A new machine learning model to predict the prognosis of cardiogenic brain infarction.

Cardiogenic cerebral infarction (CCI) is a disease in which the blood supply to the blood vessels in the brain is insufficient due to atherosclerosis or stenosis of the coronary arteries in the patient's heart, which leads to neurological deficits. To predict the pathogenic factors of cardiogenic cerebral infarction, this paper proposes a machine learning based analytical prediction model. 494 patients with CCI who were hospitalized for the first time were consecutively included in the study between January 2017 and December 2021, and followed up every three months for one year after hospital discharge. Clinical, laboratory and imaging data were collected, and predictors associated with relapse and death in CCI patients at six months and one year after discharge were analyzed using univariate and multivariate logistic regression methods, meanwhile established a new machine learning model based on the enhanced moth-flame optimization (FTSAMFO) and the fuzzy K-nearest neighbor (FKNN), called BITSAMFO-FKNN, which is practiced on the dataset related to patients with CCI. Specifically, this paper proposes the spatial transformation strategy to increase the exploitation capability of moth-flame optimization (MFO) and combines it with the tree seed algorithm (TSA) to increase the search capability of MFO. In the benchmark function experiments FTSAMFO beat 5 classical algorithms and 5 recent variants. In the feature selection experiment, ten times ten-fold cross-validation trials showed that the BITSAMFO-FKNN model proved actual medical importance and efficacy, with an accuracy value of 96.61%, sensitivity value of 0.8947, MCC value of 0.9231, and F-Measure of 0.9444. The results of the trial showed that hemorrhagic conversion and lower LVDD/LVSD were independent risk factors for recurrence and death in patients with CCI. The established BITSAMFO-FKNN method is helpful for CCI prognosis and deserves further clinical validation.

Effectiveness of Histopathological Examination of Ultrasound-guided Puncture Biopsy Samples for Diagnosis of Extrapulmonary Tuberculosis.

Objective: To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis (EPTB). Methods: This study was conducted at the Shanghai Public Health Clinical Center. A total of 115 patients underwent ultrasound-guided puncture biopsy, followed by MGIT 960 culture (culture), smear, GeneXpert MTB/RIF (Xpert), and histopathological examination. These assays were performed to evaluate their effectiveness in diagnosing EPTB in comparison to two different diagnostic criteria: liquid culture and composite reference standard (CRS). Results: When CRS was used as the reference standard, the sensitivity and specificity of culture, smear, Xpert, and histopathological examination were (44.83%, 89.29%), (51.72%, 89.29%), (70.11%, 96.43%), and (85.06%, 82.14%), respectively. Based on liquid culture tests, the sensitivity and specificity of smear, Xpert, and pathological examination were (66.67%, 72.60%), (83.33%, 63.01%), and (92.86%, 45.21%), respectively. Histopathological examination showed the highest sensitivity but lowest specificity. Further, we found that the combination of Xpert and histopathological examination showed a sensitivity of 90.80% and a specificity of 89.29%. Conclusion: Ultrasound-guided puncture sampling is safe and effective for the diagnosis of EPTB. Compared with culture, smear, and Xpert, histopathological examination showed higher sensitivity but lower specificity. The combination of histopathology with Xpert showed the best performance characteristics.

Optimization of a Ge2Sb2Te5-Based Electrically Tunable Phase-Change Thermal Emitter for Dynamic Thermal Camouflage.

Controlling infrared thermal radiations can significantly improve the environmental adaptability of targets and has attracted increasing attention in the field of thermal camouflage. Thermal emitters based on Ge2Sb2Te5 (GST) can flexibly change their radiation energy by controlling the reversible phase transition of GST, which possesses fast switching speed and low power consumption. However, the feasibility of the dynamic regulation of GST emitters lacks experimental and simulation verification. In this paper, we propose an electrically tunable thermal emitter consisting of a metal-insulator-metal plasmonic metasurface based on GST. Both optical and thermal simulations are conducted to optimize the structural parameters of the GST emitter. The results indicate that this emitter possesses large emissivity tunability, wide incident angle, polarization insensitivity, phase-transition feasibility, and dynamic thermal camouflage capability. Therefore, this work proposes a reliable optimization method to design viable GST-based thermal emitters. Moreover, it provides theoretical support for the practical application of phase-change materials in dynamic infrared thermal camouflage technology.

Potassium diformate alleviated inflammation of IPEC-J2 cells infected with EHEC.

Potassium diformate (KDF) is a kind of formate, which possesses the advantages of antimicrobial activity, growth promotion and preventing diarrhea in weaned piglets. However, the researches of KDF in animal production mostly focused on apparent indexes such as growth performance and the mechanisms of KDF on intestinal health have not been reported. Thus, porcine small intestinal epithelial cells (IPEC-J2) infected with Enterohemorrhagic Escherichia coli (EHEC) was used to investigate the role of KDF on alleviating intestinal inflammation in this study. The 0.125 mg/mL KDF treated IPEC-J2 cells for 6 h and IPEC-J2 cells challenged with 5 × 107 CFU/mL EHEC for 4 h were confirmed as the optimum concentration and time for the following experiment. The subsequent experiment was divided into four groups: control group (CON), EHEC group, KDF group, KDF+EHEC group. The results showed that KDF increased the cell viability and the gene expression levels of SGLT3 and TGF-ß, while decreased the content of IL-1ß compared with the CON group. The cell viability and the gene expressions of SGLT1, SGLT3, GLUT2, Claudin-1, Occludin and TGF-ß, and the protein expression of ZO-1 in EHEC group were lower than those in CON group, whereas the gene expressions of IL-1ß, TNF, IL-8 and TLR4, and the level of phosphorylation NF-кB protein were increased. Pretreatment with KDF reduced the content of IgM and IL-1ß, the gene expressions of IL-1ß, TNF, IL-8 and TLR4 and the level of phosphorylation NF-кB protein, and increased the gene expression of TGF-ß and the protein expression of Occludin in IPEC-J2 cells infected EHEC. In conclusion, 0.125 mg/mL KDF on IPEC-J2 cells for 6 h had the beneficial effects on ameliorating the intestinal inflammation because of reduced pro-inflammatory cytokines and enhanced anti-inflammatory cytokines through regulating NF-кB signaling pathway under the EHEC challenge.

Improving the multi-functionality of optical tweezers with FPGA integration.

The development of optical tweezers aims to extend their operating function and pattern. However, excessive programming can lead to a decrease in the system's operating speed and introduce bugs or data transmission delays. In this study, we present a time-shared optical tweezers system that allows for parallel operation of multiple functions. To enable efficient data transmission, we employ a queue structure and a buffer. To assess the system's performance, we utilize a biological sample in conjunction with the optical tweezers system and scanning imaging technique. We quantify the trapping parameter while concurrently running power stabilization programs. As a result, the standard deviation of the measured stiffness is reduced by 60% in the x and y directions and 30% in the z direction, indicating a significant improvement in calibration precision. Throughout the program execution, the system maintains an operating rate of 110 kHz, and the data are continuously updated in real time on the host. The system's performance demonstrates its potential for quantification and morphological reconstruction of biological samples.