Topical streptomycin irrigation of lesions to prevent postoperative site infections in spinal tuberculosis: a retrospective analysis.

PURPOSE: In spinal tuberculosis surgery, topical administration of drugs to the lesion is a preventive treatment measure. The aim is to achieve better bacterial inhibition and to prevent complications. As one of the most common complications after spinal tuberculosis surgery, many factors can lead to surgical site infection (SSI). No definitive reports of local streptomycin irrigation of the lesion and SSI of spinal tuberculosis have been seen. This study analyzed data related to surgical site infections (SSI) after the treatment of spinal tuberculosis using this regimen. METHODS: In this study, 31 were in the observation group (streptomycin flush) and 34 in the control group (no streptomycin flush). All patients received the same standard of perioperative care procedures. General information, operative time, intraoperative bleeding, ESR and CRP at one week postoperatively, time on antibiotics, total drainage, days in hospital, incision infection rate and secondary debridement rate were compared between the two groups. RESULTS: Patients in both groups completed the surgery successfully. The ESR and CRP levels in the observation group were lower than those in the control group one week after surgery (p < 0.05); the duration of postoperative antibiotics and hospital stay were lower than those in the control group (p < 0.05); the incidence of SSI in the two groups was 5.88% and 6.45% respectively, with no significant difference (p > 0.05). CONCLUSION: The use of topical streptomycin irrigation of the lesion during surgical procedures for spinal tuberculosis had no significant effect on the incidence of SSI, however, it helped to control the level of infection in the postoperative period and reduced the length of time patients had to use postoperative antibiotics and the number of days they stayed in hospital. Future prospective randomised controlled trials in more centres and larger samples are recommended.

TransVG++: End-to-End Visual Grounding With Language Conditioned Vision Transformer.

In this work, we explore neat yet effective Transformer-based frameworks for visual grounding. The previous methods generally address the core problem of visual grounding, i.e., multi-modal fusion and reasoning, with manually-designed mechanisms. Such heuristic designs are not only complicated but also make models easily overfit specific data distributions. To avoid this, we first propose TransVG, which establishes multi-modal correspondences by Transformers and localizes referred regions by directly regressing box coordinates. We empirically show that complicated fusion modules can be replaced by a simple stack of Transformer encoder layers with higher performance. However, the core fusion Transformer in TransVG is stand-alone against uni-modal encoders, and thus should be trained from scratch on limited visual grounding data, which makes it hard to be optimized and leads to sub-optimal performance. To this end, we further introduce TransVG++ to make two-fold improvements. For one thing, we upgrade our framework to a purely Transformer-based one by leveraging Vision Transformer (ViT) for vision feature encoding. For another, we devise Language Conditioned Vision Transformer that removes external fusion modules and reuses the uni-modal ViT for vision-language fusion at the intermediate layers. We conduct extensive experiments on five prevalent datasets, and report a series of state-of-the-art records.

Effects of Arginine-calcium carbonate pretreatment on the remineralizing and bonding performance of phosphorylated dentin.

OBJECTIVES: To evaluate the effects of Arginine-calcium carbonate (Arg-CaCO3) paste treatment of phosphorylated dentin on remineralizing and bonding performance during direct and indirect restorations under pulpal pressure. METHODS: Under simulated pulpal pressure, dentin of healthy third molars were abraded and acid etched for 15s, then randomly divided into 4 groups: negative control group; Arg-CaCO3 group (1min); 2.5% Sodium trimetaphosphate (STMP) group (3min); S-A group, 2.5% STMP + Arg-CaCO3. After 24h, remineralization and dentin tubular occlusion were assessed by Attenuated total reflection fourier transform infrared spectroscopy (ATR-FTIR), Micro-Raman spectroscopy, Vickers hardness, Field-emission scanning electron microscope (FESEM) and Energy X-ray dispersive spectrometer (EDS). The liquid environment was the simulated body fluid (SBF) permeated from dentin tubules due to pulpal pressure. Stick specimens prepared with self-etch dentin adhesive were tested for microtensile bond strength (µTBS) and interfacial silver nanoleakage on both immediate direct restoration and indirect restoration with a 7-day temporary period. Data were analyzed by the Kruskal-Wallis test, Mann-Whitney test, Welch ANOVA or one-way ANOVA and Tukey post hoc test (p < 0.05). RESULTS: The pretreatment of 2.5% STMP with Arg-CaCO3 significantly increased relative mineral content by ATR-FTIR, Raman and FESEM-EDS, simultaneously enhancing dentin tubular occlusion (%) and mechanical property to the most considerable extent. Furthermore, the pretreatment significantly promoted the µTBS of indirect restoration and reduced nanoleakage after 7 days. CONCLUSIONS: The application of Arg-CaCO3 paste on phosphorylated dentin could improve intra- and extra-tubular mineralization and the stability of adhesion interface. CLINICAL RELEVANCE: Without exceeding the amount of conventional tooth preparation, combining 2.5% STMP with Arg-CaCO3 paste before the self-etch bonding system might be a promising clinical strategy to relieve dentin hypersensitivity and strengthen bonding performance efficiently and conveniently.

Molecular Biomarker Exploration of Rituximab plus CHOP Therapy in Real-World Diffuse Large B-Cell Lymphoma Patients.

BACKGROUND: Presently, several classification methods are based on diffuse large B-cell lymphoma (DLBCL), but its clinical application has not yet been testified in Asian populations. METHODS: Twenty-five DLBCL patients were subjected to second-generation gene sequencing (NGS), and retrospective analysis of clinical features of the patients was to explore genotyping and survival prognosis biomarkers. RESULTS: The prevalent mutant genes in DLBCL patients cover myeloid differentiation factor 88 (MyD88) (40%), TP53 (32%), B-cell translocation gene 2 (BTG2) (28%), PIM1 (28%), and CREB-binding protein (CREBBP) (24%) in this study. The classical International Prognostic Index (IPI) scores were associated with progression-free survival (PFS) (HR: 7.52, 95% CI 1.51 - 37.6, p = 0.00393) via univariate analysis. Furthermore, patients with ETS-variant gene 6 (ETV6) (HR: 5.1, 95% CI 0.927 - 28.1, p = 0.0371), platelet-derived growth factor receptor A (PDGFRA) (HR: 4.29, 95% CI 0.824 - 22.3, p = 0.0594), platelet-derived growth factor receptor B (PDGFRB) (HR: 10.8, 95% CI 0.979 - 119, p = 0.0149) was distinctively correlated with poor PFS except for the IPI score. Nevertheless, the mutation of PDGFRA/B gene was not distinct in further multivariate analysis (PFS: HR: 2.72, 95% CI 0.52 - 14.23, p = 0.2369). Additionally, better survival prognosis was in DLBCL patients who did not progress within 12 months (POD12). Ultimately, caspase recruitment domain 11 (CARD11) gene mutations were enriched in patients with primary intranodal tumors, but the prognostic relevance was not discovered. CONCLUSIONS: ETV6 and platelet-derived growth factor receptor (PDGFR)A/B gene mutations are supposed to be potential biomarkers for the prognosis of DLBCL patients via the statistical analysis of this small sample, and POD12 is also expected to be an effective endpoint for efficacy assessment.

ECRG4 acts as a tumor suppressor in nasopharyngeal carcinoma by suppressing the AKT/GSK3ß/ß-catenin signaling pathway.

Nasopharyngeal carcinoma (NPC) is a malignant tumor with a poor prognosis. Studies have shown that esophageal carcinoma related gene 4 (ECRG4) is hypermethylated and significantly downregulated in NPC tissues. However, the role of ECRG4 in NPC, and in particular the underlying molecular mechanism, is largely unclear. In this study, using immunohistochemical staining of ECRG4 in NPC and normal specimens, we confirmed that ECRG4 was downregulated in human NPC tissues. In addition, various biological and molecular studies were carried out and the results showed that ECRG4 exerted anticancer effect in NPC, including inhibiting cell growth, migration, and invasion of NPC cells in vitro. Moreover, restoring ECRG4 expression suppressed the in vivo tumorigenesis of CNE2 cells. ECRG4 inhibited AKT/GSK3ß/ß-catenin signaling, as well as the downstream targets of ß-catenin. LiCl treatment, which reduced GSK3ß phosphorylation and upregulated ß-catenin expression, restored the invasive ability of ECRG4-overexpressing NPC cells. Furthermore, we showed that the DNA methylation inhibitor 5-aza-dC reduced ECRG4 methylation and the invasive ability of negative control cells, but not that of ECRG4-overexpressing cells, suggesting that the inhibitory effect of 5-aza-dC depends on low expression of ECRG4. Collectively, our results demonstrated that ECRG4 downregulation contributed to NPC growth and invasion by activating AKT/GSK3ß/ß-catenin signaling pathway. ECRG4 could be a promising therapeutic target for the treatment of NPC. Supplementary Information: The online version contains supplementary material available at 10.1007/s10616-022-00520-8.

A Practical Application for Quantitative Brain Fatigue Evaluation Based on Machine Learning and Ballistocardiogram.

Brain fatigue is often associated with inattention, mental retardation, prolonged reaction time, decreased work efficiency, increased error rate, and other problems. In addition to the accumulation of fatigue, brain fatigue has become one of the important factors that harm our mental health. Therefore, it is of great significance to explore the practical and accurate brain fatigue detection method, especially for quantitative brain fatigue evaluation. In this study, a biomedical signal of ballistocardiogram (BCG), which does not require direct contact with human body, was collected by optical fiber sensor cushion during the whole process of cognitive tasks for 20 subjects. The heart rate variability (HRV) was calculated based on BCG signal. Machine learning classification model was built based on random forest to quantify and recognize brain fatigue. The results showed that: Firstly, the heart rate obtained from BCG signal was consistent with the result displayed by the medical equipment, and the absolute difference was less than 3 beats/min, and the mean error is 1.30 ± 0.81 beats/min; secondly, the random forest classifier for brain fatigue evaluation based on HRV can effectively identify the state of brain fatigue, with an accuracy rate of 96.54%; finally, the correlation between HRV and the accuracy was analyzed, and the correlation coefficient was as high as 0.98, which indicates that the accuracy can be used as an indicator for quantitative brain fatigue evaluation during the whole task. The results suggested that the brain fatigue quantification evaluation method based on the optical fiber sensor cushion and machine learning can carry out real-time brain fatigue detection on the human brain without disturbance, reduce the risk of human accidents in human-machine interaction systems, and improve mental health among the office and driving personnel.

Transformation of non-small cell lung cancer into small cell lung cancer in a patient with advanced lung cancer: a case report.

Targeted therapy in patients with epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) often fails because of drug resistance. Here, we report a 57-year-old male patient with stage IV small cell lung cancer (SCLC) transformation during targeted therapy. Chest computerized tomography (CT), hematoxylin and eosin histological examination, immunohistochemistry, allele refractory mutation system-based quantitative polymerase chain reaction analysis of EGFR point mutations, and next-generation sequencing were performed for diagnosis and therapeutic efficacy evaluation. A combination of chest CT, histological examination, and immunohistochemistry confirmed the initial NSCLC diagnosis. Next-generation sequencing detected only EGFR exon 19 deletion (ex19del) before treatment and later identified EGFR exon20p.T790M point mutation, EGFR amplification, myc proto-oncogene (MYC) amplification, retinoblastoma 1 (RB1) mutation, and tumor protein 53 (TP53) mutation. Histology and immunohistochemistry revealed transformation from NSCLC to SCLC during treatment, which eventually returned to NSCLC. Drug resistance to targeted therapy for patients with NSCLC frequently occurs because of EGFR exon20p.T790M point mutation, TP53 mutation, RB1 mutation, and MYC amplification. These mutations are also the major determining factors of NSCLC outcomes. Therefore, next-generation sequencing should be performed to confirm drug efficacy during targeted therapy for NSCLC.