Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.

Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical drug discovery. However, current models for predicting liver microsomal stability are based on limited molecular information from a single species. To address this limitation, we constructed the largest public database of compounds from three common species: human, rat, and mouse. Subsequently, we developed a series of classification models using both traditional descriptor-based and classic graph-based machine learning (ML) algorithms. Remarkably, the best-performing models for the three species achieved Matthews correlation coefficients (MCCs) of 0.616, 0.603, and 0.574, respectively, on the test set. Furthermore, through the construction of consensus models based on these individual models, we have demonstrated their superior predictive performance in comparison with the existing models of the same type. To explore the similarities and differences in the properties of liver microsomal stability among multispecies molecules, we conducted preliminary interpretative explorations using the Shapley additive explanations (SHAP) and atom heatmap approaches for the models and misclassified molecules. Additionally, we further investigated representative structural modifications and substructures that decrease the liver microsomal stability in different species using the matched molecule pair analysis (MMPA) method and substructure extraction techniques. The established prediction models, along with insightful interpretation information regarding liver microsomal stability, will significantly contribute to enhancing the efficiency of exploring practical drugs for development.

One-Shot Single-Cell Proteome and Metabolome Analysis Strategy for the Same Single Cell.

Characterizing the profiles of proteome and metabolome at the single-cell level is of great significance in single-cell multiomic studies. Herein, we proposed a novel strategy called one-shot single-cell proteome and metabolome analysis (scPMA) to acquire the proteome and metabolome information in a single-cell individual in one injection of LC-MS/MS analysis. Based on the scPMA strategy, a total workflow was developed to achieve the single-cell capture, nanoliter-scale sample pretreatment, one-shot LC injection and separation of the enzyme-digested peptides and metabolites, and dual-zone MS/MS detection for proteome and metabolome profiling. Benefiting from the scPMA strategy, we realized dual-omic analysis of single tumor cells, including A549, HeLa, and HepG2 cells with 816, 578, and 293 protein groups and 72, 91, and 148 metabolites quantified on average. A single-cell perspective experiment for investigating the doxorubicin-induced antitumor effects in both the proteome and metabolome aspects was also performed.

Analysis of risk factors and prognosis of diarrhea after renal transplantation.

BACKGROUND: Diarrhea is a prevalent complication after renal transplantation. OBJECTIVE: To examine the risk factors for diarrhea after renal transplantation, evaluate their combined predictive values, and analyze the prognosis. METHODS: Clinical data of patients who underwent allogeneic renal transplantation in the Second People's Hospital of Shanxi Province from January 2019 to March 2020 were retrospectively analyzed, cases were screened and grouped, independent risk factors for diarrhea after renal transplantation were analyzed by univariate analysis and multivariate analysis, and their predictive value was evaluated by receiver operating characteristic (ROC) curve. The survival time of recipient grafts in diarrhea and non-diarrhea groups were evaluated by Kaplan-Meier and log-rank test. RESULTS: We included 166 recipients in the study and the incidence of diarrhea was 25.9%; univariate and logistic regression multivariate analyses revealed that independent risk factors for diarrhea in recipients were that the type of renal transplant donor was DCD (donation after circulatory death), immunity induction was onducted with basiliximab + antithymocyte globulin (ATG), and ATG alone, the type of mycophenolic acid (MPA) used was mycophenolate mofetil capsules, and delayed graft function (DGF) occurred after transplantation. The ROC curve indicated that the combination of the four factors had good accuracy in predicting the occurrence of diarrhea in recipients. The graft survival rate two years after the operation in the diarrhea group was significantly lower than that in the non-diarrhea group. CONCLUSION: Diarrhea affected the two-year survival rate of the graft. The type of donor, immunity induction scheme, and the type of MPA and DGF were independent risk factors for diarrhea in recipients, and the combination of the four factors had good prognostic prediction value.

Mirizzi syndrome: Problems and strategies.

Mirizzi syndrome is a serious complication of gallstone disease. It is caused by the impacted stones in the gallbladder neck or cystic duct. One of the features of Mirizzi syndrome is severe inflammation or dense fibrosis at the Calot's triangle. In our clinical practice, bile duct, branches of right hepatic artery and right portal vein clinging to gallbladder infundibulum are often observed due to gallbladder infundibulum adhered to right hepatic hilum. The intraoperative damage of branches of right hepatic artery occurs more easily than that of bile duct, all of which are hidden pitfalls for surgeons. Magnetic resonance cholangiopancreatography (MRCP) and endoscopic retrograde cholangiopancreatography (ERCP) are the preferable tools for the diagnosis of Mirizzi syndrome. Anterograde cholecystectomy in Mirizzi syndrome is easy to damage branches of right hepatic artery and bile duct due to gallbladder infundibulum adhered to right hepatic hilum. Subtotal cholecystectomy is an easy, safe and definitive approach to Mirizzi syndrome. When combined with the application of ERCP, a laparoscopic management of Mirizzi syndrome by well-trained surgeons is feasible and safe. The objective of this review was to highlight its existing problems: (1) low preoperative diagnostic rate, (2) easy to damage bile duct and branches of right hepatic artery, and (3) high concomitant gallbladder carcinoma. Meanwhile, the review aimed to discuss the possible therapeutic strategies: (1) to enhance its preoperative recognition by imaging findings, and (2) to avoid potential pitfalls during surgery.

Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell.

The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449-3500, 2278-3257 and 1621-2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

Emergence of Competing Orders and Possible Quantum Spin Liquid in SU(N) Fermions.

In the past few decades, tremendous efforts have been made toward understanding the exotic physics emerging from competition between various ordering tendencies in strongly correlated systems. Employing state-of-the-art quantum Monte Carlo simulation, we investigate an interacting SU(N) fermionic model with varying interaction strength and value of N, and we unveil the ground-state phase diagram of the model exhibiting a plethora of exotic phases. For small values of N-namely, N=2, 3-the ground state is an antiferromagnetic (AFM) phase, whereas in the large-N limit, a staggered valence bond solid (VBS) order is dominant. For intermediate values of N such as N=4, 5, remarkably, our study reveals that distinct VBS orders appear in the weak and strong coupling regimes. More fantastically, the competition between staggered and columnar VBS ordering tendencies gives rise to a Mott insulating phase without spontaneous symmetry breaking (SSB), existing in a large interacting parameter regime, which is consistent with a gapped quantum spin liquid. Our study not only provides a platform to investigate the fundamental physics of quantum many-body systems-it also offers a novel route toward searching for exotic states of matter such as quantum spin liquid in realistic quantum materials.

Internal exposure potential of water-soluble organic molecules in urban PM2.5 evaluated by non-covalent adductome of human serum albumin.

Water-soluble organic molecules (WSOMs) in inhaled PM2.5 can readily translocate from the lungs into the blood circulation, facilitating their distribution to and health effects on distant organs and tissues in the human body. Human serum albumin (HSA), the most abundant protein carrier in the blood, readily binds exogenous substances to form non-covalent adducts and subsequently transports them throughout the circulatory system, thereby indicating their internal exposure. The direct internal exposure of WSOMs in PM2.5 needs to be understood. In this study, the non-covalent HSA-WSOM adductome was developed as a dosimeter to evaluate the internal exposure potential of WSOMs in urban PM2.5. The WSOM composition was acquired from non-target high-resolution mass spectrometry analysis coupled with multiple ionizations. The binding level of HSA-WSOM non-covalent adducts was obtained from surface plasma resonance. Machine learning combined WSOM composition and the binding level of HSA-WSOM non-covalent adducts to screen bindable (also internalizable) WSOMs. The concentration of WSOM ranged from 4 to 13 µg/m3 during our observation period. Of the 17,513 mass spectral features detected, 9,484 contributed to the non-covalent adductome and possessed the internal exposure potential. 102 major contributors accounted for 90.6 % of the HSA-WSOM binding level. The fraction of internalizable WSOMs in PM2.5 varied from 11.9 % to 61.3 %, averaging 26.2 %. WSOMs that have internal exposure potential were primarily lignin-like and lipid-like substances. The HSA-WSOMs non-covalent adductome represents direct internal exposure potential, which can provide crucial insights into the molecular diagnosis of PM2.5 exposure and precise assessments of PM2.5 health effects.

Impact of antioxidants on PM2.5 oxidative potential, radical level, and cytotoxicity.

Antioxidants are typically seen as agents that mitigate environmental health risks due to their ability to scavenge free radicals. However, our research presents a paradox where these molecules, particularly those within lung fluid, act as prooxidants in the presence of airborne particulate matter (PM2.5), thus enhancing PM2.5 oxidative potential (OP). In our study, we examined a range of antioxidants found in the respiratory system (e.g., vitamin C, glutathione (GSH), and N-acetylcysteine (NAC)), in plasma (vitamin A, vitamin E, and ß-carotene), and in food (tert-butylhydroquinone (TBHQ)). We aimed to explore antioxidants' prooxidant and antioxidant interactions with PM2.5 and the resulting OP and cytotoxicity. We employed OH generation assays and electron paramagnetic resonance assays to assess the pro-oxidative and anti-oxidative effects of antioxidants. Additionally, we assessed cytotoxicity interaction using a Chinese hamster ovary cell cytotoxicity assay. Our findings revealed that, in the presence of PM2.5, all antioxidants except vitamin E significantly increased the PM2.5 OP by generating more OH radicals (OH generation rate: 0.16-24.67 pmol·min-1·m-3). However, it's noteworthy that these generated OH radicals were at least partially neutralized by the antioxidants themselves. Among the pro-oxidative antioxidants, vitamin A, ß-carotene, and TBHQ showed the least ability to quench these radicals, consistent with their observed impact in enhancing PM2.5 cytotoxicity (PM2.5 LC50 reduced to 91.2 %, 88.8 %, and 75.1 % of PM2.5's original level, respectively). Notably, vitamin A and TBHQ-enhanced PM2.5 OP were strongly associated with the presence of metals and organic compounds, particularly with copper (Cu) contributing significantly (35 %) to TBHQ's pro-oxidative effect. Our study underscores the potential health risks associated with the interaction between antioxidants and ambient pollutants.

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte.

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.

[Hemilateral bone longitudinal transport technique for the treatment of hemilateral defects of long bones of lower limbs].

OBJECTIVE: To explore clinical efficacy of Ilizarov hemilateral bone longitudinal transport technique in treating hemilateral bone defects associated with chronic osteomyelitis of lower extremity long bones. METHODS: Clinical data of 13 patients with hemilateral bone defects caused by chronic osteomyelitis of lower extremity long bones and treated by Ilizarov hemilateral bone longitudinal transport technique were retrospective analyzed, including 10 males and 3 female, aged from 14 to 55 years old;4 patients occurred femoral and 9 patients occurred tibial;10 patients were diagnosed as traumatic osteomyelitis and 3 patients as hematogenous osteomyelitis. The anatomical classification of Cierny-Mader in 13 patients was type Ⅲ. Bone and wound healing, postopertaive complication, and bony and functional results were observed by Paley evaluation standard. RESULTS: After removing external fixator, all patients were followed up from 6 to 70 months. Transporting time ranged from 54 to 158 d. And the time in external fixation ranged from 6.8 to 19.5 months. External fixation index (EFI) ranged from 1.23 to 1.6 months/cm. According to Paley's evaluation criteria, bony results were excellent in 13 patients;functional results showed excellent in 12 patients and good in 1 patient. Two patients occurred poor union on the docking sites and healed with autogenous iliac bone graft. The callus at the extended area was poorly mineralized and improved significantly when treated with low-intensity pulsed ultrasound in one patient. All patients had good wound healing without recurrence of osteomyelitis and refracture. There was no vascular and nerve injury and axial deviation in all patients and they were satisfied with the appearance and function of lower limbs. The range of motion of knee and ankle joint before operation was 120 ° to 150 ° and 35 °to 80 ° respectively, and at the latest follow-up was 110 ° to 140 ° and 30 ° to 75 ° . CONCLUSION: Ilizarov hemilateral bone longitudinal transport technique is effective in treating infective hemilateral bone defects of lower extremity long bones, which could not only simplify architecture of external fixation, but also reduce the number of fixation pins, shorten the time in external fixator and decrease the incidence of pin tract infection. However, this technique is highly demanding, and the growth of callus in extended region and healing of bone apposition should be noticed.

Impact of Ship Emissions on Air Quality in the Greater Bay Area in China under the Latest Global Marine Fuel Regulation.

As the main anthropogenic source in open seas and coastal areas, ship emissions impact the climate, air quality, and human health. The latest marine fuel regulation with a sulfur content limit of 0.5% went into effect globally on January 1, 2020. Investigations of ship emissions after fuel switching are necessary. In this study, online field measurements at an urban coastal site and modeling simulations were conducted to detect the impact of ship emissions on air quality in the Greater Bay Area (GBA) in China under new fuel regulation. By utilizing a high mass-resolution single particle mass spectrometer, the vanadium(V) signal was critically identified and was taken as a robust indicator for ship-emitted particles (with relative peak area > 0.1). The considerable number fractions of high-V particles (up to 30-40% during ship plumes) indicated that heavy fuel oils via simple desulfurization or blending processes with low-sulfur fuels were extensively used in the GBA to meet the global 0.5% sulfur cap. Our results showed that ship-emitted particulate matter and NOx contributed up to 21.4% and 39.5% to the ambient, respectively, in the summertime, significantly affecting the air quality in the GBA. The sea-land breeze circulation also played an important role in the transport pattern of ship-emitted pollutants in the GBA.

Visible-Light-Mediated Intermolecular [2 + 2]-Cycloaddition Reaction of 3-Alkylideneindolin-2-one with Alkenes via Triplet Energy Transfer for the Synthesis of 3-Spirocyclobutyl Oxindoles.

[2 + 2]-Cycloaddition is the most straightforward approach to the construction of cyclobutanes. In this paper, the intermolecular [2 + 2]-cycloaddition reaction of 3-alkylideneindolin-2-ones with alkenes was achieved. This reaction can be used in the synthesis of 3-spirocyclobutyl oxindoles, polycyclic oxindoles, and late stage modification of some drug molecules.

Enhanced Dielectric Properties of All-Cellulose Composite Film via Modulating Hydroxymethyl Conformation and Hydrogen Bonding Network.

Cellulose-based dielectrics with attractive dielectric performance are promising candidates to develop eco-friendly electrostatic energy storage devices. Herein, all-cellulose composite films with superior dielectric constant were fabricated by manipulating the dissolution temperature of native cellulose, where we revealed the relationship among the hierarchical microstructure of the crystalline structure, the hydrogen bonding network, the relaxation behavior at a molecular level, and the dielectric performance of the cellulose film. The coexistence of cellulose I and cellulose II led to a weakened hydrogen bonding network and unstable C6 conformations. The increased mobility of cellulose chains in the cellulose I-amorphous interphase enhanced the dielectric relaxation strength of side groups and localized main chains. As a result, the as-prepared all-cellulose composite films exhibited a fascinating dielectric constant of as high as 13.9 at 1000 Hz. This work proposed here provides a significant step toward fundamentally understanding the dielectric relaxation of cellulose, thus developing high-performance and eco-friendly cellulose-based film capacitors.

Insight into the phenolics and antioxidant activity of Indian jujube (Ziziphus mauritiana Lamk) peel and pulp subjected to the simulated digestion.

To evaluate the release and activity of Indian jujube phenolics in vivo, its peel and pulp were subjected to simulated digestions. The phenolics content and antioxidant activity of the digested samples were determined. The results showed that the total phenolics/flavonoids in the peel were respectively 4.63 and 4.48 times higher than that in the pulp. The release of phenolics and flavonoids respectively increased by 79.75% and 39.98% in the peel and 86.34% and 23.54% in the pulp after the intestinal digestion. The correlation between the total phenolics/flavonoids and antioxidant activity was higher in the peel (r > 0.858, p < 0.01) than that in the pulp. The phenolics profiles of the peel were almost the same after the digestion, and four phenolics including naringenin tri-glycoside, quercetin-3-O-[(2-hexosyl)-6-rhamnosyl] -hexoside, quercetin-3-O-pentosylhexoside and quercetin-3-O-(2-pentosyl -rhamnoside)-4'-O-rhamnoside were found to be the main flavonoids of Indian jujube peel, and they showed high recovery (>89.88%) during the digestion, implying that these phenolics may play a vital role in the function of Indian jujubes.

Reducing false positive rate of docking-based virtual screening by active learning.

Machine learning-based scoring functions (MLSFs) have become a very favorable alternative to classical scoring functions because of their potential superior screening performance. However, the information of negative data used to construct MLSFs was rarely reported in the literature, and meanwhile the putative inactive molecules recorded in existing databases usually have obvious bias from active molecules. Here we proposed an easy-to-use method named AMLSF that combines active learning using negative molecular selection strategies with MLSF, which can iteratively improve the quality of inactive sets and thus reduce the false positive rate of virtual screening. We chose energy auxiliary terms learning as the MLSF and validated our method on eight targets in the diverse subset of DUD-E. For each target, we screened the IterBioScreen database by AMLSF and compared the screening results with those of the four control models. The results illustrate that the number of active molecules in the top 1000 molecules identified by AMLSF was significantly higher than those identified by the control models. In addition, the free energy calculation results for the top 10 molecules screened out by the AMLSF, null model and control models based on DUD-E also proved that more active molecules can be identified, and the false positive rate can be reduced by AMLSF.

A remarkably diverse and well-organized virus community in a filter-feeding oyster.

BACKGROUND: Viruses play critical roles in the marine environment because of their interactions with an extremely broad range of potential hosts. Many studies of viruses in seawater have been published, but viruses that inhabit marine animals have been largely neglected. Oysters are keystone species in coastal ecosystems, yet as filter-feeding bivalves with very large roosting numbers and species co-habitation, it is not clear what role they play in marine virus transmission and coastal microbiome regulation. RESULTS: Here, we report a Dataset of Oyster Virome (DOV) that contains 728,784 nonredundant viral operational taxonomic unit contigs (≥ 800 bp) and 3473 high-quality viral genomes, enabling the first comprehensive overview of both DNA and RNA viral communities in the oyster Crassostrea hongkongensis. We discovered tremendous diversity among novel viruses that inhabit this oyster using multiple approaches, including reads recruitment, viral operational taxonomic units, and high-quality virus genomes. Our results show that these viruses are very different from viruses in the oceans or other habitats. In particular, the high diversity of novel circoviruses that we found in the oysters indicates that oysters may be potential hotspots for circoviruses. Notably, the viruses that were enriched in oysters are not random but are well-organized communities that can respond to changes in the health state of the host and the external environment at both compositional and functional levels. CONCLUSIONS: In this study, we generated a first "knowledge landscape" of the oyster virome, which has increased the number of known oyster-related viruses by tens of thousands. Our results suggest that oysters provide a unique habitat that is different from that of seawater, and highlight the importance of filter-feeding bivalves for marine virus exploration as well as their essential but still invisible roles in regulating marine ecosystems. Video Abstract.

Structural Analysis and Prediction of Hematotoxicity Using Deep Learning Approaches.

Hematotoxicity has been becoming a serious but overlooked toxicity in drug discovery. However, only a few in silico models have been reported for the prediction of hematotoxicity. In this study, we constructed a high-quality dataset comprising 759 hematotoxic compounds and 1623 nonhematotoxic compounds and then established a series of classification models based on a combination of seven machine learning (ML) algorithms and nine molecular representations. The results based on two data partitioning strategies and applicability domain (AD) analysis illustrate that the best prediction model based on Attentive FP yielded a balanced accuracy (BA) of 72.6%, an area under the receiver operating characteristic curve (AUC) value of 76.8% for the validation set, and a BA of 69.2%, an AUC of 75.9% for the test set. In addition, compared with existing filtering rules and models, our model achieved the highest BA value of 67.5% for the external validation set. Additionally, the shapley additive explanation (SHAP) and atom heatmap approaches were utilized to discover the important features and structural fragments related to hematotoxicity, which could offer helpful tips to detect undesired positive substances. Furthermore, matched molecular pair analysis (MMPA) and representative substructure derivation technique were employed to further characterize and investigate the transformation principles and distinctive structural features of hematotoxic chemicals. We believe that the novel graph-based deep learning algorithms and insightful interpretation presented in this study can be used as a trustworthy and effective tool to assess hematotoxicity in the development of new drugs.