ST-SCGNN: A Spatio-Temporal Self-Constructing Graph Neural Network for Cross-Subject EEG-Based Emotion Recognition and Consciousness Detection.

In this paper, a novel spatio-temporal self-constructing graph neural network (ST-SCGNN) is proposed for cross-subject emotion recognition and consciousness detection. For spatio-temporal feature generation, activation and connection pattern features are first extracted and then combined to leverage their complementary emotion-related information. Next, a self-constructing graph neural network with a spatio-temporal model is presented. Specifically, the graph structure of the neural network is dynamically updated by the self-constructing module of the input signal. Experiments based on the SEED and SEED-IV datasets showed that the model achieved average accuracies of 85.90% and 76.37%, respectively. Both values exceed the state-of-the-art metrics with the same protocol. In clinical besides, patients with disorders of consciousness (DOC) suffer severe brain injuries, and sufficient training data for EEG-based emotion recognition cannot be collected. Our proposed ST-SCGNN method for cross-subject emotion recognition was first attempted in training in ten healthy subjects and testing in eight patients with DOC. We found that two patients obtained accuracies significantly higher than chance level and showed similar neural patterns with healthy subjects. Covert consciousness and emotion-related abilities were thus demonstrated in these two patients. Our proposed ST-SCGNN for cross-subject emotion recognition could be a promising tool for consciousness detection in DOC patients.

ANRIL promotes the regulation of colorectal cancer on lymphatic endothelial cells via VEGF-C and is the key target for Pien Tze Huang to inhibit cancer metastasis.

lncRNA ANRIL is an oncogene, however the role of ANRIL in the regulation of colorectal cancer on human lymphatic endothelial cells (HLECs) is remain elusive. Pien Tze Huang (PZH, PTH) a Tradition Chinese Medicine (TCM) as an adjunctive medication could inhibit the cancer metastasis, however the mechanism still uncovering. We used network pharmacology, subcutaneous and orthotopic transplanted colorectal tumors models to determine the effect of PZH on tumor metastasis. Differential expressions of ANRIL in colorectal cancer cells, and stimulating the regulation of cancer cells on HLECs by culturing HLECs with cancer cells' supernatants. Network pharmacology, transcriptomics, and rescue experiments were carried out to verify key targets of PZH. We found PZH interfered with 32.2% of disease genes and 76.7% of pathways, and inhibited the growth of colorectal tumors, liver metastasis, and the expression of ANRIL. The overexpression of ANRIL promoted the regulation of cancer cells on HLECs, leading to lymphangiogenesis, via upregulated VEGF-C secretion, and alleviated the effect of PZH on inhibiting the regulation of cancer cells on HLECs. Transcriptomic, network pharmacology and rescue experiments show that PI3K/AKT pathway is the most important pathway for PZH to affect tumor metastasis via ANRIL. In conclusion, PZH inhibits the regulation of colorectal cancer on HLECs to alleviate tumor lymphangiogenesis and metastasis by downregulating ANRIL dependent PI3K/AKT/VEGF-C pathway.

Comparison of Third-Generation Sequencing Technology and Traditional Microbiological Detection in Pathogen Diagnosis of Lower Respiratory Tract Infection.

BACKGROUND: It is common to obtain a low detection rate and unsatisfactory detection results in complex infection or rare pathogen detection. This retrospective study aimed to illustrate the application value and prospect of the third-generation sequencing technology in lower respiratory tract infection disease. METHODS: This study recruited 70 patients with lower respiratory tract infection (LRTI). Pathogen detection of bronchoalveolar lavage fluid (BALF) from all patients was performed using nanopore metagenomic sequencing technology and traditional culture. BALF culture combined with quantitiative PCR (qPCR) was used as a reference standard to analyze the sensitivity and specificity of nanopore sequencing technology. The current study also collected the examination results of enrolled samples using technical methods sputum culture, tuberculosis DNA (TB-DNA), and Xpert MTB/RIF and analyzed the detection efficiency of nanopore sequencing for Mycobacterium tuberculosis. RESULTS: The positive rates of pathogens in 70 BALF samples detected by conventional culture and nanopore sequencing were 25.71% and 84.29%, respectively. Among the 59 positive BALF cases using nanopore sequencing, a total of 31 pathogens were identified, of which the proportions of bacteria, fungi, viruses, and other pathogens were 50%, 17%, 32%, and 1%, respectively. Using the results combined with culture and qPCR detection methods as the standard, the pathogen detection of BALF using nanopore sequencing had a sensitivity of 70% and a specificity of 91.7%. Additionally, the positive rate of the detection of M. tuberculosis using nanopore sequencing was 33.3% (6/18). The clinical medication plans of 74.3% (52/70) of the patients were referred to the nanopore sequencing results, of which 31 cases changed their treatment strategy, 21 supported the previous treatment plans, and 90% (47/52) of the patients finally had clinical improvement. CONCLUSIONS: BALF detection using nanopore sequencing technology improves the process of detecting pathogens in patients with LRTI, especially for M. tuberculosis, fungi, and viruses, by reducing the report time from three days to six hours. The clinical application prospect of nanopore sequencing technology is promising in the pathogen diagnosis of LRTI.

A retrospective study on epidemiological analysis of pre-hospital emergency care in Hangzhou, China.

Out-of-hospital cardiac arrest (OHCA) is a leading cause of global mortality, with numerous factors influencing the patient survival rate and prognosis. This study aimed to evaluate the OHCA epidemiology in China and elaborate on the current Hangzhou emergency system status. This retrospective analysis was based on the medical history system of the Hangzhou Emergency Center registered from 2015-2021. We provided a detailed description of OHCA characteristics and investigated the factors affecting the success rate of emergency treatment in terms of epidemiology, causes of onset, bystander rescue, and outcome factors. We included 9585 out-of-hospital cardiac arrest cases, of which 5442 (56.8%) had evidence of resuscitation. Patients with underlying diseases constituted the vast majority (80.1%); trauma and physicochemical factors accounted for 16.5% and 3.4%, respectively. Only 30.4% of patients (about 80.0% of bystanders witnessed) received bystander first aid. The outcome rate of emergency doctors dispatched by emergency centres was significantly higher than doctors dispatched by hospitals. Additionally, physician's first-aid experience, emergency response time, emergency telephone availability, initial heart rhythm, out-of-hospital defibrillation, out-of-hospital intubation, and using of epinephrine significantly can significantly improve the out-of-hospital return of spontaneous circulation in patients. All steps in pre-hospital care are important for patients, especially for bystander first aid and physician's first-aid experience. The popularity of first-aid training and the public emergency medical system are not potent enough. We should take those key factors into consideration when developing a pre-hospital care system for OHCA.

Disrupted multi-scale topological organization of directed functional brain networks in patients with disorders of consciousness.

Disorders of consciousness are impaired states of consciousness caused by severe brain injuries. Previous resting-state functional magnetic resonance imaging studies have reported abnormal brain network properties at different topological scales in patients with disorders of consciousness by using graph theoretical analysis. However, it is still unclear how inter-regional directed propagation activities affect the topological organization of functional brain networks in patients with disorders of consciousness. To reveal the altered topological organization in patients with disorders of consciousness, we constructed whole-brain directed functional networks by combining functional connectivity analysis and time delay estimation. Then we performed graph theoretical analysis based on the directed functional brain networks at three topological scales, from the nodal scale, the resting-state network scale to the global scale. Finally, the canonical correlation analysis was used to determine the correlations between altered topological properties and clinical scores in patients with disorders of consciousness. At the nodal scale, we observed decreased in-degree and increased out-degree in the precuneus in patients with disorders of consciousness. At the resting-state network scale, the patients with disorders of consciousness showed reorganized motif patterns within the default mode network and between the default mode network and other resting-state networks. At the global scale, we found a lower global clustering coefficient in the patients with disorders of consciousness than in the controls. The results of the canonical correlation analysis showed that the abnormal degree and the disrupted motif were significantly correlated with the clinical scores of the patients with disorders of consciousness. Our findings showed that consciousness impairment can be revealed by abnormal directed connection patterns at multiple topological scales in the whole brain, and the disrupted directed connection patterns may serve as clinical biomarkers to assess the dysfunction of patients with disorders of consciousness.

Chemotherapeutic Drugs Induce Different Gut Microbiota Disorder Pattern and NOD/RIP2/NF-κB Signaling Pathway Activation That Lead to Different Degrees of Intestinal Injury.

5-Fluorouracil (5-FU), irinotecan (CPT-11), oxaliplatin (L-OHP), and calcium folinate (CF) are widely used chemotherapeutic drugs to treat colorectal cancer. However, chemotherapeutic use is often accompanied by intestinal inflammation and gut microbiota disorder. Changes in gut microbiota may destroy the intestinal barrier, which contributes to the severity of intestinal injury. However, intestinal injury and gut microbiota disorder have yet to be compared among 5-FU, CPT-11, L-OHP, and CF in detail, thereby limiting the development of targeted detoxification therapy after chemotherapy. In this study, a model of chemotherapy-induced intestinal injury in tumor-bearing mice was established by intraperitoneally injecting chemotherapeutic drugs at a clinically equivalent dose. 16S rRNA gene sequencing was used to detect gut microbiota. We found that 5-FU, CPT-11, and l-OHP caused intestinal injury, inflammatory cytokine (gamma interferon [IFN-γ], tumor necrosis factor alpha [TNF-α], interleukin-1ß [IL-1ß], and IL-6) secretion, and gut microbiota disorder. We established a complex but clear network between the pattern of changes in gut microbiota and degree of intestinal damage induced by different chemotherapeutic drugs. L-OHP caused the most severe damage in the intestine and disorder of the gut microbiota and showed a considerable overlap of the pattern of changes in microbiota with 5-FU and CPT-11. Analysis by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt v.1.0) showed that the microbiota disorder pattern induced by 5-FU, CPT-11, and L-OHP was related to the NOD-like signaling pathway. Therefore, we detected the protein expression of the NOD/RIP2/NF-κB signaling pathway and found that L-OHP most activated this pathway. Redundancy analysis/canonical correlation analysis (RDA/CCA) revealed that Bifidobacterium, Akkermansia, Allobaculum, Catenibacterium, Mucispirillum, Turicibacter, Helicobacter, Proteus, Escherichia Shigella, Alloprevotealla, Vagococcus, Streptococcus, and "Candidatus Saccharimonas" were highly correlated with the NOD/RIP2/NF-κB signaling pathway and influenced by chemotherapeutic drugs. IMPORTANCE Chemotherapy-induced intestinal injury limits the clinical use of drugs. Intestinal injury involves multiple signaling pathways and gut microbiota disruption. Our results suggested that the degree of intestinal injury caused by different drugs of the first-line colorectal chemotherapy regimen is related to the pattern of changes in microbiota. The activation of the NOD/RIP2/NF-κB signaling pathway was also related to the pattern of changes in microbiota. l-OHP caused the most severe damage to the intestine and showed a considerable overlap of the pattern of changes in microbiota with 5-FU and CPT-11. Thirteen bacterial genera were related to different levels of intestinal injury and correlated with the NOD/RIP2/NF-κB pathway. Here, we established a network of different chemotherapeutic drugs, gut microbiota, and the NOD/RIP2/NF-κB signaling pathway. This study likely provided a new basis for further elucidating the mechanism and clinical treatment of intestinal injury caused by chemotherapy.

Fast Hydroxide Conduction via Hydrogen-Bonding Network Confined in Benzimidazolium-Functionalized Covalent Organic Frameworks.

In both hydrophobic and hydrophilic nanochannels, confined water clusters spontaneously form dense internal hydrogen bond networks and hence exhibit fast mass-transfer kinetics. Covalent organic frameworks (COFs), a porous polymer, enables one-dimensional open channels to achieve ordered assembly guided by synthetic techniques and allows the accommodation of a large number of water molecules within the nanochannels. In the field of alkaline anion exchange membrane fuel cells, it has been a long-term pursuit of scientists to build abundant hydrogen bonds around hydrogen oxides (OH-) to improve the conduction of OH- by increasing the water content. Here, we designed and synthesized a OH- conductor by assembling benzimidazolium into COFs, and a significantly high conductivity of 10-1 S cm-1 was achieved at 353 K. Theoretical calculations showed that the water clusters confined in the pores of COFs and the regularly arranged hydroxides cooperatively formed a dense hydrogen bond network and OH- conducted diffusive conduction through the Grotthuss hopping of protons in this hydrogen bond network.

Using an untargeted metabolomics approach to analyze serum metabolites in COVID-19 patients with nucleic acid turning negative.

Background: The coronavirus disease of 2019 (COVID-19) is a severe public health issue that has infected millions of people. The effective prevention and control of COVID-19 has resulted in a considerable increase in the number of cured cases. However, little research has been done on a complete metabonomic examination of metabolic alterations in COVID-19 patients following treatment. The current project pursues rigorously to characterize the variation of serum metabolites between healthy controls and COVID-19 patients with nucleic acid turning negative via untargeted metabolomics. Methods: The metabolic difference between 20 COVID-19 patients (CT ≥ 35) and 20 healthy controls were investigated utilizing untargeted metabolomics analysis employing High-resolution UHPLC-MS/MS. COVID-19 patients' fundamental clinical indicators, as well as health controls, were also collected. Results: Out of the 714 metabolites identified, 203 still significantly differed between COVID-19 patients and healthy controls, including multiple amino acids, fatty acids, and glycerophospholipids. The clinical indexes including monocytes, lymphocytes, albumin concentration, total bilirubin and direct bilirubin have also differed between our two groups of participators. Conclusion: Our results clearly showed that in COVID-19 patients with nucleic acid turning negative, their metabolism was still dysregulated in amino acid metabolism and lipid metabolism, which could be the mechanism of long-COVID and calls for specific post-treatment care to help COVID-19 patients recover.

A Self-Supervised Learning Based Channel Attention MLP-Mixer Network for Motor Imagery Decoding.

Convolutional Neural Network (CNN) is commonly used for the Electroencephalogram (EEG) based motor-imagery (MI) decoding. However, its performance is generally limited due to the small size sample problem. An alternative way to address such issue is to segment EEG trials into small slices for data augmentation, but this approach usually inevitably loses the valuable long-range dependencies of temporal information in EEG signals. To this end, we propose a novel self-supervised learning (SSL) based channel attention MLP-Mixer network (S-CAMLP-Net) for MI decoding with EEG. Specifically, a new EEG slice prediction task is designed as the pretext task to capture the long-range information of EEG trials in the time domain. In the downstream task, a newly proposed MLP-Mixer is applied to the classification task for signals rather than for images. Moreover, in order to effectively learn the discriminative spatial representations in EEG slices, an attention mechanism is integrated into MLP-Mixer to adaptively estimate the importance of each EEG channel without any prior information. Thus, the proposed S-CAMLP-Net can effectively learn more long-range temporal information and global spatial features of EEG signals. Extensive experiments are conducted on the public MI-2 dataset and the BCI Competition IV Dataset 2A. The experimental results indicate that our proposed S-CAMLP-Net achieves superior classification performance over all the compared algorithms.

Novel serological biomarker panel using protein microarray can distinguish active TB from latent TB infection.

BACKGROUND: Rapid laboratory technologies which can effectively distinguish active tuberculosis (ATB) from controls and latent tuberculosis infection (LTBI) are lacked.The objective of this study is to explore MTB biomarkers in serum that can distinguish ATB from LTBI. METHODS: We constructed a tuberculosis protein microarray containing 64 MTB associated antigens. We then used this microarray to screen 180 serum samples, from patients with ATB and LTBI, and healthy volunteer controls. Both SAM (Significance analysis of microarrays) and ROC curve analysis were used to identify the differentially recognized biomarkers between groups. Extra 300 serum samples from patients with ATB and LTBI, and healthy volunteer controls were employed to validate the identified biomarkers using ELISA-based method. RESULTS: According to the results, the best biomarker combinations of 4 proteins (Rv1860, RV3881c, Rv2031c and Rv3803c) were selected. The biomarker panel containing these 4 proteins has reached a sensitivity of 93.3% and specificity of 97.7% for distinguishing ATB from LTBI, and a sensitivity of 86% and specificity of 97.6% for distinguishing ATB from HC. CONCLUSION: The biomarker combination in this study has high sensitivity and specificity in distinguishing ATB from LTBI, suggesting it is worthy for further validation in more clinical samples.

Toward Assessment of Sound Localization in Disorders of Consciousness Using a Hybrid Audiovisual Brain-Computer Interface.

Behavioral assessment of sound localization in the Coma Recovery Scale-Revised (CRS-R) poses a significant challenge due to motor disability in patients with disorders of consciousness (DOC). Brain-computer interfaces (BCIs), which can directly detect brain activities related to external stimuli, may thus provide an approach to assess DOC patients without the need for any physical behavior. In this study, a novel audiovisual BCI system was developed to simulate sound localization evaluation in CRS-R. Specifically, there were two alternatively flashed buttons on the left and right sides of the graphical user interface, one of which was randomly chosen as the target. The auditory stimuli of bell sounds were simultaneously presented by the ipsilateral loudspeaker during the flashing of the target button, which prompted patients to selectively attend to the target button. The recorded electroencephalography data were analyzed in real time to detect event-related potentials evoked by the target and further to determine whether the target was attended to or not. A significant BCI accuracy for a patient implied that he/she had sound localization. Among eighteen patients, eleven and four showed sound localization in the BCI and CRS-R, respectively. Furthermore, all patients showing sound localization in the CRS-R were among those detected by our BCI. The other seven patients who had no sound localization behavior in CRS-R were identified by the BCI assessment, and three of them showed improvements in the second CRS-R assessment after the BCI experiment. Thus, the proposed BCI system is promising for assisting the assessment of sound localization and improving the clinical diagnosis of DOC patients.

Metaexoproteomics Reveals Microbial Behavior in the Ocean's Interior.

The proteins present in the extracellular environment of cells, named the "exoproteome," are critical for microbial survival, growth, and interaction with their surroundings. However, little is known about microbial exoproteomes in natural marine environments. Here, we used a metaproteomic approach to characterize the exoprotein profiles (10 kDa-0.2 µm) throughout a water column in the South China Sea. Viruses, together with Alpha- and Gammaproteobacteria were the predominant contributors. However, the exoprotein-producing microbial communities varied with depth: SAR11 in the shallow waters, Pseudomonadales and Nitrososphaeria in the mesopelagic layer, and Alteromonadales, Rhizobiales, and Betaproteobacteria in the bathypelagic layer. Besides viral and unknown proteins, diverse transporters contributed substantially to the exoproteomes and varied vertically in their microbial origins, but presented similar patterns in their predicted substrate identities throughout the water column. Other microbial metabolic processes subject to vertical zonation included proteolysis, the oxidation of ammonia, nitrite and carbon monoxide, C1 metabolism, and the degradation of sulfur-containing dissolved organic matter (DOM). Our metaexoproteomic study provides insights into the depth-variable trends in the in situ ecological traits of the marine microbial community hidden in the non-cellular world, including nutrient cycling, niche partitioning and DOM remineralization.

Plasma proteomic and metabolomic characterization of COVID-19 survivors 6 months after discharge.

Coronavirus disease 2019 (COVID-19) has gained prominence as a global pandemic. Studies have suggested that systemic alterations persist in a considerable proportion of COVID-19 patients after hospital discharge. We used proteomic and metabolomic approaches to analyze plasma samples obtained from 30 healthy subjects and 54 COVID-19 survivors 6 months after discharge from the hospital, including 30 non-severe and 24 severe patients. Through this analysis, we identified 1019 proteins and 1091 metabolites. The differentially expressed proteins and metabolites were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Among the patients evaluated, 41% of COVID-19 survivors reported at least one clinical symptom and 26.5% showed lung imaging abnormalities at 6 months after discharge. Plasma proteomics and metabolomics analysis showed that COVID-19 survivors differed from healthy control subjects in terms of the extracellular matrix, immune response, and hemostasis pathways. COVID-19 survivors also exhibited abnormal lipid metabolism, disordered immune response, and changes in pulmonary fibrosis-related proteins. COVID-19 survivors show persistent proteomic and metabolomic abnormalities 6 months after discharge from the hospital. Hence, the recovery period for COVID-19 survivors may be longer.

GPC2 deficiency inhibits cell growth and metastasis in colon adenocarcinoma.

Glypican-2 (GPC2) has been reported to promote tumor progression through metabolic pathways. However, the role of GPC2 in colon adenocarcinoma (COAD) remains to be further investigated. This study was designed to evaluate the role of GPC2 in COAD. Based on patients with complete clinical information and GPC2 expression from the Cancer Genome Atlas-COAD database, we found that GPC2 mRNA was highly expressed in COAD tissues, which was associated with poor prognosis and tumornode-metastasis (TNM) stage. The predicted survival probability based on GPC2 mRNA expression and TNM stage was in good agreement with the observed survival probability. Furthermore, the genes coexpressed with GPC2 in COAD tissues were significantly enriched in basal cell carcinoma, Notch signaling pathway, and Hedgehog signaling pathway. After GPC2 was decreased through transfecting short hairpin RNA of GPC2 into HCT-8 and SW620 cells, cell cycle was arrested in G0/G1 phase, proliferation was decreased, apoptosis was increased, and migration and invasion were repressed. In conclusion, decreasing GPC2 significantly inhibited proliferation, migration, and invasion, and enhanced apoptosis, which implied that GPC2 can be considered a promising therapeutic target of COAD in the future.

Metabolic tuning of a stable microbial community in the surface oligotrophic Indian Ocean revealed by integrated meta-omics.

Understanding the mechanisms, structuring microbial communities in oligotrophic ocean surface waters remains a major ecological endeavor. Functional redundancy and metabolic tuning are two mechanisms that have been proposed to shape microbial response to environmental forcing. However, little is known about their roles in the oligotrophic surface ocean due to less integrative characterization of community taxonomy and function. Here, we applied an integrated meta-omics-based approach, from genes to proteins, to investigate the microbial community of the oligotrophic northern Indian Ocean. Insignificant spatial variabilities of both genomic and proteomic compositions indicated a stable microbial community that was dominated by Prochlorococcus, Synechococcus, and SAR11. However, fine tuning of some metabolic functions that are mainly driven by salinity and temperature was observed. Intriguingly, a tuning divergence occurred between metabolic potential and activity in response to different environmental perturbations. Our results indicate that metabolic tuning is an important mechanism for sustaining the stability of microbial communities in oligotrophic oceans. In addition, integrated meta-omics provides a powerful tool to comprehensively understand microbial behavior and function in the ocean. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-021-00119-6.

An NIR-II Responsive Nanoplatform for Cancer Photothermal and Oxidative Stress Therapy.

Chemodynamic therapy as an emerging therapeutic strategy has been implemented for oncotherapy. However, the reactive oxygen species can be counteracted by the exorbitant glutathione (GSH) produced by the tumor cells before exerting the antitumor effect. Herein, borneol (NB) serving as a monoterpenoid sensitizer, and copper sulfide (CuS NPs) as an NIR-II photothermal agent were loaded in a thermo-responsive vehicle (NB/CuS@PCM NPs). Under 1,060-nm laser irradiation, the hyperthermia produced by CuS NPs can be used for photothermal therapy and melt the phase change material for drug delivery. In the acidity microenvironment, the CuS NPs released from NB/CuS@PCM NPs could degrade to Cu2+, then Cu2+ was reduced to Cu+ during the depletion of GSH. As Fenton-like catalyst, the copper ion could convert hydrogen peroxide into hydroxyl radicals for chemodynamic therapy. Moreover, the NB originated from NB/CuS@PCM NPs could increase the intracellular ROS content to improve the treatment outcome of chemodynamic therapy. The animal experimental results indicated that the NB/CuS@PCM NPs could accumulate at the tumor site and exhibit an excellent antitumor effect. This work confirmed that the combination of oxidative stress-induced damage and photothermal therapy is a potential therapeutic strategy for cancer treatment.

In Situ Aliovalent Nickle Substitution and Acidic Modification of Nanowalls Promoted Proton Conductivity in InOF with 1D Helical Channel.

Proton-conductive materials have attracted increasing attention because of their broad explorations in chemical sensors, water electrolysis, fuel cells, and biological systems. Especially, metal-organic frameworks (MOFs) have been demonstrated to be extremely promising candidates as proton-exchange membrane (PEM) fuel cells. Compared with other configurations, MOFs with one-dimensional (1D) channels have the characteristics of enhancing the host-guest interaction and promoting the anisotropic motion of proton carriers in restricted volume, which are beneficial for acquiring rich proton sources and forming successive hydrogen bonds to improve proton conductivity. We are endeavored to screen and find a helical three-dimensional (3D) framework InOF-1, namely, [In2(OH)2(BPTC)]·6H2O (BPTC4- = 3,3',5,5'-biphenyl tetracarboxylate), as a typical 1D-channel MOF, which is pristinely grafted with spirally distributed -OH groups on the channel surface. Accompanied by an aliovalent substitution Ni(II) for In(III), isostructural NiOF-1 ([Ni2(BPTC)(HCOOH)2]·3H2O) is successfully prepared and massive formic acids are anchored at interior walls, which are interacted with adsorbed water molecules via the formation of stronger O-H···O bonds. This interaction between host-guest molecules and dynamics of lattice water has already led to a remarkable conductivity of InOF-1 (σ = 7.86 × 10-3 S/cm at 328 K under 95% RH). The synergistic effect of the acidic-modified nanowall, contracted volume, and enhanced adsorption of water molecules in the NiOF-1 channel contributes to a high conductivity value of 3.41 × 10-2 S/cm (at 328 K under 95% RH). Moreover, the proton conduction mechanism is further visually presented by molecular dynamic (MD) simulation. In contrast to InOF-1, aliovalent-substituted and acidic-modified NiOF-1 has a stronger host-guest interaction and more abundant hydrogen-bond networks, resulting in shorter proton migration distances and more frequent proton hopping, in agreement with the experimental results.

Illuminating Key Microbial Players and Metabolic Processes Involved in the Remineralization of Particulate Organic Carbon in the Ocean's Twilight Zone by Metaproteomics.

The twilight zone (from the base of the euphotic zone to the depth of 1,000 m) is the major area of particulate organic carbon (POC) remineralization in the ocean, and heterotrophic microbes contribute to more than 70% of the estimated remineralization. However, little is known about the microbial community and metabolic activity directly associated with POC remineralization in this chronically understudied realm. Here, we characterized the microbial community proteomes of POC samples collected from the twilight zone of three contrasting sites in the Northwest Pacific Ocean using a metaproteomic approach. The particle-attached bacteria from Alteromonadales, Rhodobacterales, and Enterobacterales were the primary POC remineralizers. Hydrolytic enzymes, including proteases and hydrolases, that degrade proteinaceous components and polysaccharides, the main constituents of POC, were abundant and taxonomically associated with these bacterial groups. Furthermore, identification of diverse species-specific transporters and metabolic enzymes implied niche specialization for nutrient acquisition among these bacterial groups. Temperature was the main environmental factor driving the active bacterial groups and metabolic processes, and Enterobacterales replaced Alteromonadales as the predominant group under low temperature. This study provides insight into the key bacteria and metabolic processes involved in POC remineralization, and niche complementarity and species substitution among bacterial groups are critical for efficient POC remineralization in the twilight zone. IMPORTANCE The ocean's twilight zone is a critical zone where more than 70% of the sinking particulate organic carbon (POC) is remineralized. Therefore, the twilight zone determines the size of biological carbon storage in the ocean and regulates the global climate. Prokaryotes are major players that govern remineralization of POC in this region. However, knowledge of microbial community structure and metabolic activity is still lacking. This study unveiled microbial communities and metabolic activities of POC samples collected from the twilight zone of three contrasting environments in the Northwest Pacific Ocean using a metaproteomic approach. Alteromonadales, Rhodobacterales, and Enterobacterales were the major remineralizers of POC. They excreted diverse species-specific hydrolytic enzymes to split POC into solubilized POC or dissolved organic carbon. Temperature played a crucial role in regulating the community composition and metabolism. Furthermore, niche complementarity or species substitution among bacterial groups guaranteed the efficient remineralization of POC in the twilight zone.

Metaproteomics Reveals Similar Vertical Distribution of Microbial Transport Proteins in Particulate Organic Matter Throughout the Water Column in the Northwest Pacific Ocean.

Solubilized particulate organic matter (POM) rather than dissolved organic matter (DOM) has been speculated to be the major carbon and energy sources for heterotrophic prokaryotes in the ocean. However, the direct evidence is still lack. Here we characterized microbial transport proteins of POM collected from both euphotic (75 m, deep chlorophyll maximum DCM, and 100 m) and upper-twilight (200 m and 500 m) zones in three contrasting environments in the northwest Pacific Ocean using a metaproteomic approach. The proportion of transport proteins was relatively high at the bottom of the euphotic zone (200 m), indicating that this layer was the most active area of microbe-driven POM remineralization in the water column. In the upper-twilight zone, the predicted substrates of the identified transporters indicated that amino acids, carbohydrates, taurine, inorganic nutrients, urea, biopolymers, and cobalamin were essential substrates for the microbial community. SAR11, Rhodobacterales, Alteromonadales, and Enterobacteriales were the key contributors with the highest expression of transporters. Interestingly, both the taxonomy and function of the microbial communities varied among water layers and sites with different environments; however, the distribution of transporter types and their relevant organic substrates were similar among samples, suggesting that microbial communities took up similar compounds and were functionally redundant in organic matter utilization throughout the water column. The similar vertical distribution of transport proteins from the euphotic zone to the upper twilight zone among the contrasting environments indicated that solubilized POM rather than DOM was the preferable carbon and energy sources for the microbial communities.