist ASD subscale, and the Social Responsiveness Scale. We also examined the mediating roles of family conflict and children’s functional brain connectivity at baseline.
Results
Parental attention-deficit/hyperactivity problems were central symptoms and had a direct and the strongest link with child autistic-like traits in network models using baseline data. In longitudinal analyses, parental attention-deficit/hyperactivity problems at baseline were the only significant symptoms associated with child autistic-like traits at 2-year follow-up (β = 0.014, 95% confidence interval [0.010, 0.018], FDR q = 0.005), even accounting for children’s comorbid behavioral problems. The observed association was significantly mediated by family conflict (proportion mediated = 11.5%, p for indirect effect <0.001) and functional connectivity between the default mode and dorsal attention networks (proportion mediated = 0.7%, p for indirect effect = 0.047).
Conclusions
Parental attention-deficit/hyperactivity problems were associated with elevated autistic-like traits in offspring during adolescence.
Rare earth elements (REEs) preserved in speleothems have garnered increasing attention as ideal proxies for the paleoenvironmental reconstruction. However, due to their typically low contents in stalagmites, the availability of stalagmite-based REE records remains limited. Here we present high-resolution REEs alongside oxygen isotope (δ18O) records in stalagmite SX15a from Sanxing Cave, southwestern China (110.1–103.3 ka). This study demonstrates that REE records could provide useful information for the provenance and formation process of the stalagmite, due to consistent distribution pattern across different periods indicating stable provenance. More interestingly, the total REE (ΣREE) record could serve as an effective indicator to reflect local hydrological processes associated with monsoonal precipitation. During Marine Isotopic Stage (MIS) 5d, a relatively low ΣREE content is consistent with the positive SX15a δ18O and negative NGRIP δ18O, reflecting a dry-cold environment; while during MIS 5c, a generally high ΣREE content suggests a humid-warm circumstance. Furthermore, the ΣREE record captured four prominent sub-millennial fluctuations within the Greenland interstadial 24 event, implying a combined influence by the regional climate and local soil redox conditions. Our findings indicate that the stalagmite-based REE records would be a useful proxy for better understanding of past climate and environment changes.
Clinical high risk for psychosis (CHR) is often managed with antipsychotic medications, but their effects on neurocognitive performance and clinical outcomes remain insufficiently explored. This study investigates the association between aripiprazole and olanzapine use and cognitive and clinical outcomes in CHR individuals, compared to those receiving no antipsychotic treatment.
Methods
A retrospective analysis was conducted on 127 participants from the Shanghai At Risk for Psychosis (SHARP) cohort, categorized into three groups: aripiprazole, olanzapine, and no antipsychotic treatment. Neurocognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB), while clinical symptoms were assessed through the Structured Interview for Prodromal Syndromes (SIPS) at baseline, 8 weeks, and one year.
Results
The non-medicated group demonstrated greater improvements in cognitive performance, clinical symptoms, and functional outcomes compared to the medicated groups. Among the antipsychotic groups, aripiprazole was associated with better visual learning outcomes than olanzapine. Improvements in neurocognition correlated significantly with clinical symptom relief and overall functional gains at follow-up assessments.
Conclusions
These findings suggest potential associations between antipsychotic use and cognitive outcomes in CHR populations while recognizing that observed differences may reflect baseline illness severity rather than medication effects alone. Aripiprazole may offer specific advantages over olanzapine, underscoring the importance of individualized risk-benefit evaluations in treatment planning. Randomized controlled trials are needed to establish causality.
Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment and prevention strategies. Despite the recent increase in studies examining the neurophysiological traits of IA, their findings often vary. To enhance the accuracy of identifying key neurophysiological characteristics of IA, this study used the phase lag index (PLI) and weighted PLI (WPLI) methods, which minimize volume conduction effects, to analyze the resting-state electroencephalography (EEG) functional connectivity. We further evaluated the reliability of the identified features for IA classification using various machine learning methods.
Methods
Ninety-two participants (42 with IA and 50 healthy controls (HCs)) were included. PLI and WPLI values for each participant were computed, and values exhibiting significant differences between the two groups were selected as features for the subsequent classification task.
Results
Support vector machine (SVM) achieved an 83% accuracy rate using PLI features and an improved 86% accuracy rate using WPLI features. t-test results showed analogous topographical patterns for both the WPLI and PLI. Numerous connections were identified within the delta and gamma frequency bands that exhibited significant differences between the two groups, with the IA group manifesting an elevated level of phase synchronization.
Conclusions
Functional connectivity analysis and machine learning algorithms can jointly distinguish participants with IA from HCs based on EEG data. PLI and WPLI have substantial potential as biomarkers for identifying the neurophysiological traits of IA.
The robot manipulator is commonly employed in the space station experiment cabinet for the disinfection task. The challenge lies in devising a motion trajectory for the robot manipulator that satisfies both performance criteria and constraints within the confined space of an experimental cabinet. To address this issue, this paper proposes a trajectory planning method in joint space. This method constructs the optimal trajectory by transforming the original problem into a constrained multi-objective optimization problem. This is then solved and integrated with the seventh-degree B-spline curve. The optimization algorithm utilizes an indicator-based adaptive differential evolution algorithm, enhanced with improved Tent chaotic mapping and opposition-based learning for population initialization. The method employed the Fréchet distance to design a trajectory selection strategy based on the Pareto solutions to ensure that the planned trajectory complies with Cartesian space requirements. This allows the robot manipulator end-effector to approximate the desired path in Cartesian space closely. The findings indicate that the proposed method can effectively design the robot manipulator trajectory, considering both joint motion performance and end-effector motion constraints. This ensures that the robot manipulator operates efficiently and safely within the experimental cabinet.
We present a high-power mid-infrared single-frequency pulsed fiber laser (SFPFL) with a tunable wavelength range from 2712.3 to 2793.2 nm. The single-frequency operation is achieved through a compound cavity design that incorporates a germanium etalon and a diffraction grating, resulting in an exceptionally narrow seed linewidth of approximately 780 kHz. Employing a master oscillator power amplifier configuration, we attain a maximum average output power of 2.6 W at 2789.4 nm, with a pulse repetition rate of 173 kHz, a pulse energy of 15 μJ and a narrow linewidth of approximately 850 kHz. This achievement underscores the potential of the mid-infrared SFPFL system for applications requiring high coherence and high power, such as high-resolution molecular spectroscopy, precision chemical identification and nonlinear frequency conversion.
Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.
Methods
A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.
Results
Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.
Conclusions
The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.
Political connections have been tested for correlation with outward foreign direct investment (OFDI). Both theoretical rationale and research evidence are mixed. To advance this debate, we conceptualize political connections as a dual-dimensional construct and hypothesize the differential effects of the breadth and the depth of political connections on OFDI. Employing a sample of 2,374 Chinese listed firms, encompassing 15,647 firm-year observations from 2008 to 2016, we find evidence supporting our hypotheses: (1) the breadth of political connections reduces the likelihood of a firm engaging in OFDI and (2) greater depth of political connections increases the likelihood of a firm engaging in the OFDI. Thus, we advise firms to exercise caution when adopting corporate political strategies for internationalization in general and OFDI in particular.
The antidepressant mechanism of electroconvulsive therapy (ECT) remains not clearly understood. This study aimed to detect the changes in gray matter volume (GMV) in patients with major depressive disorder (MDD) caused by ECT and exploratorily analyzed the potential functional mechanisms.
Methods
A total of 24 patients with MDD who underwent eight ECT sessions were included in the study. Clinical symptom assessments and MRI scans were conducted and compared. Using whole-brain micro-array measurements provided by the Allen Human Brain Atlas (AHBA), regional gene expression profiles were calculated. The differential gene PLS1 was obtained through Partial Least Squares (PLS) regression analysis, and PLS1 was divided into positive contribution (PLS1+) and negative contribution (PLS1−) genes. Through gene function enrichment analysis, the functional pathways and cell types of PLS1 enrichment were identified.
Results
Gray matter volume (GMV) in the somatosensory and motor cortices, occipital cortex, prefrontal cortex, and insula showed an increasing trend after ECT, while GMV in the temporal cortex, posterior cingulate cortex, and orbitofrontal cortex decreased. PLS1 genes were enriched in synapse- and cell-related biological processes and cellular components (such as ‘pre- and post-synapse’, ‘synapse organization’ etc.). A large number of genes in the PLS1+ list were involved in neurons (inhibitory and excitatory), whereas PLS1− genes were significantly involved in Astrocytes (Astro) and Microglia (Micro).
Conclusions
This study established a link between treatment-induced GMV changes and specific functional pathways and cell types, which suggests that ECT may exert its effects through synapse-associated functional and affect neurons and glial cells.