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Schizophrenia is a severely debilitating psychiatric disorder with high heritability and polygenic architecture. A higher polygenic risk score for schizophrenia (SzPRS) has been associated with smaller gray matter volume, lower activation, and decreased functional connectivity (FC). However, the effect of polygenic inheritance on the brain white matter microstructure has only been sparsely reported.
Eighty-four patients with first-episode schizophrenia (FES) patients and ninety-three healthy controls (HC) with genetics, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI) data were included in our study. We investigated impaired white matter integrity as measured by fractional anisotropy (FA) in the FES group, further examined the effect of SzPRS on white matter FA and FC in the regions connected by SzPRS-related white matter tracts.
Decreased FA was observed in FES in many commonly identified regions. Among these regions, we observed that in the FES group, but not the HC group, SzPRS was negatively associated with the mean FA in the genu and body of corpus callosum, right anterior corona radiata, and right superior corona radiata. Higher SzPRS was also associated with lower FCs between the left inferior frontal gyrus (IFG)–left inferior temporal gyrus (ITG), right IFG–left ITG, right IFG–left middle frontal gyrus (MFG), and right IFG–right MFG in the FES group.
Higher polygenic risks are linked with disrupted white matter integrity and FC in patients with schizophrenia. These correlations are strongly driven by the interhemispheric callosal fibers and the connections between frontotemporal regions.
The recognition of the importance of mental health as a health-target to be pursued at a global level has received additional theoretical legitimacy through its inclusion in the United Nations (UN) 2030 Agenda for Sustainable development. The theoretical axiom – mental health as a development priority – is today expected to drive the focus of research efforts and orient the future policies and funds expenditures, at global and local level. According to these premises, it becomes central to track the international trajectories of mental health research and how the different countries are progressively defining their role in the global mental health effort. In this paper we have focused on China. In light of heavy burden of mental and substance use disorders affecting this country, and considering the impact of this burden at a global level, a basic research was conducted with the main aim of offering a preliminary view on the Chinese scientific activity within the context of global mental health research. This study is not intended to assess the quality of Chinese research, but merely to retrieve and measure a specific output of this research: the articles in mental-health produced by Chinese institutions based in mainland China, published in international journals. Although the publication of articles in internationally indexed journals in not exhaustive of China's scientific activity in global mental health, it is nevertheless informative of the production of new knowledge, it allows an assessment of the impact of this knowledge at the global scientific community level and it could partially reflect the Chinese capacity to benefit from research conducted globally.
In consideration of the very limited number of studies assessing the collective evidence of Chinese research in mental health, we developed our analysis with the purpose of providing a preliminary picture of the Chinese contribution, in terms of scientific publications, in this field of knowledge. Our research performs a bibliometric analysis on the articles in mental-health produced by Chinese institutions based in mainland China and published in English-language SCI-E and SSCI journals from 1990 to 2019, providing a measure of the impact of this research at the global scientific community level.
We performed a search on the Web of Science (WoS) using seven mental and substance use disorders according to their global prevalence, as per estimates of the Global Burden of Disease 2019. A dataset including the overall number of publications for seven diseases was created and exported in InCites. The dataset was analysed on the basis of 11 research areas (WoS categories) to which mental health topic is associated in SCI-E and SSCI journals in WoS. We further extracted publications that originated in mainland China. The citational trends over time are calculated with nonparametric test for trends across ordered groups. An evaluation of the impact of the Chinese scientific production is provided by the number of citations received at the global scientific community level, both as average and percentile.
From 1990 to 2020 the overall Chinese scientific production in mental health has been generally increasing, reaching the highest growth in the last decade. A statistically significant increase (p < 0.001) is reported for articles produced by Chinese institutions in mainland China regarding ‘depression*’, ‘bipolar disorders*’ and ‘schizophrenia*’. Published Chinese research is mostly included in SCI-E journals. There is a substantial overlap regarding the average number of citations for articles in mental-health produced by Chinese institutions and the rest of the world. Despite the increasing trend, the percentage of articles in mental health produced by Chinese institutions in mainland China on the overall scientific production worldwide is below 10%.
Notwithstanding a substantial increase in the last decade, the volume of Chinese publications appears to be very limited, thus resulting in a relatively low impact at a global level. These results are affecting the potential contribution of Chinese research in the global mental health effort.
Antipsychotics are widely used for treating patients with psychosis, and target threshold psychotic symptoms. Individuals at clinical high risk (CHR) for psychosis are characterized by subthreshold psychotic symptoms. It is currently unclear who might benefit from antipsychotic treatment. Our objective was to apply a risk calculator (RC) to identify people that would benefit from antipsychotics.
Drawing on 400 CHR individuals recruited between 2011 and 2016, 208 individuals who received antipsychotic treatment were included. Clinical and cognitive variables were entered into an individualized RC for psychosis; personal risk was estimated and 4 risk components (negative symptoms-RC-NS, general function-RC-GF, cognitive performance-RC-CP, and positive symptoms-RC-PS) were constructed. The sample was further stratified according to the risk level. Higher risk was defined based on the estimated risk score (20% or higher).
In total, 208 CHR individuals received daily antipsychotic treatment of an olanzapine-equivalent dose of 8.7 mg with a mean administration duration of 58.4 weeks. Of these, 39 (18.8%) developed psychosis within 2 years. A new index of factors ratio (FR), which was derived from the ratio of RC-PS plus RC-GF to RC-NS plus RC-CP, was generated. In the higher-risk group, as FR increased, the conversion rate decreased. A small group (15%) of CHR individuals at higher-risk and an FR >1 benefitted from the antipsychotic treatment.
Through applying a personal risk assessment, the administration of antipsychotics should be limited to CHR individuals with predominantly positive symptoms and related function decline. A strict antipsychotic prescription strategy should be introduced to reduce inappropriate use.
Age effects may be important for improving models for the prediction of conversion to psychosis for individuals in the clinical high risk (CHR) state. This study aimed to explore whether adolescent CHR individuals (ages 9–17 years) differ significantly from adult CHR individuals (ages 18–45 years) in terms of conversion rates and predictors.
Consecutive CHR individuals (N = 517) were assessed for demographic and clinical characteristics and followed up for 3 years. Individuals with CHR were classified as adolescent (n = 244) or adult (n = 273) groups. Age-specific prediction models of psychosis were generated separately using Cox regression.
Similar conversion rates were found between age groups; 52 out of 216 (24.1%) adolescent CHR individuals and 55 out of 219 (25.1%) CHR adults converted to psychosis. The conversion outcome was best predicted by negative symptoms compared to other clinical variables in CHR adolescents (χ2 = 7.410, p = 0.006). In contrast, positive symptoms better predicted conversion in CHR adults (χ2 = 6.585, p = 0.01).
Adolescent and adult CHR individuals may require a different approach to early identification and prediction. These results can inform the development of more precise prediction models based on age-specific approaches.
Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program.
In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC.
The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal.
The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
Few of the previous studies of clinical high risk of psychosis (CHR) have explored whether outcomes other than conversion, such as poor functioning or treatment responses, are better predicted when using risk calculators. To answer this question, we compared the predictive accuracy between the outcome of conversion and poor functioning by using the NAPLS-2 risk calculator.
Three hundred CHR individuals were identified using the Chinese version of the Structured Interview for Prodromal Symptoms. Of these, 228 (76.0%) completed neurocognitive assessments at baseline and 199 (66.3%) had at least a 1-year follow-up assessment. The latter group was used in the NAPLS-2 risk calculator.
We divided the sample into two broad categories based on different outcome definitions, conversion (n = 46) v. non-conversion (n = 153) or recovery (n = 138) v. poor functioning (n = 61). Interestingly, the NAPLS-2 risk calculator showed moderate discrimination of subsequent conversion to psychosis in this sample with an area under the receiver operating characteristic curve (AUC) of 0.631 (p = 0.007). However, for discriminating poor functioning, the AUC of the model increased to 0.754 (p < 0.001).
Our results suggest that the current risk calculator was a better fit for predicting a poor functional outcome and treatment response than it was in the prediction of conversion to psychosis.
This study aim to derive and validate a simple and well-performing risk calculator (RC) for predicting psychosis in individual patients at clinical high risk (CHR).
From the ongoing ShangHai-At-Risk-for-Psychosis (SHARP) program, 417 CHR cases were identified based on the Structured Interview for Prodromal Symptoms (SIPS), of whom 349 had at least 1-year follow-up assessment. Of these 349 cases, 83 converted to psychosis. Logistic regression was used to build a multivariate model to predict conversion. The area under the receiver operating characteristic (ROC) curve (AUC) was used to test the effectiveness of the SIPS-RC. Second, an independent sample of 100 CHR subjects was recruited based on an identical baseline and follow-up procedures to validate the performance of the SIPS-RC.
Four predictors (each based on a subset of SIPS-based items) were used to construct the SIPS-RC: (1) functional decline; (2) positive symptoms (unusual thoughts, suspiciousness); (3) negative symptoms (social anhedonia, expression of emotion, ideational richness); and (4) general symptoms (dysphoric mood). The SIPS-RC showed moderate discrimination of subsequent transition to psychosis with an AUC of 0.744 (p < 0.001). A risk estimate of 25% or higher had around 75% accuracy for predicting psychosis. The personalized risk generated by the SIPS-RC provided a solid estimate of conversion outcomes in the independent validation sample, with an AUC of 0.804 [95% confidence interval (CI) 0.662–0.951].
The SIPS-RC, which is simple and easy to use, can perform in the same manner as the NAPLS-2 RC in the Chinese clinical population. Such a tool may be used by clinicians to counsel appropriately their patients about clinical monitor v. potential treatment options.
The duration of untreated psychosis (DUP) has been widely studied. However, for individuals with attenuated psychosis syndrome (APS), it is unclear whether the duration of untreated prodromal symptoms (DUPrS) also has a negative effect on the progression of psychosis. Our aim was to identify demographic and clinical factors contributing to the DUPrS in a large sample of individuals with APS, and to evaluate the association between DUPrS and the conversion to psychosis.
A sample of 391 individuals with APS, who were identified through a structured interview for prodromal syndromes, were included in this study, of whom a total of 334 patients had completed at least a 1-year clinical follow-up. A total of 57 individuals had converted to psychosis.
The average DUPrS was 4.8 months for the whole sample. Individuals with a longer DUPrS were likely to be men, non-local residents, with abnormal thought symptoms, a higher severity level of negative symptoms, the lower severity level of general symptoms, and lower level of general function before the onset of attenuated positive symptoms. A DUPrS of less than 2 months, or more than 6 months, lowered the risk for conversion to psychosis.
Our data suggested that the association between the DUPrS and outcome in individuals with APS were likely to be different, which is either long or short DUPrS was not related to future psychosis onset. Individuals with APS were more likely to have a group of features associated with a longer DUPrS.
The present work investigates the effects of a passive film formed during stress corrosion cracking on ductile/brittle fracture behavior, considering the interaction of a dislocation with a thin- film-covered crack under an applied remote load. The dislocation emission from the thin-film- covered crack tip is analyzed, on the basis of the two-dimensional Rice-Thomson model, for screw and edge dislocations. The results show that the nominally critical stress intensity factor for dislocation emission is related to the thin film thickness, the properties of the film and the loading conditions. For a given loading mode and a given crack length, there exists a critical value of the film thickness at which the film does not influence the dislocation emission. When the film thickness is smaller than the critical value, a harder thin film makes the dislocation emission easier and a softer film makes the dislocation emission more difficult. The opposite is also true if the film thickness is larger than the critical value.
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