Waveguide-integrated twisted bilayer graphene photodetectors.

Graphene photodetectors have exhibited high bandwidth and capability of being integrated with silicon photonics (SiPh), holding promise for future optical communication devices. However, they usually suffer from a low photoresponsivity due to weak optical absorption. In this work, we have implemented SiPh-integrated twisted bilayer graphene (tBLG) detectors and reported a responsivity of 0.65 A W-1 for telecom wavelength 1,550 nm. The high responsivity enables a 3-dB bandwidth of >65 GHz and a high data stream rate of 50 Gbit s-1. Such high responsivity is attributed to the enhanced optical absorption, which is facilitated by van Hove singularities in the band structure of high-mobility tBLG with 4.1o twist angle. The uniform performance of the fabricated photodetector arrays demonstrates a fascinating prospect of large-area tBLG as a material candidate for heterogeneous integration with SiPh.

[Brain magnetic resonance image registration based on parallel lightweight convolution and multi-scale fusion].

Medical image registration plays an important role in medical diagnosis and treatment planning. However, the current registration methods based on deep learning still face some challenges, such as insufficient ability to extract global information, large number of network model parameters, slow reasoning speed and so on. Therefore, this paper proposed a new model LCU-Net, which used parallel lightweight convolution to improve the ability of global information extraction. The problem of large number of network parameters and slow inference speed was solved by multi-scale fusion. The experimental results showed that the Dice coefficient of LCU-Net reached 0.823, the Hausdorff distance was 1.258, and the number of network parameters was reduced by about one quarter compared with that before multi-scale fusion. The proposed algorithm shows remarkable advantages in medical image registration tasks, and it not only surpasses the existing comparison algorithms in performance, but also has excellent generalization performance and wide application prospects.

Energy-Efficient Electrosynthesis of High Value-Added Active Chlorine Coupled with H2 Generation from Direct Seawater Electrolysis through Decoupling Electrolytes.

Direct saline (seawater) electrolysis is a well-recognized system to generate active chlorine species for the chloride-mediated electrosynthesis, environmental remediation and sterilization over the past few decades. However, the large energy consumption originated from the high cell voltage of traditional direct saline electrolysis system, greatly restricts its practical application. Here, we report an acid-saline hybrid electrolysis system for energy-saving co-electrosynthesis of active chlorine and H2. We demonstrate that this system just requires a low cell voltage of 1.59 V to attain 10 mA cm-2 with a large energy consumption decrease of 27.7 % compared to direct saline electrolysis system (2.20 V). We further demonstrate that such acid-saline hybrid electrolysis system could be extended to realize energy-saving and sustainable seawater electrolysis. The acidified seawater in this system can absolutely avoid the formation of Ca/Mg-based sediments that always form in the seawater electrolysis system. We also prove that this system in the half-flow mode can realize real-time preparation of active chlorine used for sterilization and pea sprout production.

Studies on immunotoxicity induced by emamectin benzoate in zebrafish embryos based on metabolomics.

Emamectin benzoate (EMB) is an insecticide for the control of agricultural lepidoptera pests, and also an anti-parasiticide for the control of exoparasites in aquaculture industry. Increased studies suggest that EMB could cause toxicity to non-targeted organisms, but its immunotoxicity to human remains unclear. In this study, zebrafish were used to investigate the immunotoxic effects induced by environmentally relevant doses of EMB. We observed that EMB exposure led to embryo mortality and delayed hatching, as well as increased malformations. Meanwhile, zebrafish exposed to EMB exhibited a significant decrease in the number of neutrophils and macrophages. In addition, untargeted metabolomics approach was developed to elucidate the mechanism of EMB-induced immunotoxicity. We found that a total of 10 shared biomarkers were identified in response to EMB exposure. Furthermore, pathway analysis identified glycerophospholipid metabolism was the most relevant pathway. Within this pathway, it was observed abnormal increases in glycerol 3-phosphate content, which could be attributed to the increased expression of GK5 and decreased expression of GPAT3. Our study provided novel and robust perspectives, which showed that EMB exposure to zebrafish embryos could cause metabolic disturbances that adversely affected development and immune system.

Federated Domain Adaptation via Transformer for Multi-Site Alzheimer's Disease Diagnosis.

In multi-site studies of Alzheimer's disease (AD), the difference of data in multi-site datasets leads to the degraded performance of models in the target sites. The traditional domain adaptation method requires sharing data from both source and target domains, which will lead to data privacy issue. To solve it, federated learning is adopted as it can allow models to be trained with multi-site data in a privacy-protected manner. In this paper, we propose a multi-site federated domain adaptation framework via Transformer (FedDAvT), which not only protects data privacy, but also eliminates data heterogeneity. The Transformer network is used as the backbone network to extract the correlation between the multi-template region of interest features, which can capture the brain abundant information. The self-attention maps in the source and target domains are aligned by applying mean squared error for subdomain adaptation. Finally, we evaluate our method on the multi-site databases based on three AD datasets. The experimental results show that the proposed FedDAvT is quite effective, achieving accuracy rates of 88.75%, 69.51%, and 69.88% on the AD vs. NC, MCI vs. NC, and AD vs. MCI two-way classification tasks, respectively.

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19.

BACKGROUND: Biomedical relation extraction (RE) is of great importance for researchers to conduct systematic biomedical studies. It not only helps knowledge mining, such as knowledge graphs and novel knowledge discovery, but also promotes translational applications, such as clinical diagnosis, decision-making, and precision medicine. However, the relations between biomedical entities are complex and diverse, and comprehensive biomedical RE is not yet well established. OBJECTIVE: We aimed to investigate and improve large-scale RE with diverse relation types and conduct usability studies with application scenarios to optimize biomedical text mining. METHODS: Data sets containing 125 relation types with different entity semantic levels were constructed to evaluate the impact of entity semantic information on RE, and performance analysis was conducted on different model architectures and domain models. This study also proposed a continued pretraining strategy and integrated models with scripts into a tool. Furthermore, this study applied RE to the COVID-19 corpus with article topics and application scenarios of clinical interest to assess and demonstrate its biological interpretability and usability. RESULTS: The performance analysis revealed that RE achieves the best performance when the detailed semantic type is provided. For a single model, PubMedBERT with continued pretraining performed the best, with an F1-score of 0.8998. Usability studies on COVID-19 demonstrated the interpretability and usability of RE, and a relation graph database was constructed, which was used to reveal existing and novel drug paths with edge explanations. The models (including pretrained and fine-tuned models), integrated tool (Docker), and generated data (including the COVID-19 relation graph database and drug paths) have been made publicly available to the biomedical text mining community and clinical researchers. CONCLUSIONS: This study provided a comprehensive analysis of RE with diverse relation types. Optimized RE models and tools for diverse relation types were developed, which can be widely used in biomedical text mining. Our usability studies provided a proof-of-concept demonstration of how large-scale RE can be leveraged to facilitate novel research.

Investigation on the immunotoxicity induced by Emamectin benzoate on THP-1 macrophages based on metabolomics analysis.

Emamectin benzoate (EMB) is an insecticide extensively used in agricultural area. Assessing the toxic effects of EMB in mammals or humans and its endogenous metabolites alteration are the appropriate means of evaluating its risks to human health. In the study, THP-1 macrophage, a human immune model, was applied to investigate the immunotoxicity of EMB. A global metabolomics approach was developed to analyze metabolic perturbation on macrophages and discover the potential biomarkers of EMB-induced immunotoxicity. The results indicated that EMB could inhibit immune functions of macrophages. Based on metabolomics analysis, our results illustrated that EMB caused significant alterations in metabolic profiles on macrophages. 22 biomarkers associated with immune response were screened by pattern recognition and multivariate statistical analysis. Furthermore, pathway analysis identified purine metabolism was the most relevant pathway in the metabolic process and the abnormal conversion of AMP to xanthosine regulated by NT5E might be a potential mechanism of immunotoxicity induced by EMB. Our study provides important insights for understanding and underlying mechanism of immunotoxicity exposed to EMB.

ViMRT: a text-mining tool and search engine for automated virus mutation recognition.

MOTIVATION: Virus mutation is one of the most important research issues which plays a critical role in disease progression and has prompted substantial scientific publications. Mutation extraction from published literature has become an increasingly important task, benefiting many downstream applications such as vaccine design and drug usage. However, most existing approaches have low performances in extracting virus mutation due to both lack of precise virus mutation information and their development based on human gene mutations. RESULTS: We developed ViMRT, a text-mining tool and search engine for automated virus mutation recognition using natural language processing. ViMRT mainly developed 8 optimized rules and 12 regular expressions based on a development dataset comprising 830 papers of 5 human severe disease-related viruses. It achieved higher performance than other tools in a test dataset (1662 papers, 99.17% in F1-score) and has been applied well to two other viruses, influenza virus and severe acute respiratory syndrome coronavirus-2 (212 papers, 96.99% in F1-score). These results indicate that ViMRT is a high-performance method for the extraction of virus mutation from the biomedical literature. Besides, we present a search engine for researchers to quickly find and accurately search virus mutation-related information including virus genes and related diseases. AVAILABILITY AND IMPLEMENTATION: ViMRT software is freely available at http://bmtongji.cn:1225/mutation/index.

The potential immunotoxicity of emamectin benzoate on the human THP-1 macrophages.

Emamectin benzoate (EMB) as one of the typical biological pesticides has a wide range of applications in agriculture. However, the immune toxic effects of EMB in human received limited attention. In our study, THP-1 macrophage as an in vitro model was used to evaluate immune functions exposed to EMB. We observed that EMB inhibited phagocytic activity and respiratory burst capacity of macrophages without inducing cellular toxicity, implying the potential immunosuppression. Besides, EMB disturbed the cytokines balance embodied in the increase of TNF-α, IL-1ß, IL-6, CCL27, CXCL8 mRNA expression and the decrease of IL-4, IL-13, IL-10 mRNA expression. EMB could exhibit pro-inflammatory responses in macrophages and promote the conversion of macrophages to M1 phenotype. Moreover, NF-κB pathway involved in regulating immune function from KEGG pathway analysis. EMB exposure could activate the NF-κB pathway in THP-1 macrophages by exploring the critical proteins. This research provided insights on immunotoxicity evaluation and clarified EMB-induced immunotoxicity was related to NF-κB pathway activation.

Linearity of a silicon-based graphene electro-absorption modulator.

A silicon-based graphene modulator, holding the advantages of high modulation efficiency, high speed, and being ultra-compact, is regarded as a promising candidate for next-generation communication networks. Although the properties involved for optical communications have been widely studied, very few works evaluate the performance required for the microwave scenarios. Here, for the first time, to the best of our knowledge, the linearity of silicon-based graphene electro-absorption modulator (EAM) is analyzed and experimentally characterized through spurious free dynamic range (SFDR) with 82.5 dB·Hz1/2 and 100.3 dB·Hz2/3. Further calculations reveal that a higher SFDR value could be achieved through optimizing the bias voltage. Variations of capacitor structural parameters have little influence on the linearity. Such performance leads to the first, to the best of our knowledge, demonstration of a Gbps-level pulse-amplitude 4-level modulation scheme (PAM-4) eye diagram in a silicon-based graphene modulator.

Analysis on short-term change of macular function and the correlates after intravitreal conbercept for CRVO-ME.

AIM: To study the short-term change of macular function and the correlates after intravitreal conbercept for CRVO-ME. STUDY DESIGN: Prospective, clinical study. METHODS: Twenty Three patients(23 eyes) were recruited, who were non-ischemia central retinal vein occlusion diagnosed by FFA (fundus fluorescein angiography) and treated with intravitreal conbercept for macular edema, best - corrected visual acuity ( BCVA), central macular thickness(CMT), amplitude density of P1 wave and implicit time of P1,N1 wave from ring 1 and ring 2 of mf-ERG were measured before and 1 week、2 month after treatment. RESULTS: Compared to the baseline, BCVA、CMT、amplitude density of P1 wave and implicit time of P1,N1 wave from ring 1 and ring 2 were greatly improved at 1 W、2 M after treatment; better results were gained at 2 M compared to 1 W; Pearson correlation analysis shows no significantly correlation between the improvement of mf-ERG with the change of BCVA、CMT. CONCLUSION: The BCVA、the structure and the function of macular were greatly improved after intravitreal conbercept for central retinal vein occlusion induced macular edema; however no significantly correlation between the improvement of the function of macular with the strcture of macular and BCVA.

Synthesis and Biological Activity of Novel Antifungal Leads: 3,5-Dichlorobenzyl Ester Derivatives.

Succinate dehydrogenase (SDH) is one of the most important molecular targets for the development of new fungicides. Carboxamide fungicides are a class of SDH inhibitors widely used to inhibit highly destructive plant pathogens. Although cases of resistance have been found in fungal pathogens due to the unrestricted use in recent years, there is still demand for new compounds with improved fungicidal activity. Therefore, a series of ester compounds were designed to investigate potential novel antifungal molecules. First, the antifungal activity of different benzyl alcohol compounds (A1-A21) was tested, and a highly active fragment (3,5-dichlorobenzyl alcohol) was found. Subsequently, various compounds were synthesized by esterification between different acids and 3,5-dichlorobenzyl alcohol, among which compound 5 exhibited remarkable antifungal activity against Botrytis cinerea and Rhizoctonia solani with EC50 values of 6.60 and 1.61 mg/L, respectively, which were comparable to those of commercial fungicide boscalid (EC50 = 1.24 and 1.01 mg/L). In vivo testing further demonstrated that compound 5 was effective in suppressing B. cinerea (200 mg/L, 50.9%). Moreover, SDH inhibition assays, fluorescence quenching analysis, and determination of mitochondrial membrane potential revealed that compound 5 has similar effects to boscalid. Furthermore, the fungicidal activity of target compounds can be maintained by modifying the amide bond to an ester bond. These results will provide basis for the development of novel fungicides.

Isolation, structures and biological activities of polysaccharides from Chlorella: A review.

Chlorella, a green microalga, has been used as an important ingredient in food and medicine because of its excellent nutritive and functional properties. Polysaccharides, as major active ingredients of Chlorella, have attracted increasing attention due to their various health promotion activities, such as those associated with immunomodulation, antioxidation, anti-hyperlipidemia, antitumor, neuroprotection, and anti-asthmatic effect. The significance of polysaccharides from various species of the Chlorella genus has been extensively reported by the scientific community from the perspectives of extraction, structural features, biological activities, and potential uses, which need to be reviewed to improve the understanding, development and utilization of these species. Therefore, this review aims to comprehensively summarize previous and current references regarding the extraction, purification, structural characterization and biological activities of polysaccharides from Chlorella. Moreover, this review also highlights the challenges of investigation and future considerations for holistic utilization in food and medicine.

Profiling the constituents of Dachuanxiong decoction by liquid chromatography with high-resolution tandem mass spectrometry using target and nontarget data mining.

Comprehensive characterization of the large number of compounds existing in traditional Chinese medicines is still a great challenge. In this study, a strategy of precursor ion selected acquisition coupled with target and nontarget data mining was established to systematically characterize the chemical constituents of traditional Chinese medicines. This strategy consisted of four steps: (1) precursor ion selected acquisition was developed to trigger additional tandem mass spectrometry fragmentation reactions, especially for trace constituents; (2) in-house database of compounds was established and diagnostic characteristics were summarized; (3) compounds were identified by target and nontarget data mining; and (4) compound structures were elucidated based on accurate mass matching and comparison of fragment ions, and isomers were discriminated by the intensity of fragment ions, fragmentation pattern analysis, and calculated log P values. This strategy was successfully applied to comprehensively identify the constituents in Dachuanxiong decoction. Finally, a total of 218 compounds assigned to six categories were characterized, and 107 compounds were characterized by nontarget analysis for the first time. In addition, three new diagnostic characteristics of esters of citric acids were elucidated. This research enriched the material basis of Dachuanxiong decoction and provided a new strategy for identifying the chemical constituents of other traditional Chinese medicines.

[Simultaneous quantification and consistency analysis of 19 representative components in Longshengzhi Capsules by HPLC-QQQ/MS].

Longshengzhi capsule consisting of 12 herbs is widely used in clinically treating cerebral ischemia during recovery period.In this study,in order to investigate the consistency of different batches of Longshengzhi capsules,a high performance liquid chromatography coupled to triple quadrupole mass spectrometry method(HPLC-QQQ/MS) was developed for the determination of 19 representative components in Longshengzhi Capsules within 9 min. Methodology validation indicated this method was simple,rapid,accurate,highly sensitive and reproducible,and it could be used for the content determination of components in Longshengzhi Capsules. The consistency analysis results showed that paeoniflorin and calycosin-7-glucoside in Longshengzhi Capsules had the highest content; RSD value of total content of 19 compounds was 5. 2% and the RSD value of main compounds such as astragaloside and calycosin-7-glucoside was all less than 15%,reflecting good consistency among different batches. This study has provided a scientific method and basis for the quality control and consistency evaluation of Longshengzhi Capsules.

Two-Dimensional Zeolitic Imidazolate Framework-L-Derived Iron-Cobalt Oxide Nanoparticle-Composed Nanosheet Array for Water Oxidation.

Rational design of various functional nanomaterials using MOFs as a template provides an effective strategy to synthesize electrocatalysts for water splitting. In this work, we reported that an iron-cobalt oxide with 2D well-aligned nanoflakes assembling on carbon cloth (Fe-Co3O4 NS/CC), fabricated by an anion-exchange reaction followed by an annealing process, could serve as a high-performance oxygen-evolving catalyst. Specifically, the zeolitic imidazolate framework-L-Co nanosheet array (ZIF-L-Co NS/CC) was synthesized through a facile ambient liquid-phase deposition reaction, and then reacted with [Fe(CN)6]3- ions as precursors during the anion-exchange reaction at room temperature. Finally, the Fe-Co3O4 NS/CC was obtained via annealing treatment. On account of the compositional and structural superiority, this 3D monolithic anode exhibited outstanding electrocatalytic performance with a low overpotential of 290 mV to obtain a geometrical current density of 10 mA cm-2 and good durability for water oxidation in base.

Network Pharmacology-Based Investigation of Protective Mechanism of Aster tataricus on Lipopolysaccharide-Induced Acute Lung Injury.

Acute lung injury (ALI) is a common clinical condition that badly influences people's health. Recent studies indicated that Aster tataricus (RA) had potential effects on ALI, but the effective components and their mechanism is not clear. In this study, we found that the Fraction-75 eluted from RA extract could significantly protect the lipopolysaccharide (LPS)-induced ALI in mice, including alleviating the severity of lung pathology, attenuating the pulmonary edema, and reducing the release of inflammatory cells. Further ingredient analyses demonstrated that there were mainly 16 components in it, among which 10 components were collected according to their relative peak area and oral bioavailability. Next, the components-disease targets network suggested that the candidate components had extensive associations with 49 known therapeutic targets of ALI, among which 31 targets could be regulated by more than one component. Herein, GO functional and pathway analysis revealed that the common targets were associated with four biological processes, including the inflammatory response to stimulus, cellular process, chemokine biosynthetic process and immune system process. Furthermore, the ELISA validation indicated that the candidate components in RA extract may protect the LPS-induced ALI mainly through inhibiting the release of inflammatory cytokines and promoting the repair of vascular endothelial.

[Studies on constituents of Polygonum multiflorum extract in vivo and in vitro based on UPLC-Q-TOF-MS].

To explore the drug-induced constituents in vivo of Polygonum multiflorum extract (PM). This study was the first to study the drug-induced constituents in target organ liver. Agilent MassHunter qualitative analysis software and Metabolite ID software were applied for the analysis of retention time, exact relative molecular mass, primary and secondary mass spectrum information based on ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and targeted-MS/MS. By comparison with literature and standards, a total of 5 prototypes and 6 metabolites were identified or tentatively elucidated from the liver samples. In addition, the drug-induced constituents in plasma and PM were also analyzed in this study and 8 prototypes and 19 metabolites were detected from the plasma samples, while 30 compounds were detected from the extract of PM. Emodin oxidative acetylation metabolites, hydroxyl methylation metabolites, carboxylation glucuronidation metabolites and ketone glucuronidation metabolites in this study were first reported. Through the comparative analysis between the in vivo and in vitro constituents of PM, the study preliminarily revealed the drug-induced constituents (prototypes and metabolites) in liver and clarified the transfer process and transmutation rules of constituents in PM, blood and liver, which would further deepen our understanding on constituents of PM in vivo.

Dose-dependent target diversion of Danhong injection on the Glu-GLT-1/Gly-GlyRα dynamic balance module of cerebral ischemia.

Function-oriented modular structure analysis is a great challenge in module-based pharmacological studies. A strategy to uncover target-target interaction (TTI) and dynamic balance regularity (DBR) was established to discover the structural factors influencing modular functions and explore the mechanism of Danhong injection (DHI) in treating cerebral ischemia. The dose-related metabolic features of DHI intervention were investigated using metabolomics and modular pharmacology. The findings indicated that Glu/Gly was a biomarker and Glu-GLT-1/Gly-GlyRα was the core unit regulated by DHI. Gly and Glu displayed opposite patterns and functional roles, representing intra-modular balance. GlyRα was identified as the upstream target and GLT-1 as the downstream target by inhibiting or activating GlyRα, indicating that DHI has two dose-dependent regulatory modes. GlyRα was the major target at low doses, while GLT-1 was activated as the dominant target as doses accumulated. Our study reveals that target-target interaction and dynamic balance regularity are the key factors influencing modular functions, which is a promising breakthrough for module-based pharmacological studies.

Conductive Leaflike Cobalt Metal-Organic Framework Nanoarray on Carbon Cloth as a Flexible and Versatile Anode toward Both Electrocatalytic Glucose and Water Oxidation.

Transition metal-organic frameworks (MOFs), on account of their unique inherent properties of large pore volume, high specific surface area, tunable pores, and good catalytic activity, have been highly regarded as superior catalysts recently for water electrolysis, supercapacitors, batteries, sensors, and so on. Herein, we report on a cobalt MOF phase with 3D well-aligned nanosheets array architecture on carbon cloth (Co-MOF NS/CC), fabricated by a facile ambient liquid-phase deposition, could serve as a self-standing Janus catalytic electrode toward both glucose and water oxidation. It shows good glucose-sensing performance with low determination limit and large detection range. Also, it exhibits high water-oxidation efficiency with low overpotential and good durability. This work demonstrates the potential of utilizing transition-metal based well-aligned MOF nanoarrays for electrocatalytic oxidation.