Pr2Ni0.8Co0.2O4+δ impregnated La0.6Sr0.4CoO3-δ oxygen electrode for efficient CO2 electroreduction in solid oxide electrolysis cells.

The solid oxide electrolysis cell (SOEC) is an advanced electrochemical device with a promising future in reducing CO2 emissions. Currently, the insufficient oxygen evolution reaction activity in conventional anode materials severely restricts the development of electrolytic CO2. Herein, the PNCO-LSC composite oxygen electrode was exploited by impregnating Pr2Ni0.8Co0.2O4+δ (PNCO) on the surface of La0.6Sr0.4CoO3-δ (LSC) oxygen electrode. The results of electrochemical tests and various physicochemical characterizations indicate that the infiltration of PNCO can lead to a significant improvement in the performance of the cell for CO2 electroreduction by increasing the surface oxygen exchange. The current density of the PNCO-LSC oxygen electrode infiltrated twice at 800 °C and 1.5 V reaches 0.917 A cm-2, which is about 40% higher than that of the bare LSC oxygen electrode. In addition, the single cell did not show significant degradation in a long-term stability test at a current density of 0.4 A cm-2 for 100 h of electrolysis. Therefore, the PNCO-LSC composite oxygen electrode material is effective in enhancing electrolytic CO2 performance.

Thalamic segmentation based on diffusion tensor imaging in patients with trigeminal neuralgia.

Classical trigeminal neuralgia (CTN) refers to episodic pain that is strictly confined to the trigeminal distribution area, and the thalamus is an important component of the trigeminal sensory pathway. Probabilistic tracking imaging algorithm was used to identify specific connections between the thalamus and the cortex, in order to identify structural changes in the thalamus of patients with CTN and perform thalamic segmentation. A total of 32 patients with CTN and 32 healthy controls underwent DTI-MRI scanning (3.0 T). Differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) between the groups were studied. Correlation analysis was performed with clinical course and pain level. Compared to the healthy controls, patients in the CTN group had significantly reduced FA, increased AD, RD and MD in somatosensory subregion of the bilateral thalamus, increased RD in frontal subregion, increased RD and MD in motor subregion. Correlation analysis showed that patient history was positively correlated with pain grading, and that medical history was positively correlated with significantly reduced FA in somatosensory subregion, negatively correlated with increased RD and MD in motor subregion. We used DTI-based probabilistic fiber tracking to discover altered structural connectivity between the thalamus and cerebral cortex in patients with CTN and to obtain a thalamic segmentation atlas, which will help to further understand the pathophysiology of CTN and serve as a future reference for thalamic deep brain stimulation electrode implantation for the treatment of intractable pain.

Governance pathway for coastal eutrophication based on regime shifts in diatom-dinoflagellate composition of the Bohai and Baltic Seas.

Regime shifts in the diatom-dinoflagellate composition have occurred in the Baltic Sea (BS) and Bohai Sea (BHS) under eutrophication and have affected the entire coastal ecosystem, damaging the regulatory, provisioning, cultural, and supporting service functions of marine ecosystems. Therefore, finding a solution to restore the balance of phytoplankton community composition and mitigate eutrophication is of utmost importance. In this study, the Driver (per capita gross domestic product)-Pressure (terrestrial inputs)-State (seawater environmental parameters)-Impact (proportions of diatoms and dinoflagellates)-Response (eutrophication governance projects) framework served as a guide for our analysis of the causal relationship among various environmental components in the coastal system. The relevant data in BS and BHS spanning from the 1950s to the 2010s were collected and used to construct a diatom-dinoflagellate composition single index, which allowed us to identify the shifts in regimes (mutation points and phases) of the diatom-dinoflagellate composition and environmental factors using sequential t-test analysis. We also identified key environmental factors that moderated the diatom-dinoflagellate composition using redundancy analysis and analyzed the partial effects of the main environmental factors on the diatom-dinoflagellate composition using a generalized additive model. Finally, the regulation of the eutrophication governance investment on diatom-dinoflagellate composition was investigated. We found that (1) BS is a "time machine," with coastal eutrophication governance and regime shift of diatom-dinoflagellate composition and environmental factors two decades earlier than that in BHS; (2) in BS, the key moderation factor of diatom proportion is SiO3-Si and those of dinoflagellates are sea surface salinity and N:P ratio; in BHS, the key moderation factors of diatom proportion are PO4-P and Si:N ratio and those of dinoflagellate are dissolved inorganic nitrogen and N:P and Si:P ratios; (3) it is projected that BHS will enter its recovery phase from eutrophication after mid-2020s. In summary, the N/P/Si stoichiometric relationships should be given greater consideration, with the exception of the "dose-response" relationship in both sea areas. Our results indicate an urgent need for an improved mechanistic understanding of how phytoplankton biodiversity changes in response to changes in nutrient load and how we should ultimately deal with the challenges that arise.

Enzyme-free ratiometric fluorescence and colorimetric dual-signal determination of glyphosate based on copper nanoclusters (ZIF/CuNCs) combined with blue carbon dots (bCDs).

A novel ratio fluorescent and colorimetric dual-signal sensing platform for detecting glyphosate based on blue carbon dots (bCDs) combined with ZIF/CuNCs nanomaterials that encapsulate copper nanoclusters (CuNCs) in a metal-organic framework (MOF). In principle, the immobilization of Cu2+ in ZIF/CuNCs results in complexation with imidazole in ZIF, leading to fluorescence quenching of ZIF/CuNCs, while the reference fluorophore bCDs remains unaffected. In addition, the colorimetric sensing strategy was based on the efficient peroxidase-like activity of bCDs binding to Cu2+, catalyzing H2O2 to generate OH. Under this condition, TMB could be oxidized to form blue oxTMB. However, when glyphosate was involved in the system, the fluorescence of ZIF/CuNCs was restored upon due to the strong chelation between Cu2+ and glyphosate, while the peroxidase-like activity of bCDs/Cu2+ decreased and resulted in the generation of fewer oxTMB, accompanied by a lighter blue color. The sensing platform was successfully applied to the determination of glyphosate in real samples of lake water and cabbage, demonstrating reliable and sensitive performance in practical applications.

Seasonal dynamics of dissolved organic matter bioavailability coupling with water mass circulation in the South Yellow Sea.

As a typical shelf-marginal sea, the South Yellow Sea (SYS) is significantly influenced by various factors such as land-based inputs and water mass movements, leading the complex biogeochemical processes of dissolved organic matter (DOM) to become highly dynamic. However, the bioavailability of dissolved organic matter (DOM) coupled with water mass circulation has not been accurately assessed, despite being crucial for understanding the source-sink pattern of organic carbon in marginal sea. In this study, four cruises were conducted in the SYS to analyze the spatial and temporal distribution characteristics of dissolved organic carbon (DOC), dissolved organic nitrogen (DON), and total dissolved amino acids (TDAA). Combined with the bioassay experiments, TDAA carbon normalized yield [TDAA (%DOC)] and TDAA degradation index (DIAA) were used as indicators to explore the bioavailability of DOM across different water masses. Results show that the DOC of the SYS exhibits higher average value in late autumn and early winter, and lower value in spring and summer due to the seasonal alternation of water mass and biological activities. The collective results indicate that DOM bioavailability is higher in the Changjiang River diluted water (CDW) and lower in the Yellow Sea warm current (YSWC) and the Yellow Sea cold water mass (YSCWM). Approximately 20 % of DON can be degraded in the YSCWM during autumn. Notably, although the YSCWM constitutes merely constitutes 10 % of the SYS volume, it stores 18.1 % dissolved inorganic nitrogen (DIN) and 23.9 % PO43- of total nutrients, indicating that the YSCWM is a significant nutrient reservoir within the SYS.

An efficient memory reserving-and-fading strategy for vector quantization based 3D brain segmentation and tumor extraction using an unsupervised deep learning network.

Deep learning networks are state-of-the-art approaches for 3D brain image segmentation, and the radiological characteristics extracted from tumors are of great significance for clinical diagnosis, treatment planning, and treatment outcome evaluation. However, two problems have been the hindering factors in brain image segmentation techniques. One is that deep learning networks require large amounts of manually annotated data. Another issue is the computational efficiency of 3D deep learning networks. In this study, we propose a vector quantization (VQ)-based 3D segmentation method that employs a novel unsupervised 3D deep embedding clustering (3D-DEC) network and an efficiency memory reserving-and-fading strategy. The VQ-based 3D-DEC network is trained on volume data in an unsupervised manner to avoid manual data annotation. The memory reserving-and-fading strategy beefs up model efficiency greatly. The designed methodology makes deep learning-based model feasible for biomedical image segmentation. The experiment is divided into two parts. First, we extensively evaluate the effectiveness and robustness of the proposed model on two authoritative MRI brain tumor databases (i.e., IBSR and BrainWeb). Second, we validate the model using real 3D brain tumor data collected from our institute for clinical practice significance. Results show that our method (without data manual annotation) has superior accuracy (0.74±0.04 Tanimoto coefficient on IBSR, 97.5% TP and 97.7% TN on BrainWeb, and 91% Dice, 88% sensitivity and 87% specificity on real brain data) and remarkable efficiency (speedup ratio is 18.72 on IBSR, 31.16 on BrainWeb, 31.00 on real brain data) compared to the state-of-the-art methods. The results show that our proposed model can address the lacks of manual annotations, and greatly increase computation speedup with competitive segmentation accuracy compared to other state-of-the-art 3D CNN models. Moreover, the proposed model can be used for tumor treatment follow-ups every 6 months, providing critical details for surgical and postoperative treatment by correctly extracting numerical radiomic features of tumors.

Two dimensional twin T-graphene: monolayer for visible-light photocatalytic water splitting and bulk for anode material of magnesium batteries.

Two-dimensional (2D) carbon allotropes with all-sp2-hybridization have demonstrated great potential in nano-photoelectric devices, but the application of semiconductor photocatalysts for water splitting and anodes in magnesium batteries remains unoptimistic. Motivated by this, we theoretically study a highly stable all-sp2-hybridized 2D carbon allotrope twin T-graphene (TTG) via first-principles simulations. And through the calculations of the HSE06 functional, we find that TTG has a wide bandgap (2.70 eV) and suitable band edge positions satisfying the criteria of photocatalysts for overall water splitting. Additionally, TTG exhibits excellent photocatalytic properties for overall water splitting reflecting a high STH efficiency (12.34%), strong absorption coefficient in the visible-light region and the carrier mobility being high for electrons but low for holes. By investigating the strain effects, we get that, with biaxial compressive strain, the ability of overall photocatalytic water splitting can be effectively improved including STH up to ∼30%. Moreover, the bulk TTG also exhibits great potential as an anode material of magnesium batteries with a theoretical capacity of 556 mA h g-1, average voltage of 0.74 V and diffusion energy barrier of ∼0.96 eV. Our results would broaden the application of all-sp2-hybridized 2D carbon allotropes in the semiconductor photocatalytic and magnesium batteries field.

Decabromodiphenyl ethane induced hyperactivity in developing zebrafish at environmentally relevant concentrations.

Decabromodiphenyl ethane (DBDPE), a widely used novel brominated flame retardant, is gaining concerns due to rapidly increased contents in various environmental and biota samples. In the present study, zebrafish (Danio rerio) embryos were exposed to 2.91, 9.71, 29.14 and 97.12 µg/L of DBDPE until 120 h post-fertilization (hpf) to investigate the potential developmental neurotoxicity and underlying mechanisms. Chemical analysis revealed concentration-dependently increased body burdens of DBDPE in zebrafish larvae, with bioaccumulation factors (BCFs) ranging from 414 to 726. Embryonic exposure to DBDPE caused hyperactivity without affecting the development of secondary motoneuron axons and muscle fibers. However, further results implicated that DBDPE may affect the locomotor regulatory network via different mechanisms at lower and higher concentrations. On the one hand, embryonic exposure to 2.91 µg/L DBDPE transiently promoted spontaneous coiling contractions, but showed no effects on touch-response and swimming activity in zebrafish larvae. The whole-body contents of neurotransmitters were significantly decreased. Significant decreased protein abundances of α1-TUBULIN and SYN2a and molecular docking results pointed out possible interactions of DBDPE with these two proteins. However, these changes may be unconcerned with the transient hyperactivity, and the exact molecular mechanisms need further investigation. On the other hand, 29.14 and 97.12 µg/L DBDPE exposure caused longer-lasting effects in promoting spontaneous coiling contractions, and also touch-response and swimming activity. At the same time, increased ACh contents (without changes of other neurotransmitters) and ChAT activity and inhibited transcription of nAChRs were observed at higher concentrations. Molecular docking indicated direct interaction of DBDPE with ChAT. The results suggested that DBDPE induced hyperactivity at higher concentrations was probably involved with disrupted cholinergic system, with ChAT as a potential target. Given that the body burden of DBDPE in lower concentration group was comparable with those detected in wild fish, the current results may provide useful information for ecological risk assessment.

Exposure to tris(1,3-dichloro-2-propyl) phosphate for two generations aggravates the adverse effects on survival and growth of zebrafish at environmentally relevant concentrations.

It was reported that tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) could inhibit the growth of F0-generation fish. However, multi-generation effects of TDCIPP on survival and growth of fish remain unknown. In this study, the effects of TDCIPP on survival and growth in F1 generation zebrafish were evaluated after two-generation exposure. Results demonstrated that TDCIPP inhibited the survival and growth of F1-generation zebrafish at 96 hpf and 30 dpf. Moreover, compared with the F0 generation, two-generation exposure resulted in a greater accumulation of TDCIPP in F1 generation zebrafish, and strongly down-regulated the expression of genes related to the GH/IGF axis (gh, igf1, igf2b) and HPT axis (tshß). Taken together, for the first time, this study revealed that exposure to TDCIPP for two generations at environmentally relevant concentrations aggravated the adverse effects on growth and survival in zebrafish.

A Novel Combined Nomogram Model for Predicting the Pathological Complete Response to Neoadjuvant Chemotherapy in Invasive Breast Carcinoma of No Specific Type: Real-World Study.

Objective: To explore the value of a predictive model combining the multiparametric magnetic resonance imaging (mpMRI) radiomics score (RAD-score), clinicopathologic features, and morphologic features for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in invasive breast carcinoma of no specific type (IBC-NST). Methods: We enrolled, retrospectively and consecutively, 206 women with IBC-NST who underwent surgery after NAC and obtained pathological results from August 2018 to October 2021. Four RAD-scores were constructed for predicting the pCR based on fat-suppression T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI+C) and their combination, which was called mpMRI. The best RAD-score was combined with clinicopathologic and morphologic features to establish a nomogram model through binary logistic regression. The predictive performance of the nomogram was evaluated using the area under receiver operator characteristic (ROC) curve (AUC) and calibration curve. The clinical net benefit of the model was evaluated using decision curve analysis (DCA). Results: The mpMRI RAD-score had the highest diagnostic performance, with AUC of 0.848 among the four RAD-scores. T stage, human epidermal growth factor receptor-2 (HER2) status, RAD-score, and roundness were independent factors for predicting the pCR (P < 0.05 for all). The combined nomogram model based on these factors achieved AUCs of 0.930 and 0.895 in the training cohort and validation cohort, respectively, higher than other models (P < 0.05 for all). The calibration curve showed that the predicted probabilities of the nomogram were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme by decision curve analysis in both training and validation datasets. Conclusion: The combined nomogram model based on the mpMRI RAD-score combined with clinicopathologic and morphologic features may improve the predictive performance for the pCR of NAC in patients with IBC-NST.

High precision even-power phase modulation method for a self-mixing displacement sensor under the weak feedback regime.

A novel method called even-power phase modulation is proposed in a self-mixing displacement sensor to improve measuring accuracy, to the best of our knowledge, which is realized by combining the even-power fast algorithm with the sinusoidal phase-modulation method. By performing the even-power fast algorithm in the self-mixing interference system, the spectrum of harmonic components is broadened. In this case, the extracted first and second harmonic components in the frequency domain contain rich information, and the displacement of the target can be accurately reconstructed. The principle and signal processing approach are introduced in detail, and the simulation results show that the reconstruction error can be effectively reduced compared with the electro-optic modulator phase modulation method. A series of experiments at different vibration amplitudes is conducted to confirm the feasibility and effectiveness of the method. An amplitude of 120 nm is proved to be measurable, and the absolute error is 10 nm, which shows great potential in the field of non-contact nanometer vibration measurement sensors.

Exploring Oscillatory Dysconnectivity Networks in Major Depression During Resting State Using Coupled Tensor Decomposition.

Dysconnectivity of large-scale brain networks has been linked to major depression disorder (MDD) during resting state. Recent researches show that the temporal evolution of brain networks regulated by oscillations reveals novel mechanisms and neural characteristics of MDD. Our study applied a novel coupled tensor decomposition model to investigate the dysconnectivity networks characterized by spatio-temporal-spectral modes of covariation in MDD using resting electroencephalography. The phase lag index is used to calculate the functional connectivity within each time window at each frequency bin. Then, two adjacency tensors with the dimension of time × frequency × connectivity × subject are constructed for the healthy group and the major depression group. We assume that the two groups share the same features for group similarity and retain individual characteristics for group differences. Considering that the constructed tensors are nonnegative and the components in spectral and adjacency modes are partially consistent among the two groups, we formulate a double-coupled nonnegative tensor decomposition model. To reduce computational complexity, we introduce the low-rank approximation. Then, the fast hierarchical alternative least squares algorithm is applied for model optimization. After clustering analysis, we summarize four oscillatory networks characterizing the healthy group and four oscillatory networks characterizing the major depression group, respectively. The proposed model may reveal novel mechanisms of pathoconnectomics in MDD during rest, and it can be easily extended to other psychiatric disorders.

Effects of organic nitrogen components from terrestrial input on the phytoplankton community in Jiaozhou Bay.

Dissolved organic nitrogen (DON) from terrestrial input exacerbates eutrophication and induces harmful algal blooms. We investigated the effects of hydrophilic (Hic) and low molecular weight (LMW) DON on the phytoplankton community in Jiaozhou Bay during autumn (October 2017) and spring (May 2018). Our results showed DON additions significantly increased algal growth while decreasing community biodiversity and provide a competitive advantage for Skeletonema costatum. These situations were further intensified by increasing temperature in autumn. Additionally, Hic DON had a higher bioavailability than LMW DON. Based on emission-excitation matrix spectra, we identified protein-like components as the main components of Hic DON whereas humus-like components were the principal components of LMW. Correlation analysis confirmed a positive correlation between DON bioavailability and protein-like components. Therefore, our results indicate DON from terrestrial input disrupts the structural stability of the phytoplankton community and increases the risk of harmful algal blooms, which in turn threaten coastal ecosystems.

Decabromodiphenyl Ethane Mainly Affected the Muscle Contraction and Reproductive Endocrine System in Female Adult Zebrafish.

The novel brominated flame retardant decabromodiphenyl ethane (DBDPE) has become a widespread environmental pollutant. However, the target tissue and toxicity of DBDPE are still not clear. In the current study, female zebrafish were exposed to 1 and 100 nM DBDPE for 28 days. Chemical analysis revealed that DBDPE tended to accumulate in the brain other than the liver and gonad. Subsequently, tandem mass tag-based quantitative proteomics and parallel reaction monitoring verification were performed to screen the differentially expressed proteins in the brain. Bioinformatics analysis revealed that DBDPE mainly affected the biological process related to muscle contraction and estrogenic response. Therefore, the neurotoxicity and reproductive disruptions were validated via multilevel toxicological endpoints. Specifically, locomotor behavioral changes proved the potency of neurotoxicity, which may be caused by disturbance of muscular proteins and calcium homeostasis; decreases of sex hormone levels and transcriptional changes of genes related to the hypothalamic-pituitary-gonad-liver axis confirmed reproductive disruptions upon DBDPE exposure. In summary, our results suggested that DBDPE primarily accumulated in the brain and evoked neurotoxicity and reproductive disruptions in female zebrafish. These findings can provide important clues for a further mechanism study and risk assessment of DBDPE.

Access to sanitary toilets and health outcomes: A panel data analysis using two-way fixed effects model.

Based on the data regarding the renovation of the toilets of 30 provinces (municipalities) in rural China from 2005 to 2017, this study utilized a two-way fixed effect model to empirically test the impact of access to sanitary toilets on health, which include intestinal infectious diseases (consisting of hepatitis A, dysentery, and typhoid) and child mortality (consisting of perinatal mortality, infant mortality, and the mortality rate of children under 5). This study attempted to assess the health outcomes of the "toilet revolution" in rural China. The results showed that: (1) Access to sanitary toilets effectively reduced the incidence of hepatitis A and dysentery. For every 1% increase in the rate of access to sanitary toilets, the incidence of hepatitis A was reduced by 5.6%, and the incidence of dysentery was reduced by 36.5%. (2) Access to sanitary toilets does not significantly reduce child mortality. (3) There are obviously regional differences in the impact of access to sanitary toilets on the health outcomes. The renovation of sanitary toilets has shown the most significant effect on reducing the incidence of intestinal infectious diseases in the central region as well as the effect on reducing child mortality in the western region. It is implied that the health outcomes of China's "toilet revolution" may provide supporting evidence and experience for other developing countries and regions in implementing toilet renovation projects.

Identifying Oscillatory Hyperconnectivity and Hypoconnectivity Networks in Major Depression Using Coupled Tensor Decomposition.

Previous researches demonstrate that major depression disorder (MDD) is associated with widespread network dysconnectivity, and the dynamics of functional connectivity networks are important to delineate the neural mechanisms of MDD. Neural oscillations exert a key role in coordinating the activity of remote brain regions, and various assemblies of oscillations can modulate different networks to support different cognitive tasks. Studies have demonstrated that the dysconnectivity of electroencephalography (EEG) oscillatory networks is related with MDD. In this study, we investigated the oscillatory hyperconnectivity and hypoconnectivity networks in MDD under a naturalistic and continuous stimuli condition of music listening. With the assumption that the healthy group and the MDD group share similar brain topology from the same stimuli and also retain individual brain topology for group differences, we applied the coupled nonnegative tensor decomposition algorithm on two adjacency tensors with the dimension of time × frequency × connectivity × subject, and imposed double-coupled constraints on spatial and spectral modes. The music-induced oscillatory networks were identified by a correlation analysis approach based on the permutation test between extracted temporal factors and musical features. We obtained three hyperconnectivity networks from the individual features of MDD and three hypoconnectivity networks from common features. The results demonstrated that the dysfunction of oscillatory networks could affect the involvement in music perception for MDD patients. Those oscillatory dysconnectivity networks may provide promising references to reveal the pathoconnectomics of MDD and potential biomarkers for the diagnosis of MDD.

Influences of the hydrophilic components of two anthropogenic dissolved organic nitrogen groups on phytoplankton growth in Jiaozhou Bay, China.

Increasing human activities have caused the accumulation of dissolved organic nitrogen (DON) in the ocean, which can alter dominant coastal phytoplankton species. However, insights into DON's effects on marine phytoplankton growth are insufficient compared with those of dissolved inorganic nitrogen (DIN), especially regarding the role of specific DON components. Therefore, in this study, the effects of the hydrophilic (Hic) and low molecular weight (LMW) components of two anthropogenic DON sources on the growth and bioavailable nitrogen uptake of phytoplankton were studied using in situ cultural experiments conducted in Jiaozhou Bay, China. Animal-derived DON from domestic and livestock breeding showed a higher bioavailability compared with that of vegetal DON derived from agricultural sources, with bioavailable component proportions of 76% ± 4% and 66% ± 3%, respectively. Both forms of DON could be absorbed by Skeletonema costatum, stimulating it to become the dominant species in the mesocosm ecosystem; the hydrophilic components of DON contributed approximately 75% of the uptake of DON by S. costatum. The bioavailability of LMW DON was significantly (p < 0.05) lower than that of the Hic DON. The high bioavailability of the Hic DON was mainly associated with its protein-like T1 and T2 components, identified using parallel factor analysis on the excitation-emission-matrix spectra, while the low bioavailability of LMW DON was mainly associated with the humus-like A component. The protein-like T2 components may be directly absorbed by algae, while T1 may be transformed through mineralization and algal absorption. Understanding the impacts of anthropogenic DON and its components on phytoplankton will help improve coastal environmental management. More knowledge of the effect of anthropogenic DON on the phytoplankton community structure in coastal waters should be accumulated in the future.

Shared and Unshared Feature Extraction in Major Depression During Music Listening Using Constrained Tensor Factorization.

Ongoing electroencephalography (EEG) signals are recorded as a mixture of stimulus-elicited EEG, spontaneous EEG and noises, which poses a huge challenge to current data analyzing techniques, especially when different groups of participants are expected to have common or highly correlated brain activities and some individual dynamics. In this study, we proposed a data-driven shared and unshared feature extraction framework based on nonnegative and coupled tensor factorization, which aims to conduct group-level analysis for the EEG signals from major depression disorder (MDD) patients and healthy controls (HC) when freely listening to music. Constrained tensor factorization not only preserves the multilinear structure of the data, but also considers the common and individual components between the data. The proposed framework, combined with music information retrieval, correlation analysis, and hierarchical clustering, facilitated the simultaneous extraction of shared and unshared spatio-temporal-spectral feature patterns between/in MDD and HC groups. Finally, we obtained two shared feature patterns between MDD and HC groups, and obtained totally three individual feature patterns from HC and MDD groups. The results showed that the MDD and HC groups triggered similar brain dynamics when listening to music, but at the same time, MDD patients also brought some changes in brain oscillatory network characteristics along with music perception. These changes may provide some basis for the clinical diagnosis and the treatment of MDD patients.

The effect of Xiaobi decoction on minimal erythema dose of irradiation with 308 nm excimer lamp in guinea pigs.

BACKGROUND: Psoriasis is a chronic autoimmune-mediated inflammatory skin disease. The main clinical manifestation of this complex condition is scaly erythema. Excimer 308-nm light can be used to selectively and safely treat skin lesions. In clinical practice, the combination of Xiaobi decoction combined with 308-nm excimer light therapy has been found to have a beneficial effect on advanced psoriasis vulgaris. However, the effect of Xiaobi decoction on light sensitivity in psoriasis patients has not been explored. Therefore, this study aimed to observe the effect of Xiaobi decoction on the minimal erythema dose (MED) value in guinea pigs. METHODS: Eighty guinea pigs were divided into a Xiaobi decoction group and a control group according to the serial number: guinea pigs with odd numbers were assigned into the Xiaobi decoction group, and those with even numbers were assigned into the control group. The Xiaobi decoction group was administrated Xiaobi decoction by gastric lavage, while the control group was given distilled water by gastric lavage. The back skin of the guinea pigs in the two groups was irradiated with a 308-nm excimer lamp before gavaging, and after 10, 20, and 30 days of gavaging. The MED values 24 hours after irradiation were recorded. RESULTS: The average MED in the Xiaobi decoction group was (800±126.5) mJ/cm2, compared with (780±107.7) mJ/cm2 in the control group, and the difference was not significant (P>0.05). After 10 days, 20 days, and 30 days of gavaging, the MED values of the guinea pigs in the Xiaobi decoction group were significantly lower than those of the control group (P<0.05). Blood tests showed that the levels of vascular endothelial growth factor (164.5±25.7 vs. 145.3±27.4, P=0.002) and interleukin-23 (1.8±0.7 vs. 1.5±0.5, P=0.030) were significantly lower in the Xiaobi decoction group than in the control group. CONCLUSIONS: Xiaobi decoction can reduce the MED value of guinea pigs, and increase the sensitivity of skin lesions to 308-nm excimer light and the amount of light absorbed by skin lesions. These results may represent the mechanisms of action of Xiaobi decoction in the treatment of psoriasis.

Characterization of the development stages and roles of nutrients and other environmental factors in green tides in the Southern Yellow Sea, China.

Large-scale floating green tides in the Southern Yellow Sea (SYS) caused by the macroalgal species Ulva prolifera have been recurring for 13 years and have become one of the greatest marine ecological disasters in the world. In this study, we attempt to explore the development pattern of green tides and find its key environmental influencing factors. The satellite remote sensing data of the development process of green tides fit the logistic growth curve (R2 = 0.93, P < 0.01) well, showing three distinct growth phases (lag, exponential growth, and short plateau phases). Correspondingly, the green tide-drifting area from the coast of Jiangsu to the nearshore waters of the Shandong Peninsula was divided into three sections: the lag phase zone (A), the exponential growth phase zone (B), and the plateau phase zone (C). Zone A in the south of Jiangsu coastal waters had abundant inorganic nutrients that were indispensable to the green tide initiation. Zone B was mainly located out of Haizhou Bay, south of 34.5° N and north of 35.5° N, where approximately 80% of the green tide biomass was generated. The rich bioavailable nutrient sources, suitable temperature, and irradiance in this area were the main promotion factors for the rapid growth and scale expansion of green tides. Wet precipitation in zone B in May and June also played an important role in the final scale of green tides. Zone C had poor nutrients, increasing temperature, and irradiance (high transparency), which limited the continued expansion of green tides, and organic nutrients might be an important support to green tides development in this region. The study based on the growth phases of green tides could help us further understand the eutrophication mechanism in the green tide outbreaks in SYS.