scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics.

Single-cell RNA sequencing has achieved massive success in biological research fields. Discovering novel cell types from single-cell transcriptomics has been demonstrated to be essential in the field of biomedicine, yet is time-consuming and needs prior knowledge. With the unprecedented boom in cell atlases, auto-annotation tools have become more prevalent due to their speed, accuracy and user-friendly features. However, existing tools have mostly focused on general cell-type annotation and have not adequately addressed the challenge of discovering novel rare cell types. In this work, we introduce scNovel, a powerful deep learning-based neural network that specifically focuses on novel rare cell discovery. By testing our model on diverse datasets with different scales, protocols and degrees of imbalance, we demonstrate that scNovel significantly outperforms previous state-of-the-art novel cell detection models, reaching the most AUROC performance(the only one method whose averaged AUROC results are above 94%, up to 16.26% more comparing to the second-best method). We validate scNovel's performance on a million-scale dataset to illustrate the scalability of scNovel further. Applying scNovel on a clinical COVID-19 dataset, three potential novel subtypes of Macrophages are identified, where the COVID-related differential genes are also detected to have consistent expression patterns through deeper analysis. We believe that our proposed pipeline will be an important tool for high-throughput clinical data in a wide range of applications.

In vivo therapy of osteosarcoma using anion transporters-based supramolecular drugs.

BACKGROUND: Osteosarcoma represents a serious clinical challenge due to its widespread genomic alterations, tendency for drug resistance and distant metastasis. New treatment methods are urgently needed to address those treatment difficulties in osteosarcoma to improve patient prognoses. In recent years, small-molecule based anion transporter have emerged as innovative and promising therapeutic compound with various biomedical applications. However, due to a lack of efficient delivery methods, using ion transporters as therapeutic drugs in vivo remains a major challenge. RESULT: Herein, we developed self-assembled supramolecular drugs based on small-molecule anion transporters, which exhibited potent therapeutic effect towards osteosarcoma both in vitro and in vivo. The anion transporters can disrupt intracellular ion homeostasis, inhibit proliferation, migration, epithelial-mesenchymal transition process, and lead to osteosarcoma cell death. RNA sequencing, western blot and flow cytometry indicated reprogramming of HOS cells and induced cell death through multiple pathways. These pathways included activation of endoplasmic reticulum stress, autophagy, apoptosis and cell cycle arrest, which avoided the development of drug resistance in osteosarcoma cells. Functionalized with osteosarcoma targeting peptide, the assembled supramolecular drug showed excellent targeted anticancer therapy against subcutaneous xenograft tumor and lung metastasis models. Besides good tumor targeting capability and anti-drug resistance, the efficacy of the assembly was also attributed to its ability to regulate the tumor immune microenvironment in vivo. CONCLUSIONS: In summary, we have demonstrated for the first time that small-molecule anion transporters are capable of killing osteosarcoma cells through multiple pathways. The assemblies, OTP-BP-L, show excellent targeting and therapeutic effect towards osteosarcoma tumors. Furthermore, the supramolecular drug shows a strong ability to regulate the tumor immune microenvironment in vivo. This work not only demonstrated the biomedical value of small-molecule anion transporters in vivo, but also provided an innovative approach for the treatment of osteosarcoma.

Nanocomposite Polymer Colloids Prepared via Emulsion Polymerization and Stabilized Using Polydopamine-Coated Silica Particles.

Polymer/inorganic colloidal nanocomposites can be prepared via Pickering emulsion polymerization (PEP); however, this process usually requires the use of surfactants, auxiliary comonomers, and volatile organic compounds. Herein, we report a versatile and efficient method for synthesizing stable monodisperse polymer/silica colloidal nanocomposite particles via PEP. First, silica nanoparticles were modified by depositing a multifunctional polydopamine (PDA) film. The outermost PDA film could enhance the precipitation of oligomeric polymer radicals on the silica surface, which is crucial for the preparation of stable polymer/inorganic colloidal nanocomposites via PEP. Notably, this PDA modification approach can employ different initiator systems, such as cationic initiators and redox initiator couples, and can be applied to various monomers and monomer pairs (St, St/nBA, MMA, MMA/nBA, Vac, Vac/nBA). The influence of the concentration and size of polydopamine-coated silica (SiO2@PDA) on the colloidal nanocomposite was investigated. Increasing the diameter of SiO2@PDA and decreasing the concentration of SiO2@PDA both lead to the formation of larger nanocomposite particles. Considering its wide applicability, the proposed PDA modification approach can be applied to other functional inorganic particles to prepare multifunctional polymer/inorganic nanocomposite particles.

Abrasivity database of different genetic rocks based on CERCHAR Abrasivity Test.

Rock abrasivity is one of the main factors affecting the wear of rock-cutting tools, which is usually quantified by the CERCHAR Abrasivity Index (CAI). Researchers and engineers study tool wear and predict tool life based on the CAI of rocks. However, there is still a lack of a dataset on rock properties, especially the abrasivity of various rocks. This paper reports the abrasive dataset of 10 kinds of rocks, including sedimentary rocks, metamorphic rocks, and igneous rocks, with the aid of the CERCHAR Abrasivity Test and digital measurement techniques. The dataset comprises rock abrasivity data, point cloud data for visualization, scratch photos, CERCHAR Abrasivity Test force data, and mechanical properties (uniaxial compressive strength) of rock samples. This dataset facilitates future research on rock abrasivity and rock-cutting tool wear.

Citronellol-Based Long-Lasting Antibacterial Cotton Fabrics without Bacterial Resistance.

Antibacterial cotton helps prevent the growth and spread of harmful microorganisms, reduces the risk of infection, and has a prolonged service life by reducing bacterial degradation. However, most antibacterial agents used are toxic to humans and the environment. Citronellol-poly(N,N-dimethyl ethyl methacrylate) (CD), a highly effective antibacterial polymer, is synthesized from natural herbal essential oils (EOs). CD exhibited efficient, rapid bactericidal activity against Gram-positive, Gram-negative, and drug-resistant bacteria. Citronellol's environmental benignity makes CDs less hemolytic. Notably, negligible drug resistance developed after 15 bacterial subcultures. The CD-treated cotton fabric displayed better antibacterial performance than AAA-grade antibacterial fabric, even after repeated washing. This study extends the practical application of EOs to antibacterial surfaces and fabrics, which is promising for use in personal care products and medical settings.

Deep Learning From Multiple Noisy Annotators as A Union.

Crowdsourcing is a popular solution for large-scale data annotations. So far, various end-to-end deep learning methods have been proposed to improve the practical performance of learning from crowds. Despite their practical effectiveness, most of them have two major limitations-they do not hold learning consistency and suffer from computational inefficiency. In this article, we propose a novel method named UnionNet, which is not only theoretically consistent but also experimentally effective and efficient. Specifically, unlike existing methods that either fit a given label from each annotator independently or fuse all the labels into a reliable one, we concatenate the one-hot encoded vectors of crowdsourced labels provided by all the annotators, which takes all the labeling information as a union and coordinates multiple annotators. In this way, we can directly train an end-to-end deep neural network by maximizing the likelihood of this union with only a parametric transition matrix. We theoretically prove the learning consistency and experimentally show the effectiveness and efficiency of our proposed method.

Bacteria-targeted photothermal therapy for combating drug-resistant bacterial infections.

Photothermal therapy is an ideal non-invasive treatment for bacterial infections. However, if photothermal agents are unable to target bacteria, they can also cause thermal damage to healthy tissue. This study describes the fabrication of a Ti3C2Tx MXene-based photothermal nanobactericide (denoted as MPP) that targets bacteria by modifying MXene nanosheets with polydopamine and the bacterial recognition peptide CAEKA. The polydopamine layer blunts the sharp edges of MXene nanosheets, preventing their damage to normal tissue cells. Furthermore, as a constituent of peptidoglycan, CAEKA can recognize and penetrate the bacterial cell membrane based on similar compatibility. The obtained MPP exhibits superior antibacterial activity and high cytocompatibility compared to the pristine MXene nanosheets. In vivo studies showed that MPP colloidal solution under 808 nm NIR light can effectively treat a subcutaneous abscess caused by multi-drug resistant bacterial infection without adverse effects.

Development and evaluation of an ultra-wide bandwidth based electronic hand hygiene monitoring system.

BACKGROUND: A large variety of electronic hand hygiene monitoring systems (EHHMS) are being developed and applied in health care settings. Monitoring hand hygiene (HH) opportunity at bed-level has been the key technical challenge. Accuracy evaluation needs more attention as the prerequisite upon widespread acceptance and adoption. METHODS: For the first time, we explored, debugged and upgraded an EHHMS based on ultra-wide bandwidth (UWB) which can obtain HH opportunities at bed-level. The real-time positioning and electronic fence of UWB technology was applied for EHHMS. The accuracy of EHHMS was compared with the simultaneous manual direct observations in real-world clinical setting. Sensitivity and specificity were calculated for EHHMS capturing HH action and opportunity. RESULTS: Two generations of EHHMS were constructed. For the first generation, the system properly recorded 84% and 78% of the pre-identified HH actions and opportunities performed by experimenters. For the second generation, sensitivity and specificity of the system capturing HH action were 89% (84.83-92.36) and 100% (98.26-100.00), respectively. For capturing HH opportunity, the system showed the sensitivity and specificity of 86.52% (82.52-89.89) and 88.10% (84.14-91.36)), respectively. CONCLUSION: The EHHMS based on UWB could accurately identify HH action and opportunity with equivalent accuracy compared with simultaneous direct observation.

Investigation on the potential adverse outcome pathway of the sensitive endpoint for nephrotoxicity induced by gardenia yellow based on an integrated strategy using bioinformatics analysis and in vitro testing validation.

To explore the potential the adverse outcome pathway of Gardenia Yellow (GY)-induced sensitive endpoint for nephrotoxicity, an integrated strategy was applied in the present study. Using bioinformatic analysis, based on the constructed Protein-protein interaction networks, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis on the core target network were performed to illustrate the potential gene targets and signal pathways. Then, the most enriched pathway was validated with Cell counting kit-8 assays and Western blot analysis in embryonic kidney epithelial 293 cell models. According to the findings, GY may interact with 321 targets related to the endpoint. The five targets on the top ranking in the PPI network were STAT3, SRC, HRAS, AKT1, EP300. Among them, PI3K/Akt was the most enriched pathway. In vitro testing showed that GY exerted a proliferative effect on the cell variability in a dose-dependent manner. GY at concentration of 1000 µg/ml and stimulation for 30 min can significantly enhance the expression of phosphorylated Akt. Thus, after the quantitative weight of evidence evaluation, Akt phosphorylation induced PI3K/Akt activation was speculated as a molecular initiating event leading to a proliferative and inflammatory response in renal tubular epithelial cells.

Low-Temperature Photothermal Therapy Based on Borneol-Containing Polymer-Modified MXene Nanosheets.

Noninvasive photothermal therapy (PTT) is an emerging strategy for eliminating multidrug-resistant (MDR) bacteria that achieve sterilization by generating temperatures above 50 °C; however, such a high temperature also causes collateral damage to healthy tissues. In this study, we developed a low-temperature PTT based on borneol-containing polymer-modified MXene nanosheets (BPM) with bacteria-targeting capabilities. BPM was fabricated through the electrostatic coassembly of negatively charged two-dimensional MXene nanosheets (2DM) and positively charged quaternized α-(+)-borneol-poly(N,N-dimethyl ethyl methacrylate) (BPQ) polymers. Integrating BPQ with 2DM improved the stability of 2DM in physiological environments and enabled the bacterial membrane to be targeted due to the presence of a borneol group and the partially positive charge of BPQ. With the aid of near-infrared irradiation, BPM was able to effectively eliminate methicillin-resistant Staphylococcus aureus (MRSA) and Escherichia coli (E. coli) through targeted photothermal hyperthermia. More importantly, BPM effectively eradicated more than 99.999% (>5 orders of magnitude) of MRSA by localized heating at a temperature that is safe for the human body (≤40 °C). Together, these findings suggest that BPM has good biocompatibility and that membrane-targeting low-temperature PTT could have great therapeutic potential against MDR infections.