We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Tumour immunotherapy holds great promise as a treatment for cancer, which ranks as the second highest cause of mortality worldwide. This therapeutic approach can be broadly categorized into two main types: active immunotherapy and passive or adoptive immunotherapy. Active immunotherapy, such as cancer vaccines, stimulates the patients’ immune system to target tumour cells. On the other hand, adoptive immunotherapy involves supplying in vitro activated immune cells, such as T cells, natural killer cells and macrophages, to the patient to combat the tumour. Induced pluripotent stem cells are extensively utilized in both active and adoptive tumour immunotherapy due to their pluripotency and ease of gene editing. They can be differentiated into various types of immune cells for direct cancer treatment and can also function as tumour vaccines to elicit an immune response against the tumour. Importantly, iPSCs can be leveraged to develop off-the-shelf allogenic immunotherapy products.
Conclusion
This article provides a comprehensive review of the application of iPSCs in tumor immunotherapy, along with a discussion of the opportunities and challenges in this evolving field.
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 incorporation of trace metals into land snail shells may record the ambient environmental conditions, yet this potential remains largely unexplored. In this study, we analyzed modern snail shells (Cathaica sp.) collected from 16 sites across the Chinese Loess Plateau to investigate their trace metal compositions. Our results show that both the Sr/Ca and Ba/Ca ratios exhibit minimal intra-shell variability and small inter-shell variability at individual sites. A significant positive correlation is observed between the shell Sr/Ca and Ba/Ca ratios across the plateau, with higher values being recorded in the northwestern sites where less monsoonal rainfall is received. We propose that shell Sr/Ca and Ba/Ca ratios, which record the composition of soil solution, may be controlled by the Rayleigh distillation in response to prior calcite precipitation. Higher rainfall amounts may lead to a lower degree of Rayleigh distillation and thus lower shell Sr/Ca and Ba/Ca ratios. This is supported by the distinct negative correlation between summer precipitation and shell Sr/Ca and Ba/Ca ratios, enabling us to reconstruct summer precipitation amounts using the Sr/Ca and Ba/Ca ratios of Cathaica sp. shells. The potential application of these novel proxies may also be promising for other terrestrial mollusks living in the loess deposits globally.
The present study investigated the associations among pre-loss grief, relational closeness, attachment insecurities, continuing bonds (CBs) with the deceased person, and the post-loss adjustment of the caregivers of patients with terminal cancer.
Methods
Data were collected in the hospice department of a cancer center in northern Taiwan; 66 bereaved caregivers completed both pre-loss and post-loss scales. The measures used for the pre-loss phase included the Hogan Grief Reaction Checklist (HGRC; pre-loss version), the Experiences in Close Relationship – Relationship Structures Questionnaire (ECR-RS), and the Inclusion of Other in the Self Scale. The measures used 6–12 months after the death of the patients were the HGRC (post-loss version) and the Continuing Bond Scale (CBS).
Results
Pre-loss grief and externalized CBs had a significant impact on the amount of post-loss grief, indicating that pre-loss grief and ongoing transformation of relationships after patients’ death may be predictors of caregivers’ post-loss grieving.
Significance of results
This longitudinal study provides preliminary evidence that pre-loss grief and the relationship with the patient are key to caregivers’ post-loss adjustment, suggesting that psychosocial intervention focuses on caregivers’ pre-loss grief and relationship quality with the patient during palliative care.
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.
This paper introduces a novel ray-tracing methodology for various gradient-index materials, particularly plasmas. The proposed approach utilizes adaptive-step Runge–Kutta integration to compute ray trajectories while incorporating an innovative rasterization step for ray energy deposition. By removing the requirement for rays to terminate at cell interfaces – a limitation inherent in earlier cell-confined approaches – the numerical formulation of ray motion becomes independent of specific domain geometries. This facilitates a unified and concise tracing method compatible with all commonly used curvilinear coordinate systems in laser–plasma simulations, which were previously unsupported or prohibitively complex under cell-confined frameworks. Numerical experiments demonstrate the algorithm’s stability and versatility in capturing diverse ray physics across reduced-dimensional planar, cylindrical and spherical coordinate systems. We anticipate that the rasterization-based approach will pave the way for the development of a generalized ray-tracing toolkit applicable to a broad range of fluid simulations and synthetic optical diagnostics.
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.
Cleavers, an annual or winter annual broadleaf weed in the Rubiaceae family, has become troublesome in the wheat fields of the Huang-Huai-Hai region in China due to its herbicide resistance. In North America the common name of the plant is stickwilly; in China it known as cleavers. Four populations of cleavers (JS-15, SD-10, JS-22, and AH-20) were collected from wheat fields in Jiangsu, Shandong, and Anhui provinces, where the plant was not being controlled with applications of florasulam. The aims of this study were to identify the herbicide resistance patterns and investigate the mechanism underlying florasulam resistance. Whole-plant dose-response experiments revealed a notable variation in the degree of resistance exhibited by three specific populations toward florasulam, in comparison to the most sensitive population (S and AH-9), with the highest resistance index reaching 841.4. A gene-sequencing assay for acetolactate synthase (ALS) found that plants that were resistant to ALS from the JS-15, JS-22, and AH-20 populations had a Trp-574-Leu mutation, while no known ALS resistance mutations were discovered in SD-10 plants. In vitro ALS enzyme activity assays also indicated that the extractable ALS from JS-15, JS-22, and AH-20 plants was greatly resistant to florasulam relative to plants that are susceptible. Additionally, according to the resistance rating system, all resistant populations were susceptible to carfentrazone-ethyl + MCPA-sodium and bipyrazone + fluroxypyr-methyl. AH-20, JS-15, and JS-22 exhibited resistance to selected ALS, 4-hydroxyphenylpyruvate dioxygenase (HPPD), and photosystem II (PS II) complex inhibitors, demonstrating RR and RRR resistance profiles, whereas AH-9 displayed sensitivity to virtually all tested agents. The SD-10 population, on the other hand, exhibited RR and RRR resistance to HPPD and PS II inhibitors, and sensitivity to tribenuron-methyl. These findings indicate that a target site–based mechanism drives resistance to the ALS inhibitor florasulam in populations of cleavers, but nontarget site resistance may also have contributed to resistance, but this was not investigated. Other herbicides with different sites of action were tested and were active against cleavers.
Accurate characterization of high-power laser parameters, especially the near-field and far-field distributions, is crucial for inertial confinement fusion experiments. In this paper, we propose a method for computationally reconstructing the complex amplitude of high-power laser beams using modified coherent modulation imaging. This method has the advantage of being able to simultaneously calculate both the near-field (intensity and wavefront/phase) and far-field (focal-spot) distributions using the reconstructed complex amplitude. More importantly, the focal-spot distributions at different focal planes can also be calculated. To verify the feasibility, the complex amplitude optical field of the high-power pulsed laser was measured after static aberrations calibration. Experimental results also indicate that the near-field wavefront resolution of this method is higher than that of the Hartmann measurement. In addition, the far-field focal spot exhibits a higher dynamic range (176 dB) than that of traditional direct imaging (62 dB).
Bronze mou vessels appear in Shu tombs in south-west China during the Eastern Zhou period (c. 771–256 BC). Examination of these vessels reveals major changes in the supply of metal and alloying technology in the Shu State, throwing new light on the social impact of the Qin conquest and later unification of China.
The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.
Methods
A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.
Results
Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.
Conclusions
These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely used due to their profound efficacy in glycemic control and weight management. Real-world observations have revealed potential neuropsychiatric adverse events (AEs) associated with GLP-1RAs. This study aimed to comprehensively investigate and characterize these neuropsychiatric AEs with GLP-1RAs.
Methods
We analyzed GLP-1RA adverse reaction reports using the FDA Adverse Event Reporting System database. Disproportionality analysis using reporting odds ratio (ROR) identified eight categories of neuropsychiatric AEs associated with GLP-1RAs. We conducted descriptive and time-to-onset (TTO) analyses and explored neuropsychiatric AE signals among individual GLP-1RAs for weight loss and diabetes mellitus (DM) indications.
Results
We identified 25,110 cases of GLP-1RA-related neuropsychiatric AEs. GLP-1RAs showed an association with headache (ROR 1.74, 95% confidence interval [CI] 1.65–1.84), migraine (ROR 1.28, 95%CI 1.06–1.55), and olfactory and sensory nerve abnormalities (ROR 2.44, 95%CI 1.83–3.25; ROR 1.69, 95%CI 1.54–1.85). Semaglutide showed a moderate suicide-related AEs signal in the weight loss population (ROR 2.55, 95%CI 1.97–3.31). The median TTO was 16 days (interquartile range: 3–66 days).
Conclusions
In this study, we identified eight potential neuropsychiatric adverse events (AEs) associated with GLP-1RAs and, for the first time, detected positive signals for migraine, olfactory abnormalities, and sensory abnormalities. We also observed positive suicide-related signals of semaglutide, in weight loss population. This study provides a reliable basis for further investigation of GLP-1RA-related neuropsychiatric AEs. However, as an exploratory study, our findings require confirmation through large-scale prospective studies.
An increasing number of observational studies have reported associations between frailty and mental disorders, but the causality remains ambiguous.
Aims
To assess the bidirectional causal relationship between frailty and nine mental disorders.
Method
We conducted a bidirectional two-sample Mendelian randomisation on genome-wide association study summary data, to investigate causality between frailty and nine mental disorders. Causal effects were primarily estimated using inverse variance weighted method. Several secondary analyses were applied to verify the results. Cochran's Q-test and Mendelian randomisation Egger intercept were applied to evaluate heterogeneity and pleiotropy.
Results
Genetically determined frailty was significantly associated with increased risk of major depressive disorder (MDD) (odds ratio 1.86, 95% CI 1.36–2.53, P = 8.1 × 10−5), anxiety (odds ratio 2.76, 95% CI 1.56–4.90, P = 5.0 × 10−4), post-traumatic stress disorder (PTSD) (odds ratio 2.56, 95% CI 1.69–3.87, P = 9.9 × 10−6), neuroticism (β = 0.25, 95% CI 0.11–0.38, P = 3.3 × 10−4) and insomnia (β = 0.50, 95% CI 0.25–0.75, P = 1.1 × 10−4). Conversely, genetic liability to MDD, neuroticism, insomnia and suicide attempt significantly increased risk of frailty (MDD: β = 0.071, 95% CI 0.033–0.110, P = 2.8 × 10−4; neuroticism: β = 0.269, 95% CI 0.173–0.365, P = 3.4 × 10−8; insomnia: β = 0.160, 95% CI 0.141–0.179, P = 3.2 × 10−61; suicide attempt: β = 0.056, 95% CI 0.029–0.084, P = 3.4 × 10−5). There was a suggestive detrimental association of frailty on suicide attempt and an inverse relationship of subjective well-being on frailty.
Conclusions
Our findings show bidirectional causal associations between frailty and MDD, insomnia and neuroticism. Additionally, higher frailty levels are associated with anxiety and PTSD, and suicide attempts are correlated with increased frailty. Understanding these associations is crucial for the effective management of frailty and improvement of mental disorders.
We demonstrate a high-peak-power master oscillator power amplifier burst-mode laser system that generates microsecond burst duration pulses at 355 nm with a GHz-adjustable intra-burst pulse frequency. In the fiber seed, a high-bandwidth electro-optic modulator is employed to modulate a continuous-wave (CW) laser into a pulse train at GHz frequency. To acquire a microsecond rectangular burst pulse envelope, two acousto-optic modulators are used to chop the CW pulse train and generate a pre-compensation burst envelope. A three-stage neodymium-doped yttrium aluminum garnet amplifier boosts the burst-mode fiber seed’s burst energy of 1.65 J at 1064 nm. To achieve a high-power ultraviolet (UV) burst-mode laser, sum frequency generation in a LiB3O5 crystal is employed to convert the wavelength, achieving over 300 kW of peak power at 1.15 μs/10 Hz. The intra-burst pulse frequency of the UV burst laser can be adjustable from 1 to 10 GHz with a sinusoidal waveform. To the best of our knowledge, this paper represents the highest reported microsecond UV burst-mode laser in terms of output energy and peak power with the GHz-adjustable intra-burst frequency. The high-power microsecond UV burst-mode pulse laser can be directly used as a light-driven source in large-bandwidth/high-power microwave photonic systems, providing a long pulse width and high peak power laser while significantly improving the system’s multi-parameter adjustment capability and adaptability.
Depressive and anxiety disorders constitute a major component of the disease burden of mental disorders in China.
Aims
To comprehensively evaluate the disease burden of depressive and anxiety disorders in China.
Method
The raw data is sourced from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2021. This study presented the disease burden by prevalence and disability-adjusted life years (DALYs) of depressive and anxiety disorders at both the national and provincial levels in China from 1990 to 2021, and by gender (referred to as 'sex' in the GBD 2021) and age.
Results
From 1990 to 2021, the number of depressive disorder cases (from 34.4 to 53.1 million) and anxiety disorders (from 40.5 to 53.1 million) increased by 54% (95% uncertainty intervals: 43.9, 65.3) and 31.2% (19.9, 43.8), respectively. The age-standardised prevalence rate of depressive disorders decreased by 6.4% (2.9, 10.4), from 3071.8 to 2875.7 per 100 000 persons, while the prevalence of anxiety disorders remained stable. COVID-19 had a significant adverse impact on both conditions. There was considerable variability in the disease burden across genders, age groups, provinces and temporal trends. DALYs showed similar patterns.
Conclusion
The burden of depressive and anxiety disorders in China has been rising over the past three decades, with a larger increase during COVID-19. There is notable variability in disease burden across genders, age groups and provinces, which are important factors for the government and policymakers when developing intervention strategies. Additionally, the government and health authorities should consider the potential impact of public health emergencies on the burden of depressive and anxiety disorders in future efforts.
Depression is associated with serious disease burden. Despite the multitude of antidepressant options available, the adherence rate is often low. Accounting for patient preferences can potentially boost adherence to antidepressant medication and elevate patient satisfaction. However, limited evidence exists regarding patient preferences for antidepressant selection. This study aims to elicit patient preferences regarding the benefits, risks, and cost attributes of antidepressants in China.
Methods
A best-worst scaling profile case experiment was conducted using a face-to-face survey administered to patients diagnosed with depression. Patients were recruited from general and psychiatric hospitals. We utilized a multiphase approach that integrated literature review, expert consultation, and best-worst scaling to develop attributes within choice sets. The attributes with each varying across two or three levels encompassed remission rate, sleep disorders, risk of headache or dizziness, risk of gastrointestinal adverse events, risk of liver or kidney injury, and monthly out-of-pocket costs. Each respondent answered seven choice tasks, including a dominant task. Data were analyzed using conditional logit, mixed logit, and generalized multinomial logit models. Subgroup analyses were conducted to explore preference heterogeneity.
Results
A total of 331 participants completed the survey and met the inclusion criteria. Almost all attribute levels were statistically significant. Overall, the most desirable characteristics of antidepressant medications were higher remission rates (80% and 55% rates; p<0.05), lower risk of liver or kidney injury (1% rate; p<0.05), and fewer monthly out-of-pocket costs (CNY100 [USD13.93, EUR12.75]; p<0.05). Risks of gastrointestinal adverse events (60% and 35% rates) and insomnia were the least preferred features. Regarding attributes, efficacy, the risk of gastrointestinal adverse events, and sleep disorders were relatively important factors influencing patient choice. Preferences differed slightly by age, degree of education, personal annual income, and treatments currently received.
Conclusions
Our study suggests that efficacy, gastrointestinal adverse effects, sleep disorders, and treatment costs are critical drivers behind medication choices among patients with depression. Preference heterogeneity also exists regarding individual and therapeutic characteristics, which need more samples and further analyses to identify. These discoveries hold the potential to enrich the shared decision-making process between physicians and patients within healthcare settings.
We develop a latent variable selection method for multidimensional item response theory models. The proposed method identifies latent traits probed by items of a multidimensional test. Its basic strategy is to impose an \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$L_{1}$$\end{document} penalty term to the log-likelihood. The computation is carried out by the expectation–maximization algorithm combined with the coordinate descent algorithm. Simulation studies show that the resulting estimator provides an effective way in correctly identifying the latent structures. The method is applied to a real dataset involving the Eysenck Personality Questionnaire.
Pro-environmental behavior, including waste sorting and recycling, involves a combination of future-oriented (futureness) and other-oriented (otherness) attributes. Inspired by the perspective of intergenerational choice, this work explores whether eliciting concerns for future others could increase public support for recycling policy and recycling behavior. Study 1 consisted of an online random controlled trial and a laboratory experiment. In Study 1A (N = 400), future other-concern was primed using a static text manipulation, whereas in Study 1B (N = 192), a dynamic virtual manipulation was employed. The results showed that people in the conditions that elicited future other-concern reported greater household recycling intentions and more actual recycling behavior than those in the control conditions. Study 2A (N = 467) and Study 2B (N = 600) generalized this effect on the acceptance of the ‘Certain Time Certain Place’ waste sorting policy in China. Consistent with the intergenerational choice model, envisioning the future of subsequent generations is more impactful in gaining policy approval than merely envisioning a future time. These findings provide a new method for promoting public policy approval and recycling behavior, suggesting that people could become environmentally friendly when they are guided to consider future others.
The inverse dynamics model of an industrial robot can predict and control the robot’s motion and torque output, improving its motion accuracy, efficiency, and adaptability. However, the existing inverse rigid body dynamics models still have some unmodelled residuals, and their calculation results differ significantly from the actual industrial robot conditions. The bootstrap aggregating (bagging) algorithm is combined with a long short-term memory network, the linear layer is introduced as the network optimization layer, and a compensation method of hybrid inverse dynamics model for robots based on the BLL residual prediction algorithm is proposed to meet the above needs. The BLL residual prediction algorithm framework is presented. Based on the rigid body inverse dynamics of the Newton–Euler method, the BLL residual prediction network is used to perform error compensation on the inverse dynamics model of the Franka robot. The experimental results show that the hybrid inverse dynamics model based on the BLL residual prediction algorithm can reduce the average residuals of the robot joint torque from 0.5651 N·m to 0.1096 N·m, which improves the accuracy of the inverse dynamics model compared with those of the rigid body inverse dynamics model. This study lays the foundation for performing more accurate operation tasks using industrial robots.
Major psychiatric disorders (MPDs) are delineated by distinct clinical features. However, overlapping symptoms and transdiagnostic effectiveness of medications have challenged the traditional diagnostic categorisation. We investigate if there are shared and illness-specific disruptions in the regional functional efficiency (RFE) of the brain across these disorders.
Methods
We included 364 participants (118 schizophrenia [SCZ], 80 bipolar disorder [BD], 91 major depressive disorder [MDD], and 75 healthy controls [HCs]). Resting-state fMRI was used to caclulate the RFE based on the static amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality and corresponding dynamic measures indicating variability over time. We used principal component analysis to obtain static and dynamic RFE values. We conducted functional and genetic annotation and enrichment analysis based on abnormal RFE profiles.
Results
SCZ showed higher static RFE in the cortico-striatal regions and excessive variability in the cortico-limbic regions. SCZ and MDD shared lower static RFE with higher dynamic RFE in sensorimotor regions than BD and HCs. We observed association between static RFE abnormalities with reward and sensorimotor functions and dynamic RFE abnormalities with sensorimotor functions. Differential spatial expression of genes related to glutamatergic synapse and calcium/cAMP signaling was more likely in the regions with aberrant RFE.
Conclusions
SCZ shares more regions with disrupted functional integrity, especially in sensorimotor regions, with MDD rather than BD. The neural patterns of these transdiagnostic changes appear to be potentially driven by gene expression variations relating to glutamatergic synapses and calcium/cAMP signaling. The aberrant sensorimotor, cortico-striatal, and cortico-limbic integrity may collectively underlie neurobiological mechanisms of MPDs.