Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models.

The prediction of thermodynamic properties of carbon-based molecules based on their geometrical conformation using fluctuation and density functional theories has achieved great success in the field of energy chemistry, while the excessive computational cost provides both opportunities and challenges for the integration of machine learning. In this work, a deep learning-based quantum chemical prediction model was constructed for efficient prediction of thermodynamic properties of carbon-based molecules. We constructed a novel framework - encoding the 3D information into a large language model (LLM), which in turn generates a 2D SMILES string, while embedding a learnable encoding designed to preserve the integrity of the original 3D information, providing better structural information for the model. Additionally, we have designed an equivariant learning module to encompass representations of conformations and feature learning for conformational sampling. This framework aims to predict thermodynamic properties more accurately than learning from 2D topology alone, while providing faster computational speeds than conventional simulations. By combining machine learning and quantum chemistry, we pioneer efficient practical applications in the field of energy chemistry. Our model advances the integration of data-driven and physics-based modeling to unlock novel insights into carbon-based molecules.

Metallofullerenol alleviates alcoholic liver damage via ROS clearance under static magnetic and electric fields.

Alcoholic liver disease (ALD) is a common chronic redox disease caused by increased alcohol consumption. Abstinence is a major challenge for people with alcohol dependence, and approved drugs have limited efficacy. Therefore, this study aimed to explore a new treatment strategy for ALD using ferroferric oxide endohedral fullerenol (Fe3O4@C60(OH)n) in combination with static magnetic and electric fields (sBE). The primary hepatocytes of 8-9-week-old female BALB/c mice were used to evaluate the efficacy of the proposed combination treatment. A mouse chronic binge ethanol feeding model was established to determine the alleviatory effect of Fe3O4@C60(OH)n on liver injury under sBE exposure. Furthermore, the ability of Fe3O4@C60(OH)n to eliminate •OH was evaluated. Alcohol-induced hepatocyte and mitochondrial damage were reversed in vitro. Additionally, the combination therapy reduced liver damage, alleviated oxidative stress by improving antioxidant levels, and effectively inhibited liver lipid accumulation in animal experiments. Here, we used a combination of magnetic derivatives of fullerenol and sBE to further improve the ROS clearance rate, thereby alleviating ALD. The developed combination treatment may effectively improve alcohol-induced liver damage and maintain redox balance without apparent toxicity, thereby enhancing therapy aimed at ALD and other redox diseases.

Exploration of identifying individual tumor tissue based on probabilistic model.

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log 10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log 10(LR) values less than 0. When the defense's hypothesis took into account the possibility that the tumor samples came from the patient's relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.

AuNi bimetallic aerogel with ultra-high stability applied in smart and portable biosensing.

Glucose detection is of significant importance in providing information to the human health management. However, conventional enzymatic glucose sensors suffer from a limited long-term stability due to the losing activity of the enzymes. In this work, the AuNi bimetallic aerogel with a well-defined nanowire network is synthesized and applied as the sensing nanomaterial in the non-enzymatic glucose detection. The three-dimensional (3D) hierarchical porous structure of the AuNi bimetallic aerogel ensures the high sensitivity of the sensor (40.34 µA mM-1 cm-2). Theoretical investigation unveiled the mechanism of the boosting electrocatalytic activity of the AuNi bimetallic aerogel toward glucose. A better adhesion between the sensing nanomaterial and the screen-printing electrodes (SPEs) is obtained after the introduction of Ni. On the basis of a wide linearity in the range of 0.1-5 mM, an excellent selectivity, an outstanding long-term stability (90 days) as well as the help of the signal processing circuit and an M5stack development board, the as-prepared glucose sensor successfully realizes remote monitoring of the glucose concentration. We speculate that this work is favorable to motivating the technological innovations of the non-enzymatic glucose sensors and intelligent sensing devices.

Characterization, antioxidant activity and in vitro digestion of hawthorn pectin prepared by gradient ethanol precipitation.

Four modified hawthorn pectin fractions (MHPs), named MHP-30, MHP-50, MHP-70 and MHP-90, were obtained by ultrasonic-assisted pectin methyl esterase modification and gradient ethanol precipitation. The results indicated that all four MHPs were composed of galacturonic acid, galactose, xylose, arabinose, glucose and mannose in different proportions. With the increase of the ethanol concentration, the molecular weight, esterification degree and galacturonic acid content of MHPs all decreased, whereas the arabinose content and branching degree increased. The structural characterization from XRD, SEM, and FT-IR showed that four MHPs exhibited amorphous structure, similar functional groups, diverse surface morphologies. Besides, in vitro antioxidant assays confirmed that MHP-70 and MHP-90 exhibited stronger total antioxidant activities than MHP-30 and MHP-50. The results of simulated saliva-gastrointestinal digestion showed that the molecular weight of MHP-70 and MHP-90 remained stable, yielded small amounts of reducing sugars, and were resistant to digestion in the human upper digestive tract. Overall, MHP-70 and MHP-90 shown great potential as novel natural antioxidants, which are expected to be good carbon sources for the utilization of intestinal microorganisms.

Short-term forecasting approach of single well production based on multi-intelligent agent hybrid model.

The short-term prediction of single well production can provide direct data support for timely guiding the optimization and adjustment of oil well production parameters and studying and judging oil well production conditions. In view of the coupling effect of complex factors on the daily output of a single well, a short-term prediction method based on a multi-agent hybrid model is proposed, and a short-term prediction process of single well output is constructed. First, CEEMDAN method is used to decompose and reconstruct the original data set, and the sliding window method is used to compose the data set with the obtained components. Features of components by decomposition are described as feature vectors based on values of fuzzy entropy and autocorrelation coefficient, through which those components are divided into two groups using cluster algorithm for prediction with two sub models. Optimized online sequential extreme learning machine and the deep learning model based on encoder-decoder structure using self-attention are developed as sub models to predict the grouped data, and the final predicted production comes from the sum of prediction values by sub models. The validity of this method for short-term production prediction of single well daily oil production is verified. The statistical value of data deviation and statistical test methods are introduced as the basis for comparative evaluation, and comparative models are used as the reference model to evaluate the prediction effect of the above multi-agent hybrid model. Results indicated that the proposed hybrid model has performed better with MAE value of 0.0935, 0.0694 and 0.0593 in three cases, respectively. By comparison, the short-term prediction method of single well production based on multi-agent hybrid model has considerably improved the statistical value of prediction deviation of selected oil well data in different periods. Through statistical test, the multi-agent hybrid model is superior to the comparative models. Therefore, the short-term prediction method of single well production based on a multi-agent hybrid model can effectively optimize oilfield production parameters and study and judge oil well production conditions.

Merging total synthesis and NMR technology for deciphering the realistic structure of natural 2,6-dideoxyglycosides.

The structural identification and efficient synthesis of bioactive 2,6-dideoxyglycosides are daunting challenges. Here, we report the total synthesis and structural revision of a series of 2,6-dideoxyglycosides from folk medicinal plants Ecdysanthera rosea and Chonemorpha megacalyx, which feature pregnane steroidal aglycones bearing an 18,20-lactone and glycans consisting of 2,6-dideoxy-3-O-methyl-ß-pyranose residues, including ecdysosides A, B, and F and ecdysantheroside A. All the eight possible 2,6-dideoxy-3-O-methyl-ß-pyranoside stereoisomers (of the proposed ecdysantheroside A) have been synthesized that testify the effective gold(I)-catalyzed glycosylation methods for the synthesis of various 2-deoxy-ß-pyranosidic linkages and lays a foundation via nuclear magnetic resonance data mapping to identify these sugar units which occur promiscuously in the present and other natural glycosides. Moreover, some synthetic natural compounds and their isomers have shown promising anticancer, immunosuppressive, anti-inflammatory, and anti-Zika virus activities.

Efficient Production of 9,22-Dihydroxy-23,24-bisnorchol-4-ene-3-one from Phytosterols by Modifying Multiple Genes in Mycobacterium fortuitum.

C19 steroids and C22 steroids are vital intermediates for the synthesis of steroid drugs. Compared with C19 steroids, C22 steroids are more suitable for synthesizing progesterone and adrenocortical hormones, albeit less developed. 9,22-dihydroxy-23,24-bisnorchol-4-ene-3-one(9-OHBA), due to its substituents at positions C-9 and C-22, is a beneficial and innovative steroid derivative for synthesizing corticosteroids. We focused on the C22 pathway in Mycobacterium fortuitum ATCC 35855, aiming to develop a productive strain that produces 9-OHBA. We used a mutant strain, MFΔkstD, that knocked out kstds from Mycobacterium fortuitum ATCC 35855 named MFKD in this study as the original strain. Hsd4A and FadA5 are key enzymes in controlling the C19 metabolic pathway of steroids in Mycobacterium fortuitum ATCC 35855. After knocking out hsd4A, MFKDΔhsd4A accumulated 81.47% 9-OHBA compared with 4.13% 9-OHBA in the strain MFKD. The double mutant MFKDΔhsd4AΔfadA5 further improved the selectivity of 9-OHBA to 95.13%, and 9α-hydroxy-4-androstenedione (9-OHAD) decreased to 0.90% from 4.19%. In the end, we obtained 6.81 g/L 9-OHBA from 10 g/L phytosterols with a molar yield of 80.33%, which showed the best performance compared with formerly reported strains.

Arbuscular Mycorrhizal Fungi-Mediated Modulation of Physiological, Biochemical, and Secondary Metabolite Responses in Hemp (Cannabis sativa L.) under Salt and Drought Stress.

The increasing impact of global climate change has resulted in adversity stresses, like salt and drought, gradually becoming the main factors that limit crop growth. Hemp, which contains numerous medicinal active components and multiple bioactive functions, is widely used in the agricultural, industrial, and medical fields, hence promoting the rapid development of related industries. Arbuscular mycorrhizal fungi (AMF) can establish a symbiotic relationship with 80% of vascular plants. This symbiosis promotes host plant growth, regulates plant physiology and biochemistry, facilitates secondary metabolite synthesis, and enhances resistance to abiotic stresses. However, the effects of salt stress, drought stress, and AMF interaction in hemp are not well understood. In this study, to investigate this, we performed a study where we cultured hemp that was either inoculated or uninoculated with Funneliformis mosseae and determined changes in effective colonization rate, growth, soluble substances, photosynthesis, fluorescence, ions, and secondary metabolites by cultivating hemp under different concentrations of NaCl (0 mM, 100 mM, and 200 mM) and different soil moisture content (45%, 25%, and 15%). The results showed that salt, drought stress, or salt-drought interaction stress all inhibited colonization rate after stress, plant growth, mainly due to ion toxicity and oxidative damage. Inoculation with F. mosseae effectively alleviated plant growth inhibition under 100 mM NaCl salt stress, drought stress, and salt-drought interaction stress conditions. It also improved osmoregulation, photosynthetic properties, fluorescence properties, and ion homeostasis, and promoted the accumulation of secondary metabolites. However, under 200 mM NaCl salt stress conditions, inoculation with F. mosseae negatively affected plant physiology, biochemistry, and secondary metabolite synthesis, although it did alleviate growth inhibition. The results demonstrate that there are different effects of salt-drought interaction stress versus single stress (salt or drought stress) on plant growth physiology. In addition, we provide new insights about the positive effects of AMF on host plants under such stress conditions and the effects of AMF on plants under high salt stress.

A Compact-Sized Fully Self-Powered Wireless Flowmeter Based on Triboelectric Discharge.

Flow sensing exhibits significant potential for monitoring, controlling, and optimizing processes in industries, resource management, and environmental protection. However, achieving wireless real-time and omnidirectional sensing of gas/liquid flow on a simple, self-contained device without external power support has remained a formidable challenge. In this study, a compact-sized, fully self-powered wireless sensing flowmeter (CSWF) is introduced with a small size diameter of down to less than 50 mm, which can transmit real-time and omnidirectional wireless signals, as driven by a rotating triboelectric nanogenerator (R-TENG). The R-TENG triggers the breakdown discharge of a gas discharge tube (GDT), which enables flow rate wireless sensing through emitted electromagnetic waves. Importantly, the performance of the CSWF is not affected by the R-TENG's varied output, while the transmission distance is greater than 10 m. Real-time wireless remote monitoring of wind speed and water flow rate is successfully demonstrated. This research introduces an approach to achieve a wireless, self-powered environmental monitoring system with a diverse range of potential applications, including prolonged meteorological observations, marine environment monitoring, early warning systems for natural disasters, and remote ecosystem monitoring.

Magnetic-driven hydrogel microrobots for promoting osteosarcoma chemo-therapy with synthetic lethality strategy.

The advancements in the field of micro-robots for drug delivery systems have garnered considerable attention. In contrast to traditional drug delivery systems, which are dependent on blood circulation to reach their target, these engineered micro/nano robots possess the unique ability to navigate autonomously, thereby enabling the delivery of drugs to otherwise inaccessible regions. Precise drug delivery systems can improve the effectiveness and safety of synthetic lethality strategies, which are used for targeted therapy of solid tumors. MYC-overexpressing tumors show sensitivity to CDK1 inhibition. This study delves into the potential of Ro-3306 loaded magnetic-driven hydrogel micro-robots in the treatment of MYC-dependent osteosarcoma. Ro-3306, a specific inhibitor of CDK1, has been demonstrated to suppress tumor growth across various types of cancer. We have designed and fabricated this micro-robot, capable of delivering Ro-3306 precisely to tumor cells under the influence of a magnetic field, and evaluated its chemosensitizing effects, thereby augmenting the therapeutic efficacy and introducing a novel possibility for osteosarcoma treatment. The clinical translation of this method necessitates further investigation and validation. In summary, the Ro-3306-loaded magnetic-driven hydrogel micro-robots present a novel strategy for enhancing the chemosensitivity of MYC-dependent osteosarcoma, paving the way for new possibilities in future clinical applications.

Ogataea polymorpha as a next-generation chassis for industrial biotechnology.

Ogataea (Hansenula) polymorpha is a nonconventional yeast with some unique characteristics, including fast growth, thermostability, and broad substrate spectrum. Other than common applications for protein production, O. polymorpha is attracting interest for chemical and protein production from methanol; a promising feedstock for the next-generation biomanufacturing due to its abundant sources and excellent characteristics. Benefiting from the development of synthetic biology, it has been engineered to produce value-added chemicals by extensively rewiring cellular metabolism. This Review discusses recently developed synthetic biology tools of O. polymorpha. The advances of chemicals production and systems biology were reviewed comprehensively. Finally, we look ahead to the developments of biomanufacturing in O. polymorpha to make an overall understanding of this chassis for academia and industry.

Creation of Porous, Perfusable Microtubular Networks for Improved Cell Viability in Volumetric Hydrogels.

The creation of large, volumetric tissue-engineered constructs has long been hindered due to the lack of effective vascularization strategies. Recently, 3D printing has emerged as a viable approach to creating vascular structures; however, its application is limited. Here, we present a simple and controllable technique to produce porous, free-standing, perfusable tubular networks from sacrificial templates of polyelectrolyte complex and coatings of salt-containing citrate-based elastomer poly(1,8-octanediol-co-citrate) (POC). As demonstrated, fully perfusable and interconnected POC tubular networks with channel diameters ranging from 100 to 400 µm were created. Incorporating NaCl particulates into the POC coating enabled the formation of micropores (∼19 µm in diameter) in the tubular wall upon particulate leaching to increase the cross-wall fluid transport. Casting and cross-linking gelatin methacrylate (GelMA) suspended with human osteoblasts over the free-standing porous POC tubular networks led to the fabrication of 3D cell-encapsulated constructs. Compared to the constructs without POC tubular networks, those with either solid or porous wall tubular networks exhibited a significant increase in cell viability and proliferation along with healthy cell morphology, particularly those with porous networks. Taken together, the sacrificial template-assisted approach is effective to fabricate tubular networks with controllable channel diameter and patency, which can be easily incorporated into cell-encapsulated hydrogels or used as tissue-engineering scaffolds to improve cell viability.

Artificial Heterointerfaces with Regulated Charge Distribution of Ni Active Sites for Urea Oxidation Reaction.

In contrast to the thermodynamically unfavorable anodic oxygen evolution reaction, the electrocatalytic urea oxidation reaction (UOR) presents a more favorable thermodynamic potential. However, the practical application of UOR has been hindered by sluggish kinetics. In this study, hierarchical porous nanosheet arrays featuring abundant Ni-WO3 heterointerfaces on nickel foam (Ni-WO3/NF) is introduced as a monolith electrode, demonstrating exceptional activity and stability toward UOR. The Ni-WO3/NF catalyst exhibits unprecedentedly rapid UOR kinetics (200 mA cm-2 at 1.384 V vs. RHE) and a high turnover frequency (0.456 s-1), surpassing most previously reported Ni-based catalysts, with negligible activity decay observed during a durability test lasting 150 h. Ex situ X-ray photoelectron spectroscopy and density functional theory calculations elucidate that the WO3 interface significantly modulates the local charge distribution of Ni species, facilitating the generation of Ni3+ with optimal affinity for interacting with urea molecules and CO2 intermediates at heterointerfaces during UOR. This mechanism accelerates the interfacial electrocatalytic kinetics. Additionally, in situ Fourier transform infrared spectroscopy provides deep insights into the substantial contribution of interfacial Ni-WO3 sites to UOR electrocatalysis, unraveling the underlying molecular-level mechanisms. Finally, the study explores the application of a direct urea fuel cell to inspire future practical implementations.

Smad4 Loss in the Mouse Intestinal Epithelium Alleviates the Pathological Fibrotic Response to Injury in the Colon.

Mucosal healing is associated with better clinical outcomes in patients with inflammatory bowel diseases (IBDs). Unresolved injury and inflammation, on the other hand, increases pathological fibrosis and the predisposition to cancer. Loss of Smad4, a tumor suppressor, is known to increase colitis-associated cancer in mouse models of chronic IBD. Since common biological processes are involved in both injury repair and tumor growth, we sought to investigate the effect of Smad4 loss on the response to epithelial injury. To this end, Smad4 was knocked out specifically in the intestinal epithelium and transcriptomic and morphological changes compared between wild type mice and Smad4 knock out mice after DSS-induced injury. We find that Smad4 loss alleviates pathological fibrosis and enhances mucosal repair. The transcriptomic changes specific to epithelium indicate molecular changes that affect epithelial extracellular matrix (ECM) and promote enhanced mucosal repair. These findings suggest that the biological processes that promote wound healing alleviate the pathological fibrotic response to DSS. Therefore, these mucosal repair processes could be exploited to develop therapies that promote normal wound healing and prevent fibrosis. NEW AND NOTEWORTHY: We show that transcriptomic changes due to Smad4 loss in the colonic epithelium alleviates the pathological fibrotic response to DSS in an IBD mouse model of acute inflammation. Most notably, we find that collagen deposition in the epithelial ECM, as opposed to that in the lamina propria, correlates with epithelial changes that enhance wound healing. This is the first report on a mouse model providing alleviated fibrotic response in a DSS-IBD mouse model in vivo .

The Neglected Role of Asphaltene in the Synthesis of Mesophase Pitch.

This study investigates the synthesis of mesophase pitch using low-cost fluid catalytic cracking (FCC) slurry and waste fluid asphaltene (WFA) as raw materials through the co-carbonization method. The resulting mesophase pitch product and its formation mechanism were thoroughly analyzed. Various characterization techniques, including polarizing microscopy, softening point measurement, Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), were employed to characterize and analyze the properties and structure of the mesophase pitch. The experimental results demonstrate that the optimal optical texture of the mesophase product is achieved under specific reaction conditions, including a temperature of 420 °C, pressure of 1 MPa, reaction time of 6 h, and the addition of 2% asphaltene. It was observed that a small amount of asphaltene contributes to the formation of mesophase pitch spheres, facilitating the development of the mesophase. However, excessive content of asphaltene may cover the surface of the mesophase spheres, impeding the contact between them and consequently compromising the optical texture of the mesophase pitch product. Furthermore, the inclusion of asphaltene promotes polymerization reactions in the system, leading to an increase in the average molecular weight of the mesophase pitch. Notably, when the amount of asphaltene added is 2%, the mesophase pitch demonstrates the lowest ID/IG value, indicating superior molecular orientation and larger graphite-like microcrystals. Additionally, researchers found that at this asphaltene concentration, the mesophase pitch exhibits the highest degree of order, as evidenced by the maximum diffraction angle (2θ) and stacking height (Lc) values, and the minimum d002 value. Moreover, the addition of asphaltene enhances the yield and aromaticity of the mesophase pitch and significantly improves the thermal stability of the resulting product.

Hierarchical Self-Assembly of Multidimensional Functional Materials from Sequence-Defined Peptoids.

Hierarchical self-assembly represents a powerful strategy for the fabrication of functional materials across various length scales. However, achieving precise formation of functional hierarchical assemblies remains a significant challenge and requires a profound understanding of molecular assembly interactions. In this study, we present a molecular-level understanding of the hierarchical assembly of sequence-defined peptoids into multidimensional functional materials, including twisted nanotube bundles serving as a highly efficient artificial light harvesting system. By employing synchrotron-based powder X-ray diffraction and analyzing single crystal structures of model compounds, we elucidated the molecular packing and mechanisms underlying the assembly of peptoids into multidimensional nanostructures. Our findings demonstrate that incorporating aromatic functional groups, such as tetraphenyl ethylene (TPE), at the termini of assembling peptoid sequences promotes the formation of twisted bundles of nanotubes and nanosheets, thus enabling the creation of a highly efficient artificial light harvesting system. This research exemplifies the potential of leveraging sequence-defined synthetic polymers to translate microscopic molecular structures into macroscopic assemblies. It holds promise for the development of functional materials with precisely controlled hierarchical structures and designed functions.

Association of pretreatment neutrophil-to-lymphocyte ratio with clinical outcomes in cancer immunotherapy: An evidence synthesis from 30 meta-analyses.

BACKGROUND: The Neutrophil-to-lymphocyte ratio (NLR) holds relevance in cancer immunotherapy outcomes, yet its validation remains limited. Thus, we conducted an umbrella review to comprehensively assess the association between pretreatment NLR and immunotherapy outcomes, along with evaluating their credibility and strength. METHODS: Electronic databases, including PubMed, Web of Science, Embase, Scopus, and Cochrane, were systematically searched for eligible systematic reviews and meta-analyses. Quality assessment and evidence grading utilized AMSTAR, GRADE, and additional classification criteria, following PRISMA and PRIOR guidelines. RESULTS: Thirty unique meta-analyses were included, with 24 associations (80%) exhibiting statistical significance. Notably, associations between pretreatment NLR and the prognosis of renal cell carcinoma, hepatocellular carcinoma, melanoma, and non-small cell lung cancer garnered highly suggestive or convincing evidence grading. CONCLUSIONS: Elevated pretreatment NLR correlates with poor outcomes in cancer immunotherapy, suggesting its potential as a biomarker for identifying appropriate treatment populations and predicting clinical outcomes. Nevertheless, further validation through prospective cohort studies is warranted.