DeepIRES: a hybrid deep learning model for accurate identification of internal ribosome entry sites in cellular and viral mRNAs.

The internal ribosome entry site (IRES) is a cis-regulatory element that can initiate translation in a cap-independent manner. It is often related to cellular processes and many diseases. Thus, identifying the IRES is important for understanding its mechanism and finding potential therapeutic strategies for relevant diseases since identifying IRES elements by experimental method is time-consuming and laborious. Many bioinformatics tools have been developed to predict IRES, but all these tools are based on structure similarity or machine learning algorithms. Here, we introduced a deep learning model named DeepIRES for precisely identifying IRES elements in messenger RNA (mRNA) sequences. DeepIRES is a hybrid model incorporating dilated 1D convolutional neural network blocks, bidirectional gated recurrent units, and self-attention module. Tenfold cross-validation results suggest that DeepIRES can capture deeper relationships between sequence features and prediction results than other baseline models. Further comparison on independent test sets illustrates that DeepIRES has superior and robust prediction capability than other existing methods. Moreover, DeepIRES achieves high accuracy in predicting experimental validated IRESs that are collected in recent studies. With the application of a deep learning interpretable analysis, we discover some potential consensus motifs that are related to IRES activities. In summary, DeepIRES is a reliable tool for IRES prediction and gives insights into the mechanism of IRES elements.

Tissue-infiltrating alloreactive T cells require Id3 to deflect PD-1-mediated immune suppression during GVHD.

ABSTRACT: Persisting alloreactive donor T cells in target tissues are a determinant of graft-versus-host disease (GVHD), but the transcriptional regulators that control the persistence and function of tissue-infiltrating T cells remain elusive. We demonstrate here that Id3, a DNA-binding inhibitor, is critical for sustaining T-cell responses in GVHD target tissues in mice, including the liver and intestine. Id3 loss results in aberrantly expressed PD-1 in polyfunctional T helper 1 (Th1) cells, decreased tissue-infiltrating PD-1+ polyfunctional Th1 cell numbers, impaired maintenance of liver TCF-1+ progenitor-like T cells, and inhibition of GVHD. PD-1 blockade restores the capacity of Id3-ablated donor T cells to mediate GVHD. Single-cell RNA-sequencing analysis revealed that Id3 loss leads to significantly decreased CD28- and PI3K/AKT-signaling activity in tissue-infiltrating polyfunctional Th1 cells, an indicator of active PD-1/PD-L1 effects. Id3 is also required for protecting CD8+ T cells from the PD-1 pathway-mediated suppression during GVHD. Genome-wide RNA-sequencing analysis reveals that Id3 represses transcription factors (e.g., Nfatc2, Fos, Jun, Ets1, and Prdm1) that are critical for PD-1 transcription, exuberant effector differentiation, and interferon responses and dysfunction of activated T cells. Id3 achieves these effects by restraining the chromatin accessibility for these transcription factors. Id3 ablation in donor T cells preserved their graft vs tumor effects in mice undergoing allogeneic hematopoietic stem cell transplantation. Furthermore, CRISPR/Cas9 knockout of ID3 in human CD19-directed chimeric antigen receptor T cells retained their antitumor activity in NOD/SCID/IL2Rg-/- mice early after administration. These findings identify that ID3 is an important target to reduce GVHD, and the gene-editing program of ID3 may have broad implications in T-cell-based immunotherapy.

The pyrenoid: the eukaryotic CO2-concentrating organelle.

The pyrenoid is a phase-separated organelle that enhances photosynthetic carbon assimilation in most eukaryotic algae and the land plant hornwort lineage. Pyrenoids mediate approximately one-third of global CO2 fixation, and engineering a pyrenoid into C3 crops is predicted to boost CO2 uptake and increase yields. Pyrenoids enhance the activity of the CO2-fixing enzyme Rubisco by supplying it with concentrated CO2. All pyrenoids have a dense matrix of Rubisco associated with photosynthetic thylakoid membranes that are thought to supply concentrated CO2. Many pyrenoids are also surrounded by polysaccharide structures that may slow CO2 leakage. Phylogenetic analysis and pyrenoid morphological diversity support a convergent evolutionary origin for pyrenoids. Most of the molecular understanding of pyrenoids comes from the model green alga Chlamydomonas (Chlamydomonas reinhardtii). The Chlamydomonas pyrenoid exhibits multiple liquid-like behaviors, including internal mixing, division by fission, and dissolution and condensation in response to environmental cues and during the cell cycle. Pyrenoid assembly and function are induced by CO2 availability and light, and although transcriptional regulators have been identified, posttranslational regulation remains to be characterized. Here, we summarize the current knowledge of pyrenoid function, structure, components, and dynamic regulation in Chlamydomonas and extrapolate to pyrenoids in other species.

Improving therapeutic synergy score predictions with adverse effects using multi-task heterogeneous network learning.

Drug combinations could trigger pharmacological therapeutic effects (TEs) and adverse effects (AEs). Many computational methods have been developed to predict TEs, e.g. the therapeutic synergy scores of anti-cancer drug combinations, or AEs from drug-drug interactions. However, most of the methods treated the AEs and TEs predictions as two separate tasks, ignoring the potential mechanistic commonalities shared between them. Based on previous clinical observations, we hypothesized that by learning the shared mechanistic commonalities between AEs and TEs, we could learn the underlying MoAs (mechanisms of actions) and ultimately improve the accuracy of TE predictions. To test our hypothesis, we formulated the TE prediction problem as a multi-task heterogeneous network learning problem that performed TE and AE learning tasks simultaneously. To solve this problem, we proposed Muthene (multi-task heterogeneous network embedding) and evaluated it on our collected drug-drug interaction dataset with both TEs and AEs indications. Our experimental results showed that, by including the AE prediction as an auxiliary task, Muthene generated more accurate TE predictions than standard single-task learning methods, which supports our hypothesis. Using a drug pair Vincristine-Dasatinib as a case study, we demonstrated that our method not only provides a novel way of TE predictions but also helps us gain a deeper understanding of the MoAs of drug combinations.

MpbPPI: a multi-task pre-training-based equivariant approach for the prediction of the effect of amino acid mutations on protein-protein interactions.

The accurate prediction of the effect of amino acid mutations for protein-protein interactions (PPI $\Delta \Delta G$) is a crucial task in protein engineering, as it provides insight into the relevant biological processes underpinning protein binding and provides a basis for further drug discovery. In this study, we propose MpbPPI, a novel multi-task pre-training-based geometric equivariance-preserving framework to predict PPI  $\Delta \Delta G$. Pre-training on a strictly screened pre-training dataset is employed to address the scarcity of protein-protein complex structures annotated with PPI $\Delta \Delta G$ values. MpbPPI employs a multi-task pre-training technique, forcing the framework to learn comprehensive backbone and side chain geometric regulations of protein-protein complexes at different scales. After pre-training, MpbPPI can generate high-quality representations capturing the effective geometric characteristics of labeled protein-protein complexes for downstream $\Delta \Delta G$ predictions. MpbPPI serves as a scalable framework supporting different sources of mutant-type (MT) protein-protein complexes for flexible application. Experimental results on four benchmark datasets demonstrate that MpbPPI is a state-of-the-art framework for PPI $\Delta \Delta G$ predictions. The data and source code are available at https://github.com/arantir123/MpbPPI.

Accelerated Solar-Driven Polyolefin Degradation via Self-Activated Hydroxy-Rich ZnIn2S4.

Degradation of polyolefin (PE) plastic by a traditional chemical method requires a high pressure and a high temperature but generates complex products. Here, sulfur vacancy-rich ZnIn2S4 and hydroxy-rich ZnIn2S4 were rationally fabricated to realize photocatalytic degradation of PE in an aqueous solution under mild conditions. The results reveal that the optimized photocatalyst could degrade PE into CO2 and CO, and PE had a weight loss of 84.5% after reaction for 60 h. Systematic experiments confirm that the synergetic effect of hydroxyl groups and S vacancies contributes to improve the photocatalytic degradation properties of plastic wastes. In-depth investigation illustrates that the active radicals attack (h+ and •OH) weak spots (C-H and C-C bonds) of the PE chain to form CO2, which is further selectively photoreduced to CO. Multimodule synergistic tandem catalysis can further improve the utilization value of plastic wastes; for example, product CO2/CO in the plastic degradation process can be converted in situ into HCOOH by coupling with electrocatalytic technology.

Endothelial POFUT1 controls injury-induced liver fibrosis by repressing fibrinogen synthesis.

BACKGROUND & AIMS: NOTCH signaling in liver sinusoidal endothelial cells (LSECs) regulates liver fibrosis, a pathological feature of chronic liver diseases. POFUT1 is an essential regulator of NOTCH signaling. Here, we investigated the role of LSEC-expressed POFUT1 in liver fibrosis. METHODS: Endothelial-specific Pofut1 knockout mice were generated and experimental liver fibrosis was induced by chronic carbon tetrachloride exposure or common bile duct ligation. Liver samples were assessed by ELISA, histology, electron microscopy, immunostaining and RNA in situ hybridization. LSECs and hepatic stellate cells (HSCs) were isolated for gene expression analysis by RNA sequencing, qPCR, and western blotting. Signaling crosstalk between LSECs and HSCs was investigated by treating HSCs with supernatant from LSEC cultures. Liver single-cell RNA sequencing datasets from patients with cirrhosis and healthy individuals were analyzed to evaluate the clinical relevance of gene expression changes observed in mouse studies. RESULTS: POFUT1 loss promoted injury-induced LSEC capillarization and HSC activation, leading to aggravated liver fibrosis. RNA sequencing analysis revealed that POFUT1 deficiency upregulated fibrinogen expression in LSECs. Consistently, fibrinogen was elevated in LSECs of patients with cirrhosis. HSCs treated with supernatant from LSECs of Pofut1 null mice showed exacerbated activation compared to those treated with supernatant from control LSECs, and this effect was attenuated by knockdown of fibrinogen or by pharmacological inhibition of fibrinogen receptor signaling, altogether suggesting that LSEC-derived fibrinogen induced the activation of HSCs. Mechanistically, POFUT1 loss augmented fibrinogen expression by enhancing NOTCH/HES1/STAT3 signaling. CONCLUSIONS: Endothelial POFUT1 prevents injury-induced liver fibrosis by repressing the expression of fibrinogen, which functions as a profibrotic paracrine signal to activate HSCs. Therapies targeting the POFUT1/fibrinogen axis offer a promising strategy for the prevention and treatment of fibrotic liver diseases. IMPACT AND IMPLICATIONS: Paracrine signals produced by liver vasculature play a major role in the development of liver fibrosis, which is a pathological hallmark of most liver diseases. Identifying those paracrine signals is clinically relevant in that they may serve as therapeutic targets. In this study, we discovered that genetic deletion of Pofut1 aggravated experimental liver fibrosis in mouse models. Moreover, fibrinogen was identified as a downstream target repressed by Pofut1 in liver endothelial cells and functioned as a novel paracrine signal that drove liver fibrosis. In addition, fibrinogen was found to be relevant to cirrhosis and may serve as a potential therapeutic target for this devastating human disease.

Microfluidic Immunosensing Platform Based on a Rolling Circle Amplification-Assisted DNA Dendrimer Probe for Portable and Sensitive Detection of Allergen-Specific IgE.

The robust point-of-care platform for sensitive, multiplexed, and affordable detection of allergen-specific IgE (sIgE) is an urgent demand in component-resolved diagnostics. Here, we developed a microfluidic immunosensing platform based on a rolling circle amplification-assisted DNA dendrimer probe for sensitive detection of multiple sIgEs. The versatile multichannel microfluidic whole blood analytical device integrates cell filtration, recombinant antigen-modified magnetic enrichment, and DNA dendrimer probe-amplified signal transduction for portable on-chip analysis. Three sIgEs against common oyster allergens were simultaneously detected in blood samples by simple smartphone-based imaging without any pretreatment. The quantitative detection of multiple allergen-specific antibodies on the platform was achieved with limits of detection of less than 50 pg/mL, exhibiting superior sensitivity compared to most point-of-care testing. The detection results of 55 serum samples and 4 whole blood samples were 100% consistent with the ELISA results, confirming the accuracy and stability of our platform. Additionally, the reversible combination of hexahistidine6-tag and Ni-IMAC magbead was elegantly utilized on the immunosensing platform for desired reversibility. With the advantages of general applicability, high sensitivity, and reversibility, the DNA dendrimer-based microfluidic immunosensing platform provides great potential for the portable detection of immune proteins as a point-of-care platform in disease diagnostics and biological analysis.

HGF facilitates methylation of MEG3, potentially implicated in vemurafenib resistance in melanoma.

BACKGROUND: Melanoma, a frequently encountered cutaneous malignancy characterized by a poor prognosis, persists in presenting formidable challenges despite the advancement in molecularly targeted drugs designed to improve survival rates significantly. Unfortunately, as more therapeutic choices have developed over time, the gradual emergence of drug resistance has become a notable impediment to the effectiveness of these therapeutic interventions. The hepatocyte growth factor (HGF)/c-met signaling pathway has attracted considerable attention, associated with drug resistance stemming from multiple potential mutations within the c-met gene. The activation of the HGF/c-met pathway operates in an autocrine manner in melanoma. Notably, a key player in the regulatory orchestration of HGF/c-met activation is the long non-coding RNA MEG3. METHODS: Melanoma tissues were collected to measure MEG3 expression. In vitro validation was performed on MEG3 to prove its oncogenic roles. Bioinformatic analyses were conducted on the TCGA database to build the MEG3-related score. The immune characteristics and mutation features of the MEG3-related score were explored. RESULTS: We revealed a negative correlation between HGF and MEG3. In melanoma cells, HGF inhibited MEG3 expression by augmenting the methylation of the MEG3 promoter. Significantly, MEG3 exhibits a suppressive impact on the proliferation and migration of melanoma cells, concurrently inhibiting c-met expression. Moreover, a predictive model centered around MEG3 demonstrates notable efficacy in forecasting critical prognostic indicators, immunological profiles, and mutation statuses among melanoma patients. CONCLUSIONS: The present study highlights the potential of MEG3 as a pivotal regulator of c-met, establishing it as a promising candidate for targeted drug development in the ongoing pursuit of effective therapeutic interventions.

MIX-TPI: a flexible prediction framework for TCR-pMHC interactions based on multimodal representations.

MOTIVATION: The interactions between T-cell receptors (TCR) and peptide-major histocompatibility complex (pMHC) are essential for the adaptive immune system. However, identifying these interactions can be challenging due to the limited availability of experimental data, sequence data heterogeneity, and high experimental validation costs. RESULTS: To address this issue, we develop a novel computational framework, named MIX-TPI, to predict TCR-pMHC interactions using amino acid sequences and physicochemical properties. Based on convolutional neural networks, MIX-TPI incorporates sequence-based and physicochemical-based extractors to refine the representations of TCR-pMHC interactions. Each modality is projected into modality-invariant and modality-specific representations to capture the uniformity and diversities between different features. A self-attention fusion layer is then adopted to form the classification module. Experimental results demonstrate the effectiveness of MIX-TPI in comparison with other state-of-the-art methods. MIX-TPI also shows good generalization capability on mutual exclusive evaluation datasets and a paired TCR dataset. AVAILABILITY AND IMPLEMENTATION: The source code of MIX-TPI and the test data are available at: https://github.com/Wolverinerine/MIX-TPI.

γδ T cells and the PD-1/PD-L1 axis: a love-hate relationship in the tumor microenvironment.

Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αß T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.

Deficiency of UCHL1 results in insufficient decidualization accompanied by impaired dNK modulation and eventually miscarriage.

BACKGROUND: Miscarriage is a frustrating complication of pregnancy that is common among women of reproductive age. Insufficient decidualization which not only impairs embryo implantation but disturbs fetomaternal immune-tolerance, has been widely regarded as a major cause of miscarriage; however, the underlying mechanisms resulting in decidual impairment are largely unknown. METHODS: With informed consent, decidual tissue from patients with spontaneous abortion or normal pregnant women was collected to detect the expression profile of UCHL1. Human endometrial stromal cells (HESCs) were used to explore the roles of UCHL1 in decidualization and dNK modulation, as well as the mechanisms involved. C57/BL6 female mice (7-10 weeks old) were used to construct pregnancy model or artificially induced decidualization model to evaluate the effect of UCHL1 on mice decidualization and pregnancy outcome. RESULTS: The Ubiquitin C-terminal hydrolase L1 (UCHL1), as a deubiquitinating enzyme, was significantly downregulated in decidua from patients with miscarriage, along with impaired decidualization and decreased dNKs. Blockage of UCHL1 led to insufficient decidualization and resultant decreased expression of cytokines CXCL12, IL-15, TGF-ß which were critical for generation of decidual NK cells (dNKs), whereas UCHL1 overexpression enhanced decidualization accompanied by increase in dNKs. Mechanistically, the promotion of UCHL1 on decidualization was dependent on its deubiquitinating activity, and intervention of UCHL1 inhibited the activation of JAK2/STAT3 signaling pathway, resulting in aberrant decidualization and decreased production of cytokines associated with dNKs modulation. Furthermore, we found that inhibition of UCHL1 also disrupted the decidualization in mice and eventually caused adverse pregnancy outcome. CONCLUSIONS: UCHL1 plays significant roles in decidualization and dNKs modulation during pregnancy in both humans and mice. Its deficiency indicates a poor pregnancy outcome due to defective decidualization, making UCHL1 a potential target for the diagnosis and treatment of miscarriage.

Pulmonary interstitial lesions in pemphigus mouse model: Verifying pemphigus may not be only limited to skin and mucosa.

Interstitial lung disease (ILD) has been identified as a prevalent complication and significant contributor to mortality in individuals with pemphigus. In this study, a murine model of pemphigus was developed through the subcutaneous administration of serum IgG obtained from pemphigus patients, allowing for an investigation into the association between pemphigus and ILD. Pulmonary interstitial lesions were identified in the lungs of a pemphigus mouse model through histopathology, RT-qPCR and Sircol assay analyses. The severity of these lesions was found to be positively associated with the concentration of IgG in the injected serum. Additionally, DIF staining revealed the deposition of serum IgG in the lung tissue of pemphigus mice, indicating that the subcutaneous administration of human IgG directly impacted the lung tissue of the mice, resulting in damage. This study confirms the presence of pulmonary interstitial lesions in the pemphigus mouse model and establishes a link between pemphigus and ILD.

BTN3A1 expressed in cervical cancer cells promotes Vγ9Vδ2 T cells exhaustion through upregulating transcription factors NR4A2/3 downstream of TCR signaling.

BACKGROUND: Clinical trials have shown that immunotherapy based on Vγ9Vδ2 T cells (Vδ2 T cells) is safe and well-tolerated for various cancers including cervical cancer (CC), but its overall treatment efficacy remains limited. Therefore, exploring the mechanisms underlying the suboptimal efficacy of Vδ2 T cell-based cancer immunotherapy is crucial for enabling its successful clinical translation. METHODS: Tumor samples from CC patients and CC cell line-derived xenograft (CDX) mice were analyzed using flow cytometry to examine the exhausted phenotype of tumor-infiltrating Vδ2 T cells. The interrelationship between BTN3A1 expression and Vδ2 T cells in CC, along with their correlation with patient prognosis, was analyzed using data from The Cancer Genome Atlas (TCGA) database. CC cell lines with BTN3A1 knockout (KO) and overexpression (OE) were constructed through lentivirus transduction, which were then co-cultured with expanded Vδ2 T cells, followed by detecting the function of Vδ2 T cells using flow cytometry. The pathways and transcription factors (TFs) related to BTN3A1-induced Vδ2 T cells exhaustion and the factors affecting BTN3A1 expression were identified by RNA-seq analysis, which was confirmed by flow cytometry, Western Blot, and gene manipulation. RESULTS: Tumor-infiltrating Vδ2 T cells exhibited an exhausted phenotype in both CC patients and CDX mice. BTN3A1 expressed in CC is highly enhancing exhaustion markers, while reducing the secretion of effector molecules in Vδ2 T cells. Blocking TCR or knocking down nuclear receptor subfamily 4 group A (NR4A) 2/3 can reverse BTN3A1-induced exhaustion in Vδ2 T cells. On the other hand, IFN-γ secreted by Vδ2 T cells promoted the expression of BTN3A1 and PD-L1. CONCLUSIONS: Through binding γδ TCRs, BTN3A1 expressed on tumor cells, which is induced by IFN-γ, can promote Vδ2 T cells to upregulate the expression of TFs NR4A2/3, thereby affecting their activation and expression of exhaustion-related molecules in the tumor microenvironment (TME). Therefore, targeting BTN3A1 might overcome the immunosuppressive effect of the TME on Vδ2 T cells in CC.

Marinicella meishanensis sp. nov., a novel Marinicella member isolated from coastal mudflat sediment of Meishan Islandin the East China Sea.

A Gram-negative, rod-shaped, non-motile and strictly aerobic strain, designated NBU2979T, was isolated from a coastal mudflat located on Meishan Island in the East China Sea. Strain NBU2979T grew optimally at 32 °C, with 2.0 % NaCl (w/v) and at pH 7.0-7.5. The predominant fatty acid (>10 %) was iso-C15 : 0. The major polar lipids included phosphatidylglycerol, phosphatidylethanolamine, diphosphatidylglycerol, phosphatidyldimethylethanolamine, phosphatidylcholine, an unidentified glycolipid, two unidentified aminophospholipids, an unidentified phospholipid and an unidentified lipid. The only respiratory quinone was ubiquinone-8. Comparative analysis of 16S rRNA gene sequences showed that strain NBU2979T exhibited highest similarity to Marinicella sediminis F2T (98.0 %), Marinicella marina S1101T (97.5 %), Marinicella litoralis KMM 3900T (96.6 %), Marinicella rhabdoformis 3539T (95.5 %), Marinicella pacifica sw153T (95.2 %) and Marinicella gelatinilytica S6413T (94.9 %). Phylogenetic analyses indicated that strain NBU2979T clustered with the genus Marinicella and was closely related to strain M. sediminis F2T. The average nucleotide identity and digital DNA-DNA hybridization values between strain NBU2979T and related species of genus Marinicella were well below the threshold limit for prokaryotic species delineation. The DNA G+C content of strain NBU2979T was 51.6 mol%. Based on its phenotypic, chemotaxonomic and genotypic data, strain NBU2979T (=KCTC 82911T=MCCC 1K06402T) is considered to be a representative of a novel species in the genus Marinicella, for which the name Marinicella meishanensis sp. nov. is proposed.

Pestanoid A, a Rearranged Pimarane Diterpenoid Osteoclastogenesis Inhibitor from a Marine Mesophotic Zone Chalinidae Sponge-Associated Fungus, Pestalotiopsis sp. NBUF145.

One novel rearranged pimarane diterpenoid, pestanoid A (1), and two reported molecules, nodulisporenones A (2) and B (3), were discovered from Pestalotiopsis sp. NBUF145 fungus associated with a 62 m deep mesophotic ("twilight") zone Chalinidae sponge. The structures of 1-3 were identified by spectrometry, spectroscopy, quantum-chemical calculations, and X-ray crystallography. Compounds 1 and 2 inhibited bone marrow monocyte osteoclastogenesis in vitro with the IC50 values 4.2 ± 0.2 µM and 3.0 ± 0.4 µM, respectively, without observed cytotoxicity. Both 1 and 2 suppressed the receptor activator of NF-kB ligand-induced MAPK and NF-κB signaling by inhibiting the phosphorylation of ERK1/2-JNK1/2-p38 MAPKs and NF-κB nuclear translocation.

Irpetones A and B, Anti-Osteoclastic Heptaketides from a Marine Mesophotic Zone Ircinia Sponge-Associated Fungus Irpex sp. NBUF088.

Chemical investigation of Irpex sp. NBUF088, associated with an Ircinia sp. sponge located at an 84 m deep mesophotic zone, led to the discovery of two new heptaketides, named irpetones A (1) and B (2). Their structures were identified by analysis of spectroscopic data and quantum-chemical calculations. Compound 1 exhibited inhibition against the receptor activator of NF-κB ligand-induced osteoclastogenesis in bone marrow monocytes with an IC50 of 6.3 ± 0.2 µM, causing no notable cytotoxicity. It was also determined that 1 inhibited the phosphorylation of ERK1/2-JNK1/2-p38 MAPKs and the nuclear translocation of NF-κB, consequently suppressing the activation of MAPK and NF-κB signaling pathways induced by the NF-κB ligand.

Medical therapy has similar hemostatic efficacy with endoscopic treatment for PUB patients with adherent clot (FIIb ulcers).

BACKGROUND: Currently, there is no clear consensus on whether medical treatment or endoscopic treatment should be used for peptic ulcer bleeding patients with adherent clot. The aim of this study is to investigate the hemostatic effects of medical treatment, single endoscopic treatment, and combination endoscopic treatment for peptic ulcer bleeding (PUB) patients with adherent clot. METHODS: We retrospectively analyzed PUB patients with adherent clot who underwent endoscopic examination or treatment in our center from March 2014 to January 2023 and received intravenous administration of proton pump inhibitors. Patients were divided into medical treatment (MT) group, single endoscopic treatment (ST) group, and combined endoscopic treatment (CT) group. Subsequently, inverse probability of treatment weighting (IPTW) was performed to calculate the rebleeding rate. RESULTS: A total of 605 eligible patients were included in this study. After IPTW, the rebleeding rate in the MT group on days 3, 7, 14, and 30 were 13.3 (7.3), 14.2 (7.8), 14.5 (7.9), and 14.5 (7.9), respectively; the rebleeding rates in the ST group were 17.4 (5.1), 20.8 (6.1), 20.8 (6.1), and 20.8 (6.1), respectively; the rebleeding rates in the CT group were 0.4 (0.9), 1.7 (3.3), 2.3 (4.5), and 2.3 (4.5), respectively. Although the rebleeding rate in the medical treatment group was higher, there was no significant difference among the three groups on days 3, 7, 14, and 30 (P = 0.132, 0.442, 0.552, and 0.552). CONCLUSIONS: Medical therapy has similar hemostatic efficacy with endoscopic treatment for PUB patients with adherent clot (FIIb ulcers). However, for patients with more risk factors and access to well-equipped endoscopy centers, endoscopic treatment may be considered. The choice of treatment approach should be based on the individual conditions of the patient, as well as other factors such as medical resources available.

Cluster intercalation of aluminum tetrachloride in AlN cathode: Exploration and analysis of aluminum ion batteries.

When chloroaluminate (AlCl4-) serves as the electrolyte, aluminum nitride (AlN) has shown promise as a cathode material in aluminum ion batteries. However, there is currently a lack of research on the mechanisms of charge transfer and cluster intercalation between AlCl4 and AlN cathode materials. Herein, first-principles calculations are employed to investigate the intercalation mechanism of AlCl4 within the AlN cathode. By calculating the formation energies of stage-1-5 AlN-AlCl4 intercalation compounds with the insertion of individual AlCl4 cluster, we found that the structure of the stage-4 intercalation compounds exhibits the highest stability, suggesting that when the clusters begin to intercalate, it is important to start with the formation of the stage-4 intercalation compounds. In the subsequent phases of the charging process (stages 1 and 2), the stabilized structure with four inserted clusters demonstrates two characteristics: the coexistence of standing and lying clusters and the insertion of two standing clusters in an upside-down doubly stacked configuration, which further improve the spatial utilization while maintaining the structural stability. In addition, we infer that a phenomenon of coexisting intercalation compounds with mixed stages will occur in the course of the charging and discharging processes. More importantly, the diffusion barrier of AlCl4 in AlN-AlCl4 intercalation compounds decreases with the reduction of stage number, ensuring the rate performance of batteries. Therefore, we expect that our work will contribute to comprehend the intercalation mechanism of AlCl4 into the AlN cathode materials of aluminum ion batteries, providing guidance for related experimental work.

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study.

Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe3O4_A and Fe3O4_B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe3O4_A and Fe3O4_B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.