Expanding the clinical application of OPM-MEG using an effective automatic suppression method for the dental brace metal artifact.

Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5-8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process. The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.

Bronchogenic cysts with infection in the chest wall skin of a 64-year-old asymptomatic patient: A case report.

BACKGROUND: Skin bronchogenic cysts are extremely rare congenital bronchocystic changes caused by the abnormal development of the trachea, bronchial trees or lung buds during the embryonic period. The first case of skin bronchogenic cysts was reported in 1945. Since then, this disease has attracted increasing attention, but due to the low incidence, its pathogenesis is still not clear. CASE SUMMARY: Here, we report another case of skin bronchogenic cysts with infection in a 64-year-old female patient. The patient had no symptoms for more than 60 years until her chest wall was recently found to be swollen, and she felt pain and discomfort. At the same time, secretions were found on the surface of the swelling. Color Doppler ultrasound examination showed abnormal echoes in the soft tissue under the frontal chest wall, suggesting the presence of cysts. Cytological puncture resulted in about 2 mL of pus and showed the presence of more acute inflammatory cells. The final clinical diagnosis was skin cyst with infection, and surgery was carried out. The pathological results obtained after surgery showed that the cystic wall was covered with column-like cilia epithelial cells, and the interstitial structure was partially inundated with inflammatory cells. After a variety of examinations and clinical diagnoses, we finally confirmed that the patient was suffering from bronchogenic cyst. CONCLUSION: This article not only describes the case of an elderly patient with rare skin bronchogenic cysts with infection but also provides a detailed and correct diagnosis and a successful treatment process, which is of great value for the diagnosis and treatment of the disease.

Research on value co-creation mechanism of platform enterprises in digital innovation ecosystem: A case study on Haier HOPE platform in China.

Digital technology has given the innovation subject a new way of value creation, expanded the existing innovation ecosystem theory, and triggered scholars' in-depth thinking on the digital innovation ecosystem. Based on the event system theory and taking Haier's hope platform as a vertical case study, this paper deeply explores the research mechanism of value creation of platform enterprises in the digital innovation ecosystem, and reveals the role and impact of digital innovation ability, openness, and business innovation model on the process of co-creation. The research results show that: in the open connection stage, the platform solves the problem of weakening the advantages of the platform, and improves the innovation efficiency of enterprises by continuously improving the digital innovation ability; in the interactive and iterative stage, the platform carries out open innovation, breaks through the difficulties of platform expansion, and realizes the benign expansion of the platform. In the co-creation stage, the user experience is blocked, and the platform adopts the platform community business model to connect the user relationship and improve the user experience. In the digital innovation ecosystem, platform enterprises gradually form self-organization and self-circulation value co-creation through internal self-construction and external cooperation, and form a data-driven co-creation model.

Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia.

BACKGROUND: Stage T1 nasopharyngeal carcinoma (NPCT1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPCT1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases. METHODS: A total of 91 patients (44 NPCT1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPCT1 and BH. The demarcation of NPCT1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λHU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZeff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. RESULTS: The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPCT1 yielded higher attenuation values on VMI (+) at 40 keV (A40), NIC, λHU, and NZeff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A40, NIC, λHU, and NZeff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%). CONCLUSIONS: The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPCT1 and BH.

Comprehensive analysis of the differential expression profile of microRNAs in rats with spinal cord injury treated by electroacupuncture.

Abnormal microRNA (miRNA) expression has been implicated in spinal cord injury (SCI), but the underlying mechanisms are poorly understood. To observe the effect of electroacupuncture (EA) on miRNA expression profiles in SCI rats and investigate the potential mechanisms involved in this process, Sprague­Dawley rats were divided into sham, SCI and SCI+EA groups (n=6 each). Basso, Beattie and Bresnahan (BBB) scoring and hematoxylin­eosin staining of cortical tissues were used to evaluate spinal cord recovery with EA treatment 21 days post­surgery across the three groups. To investigate miRNA expression profiles, 6 Sprague­Dawley rats were randomly divided into SCI and SCI+EA groups (n=3 in each group) and examined using next­generation sequencing. Integrated miRNA­mRNA­pathway network analysis was performed to elucidate the interaction network of the candidate miRNAs, their target genes and the involved pathways. Behavioral scores suggested that hindlimb motor functions improved with EA treatments. Apoptotic indices were lower in the SCI+EA group compared with the SCI group. It was also observed that 168 miRNAs were differentially expressed between the SCI and SCI+EA groups, with 29 upregulated and 139 downregulated miRNAs in the SCI+EA group. Changes in miRNA expression are involved in SCI physiopathology, including inflammation and apoptosis. Reverse transcription­quantitative PCR measurement of the five candidate miRNAs, namely rno­miR­219a­5p, rno­miR­486, rno­miR­136­5p, rno­miR­128­3p, and rno­miR­7b, was consistent with RNA sequencing data. Integrated miRNA­mRNA­pathway analysis suggested that the MAPK, Wnt and NF­κB signaling pathways were involved in EA­mediated recovery from SCI. The present study evaluated the miRNA expression profiles involved in EA­treated SCI rats and demonstrated the potential mechanism and functional role of miRNAs in SCI in rats.

Hypoxia-inducible gene 2 promotes the immune escape of hepatocellular carcinoma from nature killer cells through the interleukin-10-STAT3 signaling pathway.

BACKGROUND: The study examines the expression and function of hypoxia-inducible gene 2 (HIG2) in hepatocellular carcinoma (HCC) tissues and cells. METHODS: Forty patients with HCC were included in the study. Bioinformatic analysis was used to analyze the clinical relevance of HIG2 expression in HCC tissue samples. Immunohistochemistry was employed to determine the expression of target proteins in tumor tissues. Hepatic HepG2 and SMMC-7721 cells were transfected with HIG2-targeting siRNA with Lipofectamine 2000. qRT-PCR was carried out to determine gene expression levels, while Western blotting was used to determine protein expression. A CCK-8 assay was performed to detect proliferation of cells, while migration and invasion of cells were studied by Transwell assay. Flow cytometry was carried out to detect surface markers and effector molecules in Nature killercells, as well as the killing effect of NK cells. RESULTS: HIG2 expression was upregulated in HCC. Silencing of HIG2 suppressed HCC cell migration and invasion. The killing effect of NK cells on HCC cells was enhanced after HIG2 was silenced in HCC cells. Conditioned media from HIG2-silenced SMMC-7721 cells inhibited the phenotype and function of NK cells. HCC cells with silenced expression of HIG2 modulated the activity of NK cells via STAT3. HIG2 promoted the evasion of HCC cells from killing by NK cells through upregulation of IL-10 expression. CONCLUSION: The study demonstrates that HIG2 activates the STAT3 signaling pathway in NK cells by promoting IL-10 release by HCC cells, thereby inhibiting the killing activity of NK cells, and subsequently promoting the recurrence and metastasis of HCC.