Machine learning of spectra-property relationship for imperfect and small chemistry data.

Machine learning (ML) is causing profound changes to chemical research through its powerful statistical and mathematical methodological capabilities. However, the nature of chemistry experiments often sets very high hurdles to collect high-quality data that are deficiency free, contradicting the need of ML to learn from big data. Even worse, the black-box nature of most ML methods requires more abundant data to ensure good transferability. Herein, we combine physics-based spectral descriptors with a symbolic regression method to establish interpretable spectra-property relationship. Using the machine-learned mathematical formulas, we have predicted the adsorption energy and charge transfer of the CO-adsorbed Cu-based MOF systems from their infrared and Raman spectra. The explicit prediction models are robust, allowing them to be transferrable to small and low-quality dataset containing partial errors. Surprisingly, they can be used to identify and clean error data, which are common data scenarios in real experiments. Such robust learning protocol will significantly enhance the applicability of machine-learned spectroscopy for chemical science.

AFF4 regulates cellular adipogenic differentiation via targeting autophagy.

Transcriptional elongation is a universal and critical step during gene expression. The super elongation complex (SEC) regulates the rapid transcriptional induction by mobilizing paused RNA polymerase II (Pol II). Dysregulation of SEC is closely associated with human diseases. However, the physiological role of SEC during development and homeostasis remains largely unexplored. Here we studied the function of SEC in adipogenesis by manipulating an essential scaffold protein AF4/FMR2 family member 4 (AFF4), which assembles and stabilizes SEC. Knockdown of AFF4 in human mesenchymal stem cells (hMSCs) and mouse 3T3-L1 preadipocytes inhibits cellular adipogenic differentiation. Overexpression of AFF4 enhances adipogenesis and ectopic adipose tissue formation. We further generate Fabp4-cre driven adipose-specific Aff4 knockout mice and find that AFF4 deficiency impedes adipocyte development and white fat depot formation. Mechanistically, we discover AFF4 regulates autophagy during adipogenesis. AFF4 directly binds to autophagy-related protein ATG5 and ATG16L1, and promotes their transcription. Depleting ATG5 or ATG16L1 abrogates adipogenesis in AFF4-overepressing cells, while overexpression of ATG5 and ATG16L1 rescues the impaired adipogenesis in Aff4-knockout cells. Collectively, our results unveil the functional importance of AFF4 in regulating autophagy and adipogenic differentiation, which broaden our understanding of the transcriptional regulation of adipogenesis.

Berberine alleviated contrast-induced acute kidney injury by mitophagy-mediated NLRP3 inflammasome inactivation in a mice model.

The incidence of contrast-induced acute kidney injury (CI-AKI) has escalated to become the third most prevalent cause of hospital-acquired AKI, with a lack of efficacious interventions. Berberine (BBR) possesses diverse pharmacological effects and exhibits renoprotective properties; however, limited knowledge exists regarding its impact on CI-AKI. Therefore, our study aimed to investigate the protective effects and underlying mechanisms of BBR on CI-AKI in a mice model, focusing on the nucleotide-binding oligomerization domain-like pyrin domain-containing protein 3 (NLRP3) inflammasome and mitophagy. The CI-AKI mice model was established by administering NG-nitro-L-arginine methyl ester (L-NAME) (10 mg/kg), indomethacin (10 mg/kg), and iohexol (11 g/kg) following water deprivation. A pretreatment of 100 mg/kg of BBR was orally administered to the mice for two weeks. Renal injury markers, damage-associated molecular patterns (DAMPs), renal histopathology, mitochondrial morphology, autophagosomes, and potential mechanisms were investigated. BBR effectively reduced levels of renal injury biomarkers such as serum cystatin C, urea nitrogen, and creatinine, downregulated the protein level of kidney injury molecule 1 (KIM1), and mitigated renal histomorphological damage. Moreover, BBR reduced DAMPs, including high mobility group box-1 (HMGB1), heat shock protein 70 (HSP70), and uric acid (UA). It also alleviated oxidative stress and inflammatory factors such as monocyte chemotactic protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-1 beta (IL-1ß). Furthermore, the activation of NLRP3 inflammasome was attenuated in the BBR pretreatment group, as evidenced by both mRNA and protein levels. Electron microscopy and western blotting examination revealed that BBR mitigated mitochondrial damage and enhanced mitophagy. Additionally, BBR increased the P-AMPK/AMPK ratio. These findings indicated that BBR exerted a protective effect against CI-AKI by suppressing NLRP3 inflammasome activation and modulating mitophagy, providing a potential therapeutic strategy for its prevention.

Bioinformatics integration reveals key genes associated with mitophagy in myocardial ischemia-reperfusion injury.

BACKGROUND: Myocardial ischemia is a prevalent cardiovascular disorder associated with significant morbidity and mortality. While prompt restoration of blood flow is essential for improving patient outcomes, the subsequent reperfusion process can result in myocardial ischemia-reperfusion injury (MIRI). Mitophagy, a specialized autophagic mechanism, has consistently been implicated in various cardiovascular disorders. However, the specific connection between ischemia-reperfusion and mitophagy remains elusive. This study aims to elucidate and validate central mitophagy-related genes associated with MIRI through comprehensive bioinformatics analysis. METHODS: We acquired the microarray expression profile dataset (GSE108940) from the Gene Expression Omnibus (GEO) and identified differentially expressed genes (DEGs) using GEO2R. Subsequently, these DEGs were cross-referenced with the mitophagy database, and differential nucleotide sequence analysis was performed through enrichment analysis. Protein-protein interaction (PPI) network analysis was employed to identify hub genes, followed by clustering of these hub genes using cytoHubba and MCODE within Cytoscape software. Gene set enrichment analysis (GSEA) was conducted on central genes. Additionally, Western blotting, immunofluorescence, and quantitative polymerase chain reaction (qPCR) analyses were conducted to validate the expression patterns of pivotal genes in MIRI rat model and H9C2 cardiomyocytes. RESULTS: A total of 2719 DEGs and 61 mitophagy-DEGs were identified, followed by enrichment analyses and the construction of a PPI network. HSP90AA1, RPS27A, EEF2, EIF4A1, EIF2S1, HIF-1α, and BNIP3 emerged as the seven hub genes identified by cytoHubba and MCODE of Cytoscape software. Functional clustering analysis of HIF-1α and BNIP3 yielded a score of 9.647, as determined by Cytoscape (MCODE). In our MIRI rat model, Western blot and immunofluorescence analyses confirmed a significant elevation in the expression of HIF-1α and BNIP3, accompanied by a notable increase in the ratio of LC3II to LC3I. Subsequently, qPCR confirmed a significant upregulation of HIF-1α, BNIP3, and LC3 mRNA in the MIRI group. Activation of the HIF-1α/BNIP3 pathway mediates the regulation of the degree of Mitophagy, thereby effectively reducing apoptosis in rat H9C2 cardiomyocytes. CONCLUSIONS: This study has identified seven central genes among mitophagy-related DEGs that may play a pivotal role in MIRI, suggesting a correlation between the HIF-1α/BNIP3 pathway of mitophagy and the pathogenesis of MIRI. The findings highlight the potential importance of mitophagy in MIRI and provide valuable insights into underlying mechanisms and potential therapeutic targets for further exploration in future studies.

Pharmacokinetics of four tannin compounds from Sanguisorba officinalis L. before and after processing by ultra-high-performance liquid chromatography-tandem mass spectrometry.

Sanguisorba officinalis L. possesses detoxifying, analgesic, and hemostatic properties. After charred processing, S. officinalis exhibits significantly enhanced medicinal effects. Currently, most pharmacokinetic studies focus on the chemical constituents of unprocessed S. officinalis. There is limited research on the comparison of chemical constituents before and after processing. This study established a pharmacokinetic method using ultra-high-performance liquid chromatography-tandem mass spectroscopy (UHPLC-MS/MS) to simultaneously determine the levels of four tannin compounds in rat plasma. In negative ion mode, MS/MS detection was performed using an electrospray ionization source. Chromatographic separation was performed using WATERS ACQUITY HSS T3 column (2.1 × 100 mm, 1.8 µm) with a gradient elution of water and acetonitrile as the mobile phase. The pharmacokinetic results indicate that all four compounds reached peak concentrations within 2 h, demonstrating rapid absorption into the bloodstream within the gastrointestinal tract. Notably, the absorption was generally faster in the charred compound of S. officinalis after processing. These four compounds exhibited slower elimination in rat plasma, while in S. officinalis charcoal, the compounds were eliminated more rapidly. The pharmacokinetic results have revealed the pharmacokinetic characteristics of the four analytes in rat plasma which provides valuable reference information for further investigating the in vivo absorption process of S. officinalis after processing.

A breakthrough in phytochemical profiling: ultra-sensitive surface-enhanced Raman spectroscopy platform for detecting bioactive components in medicinal and edible plants.

A perennial challenge in harnessing the rich biological activity of medicinal and edible plants is the accurate identification and sensitive detection of their active compounds. In this study, an innovative, ultra-sensitive detection platform for plant chemical profiling is created using surface-enhanced Raman spectroscopy (SERS) technology. The platform uses silver nanoparticles as the enhancing substrate, excess sodium borohydride prevents substrate oxidation, and methanol enables the tested molecules to be better adsorbed onto the silver nanoparticles. Subsequently, nanoparticle aggregation to form stable "hot spots" is induced by Ca2+, and the Raman signal of the target molecule is strongly enhanced. At the same time, deuterated methanol was used as the internal standard for quantitative determination. The method has excellent reproducibility, RSD ≤ 1.79%, and the enhancement factor of this method for the detection of active ingredients in the medicinal plant Coptis chinensis was 1.24 × 109, with detection limits as low as 3 fM. The platform successfully compared the alkaloid distribution in different parts of Coptis chinensis: root > leaf > stem, and the difference in content between different batches of Coptis chinensis decoction was successfully evaluated. The analytical technology adopted by the platform can speed up the determination of Coptis chinensis and reduce the cost of analysis, not only making better use of these valuable resources but also promoting development and innovation in the food and pharmaceutical industries. This study provides a new method for the development, evaluation, and comprehensive utilization of both medicinal and edible plants. It is expected that this method will be extended to the modern rapid detection of other medicinal and edible plants and will provide technical support for the vigorous development of the medicinal and edible plants industry.

Correlation analysis of Type-2 diabetes mellitus with proliferative retinopathy and central macular thickness.

Objective: To investigate the relevant risk factors of proliferative diabetic retinopathy (PDR) in patients with Type-2 diabetes mellitus (T2DM) and their correlations with the central macular thickness (CMT). Methods: This is a retrospective study. The clinical data of 300 patients with T2DM were collected and divided into a PDR group (observation group) and non-PDR group (control group) according to the occurrence of PDR in Aier Eye Hospital (Taiyuan) from February 2019 to February 2022. The relevant risk factors were screened out through the t test and the χ2 test, and analyzed by logistic regression. Results: Logistic regression analysis showed that systolic blood pressure, diastolic blood pressure, course of diabetes, fasting blood glucose (FBG), two hours postprandial blood glucose (two hours PBG) and urinary albumin were independent risk factors for T2DM complicated with PDR. ROC curve revealed that systolic blood pressure, course of diabetes and urinary albumin had the highest diagnostic efficiency. Correlation analysis demonstrated that CMT was positively correlated with systolic blood pressure, course of diabetes, HbA1c level and urinary albumin level. Conclusion: For patients with T2DM, blood pressure, course of diabetes, FBG, 2hPBG and urinary albumin are independent risk factors for PDR, and increased systolic blood pressure, course of diabetes, HbA1c level and urinary albumin level will increase CMT. Combining the above indexes to predict the occurrence of PDR has a synergistic effect, and the increase in systolic blood pressure, course of diabetes, HbA1c level and urinary albumin level will increase the CMT of the patients.

DNA demethylase ALKBH1 promotes adipogenic differentiation via regulation of HIF-1 signaling.

DNA N6-adenine methylation (6mA), as a novel adenine modification existing in eukaryotes, shows essential functions in embryogenesis and mitochondrial transcriptions. ALKBH1 is a demethylase of 6mA and plays critical roles in osteogenesis, tumorigenesis, and adaptation to stress. However, the integrated biological functions of ALKBH1 still require further exploration. Here, we demonstrate that knockdown of ALKBH1 inhibits adipogenic differentiation in both human mesenchymal stem cells (hMSCs) and 3T3-L1 preadipocytes, while overexpression of ALKBH1 leads to increased adipogenesis. Using a combination of RNA-seq and N6-mA-DNA-IP-seq analyses, we identify hypoxia-inducible factor-1 (HIF-1) signaling as a crucial downstream target of ALKBH1 activity. Depletion of ALKBH1 leads to hypermethylation of both HIF-1α and its downstream target GYS1. Simultaneous overexpression of HIF-1α and GYS1 restores the adipogenic commitment of ALKBH1-deficient cells. Taken together, our data indicate that ALKBH1 is indispensable for adipogenic differentiation, revealing a novel epigenetic mechanism that regulates adipogenesis.

Catalytic Structure Design by AI Generating with Spectroscopic Descriptors.

Generative artificial intelligence has depicted a beautiful blueprint for on-demand design in chemical research. However, the few successful chemical generations have only been able to implement a few special property values because most chemical descriptors are mathematically discrete or discontinuously adjustable. Herein, we use spectroscopic descriptors with machine learning to establish a quantitative spectral structure-property relationship for adsorbed molecules on metal monatomic catalysts. Besides catalytic properties such as adsorption energy and charge transfer, the complete spatial relative coordinates of the adsorbed molecule were successfully inverted. The spectroscopic descriptors and prediction models are generalized, allowing them to be transferred to several different systems. Due to the continuous tunability of the spectroscopic descriptors, the design of catalytic structures with continuous adsorption states generated by AI in the catalytic process has been achieved. This work paves the way for using spectroscopy to enable real-time monitoring of the catalytic process and continuous customization of catalytic performance, which will lead to profound changes in catalytic research.

Ligand-Assisted Self-Assembly of 3D Perovskite Nanocrystals into Chiral Inorganic Quasi-2D Perovskites (n = 3) with Ligand-Ratio-Dependent Chirality Inversion.

Chiral inorganic quasi-2D perovskites are prepared by self-assembling 3D perovskites in solution for the first time. The quasi-2D perovskite synthesized is a pure-phase perovskite with = 3 and is periodically arranged, which is a big breakthrough in quasi-2D inorganic perovskites.  With the individual chiral CsPbBr3 nanocrystals (NCs) assemble into quasi-2D perovskite, the g-factor significantly improved (≈5 × 10-3 ). In addition, the chiroptical activity of quasi-2D perovskites is explored to be improved with the lateral size increasing. In the first stage of assembly, chiral optical activity is increased due to the lateral size-dependent optical activity, while the changes in the later stages are attributable to the chiral morphology. Interestingly, chirality inversion is found to be correlated to the number of ligands. It is believed that different conformers of chiral ligands caused by steric hindrance of the original ligand oleylamine result in opposite circular dichroism (CD) polarities. The chirality inversion phenomenon is universal, regardless of the choice of ligands. This work opens up a new path for the synthesis of quasi-2D perovskites and provides more opportunities for the modulation of chiral optical activity.

Synthesis of copper naphthalocyanine/graphene oxide composites as anode materials for lithium-ion batteries.

Naphthalocyanine and its derivatives are new types of functional materials with wide application prospects. This paper discusses the synthesis of copper tetra tert-butyl-naphthalocyanine (CuNc) and analyses its molecular and electronic structure. Next, CuNc is combined with graphene oxide (GO) through π-π interaction and then pyrolyzed to form a CuNc/GO composite. A systematic investigation of the morphology, structure, composition and properties of CuNc/GO revealed that N-doped graphene is decorated with CuO particles. The electrochemical properties of CuNc/GO are compared with those of directly pyrolysed CuNc. The prepared CuNc/GO (1 : 1) electrode shows a large specific capacity (655.1 mA h g-1) after 100 cycles at 100 mA g-1. Its high capacity, enhanced cycling stability and strong rate performance are attributed to the synergetic effect of N-doped graphene and CuO particles. Besides expanding the use of naphthalocyanine compounds, this work presents a promising candidate material for lithium-ion battery anodes.

Simultaneous determination of four phytoecdysteroids by LC-MS/MS: application to a comparative pharmacokinetic study in normal and adjuvant arthritis rats after oral administration of C. officinalis Kuan phytoecdysteroids extract.

C. officinalis Kuan is the dry root of Cyathula officinalis Kuan. Clinically, it is used for fall and flutter injury, rheumatism and arthralgia. Phytoecdysteroids have significant anti-inflammatory effects, and the phytoecdysteroids present in C. officinalis Kuan exhibit potential for treating rheumatoid arthritis.This study first developed a selective, accurate and efficient LC-MS/MS method for 12-day pharmacokinetic studies regarding the simultaneous determination of cyasterone, 25-epi-28-epi-cyasterone, precyasterone and capitasterone from C. officinalis Kuan phytoecdysteroids extract in normal and adjuvant arthritis rats.An Agilent Eclipse Plus C18 RRHD column (1.8 µm, 50mm × 2.1 mm) with a gradient mobile phase consisting of water (A) and acetonitrile (B) was used for analysis. The mass analysis was performed in an Agilent 6430 QQQ-MS mass spectrometer with positive mode multiple reaction monitoring (MRM).The results indicated that the AUC0-t and AUC0-∞ values of the four phytoecdysteroids in adjuvant arthritis rats were different from those in normal rats on the first day, which could provide a helpful reference for pharmacological and toxicological studies, as well as clinical applications of C. officinalis Kuan in the treatment of rheumatoid arthritis.

1. C. officinalis Kuan is the dry root of Cyathula officinalis Kuan which has been used for the treatment of flapping injury, rheumatism arthralgia, foot flaccidity, and tendon contracture thousands of years in China, and has been officially included in the Chinese Pharmacopoeia.2. A highly accurate, stable, and sensitive ultra-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) method was first established and validated for simultaneously determination four phytoecdysteroids: cyasterone, 25-epi-28-epi-cyasterone, precyasterone and capitasterone in normal and adjuvant arthritis rats plasma samples 12 days of continuous gavage of C. officinalis Kuan phytoecdysteroids extract.3. The phytoecdysteroids is the important component of C. officinalis Kuan, which is difficult to separated. And there is no report for the pharmacokinetic study of phytoecdysteroids from C. officinalis Kuan. And the method provides a good reference for the follow-up studies clinical medication of the phytoecdysteroids from C. officinalis Kuan.

Schisandra B, a representative lignan from Schisandra chinensis, improves cisplatin-induced toxicity: An in vitro study.

Schisandrin B (Scheme B) is the most abundant and active lignan monomer isolated from Schisandra chinensis. At present, most reports focus on its cardioprotective and hepatoprotective effects, however, the related reports on gastrointestinal protective effects are still limited. The study aims to evaluate the protective effect of Scheme B on cisplatin-induced rat intestinal crypt epithelial (IEC-6) cell injury and the possible molecular mechanisms. The results showed that Scheme B at 2.5, 5 and 10 µM could inhibit dose-dependently the reduction of cell activity induced by cisplatin exposure at 1 µM, decrease the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), while increasing glutathione (GSH), superoxide dismutase (SOD) and catalase (CAT) to alleviate oxidative stress injury in IEC-6 cell lines. Meanwhile, Scheme B could relieve cisplatin-induced apoptosis by regulating PI3K/AKT and the downstream caspase signaling pathway. The results from flow cytometry analysis and mitochondrial membrane potential (MMP) staining also demonstrated the anti-apoptosis effect of Scheme B. Furthermore, Scheme B was found to reduce the inflammation associated with cell damage by evaluating the protein expressions of the nuclear factor-kappa B (NF-κB) signaling pathway. Importantly, Wnt/ß-catenin, as a functional signaling pathway that drives intestinal self-recovery, was also in part regulated by Scheme B. In conclusion, Scheme B might alleviate cisplatin-induced IEC-6 cell damage by inhibiting oxidative stress, apoptosis, inflammation, and repairing intestinal barrier function. The present research provides a strong evidence that Scheme B may be a useful modulator in cisplatin-induced intestinal toxicity.

Recent Study Advances in Flexible Sensors Based on Polyimides.

With the demand for healthy life and the great advancement of flexible electronics, flexible sensors are playing an irreplaceably important role in healthcare monitoring, wearable devices, clinic treatment, and so on. In particular, the design and application of polyimide (PI)-based sensors are emerging swiftly. However, the tremendous potential of PI in sensors is not deeply understood. This review focuses on recent studies in advanced applications of PI in flexible sensors, including PI nanofibers prepared by electrospinning as flexible substrates, PI aerogels as friction layers in triboelectric nanogenerator (TENG), PI films as sensitive layers based on fiber Bragg grating (FBG) in relative humidity (RH) sensors, photosensitive PI (PSPI) as sacrificial layers, and more. The simple laser-induced graphene (LIG) technique is also introduced in the application of PI graphitization to graphene. Finally, the prospect of PIs in the field of electronics is proposed in the review.

Red Ginseng Improves D-galactose-Induced Premature Ovarian Failure in Mice Based on Network Pharmacology.

In this study, we evaluated the ameliorative effect and molecular mechanism of red ginseng (Panax ginseng C.A. Meyer) extract (RGE) on D-galactose (D-gal)-induced premature ovarian failure (POF) using network pharmacology analysis. Ginsenosides are important active ingredients in ginseng, which also contains some sugar and amino acid derivatives. We aimed to determine the key proteins through which RGE regulates POF. In this work, we retrieved and screened for active ingredients in ginseng and the corresponding POF disease targets in multiple databases. A PPI network of genes was constructed in the STRING database and core targets were screened using topological analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted in R software. Finally, molecular docking was conducted to validate the results. Female ICR mice were used to establish a POF mouse model for in vivo experiments. Serum levels of relevant estrogens were determined using ELISA and expression levels of relevant proteins in ovarian tissues were detected using immunofluorescence and western blot analysis. Network pharmacology analysis predicted that PI3K, Akt, Bax, Bcl-2, p16, and other proteins were highly correlated with POF and RGE. The results clearly showed that RGE could increase estradiol (E2) and lower follicle-stimulating hormone (FSH) levels in D-gal-fed mice. RGE restored the expression levels of related proteins by reducing Nrf2-mediated oxidative stress, PI3K/Akt-mediated apoptosis, and senescence signaling pathways. Overall, RGE has the potential to prevent and treat POF and is likely to be a promising natural protector of the ovaries.

Identification of Uncaria rhynchophylla in the Potential Treatment of Alzheimer's Disease by Integrating Virtual Screening and In Vitro Validation.

Uncaria rhynchophylla (Gouteng in Chinese, GT) is the main medicine in many traditional recipes in China. It is commonly used to alleviate central nervous system (CNS) disorders, although its mechanism in Alzheimer's disease is still unknown. This study was designed to predict and validate the underlying mechanism in AD treatment, thus illustrating the biological mechanisms of GT in treating AD. In this study, a PPI network was constructed, KEGG analysis and GO analysis were performed, and an "active ingredient-target-pathway" network for the treatment of Alzheimer's disease was constructed. The active ingredients of GT were screened out, and the key targets were performed by molecular docking. UHPLC-Q-Exactive Orbitrap MS was used to screen the main active ingredients and was compared with the network pharmacology results, which verified that GT did contain the above ingredients. A total of targets were found to be significantly bound up with tau, Aß, or Aß and tau through the network pharmacology study. Three SH-SY5Y cell models induced by okadaic acid (OA), Na2S2O4, and H2O2 were established for in vitro validation. We first found that GT can reverse the increase in the hyperphosphorylation of tau induced by OA to some extent, protecting against ROS damage. Moreover, the results also indicated that GT has significant neuroprotective effects. This study provides a basis for studying the potential mechanisms of GT in the treatment of AD.

Simultaneous Determination of Five Iridoids of Picrorhiza scrophulariiflora in Rat Plasma Using UHPLC-ESI-MS/MS.

In this study, we developed an ultra-performance liquid chromatography-electrospray tandem quadrupole mass spectrometry (UHPLC-ESI-MS/MS) method to simultaneously determine Picroside-I, Picroside-II, Picroside-III, minecoside, and sweroside in rat plasma. The chromatographic column was an ACQUITY UHPLC® BEH Amide Column (2.1 × 100 mm, 1.7 µm; Waters, MA, USA), column temperature 40 °C. The mobile phase was 0.1% formic acid aqueous solution-0.1% formic acid acetonitrile solution. The flow rate was 0.4 mL/min. Multiple reaction monitoring (MRM) and negative ion modes were adopted. The results showed that the calibration curves of five compounds in plasma showed good linearity (r > 0.9911) over the studied dose range. The lower limits of quantification (LLOQ) for Picroside-I, Picroside-II, Picroside-III, minecoside, and sweroside were 6.876, 5.193, 5.040, 1.260, and 4.527 ng/mL, respectively. The intra-day and inter-day precision were <15%. The matrix effects ranged from 95.77 to 101.9%. The Tmax were 1.1 ± 0.2, 1.1 ± 0.1, 0.8 ± 0.1, 1.0 ± 0.2, and 2.1 ± 0.1 h. This study will be useful in understanding the behavior of drugs in the body and the body's effect on drugs. It also offers theoretical underpinnings and highlights the importance of clinical applications and creating novel drugs.

Bilobetin attenuates Staphylococcus aureus virulence by targeting Von Willebrand factor-binding protein and staphylocoagulase.

Staphylococcus aureus (S. aureus) induces a variety of infectious diseases in humans and animals and is responsible for hospital- and community-acquired infections. The aim of this study was to investigate how bilobetin, a natural compound, attenuates S. aureus virulence by inhibiting two key virulence factors, von Willebrand factor-binding protein (vWbp) and staphylocoagulase (Coa). The results showed that bilobetin inhibited Coa- or vWbp-induced coagulation without affecting S. aureus proliferation. The Western blotting and fluorescence quenching assays indicated that bilobetin did not affect the expression of vWbp and Coa but directly bound to the proteins with KA values of 1.66 × 104 L/mol and 1.04 × 104 L/mol, respectively. To gain further insight into the mechanism of interaction of bilobetin with these virulence factors, we performed molecular docking and point mutation assays, which indicated that the TYR-6 and TYR-18 residues on vWbp and the ALA-190 and ASP-189 residues on Coa were essential for the binding of bilobetin. In addition, the in vivo studies showed that bilobetin ameliorated lung tissue damage and inflammation caused by S. aureus, thereby improving the survival of mice. Furthermore, the use of bilobetin as an adjuvant in combination with vancomycin was more effective in the treatment of a mouse model of pneumonia. Taken together, bilobetin had a dual inhibitory effect on vWbp and Coa by reducing the virulence of S. aureus, suggesting that it is a viable lead compound against S. aureus infections.

Quantitatively Determining Surface-Adsorbate Properties from Vibrational Spectroscopy with Interpretable Machine Learning.

Learning microscopic properties of a material from its macroscopic measurables is a grand and challenging goal in physical science. Conventional wisdom is to first identify material structures exploiting characterization tools, such as spectroscopy, and then to infer properties of interest, often with assistance of theory and simulations. This indirect approach has limitations due to the accumulation of errors from retrieving structures from spectral signals and the lack of quantitative structure-property relationship. A new pathway directly from spectral signals to microscopic properties is highly desirable, as it would offer valuable guidance toward materials evaluation and design via spectroscopic measurements. Herein, we exploit machine-learned vibrational spectroscopy to establish quantitative spectrum-property relationships. Key interaction properties of substrate-adsorbate systems, including adsorption energy and charge transfer, are quantitatively determined directly from Infrared and Raman spectroscopic signals of the adsorbates. The machine-learned spectrum-property relationships are presented as mathematical formulas, which are physically interpretable and therefore transferrable to a series of metal/alloy surfaces. The demonstrated ability of quantitative determination of hard-to-measure microscopic properties using machine-learned spectroscopy will significantly broaden the applicability of conventional spectroscopic techniques for materials design and high throughput screening under operando conditions.

A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data.

Microbiome omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with identification of specific bacteria taxa associated with diseases, recent scientific advancements provide mounting evidence that metabolism, genetics, and environmental factors can all modulate these microbial effects. However, the current methods for integrating microbiome data and other covariates are severely lacking. Hence, we present an integrative Bayesian zero-inflated negative binomial regression model that can both distinguish differentially abundant taxa with distinct phenotypes and quantify covariate-taxa effects. Our model demonstrates good performance using simulated data. Furthermore, we successfully integrated microbiome taxonomies and metabolomics in two real microbiome datasets to provide biologically interpretable findings. In all, we proposed a novel integrative Bayesian regression model that features bacterial differential abundance analysis and microbiome-covariate effects quantifications, which makes it suitable for general microbiome studies.