Gas-Liquid Interface Route to Hybrid Copper Bromine Perovskite Single-Crystal Membrane with Dielectric Transitions and Ferromagnetic Exchanges.

Single-crystal membranes (SCMs) show great promise in the fields of sensors, light-emitting diodes, and photodetection. However, the growth of a large-area single-crystal membranes is challenging. We report a new organic-inorganic SCMs [HCMA]2CuBr4 (HCMA = cyclohexanemethylamine) crystallized at the gas-liquid interface. It also has low-temperature ferromagnetic order, high-temperature dielectric anomalies, and narrow band gap indirect semiconductor properties. Specifically, the reversible phase transition of the compound occurs at 350/341 K on cooling/heating and exhibits dielectric anomalies and stable switching performance near the phase transition temperature. The ferromagnetic exchange interaction in the inorganic octahedra and the organic layer enables ferromagnetic ordering at low-temperature 10 K. Finally, the single crystal exhibits an indirect semiconducting property with a narrow band gap of 0.99 eV. Such rich multichannel physical properties make it a potential application in photodetection, information storage and sensors.

A new paradigm for smart packaging: A dual-channel freshness monitoring platform based on aerogels of sodium alginate-anthocyanin complex with high colorimetric sensitivity and stability.

Global seafood consumption is estimated at 156 million tons annually, with an economic loss of >25 billion euros annually due to marine fish spoilage. In contrast to traditional smart packaging which can only roughly estimate food freshness, an intelligent platform integrating machine learning and smart aerogel can accurately predict remaining shelf life in food products, reducing economic losses and food waste. In this study, we prepared aerogels based on anthocyanin complexes that exhibited excellent environmental responsiveness, high porosity, high color-rendering properties, high biocompatibility, high stability, and irreversibility. The aerogel showed excellent indication properties for rainbow trout and proved suitable for fish storage environments. Among the four machine learning models, the radial basis function neural network and backpropagation network optimized by genetic algorithm demonstrated excellent monitoring performance. Also, the two-channel dataset provided more comprehensive information and superior descriptive capability. The three-layer structure of the monitoring platform provided a new paradigm for intelligent and sophisticated food packaging. The results of the study might be of great significance to the food industry and sustainable development.

Distinct Patterns of SARS-CoV-2 BA.2.87.1 and JN.1 Variants in Immune Evasion, Antigenicity and Cell-Cell Fusion.

The rapid evolution of SARS-CoV-2 variants presents a constant challenge to the global vaccination effort. In this study, we conducted a comprehensive investigation into two newly emerged variants, BA.2.87.1 and JN.1, focusing on their neutralization resistance, infectivity, antigenicity, cell-cell fusion, and spike processing. Neutralizing antibody (nAb) titers were assessed in diverse cohorts, including individuals who received a bivalent mRNA vaccine booster, patients infected during the BA.2.86/JN.1-wave, and hamsters vaccinated with XBB.1.5-monovalent vaccine. We found that BA.2.87.1 shows much less nAb escape from WT-BA.4/5 bivalent mRNA vaccination and JN.1-wave breakthrough infection sera compared to JN.1 and XBB.1.5. Interestingly. BA.2.87.1 is more resistant to neutralization by XBB.15-monovalent-vaccinated hamster sera than BA.2.86/JN.1 and XBB.1.5, but efficiently neutralized by a class III monoclonal antibody S309, which largely fails to neutralize BA.2.86/JN.1. Importantly, BA.2.87.1 exhibits higher levels of infectivity, cell-cell fusion activity, and furin cleavage efficiency than BA.2.86/JN.1. Antigenically, we found that BA.2.87.1 is closer to the ancestral BA.2 compared to other recently emerged Omicron subvariants including BA.2.86/JN.1 and XBB.1.5. Altogether, these results highlight immune escape properties as well as biology of new variants and underscore the importance of continuous surveillance and informed decision-making in the development of effective vaccines.

Distinct patterns of SARS-CoV-2 BA.2.87.1 and JN.1 variants in immune evasion, antigenicity, and cell-cell fusion.

The rapid evolution of SARS-CoV-2 variants presents a constant challenge to the global vaccination effort. In this study, we conducted a comprehensive investigation into two newly emerged variants, BA.2.87.1 and JN.1, focusing on their neutralization resistance, infectivity, antigenicity, cell-cell fusion, and spike processing. Neutralizing antibody (nAb) titers were assessed in diverse cohorts, including individuals who received a bivalent mRNA vaccine booster, patients infected during the BA.2.86/JN.1-wave, and hamsters vaccinated with XBB.1.5-monovalent vaccine. We found that BA.2.87.1 shows much less nAb escape from WT-BA.4/5 bivalent mRNA vaccination and JN.1-wave breakthrough infection sera compared to JN.1 and XBB.1.5. Interestingly, BA.2.87.1 is more resistant to neutralization by XBB.1.5-monovalent-vaccinated hamster sera than BA.2.86/JN.1 and XBB.1.5, but efficiently neutralized by a class III monoclonal antibody S309, which largely fails to neutralize BA.2.86/JN.1. Importantly, BA.2.87.1 exhibits higher levels of infectivity, cell-cell fusion activity, and furin cleavage efficiency than BA.2.86/JN.1. Antigenically, we found that BA.2.87.1 is closer to the ancestral BA.2 compared to other recently emerged Omicron subvariants including BA.2.86/JN.1 and XBB.1.5. Altogether, these results highlight immune escape properties as well as biology of new variants and underscore the importance of continuous surveillance and informed decision-making in the development of effective vaccines. IMPORTANCE: This study investigates the recently emerged SARS-CoV-2 variants, BA.2.87.1 and JN.1, in comparison to earlier variants and the parental D614G. Varied infectivity and cell-cell fusion activity among these variants suggest potential disparities in their ability to infect target cells and possibly pathogenesis. BA.2.87.1 exhibits lower nAb escape from bivalent mRNA vaccinee and BA.2.86/JN.1-infected sera than JN.1 but is relatively resistance to XBB.1.5-vaccinated hamster sera, revealing distinct properties in immune reason and underscoring the significance of continuing surveillance of variants and reformulation of vaccines. Antigenic differences between BA.2.87.1 and other earlier variants yield critical information not only for antibody evasion but also for viral evolution. In conclusion, this study furnishes timely insights into the spike biology and immune escape of the emerging variants BA.2.87.1 and JN.1, thus guiding effective vaccine development and informing public health interventions.

Rare-Earth Metal-Organic Framework with Nonplanar Porphyrin Groups for High-Efficiency Photocatalysis.

Nonplanar porphyrins play crucial roles in many biological processes and chemical reactions as catalysts. However, the preparation of artificial nonplanar porphyrins suffers from complicated organic syntheses. Herein, we present a new rare-earth porphyrinic metal-organic framework (RE-PMOF), BUT-233, which is a three-dimensional (3D) framework structure with the flu topology consisting of 4-connected BBCPPP-Ph ligands H4BBCPPP-Ph = 5',5⁗-(10,20-diphenylporphyrin-5,15-diyl)bis([1,1':3',1″-terphenyl]-4,4'' dicarboxylic acid) and 8-connected Eu6 clusters. Noteworthily, the porphyrin cores of the BBCPPP-Ph ligands in BUT-233 are nonplanar with a ruffle-like conformation. In contrast, the porphyrin core in the free ligand H4BBCPPP-Ph is in a nearly ideally planar conformation, as confirmed by its single-crystal structure. BUT-233 is microporous with 6-8 Špores and a Brunauer-Emmett-Teller (BET) surface area of 649 m2/g, as well as high stability in common solvents. The MOF was used as a photocatalyst for the oxidation degradation of a chemical warfare agent model molecule CEES (CEES = 2-chloroethyl ethyl sulfide) under the light-emitting diode (LED) irradiation and an O2 atmosphere at room temperature. CEES was almost completely converted into its nontoxic light-oxidized product CEESO (CEESO = 2-chloroethyl ethyl sulfoxide) in only 5 min with t1/2 = 2 min (t1/2: half-life). Moreover, the toxic deep-oxidized product 2-chloroethyl ethyl sulfone (CEESO2) was not detected. The catalytic activity of BUT-233 was high in comparison with those of some previously reported MOF catalysts. The results of photo/electrochemical property studies suggested that the high catalytic activity of BUT-233 was benefited from the presence of nonplanar porphyrin rings on its pore surface.

A dual-mode fluorometric/colorimetric sensor for sulfadimethoxine detection based on Prussian blue nanoparticles and carbon dots.

A dual-mode (colorimetric/fluorescence) nanoenzyme-linked immunosorbent assay (NLISA) was developed based on Au-Cu nanocubes generating Prussian blue nanoparticles (PBNPs). It is expected that this method can be used to detect the residues of sulfonamides in the field, and solve the problem of long analysis time and high cost of the traditional method. Sulfadimethoxine (SDM) was selected as the proof-of-concept target analyte. The Au-Cu nanocubes were linked to the aptamer by amide interaction, and the Au-Cu nanocubes, SDM and antibody were immobilized on a 96-well plate using the sandwich method. The assay generates PBNPs by oxidising the Cu shells on the Au-Cu nanocubes in the presence of hydrochloric acid, Fe3+ and K3[Fe (CN)6]. In this process, the copper shell undergoes oxidation to Cu2+ and subsequently Cu2 + further quenches the fluorescence of the carbon point. PBNPs exhibit peroxidase-like activity, oxidising 3,3',5,5'-tetramethylbenzidine (TMB) to OX-TMB in the presence of H2O2, which alters the colorimetric signal. The dual-mode signals are directly proportional to the sulfadimethoxine concentration within the range 10- 3~10- 7 mg/mL. The limit of detection (LOD) of the assay is 0.023 ng/mL and 0.071 ng/mL for the fluorescent signal and the colorimetric signal, respectively. Moreover, the assay was successfully applied to determine sulfadimethoxine in silver carp, shrimp, and lamb samples with satisfactory results.

Effect of starch and peanut oil on physicochemical and gel properties of myofibrillar protein: Amylose content and addition form.

Starch and peanut oil (PO) were widely used to improve the gel properties of surimi, however, the impact mechanism of addition forms on the denaturation and aggregation behavior of myofibrillar protein (MP) is not clear. Therefore, the effect of starch, PO, starch/PO mixture, and starch-based emulsion on the physicochemical and gel properties of MP was investigated. The results showed that amylose could accelerate the aggregation of MP, while amylopectin was conducive to the improvement of gel properties. The addition of PO, starch/PO mixture, or starch-based emulsion increased the turbidity, solubility, sulfhydryl content of MP, and improved the gel strength, whiteness, and texture of MP gel. However, compared with starch/PO mixture group, the gel strength of MP with waxy, normal and high amylose corn starch-based emulsion increased by 22.68 %, 10.27 %, and 32.89 %, respectively. The MP containing emulsion had higher storage modulus than MP with starch/PO mixture under the same amylose content. CLSM results indicated that the oil droplets aggregated in PO or starch/PO mixture group, while emulsified oil droplets filled the protein gel network more homogeneously. Therefore, the addition of starch and PO in the form of emulsion could effectively play the filling role to improve the gel properties of MP.

Development of machine learning-based shelf-life prediction models for multiple marine fish species and construction of a real-time prediction platform.

At least 10 million tons of seafood products are spoiled or damaged during transportation or storage every year worldwide. Monitoring the freshness of seafood in real time has become especially important. In this study, four machine learning algorithms were used for the first time to develop a multi-objective model that can simultaneously predict the shelf-life of five marine fish species at multiple storage temperatures using 14 features such as species, temperature, total viable count, K-value, total volatile basic­nitrogen, sensory and E-nose-GC-Ms/Ms. as inputs. Among them, the radial basis function model performed the best, and the absolute errors of all test samples were <0.5. With the optimal model as the base layer, a real-time prediction platform was developed to meet the needs of practical applications. This study successfully realized multi-objective real-time prediction with accurate prediction results, providing scientific basis and technical support for food safety and quality.

Study on the interaction mechanism between (-)-epigallocatechin-3-gallate and myoglobin: Multi-spectroscopies and molecular simulation.

(-)-Epigallocatechin-3-gallate (EGCG) is remarkably efficacious in inhibiting the browning of red meat. We therefore propose a hypothesis that EGCG forms complexes with myoglobin, thereby stabilizing its structure and thus preventing browning. This study investigated the interaction mechanism between EGCG and myoglobin. EGCG induced static quenching of myoglobin. Noncovalent forces, including hydrogen bonds and van der Waals, primarily governing the interactions between myoglobin and EGCG. The interactions primarily disrupted myoglobin's secondary structure, thus significantly reducing surface hydrophobicity by 53% (P < 0.05). The modification augmented the solubility and thermal stability of myoglobin. The radius of gyration (Rg) value fluctuated between 1.47 and 1.54 nm, and the hydroxyl groups in EGCG formed an average of 2.93 hydrogen bonds with myoglobin. Our findings elucidated the formation of stable myoglobin-EGCG complexes and the myoglobin-EGCG interaction, thus confirming our initial hypothesis.

Evaluation of Open-Source Large Language Models for Metal-Organic Frameworks Research.

Along with the development of machine learning, deep learning, and large language models (LLMs) such as GPT-4 (GPT: Generative Pre-Trained Transformer), artificial intelligence (AI) tools have been playing an increasingly important role in chemical and material research to facilitate the material screening and design. Despite the exciting progress of GPT-4 based AI research assistance, open-source LLMs have not gained much attention from the scientific community. This work primarily focused on metal-organic frameworks (MOFs) as a subdomain of chemistry and evaluated six top-rated open-source LLMs with a comprehensive set of tasks including MOFs knowledge, basic chemistry knowledge, in-depth chemistry knowledge, knowledge extraction, database reading, predicting material property, experiment design, computational scripts generation, guiding experiment, data analysis, and paper polishing, which covers the basic units of MOFs research. In general, these LLMs were capable of most of the tasks. Especially, Llama2-7B and ChatGLM2-6B were found to perform particularly well with moderate computational resources. Additionally, the performance of different parameter versions of the same model was compared, which revealed the superior performance of higher parameter versions.

Tissue-resident memory T cell signatures from single-cell analysis associated with better melanoma prognosis.

Tissue-resident memory T cells (TRM) are a specialized T cell population residing in peripheral tissues. The presence and potential impact of TRM in the tumor immune microenvironment (TIME) remain to be elucidated. Here, we systematically investigated the relationship between TRM and melanoma TIME based on multiple clinical single-cell RNA-seq datasets and developed signatures indicative of TRM infiltration. TRM infiltration is associated with longer overall survival and abundance of T cells, NK cells, M1 macrophages, and memory B cells in the TIME. A 22-gene TRM-derived risk score was further developed to effectively classify patients into low- and high-risk categories, distinguishing overall survival and immune activation, particularly in T cell-mediated responses. Altogether, our analysis suggests that TRM abundance is associated with melanoma TIME activation and patient survival, and the TRM-based machine learning model can potentially predict prognosis in melanoma patients.

Cryoprotective effect of soluble soybean polysaccharides and enzymatic hydrolysates on the myofibrillar protein of Nemipterus virgatus surimi.

Cryoprotective effect and potential mechanism of soluble soybean polysaccharides (SSPS) and enzymatic hydrolysates on surimi was investigated. After hydrolysis, the molecular weight of SSPS significantly decreased, and the hydrolysates prepared by endo-polygalacturonase (EPG-SSPS) was the lowest (154 kDa). Infrared spectrum analysis revealed that enzymatic hydrolysis didn't alter the functional groups of SSPS, but it did augment the exposure to hydroxyl groups. Surimi containing 5 % EPG-SSPS had the lowest freezable water after 20 days of frozen storage. Furthermore, the 5 % EPG-SSPS group manifested the highest metrics in total sulfhydryl (8.0 × 10-5 mol/g), active sulfhydryl content (6.7 × 10-5 mol/g), Ca2+-ATPase activity, and exhibited the lowest level in carbonyl content, surface hydrophobicity (153 µg). Notably, the 5 % EPG-SSPS maintained the stability of protein structure. Conclusively, SSPS enzymatic hydrolysate using endo-polygalacturonase imparted superior cryoprotective effect on the myofibrillar protein of surimi, and the mechanism might be a decrease in molecular weight and exposure of hydroxyl groups.

Neuronal ablation of GHSR mitigates diet-induced depression and memory impairment via AMPK-autophagy signaling-mediated inflammation.

Obesity is associated with chronic inflammation in the central nervous system (CNS), and neuroinflammation has been shown to have detrimental effects on mood and cognition. The growth hormone secretagogue receptor (GHSR), the biologically relevant receptor of the orexigenic hormone ghrelin, is primarily expressed in the brain. Our previous study showed that neuronal GHSR deletion prevents high-fat diet-induced obesity (DIO). Here, we investigated the effect of neuronal GHSR deletion on emotional and cognitive functions in DIO. The neuron-specific GHSR-deficient mice exhibited reduced depression and improved spatial memory compared to littermate controls under DIO. We further examined the cortex and hippocampus, the major regions regulating cognitive and emotional behaviors, and found that the neuronal deletion of GHSR reduced DIO-induced neuroinflammation by suppressing proinflammatory chemokines/cytokines and decreasing microglial activation. Furthermore, our data showed that neuronal GHSR deletion suppresses neuroinflammation by downregulating AMPK-autophagy signaling in neurons. In conclusion, our data reveal that neuronal GHSR inhibition protects against DIO-induced depressive-like behavior and spatial cognitive dysfunction, at least in part, through AMPK-autophagy signaling-mediated neuroinflammation.

Microplastics in three types of human arteries detected by pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS).

Microplastics are ubiquitous in the environment. Human body can be exposed to microplastics through inhalation and ingestion and some microplastics can enter the blood and accumulate in various tissues and organs throughout the body. Animal experiments have suggested that microplastics may promote atherosclerosis. However, data on microplastics in human arteries and clinical evidence supporting a link between microplastics and atherosclerosis are currently lacking. Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) was used in this study to detect microplastics in three types of human arteries: coronary and carotid arteries with atherosclerotic plaques, as well as the aorta without plaques. Microplastics were detected in all 17 arterial samples, with an average concentration of 118.66 ± 53.87 µg/g tissue. Four types of microplastics were identified: polyethylene terephthalate (PET, 73.70%), polyamide-66 (PA-66, 15.54%), polyvinyl chloride (PVC, 9.69%), and polyethylene (PE, 1.07%). Most importantly, the concentration of microplastics in arteries containing atherosclerotic plaques, both coronary arteries (156.50 ± 42.14 vs. 76.26 ± 14.86 µg/g tissue, P = 0.039), and carotid arteries (133.37 ± 60.52 vs. 76.26 ± 14.86 µg/g tissue, P = 0.015), was significantly higher than that in aortas which did not contain atherosclerotic plaques, suggesting that microplastics might be associated with atherosclerosis in humans. This study provides valuable data for further hazard assessments of microplastics on human cardiovascular health.

Enhancing prognostic power in multiple myeloma using a plasma cell signature derived from single-cell RNA sequencing.

Multiple myeloma (MM) is a heterogenous plasma cell malignancy, for which the established prognostic models exhibit limitations in capturing the full spectrum of outcome variability. Leveraging single-cell RNA-sequencing data, we developed a novel plasma cell gene signature. We evaluated and validated the associations of the resulting plasma cell malignancy (PBM) score with disease state, progression and clinical outcomes using data from five independent myeloma studies consisting of 2115 samples (1978 MM, 65 monoclonal gammopathy of undetermined significance, 35 smoldering MM, and 37 healthy controls). Overall, a higher PBM score was significantly associated with a more advanced stage within the spectrum of plasma cell dyscrasias (all p < 0.05) and a shorter overall survival in MM (hazard ratio, HR = 1.72; p < 0.001). Notably, the prognostic effect of the PBM score was independent of the International Staging System (ISS) and Revised ISS (R-ISS). The downstream analysis further linked higher PBM scores with the presence of cytogenetic abnormalities, TP53 mutations, and compositional changes in the myeloma tumor immune microenvironment. Our integrated analyses suggest the PBM score may provide an opportunity for refining risk stratification and guide decisions on therapeutic approaches to MM.

Enabling C2 H2 /CO2 Separation Under Humid Conditions with a Methylated Copper MOF.

As a unique subclass of metal-organic frameworks (MOFs), MOFs with open metal site (OMS) are demonstrated efficient gas separation performance through pi complexation with unsaturated hydrocarbons. However, their practical application faces the challenge of humidity that causes structure degradation and completive binding at the OMS. In this work, the effect of linker methylation of a copper MOF (BUT-155) on the C2 H2 /CO2 separation performance under humid condition is evaluated. The water adsorption isotherm, adsorption kinetics, and breakthrough under dry and humid conditions are performed. The BUT-155 with methylated linker exhibits lower water uptake and adsorption kinetics under humid condition (RH = 20%), in comparison with HKUST-1. Therefore, the C2 H2 /CO2 separation performance of BUT-155 is much less affected by water, especially under higher gas flow rate. Moreover, the dynamic C2 H2 /CO2 separation performance of BUT-155 can maintain five breakthrough cycles under humid conditions (RH = 20% and RH = 80%) without obvious performance degradation.

Interior and Exterior Surface Modification of Zr-Based Metal-Organic Frameworks for Trace Benzene Removal.

The emission of volatile organic compounds (VOCs) significantly contributes to air pollution and poses a serious threat to human health. Benzene, one of the most toxic VOCs, is difficult for the human body to metabolize and is classified as a Group 1 carcinogen. The development of efficient adsorbents for removing trace amounts of benzene from ambient air is thus of great importance. In this work, we studied the benzene adsorption properties of four Zr-based metal-organic frameworks (Zr-MOFs) through static volumetric and dynamic breakthrough experiments. Two previously reported Zr-MOFs, BUT-12 and STA-26, were prepared with a tritopic carboxylic acid ligand (H3L1) functionalized with three methyl groups, and STA-26 is a 2-fold interpenetrated network of BUT-12. Two new isoreticular Zr-MOFs, BUT-12-Et and STA-26-Et, were synthesized using a similar ligand, H3L2, where the methyl groups are replaced with ethyl groups. There are mesopores in BUT-12 and BUT-12-Et and micropores in STA-26 and STA-26-Et. The four Zr-MOFs all showed high stability in liquid water and acidic aqueous solutions. The microporous STA-26 and STA-26-Et showed much higher benzene uptakes than mesoporous BUT-12 and BUT-12-Et at room temperature under low pressures. Particularly, the benzene adsorption capacity of STA-26-Et was high up to 2.21 mmol/g at P/P0 = 0.001 (P0 = 12.78 kPa), higher than those of the other three Zr-MOFs and most reported solid adsorbents. Breakthrough experiments confirmed that STA-26-Et could effectively capture trace benzene (10 ppm) from dry air; however, its benzene capture capacity was reduced by 90% under humid conditions (RH = 50%). Coating of the crystals of STA-26-Et with polydimethylsiloxane (PDMS) increased the hydrophobicity of the exterior MOF surfaces, leading to a more than 2-fold improvement in its benzene capture capacity in the breakthrough experiment under humid condition. PDMS coating of STA-26-Et likely slowed down the water adsorption process, and thus, the adsorbent afforded more efficient capture of benzene. This work demonstrates that modifying both the interior and exterior surfaces of MOFs can effectively enhance their performance in capturing trace benzene from ambient air, even under humid conditions. This finding is meaningful for the development of new adsorbents for effective air purification applications.

Artificial intelligence-powered discovery of small molecules inhibiting CTLA-4 in cancer.

BACKGROUND/OBJECTIVES: Checkpoint inhibitors, which generate durable responses in many cancer patients, have revolutionized cancer immunotherapy. However, their therapeutic efficacy is limited, and immune-related adverse events are severe, especially for monoclonal antibody treatment directed against cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), which plays a pivotal role in preventing autoimmunity and fostering anticancer immunity by interacting with the B7 proteins CD80 and CD86. Small molecules impairing the CTLA-4/CD80 interaction have been developed; however, they directly target CD80, not CTLA-4. SUBJECTS/METHODS: In this study, we performed artificial intelligence (AI)-powered virtual screening of approximately ten million compounds to identify those targeting CTLA-4. We validated the hits molecules with biochemical, biophysical, immunological, and experimental animal assays. RESULTS: The primary hits obtained from the virtual screening were successfully validated in vitro and in vivo. We then optimized lead compounds and obtained inhibitors (inhibitory concentration, 1 micromole) that disrupted the CTLA-4/CD80 interaction without degrading CTLA-4. CONCLUSIONS: Several compounds inhibited tumor development prophylactically and therapeutically in syngeneic and CTLA-4-humanized mice. Our findings support using AI-based frameworks to design small molecules targeting immune checkpoints for cancer therapy.