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Functionalizing the organic building blocks of electrically conductive MOFs (EC-MOFs) can be a powerful method for adjusting the electronic structure and introducing a specific chemistry. However, designing EC-MOF linkers with reactive functional groups for postsynthetic modification is challenging due to the requirements of d-p conjugation. This work addresses such design limitations by synthesizing an EC-MOF, Cu-thiatruxene (Cu-thiaTRX). This conductive framework incorporated a truxene-based linker with heterocyclic sulfur, allowing for efficient conjugation and an electrical conductivity of 2.2 × 10-2 S cm-1. Harnessing sulfur chemistry in Cu-thiaTRX involves a two-step postsynthetic modification: oxidation and SNAr. The sulfinic groups introduced in the framework enabled tunable proton conductivity, leading to a 200-fold improvement. These results highlight the importance of a rational linker design for functionalization.

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ConspectusPhotocatalytic energy conversion is a pivotal process for harnessing solar energy to produce chemicals and presents a sustainable alternative to fossil fuels. Key strategies to enhance photocatalytic efficiency include facilitating mass transport and reactant adsorption, improving light absorption, and promoting electron and hole separation to suppress electron-hole recombination. This Account delves into the potential advantages of electrically conductive metal-organic frameworks (EC-MOFs) in photocatalytic energy conversion and examines how manipulating electronic structures and controlling morphology and defects affect their unique properties, potentially impacting photocatalytic efficiency and selectivity. Moreover, with a proof-of-concept study of photocatalytic hydrogen peroxide production by manipulating the EC-MOF's electronic structure, we highlight the potential of the strategies outlined in this Account.EC-MOFs not only possess porosity and surface areas like conventional MOFs, but exhibit electronic conductivity through d-p conjugation between ligands and metal nodes, enabling effective charge transport. Their narrow band gaps also allow for visible light absorption, making them promising candidates for efficient photocatalysts. In EC-MOFs, the modular design of metal nodes and ligands allows fine-tuning of both the electronic structure and physical properties, including controlling the particle morphology, which is essential for optimizing band positions and improving charge transport to achieve efficient and selective photocatalytic energy conversion.Despite their potential as photocatalysts, modulating the electronic structure or controlling the morphology of EC-MOFs is nontrivial, as their fast growth kinetics make them prone to defect formation, impacting mass and charge transport. To fully leverage the photocatalytic potential of EC-MOFs, we discuss our group's efforts to manipulate their electronic structures and develop effective synthetic strategies for morphology control and defect healing. For tuning electronic structures, diversifying the combinations of metals and linkers available for EC-MOF synthesis has been explored. Next, we suggest that synthesizing ligand-based solid solutions will enable continuous tuning of the band positions, demonstrating the potential to distinguish between photocatalytic reactions with similar redox potentials. Lastly, we present incorporating a donor-acceptor system in an EC-MOF to spatially separate photogenerated carriers, which could suppress electron-hole recombination. As a synthetic strategy for morphology control, we demonstrated that electrosynthesis can modify particle morphology, enhancing electrochemical surface area, which will be beneficial for reactant adsorption. Finally, we suggest a defect healing strategy that will enhance charge transport by reducing charge traps on defects, potentially improving the photocatalytic efficiency.Our vision in this Account is to introduce EC-MOFs as an efficient platform for photocatalytic energy conversion. Although EC-MOFs are a new class of semiconductor materials and have not been extensively studied for photocatalytic energy conversion, their inherent light absorption and electron transport properties indicate significant photocatalytic potential. We envision that employing modular molecular design to control electronic structures and applying effective synthetic strategies to customize morphology and defect repair can promote charge separation, electron transfer to potential reactants, and mass transport to realize high selectivity and efficiency in EC-MOF-based photocatalysts. This effort not only lays the foundation for the rational design and synthesis of EC-MOFs, but has the potential to advance their use in photocatalytic energy conversion.

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Chiral Plasmonic nanomaterials have gradually illustrated intriguing circularly polarized light (CPL)-dependent properties in photocatalysis due to their unique chiral optical activity. However, the connection between chiral characteristics and catalytic performance of these materials in cooperative systems is rarely reported and remains a challenge task. In this work, branched AgAuPt nanoparticles induced by L/d-cysteine (Cys) with strong and perfectly symmetric circular dichroism (CD) signals are synthesized. Chiral branched AgAuPt nanoparticles firstly exhibit superior typical electrocatalytic performance. In the photoelectrocatalytic system, chiral branched AgAuPt nanoparticles demonstrate selective catalytic water splitting performance. Specifically, chiral branched AgAuPt with related CPL irradiation exhibits enhanced acidic hydrogen evolution reaction (HER) performance. Under the continuous irradiation of related CPL, the chiral catalyst generates more heat, which further increases the catalytic activity. This contribution of heat is supported by density functional theory (DFT) calculation results. The changes in chiroptical activity during this process are recorded by variable temperature CD spectra. This work provides a novel paradigm for designing chiral catalysis systems and emphasizes the profound promise of chiral plasmonic nanomaterials as chiral catalysts.

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Serial correlations within temperature time series serve as indicators of the temporal consistency of climate events. This study delves into the serial correlations embedded in global surface air temperature (SAT) data. Initially, we preprocess the SAT time series to eradicate seasonal patterns and linear trends, resulting in the SAT anomaly time series, which encapsulates the inherent variability of Earth's climate system. Employing diverse statistical techniques, we identify three distinct types of serial correlations: short-term, long-term, and nonlinear. To identify short-term correlations, we utilize the first-order autoregressive model, AR(1), revealing a global pattern that can be partially attributed to atmospheric Rossby waves in extratropical regions and the Eastern Pacific warm pool. For long-term correlations, we adopt the standard detrended fluctuation analysis, finding that the global pattern aligns with long-term climate variability, such as the El Niño-Southern Oscillation (ENSO) over the Eastern Pacific. Furthermore, we apply the horizontal visibility graph (HVG) algorithm to transform the SAT anomaly time series into complex networks. The topological parameters of these networks aptly capture the long-term correlations present in the data. Additionally, we introduce a novel topological parameter, Δσ, to detect nonlinear correlations. The statistical significance of this parameter is rigorously tested using the Monte Carlo method, simulating fractional Brownian motion and fractional Gaussian noise processes with a predefined DFA exponent to estimate confidence intervals. In conclusion, serial correlations are universal in global SAT time series and the presence of these serial correlations should be considered carefully in climate sciences.

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Ultralong room-temperature phosphorescence (RTP) and thermally activated delayed fluorescence (TADF) materials provide exciting opportunities for the rational design of persistent luminescence owing to their long-lived excitons. However, conventional rare-earth-based all-inorganic emitters involve high cost and harsh synthesis conditions, and purely organic systems may require complicated synthesis routes and tedious purification. Therefore, it is highly desirable to develop a cost-effective and easily manufacturable method for achieving color-tunable RTP-TADF with a long afterglow. Herein, we demonstrate a rational strategy to introduce different anions (Cl-, Br- and OAc- ions) into a Zn-based metal-organic scaffold, which can improve the crystal rigidity and achieve a well-balanced RTP-TADF. Both theoretical and experimental studies have demonstrated that the adjustment of different anions can effectively modulate the spin-orbit coupling (SOC) and the energy gap of singlet-triplet states (ΔEST) and then tailor the afterglow lifetime. Moreover, we prepared dye-doped metal-organic hybrid glasses with remarkable potential for the color-tunable afterglow. Therefore, this work not only provides a new horizon for modulating crystal and glass states with color/lifetime-tunable persistent luminescence, but also contributes to optical information storage and anti-counterfeiting technology.

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This research introduces a method to enhance the mechanical properties of elastomers by grafting polymer chains onto single-chain flexible nanoparticles (SCNPs) and incorporating dynamic functional groups. Drawing on developments in grafting polymers onto hard nanoparticle fillers, this method employs the distinct flexibility of SCNPs to diminish heterogeneity and enhance core size control. We use molecular dynamics (MD) simulations for a mesoscale analysis of structural properties, particularly the effects of dynamic functional group quantities and their distribution. The findings demonstrate that increased quantities of functional groups are correlated with enhanced mechanical strength and toughness, showing improved stress-strain responses and energy dissipation capabilities. Moreover, the uniformity in the distribution of these functional groups is crucial, promoting a more cohesive and stable dynamic bonding network. The insights gained from MD simulations not only advance our understanding of the microstructural control necessary for optimizing macroscopic properties, but also provide valuable guidance for the design and engineering of advanced polymer nanocomposites, thereby enhancing the material performance through strategic molecular design.

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Hydrogen peroxide (H2O2) holds significance as a vital chemical with the potential to serve as an energy carrier. Compared with the conventional anthraquinone process, photocatalytic H2O2 production has emerged as an appealing alternative because of its energy efficiency and environmental sustainability. However, the existing photocatalysts suffer from low catalytic efficiency, limited tunability of optical properties, and reliance on sacrificial agents due to high energy loss caused by inefficient charge separation. Therefore, developing catalysts with tunable optical properties and efficient charge separation is desirable. In this work, we introduce postsynthetic functionalization into an electrically conductive metal-organic framework, namely, DPT-MOF. Leveraging DPT (3,6-di(4-pyridyl)-1,2,4,5-tetrazine) as a pillar ligand, we exploited click-type chemistry to manipulate band position and charge separation efficiency, allowing for photocatalytic nonsacrificial H2O2 production. Notably, the fluorine-functionalized MOF exhibited the highest H2O2 production rate of 1676 µmol g-1 h-1 under visible light in O2-saturated water among our other samples. This high production rate is attributed to the tuned electronic structure and prolonged charge lifetime facilitated by the fluorine groups. This work highlights the effectiveness of postsynthetic methodology in tuning optical properties, opening a promising avenue for advancing the field of semiconductive MOF-based photocatalysis.

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Color-tunable room temperature phosphorescent (RTP) materials have raised wide interest due to their potential application in the fields of encryption and anti-counterfeiting. Herein, a series of CdX2-organic hybrid perovskitoids, (H-apim)CdX3 and (apim)CdX2 (denoted as CdX-apim1 and CdX-apim2, apim = 1-(3-aminopropyl)imidazole, X = Cl, Br), were synthesized using apim with both rigid and flexible groups as ligands, which exhibit naked-eye detectable RTP with different durations and colors (from cyan to red) by virtue of different halogen atoms, coordination modes and the coplanar configuration of flexible groups. Interestingly, CdCl-apim1 and CdX-apim2 both exhibit excitation wavelength-dependent RTP properties, which can be attributed to the multiple excitation of imidazole/apim, the diverse interactions with halogen atoms, and aggregated state of imidazoles. Structural analysis and theoretical calculations confirm that the aminopropyl groups in CdCl-apim1 do not participate in luminescence, while those in CdCl-apim2 are involved in luminescence including both metal/halogen to ligand charge transfer and twisted intramolecular charge transfer. Furthermore, we demonstrate that these perovskitoids can be applied in multi-step anti-counterfeiting, information encryption and smart ink fields. This work not only develops a new type of perovskitoid with full-color persistent luminescence, but also provides new insight into the effect of flexible ligands and halogen engineering on the wide-range modulation of RTP properties.

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Background: Nanopore Target Sequencing (NTS) represents a novel iteration of gene sequencing technology; however, its potential utility in the detection of infection in deceased donors has yet to be documented. The present study endeavors to assess the applicability of NTS in this domain. Methods: This retrospective study comprised a cohort of 71 patients who were under intensive care at Renmin Hospital of Wuhan University between June 2020 and January 2022. The specimens were subjected to microbiological tests utilizing NTS, culture, and other techniques, and subsequently, the diagnostic accuracy of NTS was compared with conventional methods. Results: Blood NTS exhibited a better agreement rate of 52.11% and a greater positive rate of pathogen detection than blood culture (50.70% vs. 5.63%, p < 0.001). In NTS of deceased donors, Klebsiella pneumoniae, Escherichia coli, and Acinetobacter baumannii were the most frequently found bacteria, and Candida was the most frequently found fungus. Blood NTS had a considerably better sensitivity for detecting clinical bloodstream infection than blood culture (62.50%: 7.14%, p < 0.001). These findings were supported by comparisons between blood NTS and conventional microbial detection methods (such as blood culture, glucan testing, galactomannan testing, T cell spot testing for tuberculosis infection, smear, etc.). Conclusion: The pathogen detection technology NTS has a high sensitivity and positive rate. It can more accurately and earlier detect infection in deceased donors, which could be very important for raising the donation conversion rate.

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A major challenge in managing and engineering microbial communities is determining whether and how microbial community responses to environmental alterations can be predicted and explained, especially in microorganism-driven systems. We addressed this challenge by monitoring microbial community responses to the periodic addition of the same feedstock throughout anaerobic digestion, a typical microorganism-driven system where microorganisms degrade and transform the feedstock. The immediate and delayed response consortia were assemblages of microorganisms whose abundances significantly increased on the first or third day after feedstock addition. The immediate response consortia were more predictable than the delayed response consortia and showed a reproducible and predictable order-level composition across multiple feedstock additions. These results stood in both present (16 S rRNA gene) and potentially active (16 S rRNA) microbial communities and in different feedstocks with different biodegradability and were validated by simulation modeling. Despite substantial species variability, the immediate response consortia aligned well with the reproducible CH4 production, which was attributed to the conservation of expressed functions by the response consortia throughout anaerobic digestion, based on metatranscriptomic data analyses. The high species variability might be attributed to intraspecific competition and contribute to biodiversity maintenance and functional redundancy. Our results demonstrate reproducible and predictable microbial community responses and their importance in stabilizing system functions.

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BACKGROUND: The central role of inflammatory progression in the development of Coronavirus disease 2019 (COVID-19), especially in severe cases, is indisputable. However, the role of some novel inflammatory biomarkers in the prognosis of COVID-19 remains controversial. OBJECTIVE: To assess the effect of some novel inflammatory biomarkers in the occurrence and prognosis of COVID-19. METHODS: We systematically retrieved the studies related to COVID-19 and the inflammatory biomarkers of interest. The data of each biomarker in different groups were extracted, then were categorized and pooled. The standardized mean difference was chosen as an effect size measure to compare the difference between groups. RESULTS: A total of 90 studies with 12,059 participants were included in this study. We found higher levels of endocan, PTX3, suPAR, sRAGE, galectin-3, and monocyte distribution width (MDW) in the COVID-19 positive groups compared to the COVID-19 negative groups. No significant differences for suPAR and galectin-3 were detected between the severe group and mild/moderate group of COVID-19. In addition, the deaths usually had higher levels of PTX3, sCD14-ST, suPAR, and MDW at admission compared to the survivors. Furthermore, patients with higher levels of endocan, galectin-3, sCD14-ST, suPAR, and MDW usually developed poorer comprehensive clinical prognoses. CONCLUSIONS: In summary, this meta-analysis provides the most up-to-date and comprehensive evidence for the role of the mentioned novel inflammatory biomarkers in the prognosis of COVID-19, especially in evaluating death and other poor prognoses, with most biomarkers showing a better discriminatory ability.

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A reversible CO2-responsive luminescent material was constructed by a facile hydrogen-bond self-assembly of a two-component ionic crystal. The modification of CO2 on the ionic crystal not only alternates the green afterglow, but also endows the material with inverse excitation wavelength dependence for multicolor emission.

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Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), the prime causes of morbidity and mortality in critically ill patients, are usually treated by general supportive treatments. Endoplasmic reticulum autophagy (ER-phagy) maintains cellular homeostasis by degrading damaged endoplasmic reticulum (ER) fragments and misfolded proteins. ER-phagy is crucial for maintaining ER homeostasis and improving the internal environment. ER-phagy has a particular role in some aspects, such as immunity, inflammation, cell death, pathogen infection, and collagen quality. In this review, we summarized the definition, epidemiology, and pathophysiology of ALI/ARDS and described the regulatory mechanisms and functions of ER-phagy as well as discussed the potential role of ER-phagy in ALI/ARDS from the perspectives of immunity, inflammation, apoptosis, pathogen infection, and fibrosis to provide a novel and effective target for improving the prognosis of ALI/ARDS.

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PURPOSE: Although estrogen receptors (ERs) signal pathways are involved in the pathogenesis and development of asthma, their expressions and effects remain controversial. This study aimed to investigate the expressions of ERα and ERß as well as their mechanisms in airway remodeling and mucus production in asthma. METHODS: The expressions of ERα and ERß in the airway epithelial cells of bronchial biopsies and induced sputum cells were examined by immunohistochemistry. The associations of ERs expressions with airway inflammation and remodeling were evaluated in asthmatic patients. In vitro, the regulations of ERs expressions in human bronchial epithelial cell lines were examined using western blot analysis. The epidermal growth factor (EGF)-mediated ligand-independent activation of ERα and its effect on epithelial-mesenchymal transitions (EMTs) were investigated in asthmatic epithelial cells by western blot, immunofluorescent staining, and quantitative real-time polymerase chain reaction. RESULTS: ERα and ERß were expressed on both bronchial epithelial cells and induced sputum cells, and the expressions showed no sex difference. Compared to controls, male asthmatic patients had higher levels of ERα on the bronchial epithelium, and there were cell-specific expressions of ERα and ERß in induced sputum. The expression of ERα in the airway epithelium was inversely correlated to forced expiratory volume in 1 second (FEV1) % and FEV1/forced vital capacity. Severe asthmatic patients had significantly greater levels of ERα in the airway epithelium than mild-moderate patients. ERα level was positively correlated with the thickness of the subepithelial basement membrane and airway epithelium. In vitro, co-stimulation of interleukin (IL)-4 and EGF increased the expression of ERα and promoted its nuclear translocation. EGF activated the phosphorylation of ERα via extracellular signal-regulated kinase and c-Jun N-terminal kinase pathways. ERα knockdown alleviated EGF-mediated EMTs and mucus production in airway epithelial cells of asthma. CONCLUSIONS: ERα contributes to asthmatic airway remodeling and mucus production through the EGF-mediated ligand-independent pathway.

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Ammonia is a ubiquitous potential inhibitor of anaerobic digestion processes, mainly exhibiting inhibition towards methanogenic activity. However, knowledge as to how ammonia affects the methanogens is still limited. In this study, we cultured a multitrophic methanogen, Methanosarcina barkeri DSM 800, with acetate, H2/CO2, and methanol to evaluate the influence of ammonia on different methanogenic pathways. Aceticlastic methanogenesis was more sensitive to increased ammonia concentrations than hydrogenotrophic and methylotrophic methanogenesis. Theoretical maximum NH3 tolerances of M. barkeri fed with acetate, H2/CO2, and methanol were calculated to be 39.1 ± 9.0, 104.3 ± 7.4, and 85.7 ± 1.0 mg/L, respectively. The order of the ΔG range of M. barkeri under three methanogenic pathways reflected the order of ammonia tolerance of M. barkeri. Our results provide insights into the role of the thermodynamic potential of methanogenesis on the tolerance of ammonia stress; and shed light on the mechanism of ammonia inhibition on anaerobic digestion.

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Microorganisms in anaerobic digestion (AD) are essential for wastes/pollutants treatment and energy recovery. Due to microbial enormous diversity, developing effective perspectives to understand microbial roles therein is urgent. This study conducted AD of swine manure, used an ensemble-based network analysis to distinguish interconnected, unconnected, copresence (positively interconnected) and mutual-exclusion (negatively interconnected) microorganisms within microbial communities, and explored their importance towards AD performances, using amplicon sequencing of 16S rRNA and 16S rRNA gene. Our analyses revealed greater importance of interconnected than unconnected microorganisms towards CH4 production and AD multifunctionality, which was attributed to higher niche breadth, deterministic community assembly, community stability and phylogenetic conservatism. The diversity was higher in unconnected than interconnected microorganisms, but was not linked to AD performances. Compared to copresence microorganisms, mutual-exclusion microorganisms showed greater and equal importance towards CH4 production and AD multifunctionality, which was attributed to their roles in stabilizing microbial communities. The increased feedstock biodegradability, by replacing part of manure with fructose or apple waste, hardly affected the relative importance of interconnected versus unconnected microorganisms towards CH4 production or AD multifunctionality. Our findings develop a new framework to understand microbial roles, and have important implications in targeted manipulation of critical microorganisms in waste-treatment systems.

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BACKGROUND: No study has yet systematically evaluated the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with type 2 diabetes (T2D). OBJECTIVE: We aimed to evaluate the effect of different antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. METHODS: We comprehensively retrieved the published research which examined the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. The odds ratio (OR) and its 95% confidence interval (95% CI) for clinical outcomes were calculated using the random-effects model, and meta-regression was adopted to evaluate the potential sources of heterogeneity between studies. RESULTS: A total of 54 studies were included in this study. We found that the use of metformin (OR = 0.66, 95% CI: 0.58-0.75), SGLT-2i (OR = 0.80, 95% CI: 0.73-0.88), and GLP-1ra (OR = 0.83, 95% CI: 0.70-0.98) were significantly associated with lower mortality risk in COVID-19 patients with T2D, while insulin use might unexpectedly increase the ICU admission rate (OR = 2.32, 95% CI: 1.34-4.01) and risk of death (OR = 1.52, 95% CI: 1.32-1.75). No statistically significant associations were identified for DPP-4i, SUs, AGIs, and TZDs. CONCLUSION AND RELEVANCE: We demonstrated that the usage of metformin, SGLT-2i, and GLP-1ra could significantly decrease mortality in COVID-19 patients with T2D. The heterogeneity across the studies, baseline characteristics of the included patients, shortage of dosage and the duration of antidiabetic drugs and autonomy of drug selection might limit the objectivity and accuracy of results. Further adequately powered and high-quality randomized controlled trials are warranted for conclusive findings.

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In avionics and industrial electronic systems, analog circuits are one of the most commonly used components. Intermittent faults (IFs) are a no fault found (NFF) state in analog circuits that are difficult to detect. In addition, the presence of noise may obscure critical information about the state of the circuit. Considering these challenges, this paper proposes an adaptive multiscale and dual subnet convolutional auto-encoder (AMDSCAE) to detect IFs. The proposed method can adaptively assign different attention to each scale and then fuse the multiscale information, which has better noise robustness. Then, the fault reconstruction error is amplified by the dual subnet structure to enhance the IF detection ability and find weaker faults. Considering the difficulty of obtaining fault sample labels, the proposed model requires only fault-free samples in the training process. In three typical analog filter circuit experiments, AMDSCAE has better noise immunity and can detect weaker IFs.

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Uncovering differences between crystalline and amorphous states in molecular solids would both promote the understanding of their structure-property relationships, as well as inform development of multi-functional materials based on the same compound. Herein, for the first time, we report an approach to leverage crystalline and amorphous states of a zero-dimensional metal-organic complex, which exhibited negative and positive photochromism, due to the competitive chemical routes between photocycloaddition and photogenerated radicals. Furthermore, different polymorphs lead to the on/off toggling of photo-burst movement (photosalient effect), indicating the controllable light-mechanical conversion. Three demos were further constructed to support their application in information encryption and anti-counterfeiting. This work provides the proof-of-concept of a state- and polymorph-dependent photochemical route, paving an effective way for the design of new dynamically responsive systems.