Partial Multilabel Learning Using Noise-Tolerant Broad Learning System With Label Enhancement and Dimensionality Reduction.

Partial multilabel learning (PML) addresses the issue of noisy supervision, which contains an overcomplete set of candidate labels for each instance with only a valid subset of training data. Using label enhancement techniques, researchers have computed the probability of a label being ground truth. However, enhancing labels in the noisy label space makes it impossible for the existing partial multilabel label enhancement methods to achieve satisfactory results. Besides, few methods simultaneously involve the ambiguity problem, the feature space's redundancy, and the model's efficiency in PML. To address these issues, this article presents a novel joint partial multilabel framework using broad learning systems (namely BLS-PML) with three innovative mechanisms: 1) a trustworthy label space is reconstructed through a novel label enhancement method to avoid the bias caused by noisy labels; 2) a low-dimensional feature space is obtained by a confidence-based dimensionality reduction method to reduce the effect of redundancy in the feature space; and 3) a noise-tolerant BLS is proposed by adding a dimensionality reduction layer and a trustworthy label layer to deal with PML problem. We evaluated it on six real-world and seven synthetic datasets, using eight state-of-the-art partial multilabel algorithms as baselines and six evaluation metrics. Out of 144 experimental scenarios, our method significantly outperforms the baselines by about 80%, demonstrating its robustness and effectiveness in handling partial multilabel tasks.

Novel HIF-1α Inhibitor AMSP-30m Mitigates the Pathogenic Cellular Behaviors of Hypoxia-Stimulated Fibroblast-Like Synoviocytes and Alleviates Collagen-Induced Arthritis in Rats via Inhibiting Sonic Hedgehog Pathway.

Synovial hypoxia-inducible factor 1α (HIF-1α) is a prospective therapeutic target for rheumatoid arthritis (RA). AMSP-30 m, a novel HIF-1α inhibitor, was reported to have notable anti-arthritic effects in rats with adjuvant-induced arthritis. However, its roles in inhibiting the pathogenic behaviors of fibroblast-like synoviocytes (FLS) and the involved mechanisms remain unknown. Here, AMSP-30 m inhibited proliferation and induced apoptosis in hypoxia-induced RA FLS (MH7A cell line), as evidenced by decreased cell viability, reduced Ki67-positive cells, G0/G1 phase arrest, lowered C-myc and Cyclin D1 protein levels, emergence of apoptotic nuclear fragmentation, raised apoptosis rates, and activation of caspase 3. Furthermore, AMSP-30 m prevented hypoxia-induced increases in pro-inflammatory factor production, MMP-2 activity, migration index, migrated/invasive cells, and actin cytoskeletal rearrangement. In vivo, AMSP-30 m alleviated the severity of rat collagen-induced arthritis (CIA). Mechanically, AMSP-30 m reduced HIF-1α expression and blocked sonic hedgehog (Shh) pathway activation in hypoxia-induced MH7A cells and CIA rat synovium, as shown by declines in pathway-related proteins (Shh, Smo, and Gli-1). Particularly, the combination of Shh pathway inhibitor cyclopamine enhanced AMSP-30 m's inhibitory effects on the pathogenic behaviors of hypoxia-stimulated MH7A cells, whereas the combination of Shh pathway activator SAG canceled AMSP-30 m's therapeutic effects in vitro and in CIA rats, implying a close involvement of Shh pathway inhibition in its anti-arthritic effects. We likewise confirmed AMSP-30 m's anti-proliferative role in hypoxia-induced primary CIA FLS. Totally, AMSP-30 m suppressed hypoxia-induced proliferation, inflammation, migration, and invasion of MH7A cells and ameliorated the severity of rat CIA via inhibiting Shh signaling.

Self-assembled ratiometric sensor for specific detection of hypoxia in living cells based on lanthanide-doped upconversion nanoparticles and gold nanoparticles.

We describes the development of a self-assembled nanoprobe for ratiometric sensing of hypoxia in living cells. The probe, UC-AuNPs, is composed of azo-functionalized upconversion nanoparticles (azo-UCNPs) and gold nanoparticles functionalized withß-cyclodextrin (CD-AuNPs). Under hypoxic conditions, reductases reduce azo derivatives on the UCNPs, leading to detachment of the CD-AuNPs and subsequent fluorescence recovery of the green emission. The ratiometric measurement incorporated into the strategy reduces the impact of external factors and improves sensitivity of the probe. The use of NIR excitation effectively minimizes interference from strong luminescence backgrounds in biosystems. The UC-AuNPs nanoprobe is able to effectively sense and monitor hypoxia conditions in living cells and has the potential to distinguish hypoxia-related diseases from healthy tissue, making it a valuable tool for early clinical diagnosis.

Catalytic probes based on aggregation-induced emission-active Au nanoclusters for visualizing MicroRNA in living cells and in vivo.

Highly sensitive monitoring of cancer-related miRNAs is of great significance for tumor diagnosis. Herein, catalytic probes based on DNA-functionalized Au nanoclusters (AuNCs) were prepared in this work. The aggregation-induced emission-active Au nanoclusters showed an interesting phenomenon of aggregation induced emission (AIE) affected by the aggregation state. Leveraging this property, the AIE-active AuNCs were used to develop catalytic turn-on probes for detecting in vivo cancer-related miRNA based on a hybridization chain reaction (HCR). The target miRNA triggered the HCR and induced aggregation of AIE-active AuNCs, leading to a highly luminescent signal. The catalytic approach demonstrated a remarkable selectivity and a low detection limit in comparison to noncatalytic sensing signals. In addition, the excellent delivery the ability of MnO2 carrier made it possible to use the probes for intracellular imaging and in vivo imaging. Effective in situ visualization of miR-21 was achieved not only in living cells but also in tumors in living animals. This approach potentially offers a novel method for obtaining information for tumor diagnosis via highly sensitive cancer-related miRNA imaging in vivo.

Acetylcholinesterase electrochemical biosensors with graphene-transition metal carbides nanocomposites modified for detection of organophosphate pesticides.

An acetylcholinesterase biosensor modified with graphene and transition metal carbides was prepared to detect organophosphorus pesticides. Cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy were used to characterize the electrochemical catalysis of the biosensor: acetylcholinesterase/chitosan-transition metal carbides/graphene/glassy carbon electrode. With the joint modification of graphene and transition metal carbides, the biosensor has a good performance in detecting dichlorvos with a linear relationship from 11.31 µM to 22.6 nM and the limit of detection was 14.45 nM. Under the premise of parameter optimization, the biosensor showed a good catalytic performance for acetylcholine. Compared to the biosensors without modification, it expressed a better catalytic performance due to the excellent electrical properties, biocompatibility and high specific surface area of graphene, transition metal carbides. Finally, the biosensor exhibits good stability, which can be stored at room temperature for one month without significant performance degradation, and has practical potential for sample testing.

An acetylcholinesterase biosensor with high stability and sensitivity based on silver nanowire-graphene-TiO2 for the detection of organophosphate pesticides.

An electrochemical acetylcholinesterase biosensor based on silver nanowire, graphene, TiO2 sol-gel, chitosan and acetylcholinesterase has been fabricated successfully for the detection of organophosphate pesticides. The outstanding electrical properties of silver nanowires and graphene, and moreover the self-assembly of these two nanomaterials make the biosensor highly sensitive. Simultaneously, the immobilization efficiency of the enzyme is greatly improved by the action of the TiO2 fixed matrix. Under optimum conditions, the biosensor exhibited excellent performance for the detection of dichlorvos with a linearity in the range of 0.036 µM to 22.63 µM and the detection limit was found to be 7.4 nM. The biosensor was highly reproducible and stable during detection and storage.