C-H-activated Csp2-Csp3 diastereoselective gridization enables ultraviolet-emitting stereo-molecular nanohydrocarbons with mulitple H···H interactions.

Gridization is an emerging molecular integration technology that enables the creation of multifunctional organic semiconductors through precise linkages. While Friedel-Crafts gridization of fluorenols is potent, direct linkage among fluorene molecules poses a challenge. Herein, we report an achiral Pd-PPh3-cataylized diastereoselective (>99:1 d.r.) gridization based on the C-H-activation of fluorene to give dimeric and trimeric windmill-type nanogrids (DWGs and TWGs). These non-conjugated stereo-nanogrids showcase intramolecular multiple H…H interactions with a low field shift to 8.51 ppm and circularly polarized luminescence with high luminescent dissymmetry factors (|gPL | = 0.012). Significantly, the nondoped organic light-emitting diodes (OLEDs) utilizing cis-trans-TWG1 emitter present an ultraviolet electroluminescent peak at ~386 nm (CIE: 0.17, 0.04) with a maximum external quantum efficiency of 4.17%, marking the highest record among nondoped ultraviolet OLEDs based on hydrocarbon compounds and the pioneering ultraviolet OLEDs based on macrocycles. These nanohydrocarbon offer potential nanoscafflolds for ultraviolet light-emitting optoelectronic applications.

A polo-like kinase 1 inhibitor enhances erastin sensitivity in head and neck squamous cell carcinoma cells in vitro.

BACKGROUND: Polo-like kinase 1 (PLK1) is a critical therapeutic target in the treatment of head and neck squamous cell carcinoma (HNSCC). The objective of this study was to investigate the therapeutic effect of the combination of BI 2536, a PLK1 inhibitor, and erastin, a ferroptosis inducer, in HNSCC. METHODS: The proliferation, invasion, and migration abilities of Tu177 and FaDu cells upon exposure to BI 2536 and erastin, used in combination or alone, were tested. Fe2+, glutathione (GSH), and malondialdehyde (MDA) detection kits were used to determine whether the addition of BI 2536 enhanced the accumulation of Fe2+ and MDA, along with the depletion of GSH. Quantitative real-time PCR, western blot analyses were performed to investigate whether BI 2536 further altered the mRNA and expression level of ferroptosis genes. Furthermore, si PLK1 was used to investigate whether targeting PLK1 gene promoted erastin-induced ferroptosis. RESULTS: The combination of BI 2536 and erastin exerted a stronger cytotoxicity than treatment with a single agent. Compared with erastin treatment alone, the combination of BI 2536 and erastin lowered the ability of tumor cells to self-clone, invade, and migrate. BI 2536 enhanced the accumulation of Fe2+ and MDA, and the depletion of GSH. BI 2536 increased erastin-induced changes in ferroptosis-related gene mRNA and expression. Importantly, targeting PKL1 enhanced the anti-cancer effect of erastin. CONCLUSION: BI 2536 enhanced the sensitivity of HNSCC cells to erastin, which provides a new perspective for cancer treatment.

Confounder balancing in adversarial domain adaptation for pre-trained large models fine-tuning.

The excellent generalization, contextual learning, and emergence abilities in the pre-trained large models (PLMs) handle specific tasks without direct training data, making them the better foundation models in the adversarial domain adaptation (ADA) methods to transfer knowledge learned from the source domain to target domains. However, existing ADA methods fail to account for the confounder properly, which is the root cause of the source data distribution that differs from the target domains. This study proposes a confounder balancing method in adversarial domain adaptation for PLMs fine-tuning (CadaFT), which includes a PLM as the foundation model for a feature extractor, a domain classifier and a confounder classifier, and they are jointly trained with an adversarial loss. This loss is designed to improve the domain-invariant representation learning by diluting the discrimination in the domain classifier. At the same time, the adversarial loss also balances the confounder distribution among source and unmeasured domains in training. Compared to newest ADA methods, CadaFT can correctly identify confounders in domain-invariant features, thereby eliminating the confounder biases in the extracted features from PLMs. The confounder classifier in CadaFT is designed as a plug-and-play and can be applied in the confounder measurable, unmeasurable, or partially measurable environments. Empirical results on natural language processing and computer vision downstream tasks show that CadaFT outperforms the newest GPT-4, LLaMA2, ViT and ADA methods.

Corrigendum: Therapy by physician-pharmacist combination and economic returns for cancer pain management in China: a cost-effectiveness analysis.

[This corrects the article DOI: 10.3389/fphar.2023.1073939.].

Antidepressant effect of bright light therapy on patients with Alzheimer's disease and their caregivers.

Background: As a non-pharmacologic treatment, bright light therapy (BLT) is often used to improve affective disorders and memory function. In this study, we aimed to determine the effect of BLT on depression and electrophysiological features of the brain in patients with Alzheimer's disease (AD) and their caregivers using a light-emitting diode device of 14000 lux. Methods: A 4-week case-control trial was conducted. Neuropsychiatric and electroencephalogram (EEG) examination were evaluated at baseline and after 4 weeks. EEG power in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) bands was calculated for our main analysis. Demographic and clinical variables were analyzed using Student's t test and the chi-square test. Pearson's correlation was used to determine the correlation between electrophysiological features, blood biochemical indicators, and cognitive assessment scale scores. Results: In this study, 22 in-patients with AD and 23 caregivers were recruited. After BLT, the Hamilton depression scale score decreased in the fourth week. Compared with the age-matched controls of their caregivers, a higher spectral power at the lower delta and theta frequencies was observed in the AD group. After BLT, the EEG power of the delta and theta frequencies in the AD group decreased. No change was observed in blood amyloid concentrations before and after BLT. Conclusion: In conclusion, a 4-week course of BLT significantly suppressed depression in patients with AD and their caregivers. Moreover, changes in EEG power were also significant in both groups.

Therapy by physician-pharmacist combination and economic returns for cancer pain management in China: a cost-effectiveness analysis.

Objective: To examine whether joint management of cancer pain by physicians and pharmacists in clinics provides economic advantages from the perspective of the Chinese healthcare system. Methods: From February 2018 to March 2020, 100 patients who visited the joint cancer pain clinic at the Xiangya Hospital of Central South University were included. These patients were randomly assigned to either the control or intervention groups. The control group received regular outpatient services from a physician, while the intervention group received regular outpatient services from a physician and medication education provided by a pharmacist. The study considered various direct costs, including drug expenses, physician-pharmacist outpatient services, adverse event management, consultations, examinations, and readmissions. The outcome indicators considered were the cancer pain control rate and the reduction in pain scores. Decision tree modeling, single-factor sensitivity analysis, and probabilistic sensitivity analysis were performed to evaluate the cost-effectiveness of joint physician-pharmacist outpatient services compared to physician-alone outpatient services. Results: The intervention group showed a significantly higher cancer pain control rate than the control group (0.69 vs. 0.39, p = 0.03). In the decision tree model, the intervention group had a significantly lower pain score than the control group (0.23 vs. 0.14). The cost per person in the intervention group was $165.39, while it was $191.1 per person in the control group. The univariate sensitivity analysis showed that the cost of self-management for patients in the control group was identified as the primary sensitivity factor. Probabilistic sensitivity analysis indicated that the joint clinic group had a favorable incremental cost-effectiveness compared to the physician clinic group. In addition, the probabilistic sensitivity analysis demonstrated an absolute advantage in the incremental cost-effectiveness of the joint clinic group over the outpatient physician group. Conclusion: The participation of pharmacists in joint cancer pain clinic services led to improved pain management for patients, demonstrating a clear advantage in terms of cost-effectiveness.

Post-Marketing Safety Concerns with Upadacitinib: A Disproportionality Analysis of the FDA Adverse Event Reporting system.

BACKGROUND: Upadacitinib was approved to treat rheumatoid arthritis, psoriasis, ulcerative colitis, ankylosing spondylitis, and atopic dermatitis. This study assessed the adverse events (AEs) associated with upadacitinib by mining data from the US Food and Drug Administration Adverse Event Reporting System (FAERS). METHODS: Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) algorithms, were employed to quantify the signals of upadacitinib-associated AEs. RESULTS: A total of 3,837,420 reports of AEs were collected from the FAERS database, of which 4494 reports were identified with upadacitinib as the "primary suspect (PS)". Upadacitinib-induced AEs occurrence targeted 27 system organ clases (SOCs). A total of 200 significant disproportionality PTs conforming to the four algorithms were simultaneously retained. Unexpected significant AEs, such as arthralgia, musculoskeletal stiffness, diverticulitis, and cataract might also occur. The median onset time of upadacitinib-associated AEs was 65 days (interquartile range [IQR] 21-182 days), and most of the onsets occurred within the first 1, 2, 3, and 4 months after initiation of upadacitinib. CONCLUSION: This study found potential new AEs signals and might provide important support for clinical monitoring and risk identification of upadacitinib.

Sentiment analysis algorithm using contrastive learning and adversarial training for POI recommendation.

Finding a suitable POI based on the user's needs and intentions is a complex decision-making process. Obtaining valuable information from the vast amount of social media data and using it for travel recommendations is a challenging issue. Traditional POI recommendation algorithms do not fully take into account the true feelings of customers about tourist attractions implied in social media data because they usually require a large amount of tagged travel commentary data. This study presents an aspect-based sentiment analysis model and POI recommendation method to accurately capture sentiment information contained in social media data with a small amount of tagged data. The pre-training model BERT is used to obtain the embedded representation of words that fuse the semantic information of the text. Using contrastive learning, point clusters belonging to the same class in the embedded space of words are pulled together, and sample clusters from different classes are separated. The potential relationship between comment ratings and their impact on user perception is analyzed, and the best performance formula for the loss function is determined. The test accuracy and F1-Score of the model in the experiment improved by 13.03% and 12.23%, respectively, compared to the BERT base model. POI recommendation validation is performed using a variety of recommendation algorithms. The experimental results show that the addition of aspect-based sentiment attributes can effectively improve the accuracy of recommendations.

Aqueous-soluble components of sporoderm-removed Ganoderma lucidum spore powder promote ferroptosis in oral squamous cell carcinoma.

Objective: Ferroptosis is a novel cell death process which displays a promising role in cancer treatment. However, clinically available drugs targeting ferroptosis are rarely used, and yet there are no studies reporting on inducing ferroptosis via Chinese herbal extracts. Here we explored the tumor inhibition effects of Ganoderma lucidum (G. lucidum) on oral squamous cell carcinoma (OSCC). Specifically, we aimed to clarify the biological mechanism of components in the dietary, aqueous-soluble sporoderm-removed G. lucidum spore powder (A-GSP). Methods: Preliminary transcriptome analysis revealed the significant enrichment of the ferroptosis pathway. Cellular Fe2+, glutathione (GSH), malondialdehyde (MDA), reactive oxygen species (ROS) and lipid peroxide levels were measured to identify ferroptosis occurrence. Western blotting was used to measure ferroptosis-related proteins. Changes in mitochondria morphology and function were observed with transmission electron microscopy (TEM) and ATP detection assays. Ferroptosis inhibitor ferrostatin-1 was then used to verify the anti-tumor effects of A-GSP. Finally, nude mice xenograft models of oral cancer confirmed that A-GSP inhibited tumor growth. Results: A-GSP promoted ferroptosis in oral cancer cells by inducing Fe2+ influx, GSH depletion, as well as lipid peroxide and ROS accumulation. Ferroptosis-related proteins exhibited corresponding changes, particularly Acyl-coA synthetase long chain family member 4 (ACSL4) increase and glutathione peroxidase 4 (GPX4) decrease. A-GSP considerably lowered mitochondrial volume and ridge number, while significantly decreasing ATP production. Ferrostatin-1 reversed all of these A-GSP-induced changes. In vivo, A-GSP exerted a ferroptosis-mediated tumor-suppressing effect without observable adverse reactions. Conclusions: Our findings demonstrate the therapeutic potential of A-GSP for treating patients with OSCC by targeting ferroptosis.

Signal mining and analysis for central nervous system adverse events due to taking oxycodone based on FAERS database. / 基于FAERSæ•°æ®åº“çš„ç¾Ÿè€ƒé ®ä¸­æž¢ç¥žç»ç³»ç»Ÿä¸è‰¯äº‹ä»¶ä¿¡å·æŒ–æŽ˜åŠåˆ†æž.

OBJECTIVES: Central nervous system adverse events (AEs) occur when oxycodone is used in combination with benzodiazepines, antidepressants and anticonvulsants. There have been no reports of central nervous system AEs with oxycodone alone or in combination with oxycodone. Based on USA Food and Drug Administration Adverse Event Reporting System (FAERS) data, this study aims to explore the risk signals of central nervous system AEs with oxycodone alone or in combination with benzodiazepines, antidepressants and anticonvulsants, and to provide a reference for the safe and rational use of this drug. METHODS: Extracted AEs data from the FAERS for oxycodone alone and in combination with benzodiazepines, antidepressants, and anticonvulsants from Q1 2004 to Q2 2021. The risk signal mining analysis of AEs was performed using the proportional imbalance method and Bayesian method. Number of reports ≥3 and lower 95% CI limit of reporting odds ratio (ROR)>1; number of reports ≥3, proportional reporting ratio (PRR)≥2 and χ2≥4; lower information components (IC) lower 95% CI limit (IC025)>0; empirical Bayes geometric mean (EBGM) lower 95% CI limit (EBGM05)>2, and N>0 were defined as positive signals. RESULTS: A total of 5 793 reports of central nervous system AEs with oxycodone alone were tapped, and 366, 622, and 740 reports of combined benzodiazepines, antidepressants, and anticonvulsants, respectively. Consumers and physicians were the main reporting population. The age distribution of oxycodone alone was mainly from 61 to 80 years old. The age distribution of oxycodone in combination with related drugs was mainly from 46 to 60 years old. The risk of AEs was greater in women than in men, and the United States was the predominant reporting country. Oxycodone alone was strongly associated with myoclonus [ROR=2.92, 95% CI 2.28 to 3.76); PRR=2.92, χ2(77.49); IC=1.52, IC025(0.65); EBGM=2.89, EBGM05(2.33)], delirium [ROR=4.69, 95% CI 4.24 to 5.21; PRR=4.66, χ2(1 052.64); IC=2.17, IC025(1.81); EBGM=4.50, EBGM05 (4.13)], mental disorder [ROR=2.95, 95% CI 2.53 to 3.44; PRR=2.94, χ2(206.93); IC=1.56, IC025(0.96); EBGM=2.95, EBGM05(2.58)], and acute central respiratory depression [ROR=2.87, 95% CI 2.68 to 3.08); PRR=2.82, χ2(971.62); IC=1.52, IC025(1.33), EBGM=2.87, EBGM05 (2.76)]. Combination of benzodiazepines was most strongly associated with mental disorder [ROR=10.08, 95% CI 9.38 to 10.78; PRR=9.90, χ2(64.06); IC=3.33, IC025 (1.65); EBGM=10.08, EBGM05(5.61)], and tremor [ROR=3.09, 95% CI 2.76 to 3.42); PRR=3.08, χ2(48.93); IC=1.63, IC025 (1.17); EBGM=3.09, EBGM05(2.34)]. Combination of antidepressants was most strongly associated with delirium [ROR=13.23, 95% CI 12.23 to 14.23; PRR=12.87, χ2(43.86); IC=3.69, IC025(1.36); EBGM=12.23, EBGM05 (5.32)] and somnolence [ROR=6.74, 95% CI 6.15 to 7.33); PRR=6.73, χ2(53.42); IC=2.75, IC025(1.52); EBGM=6.73, EBGM05(4.10)]. Combination of anticonvulsants was most strongly associated with myoclonus [ROR=17.89, 95% CI 17.46 to 18.32; PRR=17.72, χ2(971.39); IC=4.16, IC025(2.70); EBGM=17.89, EBGM05(12.46)] and delirium [ROR=4.86, 95% CI 4.45 to 5.27); PRR=4.82, χ2(69.49); IC=2.28, IC025 (1.51); EBGM=4.86, EBGM05(3.44)]. CONCLUSIONS: Based on pharmacovigilance studies of the FAERS database, clinical medication monitoring of oxycodone alone and in combination with benzodiazepines, antidepressants, and anticonvulsants should be strengthened to be alert to the occurrence of central nervous system-related AEs.

Late-life depression: Epidemiology, phenotype, pathogenesis and treatment before and during the COVID-19 pandemic.

Late-life depression (LLD) is one of the most common mental disorders among the older adults. Population aging, social stress, and the COVID-19 pandemic have significantly affected the emotional health of older adults, resulting in a worldwide prevalence of LLD. The clinical phenotypes between LLD and adult depression differ in terms of symptoms, comorbid physical diseases, and coexisting cognitive impairments. Many pathological factors such as the imbalance of neurotransmitters, a decrease in neurotrophic factors, an increase in ß-amyloid production, dysregulation of the hypothalamic-pituitary-adrenal axis, and changes in the gut microbiota, are allegedly associated with the onset of LLD. However, the exact pathogenic mechanism underlying LLD remains unclear. Traditional selective serotonin reuptake inhibitor therapy results in poor responsiveness and side effects during LLD treatment. Neuromodulation therapies and complementary and integrative therapies have been proven safe and effective for the treatment of LLD. Importantly, during the COVID-19 pandemic, modern digital health intervention technologies, including socially assistive robots and app-based interventions, have proven to be advantageous in providing personal services to patients with LLD.

Does China's competitive generic substitution policy deliver equivalent clinical outcomes? A pilot study with two generic formulations of olanzepine.

With the National Centralized Drug Procurement policy gradually applied nationally in China, concerns about the effectiveness and safety of bid-winning generic drugs are growing again, but relevant studies are lacking. This real-world, before-and-after study was conducted to explore the clinical effects of switching between two versions of generic olanzapine (one of them was bid-winning product). Pre-and post-switching serum olanzapine concentrations were compared. A total of 30 patients were included and results showed the log-transformed, dose-adjusted concentration of bid-winning generic olanzapine was significantly lower than that of another generic olanzapine, while no significant differences were shown on Clinical Global Impressions Severity of Illness or Improvement ratings before and after switching. This study suggest that a generic version of a psychotropic medication may not be of therapeutic equivalence or bioequivalence with another generic one. Changes in efficacy or tolerability are possible in every switch. Therapeutic drug monitoring could be a valuable tool during switches between generic drugs. Larger prospective clinical studies for other generic psychotropic medications in target populations are warranted.

Evaluation of anticholinergic burden in elderly outpatients and the risk factors. / è€å¹´é—¨è¯Šæ‚£è€ æŠ—èƒ†ç¢±èƒ½å¤„æ–¹è´Ÿæ‹ è¯„ä»·åŠå ¶å±é™©å› ç´ .

OBJECTIVES: The use of anticholinergic drugs in the elderly may lead to negative events such as falls, delirium, urinary retention and cognitive decline, and the higher the number of anticholinergic drugs use, the more such negative events occur. This study aims to analyze the risk factors associated with the prescription of total anticholinergic drugs in elderly outpatients and evaluate the rationality of anticholinergic drugs, and to provide a reference for reducing the adverse effects of anticholinergic drugs. METHODS: A list of drugs with anticholinergic activity based on the Beers criteria was established. The basic information (such as age and gender), clinical diagnosis, and medications of elderly outpatient were extracted from hospital electronic medical records, and the Anticholinergic Cognitive Burden (ACB) Scale was used to calculate the anticholinergic burden for each patient. Logistic regression analysis was used to identify the potential risk factors for the occurrence of problems such as multiple medication and insomnia. RESULTS: A total of 1 840 prescriptions for elderly patients were reviewed. Of these patients, ACB score was more than or equal to 1 in 648 (35.22%) patients. Number of prescription medication (95% CI: 1.221 to 1.336) and insomnia (95% CI: 3.538 to 6.089) were independent factors affecting ACB scores (both P<0.01). Medications for patients of ACB scores were most commonly treated with the central nervous system drugs (such as alprazolam and eszopiclone) and for the cardiovascular system drugs (such as metoprolol and nifedipine). CONCLUSIONS: There is a high rate of ACB drugs use in geriatric patients, and the clinical focus should be on multiple medication prescriptions, especially on the central nervous system drugs (such as alprazolam and eszopiclone) and cardiovascular system drugs (such as metoprolol and nifedipine). The prescription review should be emphasized to reduce adverse reactions to anticholinergic drugs in elderly patients.

Intelligent Design of Construction Materials: A Comparative Study of AI Approaches for Predicting the Strength of Concrete with Blast Furnace Slag.

Concrete production by replacing cement with green materials has been conducted in recent years considering the strategy of sustainable development. This study researched the topic of compressive strength regarding one type of green concrete containing blast furnace slag. Although some researchers have proposed using machine learning models to predict the compressive strength of concrete, few researchers have compared the prediction accuracy of different machine learning models on the compressive strength of concrete. Firstly, the hyperparameters of BP neural network (BPNN), support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbor algorithm (KNN), logistic regression (LR), and multiple linear regression (MLR) are tuned by the beetle antennae search algorithm (BAS). Then, the prediction effects of the above seven machine learning models on the compressive strength of concrete are evaluated and compared. The comparison results show that KNN has higher R values and lower RSME values both in the training set and test set; that is, KNN is the best model for predicting the compressive strength of concrete among the seven machine learning models mentioned above.

Intelligent Design of Building Materials: Development of an AI-Based Method for Cement-Slag Concrete Design.

Cement-slag concrete has become one of the most widely used building materials considering its economical advantage and satisfying uniaxial compressive strength (UCS). In this study, an AI-based method for cement-slag concrete design was developed based on the balance of economic and mechanical properties. Firstly, the hyperparameters of random forest (RF), decision tree (DT), and support vector machine (SVM) were tuned by the beetle antennae search algorithm (BAS). The results of the model evaluation showed the RF with the best prediction effect on the UCS of concrete was selected as the objective function of UCS optimization. Afterward, the objective function of concrete cost optimization was established according to the linear relationship between concrete cost and each mixture. The obtained results showed that the weighted method can be used to construct the multi-objective optimization function of UCS and cost for cement-slag concrete, which is solved by the multi-objective beetle antennae search (MOBAS) algorithm. An optimal concrete mixture ratio can be obtained by Technique for Order Preference by Similarity to Ideal Solution. Considering the current global environment trend of "Net Carbon Zero", the multi-objective optimization design should be proposed based on the objectives of economy-carbon emission-mechanical properties for future studies.

Reduced Cell-Free Mitochondrial DNA Levels Were Induced by Antipsychotics Treatment in First-Episode Patients With Schizophrenia.

Cell-free mitochondrial DNA (cf-mtDNA) is a damage-associated molecular pattern that boosts the release of cytokines and induces the immune response of the body; therefore, it is closely related to mental diseases. This study aims to evaluate a potential link between cf-mtDNA and clinical progression in first-episode patients with schizophrenia. In this study, plasma cf-mtDNA levels in 34 first-episode patients with schizophrenia before and after 8 weeks of antipsychotic treatment were examined. In addition, the clinical progression of first-episode schizophrenia was assessed using the Positive and Negative Syndrome Scale (PANSS). The copy number changes in the plasma cf-mtDNA (Δcf-mtDNA) were significantly correlated with changes in the PANSS scale scores (ΔPANSS) in first-episode patients with schizophrenia (ΔPANSS total score, P = 0.002; ΔPANSS positive score, P = 0.01). Plasma cf-mtDNA may represent a relevant tool in the future to assist in the assessment of clinical progression in first-episode patients with schizophrenia.

A rapid liquid chromatography-electrospray ionization-ion mobility spectrometry method for monitoring nine representative metabolites in the seedlings of cucumber and wheat.

A fast and convenient high-performance liquid chromatography-electrospray ionization-ion mobility spectrometry method was developed to determine nine representative metabolites in the seedlings of cucumber and wheat. The analytical conditions were obtained by optimizing the parameters of high-performance liquid chromatography and ion mobility spectrometry. Briefly, acetonitrile-0.1% formic acid solution was selected as the mobile phase for gradient elution at a flow velocity of 0.4 mL/min. Under negative electrospray ionization mode, spray voltage of ion mobility spectrometry was 4.5 kV, and drift tube temperature was set at 90°C. The metabolites from seedling leaves were extracted using 80% acetonitrile as the solvent at 4°C for 12 h. Results showed that under soilless culture conditions, the contents of maltose, citric acid, and p-hydroxybenzoic acid in the seedlings of cucumber and wheat were reduced by low concentration of itaconic acid, succinic acid, and citric acid. Importantly, this analytical approach demonstrated high sensitivity, good linear response, and high selectivity. The lowest limit of detection was 0.004 µg for p-hydroxybenzoic acid. Overall, this high-performance liquid chromatography-electrospray ionization-ion mobility spectrometry method is sensitive and efficient for rapid separation and identification of plant metabolites.

Reduced serum VGF levels are linked with suicide risk in Chinese Han patients with major depressive disorder.

BACKGROUND: VGF (nonacronymic) is a neuropeptide that plays an important role in the pathogenesis of major depressive disorder (MDD). However, no studies have yet investigated VGF levels in patients with MDD who are at risk of suicide. The purpose of the present study was to determine whether serum VGF levels are related to suicide risk in patients with MMD. METHODS: A total of 107 patients with MDD and 40 normal control participated in the present study. The risk of suicide was assessed using the Nurses Global Assessment of Suicide Risk (NGASR). On this basis, 60 patients were assigned to a high-risk group (NGASR≥9) and 47 were assigned to a low-risk group (NGASR< 9). The severity of depression was measured using the 17-item Hamilton Depression Rating Scale (HDRS). Levels of serum VGF were determined using a double antibody sandwich enzyme-linked immunosorbent assay. RESULTS: Serum VGF levels in the high-risk group (883.34 ± 139.67 pg/mL) were significantly lower than in the low-risk group (1020.56 ± 131.76 pg/mL) and in the control group (1107.00 ± 155.38 pg/mL) (F = 31.90, p < 0.001). In patients with MDD, suicide risk was significantly negatively correlated with VGF levels (r = - 0.55, p = 0.001). CONCLUSIONS: Reduced serum VGF levels are related to risk of suicide in patients with MDD, so VGF may be a biomarker of suicide risk in MDD.

Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition.

We propose a novel model, called stroke sequence-dependent deep convolutional neural network (SSDCNN), which uses the stroke sequence information and eight-directional features of Chinese characters for online handwritten Chinese character recognition (OLHCCR). SSDCNN learns the representation of OLHCCs by incorporating the natural sequence information of the strokes. Furthermore, it naturally incorporates the eight-directional features. First, SSDCNN inputs the stroke sequence and transforms it into stacks of feature maps following the writing order of the strokes. Second, the fixed-length, stroke sequence-dependent representations of OLHCC are derived through convolutional, residual, and max-pooling operations. Third, the stroke sequence-dependent representation is combined with the eight-directional features via a number of fully connected neural network layers. Finally, the Chinese characters are recognized using a softmax classifier. The SSDCNN is trained in two stages: 1) the whole architecture is pretrained using the training data until the performance converges to an acceptable degree. 2) The stroke sequence-dependent representation is combined with the eight-directional features by a fully connected neural network and a softmax layer for further training. The model was experimentally evaluated on the OLHCCR competition tasks of International Conference on Document Analysis and Recognition (ICDAR) 2013. The recognition error was a maximum 58.28% lower in SSDCNN than in a model using the eight-directional features alone (5.13% versus 2.14%). Owing to its high accuracy (97.86%), the proposed SSDCNN reduced the recognition error by approximately 18.0% as compared with that of the winning system in the ICDAR 2013 competition. SSDCNN integrated with an adaptation mechanism, called the SSDCNN+Adapt model, and reached a new state-of-the-art (SOTA) standard with an accuracy of 97.94%. The SSDCNN exploits the stroke sequence information to learn high-quality OLHCC representations. Moreover, the learned representation and the classical eight-directional features complement each other within the SSDCNN architecture.