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The Kirkpatrick–Baez (KB) microscope is an effective instrument for x-ray imaging of hot spot. However, the non-uniform distribution of response efficiency in the field of view is a drawback of the KB microscope. A more accurate hot spot image requires the correction of the measured image by combining the hot spot position and the response efficiency distribution. Here, we describe a method to locate the position of the hot spot in the field of view during hot spot imaging with a KB microscope. The position of the hot spot in the field of view can be obtained by measuring the grazing incidence angle change during hot spot imaging. In the experiment of hot spot self-emission imaging with a four-channel KB microscope, the location of the hot spot with an accuracy of 15 μm was realized, and the intensity corrected hot spot image was obtained. This will solve the problem of the non-uniform distribution of the response efficiency of the KB microscope and enable quantitative measurement of hot spot radiation intensity.

Abstract This study associated the liver proton density fat fraction (PDFF), measured by multi-echo Dixon (ME-Dixon) and breath-hold single-voxel high-speed T2-corrected multi-echo 1H magnetic resonance spectroscopy (HISTO) at 1.5 T, with serum biomarkers and liver fibrosis stages. This prospective study enrolled 75 patients suspected of liver fibrosis and scheduled for liver biopsy and 23 healthy participants with normal liver function. The participant underwent ME-Dixon and HISTO scanning. The agreement of PDFF measured by ME-Dixon (PDFF-D) and HISTO (PDFF-H) were compared. Correlations between PDFF and serum fat biomarkers (total cholesterol, triglyceride, and high- and low-density lipoproteins) and the liver fibrosis stages were assessed. PDFF were compared among the liver fibrosis stages (F0–F4) based on clinical liver biopsies. The Bland–Altman plot showed agreement between PDFF-D and PDFF-H(LoA, − 4.44 to 6.75), which have high consistency (ICC 0.752, P

Advances in transcriptomic technologies have deepened our understanding of the cellular gene expression programs of multicellular organisms and provided a theoretical basis for disease diagnosis and therapy. However, both bulk and single-cell RNA sequencing approaches lose the spatial context of cells within the tissue microenvironment, and the development of spatial transcriptomics has made overall bias-free access to both transcriptional information and spatial information possible. Here, we elaborate development of spatial transcriptomic technologies to help researchers select the best-suited technology for their goals and integrate the vast amounts of data to facilitate data accessibility and availability. Then, we marshal various computational approaches to analyze spatial transcriptomic data for various purposes and describe the spatial multimodal omics and its potential for application in tumor tissue. Finally, we provide a detailed discussion and outlook of the spatial transcriptomic technologies, data resources and analysis approaches to guide current and future research on spatial transcriptomics.

Designing ultrathin and flexible antenna is of great interest for efficient wireless data communication and transmission at fast-growing IoT applications. The authors report a flexible ultrawideband Ti3C2 monopole antenna by combining strategies of interfacial modification and advanced extrusion printing technology.

Coverage-guided greybox fuzzing (CGF) has become the mainstream technology used in the field of vulnerability mining, which has been proven to be effective. Seed scheduling, the process of selecting seeds from the seeds pool for subsequent fuzzing iterations, is a critical component of CGF. While many seed scheduling strategies have been proposed in academia, they all focus on the explored regions within programs. In response to the inefficiencies of traditional seed scheduling strategies, which often allocate resources to ineffective seeds, we introduce a novel seed scheduling strategy guided by untouched edges. The strategy generates the optional seed set according to the information on the untouched edges. We also present a new instrumentation method to capture unexplored areas and guide the fuzzing process toward them. We implemented the prototype UntouchFuzz on top of American Fuzzy Lop (AFL) and conducted evaluation experiments against the most advanced seed scheduling strategies. Our results demonstrate that UntouchFuzz has improved in code coverage and unique vulnerabilities. Furthermore, the method proposed is transplanted into the fuzzer MOpt, which further proves the scalability of the method. In particular, 13 vulnerabilities were found in the open-source projects, with 7 of them having assigned CVEs.

Abstract Background The One Health (OH) concept has been promoted widely around the globe. OH framework is expected to be applied as an integrated approach to support addressing zoonotic diseases as a significant global health issue and to improve the efficiency and effectiveness of zoonosis prevention and control. This review is intended to overview the social impact of the implementation of OH on zoonosis prevention and control. Methods A scoping review of studies in the past 10 years was performed to overview the integration feature of OH in zoonosis prevention and control and the social impacts of OH. PubMed and Web of Science were searched for studies published in English between January 2011 and June 2021. The included studies were selected based on predefined criteria. Results Thirty-two studies were included in this review, and most of them adopted qualitative and semi-qualitative methods. More than 50% of the studies focused on zoonosis prevention and control. Most studies were conducted in low- and middle-income countries in Africa and Asia. Applying OH approach in diseases control integrates policymakers, stakeholders, and academics from various backgrounds. The impact of OH on economic is estimated that it may alleviate the burden of diseases and poverty in the long term, even though more financial support might be needed at the initial stage of OH implementation. OH implementation considers social and ecological factors related to zoonosis transmission and provides comprehensive strategies to assess and address related risks in different communities according to regions and customs. Conclusions Based on reviewed literature, although there seems to be a lack of guidelines for assessing and visualizing the outcomes of OH implementation, which may limit the large-scale adoption of it, evidence on the contributions of implementing OH concepts on zoonosis prevention and control indicates long-term benefits to society, including a better integration of politics, stakeholders and academics to improve their cooperation, a potential to address economic issues caused by zoonosis, and a comprehensive consideration on social determinants of health during zoonosis prevention and control.

Background: Major depression is one of the most common psychiatric disorders worldwide, inflicting suffering, significant reduction in life span, and financial burdens on families and society. Mounting evidence implicates that exposure to chronic stress can induce the dysregulation of the immune system, and the activation of brain-resident innate immune cells, microglia, leading to depression-like symptoms. However, the specific mechanisms need to be further elucidated.Method: Animal models of depression were established by chronic restraint stress (CRS), and depression-like behavior was assessed by sucrose preference test (SPT), open field test (OFT), tail suspension test (TST) and forced swimming test (FST). Microglial activation was visualized by immunofluorescent and immunohistochemical staining, and microglial morphological changes were further analyzed by skeleton analysis. The levels of inflammatory cytokines were detected by western blotting and qPCR.Result: Microglial Dlg1 knockout ameliorates CRS-induced mice depression-like behavior. In contrast to the effect of Dlg1 in the LPS-induced mouse model, Dlg1 knockout had little effect on microglial density, but significantly decreased the number of activated microglia and reversed microglia morphological changes in mice challenged with CRS. Moreover, the upregulation of inflammatory cytokines following CRS exposure was partially reversed by Dlg1 deletion.Conclusion: Our study provides the evidence that Dlg1 ablation in microglia remarkedly reverses microglial activation and depression-like behavior in mice exposed to CRS, implicating a potential target for the treatment of clinical depression.

A recently proposed octahedral spherical hohlraum with six laser entrance holes (LEHs) is an attractive concept for an upgraded laser facility aiming at a predictable and reproducible fusion gain with a simple target design. However, with the laser energies available at present, LEH size can be a critical issue. Owing to the uncertainties in simulation results, the LEH size should be determined on the basis of experimental evidence. However, determination of LEH size of an ignition target at a small-scale laser facility poses difficulties. In this paper, we propose to use the prepulse of an ignition pulse to determine the LEH size for ignition-scale hohlraums via LEH closure behavior, and we present convincing evidence from multiple diagnostics at the SGIII facility with ignition-scale hohlraum, laser prepulse, and laser beam size. The LEH closure observed in our experiment is in agreement with data from the National Ignition Facility. The total LEH area of the octahedral hohlraum is found to be very close to that of a cylindrical hohlraum, thus successfully demonstrating the feasibility of the octahedral hohlraum in terms of laser energy, which is crucially important for sizing an ignition-scale octahedrally configured laser system. This work provides a novel way to determine the LEH size of an ignition target at a small-scale laser facility, and it can be applied to other hohlraum configurations for the indirect drive approach.

Objectives: Schistosomiasis is a zoonotic infectious disease that seriously harms people’s physical and mental health. As early as 1985, the WHO suggested that health education and health promotion should be the focus of schistosomiasis prevention work. This study aimed to explore the effect of health education on controlling the risk of schistosomiasis transmission after schistosomiasis blocking and to provide a scientific basis for the further improvement of intervention strategies after schistosomiasis interruption in China and other endemic countries. Methods: In Jiangling County, Hubei Province, China, one severe, one moderate, and one mildly endemic village were selected as the intervention group; two severe, two moderate, and two mildly endemic villages were selected as the control group. In towns with different epidemic types, a primary school was randomly selected for intervention. In September 2020, a baseline survey was carried out through a questionnaire survey to understand the knowledge, attitudes, and practices (KAP) of adults and students concerning schistosomiasis control. Next, two rounds of health education interventions for schistosomiasis control were carried out. The evaluation survey was conducted in September 2021 and the follow-up survey conducted in September 2022. Results: Compared with the baseline survey, the qualified rate of the KAP on schistosomiasis prevention of the control group in the follow-up survey increased from 79.1% (584/738) to 81.0% (493/609) (p > 0.05); in the intervention group, the qualified rate of the KAP on schistosomiasis control increased from 74.9% (286/382) to 88.1% (260/295) (p < 0.001). In the baseline survey, the qualified rate of the KAP of the intervention group was lower than that of the control group, and in the follow-up survey, the qualified rate of the KAP of the intervention group was 7.2% higher than that of the control group (p < 0.05). Compared with the baseline survey, the accuracy rates of the KAP of the intervention group’s adults were higher than those of the control group, with statistical significance (p < 0.001). Compared with the baseline survey, the qualified rate of the students’ KAP in the follow-up survey increased from 83.8% (253/302) to 97.8% (304/311) (p < 0.001). In the follow-up survey, the accuracy rate of the knowledge, attitudes, and practices of the students was significantly different from the baseline accuracy (p < 0.001). Conclusion: a health education-led risk control model of schistosomiasis can significantly improve schistosomiasis control knowledge among adults and students, establishing correct attitudes and leading to the development of correct hygiene habits.

With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention. Nowadays, malware has become a huge security threat in cyberspace. Traditional signature-based malware detection methods are not adaptable to the current large-scale malware detection. Thus many deep learning-based malware detection models are widely used in real malware detection scenarios. Therefore, we need to secure the deep learning-based malware detection models. However, model testing currently focuses on image and natural language processing models. There is no related work to test deep learning-based malware detection models specifically. Therefore, to fill this gap, we propose MalFuzz. MalFuzz uses the idea of coverage-guided fuzzing to test deep learning-based malware detection models. To solve the model state representation problem, MalFuzz uses the first and last layer neuron values to approximately represent the model state. To solve the new coverage calculation problem, MalFuzz uses the fast approximate nearest neighbor algorithm to compute the new coverage. The mutation strategy and seed selection strategy in image model or natural language processing model testing is not appropriate in deep learning-based malware detection model testing. Hence MalFuzz designs the seed selection strategy and seed mutation strategy for malware detection model testing. We performed extensive experiments to demonstrate the effectiveness of MalFuzz. Based on MalConv, Convnet, and CNN 2-d, we compared the modified TensorFuzz and MAB-malware with MalFuzz. Experiment results show that MalFuzz can detect more model classification errors. Likewise, the mutation operation of MalFuzz can retain the original functionality of malware with high probability. Moreover, the seed selection strategy of MalFuzz can help us explore the model state space quickly.

Refractory complex concentrated alloys are an emerging class of materials that attracts attention due to their stability and performance at high temperatures. In this study, we investigate the variations in the mechanical and thermal properties across a broad compositional space for the refractory MoNbTaTi quaternary using high-throughput ab-initio calculations and experimental characterization. For all the properties surveyed, we note a good agreement between our modeling predictions and the experimentally measured values. We reveal the particular role of molybdenum (Mo) to achieve high strength when in high concentration. We trace the origin of this phenomenon to a shift from metallic to covalent bonding when the Mo content is increased. Additionally, a mechanistic, dislocation-based description of the yield strength further explains such high strength due to a combination of high bulk and shear moduli, accompanied by the relatively small size of the Mo atom compared to the other atoms in the alloy. Our analysis of the thermodynamics properties shows that regardless of the composition, this class of quaternary alloys shows good stability and low sensitivity to temperature. Taken together, these results pave the way for the design of new high-performance refractory alloys beyond the equimolar composition found in high-entropy alloys.

Database Management Systems (DBMSs) are the core of management information systems. Thus, detecting security bugs or vulnerabilities of DBMSs is an essential task. In recent years, grey-box fuzzing has been adopted to detect DBMS bugs for its high effectiveness. However, the seed scheduling strategy of existing fuzzing techniques does not consider the seeds’ correctness, which is inefficient in finding vulnerabilities in DBMSs. Moreover, current tools cannot correctly generate SQL statements with nested structures, which limits their effectiveness. This paper proposes a fuzzing solution named Squill to address these challenges. First, we propose correctness-guided mutation to utilize the correctness of seeds as feedback to guide fuzzing. Second, Squill embeds semantics-aware instantiation to correctly fill semantics to SQL statements with nested structures by collecting the context information of AST nodes. We implemented Squill based on Squirrel and evaluated it on three popular DBMSs: MySQL, MariaDB, and OceanBase. In our experiment, Squill explored 29% more paths and found 3.4× more bugs than the existing tool. In total, Squill detected 30 bugs in MySQL, 27 in MariaDB, and 6 in OceanBase. Overall, 19 of the bugs are fixed with 9 CVEs assigned. The results show that Squill outperforms the previous fuzzer in terms of both code coverage and bug discovery.

Abstract Although the focus in the area of health research may be shifting from infectious to non-communicable diseases, the infectious diseases of poverty remain a major burden of disease of global health concern. A global platform to communicate and share the research on these diseases is needed to facilitate the translation of knowledge into effective approaches and tools for their elimination. Based on the “One health, One world” mission, a new, open-access journal, Infectious Diseases of Poverty (IDP), was launched by BioMed Central in partnership with the National Institute of Parasitic Diseases (NIPD), Chinese Center for Disease Control and Prevention (China CDC) on October 25, 2012. Its aim is to identify and assess research and information gaps that hinder progress towards new interventions for a particular public health problem in the developing world. From the inaugural IDP issue of October 25, 2012, a total of 256 manuscripts have been published over the following five years. Apart from a small number of editorials, opinions, commentaries and letters to the editor, the predominant types of publications are research articles (69.5%) and scoping reviews (21.5%). A total of 1 081 contributing authors divided between 323 affiliations across 68 countries, territories and regions produced these 256 publications. The journal is indexed in major international biomedical databases, including Web of Science, PubMed, Scopus and Embase. In 2015, it was assigned its first impact factor (4.11), which is now 2.13. During the past five years, IDP has received manuscripts from 90 countries, territories and regions across six continents with an annual acceptance rate of all contributions maintained at less than 40%. Content analysis shows that neglected tropical diseases (NTDs), followed by the “Big Three” (HIV/AIDS, malaria and tuberculosis) and infectious diseases in general comprise 88% of all publications. In addition, a series of 10 thematic issues, covering 118 publications in all, was published as separate parts of the first five volumes. These publications were cited 975 times, which equals an average of 8.3 times per publication. The current challenge is to identify cutting-edge research topics and attract and to publish first-rate publications leading to increasing importance and impact of the journal in its field.

In order to study the laser plasma instabilities (LPIs) in the context of some novel six-side laser-driven indirect designs like the six-cylinder-port hohlraum and the three-axis cylindrical hohlraum, where the laser beams inject in hohlraum with a large angle. LPI experiments in cylindrical hohlraum with only outer beams were designed and performed based on the current laser arrangement condition of SGIII laser facility for the first time. Stimulated Brillouin backscatter (SBS) was found to be the dominant instability with high instantaneous reflectivity in experiments. A typical feature was obtained in the time-resolved spectra of SBS, which maintained similar for different laser intensities of the interaction beam. The experimental data are analyzed by the hydrodynamic simulations combined with HLIP code, which is based on the ray-tracing model. By analysis of experimental data, it is argued that the mixture of gas and Au in the region of their interface is important to SBS, which indicates the need for the mixture model between the filled gas and the high Z plasma from hohlraum wall in the hydrodynamic simulations. Nonlinear saturation of SBS as well as the smoothed beam are also discussed here. Our effective considerations of the ions pervasion effect and the smoothed beam provide utilitarian ways for improvement of the current ray-tracing method.

As a special kind of handwriting with a brush, Chinese calligraphic handwriting (CCH) requires a large amount of practice with high levels of concentration and emotion regulation. Previous studies have showed that long-term CCH training has positive effects physically (induced by handwriting activities) and psychologically (induced by the state of relaxation and concentration), the latter of which is similar to the effects of meditation. The aim of this study was to investigate the long-term CCH training effect on anxiety and attention, as well as brain structure. Participants were 32 individuals who had at least five years of CCH experience and 44 controls. Results showed that CCH training benefited individuals' selective and divided attention but did not decrease their anxiety level. Moreover, the VBM analysis showed that long-term CCH training was mainly associated with smaller grey matter volumes (GMV) in the right precuneus/posterior cingulate cortex (PCC). No brain areas showed larger GMV in the CCH group than the control group. Using two sets of regions of interest (ROIs), one related to meditation and the other to handwriting, ROI analysis showed significant differences between the CCH and the control group only at the meditation-related ROIs, not at the handwriting-related ROIs. Finally, for the whole sample, the GMV of both the whole brain and the PCC were negatively correlated with selective attention and divided attention. The present study was cross-sectional and had a relatively small sample size, but its results suggested that CCH training might benefit attention and influence particular brain structure through mental processes such as meditation.

With the progressive deterioration of cyber threats, collecting cyber threat intelligence (CTI) from open-source threat intelligence publishing platforms (OSTIPs) can help information security personnel grasp public opinions with specific pertinence, handle emergency events, and even confront the advanced persistent threats. However, due to the explosive growth of information shared on multi-type OSTIPs, manually collecting the CTI has had low efficiency. Articles published on the OSTIPs are unstructured, leading to an imperative challenge to automatically gather CTI records only through natural language processing (NLP) methods. To remedy these limitations, this paper proposes an automatic approach to generate the CTI records based on multi-type OSTIPs (GCO), combing the NLP method, machine learning method, and cybersecurity threat intelligence knowledge. The experiment results demonstrate that the proposed GCO outperformed some state-of-the-art approaches on article classification and cybersecurity intelligence details (CSIs) extraction, with accuracy, precision, and recall all over 93%; finally, the generated records in the Neo4j-based CTI database can help reveal malicious threat groups.

The emergence of a large number of new malicious code poses a serious threat to network security, and most of them are derivative versions of existing malicious code. The classification of malicious code is helpful to analyze the evolutionary trend of malicious code families and trace the source of cybercrime. The existing methods of malware classification emphasize the depth of the neural network, which has the problems of a long training time and large computational cost. In this work, we propose the shallow neural network-based malware classifier (SNNMAC), a malware classification model based on shallow neural networks and static analysis. Our approach bridges the gap between precise but slow methods and fast but less precise methods in existing works. For each sample, we first generate n-grams from their opcode sequences of the binary file with a decompiler. An improved n-gram algorithm based on control transfer instructions is designed to reduce the n-gram dataset. Then, the SNNMAC exploits a shallow neural network, replacing the full connection layer and softmax with the average pooling layer and hierarchical softmax, to learn from the dataset and perform classification. We perform experiments on the Microsoft malware dataset. The evaluation result shows that the SNNMAC outperforms most of the related works with 99.21% classification precision and reduces the training time by more than half when compared with the methods using DNN (Deep Neural Networks).

Since microglia possess both neuroprotective and neurotoxic potential, they play a crucial role in the central nervous system (CNS). Excessive microglial activation induces inflammation-mediated neuronal damage and degeneration. At present, numerous herbal compounds are able to suppress neurotoxicity via inhibiting microglial activation. Therefore, many researchers focus on pharmacological inhibitors of microglial activation to ameliorate neurodegenerative disorders. Further work should concentrate on the exploration of new herbal compounds, which characteristically inhibit microglial neurotoxicity, rather than modulating neuroprotection alone. In this review, we summarize these herbal compounds, which in the past several years have been shown to exert potential neuroprotective activity by inhibiting microglial activation. The therapeutic targets and pharmacological mechanisms of these compounds have also been discussed.

Chinese calligraphic handwriting (CCH) is a traditional art form that requires high levels of concentration and motor control. Previous research has linked short-term training in CCH to improvements in attention and memory. Little is known about the potential impacts of long-term CCH practice on a broader array of executive functions and their potential neural substrates. In this cross-sectional study, we recruited 36 practitioners with at least 5 years of CCH experience and 50 control subjects with no more than one month of CCH practice and investigated their differences in the three components of executive functions (i.e., shifting, updating, and inhibition). Valid resting-state fMRI data were collected from 31 CCH and 40 control participants. Compared with the controls, CCH individuals showed better updating (as measured by the Corsi Block Test) and inhibition (as measured by the Stroop Word-Color Test), but the two groups did not differ in shifting (as measured by a cue-target task). The CCH group showed stronger resting-state functional connectivity (RSFC) than the control group in brain areas involved in updating and inhibition. These results suggested that long-term CCH training may be associated with improvements in specific aspects of executive functions and strengthened neural networks in related brain regions.

Oncomelania hupensis is the unique intermediate host of Schistosoma japonicum, which plays a key role during the transmission of schistosomiasis. It is mainly found in the Yangtze River valley and mountains or hills in southwest China. In this paper, we described 15 new microsatellite makers in O. hupensis. Polymorphism of each locus was assessed in 80 individuals from four wild populations (n = 20 per population). The number of alleles per locus ranged from 6 to 29, with an average of 15.8. The observed (HO) and expected (HE) heterozygosities varied from 0.397 to 0.851 and from 0.696 to 0.948, respectively. These microsatellite markers will be useful for population genetic studies and genome mapping in O. hupensis.

The biological effect of rare earth represents the dual natures of promoting cell proliferation and apoptosis. The research on the biological effect of rare earth compound has aroused wide concerns, but it remained unknown for the transmembrane and distribution under the action of rare earth oxide nanoparticle with cell as well as its biological effects. In the present data, it was firstly observed that the nano Eu2O3 entered the living HeLa cell by endocytosis using Laser Scanning Confocal Microscope. The distribution of nano Eu2O3 was in the cytoplasm around the nucleus. Moreover, we studied the effect of nano Eu2O3 on living cells under the condition of in vitro culture. The result showed that within the low concentration range (

Background: Factors affecting the effectiveness of electroencephalogram-based neurofeedback (EEG-NF) against the core symptoms of attention-deficit/hyperactivity disorder (ADHD) remain unclear. Methods: We searched the PubMed, Embase, Web of Science, ClinicalKey, Cochrane CENTRAL, ScienceDirect, and ClinicalTrials.gov databases from inception to August 2022 for randomized controlled trials (RCTs) on patients with ADHD involving outcome assessments of improvements on behavioural rating scales of inattention, hyperactivity/impulsivity, and global symptoms. Comparators included nonactive (e.g., wait list/treatment as usual) and active (e.g., cognitive training) controls. Results: Our analyses included 21 RCTs comprising 1261 participants. Our results demonstrated significantly better improvement in symptoms of inattention, hyperactivity/impulsivity and global symptoms of ADHD associated with EEG-NF than comparators from both proximal (p = 0.01, p = 0.02 and p = 0.01, respectively; e.g., parents) and distal (p = 0.01, p < 0.05 and p = 0.01; e.g., teachers) raters. Meta-regression revealed a positive association between therapeutic effects of EEG-NF and intelligence quotient (IQ) from observations of the most proximal raters. Subgroup analysis for studies combining 2 EEG-NF protocols showed better therapeutic effectiveness against symptoms of ADHD than those using a single NF protocol, whereas subgroup analysis adopting a doubleblind design failed to demonstrate superiority of EEG-NF to sham control. Moreover, therapeutic effectiveness of EEG-NF was significantly better when wait list/treatment as usual comparators were used compared with sham/placebo EEG-NF controls on subgroup analysis. Limitations: Our findings are limited by the lack of a double-blind design in most of the studies included in our analyses. Conclusion: Our results support the effectiveness of EEG-NF for improving inattention, hyperactivity/impulsivity, and global symptoms in patients with ADHD. The high risk of detection and performance bias warrants further study., Introduction Electroencephalogram-based neurofeedback (EEG-NF) is a form of biofeedback involving real-time visual or audio feedback based on EEG signals from sensors on the participant's scalp to reinforce normal brain function [...]

Background: No established pharmacological treatment is available for the core symptoms of autism spectrum disorder (ASD). This study aimed at investigating the efficacy of antidepressants for the core and associated symptoms of ASD. Methods: We searched PubMed, Embase, ClinicalKey, Cochrane CENTRAL, ScienceDirect, Web of Science and ClinicalTrials.gov using the keywords 'ASD' and 'antidepressants.' We searched from database inception to June 2021 for randomized controlled trials of antidepressant use in patients with ASD. We calculated pooled effect sizes based on a random-effects model. Results: Analysis of 16 studies with 899 participants showed improvements in restricted and repetitive behaviours (effect size = 0.27) and global symptoms (effect size = 1.0) in patients with ASD taking antidepressants versus those taking placebos (p [less than or equal to] 0.01). We found no differences between the 2 groups (p > 0.36) in terms of dropout rate (odds ratio [OR] = 1.17) or rate of study discontinuation because of adverse events (OR = 1.05). We also noted improvements in irritability and hyperactivity in the antidepressant group (Hedges g = 0.33 and 0.22, respectively, both p < 0.03). Subgroup analyses showed significant effects of medication type (i.e., clomipramine was better than SSRIs) and age (antidepressants were more effective in adults than in children or adolescents) on both restricted and repetitive behaviours and global improvement (p < 0.05). Meta-regression demonstrated that better therapeutic effects were associated with lower symptom severity and older age. Limitations: The small effect sizes and variations in treatment response that we found warrant further study. Conclusion: Our results supported the effectiveness of antidepressants for global symptoms and symptom subdomains of ASD, with tolerable adverse effects. Low symptom severity and adulthood were associated with better outcomes., Introduction Autism spectrum disorder (ASD) comprises a range of neurodevelopmental conditions that have their onset in childhood; ASD affects about 1% of the population and is a health burden for [...]

Background and Objective: The relationship between chronic daily headache (CDH), depression symptoms, and brain volume remains unclear. Methods: To investigate the effects of CDH on brain volume and the impact of depressive symptoms (DSs) as well as the effects of demography and medication overuse, PubMed, Embase, and Web of Science databases were systematically searched using appropriate keyword strings to retrieve observational studies from inception to May 2023. Results: Two distinct comparisons were made in CDH patients: (1) those with DSs versus their pain‐free counterparts and (2) those without DSs versus pain‐free controls. The first comprised nine studies enrolling 225 CDH patients with DSs and 234 controls. Beck depression inventory, Hamilton depression scale, and Hospital anxiety/depression scale were used to assess DSs, revealing significantly more DSs in CDH patients with DSs compared to their controls (all p < 0.05). Besides, the second analysed four studies involving 117 CDH patients without DSs and 155 comparators. Compared to CDH patients without DSs, those with DSs had a smaller brain volume than controls (p = 0.03). Furthermore, CDH patients with DSs who did not overuse medications showed a smaller right cerebral cortical volume than overusers (p = 0.003). A significant inverse correlation between female prevalence and brain volume (p = 0.02) was revealed using regression analysis. Conclusions: Pain‐induced persistent depressive symptoms not only incur structural alterations but also encompass affective‐motivational changes, involving medication use and gender‐specific health concerns. Significance: This study highlighted the importance of an integrated CDH treatment, emphasizing psychological interventions for the affective‐motivational component alongside pain management. [ABSTRACT FROM AUTHOR]

Background and Objectives: Probability discounting (PD), which refers to the process of adjusting the value of future probabilities when making decisions, is a method of measuring impulsive decision‐making; however, the relationship between PD and nicotine remains unclear. The current study aimed at investigating the significance of PD in individuals who smoke. Methods: According to Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines, we searched the PubMed, Embase, PsycINFO, and Web of Science databases for articles comparing individuals who smoke and their tobacco‐naïve controls using PD task as outcome measure from inception to May 2023. The main outcome was an overall difference in PD function, while subgroup analysis and meta‐regression were conducted to examine the analysis methods and the moderators of PD. Results: Fourteen studies in total involving 384 individuals who smoke and 493 controls (mean age = 24.32 years, range = 15.1–38.05 years) were analyzed. The effect of smoking on PD was significant (g = 0.51, p =.02). The discounting parameter from the equation, compared to the area under the curve, was more sensitive to estimating PD function (p =.01). Regression analysis showed positive correlations of PD with female percentage, age, and the number of probability options (all p <.04), but not with the number of choices at each probability and maximum reward magnitude (all p >.07). There was no significant publication bias across the eligible studies (p =.09). Conclusion and Scientific Significance: Our findings, which are the first to demonstrate a smaller PD (i.e., prone to risk‐taking) in individuals who smoke, shed light on the appropriate analysis method, gender effect, age, and probability options on the PD function. Answer questions and earn CME credit [ABSTRACT FROM AUTHOR]

We present the results from a series of herpetological surveys conducted in the Tengchong Section of Gaoligongshan National Nature Reserve, Yunnan Province, China between April 2014 and November 2018. A total of 59 species of amphibians and reptiles (one salamander, 30 batrachians, four lizards, and 24 snakes) were recorded during the surveys including three newly described amphibian species and 17 new records for Tengchong, 10 of which also represent new generic records for the area. Natural history notes of some little-known species are presented. Our survey results clearly demonstrate that the herpetofauna diversity of this mountain range is still underestimated and warrants further systematic study.

In the framework of a multi-source thermal model at the partonic level, we have analyzed transverse momentum spectra of hadrons measured by the ALICE Collaboration in proton–proton (pp or p–p) collisions at the center-of-mass energy of s=7 and 13 TeV, proton–lead (p–Pb) collisions at sNN=5.02 TeV, and lead–lead (Pb–Pb) collisions at sNN=2.76 TeV. For mesons (baryons), the contributions of two (three) constituent quarks are considered, in which each quark contributes to hadron transverse momentum to obey the revised phenomenological Tsallis transverse momentum distribution for Maxwell–Boltzmann particles (the TP-like function, in short) with isotropic random azimuthal angles. Three main parameters, namely, the revised index a0, effective temperature T, and entropy-related index n, are obtained, showing the same tendency for both small and large systems with respect to the centrality (or multiplicity) of events, the rest mass of hadrons, and the constituent mass of quarks.

In this paper, we consider integrated resource management for fog networks inclusive of intelligent energy perception, service level agreement (SLA) planning and replication-based hotspot offload (RHO). In the beginning, we propose an intelligent energy perception scheme which dynamically classifies the fog nodes into a hot set, a warm set or a cold set, based on their load conditions. The fog nodes in the hot set are responsible for a quality of service (QoS) guarantee and the fog nodes in the cold set are maintained at a low-energy state to save energy consumption. Moreover, the fog nodes in the warm set are used to balance the QoS guarantee and energy consumption. Secondly, we propose an SLA mapping scheme which effectively identifies the SLA elements with the same semantics. Finally, we propose a replication-based load-balancing scheme, namely RHO. The RHO can leverage the skewed access pattern caused by the hotspot services. In addition, it greatly reduces communication overheads because the load conditions are updated only when the load variations exceed a specific threshold. Finally, we use computer simulations to compare the performance of the RHO with other schemes under a variety of load conditions. In a word, we propose a comprehensive and feasible solution that contributes to the integrated resource management of fog networks.

Cerebral edema, a well-known feature of acute liver disease, can occur in cirrhotic patients regardless of hepatic encephalopathy (HE) and adversely affect prognosis. This study characterized and correlated functional HE abnormalities in the brain to cerebral edema using resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI). Forty-one cirrhotic patients (16 without HE, 14 minimal HE, 11 overt HE) and 32 healthy controls were assessed. The HE grade in cirrhotic patients was evaluated by the West Haven criteria and neuro-psychological examinations. Functional connectivity correlation coefficient (fc-CC) of the default mode network (DMN) was determined by rs-fMRI, while the corresponding mean diffusivity (MD) was obtained from DTI. Correlations among inter-cortical fc-CC, DTI indices, Cognitive Ability Screening Instrument scores, and laboratory tests were also analyzed. Results showed that gradual reductions of HE-related consciousness levels, from "without HE" or "minimal HE" to "overt HE", correlated with decreased anterior-posterior fc-CC in DMN [F(4.415), p = 0.000)]. The MD values from regions with anterior-posterior fc-CC differences in DMN revealed significant differences between the overt HE group and other groups. Increased MD in this network was inversely associated with decreased fc-CC in DMN and linearly correlated with poor cognitive performance. In conclusion, cerebral edema can be linked to altered cerebral temporal architecture that modifies both within- and between-network connectivity in HE. Reduced fc-CC in DMN is associated with behavior and consciousness deterioration. Through appropriate targets, rs-fMRI technology may provide relevant supplemental information for monitoring HE and serve as a new biomarker for clinical diagnosis.