The functional implication of ATF6α in castration-resistant prostate cancer cells.

Stress in the endoplasmic reticulum (ER) may perturb proteostasis and activates the unfolded protein response (UPR). UPR activation is frequently observed in cancer cells and is believed to fuel cancer progression. Here, we report that one of the three UPR sensors, ATF6α, was associated with prostate cancer (PCa) development, while both genetic and pharmacological inhibition of ATF6α impaired the survival of castration-resistance PCa (CRPC) cells. Transcriptomic analyses identified the molecular pathways deregulated upon ATF6α depletion, and also discovered considerable disparity in global gene expression between ATF6α knockdown and Ceapin-A7 treatment. In addition, combined analyses of human CRPC bulk RNA-seq and single-cell RNA-seq (scRNA-seq) public datasets confirmed that CRPC tumors with higher ATF6α activity displayed higher androgen receptor (AR) activity, proliferative and neuroendocrine (NE) like phenotypes, as well as immunosuppressive features. Lastly, we identified a 14-gene set as ATF6α NE gene signature with encouraging prognostic power. In conclusion, our results indicate that ATF6α is correlated with PCa progression and is functionally relevant to CRPC cell survival. Both specificity and efficacy of ATF6α inhibitors require further refinement and evaluation.

Temporal network of experience sampling methodology identifies sleep disturbance as a central symptom in generalized anxiety disorder.

BACKGROUND: A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom. METHODS: A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network. RESULTS: In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality. CONCLUSIONS: This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

Digital Microfluidics for Microproteomic Analysis of Minute Mammalian Tissue Samples Enabled by a Photocleavable Surfactant.

Proteome profiles of precious tissue samples have great clinical potential for accelerating disease biomarker discovery and promoting novel strategies for early diagnosis and treatment. However, tiny clinical tissue samples are often difficult to handle and analyze with conventional proteomic methods. Automated digital microfluidic (DMF) workflows facilitate the manipulation of size-limited tissue samples. Here, we report the assessment of a DMF microproteomics workflow enabled by a photocleavable surfactant for proteomic analysis of minute tissue samples. The surfactant 4-hexylphenylazosulfonate (Azo) was found to facilitate fast droplet movement on DMF and enhance the proteomics analysis. Comparisons of Azo and n-Dodecyl ß-d-maltoside (DDM) using small samples of HeLa digest standards and MCF-7 cell digests revealed distinct differences at the peptide level despite similar results at the protein level. The DMF microproteomics workflow was applied for the sample preparation of ∼3 µg biopsies from murine brain tissue. A total of 1969 proteins were identified in three samples, including established neural biomarkers and proteins related to synaptic signaling. Going forward, we propose that the Azo-enabled DMF workflow has the potential to advance the practical clinical application of DMF for the analysis of size-limited tissue samples.

Comparison of Database Searching Programs for the Analysis of Single-Cell Proteomics Data.

Single-cell proteomics is emerging as an important subfield in the proteomics and mass spectrometry communities, with potential to reshape our understanding of cell development, cell differentiation, disease diagnosis, and the development of new therapies. Compared with significant advancements in the "hardware" that is used in single-cell proteomics, there has been little work comparing the effects of using different "software" packages to analyze single-cell proteomics datasets. To this end, seven popular proteomics programs were compared here, applying them to search three single-cell proteomics datasets generated by three different platforms. The results suggest that MSGF+, MSFragger, and Proteome Discoverer are generally more efficient in maximizing protein identifications, that MaxQuant is better suited for the identification of low-abundance proteins, that MSFragger is superior in elucidating peptide modifications, and that Mascot and X!Tandem are better for analyzing long peptides. Furthermore, an experiment with different loading amounts was carried out to investigate changes in identification results and to explore areas in which single-cell proteomics data analysis may be improved in the future. We propose that this comparative study may provide insight for experts and beginners alike operating in the emerging subfield of single-cell proteomics.

Trace Sample Proteome Quantification by Data-Dependent Acquisition without Dynamic Exclusion.

Despite continuous technological improvements in sample preparation, mass-spectrometry-based proteomics for trace samples faces the challenges of sensitivity, quantification accuracy, and reproducibility. Herein, we explored the applicability of turboDDA (a method that uses data-dependent acquisition without dynamic exclusion) for quantitative proteomics of trace samples. After systematic optimization of acquisition parameters, we compared the performance of turboDDA with that of data-dependent acquisition with dynamic exclusion (DEDDA). By benchmarking the analysis of trace unlabeled human cell digests, turboDDA showed substantially better sensitivity in comparison with DEDDA, whether for unfractionated or high pH fractionated samples. Furthermore, through designing an iTRAQ-labeled three-proteome model (i.e., tryptic digest of protein lysates from yeast, human, and E. coli) to document the interference effect, we evaluated the quantification interference, accuracy, reproducibility of iTRAQ labeled trace samples, and the impact of PIF (precursor intensity fraction) cutoff for different approaches (turboDDA and DEDDA). The results showed that improved quantification accuracy and reproducibility could be achieved by turboDDA, while a more stringent PIF cutoff resulted in more accurate quantification but less peptide identification for both approaches. Finally, the turboDDA strategy was applied to the differential analysis of limited amounts of human lung cancer cell samples, showing great promise in trace proteomics sample analysis.

Integrated Assembly and Photopreservation of Topographical Micropatterns.

Micromanipulation techniques that are capable of assembling nano/micromaterials into usable structures such as topographical micropatterns (TMPs) have proliferated rapidly in recent years, holding great promise in building artificial electronic and photonic microstructures. Here, a method is reported for forming TMPs based on optoelectronic tweezers in either "bottom-up" or "top-down" modes, combined with in situ photopolymerization to form permanent structures. This work demonstrates that the assembled/cured TMPs can be harvested and transferred to alternate substrates, and illustrates that how permanent conductive traces and capacitive circuits can be formed, paving the way toward applications in microelectronics. The integrated, optical assembly/preservation method described here is accessible, versatile, and applicable for a wide range of materials and structures, suggesting utility for myriad microassembly and microfabrication applications in the future.

Network structure of depression and anxiety symptoms in Chinese female nursing students.

BACKGROUND: Comorbidity between depressive and anxiety disorders is common. From network perspective, mental disorders arise from direct interactions between symptoms and comorbidity is due to direct interactions between depression and anxiety symptoms. The current study investigates the network structure of depression and anxiety symptoms in Chinese female nursing students and identifies the central and bridge symptoms as well as how other symptoms in present network are related to depression symptom "thoughts of death". METHODS: To understand the full spectrum of depression and anxiety, we recruited 776 Chinese female nursing students with symptoms of depression and anxiety that span the full range of normal to abnormal. Depression symptoms were measured by Patient Health Questionnaire-9 while anxiety symptoms were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Network analysis was used to construct networks. Specifically, we computed the predictability, expected influence and bridge expected influence for each symptom and showed a flow network of "thoughts of death". RESULTS: Nine strongest edges existed in network were from the same disorder. Four were between depression symptoms, like "sleep difficulties" and "fatigue", and "anhedonia" and "fatigue". Five were between anxiety symptoms, like "nervousness or anxiety" and "worry too much", and "restlessness" and "afraid something will happen". The symptom "fatigue", "feeling of worthlessness" and "irritable" had the highest expected influence centrality. Results also revealed two bridge symptoms: "depressed or sad mood" and "irritable". As to "thoughts of death", the direct relations between it and "psychomotor agitation/retardation" and "feeling of worthlessness" were the strongest direct relations. CONCLUSIONS: The current study highlighted critical central symptoms "fatigue", "feeling of worthlessness" and "irritable" and critical bridge symptoms "depressed or sad mood" and "irritable". Particularly, "psychomotor agitation/retardation" and "feeling of worthlessness" were identified as key priorities due to their strongest associations with suicide ideation. Implications for clinical prevention and intervention based on these symptoms are discussed.

The relations between different components of intolerance of uncertainty and symptoms of generalized anxiety disorder: a network analysis.

BACKGROUND: Intolerance of uncertainty (IU) is considered as a specific risk factor in the development and maintenance of generalized anxiety disorder (GAD). Yet, researches have investigated the relations between IU and GAD (or worry) using total scores on self-report measures. This ignores that there are different components exist in IU and the heterogeneity of GAD symptoms. In the present study, we explored the relations among different components of IU and symptoms of GAD. METHODS: A dimensional approach which take individual differences into consideration in different components of IU along a full range of normal to abnormal symptom severity levels of GAD were used in this study. Components of IU were measured by 12-item Intolerance of Uncertainty Scale and symptoms of GAD were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Regularized partial-correlation network was estimated using cross-sectional data from 624 university students. RESULTS: Four strongest edges are between components of IU, like "Unforeseen events upset me greatly" and "It frustrates me not having all the information I need". Two strongest edges are between symptoms of GAD, like "Being so restless that it is hard to sit still" and "Feeling afraid as if something awful might happen". Symptom "Worrying too much about different things" and component "It frustrates me not having all the information I need" have the highest expected influences in the present network. In the community of IU, component "It frustrates me not having all the information I need" has the highest bridge expected influence. And in the community of GAD, symptoms "Worrying too much about different things" and "Not being able to stop or control worrying" have the highest bridge expected influence. CONCLUSIONS: This study reveals potential pathways between different components of IU and various symptoms of GAD. Understanding how putative risk factors such as different components of IU are related to symptoms of GAD may provide some references for related preventions and interventions, such as targeting component "It frustrates me not having all the information I need" may be more effective at reducing symptoms of GAD than targeting other components of IU.

Robust Tightly Coupled Pose Measurement Based on Multi-Sensor Fusion in Mobile Robot System.

Currently, simultaneous localization and mapping (SLAM) is one of the main research topics in the robotics field. Visual-inertia SLAM, which consists of a camera and an inertial measurement unit (IMU), can significantly improve robustness and enable scale weak-visibility, whereas monocular visual SLAM is scale-invisible. For ground mobile robots, the introduction of a wheel speed sensor can solve the scale weak-visibility problem and improve robustness under abnormal conditions. In this paper, a multi-sensor fusion SLAM algorithm using monocular vision, inertia, and wheel speed measurements is proposed. The sensor measurements are combined in a tightly coupled manner, and a nonlinear optimization method is used to maximize the posterior probability to solve the optimal state estimation. Loop detection and back-end optimization are added to help reduce or even eliminate the cumulative error of the estimated poses, thus ensuring global consistency of the trajectory and map. The outstanding contribution of this paper is that the wheel odometer pre-integration algorithm, which combines the chassis speed and IMU angular speed, can avoid the repeated integration caused by linearization point changes during iterative optimization; state initialization based on the wheel odometer and IMU enables a quick and reliable calculation of the initial state values required by the state estimator in both stationary and moving states. Comparative experiments were conducted in room-scale scenes, building scale scenes, and visual loss scenarios. The results showed that the proposed algorithm is highly accurate-2.2 m of cumulative error after moving 812 m (0.28%, loopback optimization disabled)-robust, and has an effective localization capability even in the event of sensor loss, including visual loss. The accuracy and robustness of the proposed method are superior to those of monocular visual inertia SLAM and traditional wheel odometers.

The item network and domain network of burnout in Chinese nurses.

BACKGROUND: As a common social phenomenon, nurses' occupational burnout has a high incidence rate, which seriously affects their mental health and nursing level. The current assessment mostly uses the total score model and explores the influence of external factors on burnout, while the correlation between burnout items or dimensions is less explored. Ignoring the correlation between the items or dimensions may result in a limited understanding of nurse occupational burnout. This paper explores the item and dimension network structure of the Maslach Burnout Inventory-General Survey (MBI-GS) in Chinese nurses, so as to gain a deeper understanding of this psychological construct and identify potential targets for clinical intervention. METHODS: A total of 493 Chinese nurses were recruited by cluster sampling. All participants were invited to complete the survey on symptoms of burnout. Network analysis was used to investigate the item network of MBI-GS. In addition, community detection was used to explore the communities of MBI-GS, and then network analysis was used to investigate the dimension network of MBI-GS based on the results of community detection. Regularized partial correlation and non-regularized partial correlation were used to describe the association between different nodes of the item network and dimension network, respectively. Expected influence and predictability were used to describe the relative importance and the controllability of nodes in both the item and dimension networks. RESULTS: In the item network, most of the strongly correlated edges were in the same dimension of emotional exhaustion (E), cynicism (C) and reduced professional efficacy (R), respectively. E5 (Item 5 of emotional exhaustion, the same below) "I feel burned out from my work", C1 "I have become more callous toward work since I took this job", and R3 "In my opinion, I am good at my job" had the highest expected influence (z-scores = 0.99, 0.81 and 0.94, respectively), indicating theirs highest importance in the network. E1 "I feel emotionally drained from my work" and E5 had the highest predictability (E1 = 0.74, E5 = 0.74). It shows that these two nodes can be interpreted by their internal neighbors to the greatest extent and have the highest controllability in the network. The spinglass algorithm and walktrap algorithm obtained exactly the same three communities, which are consistent with the original dimensions of MBI-GS. In the dimension network, the emotional exhaustion dimension was closely related to the cynicism dimension (weight = 0.65). CONCLUSIONS: The network model is a useful tool to study burnout in Chinese nurses. This study explores the item and domain network structure of nurse burnout from the network perspective. By calculating the relevant indicators, we found that E5, C1, and R3 were the most central nodes in the item network and cynicism was the central node in the domain network, suggesting that interventions aimed at E5, C1, R3 and cynicism might decrease the overall burnout level of Chinese nurses to the greatest extent. This study provides potential targets and a new way of thinking for the intervention of nurse burnout, which can be explored and verified in clinical practice.

High Anti-Interfering Profiling of Endogenous Glycopeptides for Human Plasma by the Dual-Hydrophilic Metal-Organic Framework.

Glycopeptidome profiling provides large-scale information about the glycosylation level of endogenous peptides, reflecting the dynamic processes of disease occurrences and developments. However, endogenous glycopeptides are usually submerged in complex fluids containing a wide variety of interference molecules, such as high concentration proteins, nonglycopeptides, and salts, which confounds attempts to identify glycopeptidome. Here, a dual-hydrophilic metal-organic framework is developed to selectively capture endogenous glycopeptides in complex biological fluid. The hydrophilic matrix material provides specific selectivity toward glycopeptides, while the deliberate surface regulation using hydrophilic species enhances its interaction with glycopeptides. This hydrophilic probe presents an extremely high performance in anti-interfering enrichment of glycopeptides from mimic complex samples, even when the molar ratio of immunoglobulin G versus bovine serum albumin was up to about 1:5000. More excitingly, in the practical application of glycopeptidome analysis, a total of 380 endogenous N-glycopeptides with 180 unique N-glycopeptide sites were identified from human plasma. This strategy is expected to broaden the application of dual-hydrophilic MOF-based materials, especially in dealing with the challenges of extremely complex biological samples.

The efficient profiling of serum N-linked glycans by a highly porous 3D graphene composite.

In this work, an enrichment approach for the profiling of N-linked glycans was developed by utilizing a highly porous 3D graphene composite fabricated from graphene oxide nanosheets and a phenol-formaldehyde polymer via graphitization and KOH activation. In tailoring the large surface area (ca. 2213 m2 g-1) and 3D-layered mesoporous structure, the 3D graphene composite demonstrated not only high efficiency in glycan enrichment but also the size-exclusion effect against residual protein interference. For a standard protein ovalbumin digest, 26 N-linked glycans were identified with good repeatability, and the detection limit was as low as 0.25 ng µL-1 with the identification of 13 N-linked glycans (S/N > 10). When the mass ratio of the ovalbumin digest to the interfering proteins, i.e., bovine serum albumin and ovalbumin was 1 : 2000 : 2000, 18 N-linked glycans could still be detected with sufficient signal intensities. From a 60 nL minute complex human serum sample, up to 53 N-linked glycans with S/N > 10 were identified after the 3D graphene enrichment, while only 20 N-linked glycans were identified by the porous graphitized carbon material used for comparison. In addition, the application of the 3D graphene composite in profiling the up-regulated and down-regulated N-linked glycans from the real clinical serum samples of ovarian cancer patients confirmed the potential of the 3D graphene composite for analyzing minute and complicated biological samples.

Relationship between meaning in life and death anxiety in the elderly: self-esteem as a mediator.

BACKGROUND: Death anxiety is a common phenomenon in all societies. Older adults may be more prone to death anxiety than their younger counterparts; however, death anxiety among older adults is not well understood. This study explores the relationship between meaning in life, self-esteem, and death anxiety in senior citizens in China. METHODS: A total of 283 older adults participated in this study; data were collected via the Meaning in Life Questionnaire, the Rosenberg Self-Esteem Scale, and the Death Anxiety Scale. RESULTS: Results show that the dimensions of meaning in life, presence of meaning (r = - 0.43, p < 0.01), search for meaning (r = - 0.31, p < 0.01), and self-esteem (r = - 0.54, p < 0.01) were each negatively correlated with death anxiety. Regression analysis reveals that meaning in life significantly predicted self-esteem and death anxiety (F = 45.70, p < 0.01; R2 = 0.33). Path analysis indicated that self-esteem either completely or partially mediated the effects of meaning in life on death anxiety in older adults. CONCLUSIONS: Overall, meaning in life appears to be significantly correlated with death anxiety in older adults, and self-esteem can mediate this effect.

Antiamyloidogenic Activity of Aß42-Binding Peptoid in Modulating Amyloid Oligomerization.

The oligomerization and aggregation of amyloid ß (Aß) play central role in the pathogenesis of Alzheimer's disease (AD). Molecular binding agents for modulating the formation of Aß oligomers and fibrils have promising application potential in AD therapies. By screening a peptoid library using surface plasmon resonance imaging, amyloid inhibitory peptoid 1 (AIP1) that has high affinity to Aß42 is identified. AIP1 is demonstrated to inhibit Aß42 oligomerization and fibrillation and to rescue Aß42-induced cytotoxicity through decreasing the content of Aß42 oligomers that is related to cell membrane permeability. Molecular docking suggests that the binding sites of AIP1 may be at the N-terminus of Aß42. The blood-brain barrier (BBB) permeability of AIP1 using an in vitro BBB model is also revealed. This work provides a strategy for the design and development of peptoid-based antiamyloidogenic agents. The obtained amyloid inhibitory peptoid shows prospects in the therapeutic application in AD.

Aromatic-interaction-mediated inhibition of ß-amyloid assembly structures and cytotoxicity.

Abnormal aggregation of ß-amyloid (Aß) peptide plays an important role in the onset and progress of Alzheimer's disease (AD); hence, targeting Aß aggregation is considered as an effective therapeutic strategy. Here, we studied the aromatic-interaction-mediated inhibitory effect of oligomeric polypeptides (K8Y8, K4Y8, K8W8) on Aß42 fibrillization process. The polypeptides containing lysine as well as representative aromatic amino acids of tryptophan or tyrosine were found to greatly suppress the aggregation as evaluated by thioflavin T assay. Circular dichroism spectra showed that the ß-sheet formation of Aß42 peptides decreased with the polypeptide additives. Molecular docking studies revealed that the oligomeric polypeptides could preferentially bind to Aß42 through π-π stacking between aromatic amino acids and Phe19, together with hydrogen bonding. The cell viability assay confirmed that the toxicity of Aß42 to SH-SY5Y cells was markedly reduced in the presence of polypeptides. This study could be beneficial for developing peptide-based inhibitory agents for amyloidoses. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.

In Situ and Timed Extraction of Cellular Peptides from Live HeLa Cells by Photo-Switchable Mesoporous Silica Nanocarriers.

In situ and timed extraction of cellular peptides is a great challenge for dynamic and global proteomic investigation of live cells. In this work, a mesoporous silica nanocarrier with photoswitchable off/on coumarin gates (MSNcg) was developed for capturing peptides from the cytosol of living HeLa cells. The MSNcg was constructed from mesoporous silica nanoparticle (MSN) and its subsequent modifications with TAT peptides and coumarin, to endow the features of the size-exclusion effect of the mesoporous silica and the localization of nanocarrier at cytosol by TAT peptide and to control the closing and opening of the coumarin gates by reversible photodimerization and photocleavage. With the pre-endocytosing of MSNcg, 126 cytosol peptides were harvested and identified from living HeLa cells. Moreover, 3 peptides were captured containing dynamic and changeable information. The extraction strategy of using MSNcg exhibited promising potentials in the in situ and dynamic extraction of endogenous peptides and/or proteins from living systems.

Dual-affinity peptide mediated inter-protein recognition.

We present for the first time an enhanced interaction affinity between an abundant soluble protein (human serum albumin) and a membrane protein (chemokine receptor 4) mediated by a dual-affinity peptide E5.

Heavy metals in wild marine fish from South China Sea: levels, tissue- and species-specific accumulation and potential risk to humans.

Heavy metal pollution in marine fish has become an important worldwide concern, not only because of the threat to fish in general, but also due to human health risks associated with fish consumption. To investigate the occurrence of heavy metals in marine fish species from the South China Sea, 14 fish species were collected along the coastline of Hainan China during the spring of 2012 and examined for species- and tissue-specific accumulation. The median concentrations of Cd, Cr, Cu, Zn, Pb and As in muscle tissue of the examined fish species were not detectable (ND), 2.02, 0.24, 2.64, 0.025, and 1.13 mg kg(-1) wet weight, respectively. Levels of Cu, Zn, Cd and Cr were found to be higher in the liver and gills than in muscle, while Pb was preferentially accumulated in the gills. Differing from other heavy metals, As did not exhibit tissue-specific accumulation. Inter-species differences of heavy metal accumulation were attributed to the different habitat and diet characteristics of marine fish. Human dietary exposure assessment suggested that the amounts of both Cr and As in marine wild fish collected from the sites around Hainan, China were not compliant with the safety standard of less than 79.2 g d(-1) for wild marine fish set by the Joint FAO/WHO Expert Committee on Food Additives. Further research to identify the explicit sources of Cr and As in marine fish from South China Sea should be established.

Dispositional optimism, self-framing and medical decision-making.

Self-framing is an important but underinvestigated area in risk communication and behavioural decision-making, especially in medical settings. The present study aimed to investigate the relationship among dispositional optimism, self-frame and decision-making. Participants (N = 500) responded to the Life Orientation Test-Revised and self-framing test of medical decision-making problem. The participants whose scores were higher than the middle value were regarded as highly optimistic individuals. The rest were regarded as low optimistic individuals. The results showed that compared to the high dispositional optimism group, participants from the low dispositional optimism group showed a greater tendency to use negative vocabulary to construct their self-frame, and tended to choose the radiation therapy with high treatment survival rate, but low 5-year survival rate. Based on the current findings, it can be concluded that self-framing effect still exists in medical situation and individual differences in dispositional optimism can influence the processing of information in a framed decision task, as well as risky decision-making.