A V-shaped bis-coumarin based fluorescence probe for F- detection in tea infusions and potable water and bioimaging applications in living systems.

Fluorine (F) is a pivotal element in the formation of human dental and skeletal tissues, and the consumption of water and tea constitutes a significant source of fluoride intake. However, prolonged ingestion of water and tea with excessive fluoride content can lead to fluorosis, which poses a serious health hazard. In this manuscript, a novel turn-on fluorescent probe DCF synthesized by bis-coumarin and tert-butyldiphenylsilane (TBDPS) was introduced for detecting F- in potable water and tea infusions. By leveraging the unique chemical affinity between fluoride and silicon, F- triggers the silicon-oxygen bond cleavage in DCF, culminating in a conspicuous emission of yellow fluorescence. Validated through a succession of optical tests, this probe exhibits remarkable advantages in terms of superior selectivity, a low detection limit, a large Stokes shift, and robust interference resistance when detecting inorganic fluoride. Moreover, it can serve as portable test strips for on-site real-time identification and quantitative analysis of F-. Furthermore, the application of DCF for in-situ monitoring and imaging of F- in zebrafish and soybean root tissues proved its significant value for F- detection in both animal and plant systems. This probe potentially functions as an efficient instrument for delving into the toxic mechanisms of fluoride in physiological processes.

Preparation of two zwitterionic polymer functionalized stationary phases and comparative evaluation under mixed-mode of reversed phase/ hydrophilic interaction/ion exchange chromatography.

Zwitterions are a promising choice to prepare separation materials because of their hydrophilicity and biocompatibility. We described the preparation of two zwitterionic polymer functionalized stationary phases and evaluation under mixed-mode chromatography. A zwitterionic monomer, S-(4-vinylbenzyl) cysteine (SVC), was synthesized and bonded to silica via reversible addition fragmentation chain transfer (RAFT) polymerization to afford a zwitterionic stationary phase, Sil-SVC. A hydrophobic monomer, N-(4-phenylbutan-2-yl) acrylamide (NPA), was copolymerized with SVC onto the stationary phase (Sil-SVCNPA) for comparison. The stationary phases were characterized with FT-IR, TGA, EA, and zeta-potential measurements. Mobile phase composition (ACN content, pH and salt concentration) was varied to study the retention property. Linear solvation energy relationship and Van't Hoff plot were used to investigate the retention mechanism and how chromatographic conditions influenced it. Both stationary phases showed a mixed-mode of RPLC/HILIC/IEC and satisfactory performance in separating hydrophobic analytes (alkylbenzenes and polycyclic aromatic hydrocarbons), hydrophilic nucleotide and bases, and anions, high column efficiency of 60,000 plates·m-1 was achieved. In summary, zwitterionic polymers are attractive options to prepare stationary phases and the retention property can be easily regulated by copolymer.

Fabrication of ionic liquid functionalized silica with different anions and the application in mixed-mode and chiral chromatography.

To realize the potential of ionic liquid functionalized silica to prepare mixed-mode and chiral stationary phases, two ionic liquid silane reagents with different anions were synthesized via a high-efficiency click reaction. Then they were decorated onto the surface of silica by a one-step bonding reaction. The functionalized silica was characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and elemental analysis (EA). Two stationary phases provided satisfactory performance when compared with a commercial mixed-mode column. Notably, Sil-C10Im-D-BCS with D-3-bromocamphor-8-sulfonate (D-BCS) as anion presented chiral separation capacity towards 1,2,3,4-Tetrahydro-1-naphthol. The separation mechanism was investigated through multiple pathways, and the results revealed that the prepared stationary phases can retain and separate solutes through multiple interactions, like hydrophobic effect, ion exchange, hydrogen-bond interaction, etc. Quantum chemical calculation (QC) was employed to obtain the optimized structures and the binding energy of anions to cations. The results provided some insights into the retention mechanism from a molecular perspective. This work demonstrated the superiority of ionic liquid functionalized silica as mixed-mode stationary phases and the potential of chiral ionic liquid as chiral selectors.

Extraction of W, V, and As from spent SCR catalyst by alkali pressure leaching and the pressure leaching mechanism.

Spent selective catalytic reduction (SCR) catalysts are environmentally hazardous and resource-enriching. In this work, V, W, and As in a spent SCR catalyst was extracted by alkali pressure leaching. Results showed that the V, W, and As were loaded on the anatase TiO2 crystal grains as amorphous oxides. The optimum pressure leaching conditions were NaOH concentration of 20 wt%, reaction temperature of 180 °C, reaction time of 120 min, L/S of 10 mL/g, and stirring speed of 300 rpm. The leaching efficiency of W, V, and As reached 98.83%, 100%, and 100%, respectively. The experiment revealed the preferential leaching of V and As rather than W, and the leaching mechanisms of V, W, and As were studied through experiment and density functional theory (DFT). The leaching kinetics of W conformed to a variant of the shrinking core model and the leaching process of W is controlled by both chemical reactions and diffusion processes. During the leaching process, Na2Ti2O4(OH)2 product powder layer was generated, which affects the mass transfer of W. The destruction of the TiO2 skeleton in the spent SCR catalyst is essential for adequate W extraction, especially for the extraction of W embedded in the TiO2 lattice. The DFT simulation result indicated that the V and As loaded onto the TiO2 support are easier to absorb hydroxide ions rather than W, and the leaching reaction energy of V and As was lower than W, As, and V has leaching priority over the leaching of W. Furthermore, an anatase TiO2 photocatalyst with the {001} crystal surface exposed was successfully prepared from the alkali pressure leaching residue. This work provides theoretical support for the metal leaching and utilization of spent SCR catalysts via alkali pressure leaching.

Recovery of tungsten and titanium from spent SCR catalyst by sulfuric acid leaching process.

The widespread use of selective catalytic reduction (SCR) catalysts has resulted in a large accumulation of spent SCR catalysts. These spent catalysts present a significant risk of environmental hazards and potential for resource recovery. This paper presents a feasible process, which works using atmospheric pressure leaching, of tungsten and titanium recovery from spent SCR catalysts. In this new method, titanium and tungsten are simultaneously leached with sulfuric acid as the leaching agent. After hydrolysis and calcination, titanium-tungsten powder with low impurity and reconstructed pore properties was obtained. The optimal conditions for the leaching of Ti and W were as follows: temperature, 150 °C; reaction time, 60 min; H2SO4 concentration, 80 %; mass ratio of H2SO4/TiO2, 3:1; and diluted H2SO4 concentration, 20 % after reaction. With these optimum conditions, the leaching efficiency of Ti and W were found to be 95.92 % and 93.83 %, respectively. The ion speciation and reaction mechanism of W were studied by Raman spectroscopy, FTIR, and UV-vis. The formation of heteropolytungstate with a Keggin structure is essential for the synergistic leaching of Ti and W, as the heteropolytungstate can be stably dissolved in the acid solution. During the hydrolysis process, heteropolytungstate gradually decomposed into Ti4+ and WO42- due to the formation of insoluble Ti(OH)4 from Ti4+ in the solution. This study demonstrated an effective method for synergistic recovery of titanium and tungsten from the spent SCR catalyst.

Establishment of a Fah-LSL mouse model to study BEC-to-hepatocyte conversion.

The liver consists predominantly of hepatocytes and biliary epithelial cells (BECs), which serve distinct physiological functions. Although hepatocytes primarily replenish their own population during homeostasis and injury repair, recent findings have suggested that BECs can transdifferentiate into hepatocytes when hepatocyte-mediated liver regeneration is impaired. However, the cellular and molecular mechanisms governing this BEC-to-hepatocyte conversion remain poorly understood largely because of the inefficiency of existing methods for inducing lineage conversion. Therefore, this study introduces a novel mouse model engineered by the Zhou's lab, where hepatocyte senescence is induced by the deletion of the fumarylacetoacetate (Fah) gene. This model facilitates the efficient conversion of BECs to hepatocytes and allows for the simultaneous lineage tracing of BECs; consequently, a transitional liver progenitor cell population can be identified during lineage conversion. This study also outlines the technical procedures for utilizing this model to determine the underlying cellular and molecular mechanisms of BEC-to-hepatocyte conversion and provides new insights into liver regeneration and its underlying molecular mechanism.

Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles.

Objective: To explore the feasibility of a deep learning three-dimensional (3D) V-Net convolutional neural network to construct high-resolution computed tomography (HRCT)-based auditory ossicle structure recognition and segmentation models. Methods: The temporal bone HRCT images of 158 patients were collected retrospectively, and the malleus, incus, and stapes were manually segmented. The 3D V-Net and U-Net convolutional neural networks were selected as the deep learning methods for segmenting the auditory ossicles. The temporal bone images were randomized into a training set (126 cases), a test set (16 cases), and a validation set (16 cases). Taking the results of manual segmentation as a control, the segmentation results of each model were compared. Results: The Dice similarity coefficients (DSCs) of the malleus, incus, and stapes, which were automatically segmented with a 3D V-Net convolutional neural network and manually segmented from the HRCT images, were 0.920 ± 0.014, 0.925 ± 0.014, and 0.835 ± 0.035, respectively. The average surface distance (ASD) was 0.257 ± 0.054, 0.236 ± 0.047, and 0.258 ± 0.077, respectively. The Hausdorff distance (HD) 95 was 1.016 ± 0.080, 1.000 ± 0.000, and 1.027 ± 0.102, respectively. The DSCs of the malleus, incus, and stapes, which were automatically segmented using the 3D U-Net convolutional neural network and manually segmented from the HRCT images, were 0.876 ± 0.025, 0.889 ± 0.023, and 0.758 ± 0.044, respectively. The ASD was 0.439 ± 0.208, 0.361 ± 0.077, and 0.433 ± 0.108, respectively. The HD 95 was 1.361 ± 0.872, 1.174 ± 0.350, and 1.455 ± 0.618, respectively. As these results demonstrated, there was a statistically significant difference between the two groups (P < 0.001). Conclusion: The 3D V-Net convolutional neural network yielded automatic recognition and segmentation of the auditory ossicles and produced similar accuracy to manual segmentation results.

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in COVID-19 and to analyse its underlying mechanism. METHODS: Chest high-resolution computer tomography (CT) images and laboratory examination data of 31 patients with COVID-19 were extracted, and the lesion areas in CT images were quantitatively segmented and calculated using a deep learning (DL) system. A cross-sectional study method was carried out to explore the differences among the proportions of lung lobe infection and to correlate the percentage of infection (POI) of the whole lung in all patients with clinical laboratory examination values. RESULTS: No significant difference in the proportion of infection was noted among various lung lobes (P > 0.05). The POI of total lung was negatively correlated with the peripheral blood lymphocyte percentage (L%) (r = - 0.633, P < 0.001) and lymphocyte (LY) count (r = - 0.555, P = 0.001) but positively correlated with the neutrophil percentage (N%) (r = 0.565, P = 0.001). Otherwise, the POI was not significantly correlated with the peripheral blood white blood cell (WBC) count, monocyte percentage (M%) or haemoglobin (HGB) content. In some patients, as the infection progressed, the L% and LY count decreased progressively accompanied by a continuous increase in the N%. CONCLUSIONS: Lung lesions in COVID-19 patients are significantly correlated with the peripheral blood lymphocyte and neutrophil levels, both of which could serve as prognostic indicators that provide warning implications, and contribute to clinical interventions in patients.

Disrupted structural covariance network in first episode schizophrenia patients: Evidence from a large sample MRI-based morphometric study.

BACKGROUND: Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear. METHODS: In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs. RESULTS: The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area. CONCLUSION: Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.

Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined With Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy.

OBJECTIVE: Neuroimaging-based brain signatures may be informative in identifying patients with psychosis who will respond to antipsychotics. However, signatures that inform the electroconvulsive therapy (ECT) health care professional about the response likelihood remain unclear in psychosis with radiomics strategy. This study investigated whether brain structure-based signature in the prediction of ECT response in a sample of schizophrenia patients using radiomics approach. METHODS: This high-resolution structural magnetic resonance imaging study included 57 patients at baseline. After ECT combined with antipsychotics, 28 and 29 patients were classified as responders and non-responders. Features of gray matter were extracted and compared. The logistic regression model/support vector machine (LRM/SVM) analysis was used to explore the predictive performance. RESULTS: The regularized multivariate LRM accurately discriminated responders from non-responders, with an accuracy of 90.91%. The structural features were further confirmed in the validating data set, resulting in an accuracy of 87.59%. The accuracy of the SVM in the training set was 90.91%, and the accuracy in the validation set was 91.78%. CONCLUSION: Our results support the possible use of structural brain feature-based radiomics as a potential tool for predicting ECT response in patients with schizophrenia undergoing antipsychotics, paving the way for utilization of markers in psychosis.

Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging.

BACKGROUND: To investigate the ability of amide proton transfer (APT) weighted magnetic resonance imaging (MRI), arterial spin labeling (ASL), diffusion weighted imaging (DWI) and the combination for differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs). METHODS: Twenty-seven patients including nine LGGs and eighteen HGGs underwent conventional, APT, ASL and DWI MRI with a 3.0-T MR scanner. Histogram analyses was performed and quantitative parameters including mean apparent diffusion coefficient (ADC mean), 20th-percentile ADC (ADC 20th), mean APT (APT mean), 90th-percentile APT (APT 90th), relative mean cerebral blood flow (rCBF mean) and relative 90th-percentile CBF (rCBF 90th) were compared between HGGs and LGGs. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. Correlations were analyzed among the MRI parameters and Ki-67. RESULTS: The APT values were significantly higher in the HGGs compared to the LGGs (p <  0.005), whereas ADC values were significantly lower in HGGs than LGGs (P <  0.0001). The ADC 20th and APT mean had higher discrimination abilities compared with other single parameters, with the area under the ROC curve (AUC) of 0.877 and 0.840. Adding ADC parameter, the discrimination ability of APT and rCBF significantly improved. The ADC was negatively correlated with the APT and rCBF value, respectively, while APT value was positively correlated with rCBF value. Significant correlations between ADC values and Ki-67 were also observed. CONCLUSIONS: APT and DWI are valuable in differentiating HGGs from LGGs. The combination of APT, DWI and ASL imaging could improve the ability for discriminating HGGs from LGGs.

Efficient and stable catalyst of α-FeOOH for NO oxidation from coke oven flue gas by the catalytic decomposition of gaseous H2O2.

Goethite (α-FeOOH) possesses excellent catalytic activity, high selectivity and good stability as a catalyst for NO oxidation through the catalytic decomposition of gaseous H2O2. as the primary reactive oxygen species is involved in the NO oxidation process together with ·OH, and N2O5 is found for the first time in the products of NO oxidation.

Voxel-based morphometry results in first-episode schizophrenia: a comparison of publicly available software packages.

Investigations of brain structure in schizophrenia using magnetic resonance imaging (MRI) have identified variations in regional grey matter (GM) volume throughout the brain but the results are mixed. This study aims to investigate whether the inconsistent voxel-based morphometry (VBM) findings in schizophrenia are due to the use of different software packages. T1 MRI images were obtained from 86 first-episode schizophrenia (FESZ) patients and 86 age- and gender-matched Healthy controls (HCs). VBM analysis was carried out using FMRIB software library (FSL) 5.0 and statistical parametric mapping 8 (SPM8). All images were processed using the default parameter settings as provided by these software packages. FSL-VBM revealed widespread GM volume reductions in FESZ patients compared with HCs, however, for SPM-VBM, only increased and circumscribed GM volume changes were found, both software revealed increased GM volume within cerebellum. Significant correlations between Positive and Negative Syndrome Scale (PANSS) and GM volume were mainly found in frontal regions. Algorithms of GM tissue segmentation, image registration and statistical strategies might contribute to these disparate results.

An Easy-to-Implement Toolkit to Create Versatile and High-Performance HASEL Actuators for Untethered Soft Robots.

For soft robots to have ubiquitous adoption in practical applications they require soft actuators that provide well-rounded actuation performance that parallels natural muscle while being inexpensive and easily fabricated. This manuscript introduces a toolkit to rapidly prototype, manufacture, test, and power various designs of hydraulically amplified self-healing electrostatic (HASEL) actuators with muscle-like performance that achieve all three basic modes of actuation (expansion, contraction, and rotation). This toolkit utilizes easy-to-implement methods, inexpensive fabrication tools, commodity materials, and off-the-shelf high-voltage electronics thereby enabling a wide audience to explore HASEL technology. Remarkably, the actuators created from this easy-to-implement toolkit achieve linear strains exceeding 100%, a specific power greater than 150 W kg-1, and ≈20% strain at frequencies above 100 Hz. This combination of large strain, extreme speed, and high specific power yields soft actuators that jump without power-amplifying mechanisms. Additionally, an efficient fabrication technique is introduced for modular designs of HASEL actuators, which is used to develop soft robotic devices driven by portable electronics. Inspired by the versatility of elephant trunks, the above capabilities are combined to create an untethered continuum robot for grasping and manipulating delicate objects, highlighting the wide potential of the introduced methods for soft robots with increasing sophistication.

Gray matter volume changes following antipsychotic therapy in first-episode schizophrenia patients: A longitudinal voxel-based morphometric study.

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients.

Alginate microspheres prepared by ionic crosslinking of pickering alginate emulsions.

Modification of reduced graphene oxide nanosheets (MrGO) is an effective strategy to increase their dispersability and hydrophobicity in order to fabricate alginate microspheres via crosslingking stable Pickering alginate emulsions stabilized by MrGO, in where alginate aqueous solution is the dispersed phase and an organic solvent the continuous phase. The effects of MrGO concentration, water/oil ratio and salt concentration on the alginate spheres were investigated, and the results shows that MrGO could efficiently stabilize alginate spheres in suitable conditions and increasing the MrGO concentration or the oil/water ratio was favorable to the formation of alginate spheres. Using this method, alginate microspheres loaded with drug were easily fabricated and their release properties at different conditions were discussed.

Association Between Connectivity of Hippocampal Sub-Regions and Auditory Verbal Hallucinations in Schizophrenia.

Background: Hippocampal dysconnectivity has been detected in schizophrenia patients with auditory verbal hallucinations (AVHs). Neuroanatomical evidence has indicated distinct sub-regions in the hippocampus, but which sub-regions within the hippocampus may emerge dysfunction in the brain network, and the relationship between connection strength and the severity of this debilitating disorder have yet to be revealed. Masked independent component analysis (mICA), i.e., ICA restricted to a defined region of interest, can provide insight into observing local functional connectivity in a particular brain region. We aim to map out the sub-regions in the hippocampus with dysconnectivity linked to AVHs in schizophrenia. Methods: In this functional magnetic resonance imaging study of schizophrenia patients with (n = 57) and without (n = 83) AVHs, and 71 healthy controls, we first examined hippocampal connectivity using mICA, and then the correlation between connection metric and clinical severity was generated. Results: As compared with patients without AVHs, mICA showed a group of hyper-connections for the left middle part, as well as another group of hypo-connections for the bilateral antero-lateral and right antero-medial parts in patients with AVHs. Connectivity was linked to the clinical symptoms scores in the sample of patients with AVHs. Conclusion: These findings demonstrate that the left middle part is more densely connected, but the bilateral antero-lateral and right antero-medial parts are more sparsely connected in schizophrenia patients with AVHs. The findings in the present study show proof of precious location in the hippocampus mediating the neural mechanism behind AVHs in schizophrenia.

Effect of second-generation antipsychotics on brain network topology in first-episode schizophrenia: A longitudinal rs-fMRI study.

OBJECTIVE: We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs. METHODS: Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female). RESULTS: Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes. CONCLUSION: The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ.

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study.

INTRODUCTION: Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response. OBJECTS: We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia. METHODS: Amplitude of low-frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset (n = 79) and a replication dataset (n = 44). Two groups of healthy controls (n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFFratio , was evaluated based on diagnostic tests and clinical correlates. RESULTS: In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non-responders. ALFFratio of responders before treatment was significantly higher than that of non-responders (p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFFratio to distinguish responders from non-responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset. CONCLUSIONS: Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho-neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.

Fabrication of chitosan gel droplets via crosslinking of inverse Pickering emulsifications.

Hydrophobic and dispersible functionalized reduced graphene oxide (FrGO) was employed to prepare chitosan gel droplets by crosslinking an inverse Pickering emulsion. The emulsion was prepared using toluene as the continuous phase and a chitosan aqueous solution as the dispersed phase. The effects of the FrGO concentration and the water/oil ratio on the chitosan droplet morphology were studied. At appropriate concentrations, the FrGO acted as a stabilizer and chitosan gel droplets were formed. Decreasing the FrGO concentration or increasing the water/oil ratio was unfavorable to the formation of chitosan droplets. Using this method, drug loaded chitosan gel droplets (microgels) were prepared and their release profiles as well as the factors that influence the drug release were investigated.