The neural compensation phenomenon in schizophrenia with mild attention deficits during working memory task.

BACKGROUND: Working memory (WM) and attention are essential cognitive processes, and their interplay is critical for efficient information processing. Schizophrenia often exhibits deficits in both WM and attention, contributing to function impairments. This study aims to investigate the neural mechanisms underlying the relationship between WM impairments and attention deficits in schizophrenia. METHODS: We assessed the functional-MRI scans of the 184 schizophrenias with different attention deficits (mild=133; severe=51) and 146 controls during an N-back WM task. We explored their whole-brain functional connectome profile by adopting the voxel-wise degree centrality (DC). Linear analysis was conducted to explore the associations among attention deficit severity, altered DC, and WM performance in patients. RESULTS: We observed that all patients showed decreased DC in the pre-supplementary area (pre-SMA), and posterior cerebellum compared to the controls, and schizophrenia patients with mild attention deficits showed decreased DC in the supramarginal gyrus, insula, and precuneus compared with the other 2 groups. DC values of the detected brain regions displayed U-shaped or inverted U-shaped curves, rather than a linear pattern, in response to increasing attention deficits. The linear analysis indicated that altered DC of the pre-SMA can modulate the relationship between attention deficits and WM performance. CONCLUSION: The U-shaped or inverted U-shaped pattern in response to increasing attention deficits may reflect a compensation mechanism in schizophrenia with mild attention deficits. This notion is also supported by the linear analysis that schizophrenia patients with mild attention deficits can improve their WM performance by increasing the DC value of the pre-SMA.

Multicolor-Assay-on-a-Chip Processed by Robotic Operation (MACpro) with Improved Diagnostic Accuracy for Field-Deployable Detection.

The ability to deploy decentralized laboratories with autonomous and reliable disease diagnosis holds the potential to deliver accessible healthcare services for public safety. While microfluidic technologies provide precise manipulation of small fluid volumes with improved assay performance, their limited automation and versatility confine them to laboratories. Herein, we report the utility of multicolor assay-on-a-chip processed by robotic operation (MACpro), to address this unmet need. The MACpro platform comprises a robot-microfluidic interface and an eye-in-hand module that provides flexible yet stable actions to execute tasks in a programmable manner, such as the precise manipulation of the microfluidic chip along with different paths. Notably, MACpro shows improved detection performance by integrating the microbead-based antibody immobilization with enhanced target recognition and multicolor sensing via Cu2+-catalyzed plasmonic etching of gold nanorods for rapid and sensitive analyte quantification. Using interferon-gamma as an example, we demonstrate that MACpro completes a sample-to-answer immunoassay within 30 min and achieves a 10-fold broader dynamic range and a 10-fold lower detection limit compared to standard enzyme-linked immunosorbent assays (0.66 vs 5.2 pg/mL). MACpro extends the applications beyond traditional laboratories and presents an automated solution to expand diagnostic capacity in diverse settings.

Influence of TMX2-CTNND1 polymorphism on cortical thickness in schizophrenia patients and unaffected siblings: an exploratory study based on target region sequencing.

OBJECTIVE: The advancement of neuroimaging and genetic research has revealed the presence of morphological abnormalities and numerous risk genes, along with their associations. We aimed to estimate magnetic resonance imaging-derived cortical thickness across multiple brain regions. METHODS: The cortical thickness of 129 schizophrenia patients, 42 of their unaffected siblings, and 112 healthy controls was measured and the candidate genes were sequenced. Comparisons were made of cortical thickness (including 68 regions of the Desikan-Killiany Atlas) and genetic variants (in 108 risk genes for schizophrenia) among the three groups, and correlation analyses were performed regarding cortical thickness, clinical symptoms, cognitive tests (such as the N-back task and the logical memory test), and genetic variants. RESULTS: Schizophrenia patients had significantly thinner bilateral frontal, temporal, and parietal gyri than healthy controls and unaffected siblings. Association analyses in target genes showed that four single nucleotide variants (SNVs) were significantly associated with schizophrenia, including thioredoxin-related transmembrane protein 2-catenin, cadherin-associated protein, delta 1 (SNV20673) (positive false discovery rate [PFDR] = 0.008) and centromere protein M (rs35542507, rs41277477, rs73165153) (PFDR = 0.030). Additionally, cortical thickness in the right pars triangularis was lower in carriers of the SNV20673 variant than in non-carriers (PFDR = 0.048). Finally, a positive correlation was found between right pars triangularis cortical thickness and logical memory in schizophrenia patients (r = 0.199, p = 0.032). CONCLUSIONS: This study identified regional morphological abnormalities in schizophrenia, including the right homologue of Broca's area, which was associated with a risk variant that affected delta-1 catenin and logical memory. These findings suggest a potential association between candidate gene loci, cortical thickness, and schizophrenia.

Influence of TMX2-CTNND1 polymorphism on cortical thickness in schizophrenia patients and unaffected siblings: an exploratory study based on target region sequencing

Objective: The advancement of neuroimaging and genetic research has revealed the presence of morphological abnormalities and numerous risk genes, along with their associations. We aimed to estimate magnetic resonance imaging-derived cortical thickness across multiple brain regions. Methods: The cortical thickness of 129 schizophrenia patients, 42 of their unaffected siblings, and 112 healthy controls was measured and the candidate genes were sequenced. Comparisons were made of cortical thickness (including 68 regions of the Desikan-Killiany Atlas) and genetic variants (in 108 risk genes for schizophrenia) among the three groups, and correlation analyses were performed regarding cortical thickness, clinical symptoms, cognitive tests (such as the N-back task and the logical memory test), and genetic variants. Results: Schizophrenia patients had significantly thinner bilateral frontal, temporal, and parietal gyri than healthy controls and unaffected siblings. Association analyses in target genes showed that four single nucleotide variants (SNVs) were significantly associated with schizophrenia, including thioredoxin-related transmembrane protein 2-catenin, cadherin-associated protein, delta 1 (SNV20673) (positive false discovery rate [PFDR] = 0.008) and centromere protein M (rs35542507, rs41277477, rs73165153) (PFDR = 0.030). Additionally, cortical thickness in the right pars triangularis was lower in carriers of the SNV20673 variant than in non-carriers (PFDR = 0.048). Finally, a positive correlation was found between right pars triangularis cortical thickness and logical memory in schizophrenia patients (r = 0.199, p = 0.032). Conclusions: This study identified regional morphological abnormalities in schizophrenia, including the right homologue of Broca's area, which was associated with a risk variant that affected delta-1 catenin and logical memory. These findings suggest a potential association between candidate gene loci, cortical thickness, and schizophrenia.

Polygenic risk for schizophrenia and the language network: Putative compensatory reorganization in unaffected siblings.

Language-related symptoms, such as disorganized, impoverished speech and communicative behaviors, are one of the core features of schizophrenia. These features most strongly correlate with cognitive deficits and polygenic risk among various symptom dimensions of schizophrenia. Nevertheless, unaffected siblings with genetic high-risk fail to show consistent deficits in language network (LN), indicating that either (1) polygenic risk has no notable effect on LN and/or (2) siblings show compensatory changes in opposing direction to patients. To answer this question, we related polygenic risk scores (PRS) to the region-level, tract-level, and systems-level structure (cortical thickness and fiber connectivity) of LN in 182 patients, 48 unaffected siblings and 135 healthy controls. We also studied the relationships between symptoms, language-related cognition, social functioning and LN structure. We observed a significantly lower thickness in LN (especially the Broca's, Wernicke's area and their right homologues) in patients. Siblings had a distinctly higher thickness in parts of the LN and a more pronounced small-world-like structural integration within the LN. Patients with reduced LN thickness had higher PRS, more disorganization and impoverished speech with lower language-related cognition and social functioning. We conclude that the genetic susceptibility and putative compensatory changes for schizophrenia operate, in part, via key regions in the Language Network.

PD1hi CD200hi CD4+ exhausted T cell increase immunotherapy resistance and tumour progression by promoting epithelial-mesenchymal transition in bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is one of the most diagnosed cancers in humans worldwide. Recently, immunotherapy has become a main treatment option for BC. However, most BLCA patients do not respond to immune checkpoint inhibitors or relapse after immunotherapy. Therefore, it is very important to identify novel biomarkers for the prediction of immunotherapy response in B patients. METHODS: Pancancer single-cell RNA sequencing (scRNA-seq) data were used to identify the clusters of CD4+ T cells in the tumour microenvironment (TME). The clinical significance of key CD4+ T-cell clusters was evaluated based on the survival data of two independent immunotherapy bladder cancer (BLCA) cohorts. We also investigated the function of key clusters of CD4+ T cell in the TME of BC cells in vitro. RESULTS: This study identified two novel exhausted CD4+ T-cell subpopulations with the expression of PD1hi CD200hi or PD1hi CD200low in BC patients. Moreover, BLCA patients with a high level of PD1hi CD200hi CD4+ exhausted T cell showed immunotherapy resistance. Cell function analysis demonstrated that PD1hi CD200hi CD4+ exhausted T cell can promote epithelial-mesenchymal transition (EMT) and angiogenesis in BLCA cells. In addition, PD1hi CD200hi CD4+ exhausted T cells were shown to communicate with malignant BLCA cells through the GAS6-AXL axis. Finally, we also found that GAS6 expression is upregulated in B cells by METTL3-mediated m6A modification. CONCLUSIONS: PD1hi CD200hi CD4+ exhausted T cell may serve as a novel biomarker for poor prognosis and immunotherapy resistance in B. Targeted inhibitors of PD1hi CD200hi CD4+ exhausted T cells may help improve the efficacy of immunotherapy.

Cortical morphological heterogeneity of schizophrenia and its relationship with glutamatergic receptor variations.

BACKGROUND: Recent genetic evidence implicates glutamatergic-receptor variations in schizophrenia. Glutamatergic excess during early life in people with schizophrenia may cause excitotoxicity and produce structural deficits in the brain. Cortical thickness and gyrification are reduced in schizophrenia, but only a subgroup of patients exhibits such structural deficits. We delineate the structural variations among unaffected siblings and patients with schizophrenia and study the role of key glutamate-receptor polymorphisms on these variations. METHODS: Gaussian Mixture Model clustering was applied to the cortical thickness and gyrification data of 114 patients, 112 healthy controls, and 42 unaffected siblings to identify subgroups. The distribution of glutamate-receptor (GRM3, GRIN2A, and GRIA1) and voltage-gated calcium channel (CACNA1C) variations across the MRI-based subgroups was studied. The comparisons in clinical symptoms and cognition between patient subgroups were conducted. RESULTS: We observed a "hypogyric," "impoverished-thickness," and "supra-normal" subgroups of patients, with higher negative symptom burden and poorer verbal fluency in the hypogyric subgroup and notable functional deterioration in the impoverished-thickness subgroup. Compared to healthy subjects, the hypogyric subgroup had significant GRIN2A and GRM3 variations, the impoverished-thickness subgroup had CACNA1C variations while the supra-normal group had no differences. CONCLUSIONS: Disrupted gyrification and thickness can be traced to the glutamatergic receptor and voltage-gated calcium channel dysfunction respectively in schizophrenia. This raises the question of whether MRI-based multimetric subtyping may be relevant for clinical trials of agents affecting the glutamatergic system.

Construction and validation of a T cell proliferation regulator-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Background: As the main executor of immunotherapy, T cells significantly affect the efficacy of immunotherapy. However, the contribution of the T cell proliferation regulator to the prognosis of lung adenocarcinoma (LUAD) and immunotherapy is still unclear. Methods: Based on T cell proliferation regulators, LUAD samples from The Cancer Genome Atlas (TCGA) were divided into two different clusters by consensus clustering. Subsequently, the T cell proliferation regulator (TPR) signature was constructed according to the prognostic T cell proliferation regulators. Combined with clinical information, a nomogram for clinical practice was constructed. The predictive ability of the signature was verified by the additional Gene Expression Omnibus (GEO) dataset. We also analyzed the differences of tumor microenvironment (TME) in different subgroups and predicted the response to immunotherapy according to the TIDE algorithm. Finally, we further explored the role of ADA (Adenosine deaminase) in the lung adenocarcinoma cell lines through the knockdown of ADA. Results: According to the consensus clustering, there were differences in survival and tumor microenvironment between two different molecular subtypes. T cell proliferation regulator-related signature could accurately predict the prognosis of LUAD. The low-risk group had a higher level of immune infiltration and more abundant immune-related pathways, and its response to immunotherapy was significantly better than the high-risk group (Chi-square test, p<0.0001). The knockdown of ADA inhibited proliferation, migration, and invasion in lung adenocarcinoma cell lines. Conclusion: T cell proliferation regulators were closely related to the prognosis and tumor microenvironment of LUAD patients. And the signature could well predict the prognosis of LUAD patients and their response to immunotherapy. ADA may become a new target for the treatment of LUAD.

Development and validation of nomograms to predict survival in patients with invasive micropapillary carcinoma of the breast.

OBJECTIVES: The present study aimed to develop and validate nomograms to predict the survival of patients with breast invasive micropapillary carcinoma (IMPC) to aid objective decision-making. DESIGN: Prognostic factors were identified using Cox proportional hazards regression analyses and used to construct nomograms to predict overall survival (OS) and breast cancer-specific survival (BCSS) at 3 and 5 years. Kaplan-Meier analysis, calibration curves, the area under the curve (AUC) and the concordance index (C-index) evaluated the nomograms' performance. Decision curve analysis (DCA), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to compare the nomograms with the American Joint Committee on Cancer (AJCC) staging system. SETTING: Patient data were collected from the Surveillance, Epidemiology, and End Results (SEER) database. This database holds data related to the incidence of cancer acquired from 18 population-based cancer registries in the US. PARTICIPANTS: We ruled out 1893 patients and allowed the incorporation of 1340 patients into the present study. RESULTS: The C-index of the AJCC8 stage was lower than that of the OS nomogram (0.670 vs 0.766) and the OS nomograms had higher AUCs than the AJCC8 stage (3 years: 0.839 vs 0.735, 5 years: 0.787 vs 0.658). On calibration plots, the predicted and actual outcomes agreed well, and DCA revealed that the nomograms had better clinical utility compared with the conventional prognosis tool. In the training cohort, the NRI for OS was 0.227, and for BCSS was 0.182, while the IDI for OS was 0.070, and for BCSS was 0.078 (both p<0.001), confirming its accuracy. The Kaplan-Meier curves for nomogram-based risk stratification showed significant differences (p<0.001). CONCLUSIONS: The nomograms showed excellent discrimination and clinical utility to predict OS and BCSS at 3 and 5 years, and could identify high-risk patients, thus providing IMPC patients with personalised treatment strategies.

Adaptive Learning Control of Switched Strict-Feedback Nonlinear Systems With Dead Zone Using NN and DOB.

This article investigates the adaptive learning control for a class of switched strict-feedback nonlinear systems with external disturbances and input dead zone. To handle unknown nonlinearity and compound disturbances, a collaborative estimation learning strategy based on neural approximation and disturbance observation is proposed, and the adaptive neural switched control scheme is studied in a dynamic surface control framework. In the adaptive learning control design, to obtain the evaluation information of uncertain learning, the prediction error is constructed based on the composite learning scheme. Then, the prediction error and the compensated tracking error are applied to construct the adaptive laws of switched neural weights and switched disturbance observers. The system stability analysis is carried out through the Lyapunov approach, where the switching signal with average dwell time is considered. Through the simulation test, the effectiveness of the proposed adaptive learning controller is verified.

Robust Adaptive Learning Control of Space Robot for Target Capturing Using Neural Network.

This article investigates the robust adaptive learning control for space robots with target capturing. Based on the momentum conservation theory, the impact dynamics is constructed to derive the relationship of generalized velocity in the pre-impact and post-impact phase. Considering the nonlinear dynamics with contact impact, the robust control using nonsingular terminal sliding mode (NTSM) and fast NTSM is designed to achieve the fast realization of the desired states. Furthermore, for the unknown dynamics of the combination system after capturing a target, the adaptive learning control is developed based on neural network and disturbance observer. Through the serial-parallel estimation model, the prediction error is constructed for the update of adaptive law. The system signals involved in the Lyapunov function are proved to be bounded and the sliding mode surface converges in finite time. Simulation studies present the desired tracking and learning performance.

Adaptive Control of Uncertain Nonlinear Systems via Event-Triggered Communication and NN Learning.

This article concentrates on adaptive tracking control of strict-feedback uncertain nonlinear systems with an event-based learning scheme. A novel neural network (NN) learning law is proposed to design the adaptive control scheme. The NN weights information driven by the prediction-error-based control process is intermittently transmitted in the event-triggered context to the NN learning law mainly for signal tracking. The online stored sampled data of NN driven by the tracking error are utilized in the event context to update the learning law. With the adaptive control and NN learning law updated via the event-triggered communication, the improvements of NN learning capability, tracking performance, and system computing resource saving are guaranteed. In addition, it is proved that the minimum time interval for triggering errors of the two types of events is bounded and the Zeno behavior is strictly excluded. Finally, simulation results illustrate the effectiveness and good performance of the proposed control method.

Construction and validation of a nomogram to predict overall survival in patients with breast sarcoma.

Background: This study aimed to construct a nomogram for Breast sarcoma (BS) to predict the prognosis of patients with BS accurately and provide a theoretical basis for individualized treatment. Methods: Patients selected from the Surveillance, Epidemiology and End Results (SEER) database from 2000 to 2018 were assigned to a training group (TG, n = 696) and an internal validation group (IVG, n = 299) at a 7:3 ratio. Cox regression analysis was performed on the TG, and statistically significant factors were used to establish a nomogram to predict 3-, 5-, and 10-year overall survival (OS). The nomogram's predictive power was validated using data from patients who attended our institution as the external validation group (EVG, n =79). Results: Cox regression analysis identified five factors, which were used to construct the nomogram. Good prediction accuracy was demonstrated using calibration curves. The concordance (C) indices for TG = 0.804 (95% confidence interval (CI) 0.777-0.831) and IVG = 0.761 (0.716-0.806) were higher than those based on 8th American Joint Committee on Cancer (AJCC8) stage: TG = 0.695 (0.660-0.730), IVG = 0.637 (0.584-0.690). The EVG also had a high C-index: 0.844 (0.768-0.920). Decision curve analysis showed that nomogram has larger net benefits than the AJCC8. The Kaplan-Meier curves of the nomogram-based risk groups showed significant differences (p < 0.001). Conclusions: The nomogram could accurately predict 3-, 5-, and 10-year OS and provided nomogram-based risk stratification, which could help physicians to personalize treatment plans for patients with BS.

Aberrant brain dynamics in major depressive disorder with suicidal ideation.

BACKGROUND: Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD). Accumulating studies demonstrated that MDD with SI was associated with static alterations in brain activity and functional connectivity. However, given that brain is a highly dynamic system, the changes of brain dynamic patterns in MDD with SI remain unknown. METHODS: We included 60 MDD patients with SI (MDD-SI), 58 MDD patients without SI (MDD-NSI), and 58 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging. The sliding-window approach was used to calculate the dynamic fractional amplitude of low-frequency fluctuation (dfALFF) and dynamic degree centrality (dDC) to characterize the temporal dynamic regional activity and distant functional connectivity. We compared dfALFF and dDC across groups and further conducted correlations between abnormal dynamic metrics and the severity of suicidality. RESULTS: In terms of the dynamic regional activity, MDD-SI showed decreased dfALFF in the left lingual gyrus and right middle occipital gyrus compared with MDD-NSI; in terms of the dynamic distant connectivity, MDD-SI showed decreased dDC in the right middle frontal gyrus compared with MDD-NSI. The decreased dDC in the right middle frontal gyrus was correlated with increased severity of suicidality. LIMITATIONS: The relatively small sample size. CONCLUSIONS: We demonstrate the specific brain dynamic patterns of MDD-SI in regional activity and distant functional connectivity compared to MDD-NSI. Especially the decreased temporal variability of the distant connectivity in the middle frontal gyrus was associated with SI. These altered dynamic patterns may represent a potential neurobiological diathesis of SI in MDD.

Distribution of interstitial cells of Cajal in the Esophagus and change in distribution after thoracic trauma.

Interstitial cells of Cajal (ICCs) function as pacemaker cells in the gastrointestinal tract. Acute thoracic trauma is a common and lethal cause of death due to physical trauma caused by traffic accidents. This study aimed to explore the distribution of esophageal ICCs and distribution changes observed after acute thoracic trauma. Thirty rabbits were randomly divided into a control group and two study groups. The control group animals underwent an esophagectomy. All animals in the study groups underwent right chest puncture using the Hopkinson bar technique. The study groups were subjected to esophagectomy 24 and 72 h after chest puncture. Distribution, morphology, and density of esophageal ICCs were detected using transmission electron microscopy, toluidine blue staining, and immunohistochemistry. Apoptosis of esophageal ICCs was evaluated using the terminal deoxynucleotidyl transferase (TdT) dUTP Nick-End Labeling assay. Western blotting and reverse transcription polymerase chain reaction were used to detect changes in the SCF/c-kit signaling pathway. Esophageal ICCs distribution and SCF/c-kit signal pathway decreased from the upper part to the lower part in both physiological state and after thoracic trauma. In contrast, death of ICCs increased from the upper part to the lower part, both in physiological and injured state (P < 0.05). After thoracic trauma, increased ICCs and decreased death of ICCs in all parts of the esophagus (P < 0.05) were observed. The observed distribution and changes in esophageal ICCs would have an impact on motility and motility disorders of the esophagus.

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

BACKGROUND: Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD. METHODS: Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches. RESULTS: Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls. LIMITATIONS: Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD. CONCLUSION: A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD.

Aberrant integrity of the cortico-limbic-striatal circuit in major depressive disorder with suicidal ideation.

BACKGROUND: Suicidal ideation is a common symptom of major depressive disorder (MDD) that reflects a cognitive alteration in the background of intense emotional dysregulation. Amygdala is a critical emotion processing center that facilitates moving from emotional appraisal to action. However, whether MDD patients with suicidal ideation show dysconnectivity of the amygdala within a large-scale neurocognitive circuitry remains unknown. METHODS: Participants were 22 MDD patients without suicidal ideation (MDD-NSI), 59 MDD patients with suicidal ideation (MDD-SI), and 60 healthy controls (HCs). We compared the amygdala-based resting-state functional connectivity of four amygdala subregions across the three groups. We selected brain regions with significant between-group differences in amygdalar conectivity as the regions of interest (ROI) and performed ROI-to-ROI and graph-theoretical analyses to explore dysconnectivity patterns at various granularity levels. RESULTS: Brain regions showing omnibus differences across the three groups were distributed across a cortico-limbic-striatal circuitry. MDD-SI had unique dysconnectivity of the lateral amygdala with caudate, middle temporal gyrus, and postcentral gyrus compared with the other two groups. MDD-SI and MDD-NSI had shared dysconnectivity of the medial amygdala with medial superior frontal gyrus and middle temporal gyrus. Within the derived cortico-limbic-striatal circuitry, MDD-SI exhibited lower global connectivity, reduced sigma (small-worldness), but increased lambda (path-length) than HCs. Reduced sigma correlated with increased severity of suicidal ideation. We achieved high classification accuracy (84.09%, with AUC 0.82) in distinguishing MDD-SI from MDD-NSI. CONCLUSIONS: Aberrant integrity of the cortico-limbic-striatal circuit centered on the amygdala provides a promising neural substrate for suicidal ideation that requires further investigation in MDD.

Tailoring moisture electroactive Ag/Zn@cotton coupled with electrospun PVDF/PS nanofibers for antimicrobial face masks.

Face mask has become an essential and effective apparatus to protect human beings from air pollution, especially the air-borne pathogens. However, most commercial face masks can hardly achieve good particulate matters (PMs) and high bactericidal efficacy concurrently. Herein, a bilayer structured composite filter medium with built-in antimicrobial activities was constructed by combining cotton woven modified by magnetron sputtered Ag/Zn coatings and electrospun poly(vinylidene fluoride)/polystyrene (PVDF/PS) nanofibers. With the benefit of external moisture, an electrical stimulation was generated inside the composite fabric and thus endowed the fabric antimicrobial function. The resultant composite fabric presented conspicuous performance for integrated air pollution control, high filtration performance towards PM0.3 (99.1%, 79.2 Pa) and exceptional interception ratio against Escherichia coli (99.64%) and Staphylococcus aureus (98.75%) within 20 min contact. The high efficiency contact sterilization function of the bilayer fabric could further potentially promote disinfection and reuse of the filter media. This work may provide a new perspective on designing high-performance face mask media for public health protection.

Abnormal network properties and fiber connections of DMN across major mental disorders: a probability tracing and graph theory study.

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Application of Gold-Based Nanomaterials in Tumor Photothermal Therapy and Chemotherapy.

Photothermal therapy (PTT) is a minimally invasive tumor treatment method in which photothermal conversion agents (PTAs) can be enriched in tumor tissue by external light stimulation to convert photon energy into thermal energy to induce the temperature of tumor tissue higher than normal physiological, and can effectively kill tumor cells and tissues while avoiding damage to healthy tissue. As a well-known biocompatible nanomaterial, gold-based nanomaterials have high photothermal conversion efficiency and cross section, which can be used in tumor targeting therapy treatment as a potential photothermal conversion agent. Combining PTT and chemotherapy can be achieved by loading a chemotherapeutic drug modified on the surface of a gold nanomaterials. Therefore, this paper first reviews the preparation and surface functionalization of Au-based nanomaterials, such as Au nanorods, Au nanostars, Au nanoshells, and so on. Second, we have also introduced the application of Au-based nanomaterials in PTT, chemotherapy, and combination therapy. Finally, the limitations and challenges of Au-based photothermal conversion agents are summarized and the development prospects in this field are prospected.