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Major depression is the largest single contributor to suicide, and anxiety symptoms are associated with the severity of depression and suicidality. It is important to explore biomarkers of anxiety and suicidal ideation in major depression. In this study we hypothesized that the volume of subregions of the amygdala might be indicators of anxiety and suicidal ideation in patients with major depression.We recruited 59 drug-naïve patients with first-episode depression who scored17 on the Hamilton Rating Scale for depression, and 30 healthy controls to participate in a magnetic resonance imaging study. We examined the volume of sub-regions of the amygdala thought to be involved in processing anxious emotion in the depression and healthy control groups. We performed pair-wise comparisons of amygdala subfield volumes in patients with depression and healthy controls with an analysis of variance. We used logistic regression to test the relationship between suicidal ideation and anxious character with the volume of subregions of the amygdala.1) We found a significant difference in the volumes of the left amygdala (P = 0.003) and right amygdala (P = 0.001) between the two groups. There are significant differences in the volumes of the sub-region of the left amygdala. 2) The volume of the left lateral nucleus (P0.001), basal nucleus (P0.001), accessory basal nucleus (P0.05), left Paralaminar-nucleus (P0.001), right lateral-nucleus (P0.05), right basal-nucleus (P0.05), right anterior-amygdaloid area AAA (P0.05), right paralaminar-nucleus (P0.001) in the depression group are larger than healthy controls, however the volumes of the central-nucleus (P0.05), medial-nucleus (P0.001) in both sides are decreased in the major depression group. 3) There is a significantly larger volume of right medial nucleus in the suicidal ideation group comparing the hopelessness (P = 0.026), and the depressive patients without hopeless thoughts (P = 0.004). 4) We found a negative relation between the left basal nucleus and anxiety (OR: 0.940, 95%CI: 0.891-0.991), and a positive relation between the accessory basal nucleus on the left side and anxiety (OR: 1.007, 95%CI: 1.002-1.158).We were not able to examine the effects of gender or age. The changes of amygdala volume in patients with depression were not followed up. Our sample size was such that independent replication is needed to confirm the robustness of our results.The volumes of the basal nucleus in both sides are increased in depressed patients while the volumes of the central-nucleus, medial-nucleus bilaterally are reduced in the major depression group. Among the subregions, the volume of right medial nucleus might be the biomarkers for suicidal ideation in depressive patients.

Little is known how often depressive episodes are accompanied by gastrointestinal symptoms in major depressive disorders (MDD). The authors sought to determine the frequency and clinical correlates of gastrointestinal symptoms during episodes of depressive disorder.3,256 MDD patients from the National Survey on Symptomatology of Depression (NSSD), which was designed to investigate the magnitude of symptoms of current major depressive episodes in China, were enrolled and assessed for gastrointestinal symptoms in this study. Illness characteristics were compared in patients with a different frequency of gastrointestinal symptoms. Pearson correlation analysis and multiple linear regression analysis were employed to investigate the associations between gastrointestinal symptoms and psychological characteristics in the patients.More than 70% of the subjects with depressive episodes had concomitant gastrointestinal symptoms. A higher frequency of gastrointestinal symptoms was associated with an increased risk of suicide ideation, suicide attempts, anxious mood, depressed mood, insomnia, feeling a failure, poor concentration, body pain, hopelessness, anger, and irritability. Pearson correlation analysis indicated moderate but significant associations between gastrointestinal symptoms and psychological characteristics (p0.001). Multiple linear regression analysis showed that suicide ideation (β=0.161, p0.001), anxiety mood (β=0.166, p = 0.006), insomnia (β =0.262, p0.001), anger (β=0.144, p0.001), feeling a failure (β =0.365, p0.001), and body pain (β=0.581 p0.001) were independently associated with gastrointestinal symptoms in MDD patients.Gastrointestinal symptoms were one of the most prevalent clinical presentations of MDD. The associations between gastrointestinal symptoms and psychological characteristics may prove useful in expanding our understanding of how gastrointestinal symptoms contributes to MDD.

Nutritional supplementations have been widely used as adjunctive treatments for schizophrenia. However, among these supplementations, of which the most beneficial is currently unknown. This study aimed to compare and rank the effectiveness of nutritional supplementations in the adjunctive treatments of schizophrenia. The four nutritional supplementations evaluated were: 1) folate acid or vitamin B12; 2) vitamin D; 3) N-acetyl cysteine (NAC); 4) Omega-3 polyunsaturated fatty acid, including docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). 17 eligible RCTs with 1165 participants were included in this network meta-analysis based on study criteria. NAC supplementation was significantly more efficacious than folic acid or vitamin B12 [MD (95% CI): -6.6 (-10.8, -2.4)] and omega-3 polyunsaturated fatty acid [MD (95% CI): -5.1(-9.9, -0.8)] supplementation in the term of PANSS score changes. There were no significant differences in the PANSS score changes between NAC and vitamin D [MD (95% CI): -5.2 (-10.9, 0.5)] supplementations. The estimated ranking probabilities of treatments showed that NAC might be the most effective adjunctive intervention over all nutritional supplementations. These results indicate that NAC could improve PANSS score and it may be among the most effective nutritional supplementations in schizophrenia patients.

Background In spite of numerous options, the most efficacious treatment for major depressive disorder (MDD) remains elusive. Algorithm-guided treatments (AGTs) are proposed to address inadequate remission and optimize treatment delivery. This study aimed to evaluate the clinical benefit of AGTs for MDD, and to explore specific moderators of treatment outcomes for individual patients. Methods The study recruited 987 patients with MDD across eight hospitals who were randomly assigned to AGT with escitalopram (AGT-E), AGT with mirtazapine (AGT-M), or treatment-as-usual (TAU). The outcomes were symptom remission, response rate, early improvement rate, subsymptom clusters improvement over time, the mean time to first remission, relapse rate at 6-months posttreatment follow-up, quality of life (QOL), and adverse events. Resutls No significant differences were observed across groups in outcome, except that TAU showed significantly poorer QOL, higher relapse rates at 6-months posttreatment follow-up, and marginally significantly worse maximal burden of adverse events than the AGT groups. After 6 weeks of treatment initiation, remission rate did not significantly increase with extended treatment. AGT-M outperformed the TAU and AGT-E in treating sleep symptoms. AGT-E was less effective than AGT-M and TAU in patients with severe depression and somatic symptoms (DSSS). The superiority of TAU over AGTs was observed in recurrent MDD patients. Conclusion Although the superiority of AGTs over TAU was limited by failure of alternative subsequent treatment, AGTs outperformed in QOL and relapse rate. Types of disease episode and DSSS were regarded as specific moderators in treatment of depression. These findings might contribute to future research on targeted antidepressant treatment.

Purpose Early improvement in major depressive disorder is defined as a reduction of ≥20% in the 17-item Hamilton Depression Rating Scale (HAM-D-17) score at the second week after initiation of treatment, predicting long-term treatment response. However, there remains no effective strategy for switching medications when a patient fails to reach early improvement at the second week. This study focused on the predictive value of early symptom changes in each item of the HAM-D-17 scale for treatment response to selective serotonin reuptake inhibitor (SSRI) monotherapy and to provide a reference for switching antidepressants to enhance early treatment efficacy. Patients and methods Our study was an observational, real-world study that enrolled 90 treatment-naive patients experiencing their first episode of major depressive disorder in the outpatient department of Huashan Hospital. Patients who did not achieve the threshold of early improvement in the second week after starting treatment were switched to alternative SSRI monotherapy. Patient follow-up occurred at 2, 4, 8, and 12 weeks after the initiation of treatment. We analyzed the relationship between the change in each symptom on the HAM-D-17 scale and treatment efficacy. Results Early improvement predicted the treatment response at 12 weeks (χ2=19.249, P 999.999); treatment-emergent headache and tremor were associated with treatment efficacy (t=-9.521, P

Biodegradation has been considered as an ideal technique for total petroleum hydrocarbon (TPH) contamination, but its efficiency is limited by its application in the field. Herein, an original TPH-degrading strain, SCYY-5, was isolated from contaminated oil sludge and identified as Acinetobacter sp. by 16S rDNA sequence analysis. The biological function of the isolate was investigated by heavy metal tolerance, carbon, and nitrogen source and degradation tests. To enhance its biodegradation efficiency, the response surface methodology (RSM) based on a function model was adopted to investigate and optimize the strategy of microbial and environmental variables for TPH removal. Furthermore, the performance of the system increased to 79.94% with the further addition of extra nutrients, suggesting that the RSM and added nutrients increased the activity of bacteria to meet the needs of the co-metabolism matrix during growth or degradation. These results verified that it is feasible to adopt the optimal strategy of combining bioremediation with RSM to improve the biodegradation efficiency, for contaminated oil sludge.

This study reported a facile method to synthesize novel pH-sensitive nanoparticle based on nanocellulose, involving cross-linking polyethyleneimine and glutaraldehyde. The adsorbent was characterized and found to be sensitive to the solution pH, especially at pH 3. Additionally, the biosorbent exhibited rapid adsorption during the initial 10 min and the As(V) adsorption capacity of the nanoparticles reached approximately 255.19 mg g−1 at pH 3, which was five times greater than that achieved with the As(V) solution at its initial pH (44.33 mg g−1). To reflect its performance in actual acidic wastewater, the effects of coexisting anions were also investigated, showing that these anions had little influence on As(V) adsorption. Meanwhile, the adsorbent displayed excellent performance even after eight regeneration cycles. This novel material demonstrates enormous potential for the removal of arsenic contaminants and for the development of pH-sensitive materials.

Background Early improvement (EI) following treatment with antidepressants is a widely reported predictor to the treatment response. This study aimed to identify the resting-state functional connectivity (rs-FC) and its related clinical features that link the treatment response at the time of EI. Methods This study included 23 first-episode treatment-naive patients with MDD. After 2 weeks of antidepressant treatment, these patients received 3.0 Tesla resting-state functional magnetic resonance imaging scanning and were subgrouped into an EI group (N = 13) and a non-EI group (N = 10). Using the anterior insula (rAI) as a seed region, this study identified the rs-FC that were associated with both EI and the treatment response at week 12, and further tested the associations of the identified rs-FC with either the clinical features or the early symptom improvement. Results Rs-FC between rAI and the left dorsolateral prefrontal cortex (dlPFC) was associated with EI (t21 = −6.091, p = 0.022 after FDR correction for multiple comparisons). This rs-FC was also associated with an interaction between EI and the treatment response at the week 12 (t21 = −5.361, p = 6.37e-5). Moreover, among the clinical features, this rs-FC was associated with the early symptom improvement in the insomnia, somatic symptoms, and anxiety symptoms, and these early symptom improvements were associated with the treatment response. Conclusion Rs-FC between the rAI and the left dlPFC played a crucial role in the early antidepressant effect, which linked the treatment response. The early treatment effect relating to rAI may represent an early symptom improvement in self-perceptual anxiety, somatic symptoms and insomnia.

By using the "bridge joint" effect of iron ions, cellulose nanocrystal-containing high-performance adsorbents were synthesized via coprecipitation method, which enhanced the cross-linking action of cellulose nanocrystal and polyethyleneimine. The morphology, specific surface area, surface chemistry and chemical valence of the adsorbents were characterized by SEM, FTIR, BET and XPS. According to the results, the iron ions successfully connect the two dispersed polymers together, inducing a large number of O-Fe-O bonds and, providing more adsorption active sites for the removal of seriously polluted and high-toxicity As(III)/As(V). Furthermore, the arsenic removal performance of the adsorbents was studied, and the adsorption mechanism was revealed according to the spectral characteristics of the chemical components. Of note, the synthesized iron-containing adsorbents are suitable for a wide pH range, which may offer a new application for nanocellulose in the treatment of arsenic pollution.

This research was designed to investigate patient-reported and doctor-reported reasons for the discontinuation of pharmacological treatment in Chinese patients with major depressive disorder (MDD), which was part of the National Survey on Symptomatology of Depression (NSSD) from 2014 to 2015.This cross-sectional study included 649 patients who had discontinued antidepressant medications and 711 patients who had remained on them, selected from a group of 3516 candidates who have had at least one depressive episode. Differences in the two groups' sociodemographic factors, clinical characteristics, medication use, and self-reported reasons for drug discontinuation were compared via Student's t-test or chi-square test. Logistic regression analysis was then used to determine the association of all non-subjective dichotomous and ordinal categorical variables, including the additional 63 items of our physician-evaluated symptomatic assessment, with drug compliance.Compared to the spontaneous drug discontinuation (SDD) group, the drug adherence (DA) group had significantly lower rates of the following: family history of mental disease (9.0% vs 13.6%), highest level of education achieved being post-graduate or above (1.6% vs 4.7%), smoking (5.8% vs 9.7%), and other health problems (33.9% vs 42.4%) (p's 0.05). On the other hand, first-episode depression (48.5% vs 21.9%) and taking of mood stabilizer(s) (8.3% vs 5.6%) were higher in the former group than in the latter (p's 0.05). Logistic Regression Analysis showed that five symptoms, such as depressed mood, were correlated positively with SDD, while another six symptoms, such as psychomotor retardation, were correlated negatively with it. The receiver operating characteristic (ROC) curve of this model yielded an area under the curve (AUC) of 0.701 (95% CI, 0.673-0.729). Notably, there were three main reasons given by patients in the DA group as to why they discontinued their medication(s): (1) concern about long-term side effects (36.1%), (2) no perceived need for taking said medication(s) long-term (34.2%), and (3) believing oneself to have been cured completely (30.0%).The aforementioned factors may affect patient compliance and elicit maladaptive thinking even from patients with good educational backgrounds, increasing the risk of drug discontinuation. Compliance of pharmacological treatment might be improved by increasing clarification and elucidation of different symptom clusters to the patient and combating the main reasons for drug discontinuation.

The colorimeter method is widely used to identify the color and grade of a cotton sample, but this method does not give information about the variation of color within the sample. We have conducted an investigation using an image analysis method to study the intra-sample distribution and variation in cotton color. High-resolution color images of cotton samples were obtained using a color scanner. For each image the Rd and + b values of the image and specific sub-areas within it were computed to analyze the color distribution. Intra- and inter-sample variations in Rd and + b values and color grade were compared with those obtained by the HVI system. The results show that for the same cotton substrate, although the variations among the color grades of different samples (replicates) may be very small, intra-sample color variations are evident, the colors of the sub-areas being distributed over a range of areas of the cotton color chart. In other words, cotton samples of the same overall color grade may exhibit different intra-sample color variations and distribution. A description of the intra-sample color variations and distributions obtainable using an image analysis method may allow a more comprehensive evaluation of color characteristics on cotton.

Fiber length is one of the key properties of cotton and has important influences on yarn production and yarn quality. Various parameters have been developed to characterize cotton fiber length in the past decades. This study was carried out to investigate the effects of these parameters and their combinations on yarn properties. Linear regression models with different numbers of fiber length parameters and their combinations were developed for predicting ring and open-end (OE) spun yarns’ properties. The R2 and Mallows’ Cp plots of the models were compared for model selections. The results indicate that, for predicting a yarn property, a model usually involves more than three length parameters to achieve better prediction when considering the R2 and Cp values. This may be because only one single length parameter cannot sufficiently represent fiber length characteristics. The results also show that the variations in fiber length distributions play important roles in predicting yarn properties, such as strength and irregularity. The best prediction models for the properties of different yarns (ring, OE) include different combinations of length parameters. Not all yarn properties can be well predicted by linear regression models with length parameters: other fiber properties (strength, micronaire, etc.) need to be included to further improve the models.

Background: Although the diagnosis of melancholia has had a long history, the validity of the current DSM-IV definition remains contentious. We report here the first detailed comparison of melancholic and nonmelancholic major depression (MD) in a Chinese population examining in particular whether these two forms of MD differ quantitatively or qualitatively. Methods: DSM-IV criteria for melancholia were applied to 1,970 Han Chinese women with recurrent MD recruited from 53 provincial mental health centers and psychiatric departments of general medical hospitals in 41 cities. Statistical analyses, utilizing Student's t-tests and Pearson's χ(2) , were calculated using SPSS 13.0. Results: Melancholic patients with MD were distinguished from nonmelancholic by being older, having a later age at onset, more episodes of illness and meeting more A criteria. They also had higher levels of neuroticism and rates of lifetime generalized anxiety disorder, panic disorder, and social and agoraphobia. They had significantly lower rates of childhood sexual abuse but did not differ on other stressful life events or rates of MD in their families. Discussion: Consistent with most prior findings in European and US populations, we find that melancholia is a more clinically severe syndrome than nonmelancholic depression with higher rates of comorbidity. The evidence that it is a more "biological" or qualitatively distinct syndrome, however, is mixed. Depression and Anxiety 0:1-6, 2011. © 2011 Wiley Periodicals, Inc. Language: en

The beard method is used for sampling cotton fibers to generate fibrograms from which length parameters can be obtained. It is the sampling method used by the Uster High Volume Instrument (HVI™). A fundamental issue of this sampling method is its bias since the mathematical computation to obtain length parameters is quite different. There have been different assumptions regarding the bias of the beard sampling method. In our experiments, we have seen discrepancies in measurements that cannot be explained as length‐biased or unbiased, especially in the short fiber region. We report a fundamental research, including experimental and theoretical analysis, and computer simulations, that reveals the bias due to this sampling method. We find that the beard sampling method as used in HVI is not completely length‐biased; fibers sampled by using this method are similar to the original fibers except in the short fiber region. Short fiber content (SFC) of the sampled fiber is lower than that of the original fiber, a...

The quantity of short fibers in a cotton sample is an important cotton quality parameter. Short cotton fibers have detrimental impacts on yarn production performance and yarn quality. There are different parameters for characterizing the amount of short fibers in a cotton sample. The most widely used parameter is short fiber content (SFC). However, SFC has a significant shortcoming of very high measured variation. An investigation was carried out to compare the short fiber parameters to find a parameter that has lower variation and predicts yarn properties similarly as SFC does, including SFC defined at 0.5 inch length, SFC defined at 16 mm length, lower half mean length (LHML), floating fiber index (FFI), floating fiber percentage (FFP), and relative short fiber content (Rel. SFC). Based on our experimental data, we found that LHML had the lowest variation, was highly correlated with SFC, and predicted yarn properties similarly as SFC did. Therefore, LHML is a suitable alternative to short fiber content.

Dynamic electrostatic generation and dissipation on polymer surfaces are of great importance for materials such as yarns and films. To support fundamental research in this area, innovative devices and experimental techniques that can lead to a better understanding of these phenomena are of obvious academic and industrial interest. This paper reports the development of devices for testing the electrostatic generation/dissipation properties of polymer surfaces. These devices include a tester for assessing moving yarns, a high-resistance system to measure the yarn's linear resistance, a tester for evaluating stationary fabrics or films while rubbing against a moving surface and a contact charge tester for investigating charge generated by contacting of two surfaces. These devices enable the study of the influences of relative moving speed, yarn tension, electrostatic charge properties of yarns, as well as contact pressure, rubbing speed, number of rubbings or contacts on the static charge properties of films.

We developed a system to align fibres by using electrostatic forces to form fibreweb with desired fibre orientation. The purpose of developing such a system is to investigate an innovative mechanism of forming disc shape fibrewebs with engineered fibre orientation for the industrial fields such as carbon fibre reinforced brake discs and abrasive wheels for metal surface finishing. We provide computer models for simulating the process of transporting fibres in electrostatic field and laying them down to a fibre-collecting surface. The model reveals the effects of electrostatic field properties such as voltage and electrodes geometry on fibre orientation distribution. We also developed visualisation programmes to help display and analyse resultant data. Our experimental results and theoretical simulations are in a good agreement and show that the development of a new generation of non-woven fabrics with engineered fibre orientation distribution is achievable with the correct levels of the independent parame...

Background: Major depressive disorder (MDD) is a common mental illness with high lifetime prevalence close to 20%. Positron emission tomography (PET) studies have reported decreased prefrontal, insular and limbic cerebral glucose metabolism in depressed patients compared with healthy controls. However, the literature has not always been consistent. To evaluate current evidence from PET studies, we conducted a voxel-based meta-analysis of cerebral metabolism in MDD. Method: Data were collected from databases including PubMed and Web of Science, with the last report up to April 2013. Voxel-based meta-analyses were performed using the revised activation likelihood estimation (ALE) software. Results: Ten whole-brain-based FDG-PET studies in MDD were included in the meta-analysis, comprising 188 MDD patients and 169 healthy controls. ALE analyses showed the brain metabolism in bilateral insula, left lentiform nucleus putamen and extra-nuclear, right caudate and cingulate gyrus were significantly decreased. However, the brain activity in right thalamus pulvinar and declive of posterior lobe, left culmen of vermis in anterior lobe were significantly increased in MDD patients. Conclusion: Our meta-analysis demonstrates the specific brain regions where possible dysfunctions are more consistently reported in MDD patients. Altered metabolism in insula, limbic system, basal ganglia, thalamus, and cerebellum and thus these regions are likely to play a key role in the pathophysiology of depression.

High-speed airflow is widely used in many processes in the textile industry. Even though the interactions between fibers and airflows have attracted many researchers' interest, there have been few published studies that focus on the computer modeling of fiber motion in airflow fields. This research was aimed at developing a model that can effectively simulate the interactions between fibers and airflows, thus providing a clearer understanding of the behavior of textile fibers in certain processing machines. A three-dimensional model of the aerodynamic component of a rotor spinning machine was established. A commercial computation fluid dynamics (CFD) software package was used to compute the airflow field of this model and the results were analyzed to study the airflow field's characteristics. Resultant data were used as input for the fiber movement model by using a one-way coupling method. A mathematical model of fiber movement was developed, including numerical methods and visualization programs that were used to solve the model and illustrate fiber movements. The results obtained were studied and compared under different initial and boundary conditions. This research successfully demonstrates the effectiveness of computer modeling for studying the fiber motion in high-speed airflow. It provides a better understanding of fiber behavior in airflow fields and its potential and prospect in the research of textile processes, in which airflow plays an important role, are very promising.

Background: The aim of this study was to conduct a meta-analysis so we could evaluate the impact of antipsychotics on the P50 ratio in Chinese schizophrenia patients. Methods: Data were collected from the following databases: PubMed, China Biological Medicine Database, China National Knowledge Infrastructure, Cochrane Library and Elsevier Science Direct, with the latest report up to May 2011. An effect size with a 95% confidence interval (CI) was used to assess the strength of various effects of antipsychotics on P50 ratio in the patients. Results: A total of six studies including 315 and 285 schizophrenia patients at the baseline and endpoint, respectively. Overall, no significant effect of these medicines on the P50 ratio was found (overall effect z=1.03, p=0.30; heterogeneity: Chi²=2.81, df=8, p=0.95, I²=0%). In subgroup analysis by drug, we did not find any significant effects on P50 ratio in either first-generation antipsychotics (effect z=0.92, p=0.36; heterogeneity: Chi²=0.00, df=1, p=0.98, I²=0%) or second-generation antipsychotics (effect z=0.55, p=0.58; heterogeneity: Chi²=2.38, df=5, p=0.79, I²=0%). Conclusion: Our meta-analysis suggests that neither the first-generation nor the second-generation antipsychotics had any significant effects on P50 ratio in Chinese patients with schizophrenia.

Current web formation technologies used by the nonwovens industry do not provide positive control over fiber orientation and it is difficult to generate lightweight webs from staple fibers with these processes. The aim of this research is to develop new methods of fiberweb formation using electrostatic force, where orientation and orientation distribution of staple fibers are positively controlled. We carried out theoretical analysis and constructed computer models for this approach. Our analysis considered the effects of geometric configurations of fiber feeding and web formation zone, electrostatic and airflow field parameters, and the fiber's initial conditions at the feeding zone on fiber orientation. The theoretical analyses and computer modeling of the electrostatic web forming process provide better insights into this method and serve as a powerful tool for engineering development. Numerical results were obtained and presented for a range of processing variables.