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Cognitive flexibility is a fundamental ability that enables humans and animals to exhibit appropriate behaviors in various contexts. The thalamocortical interactions between the prefrontal cortex (PFC) and the mediodorsal thalamus (MD) have been identified as crucial for inferring temporal context, a critical component of cognitive flexibility. However, the neural mechanism responsible for context inference remains unknown. To address this issue, we propose a PFC-MD neural circuit model that utilizes a Hebbian plasticity rule to support rapid, online context inference. Specifically, the model MD thalamus can infer temporal contexts from prefrontal inputs within a few trials. This is achieved through the use of PFC-to-MD synaptic plasticity with pre-synaptic traces and adaptive thresholding, along with winner-take-all normalization in the MD. Furthermore, our model thalamus gates context-irrelevant neurons in the PFC, thus facilitating continual learning. We evaluate our model performance by having it sequentially learn various cognitive tasks. Incorporating an MD-like component alleviates catastrophic forgetting of previously learned contexts and demonstrates the transfer of knowledge to future contexts. Our work provides insight into how biological properties of thalamocortical circuits can be leveraged to achieve rapid context inference and continual learning., (© 2024. The Author(s).)

Background: Loss-of-function mutations of ZBTB24 cause immunodeficiency, centromeric instability, and facial anomalies syndrome 2 (ICF2). ICF2 is a rare autosomal recessive disorder with immunological defects in serum antibodies and circulating memory B cells, resulting in recurrent and sometimes fatal respiratory and gastrointestinal infections. The genotype-phenotype correlation in patients with ICF2 indicates an essential role of ZBTB24 in the terminal differentiation of B cells., Methods: We used the clustered regularly interspaced short palindromic repeats (CRISPER)/Cas9 technology to generate B cell specific Zbtb24-deficient mice and verified the deletion specificity and efficiency by quantitative polymerase chain reaction (Q-PCR) and western blotting analyses in fluorescence-activated cell sorting (FACS)-sorted cells. The development, phenotype of B cells and in vivo responses to T cell dependent or independent antigens post immunization were analyzed by flow cytometry and enzyme-linked immunosorbent assay (ELISA). Adoptive transfer experiment in combination with in vitro cultures of FACS-purified B cells and RNA-Seq analysis were utilized to specifically determine the impact of Zbtb24 on B cell biology as well as the underlying mechanisms., Results: Zbtb24 is dispensable for B cell development and maintenance in naive mice. Surprisingly, B cell specific deletion of Zbtb24 does not evidently compromise germinal center reactions and the resulting primary and secondary antibody responses induced by T cell dependent antigens (TD-Ags), but significantly inhibits T cell independent antigen-elicited antibody productions in vivo. At the cellular level, Zbtb24-deficiency specifically impedes the plasma cell differentiation of B1 cells without impairing their survival, activation and proliferation in vitro. Mechanistically, Zbtb24-ablation attenuates heme biosynthesis partially through mTORC1 in B1 cells, and addition of exogenous hemin abrogates the differentiation defects of Zbtb24-null B1 cells., Conclusions: Zbtb24 seems to regulate antibody responses against TD-Ags B cell extrinsically, but it specifically promotes the plasma cell differentiation of B1 cells via heme synthesis in mice. Our study also suggests that defected B1 functions contribute to recurrent infections in patients with ICF2., (© 2024. The Author(s).)

Background: Identical bursts on electroencephalography (EEG) are considered a specific predictor of poor outcomes in cardiac arrest, but its relationship with structural brain injury severity on magnetic resonance imaging (MRI) is not known., Methods: This was a retrospective analysis of clinical, EEG, and MRI data from adult comatose patients after cardiac arrest. Burst similarity in first 72 h from the time of return of spontaneous circulation were calculated using dynamic time-warping (DTW) for bursts of equal (i.e., 500 ms) and varying (i.e., 100-500 ms) lengths and cross-correlation for bursts of equal lengths. Structural brain injury severity was measured using whole brain mean apparent diffusion coefficient (ADC) on MRI. Pearson's correlation coefficients were calculated between mean burst similarity across consecutive 12-24-h time blocks and mean whole brain ADC values. Good outcome was defined as Cerebral Performance Category of 1-2 (i.e., independence for activities of daily living) at the time of hospital discharge., Results: Of 113 patients with cardiac arrest, 45 patients had burst suppression (mean cardiac arrest to MRI time 4.3 days). Three study participants with burst suppression had a good outcome. Burst similarity calculated using DTW with bursts of varying lengths was correlated with mean ADC value in the first 36 h after cardiac arrest: Pearson's r: 0-12 h: - 0.69 (p = 0.039), 12-24 h: - 0.54 (p = 0.002), 24-36 h: - 0.41 (p = 0.049). Burst similarity measured with bursts of equal lengths was not associated with mean ADC value with cross-correlation or DTW, except for DTW at 60-72 h (- 0.96, p = 0.04)., Conclusions: Burst similarity on EEG after cardiac arrest may be associated with acute brain injury severity on MRI. This association was time dependent when measured using DTW., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Purpose: To compare the efficacy of transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKIs) plus immune checkpoint inhibitors (ICIs) (TACE-TKI-ICI) versus TKIs plus ICIs (TKI-ICI) for unresectable hepatocellular carcinoma (HCC) with first- or lower-order portal vein tumor thrombosis (PVTT)., Materials and Methods: A retrospective study was performed in HCC patients with first- or lower-order PVTT receiving TKIs (Lenvatinib or sorafenib) plus ICIs (camrelizumab, sintilimab, or atezolizumab) with or without TACE from four institutions between January 2019 and January 2022. Propensity score-based method was performed to minimize bias by confounding factors. Tumor response, progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were evaluated and compared between the two groups., Results: After inverse probability of treatment weighting, two balanced pseudopopulations were created: 106 patients in the TACE-TKI-ICI group and 109 patients in the TKI-ICI group. The objective response rate was higher in the TACE-TKI-ICI group (50.9% vs. 28.4%, P < 0.001). The median PFS and OS were significantly longer in the TACE-TKI-ICI group than in the TKI-ICI group (PFS: 9.1 vs. 5.0 months, P = 0.005; OS: 19.1 vs. 12.7 months, P = 0.002). In Cox regression, TACE-TKI-ICI treatment was an independent predictor of favorable OS. Treatment-related grade 3/4 AEs were comparable between the two groups (22.6% vs. 17.9%, P = 0.437)., Conclusion: TACE-TKI-ICI therapy contributed to better tumor control, PFS and OS than TKI-ICI therapy in unresectable HCC patients with first- or lower-order PVTT., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and the Cardiovascular and Interventional Radiological Society of Europe (CIRSE).)

Objectives: To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest., Design: Multicenter cohort, partly prospective and partly retrospective., Setting: Seven academic or teaching hospitals from the United States and Europe., Patients: Individuals 16 years old or older who were comatose after return of spontaneous circulation following a cardiac arrest who had continuous electroencephalography monitoring were included., Interventions: Not applicable., Measurements and Main Results: Clinical and electroencephalography data were harmonized and stored in a common Waveform Database-compatible format. Automated spike frequency, background continuity, and artifact detection on electroencephalography were calculated with 10-second resolution and summarized hourly. Neurologic outcome was determined at 3-6 months using the best Cerebral Performance Category (CPC) scale. This database includes clinical data and 56,676 hours (3.9 terabytes) of continuous electroencephalography data for 1,020 patients. Most patients died ( n = 603, 59%), 48 (5%) had severe neurologic disability (CPC 3 or 4), and 369 (36%) had good functional recovery (CPC 1-2). There is significant variability in mean electroencephalography recording duration depending on the neurologic outcome (range, 53-102 hr for CPC 1 and CPC 4, respectively). Epileptiform activity averaging 1 Hz or more in frequency for at least 1 hour was seen in 258 patients (25%) (19% for CPC 1-2 and 29% for CPC 3-5). Burst suppression was observed for at least 1 hour in 207 (56%) and 635 (97%) patients with CPC 1-2 and CPC 3-5, respectively., Conclusions: The I-CARE consortium electroencephalography database provides a comprehensive real-world clinical and electroencephalography dataset for neurophysiology research of comatose patients after cardiac arrest. This dataset covers the spectrum of abnormal electroencephalography patterns after cardiac arrest, including epileptiform patterns and those in the ictal-interictal continuum., Competing Interests: Dr. van Putten is the founder of Clinical Science Systems. Dr. Westover is a co-founder of Beacon Biosignals. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2023 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objective: Sex differences in emotions have been widely perceived via self-reports, peripheral physiological signals and brain imaging techniques. However, how sex differences are reflected in the EEG neural patterns of emotions remains unresolved. In this paper, we detect sex differences in emotional EEG patterns, investigate the consistency of such differences in various emotion datasets across cultures, and study how sex as a factor affects the performance of EEG-based emotion recognition models., Approach: We thoroughly assess sex differences in emotional EEG patterns on five public datasets, including SEED, SEED-IV, SEED-V, DEAP and DREAMER, systematically examine the sex-specific EEG patterns for happy, sad, fearful, disgusted and neutral emotions, and implement deep learning models for sex-specific emotion recognition., Main Results: (1) Sex differences exist in various emotion types and both Western and Eastern cultures; (2) The emotion patterns of females are more stable than those of males, and the patterns of happiness from females are in sharp contrast with the patterns of sadness, fear and disgust, while the energy levels are more balanced for males; (3) The key features for emotion recognition are mainly located at the frontal and temporal sites for females and distributed more evenly over the whole brain for males, and (4) The same-sex emotion recognition models outperform the corresponding cross-sex models., Significance: These findings extend efforts to characterize sex differences in emotional brain activation, provide new physiological evidence for sex-specific emotion processing, and reinforce the message that sex differences should be carefully considered in affective research and precision medicine., (© 2023 IOP Publishing Ltd.)

Biochar has been used to remediate contaminated-soil with heavy metals, however, less is known on how biochar interacts with planting density and nutrient fluctuation to affect the remediation. A pot experiment was conducted in the greenhouse to investigate the effects of biochar application (without vs. with 1% biochar, g/g substrate), nutrient fluctuation (constant vs. pulsed) and planting density (1-, 3- and 6-individuals per pot) on the growth, and cadmium (Cd) and nutrient uptake of Trifolium repens population. Our results found that the growth of T. repens population increased significantly with increasing planting density, and the increment decreased with increasing planting density. Both the Cd and nutrient uptake were higher at higher planting density (e.g., 3- and 6-individuals) than at lower planting density (e.g., 1-individual). Biochar application increased the biomass and shoot Cd uptake, but decreased the ratio of root to shoot and root Cd uptake of T. repens population, the effects of which were significantly influenced by planting density. Although nutrient fluctuation had no effect on the growth of T. repens population, but its interaction with planting density had significant effects on Cd uptake in tissues. Overall, the effects of biochar application and nutrient fluctuation on the growth and Cd uptake were both influenced by planting density in the present study. Our findings highlight that biochar application and constant nutrient supply at an appropriate planting density, such as planting density of 3-individuals per pot in the present study, could promote the growth, and Cd and nutrient uptake of T. repens population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zheng, Wang, Mo, Zeng, Chen and Sun.)

Background and Objectives: Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest., Methods: Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months., Results: One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery., Discussion: Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury., (© 2023 American Academy of Neurology.)

As a biodegradable and renewable material, polylactic acid is considered a major environmentally friendly alternative to petrochemical plastics. Microbial fermentation is the traditional method for lactic acid production, but it is still too expensive to compete with the petrochemical industry. Agro-industrial wastes are generated from the food and agricultural industries and agricultural practices. The utilization of agro-industrial wastes is an important way to reduce costs, save energy and achieve sustainable development. The present study aimed to develop a method for the valorization of Zizania latifolia waste and cane molasses as carbon sources for L-lactic acid fermentation using Rhizopus oryzae LA-UN-1. The results showed that xylose derived from the acid hydrolysis of Z. latifolia waste was beneficial for cell growth, while glucose from the acid hydrolysis of Z. latifolia waste and mixed sugars (glucose and fructose) from the acid hydrolysis of cane molasses were suitable for the accumulation of lactic acid. Thus, a three-stage carbon source utilization strategy was developed, which markedly improved lactic acid production and productivity, respectively reaching 129.47 g/L and 1.51 g/L·h after 86 h of fermentation. This work demonstrates that inexpensive Z. latifolia waste and cane molasses can be suitable carbon sources for lactic acid production, offering an efficient utilization strategy for agro-industrial wastes.

Depression is a mental disorder characterized by persistent sadness and loss of interest, which has become one of the leading causes of disability worldwide. There are currently no objective diagnostic standards for depression in clinical practice. Previous studies have shown that depression causes both brain abnormalities and behavioral disorders. In this study, both electroencephalography (EEG) and eye movement signals were used to objectively detect depression. By presenting 40 carefully selected oil paintings-20 positive and 20 negative-as stimuli, we were able to successfully evoke emotions in 48 depressed patients (DPs) and 40 healthy controls (HCs) from three centers. We then used Transformer, a deep learning model, to conduct emotion recognition and depression detection. The experimental results demonstrate that: a) Transformer achieves the best accuracies of 89.21% and 92.19% in emotion recognition and depression detection, respectively; b) The HC group has higher accuracies than the DP group in emotion recognition for both subject-dependent and subject-independent experiments; c) The neural pattern differences do exist between DPs and HCs, and we find the consistent asymmetry of the neural patterns in DPs; d) For depression detection, using single oil painting achieves the best accuracies, and using negative oil paintings has higher accuracies than using positive oil paintings. These findings suggest that EEG and eye movement signals induced by oil paintings can be used to objectively identify depression.

Depression is a common mental disorder that negatively affects physical health and personal, social and occupational functioning. Currently, accurate and objective diagnosis of depression remains challenging, and electroencephalography (EEG) provides promising clinical practice or home use due to considerable performance and low cost. This work investigates the capabilities of deep neural networks with EEG-based neural patterns from both resting states and cognitive tasks for depression detection. We collect EEG signals from 33 depressed patients and 40 healthy controls using wearable dry electrodes and build Attentive Simple Graph Convolutional network and Transformer neural network for objective depression detection. Four experiment stages, including two resting states and two cognitive tasks, are designed to characterize the alteration of relevant neural patterns in the depressed patients, in terms of decreased energy and impaired performance in sustained attention and response inhibition. The Transformer model achieves an AUC of 0.94 on the Continuous Performance Test-Identical Pairs version (sensitivity: 0.87, specificity: 0.91) and the Stroop Color Word Test (sensitivity: 0.93, specificity: 0.88), and an AUC of 0.89 on the two resting states (sensitivity: 0.85 and 0.87, specificity: 0.88 and 0.90, respectively), indicating the potential of EEG-based neural patterns in identifying depression. These findings provide new insights into the research of depression mechanisms and EEG-based depression biomarkers.

Depression severely limits daily functioning, diminishes quality of life and possibly leads to self-harm and suicide. Noninvasive electroencephalography (EEG) has been shown effective as biomarkers for objective depression diagnose and treatment response prediction, and dry EEG electrodes further extend its availability for clinical use. Even though many efforts have been made to identify depression biomarkers, searching reliable EEG biomarkers for depression detection remains challenging. This work presents a systematic investigation of capabilities of emotion EEG patterns for depression detection using a dry EEG electrode system. We design an emotion elicitation paradigm with happy, neutral and sad emotions and collect EEG signals during film watching from 33 depressed patients and 40 healthy controls. The mean activation levels at frontal and temporal sites in the alpha, beta and gamma bands of the depressed group are different to those of the healthy group, indicating the impacts of depressive symptoms on the emotion experiences. To leverage the topology information among EEG channels for emotion recognition and depression detection, an Attentive Simple Graph Convolutional network is built. The deep depression-health classifier achieves a sensitivity of 81.93% and a specificity of 91.69% on the happy emotions, suggesting the promising use of the emotion neural patterns for distinguishing the depressed patients from the healthy controls.

EEG-based emotion classification has long been a critical task in the field of affective brain-computer interface (aBCI). The majority of leading researches construct supervised learning models based on labeled datasets. Several datasets have been released, including different kinds of emotions while utilizing various forms of stimulus materials. However, they adopt discrete labeling methods, in which the EEG data collected during the same stimulus material are given a same label. These methods neglect the fact that emotion changes continuously, and mislabeled data possibly exist. The imprecision of discrete labels may hinder the progress of emotion classification in concerned works. Therefore, we develop an efficient system in this paper to support continuous labeling by giving each sample a unique label, and construct a continuously labeled EEG emotion dataset. Using our dataset with continuous labels, we demonstrate the superiority of continuous labeling in emotion classification through experiments on several classification models. We further utilize the continuous labels to identify the EEG features under induced and non-induced emotions in both our dataset and a public dataset. Our experimental results reveal the learnability and generality of the relation between the EEG features and their continuous labels.

Aurantiochytrium is a promising source of docosahexaenoic acid (DHA) and carotenoids, but their synthesis is influenced by environmental stress factors. In this study, the effect of different light intensities on the fermentation of DHA oil and carotenoids using Aurantiochytrium sp. TZ209 was investigated. The results showed that dark culture and low light intensity conditions did not affect the normal growth of cells, but were not conducive to the accumulation of carotenoids. High light intensity promoted the synthesis of DHA and carotenoids, but caused cell damage, resulting in a decrease of oil yield. To solve this issue, a light intensity gradient strategy was developed, which markedly improved the DHA and carotenoid content without reducing the oil yield. This strategy produced 30.16 g/L of microalgal oil with 15.11 g/L DHA, 221 µg/g astaxanthin, and 386 µg/g β-carotene. This work demonstrates that strain TZ209 is a promising DHA producer and provides an efficient strategy for the co-production of DHA oil together with carotenoids., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

There is clear evidence that high sodium intake is associated with many health issues including hypertension and cardiovascular diseases (CVDs). Several national and worldwide studies have estimated deaths from CVDs attributable to high sodium. But how to evaluate the impact of high sodium intake on diseases using regional routine monitoring and investigation data is necessary and important. Our study aimed to quantitatively evaluate the high sodium intake attributed to CVDs deaths based on the routine monitoring data from China National Nutrition and Health Survey (CNNHS) in Tianjin, China. The population attributable fractions (PAF) were calculated by comparing the observed systolic blood pressure (SBP) distribution with the theoretical minimum or counterfactual distribution by sex and age groups. The results showed that CVDs deaths due to elevated SBP were 22728 (95% uncertainty intervals: 22679-23050), accounting for 62.8% of total CVDs deaths. According to sodium intake recommended by World Health Organization (WHO), PAF of CVDs deaths attributable to high sodium diet in our study was 14.6% of total CVDs deaths, accounting for 5228 (95% UI: 5005-5998) cases. The dietary sodium intake of residents is nearly three times than sodium intake recommended by WHO. If sodium intake was reduced to reference level, the potential avoidable CVD deaths attributable to the SBP-raising effect were more than 5200 among adults 25 aged and over in Tianjin. This evaluation method can be extended to other cities., (© 2022 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC.)

Objective: Delayed cerebral ischemia (DCI) is a leading complication of aneurysmal subarachnoid hemorrhage (SAH) and electroencephalography (EEG) is increasingly used to evaluate DCI risk. Our goal is to develop an automated DCI prediction algorithm integrating multiple EEG features over time., Methods: We assess 113 moderate to severe grade SAH patients to develop a machine learning model that predicts DCI risk using multiple EEG features., Results: Multiple EEG features discriminate between DCI and non-DCI patients when aligned either to SAH time or to DCI onset. DCI and non-DCI patients have significant differences in alpha-delta ratio (0.08 vs 0.05, p < 0.05) and percent alpha variability (0.06 vs 0.04, p < 0.05), Shannon entropy (p < 0.05) and epileptiform discharge burden (205 vs 91 discharges per hour, p < 0.05) based on whole brain and vascular territory averaging. Our model improves predictions by emphasizing the most informative features at a given time with an area under the receiver-operator curve of 0.73, by day 5 after SAH and good calibration between 48-72 hours (calibration error 0.13)., Conclusions: Our proposed model obtains good performance in DCI prediction., Significance: We leverage machine learning to enable rapid, automated, multi-featured EEG assessment and has the potential to increase the utility of EEG for DCI prediction., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

It has been established that long-chain coding RNA (lncRNA) SLC25A25-AS1 is associated with cancer progression. However, the roles and mechanisms of SLC25A25-AS1 in prostate cancer (PC) have not been reported in the literature. The present study explored the relationship between SLC25A25-AS1 expression and PC progression via comprehensive analysis. The pan-cancer expression of SLC25A25-AS1 was identified using data from The Cancer Genome Atlas (TCGA) database and tissue specimens from our hospital. The expression levels of SLC25A25-AS1 in various subgroups based on the clinical features were identified. The prognostic value of SLC25A25-AS1 and SLC25A25-AS1 co-expressed lncRNAs in PC patients was assessed by survival analysis and ROC analysis, and prognosis-related risk models of SLC25A25-AS1 were constructed. The relationship between SLC25A25-AS1 and the PC immune microenvironment was investigated using correlation analysis. SLC25A25-AS1 expression in PC was significantly increased and correlated with the T stage, clinical stage, Gleason score (GS), and dismal prognosis. SLC25A25-AS1 overexpression exhibited good performance in evaluating the prognosis of PC patients. The area under the curves (AUCs) of the 1-, 3-, and 5-year overall survival (OS) for SLC25A25-AS1 was 1, 0.876, and 0.749. Moreover, the AUCs for the 1-, 3-, and 5-year progress free interval (PFI) for SLC25A25-AS1 were 0.731, 0.701, and 0.718. SLC25A25-AS1 overexpression correlated with the infiltration of CD8 T cells, interstitial dendritic cells (IDC), macrophages and other cells. AC020558.2, ZNF32-AS2, AP4B1-AS1, AL355488.1, AC109460.3, SNHG1, C3orf35, LMNTD2-AS1, and AL365330.1 were significantly associated with SLC25A25-AS1 expression, and short OS and PFI in PC patients. The risk models of the SLC25A25-AS1-related lncRNAs were associated with a dismal prognosis in PC. Overall, SLC25A25-AS1 expression was increased in PC and related to the prognosis and PC immune microenvironment. The risk model of SLC25A25-AS1 have huge prospect for application as prognostic tools in PC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao, Xiang, Chen, Zhang, Zheng, Ke, Shi and Yang.)

Background: There is no consensus on the best surgery option for thumb carpometacarpal osteoarthritis (CMC OA). The traditional method has the risk of large trauma, obvious metacarpal subsidence, and decreased stability. The aim of this study is to introduce a different technique to restore the function and stability of the first carpal metacarpal joint with minimal trauma, rapid pain relief, reduced complications, and the clinical outcomes in the long-term follow-up was evaluated and statistically analyzed., Methods: This was a retrospective study of 10 patients with a mean age of 51.8 years. The surgery consisted of removing partial trapezium through arthroscopy, reconstructing the stability with flexor carpi radialis suspension and tendon interposition. The subjective assessment included visual analog scale (VAS) of pain, quick disabilities of the arm, shoulder, and hand (Quick-DASH) score, and patient satisfaction. The range of motion, grip strength, pinch strength, and radiographic assessment, which can reflect stability of the thumb, were objectively evaluated and statistically analyzed., Results: Ten patients were monitored at a mean follow-up of 6.8 years. The mean grip strength improved significantly from 16.64 to 22.57 kg after surgery. Pinch strength improved significantly from 3.72 to 5.71 kg on average. The Kapandji score improved significantly from 5.7 to 8.6 on average. 80% (8/10) of the patients were satisfied with this surgery. On objective indicators, the VAS score decreased significantly from 6.4 to 1.3 on average. The mean Quick-DASH score improved significantly from 6.1 to 28.9. Postoperative x-ray showed slight subsidence and dislocation of the first metacarpal in two patients and did not affect the function by measurement., Conclusion: Arthroscopy-assisted partial trapezium resection combined with ligament reconstruction could be a workable and promising surgical technique in patients with thumb CMC OA. It can offer the advantages of minimizing surgical injury by preserving the first carpal metacarpal joint capsule to protect its stability, with a rapid pain relief, function improvement, and satisfactory results in patients' clinical measurements., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Zheng, Wu, Shen, Yin and Xu.)

Objective: To investigate whether epileptiform discharge burden can identify those at risk for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH)., Methods: Retrospective analysis of 113 moderate to severe grade SAH patients who had continuous EEG (cEEG) recordings during their hospitalization. We calculated the burden of epileptiform discharges (ED), measured as number of ED per hour., Results: We find that many SAH patients have an increase in ED burden during the first 3-10 days following rupture, the major risk period for DCI. However, those who develop DCI have a significantly higher hourly burden from days 3.5-6 after SAH vs. those who do not. ED burden is higher in DCI patients when assessed in relation to the onset of DCI (area under the receiver operator curve 0.72). Finally, specific trends of ED burden over time, assessed by group-based trajectory analysis, also help stratify DCI risk., Conclusions: These results suggest that ED burden is a useful parameter for identifying those at higher risk of developing DCI after SAH. The higher burden rate associated with DCI supports the theory of metabolic supply-demand mismatch which contributes to this complication., Significance: ED burden is a novel biomarker for predicting those at high risk of DCI., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

(-)-Anisomelic acid, isolated from Anisomeles indica (L.) Kuntze (Labiatae) leaves, is a macrocyclic cembranolide with a trans -fused α-methylene-γ-lactone motif. Anisomelic acid effectively inhibits SARS-CoV-2 replication and viral-induced cytopathic effects with an EC 50 of 1.1 and 4.3 μM, respectively. Challenge studies of SARS-CoV-2-infected K18-hACE2 mice showed that oral administration of anisomelic acid and subcutaneous dosing of remdesivir can both reduce the viral titers in the lung tissue at the same level. To facilitate drug discovery, we used a semisynthetic approach to shorten the project timelines. The enantioselective semisynthesis of anisomelic acid from the naturally enriched and commercially available starting material (+)-costunolide was achieved in five steps with a 27% overall yield. The developed chemistry provides opportunities for developing anisomelic-acid-based novel ligands for selectively targeting proteins involved in viral infections., (© The Author(s) 2022. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.)

Objective: The prevalence of seizures and other types of epileptiform brain activity in patients undergoing extracorporeal membrane oxygenation (ECMO) is unknown. We aimed to estimate the prevalence of seizures and ictal-interictal continuum patterns in patients undergoing electroencephalography (EEG) during ECMO., Methods: Retrospective review of a prospective ECMO registry from 2011-2018 in a university-affiliated academic hospital. Adult subjects who had decreased level of consciousness and underwent EEG monitoring for seizure screening were included. EEG classification followed the American Clinical Neurophysiology Society criteria. Poor neurological outcome was defined as a Cerebral Performance Category of 3-5 at hospital discharge., Results: Three hundred and ninety-five subjects had ECMO, and one hundred and thirteen (28.6%) had EEG monitoring. Ninety-two (23.3%) subjects had EEG performed during ECMO and were included in the study (average EEG duration 54 h). Veno-arterial ECMO was the most common cannulation strategy (83%) and 26 (28%) subjects had extracorporeal cardiopulmonary resuscitation. Fifty-eight subjects (63%) had epileptiform activity or ictal-interictal continuum patterns on EEG, including three (3%) subjects with nonconvulsive status epilepticus, 33 (36%) generalized periodic discharges, and 4 (5%) lateralized periodic discharges. Comparison between subjects with or without epileptiform activity showed comparable in-hospital mortality (57% vs. 47%, p = 0.38) and poor neurological outcome (and 56% and 36%, p = 0.23). Twenty-seven subjects (33%) had acute neuroimaging abnormalities (stroke N = 21)., Conclusions: Seizures and ictal-interictal continuum patterns are commonly observed in patients managed with ECMO. Further studies are needed to evaluate whether epileptiform activity is an actionable target for interventions., Significance: Epileptiform and ictal-interictal continuum abnormalities are frequently observed in patients supported with ECMO undergoing EEG monitoring., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Most previous affective studies use facial expression pictures, music or movie clips as emotional stimuli, which are either too simplified without contexts or too dynamic for emotion annotations. In this work, we evaluate the effectiveness of oil paintings as stimuli. We develop an emotion stimuli dataset with 114 oil paintings selected from subject ratings to evoke three emotional states (i.e., negative, neutral and positive), and acquire both EEG and eye tracking data from 20 subjects while watching the oil paintings. Furthermore, we propose a novel affective model for multimodal emotion recognition by 1) extracting informative features of EEG signals from both the time domain and the frequency domain, 2) exploring topological information embedded in EEG channels with graph neural networks (GNNs), and 3) combining EEG and eye tracking data with a deep autoencoder neural network. From the exper-iments, our model obtains an averaged classification accuracy of 94.72 % ± 1.47 %, which demonstrates the feasibility of using oil paintings as emotion elicitation material.

Background: This study aimed to identify the subgroups of individuals sharing similar blood pressure (BP) trajectories from childhood to youth and explore the associations of these trajectories with arterial stiffness in adulthood., Methods: A group-based trajectory model was used to identify BP trajectories among 2,082 individuals in the Hanzhong adolescent hypertension cohort by using BP values repeatedly measured at four visits from childhood (6-15 years) to youth (14-23 years). The brachial-ankle pulse wave velocity (baPWV) was examined 30 years after the baseline survey. Mixed linear regression models were used to examine the associations of these trajectories with adult baPWV., Results: Among the 2,082 individuals, three trajectory groups of systolic BP were identified as follows: the low-level group ( n = 889), medium-level group ( n = 1,021), and high-level group ( n = 172). The baPWV in adulthood was higher in medium-level and high-level groups compared with the low-level group (1271.4 ± 224.7 cm/s, 1366.1 ± 249.8 cm/s vs. 1190.1 ± 220.3 cm/s, all p < 0.001). After adjustment for potential confounding factors, the association between baPWV and systolic BP trajectories was statistically significant (adjusted β = 49.4 cm/s; p < 0.001 for the medium-level group and β = 107.6 cm/s; p < 0.001 for the high-level group compared with the low-level group). Similar results were obtained for the association of baPWV with the trajectories of diastolic BP and mean arterial pressure (MAP), except for pulse pressure., Conclusion: Our investigation demonstrates different BP trajectories from childhood to youth and shows the trajectories of systolic BP, diastolic BP, and MAP are significant predictors of arterial stiffness in adulthood., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chu, Liao, He, Ma, Zheng, Yan, Hu, Xu, Fan, Yang and Mu.)

Objective: Interictal epileptiform discharges on EEG are integral to diagnosing epilepsy. However, EEGs are interpreted by readers with and without specialty training, and there is no accepted method to assess skill in interpretation. We aimed to develop a test to quantify IED recognition skills., Methods: A total of 13,262 candidate IEDs were selected from EEGs and scored by eight fellowship-trained reviewers to establish a gold standard. An online test was developed to assess how well readers with different training levels could distinguish candidate waveforms. Sensitivity, false positive rate and calibration were calculated for each reader. A simple mathematical model was developed to estimate each reader's skill and threshold in identifying an IED, and to develop receiver operating characteristics curves for each reader. We investigated the number of IEDs needed to measure skill level with acceptable precision., Results: Twenty-nine raters completed the test; nine experts, seven experienced non-experts and thirteen novices. Median calibration errors for experts, experienced non-experts and novices were -0.056, 0.012, 0.046; median sensitivities were 0.800, 0.811, 0.715; and median false positive rates were 0.177, 0.272, 0.396, respectively. The number of test questions needed to measure those scores was 549. Our analysis identified that novices had a higher noise level (uncertainty) compared to experienced non-experts and experts. Using calculated noise and threshold levels, receiver operating curves were created, showing increasing median area under the curve from novices (0.735), to experienced non-experts (0.852) and experts (0.891)., Significance: Expert and non-expert readers can be distinguished based on ability to identify IEDs. This type of assessment could also be used to identify and correct differences in thresholds in identifying IEDs.

The phenomenon of increasing accidents caused by reduced vigilance does exist. In the future, the high accuracy of vigilance estimation will play a significant role in public transportation safety. We propose a multimodal regression network that consists of multichannel deep autoencoders with subnetwork neurons (MCDAE sn ). After we define two thresholds of "0.35" and "0.70" from the percentage of eye closure, the output values are in the continuous range of 0-0.35, 0.36-0.70, and 0.71-1 representing the awake state, the tired state, and the drowsy state, respectively. To verify the efficiency of our strategy, we first applied the proposed approach to a single modality. Then, for the multimodality, since the complementary information between forehead electrooculography and electroencephalography features, we found the performance of the proposed approach using features fusion significantly improved, demonstrating the effectiveness and efficiency of our method.

Objective: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information., Methods: We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation., Results: The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04)., Conclusions and Significance: These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.

Objective. Cultures have essential influences on emotions. However, most studies on cultural influences on emotions are in the areas of psychology and neuroscience, while the existing affective models are mostly built with data from the same culture. In this paper, we identify the similarities and differences among Chinese, German, and French individuals in emotion recognition with electroencephalogram (EEG) and eye movements from an affective computing perspective. Approach. Three experimental settings were designed: intraculture subject dependent, intraculture subject independent, and cross-culture subject independent. EEG and eye movements are acquired simultaneously from Chinese, German, and French subjects while watching positive, neutral, and negative movie clips. The affective models for Chinese, German, and French subjects are constructed by using machine learning algorithms. A systematic analysis is performed from four aspects: affective model performance, neural patterns, complementary information from different modalities, and cross-cultural emotion recognition. Main results. From emotion recognition accuracies, we find that EEG and eye movements can adapt to Chinese, German, and French cultural diversities and that a cultural in-group advantage phenomenon does exist in emotion recognition with EEG. From the topomaps of EEG, we find that the γ and β bands exhibit decreasing activities for Chinese, while for German and French, θ and α bands exhibit increasing activities. From confusion matrices and attentional weights, we find that EEG and eye movements have complementary characteristics. From a cross-cultural emotion recognition perspective, we observe that German and French people share more similarities in topographical patterns and attentional weight distributions than Chinese people while the data from Chinese are a good fit for test data but not suitable for training data for the other two cultures. Significance. Our experimental results provide concrete evidence of the in-group advantage phenomenon, cultural influences on emotion recognition, and different neural patterns among Chinese, German, and French individuals., (© 2022 IOP Publishing Ltd.)

Background: Diabetic retinopathy (DR) has become a leading cause of global blindness as a microvascular complication of diabetes. Regular screening of diabetic retinopathy is strongly recommended for people with diabetes so that timely treatment can be provided to reduce the incidence of visual impairment. However, DR screening is not well carried out due to lack of eye care facilities, especially in the rural areas of China. Artificial intelligence (AI) based DR screening has emerged as a novel strategy and show promising diagnostic performance in sensitivity and specificity, relieving the pressure of the shortage of facilities and ophthalmologists because of its quick and accurate diagnosis. In this study, we estimated the cost-effectiveness of AI screening for DR in rural China based on Markov model, providing evidence for extending use of AI screening for DR., Methods: We estimated the cost-effectiveness of AI screening and compared it with ophthalmologist screening in which fundus images are evaluated by ophthalmologists. We developed a Markov model-based hybrid decision tree to analyze the costs, effectiveness and incremental cost-effectiveness ratio (ICER) of AI screening strategies relative to no screening strategies and ophthalmologist screening strategies (dominated) over 35 years (mean life expectancy of diabetes patients in rural China). The analysis was conducted from the health system perspective (included direct medical costs) and societal perspective (included medical and nonmedical costs). Effectiveness was analyzed with quality-adjusted life years (QALYs). The robustness of results was estimated by performing one-way sensitivity analysis and probabilistic analysis., Results: From the health system perspective, AI screening and ophthalmologist screening had incremental costs of $180.19 and $215.05 but more quality-adjusted life years (QALYs) compared with no screening. AI screening had an ICER of $1,107.63. From the societal perspective which considers all direct and indirect costs, AI screening had an ICER of $10,347.12 compared with no screening, below the cost-effective threshold (1-3 times per capita GDP of Chinese in 2019)., Conclusions: Our analysis demonstrates that AI-based screening is more cost-effective compared with conventional ophthalmologist screening and holds great promise to be an alternative approach for DR screening in the rural area of China., (© 2022. The Author(s).)

A plug-and-play surface plasmon resonance (SPR) dual-parameter optical fiber biosensor is reported, in which Au film was firstly coated on the fiber surface for exciting SPR and the end half of the Au film was modified with Au nanoparticles to generate double SPR resonance valleys. For simultaneous detecting of glucose and cholesterol concentrations, modified P-mercaptophenylboronic acid (PMBA) and β-cyclodextrin (β-CD) were subsequently coated on the surface of sensor probe. Due to the cis-diol structure of glucose, it can interact with PMBA, leading to a red shift of one SPR resonant valley, whose maximum wavelength shift is 11.228 nm in the range of 0-1.7 mM glucose concentration. On the same time, the cholesterol molecules can realize the host-guest combination with β-CD, leading to a red shift of another SPR resonant valley, and the maximum wavelength shift is 18.893 nm in the cholesterol concentration range of 0-300 nM. The detection limits of the sensor to glucose and cholesterol are 0.00078 mM and 0.012 nM, respectively. The enhances the practical value of the dual-parameter sensor. Both theory and experiment results verify the feasibility of the "plug-and-play" sensor to measure the dual biomass of glucose and cholesterol with ultra-low detection limit and good selectivity. The proposed method provides a huge research value for the optical fiber sensor in multi-parameter measurement., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective. Previous studies on emotion recognition from electroencephalography (EEG) mainly rely on single-channel-based feature extraction methods, which ignore the functional connectivity between brain regions. Hence, in this paper, we propose a novel emotion-relevant critical subnetwork selection algorithm and investigate three EEG functional connectivity network features: strength, clustering coefficient, and eigenvector centrality. Approach. After constructing the brain networks by the correlations between pairs of EEG signals, we calculated critical subnetworks through the average of brain network matrices with the same emotion label to eliminate the weak associations. Then, three network features were conveyed to a multimodal emotion recognition model using deep canonical correlation analysis along with eye movement features. The discrimination ability of the EEG connectivity features in emotion recognition is evaluated on three public datasets: SEED, SEED-V, and DEAP. Main results . The experimental results reveal that the strength feature outperforms the state-of-the-art features based on single-channel analysis. The classification accuracies of multimodal emotion recognition are95.08±6.42%on the SEED dataset,84.51±5.11%on the SEED-V dataset, and85.34±2.90%and86.61±3.76%for arousal and valence on the DEAP dataset, respectively, which all achieved the best performance. In addition, the brain networks constructed with 18 channels achieve comparable performance with that of the 62-channel network and enable easier setups in real scenarios. Significance. The EEG functional connectivity networks combined with emotion-relevant critical subnetworks selection algorithm we proposed is a successful exploration to excavate the information between channels., (© 2022 IOP Publishing Ltd.)

Background: Dyslipidemia is a disorder of lipid metabolism and associated with insulin resistance. The relationship between longitudinal body mass index (BMI) changes from childhood to adulthood and long-term dyslipidemia was explored in this study., Methods: We assessed the longitudinal relationship between BMI changes since childhood and dyslipidemia among 1738 participants in rural areas of Hanzhong City, Shaanxi. All participants were initially examined between the ages of 6 and 15 years in 1987 and were reexamined in 1995, 2013 and 2017; the total follow-up duration was 30 years. Anthropometric measurements and blood biochemistry indexes were measured., Results: We found that gradual progression of normal weight to overweight (OR = 1.65; 95% CI = 1.27, 2.15) or persistent overweight (OR = 2.45; 95% CI = 1.52, 3.96) from childhood to adulthood was associated with an increased risk of dyslipidemia in adulthood. And these risks were largely disappeared if the overweight or obesity during childhood was resolved by adulthood. The higher the BMI in adulthood and the younger the age at which overweight begins, the higher the risk of dyslipidemia., Conclusions: Early weight loss and any degree of weight loss from childhood to adulthood can help improve dyslipidemia in adulthood. We further emphasize the importance of weight management and control in public health primary prevention., (© The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Evidence shows that simplified SOFA scoring system has better clinical practice., Objective: This study aimed to validate and compare the scores acquired with simplified organ dysfunction criteria optimized for electronic health records (eSOFA), and simplified and accurate sequential organ failure assessment (sa-SOFA) for their accuracies in predicting the prognosis of septic patients., Methods: This retrospective observational study was conducted at three major academic hospitals. Clinical data from 574 patients diagnosed with sepsis following the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)were retrospectively retrieved and analysed. Scores from the quick sequential organ failure assessment (qSOFA) and sequential organ failure assessment (SOFA) were used as reference scores. The area under the receiver operating characteristic curve (AUROC) was used to assess the performance of eSOFA and sa-SOFA scores in predicting in-hospital mortality., Results: AUROC analysis demonstrated the predictability of the four scoring systems for sepsis surveillance, listed in descending order as: sa-SOFA, 0.790 (95% confidence interval [CI]: 0.754-0.822); SOFA, 0.774 (95% CI: 0.738-0.808); eSOFA, 0.729 (95% CI: 0.691-0.765); and qSOFA, 0.618 (95% CI: 0.577-0.658). Moreover, sa-SOFA and SOFA scores (Z = 1.950, P = .051) did not significantly differ from each other in discriminatory power, but the sa-SOFA score had a higher power than eSOFA score (P values < .001)., Conclusion: sa-SOFA appeared to have performed better than eSOFA score for predicting in-hospital mortality in patients' sepsis. Further large prospective studies are needed to externally validate., (© 2021 John Wiley & Sons Ltd.)

Objective: Electroencephalography (EEG) is an important tool for neurological outcome prediction after cardiac arrest. However, the complexity of continuous EEG data limits timely and accurate interpretation by clinicians. We develop a deep neural network (DNN) model to leverage complex EEG trends for early and accurate assessment of cardiac arrest coma recovery likelihood., Methods: We developed a multiscale DNN combining convolutional neural networks (CNN) and recurrent neural networks (long short-term memory [LSTM]) using EEG and demographic information (age, gender, shockable rhythm) from a multicenter cohort of 1,038 cardiac arrest patients. The CNN learns EEG feature representations while the multiscale LSTM captures short-term and long-term EEG dynamics on multiple time scales. Poor outcome is defined as a Cerebral Performance Category (CPC) score of 3-5 and good outcome as CPC score 1-2 at 3-6 months after cardiac arrest. Performance is evaluated using area under the receiver operating characteristic curve (AUC) and calibration error., Results: Model performance increased with EEG duration, with AUC increasing from 0.83 (95% Confidence Interval [CI] 0.79-0.87 at 12h to 0.91 (95%CI 0.88-0.93) at 66h. Sensitivity of good and poor outcome prediction was 77% and 75% at a specificity of 90%, respectively. Sensitivity of poor outcome was 50% at a specificity of 99%. Predicted probability was well matched to the observation frequency of poor outcomes, with a calibration error of 0.11 [0.09-0.14]., Conclusions: These results demonstrate that incorporating EEG evolution over time improves the accuracy of neurologic outcome prediction for patients with coma after cardiac arrest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: The purpose of this study was to retrospectively analyze clinical characteristics and prognostic risk factors of urosepsis patients admitted to two intensive care units in Shanghai, China., Methods: Clinical data from patients diagnosed with urosepsis were retrospectively retrieved and analyzed from ICU in two regional medical centers from January 2015 to December 2019., Results: Two hundred two patients were included in the subsequent analysis eventually, with an average age of 72.02 ± 9.66 years, 79.21% of the patients were female and the mortality rate of 15.84%.The proportion of patients with chronic underlying diseases such as diabetes and hypertension was relatively high (56.44, 49.50%, respectively), and the incidence of shock was also high (41.58%) correspondingly. The most common pathogen isolated was Escherichia coli (79.20%), of which the extended-spectrumβ-lactamases (ESBLs)(+) accounted for 42.57%. In multivariate analysis, the strongest predictors for death were mechanical ventilation (OR 7.260, 95% CI 2.200-23.963; P = 0.001),chronic kidney disease (CKD) (OR 5.140, 95% CI 1.596-16.550; P = 0.006), APACHE II score (OR 1.321, 95% CI 1.184-1.473; P < 0.001) and lactate (OR 1.258, 95% CI 1.037-1.527; P = 0.020). Both APACHE II score and lactate had the ideal predictive value, with the area under the ROC curve (AUC) of 0.858 and 0.805 respectively., Conclusion: The patients with urosepsis were characterized by a higher proportion of female, older age, more percentage of comorbidities in this region, and patients with ESBLs (+) Escherichia coli infection were more prone to shock. Mechanical ventilation, comorbidity with CKD, APACHE II score and lactate were independent risk factors for death in urosepsis patient, but lactate level and APACHE II score had better predictive value for prognosis., (© 2021. The Author(s).)

Purpose: HIV infection is associated with a variety of ocular surface diseases. Understanding the difference of the ocular microbiota between HIV-infected and healthy individuals as well as the influence of antiretroviral therapy will help to investigate the pathogenesis of these conditions., Methods: A cross-sectional study was conducted on subjects including HIV-negative individuals, untreated HIV-infected individuals, and HIV-infected individuals with antiretroviral therapy. Conjunctival microbiota was assessed by bacterial 16S rRNA sequencing of the samples obtained from the conjunctival swab., Results: The microbial richness in ocular surface was similar in HIV-negative, untreated HIV-positive, and highly active antiretroviral therapy (HAART) subjects. The bacterial compositions were similar in the two HIV infection groups but were significantly different from the HIV-negative group. HAART changed the beta diversity of bacterial community as determined by Shannon index. CD4+ T cell count had no significant influence on the diversity of ocular microbiota in HIV-infected individuals., Conclusions: The data revealed the compositional and structural difference in conjunctival microbial community in subjects with and without HIV infection, indicating that HIV infection or its treatment, may contribute to ocular surface dysbiosis.

Background: For women undergoing in vitro fertilization (IVF), the clinical benefit of embryo transfer at the blastocyst stage (Day 5) versus cleavage stage (Day 3) remains controversial. The purpose of this study is to compare the implantation rate, clinical pregnancy rate and odds of live birth of Day 3 and Day 5 embryo transfer, and more importantly, to address the issue that patients were chosen to receive either transfer protocol due to their underlying clinical characteristics, i.e., confounding by indication., Methods: We conducted a retrospective cohort study of 9,090 IVF cycles collected by Lee Women's Hospital in Taichung, Taiwan from 1998 to 2014. We utilized the method of propensity score matching to mimic a randomized controlled trial (RCT) where each patient with Day 5 transfer was matched by another patient with Day 3 transfer with respect to other clinical characteristics. Implantation rate, clinical pregnancy rate, and odds of live birth were compared for women underwent Day 5 transfer and Day 3 transfer to estimate the causal effects. We further investigated the causal effects in subgroups by stratifying age and anti-Mullerian hormone (AMH)., Results: Our analyses uncovered an evidence of a significant difference in implantation rate (p=0.04) favoring Day 5 transfer, and showed that Day 3 and Day 5 transfers made no difference in both odds of live birth (p=0.27) and clinical pregnancy rate (p=0.11). With the increase of gestational age, the trend toward non-significance of embryo transfer day in our result appeared to be consistent for subgroups stratified by age and AMH, while all analyses stratified by age and AMH were not statistically significant., Conclusions: We conclude that for women without strong indications for Day 3 or Day 5 transfer, there is a small significant difference in implantation rate in favor of Day 5 transfer. However, the two protocols have indistinguishable outcomes on odds of live birth and clinical pregnancy rate., (© 2021. The Author(s).)

According to the different organizational forms of logistics in manufacturing, the types of linkage development between the logistics and manufacturing industries include two different logistics service modes: logistics outsourcing and logistics self-operation. This study considers two manufacturing clusters for comparison: the northeast region in China, mainly state-owned and self-operated, and the Yangtze River Delta region in China, mainly focusing on logistics outsourcing services. First, we construct a parallel network system considering heterogeneity and an unexpected super-efficiency slacks-based measure: the Grey Relational Analysis model. Second, considering the unexpected output, this study evaluates the environmental performance of the linkage development of the logistics and manufacturing industries and explains the types of linkage development between them. Finally, the spatial and temporal characteristics of linkage efficiency under different linkage modes are studied using an exploratory spatial data analysis method. The research results show that the efficiency of the two-industry linkage in different linkage types that consider the unexpected output presents different development characteristics. Regarding time characteristics and trends, we compare the development efficiency of the two-industry linkage at the overall level of the northeast and the Yangtze River Delta regions from 2009 to 2016. The Yangtze River Delta region showed a higher state of linkage while the northeast region showed a medium linkage state. Regarding spatial pattern evolution, the effect of the technical efficiency of the linkage between the two industries in the three northeastern provinces showed continuous evolution from the medium linkage stage to the weak linkage stage, and the Yangtze River Delta showed continuous evolution from the medium linkage to the strong linkage stage. Implications : Due to data availability, references to the relevant achievements of the research on the linkage between the manufacturing and logistics industries, the transportation industry, warehousing, and postal and telecommunications industry data are generally used as logistics industry data. Manufacturing data are replaced by industrial data. The manufacturing industry is the core industry of industrial systems. Its output value accounts for more than 90% of the industrial output. Thus, it can reflect the development trend of the manufacturing industry in general.

Purpose: Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video., Methods: By randomly dividing the dataset of time-lapse videos with known outcome of preimplantation genetic testing for aneuploidy (PGT-A), a deep learning model on raw videos was trained by the 80% dataset, and used to test the remaining 20%, by feeding time-lapse videos as input and the PGT-A prediction as output. The performance was measured by an average area under the curve (AUC) of the receiver operating characteristic curve., Result(s): With 690 sets of time-lapse video image, combined with PGT-A results, our deep learning model has achieved an AUC of 0.74 from the test dataset (138 videos), in discriminating between aneuploid embryos (group 1) and others (group 2, including euploid and mosaic embryos)., Conclusion: Our model demonstrated a proof of concept and potential in recognizing the ploidy status of tested embryos. A larger scale and further optimization on the exclusion criteria would be included in our future investigation, as well as prospective approach., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To present a relatively uncommon case with a secondary iris cyst in the anterior chamber and its successful management with an anterior chamber mass excision surgery., Case Report: A 46-year-old Chinese woman presented with a dark shadow in her left eye for 6 months without any other discomfort. She had a history of blunt ocular trauma by a badminton strike 3 years ago. Slit-lamp examination showed a small, nearly circular, sharply demarcated, and movable mass in the anterior chamber OS, which could change its position with head tilt. The anterior segment optical coherence tomography revealed a well-circumscribed cystic lesion in the anterior chamber with higher reflective outer layer and lower internal reflectivity. An anterior chamber mass removal surgery was performed without recurrence up to 1 year., Conclusion: Secondary free-floating iris cyst following a blunt trauma is rarely reported. It is relatively stable and nonprogressive so it may remain asymptomatic for a long time. Appropriate imaging techniques are necessary for facilitating diagnosis and therapy. Therapeutic management should be considered if visual symptoms arise, especially when complications occur.

Objective: The relationship between child-to-adult blood pressure (BP) trajectories and metabolic syndrome (MetS) is unknown. We aimed to determine the predictive role of BP trajectories for incident MetS and its components., Methods: The prospective Hanzhong Adolescent Hypertension study began in 1987 and included 2692 participants free of MetS at baseline with at least 3 BP measurements available from 1987 to 2017., Results: The systolic BP (SBP) trajectory patterns were grouped as normal (class 1, 18.7%), high normal (class 2, 60.3%), prehypertensive (class 3, 13.1%), stage 1 hypertensive (class 4, 5.7%), and stage 2 hypertensive (class 5, 2.2%). Compared with those in the normal group, individuals in classes 2 to 5 had significantly higher risks of MetS (all Ps < .05), and those with hypertension had more than an 8-fold higher risk of MetS (both P < .05). The fully adjusted risk ratios (RRs) of central obesity increased significantly in a stepwise manner as the SBP trajectory group increased from class 1 to class 5 (P < .05). Compared with those with a normal SBP trajectory, participants in the prehypertensive group and stage 1 and stage 2 hypertensive groups had significantly higher RRs for high-risk triglycerides after full adjustment (RR = 1.89 [1.22-2.94]; RR = 3.61 [2.16-6.02]; and RR = 3.22 [1.52-6.84], respectively)., Conclusion: Our study suggests that BP trajectories are predictive of incident MetS outcomes. Early detection of hypertension or modest elevations in BP is crucial. The stage of hypertension based on SBP level showed a greater association with central obesity., (Copyright © 2020 AACE. Published by Elsevier Inc. All rights reserved.)

Background: Electrocardiographic left ventricular hypertrophy (ECG-LVH) is a common manifestation of preclinical cardiovascular disease. The present study aimed to investigate risk factors for ECG-LVH and its prevalence in a cohort of young Chinese individuals., Methods: (1) A total of 1515 participants aged 36-45 years old from our previously established cohort who were followed up in 2017 were included. Cross-sectional analysis was used to examine risk factors for ECG-LVH and its prevalence. (2) A total of 235 participants were recruited from the same cohort in 2013 and were followed up in 2017. Longitudinal analysis was used to determine the predictors of LVH occurrence over the 4-year period. We used multivariable logistic regression models to calculate OR and 95% CIs and to analyze risk factors for ECG-LVH., Results: In the cross-sectional analysis, the prevalence of LVH diagnosed by the Cornell voltage-duration product in the overall population and the hypertensive population was 4.6% and 8.8%, respectively. The logistic regression results shown that female sex [2.611 (1.591-4.583)], hypertension [2.638 (1.449-4.803)], systolic blood pressure (SBP) [1.021 (1.007-1.035)], serum uric acid (SUA) [1.004 (1.001-1.006)] and carotid intima-media thickness (CIMT) [67.670 (13.352-342.976)] were significantly associated with the risk of LVH (all P < 0.05). In the longitudinal analysis, fasting glucose [1.377 (1.087-1.754)], SBP [1.046 (1.013-1.080)] and female sex [1.242 (1.069-1.853)] were independent predictors for the occurrence of LVH in the fourth year of follow-up., Conclusions: Our study suggested that female sex, hypertension, SBP, SUA and CIMT were significantly associated with the risk of LVH in young people. In addition, fasting glucose, SBP and female sex are independent predictors of the occurrence of LVH in a young Chinese general population.

Background and Aims: Data are limited regarding the association between long-term burden of higher body mass index (BMI) from childhood and cardiometabolic biomarkers., Methods and Results: A total of 1553 individuals aged 6-15 years, who were examined 4 or more times for BMI since childhood and followed for 30 years were included in our analysis. Total area under the curve (AUCt) and incremental AUC (AUCi) were calculated as the long-term burden and trends of BMI. Cardiometabolic biomarkers including serum uric acid (SUA), fasting blood-glucose (FBG), and triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) were obtained from venous blood samples. The results showed a positive association of BMI AUCt and AUCi with cardiometabolic biomarkers. After adjusting for demographic variables, the AUCt and AUCi of BMI were significantly associated with a higher level of SUA (β = 3.71; 2.87), FBG (β = 0.09; 0.09), and TG/HDL-C (β = 0.14; 0.11). We performed further studies after dividing subjects into four groups according to AUCt and AUCi of BMI by quartiles. Compared with the lowest quartile group, the highest quartile group had significantly increased risk ratios of hyperuricemia (RR = 2.01; 1.74), type 2 diabetes mellitus (RR = 8.18; 3.96), and high-risk TG/HDL-C (RR = 4.05; 3.26)., Conclusion: Our study identifies all subjects' BMI growth curve from childhood and indicates that the long-term burden of higher BMI significantly increases the cardiometabolic risk, and the impact of excessive body weight on cardiometabolic health originates in early life. We emphasize the importance of weight control from childhood for cardiometabolic health., Competing Interests: Declaration of competing interest The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Background and Aims: Obesity and hypertension play important roles in the development of arterial stiffness. We aimed to examine the sex differences in the impact of the cumulative long-term burden and trends of body mass index (BMI) and blood pressure (BP) since childhood on adult arterial stiffness (AS)., Methods: This longitudinal study consisted of 1553 individuals aged 6-15 years, who were examined 4 or more times for BMI and BP since childhood, with a follow-up period of 30 years. The area under the curve (AUC) was calculated as a measure of the long-term burden (total AUC) and trends (incremental AUC) of BMI and BP from childhood to adulthood. Brachial-ankle pulse wave velocity (baPWV) was recorded by a non-invasive automatic waveform analyser in adulthood., Results: The total AUC and incremental AUC of systolic BP and diastolic BP were significantly associated with higher baPWV in adults, both male and female, after adjustment for other covariates. There was no association between the total AUC of BMI and arterial stiffness regardless of sex. However, there were sex differences in the association between the incremental AUC of BMI and arterial stiffness (p = 0.019 for interaction). The incremental AUC of BMI indicated an increased risk of arterial stiffening during adulthood in males, but this association was not found in females., Conclusions: These results emphasize the importance of developing prevention and intervention strategies for hypertension and obese men (especially those who are gradually gaining weight) to reduce the risk of arterial stiffening and cardiovascular disease in adulthood., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

In the current study, we aimed to identify potential biomarkers for salt sensitivity of blood pressure (SSBP), which may provide a novel insight into the pathogenic mechanisms of salt-sensitive hypertension. Firstly, we conducted weighted gene coexpression network analysis (WGCNA) and selected a gene module and 60 hub genes significantly correlated to SSBP. Then, GO function and KEGG signaling pathway enrichment analysis and protein-protein interaction (PPI) network analysis were performed. Furthermore, we identified a five-gene signature with high connectivity degree in the PPI network and high AUC of ROC curves, which may have high diagnosis value for SSBP. Moreover, through combining two gene screening methods, we identified 23 differentially expressed circRNAs and selected the top 5% circRNAs (1 circRNA) with the highest connectivity degree in the coexpression network as hub circRNA highly associated with SSBP. Finally, we carried out RT-qPCR to validate the expression of five hub genes, and our results showed that the expression of HECTD1 ( P = 0.017), SRSF5 ( P = 0.003), SRSF1 ( P = 0.006), HERC2 ( P = 0.004), and TNPO1 ( P = 0.002) was significantly upregulated in the renal tissue in salt-sensitive rats compared to salt-resistant rats, indicating that these five hub genes can serve as potential biomarkers for SSBP., (Copyright © 2020 Chen, Liu, Liao, Chu, Zheng, Wang, Hu, Ma, Wang, Yan, Yuan and Mu.)

Hydroxychloroquine (HCQ) is frequently used medications for many auto-immunity diseases. However, HCQ induced retinal toxicity, which might result in irreversible retinopathy, is one of the most important complications of HCQ. However, the molecular mechanism underlying the HCQ retinal toxicity is still not well known. Retinal pigment epithelium, in which HCQ is highly enriched due to the tissue-specific affinity of HCQ, is considered to play important role in HCQ retinopathy. Herein, we used a metabolomics approach based on liquid chromatography-mass spectrometry to investigate the metabolic changes in retinal pigment epithelial cells (ARPE-19) with HCQ exposure at 6 h and 24 h. ARPE-19 cells were treated with HCQ at sub-lethal concentration 20 (IC 20), which was determined with MTT assay. Untargeted metabolic profiling revealed 9 and 15 metabolites that were significantly different between control group and HCQ exposure group at 6 h and 24 h, respectively. Enrichment and pathway analysis highlighted ascorbate and aldarate metabolism, d-Glutamine and d-glutamate metabolism and C5-Branched dibasic acid metabolism were disturbed after HCQ exposure. These findings increased our knowledge about the metabolic perturbation induced by HCQ exposure and indicated that metabolic profiling in the ARPE-19 cells might be helpful in understanding the mechanism of HCQ retinal toxicity and exploring potential biomarker., (Copyright © 2020 Elsevier B.V. All rights reserved.)

There is currently a lack of strong evidence linking childhood elevated blood pressure to long-term cardiovascular risk in adulthood. Repeated observations of abnormal blood pressure in childhood may enhance the prediction of cardiovascular risk in adulthood compared with a single observation. The study included 1738 individuals in rural areas of Hanzhong City, Shaanxi, who had been followed for 30 years since baseline (1987, at which time participants were aged 6-15 years). According to four independent measurements of blood pressure in 1987, 1989, 1992, and 1995, childhood elevated blood pressure was defined as 2 in-person examinations with blood pressure values above the 90th percentile. Arterial stiffness and left ventricular hypertrophy in adulthood were assessed by brachial-ankle pulse wave velocity and the Cornell product index, respectively. Childhood elevated blood pressure was associated with an increased risk of adult hypertension (OR, 2.01; 95% CI, 1.53-2.65), arterial stiffness (OR, 1.69; 95% CI, 1.32-2.16) and left ventricular hypertrophy (OR, 1.86; 95% CI, 1.13-3.05) (all P < 0.05). Cardiovascular risk in adults increased with increasing childhood blood pressure levels. In addition, two abnormal childhood blood pressure observations predicted an increased likelihood of hypertension in adulthood (0.77 for 2 versus 0.70 for 1 observation, P < 0.001). Our study provides strong evidence that elevated blood pressure in childhood predicts cardiovascular risk in adults. The prediction was enhanced by two observations of abnormal blood pressure in childhood compared with a single measurement. We emphasize the importance of childhood blood pressure monitoring and control in the prevention of cardiovascular diseases.

Diabetic cataract is one of the most important causes of blindness worldwide. Cyanidin-3- O -glucoside (C3G) is found to exert beneficial effects on many diabetic complications. However, its effect on diabetic cataract is not well known. Herein, we investigated the effect of C3G on high glucose-induced lens epithelial cell (SRA01/04) apoptosis and cataract formation as well as the involved mechanisms. We found C3G (20 μM) could preserve cell viability in SRA01/04 cells exposed to high glucose (100 μM). Meanwhile, C3G inhibited SRA01/04 cell apoptosis and regulated the Bcl-2/Bax ratio. Additionally, C3G suppressed NF-κB activation and subsequent cyclooxygenases-2 (Cox-2) expression, which are associated with the protection against apoptosis. Moreover, C3G attenuated lens opacity and protein aggregation in lens culture exposed to high glucose. In conclusion, C3G protected against high glucose-induced SRA01/04 cell apoptosis and cataract formation, which indicated the potential protection of anthocyanins on diabetic cataract.

Background: Metabolically healthy obesity (MHO) has been reported to be associated with the development of vascular damage by the carotid intima-media thickness, but the relationship between metabolic health and obesity phenotypes and arterial stiffness is still unknown. Our hypothesized that different metabolic health and obesity phenotypes might be associated with the development of arterial stiffness, and that subjects in MHO phenotype might not have increased risks of arterial stiffness compared with those in metabolically healthy nonobesity phenotype (MHNO), while metabolic unhealthy individuals might have increased risks of arterial stiffness., Methods: A prospective cohort of 2076 participants (aged 36-48 years) who were enrolled in the Hanzhong Adolescent Hypertension Cohort Study in 2017 was analyzed in a cross-sectional analysis. A subgroup of 202 participants from 2005 to 2017 was selected by an isometric sampling method and was included in the final longitudinal analysis., Results: We identified four metabolic health and obesity phenotypes for both the cross-sectional and longitudinal analyses as follows: MHNO, metabolically unhealthy nonobesity (MUNO), MHO, and metabolically unhealthy obesity (MUO). In the cross-sectional analysis, individuals with the MHO phenotype had the lowest brachial-ankle pulse wave velocity (baPWV) levels of the four phenotypes ( P  < 0.001), and participants with the MHO phenotype had a similar risk of arterial stiffness after fully adjustment [odds ratio (OR) = 0.99 (0.61-1.60)] as the MUNO subjects. Subjects with metabolically unhealthy status had a significantly higher risk of arterial stiffness than the MHNO individuals, particularly females ( P  < 0.005). In the longitudinal analysis, subjects with the MUNO and MUO phenotypes had a significantly higher risk of arterial stiffness than the MHNO individuals after adjustment for age and sex [OR = 5.21 (2.26-12.02), OR = 3.32 (1.18-9.32), respectively]., Conclusions: The MHO phenotype did not significantly increase the progression of arterial stiffness. Metabolically unhealthy individuals (MUNO, MUO), regardless of obesity status, showed a worse effect for the development of arterial stiffness, particularly females., Trial Registration: NCT02734472. Registered 12 April 2016 - Retrospectively registered, http:www.clinicaltrials.gov., Competing Interests: Competing interestsAll the authors declare that there were no conflicts of interest in this study., (© The Author(s) 2020.)

Abies georgei Orr var. smithii is an evergreen coniferous species of Pinaceae, and is endemic to the Qinghai-Tibet Plateau of China. Considering its vital ecological functions in this unique area, the complete chloroplast (cp) genome was constructed in this study to provide genetic information for its further study of conservation and evolution. The complete cp genome is 121,213 bp in length with GC content of 38.3%, and contains a tetrad structure, including a large single copy region of 76,278 bp, a small single copy of 42,575 bp, and two very short repeats of 1,180 bp for each. Besides, it contains 113 genes in total, including 74 CDSs, 35 tRNAs, and four rRNAs. This genome has been deposited in Genbank under accession number of MT527722., Competing Interests: No potential conflict of interest was reported by the author(s)., (© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)