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The epidemic of 2019 novel coronavirus, later named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still gradually spreading worldwide. The nucleic acid test or genetic sequencing serves as the gold standard method for confirmation of infection, yet several recent studies have reported false-negative results of real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). Here, we report two representative false-negative cases and discuss the supplementary role of clinical data with rRT-PCR, including laboratory examination results and computed tomography features. Coinfection with SARS-COV-2 and other viruses has been discussed as well.

Threshold switching devices are of increasing importance for a number of applications including solid-state memories and neuromorphic circuits. Their non-linear characteristics are thought to be associated with a spontaneous (occurring without an apparent external stimulus) current flow constriction but the extent and the underlying mechanism are a subject of debate. Here we use Scanning Joule Expansion Microscopy to demonstrate that, in functional layers with thermally activated electrical conductivity, the current spontaneously and gradually constricts when a device is biased into the negative differential resistance region. We also show that the S-type negative differential resistance I – V characteristics are only a subset of possible solutions and it is possible to have multiple current density distributions corresponding to the same value of the device voltage. In materials with steep dependence of current on temperature the current constriction can occur in nanoscale devices, making this effect relevant for computing applications. Today the phenomenon underlying threshold switching of Oxide-based resistive memories is an unresolved debate. Here, the authors report that the TaOx-based conductive filament formation, the current density and temperature are not-uniform distributions and electric field domains are not required.

Cervical spondylosis is one of the most common degenerative diseases, seriously affecting life quality. Unlike diseases with explicit lesions like cancer, hydroncus, or fracture, the degeneration of the cervical spine cannot be explicitly detected from the appearance of medical images, requiring extensive experience of doctors to interpret subtle clues. However, the extremely high incidence of cervical spondylosis coincides with a serious shortage of experienced doctors and uneven distribution of medical resources, hindering early diagnosis. We propose a cascade-ensemble deep learning framework for cervical spondylosis diagnosis. The framework integrates vertebral body detection and degenerative diagnosis through a cascading architecture, and jointly trains an ensemble of degenerative indicators in a multi-task learning manner. We demonstrate that deep learning models are more sensitive to distance and position based indicators than angle based ones. In intervertebral stenosis analysis, our method achieves comparable performance to senior radiologists and clinicians, with much faster diagnostic speed. Cervical spondylosis is a highly prevalent degenerative disease that lacks visible lesions on medical images, making its diagnosis heavily reliant on scarce expert experience. Here the authors show a cascade-ensemble deep learning framework that achieves expert-level accuracy in diagnosing cervical degeneration by integrating multi-modal imaging data and analyzing key clinical indicators

Objective. Transforaminal endoscopic lumbar discectomy (TELD) is an effective treatment for patients with lumbar disc herniation (LDH) with failure of conservative treatment. However, defects in the annulus fibrosus after TELD usually lead to a recurrence of LDH. Platelet-rich plasma (PRP) injection has shown promising potential for the repair of injured tissues. The combination of TELD and PRP injection has rarely been reported. Hence, this study aimed to evaluate the effectiveness, disc remodeling, and recurrence rate of LDH in TELD with or without PRP in LDH treatment. Methods. A total of 108 consecutive patients who underwent TELD were prospectively registered between July 2018 and December 2019 (https://clinicaltrials.gov/ct2/show/ChiCTR1800017228). Fifty-one and fifty-seven patients underwent TELD with PRP injections and TELD only, respectively. The visual analog scale (VAS) score for back and leg pain, Oswestry Disability Index (ODI), and MacNab criteria were evaluated, and perioperative complications were documented. The disc protrusion, spinal cross-sectional area (SCSA), and disc height were measured on MRI and evaluated preoperatively, postoperatively, and at regular follow-up. Results. All patients were followed up. Clinical improvement was noted in both groups. There were statistical differences in the VAS scores of back and leg pain and ODI between the two groups at 3 months, 6 months, and 1 year follow-up (P<0.05); the improvement in the PRP group was significant. The disc protrusion and SCSA on MRI in the PRP group showed better improvement, with lower recurrence rate, than that in the control group at the final follow-up (P<0.05). No adverse events were reported in our study following PRP injection. Conclusion. Our study showed that TELD with PRP injection was a safe and effective treatment for patients with LDH in the medium and long-term follow-up. PRP injection was beneficial for disc remodeling after endoscopic discectomy and decreased the recurrence of LDH.

Unmanned aerial vehicle (UAV) detection has the advantages of flexible deployment and no casualties. It has become a force that cannot be ignored in the battlefield. Scientific and efficient mission planning can help improving the survival rate and mission completion rate of the UAV search in dynamic environments. Towards the mission planning problem of UAV collaborative search for multi-types of time-sensitive moving targets, a search algorithm based on hybrid layered artificial potential fields algorithm (HL-APF) was proposed. This method consists of two parts, a distributed artificial field algorithm and a centralized layered algorithm. In the improved artificial potential field (IAPF), this paper utilized a new target attraction field function which was segmented by the search distance to quickly search for dynamic targets. Moreover, in order to solve the problem of repeated search by the UAV in a short time interval, a search repulsion field generated by the UAV search path was proposed. Besides, in order to solve the unknown target search and improve the area coverage, a centralized layered scheduling algorithm controlled by the cloud server (CS) was added. CS divides the mission area into several sub-areas, and allocates UAV according to the priority function based on the search map. The CS activation mechanism can make full use of prior information, and the UAV assignment cool-down mechanism can avoid the repeated assignment of the same UAV. The simulation results show that compared with the hybrid artificial potential field and ant colony optimization and IAPF, HL-APF can significantly improve the number of targets and mission area coverage. Moreover, comparative experiment results of CS mechanism proved the necessity of setting CS activation and cool-down for improving the search performance. Finally, it also verified the robustness of the method under the failure of some UAVs.

Abnormal expression of long non-coding RNA often contributes to unrestricted growth of cancer cells. Long non-coding RNA XIST expression is upregulated in several cancers; however, its modulatory mechanisms have not been reported in hepatocellular carcinoma. In this study, we found that XIST expression was significantly increased in hepatocellular carcinoma tissues and cell lines. XIST promoted cell cycle progression from the G1 phase to the S phase and protected cells from apoptosis, which contributed to hepatocellular carcinoma cell growth. In addition, we revealed that there was reciprocal repression between XIST and miR-139-5p. PDK1 was identified as a direct target of miR-139-5p. We proposed that XIST was responsible for hepatocellular carcinoma cell proliferation, and XIST exerted its function through the miR-139-5p/PDK1 axis.

Since its first outbreak, Coronavirus Disease 2019 (COVID-19) has been rapidly spreading worldwide and caused a global pandemic. Rapid and early detection is essential to contain COVID-19. Here, we first developed a deep learning (DL) integrated radiomics model for end-to-end identification of COVID-19 using CT scans and then validated its clinical feasibility. We retrospectively collected CT images of 386 patients (129 with COVID-19 and 257 with other community-acquired pneumonia) from three medical centers to train and externally validate the developed models. A pre-trained DL algorithm was utilized to automatically segment infected lesions (ROIs) on CT images which were used for feature extraction. Five feature selection methods and four machine learning algorithms were utilized to develop radiomics models. Trained with features selected by L1 regularized logistic regression, classifier multi-layer perceptron (MLP) demonstrated the optimal performance with AUC of 0.922 (95% CI 0.856–0.988) and 0.959 (95% CI 0.910–1.000), the same sensitivity of 0.879, and specificity of 0.900 and 0.887 on internal and external testing datasets, which was equivalent to the senior radiologist in a reader study. Additionally, diagnostic time of DL-MLP was more efficient than radiologists (38 s vs 5.15 min). With an adequate performance for identifying COVID-19, DL-MLP may help in screening of suspected cases.

Background The long non-coding RNAs (lncRNAs) have participated in the promotion of hepatocellular carcinoma (HCC) initiation and progression. Nevertheless, the biological role and underlying mechanism of LINC01287 in HCC has never been reported. Methods The TGCA database was used to explore the abnormal expression of lncRNAs in HCC. Real-time PCR and in situ hybridization assays were used to examine the expression of LINC01287 in HCC tissues. The clinicopathological characteristics of HCC patients in relation to LINC01287 expression were then analyzed. Infection of cells with the si-LINC01287 lentiviral vector was performed to down-regulate LINC01287 expression in HCC cells. MTT and colony formation assays were performed to examine cell growth ability, and FACS analysis was performed to examine the cell cycle and apoptosis. A Boyden assay was used to examine HCC cell invasion ability, and RNA immunoprecipitation tested the interaction between LINC01287 and miR-298. A luciferase reporter assay was used to examine whether STAT3 was a direct target of miR-298, and chromatin immunoprecipitation (ChIP) was used to examine the potential binding of c-jun to the miR-298 promoter. Results We revealed that the expression of LINC01287 was increased in HCC cell lines, as well as tissues. Knockdown of LINC01287 decreased HCC cell growth and invasion both in vitro and in vivo. LINC01287 can negatively regulate miR-298 expression by acting as a ceRNA. miR-298 directly targeted STAT3 and inhibited its expression. LINC01287 exerted its function via the miR-298/STAT3 axis in HCC. Interestingly, STAT3 elevated LINC01287 expression via c-jun, which bound to the LINC01287 promoter. A feedback loop was also discovered between LINC01287 and the miR-298/STAT3 axis. Conclusions Our data indicated that LINC01287 played an oncogenic role in HCC growth and metastasis and that this lncRNA might serve as a novel molecular target for the treatment of HCC.

The time for smoke gas to reach a smoke detector would depend on its structural characteristics. However, previous studies have neglected to explore this issue. In this paper, three structural variables of a cylindrical smoke detector with a cover are chosen, and the response surface method is used to carry out the experimental design. Furthermore, the incidence point velocity and center point velocity are calculated using the computational fluid dynamics simulation, and the alarm time is obtained using a homemade device. The three parameters that influence the outcomes are then examined to obtain empirical formulas and the best solutions. Comparatively, we observe that the smoke ingress effect is most significantly influenced by the top cover height. After optimization, the incidence point velocity is increased by 115.94 %, the center point velocity is increased by 119.64 %, the alarm time is reduced by 68.57 %, and the gas flowability performance is noticeably improved.

Recent studies indicate a significant upregulation of gasdermin D (GSDMD) in acute kidney injury (AKI), a severe medical condition characterized by high morbidity and mortality globally. In this study, we identified and validated the therapeutic effects of small molecule inhibitors targeting the GSDMD pathway for AKI treatment. Using a drug screening assay, we evaluated thousands of small molecules from DrugBank against Lipopolysaccharide (LPS) and Nigericin‐stimulated immortalized bone marrow‐derived macrophages (iBMDMs) to discern GSDMD pathway activators. We simulated AKI in primary renal tubular epithelial cells using hydrogen peroxide (H2O2) exposure. Furthermore, AKI in mouse models was induced via cisplatin and ischemia/reperfusion. Our findings highlight stevioside as a potent GSDMD activator exhibiting minimal toxicity. Experimental results, both in vitro and in vivo, demonstrate stevioside's significant potential in alleviating renal tubular epithelial cell injury and AKI histological damage. After stevioside treatment, a notable decrease in cleaved GSDMD‐N terminal levels was observed coupled with diminished inflammatory factor release. This observation was consistent in both cisplatin‐ and ischemia/reperfusion‐induced AKI mouse models. Collectively, our research suggests that stevioside could be a promising candidate for modulating GSDMD signaling in AKI treatment. Stevioside, a natural compound identified in our screenings, was shown to markedly prevent cisplatin‐induced cell death in HK‐2 cells, exhibiting a clear concentration‐dependent protective effect. Post‐injury treatment with stevioside led to a decrease in GSDMD expression and cleaved GSDMD‐NT levels, curtailing the release of inflammatory cytokines and reducing apoptosis and reactive oxygen species. In AKI mouse models, induced by both cisplatin and ischemia‐reperfusion, stevioside treatment demonstrated significant renal protection, mitigating kidney damage markers, marking the first study to elucidate stevioside's therapeutic potential in AKI through GSDMD pathway inhibition.