Abstract Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of ...cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis of pancreatic cancer (PC) patients. Gene expression data and patient clinical profiles were sourced from The Cancer Genome Atlas (TCGA-PAAD: Pancreatic Adenocarcinoma) and the International Cancer Genome Consortium (ICGC-PACA: Pancreatic Ductal Adenocarcinoma). Non-cancerous pancreatic tissue gene expression data were obtained from the Genotype-Tissue Expression (GTEx) project. The R package was used to construct anoikis-related PC prognostic models, which were later validated with the ICGC-PACA database. Survival analyses demonstrated a poorer prognosis for patients in the high-risk group, consistent across both TCGA-PAAD and ICGC-PACA datasets. A nomogram was designed as a predictive tool to estimate patient mortality. The study also analyzed tumor mutations and immune infiltration across various risk groups, uncovering notable differences in tumor mutation patterns and immune landscapes between high- and low-risk groups. In conclusion, this research successfully developed a prognostic model centered on anoikis-related genes, offering a novel tool for predicting the clinical trajectory of PC patients.
Coronavirus disease 2019 (COVID‐19) has spread worldwide. To date, no specific drug for COVID‐19 has been developed. Thus, this randomized, open‐label, controlled clinical trial (ChiCTR2000029853) ...was performed in China. A total of 20 mild and common COVID‐19 patients were enrolled and randomly assigned to receive azvudine and symptomatic treatment (FNC group), or standard antiviral and symptomatic treatment (control group). The mean times of the first nucleic acid negative conversion (NANC) of ten patients in the FNC group and ten patients in the control group are 2.60 (SD 0.97; range 1–4) d and 5.60 (SD 3.06; range 2–13) d, respectively (p = 0.008). The mean times of the first NANC of four newly diagnosed subjects in the FNC group and ten subjects in the control group are 2.50 (SD 1.00; range 2–4) d and 9.80 (SD 4.73; range 3–19) d, respectively (starting from the initial treatment) (p = 0.01). No adverse events occur in the FNC group, while three adverse events occur in the control group (p = 0.06). The preliminary results show that FNC treatment in the mild and common COVID‐19 may shorten the NANC time versus standard antiviral treatment. Therefore, clinical trials of FNC treating COVID‐19 with larger sample size are warranted.
Azvudine treatment in the persistently mild and common COVID‐19 patients may shorten the nucleic acid negative conversion time versus standard antiviral treatment, regardless of whether the patients are newly diagnosed or have previously received routine treatment. Azvudine treatment could improve the lung function of patients. Moreover, the adverse events are not observed in patients receiving azvudine.
•Insulation defect identification for DC XLPE cable by considering PD aging.•PD characters significantly varied with different aging phases.•Without considering the time-sequence feature, the ...recognition rate was 72.93%.•The BRNN-based recognition model improves the recognition rate to 93.71%.
Crosslinked polyethylene (XLPE) insulated power cable has a wide application in flexible DC transmission areas. PD measurement is considered as an effective tool to detect and even identify insulation defects for XLPE cable. In this paper, four kinds of insulation defects were constructed, i.e. inner semi-conductive layer breakage, internal air cavity defect, insulation surface scratch defect and outer semi-conductive layer creepage, and PD aging experiments for each type of defect were conducted at DC voltage. It was found that PD characters significantly varied with different aging phases, leading to the fluctuation of PD fingerprint parameters. Without taking the time-sequence feature of PD data into consideration, the recognition rate was only 72.93% in the usage of fingerprint parameters. For the aim to improve recognition effect, a model based on bidirectional recurrent neural networks (BRNN) algorithm was proposed. By dividing the PD process into several stages, the model takes both the fingerprint parameter and the stage information as input, in which the output of each stage is not only related to itself, but also influenced by the preceding and subsequent inputs. Therefore, the model can reflect the time-sequence characteristic of PD. With the dataset acquired by four insulation defects testing, the recognition rate of the BRNN model is 93.71%. It is proved that the BRNN-based recognition model effectively eliminate the influence of insulation aging on the PD fingerprint of XLPE cable, and improve the identification efficiency to a certain extent.
Early fault detection (EFD) of rolling bearings aims at detecting the early symptoms of faults by monitoring small deviations of health states. Accurate EFD enables predictive maintenance and ...contributes to the stability of mechanical systems. In recent years, machine learning based methods have shown impressive performance on EFD. Most of the current machine learning‐based methods assume the availability for a large amount of data. However, in practice, the authors may only have a very limited amount of training data, which makes it hard to learn a reliable machine learning model. To address this concern, in this work, the authors propose to tackle EFD via meta learning. Specifically, the authors first formulate EFD as a few‐shot learning problem and then propose to tackle this problem with a metric‐based meta learning method. Furthermore, ensemble learning is further leveraged to improve the detection robustness. For the proposed method, the distribution difference from the working conditions and the bearings are considered. The experimental results on two bearing datasets show that the proposed method can achieve better EFD performance, that is, detecting incipient faults earlier while bringing in lower false alarms, compared with several frequently used EFD methods.
Considering the distribution drift problem along with the limited available data in early fault detection, the EFD task can be formulated to a Few‐shot Anomaly Detection problem. To solve this problem, a metric‐based meta learning method named Dynamic Relation Network with Voting Mechanism (DRNVM) is proposed. Furthermore, a dynamic support set updating strategy and ensemble learning are leveraged to improve the detection robustness.
Background. Excessive proliferation and activation of B cells, resulting in the production of various autoantibodies, is a crucial link and significant feature of the pathogenesis of systemic lupus ...erythematosus (SLE), as well as the pathological basis of systemic multiorgan damage. However, whether exosomes derived from human umbilical cord mesenchymal stem cells (hucMSCs-Exo) are involved in the immune regulation of SLE has not been clarified. Objectives. Therefore, our study aimed to investigate the efficacy of hucMSCs-Exo for treating SLE. Methods. hucMSCs-Exo and peripheral blood mononuclear cells (PBMCs) of SLE patients were cocultured in vitro, and B cell apoptosis, activation, proliferation, and inflammation levels were detected by flow cytometry. Subsequently, the expression level of miR-155 in B lymphocytes of SLE patients was detected by qRT-PCR, and the target gene relationship between miR-155 and SHIP-1 was found through bioinformatics and dual luciferase activity experiments, which verified the inhibition of miR-155 in B lymphocytes of SLE patients to regulate immunity. Results. We found that hucMSCs-Exo promoted B cell apoptosis, prevented B cell overactivation, and reduced inflammation. MicroRNA-155 (miR-155) has a powerful regulatory function in B cells. It was demonstrated that hucMSCs-Exo acts synergistically with miR-155 inhibitors to target SHIP-1 to B cells more effectively than exosomes alone. Conclusion. Our results provide insight into how hucMSCs-Exo regulates autoimmunity in patients with lupus and suggest targeting miR-155 for autoimmunity while protecting immunity.
Chronic myelogenous leukemia (CML) is characterized by the constitutive activation of Bcr-Abl tyrosine kinase. Bcr-Abl-T315I is the predominant mutation that causes resistance to imatinib, cytotoxic ...drugs, and the second-generation tyrosine kinase inhibitors. The emergence of imatinib resistance in patients with CML leads to searching for novel approaches to the treatment of CML. Gambogic acid, a small molecule derived from Chinese herb gamboges, has been approved for phase II clinical trial for cancer therapy by the Chinese Food and Drug Administration (FDA). In this study, we investigated the effect of gambogic acid on cell survival or apoptosis in CML cells bearing Bcr-Abl-T315I or wild-type Bcr-Abl.
CML cell lines (KBM5, KBM5-T315I, and K562), primary cells from patients with CML with clinical resistance to imatinib, and normal monocytes from healthy volunteers were treated with gambogic acid, imatinib, or their combination, followed by measuring the effects on cell growth, apoptosis, and signal pathways. The in vivo antitumor activity of gambogic acid and its combination with imatinib was also assessed with nude xenografts.
Gambogic acid induced apoptosis and cell proliferation inhibition in CML cells and inhibited the growth of imatinib-resistant Bcr-Abl-T315I xenografts in nude mice. Our data suggest that GA-induced proteasome inhibition is required for caspase activation in both imatinib-resistant and -sensitive CML cells, and caspase activation is required for gambogic acid-induced Bcr-Abl downregulation and apoptotic cell death.
These findings suggest an alternative strategy to overcome imatinib resistance by enhancing Bcr-Abl downregulation with the medicinal compound gambogic acid, which may have great clinical significance in imatinib-resistant cancer therapy.
Chemical compositions of particulate matter (PM) from traffic emissions vary by region and with time. Therefore, it is necessary to obtain local mobile source profiles of PM to support regional ...researches for vehicle emission control policy, source apportionment modeling, etc. In this study, PM_(2.5) and PM_(10) samples were collected from a highway tunnel in Xi’an in northwestern China. The chemical composition, specifically, the OC, EC, water-soluble ions, and elements, was analyzed in detail to (1) provide local PM profiles for a mixed vehicle fleet, (2) identify the origins of different elements in the tunnel environment, and (3) determine the associated factors influencing the profiles. The PM_(2.5) profiles in the tunnel were identified as OC (34.10%), EC (11.96%), water-soluble ions (18.22%), and elements (27.73%), while the PM_(10) profiles included OC (28.48%), EC (8.59%), water-soluble ions (14.17%), and elements (33.36%), respectively. The origins of the elements in the tunnel were classified into three categories by the receptor modeling approach: resuspended road dust and brake wear, vehicle exhaust and tire wear, and tailpipe emissions from diesel vehicles (DV). The mass fractions of OC, EC, and elements originating from resuspended road dust and brake wear were mainly affected by vehicle driving conditions (i.e., uphill/downhill and speed), whereas the mass content of bromine (Br) was influenced by the proportion of DV in the fleet.
Air traffic control (ATC) performance is important to ensure flight safety and the sustainability of aviation growth. To better evaluate the performance of ATC, this paper introduces the HFACS-BN ...model (HFACS: Human factors analysis and classification system; BN: Bayesian network), which can be combined with the subjective information of relevant experts and the objective data of accident reports to obtain more accurate evaluation results. The human factors of ATC in this paper are derived from screening and analysis of 142 civil and general aviation accidents/incidents related to ATC human factors worldwide from 1980 to 2019, among which the most important 25 HFs are selected to construct the evaluation model. The authors designed and implemented a questionnaire survey based on the HFACS framework and collected valid data from 26 frontline air traffic controllers (ATCO) and experts related to ATC in 2019. Combining the responses with objective data, the noisy MAX model is used to calculate the conditional probability table. The results showed that, among the four levels of human factors, unsafe acts had the greatest influence on ATC Performance (79.4%), while preconditions for safe acts contributed the least (40.3%). The sensitivity analysis indicates the order of major human factors influencing the performance of ATC. Finally, this study contributes to the literature in terms of methodological development and expert empirical analysis, providing data support for human error management intervention of ATC in aviation safety.
Proteasomes are attractive emerging targets for anti-cancer therapies. Auranofin (Aur), a gold-containing compound clinically used to treat rheumatic arthritis, was recently approved by US Food and ...Drug Administration for Phase II clinical trial to treat cancer but its anti-cancer mechanism is poorly understood. Here we report that (i) Aur shows proteasome-inhibitory effect that is comparable to that of bortezomib/Velcade (Vel); (ii) different from bortezomib, Aur inhibits proteasome-associated deubiquitinases (DUBs) UCHL5 and USP14 rather than the 20S proteasome; (iii) inhibition of the proteasome-associated DUBs is required for Aur-induced cytotoxicity; and (iv) Aur selectively inhibits tumor growth in vivo and induces cytotoxicity in cancer cells from acute myeloid leukemia patients. This study provides important novel insight into understanding the proteasome-inhibiting property of metal-containing compounds. Although several DUB inhibitors were reported, this study uncovers the first drug already used in clinic that can inhibit proteasome-associated DUBs with promising anti-tumor effects.
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