Search

Minimum quantity lubrication (MQL), which considers the cost, sustainability, flexibility, and quality, has been actively explored by scholars. Nanoadditive phases have been widely investigated as atomizing media for MQL, aimed at enhancing the heat transfer and friction reduction performance of vegetable-oil-based biolubricants. However, the industrial application of nano-enhanced biolubricants (NEBL) in grinding wheels and workpiece interfaces as a cooling and lubricating medium still faces serious challenges, which are attributed to the knowledge gap in the current mapping between the properties and grindability of NEBL. This paper presents a comprehensive literature review of research developments in NEBL grinding, highlighting the key challenges, and clarifies the application of blind spots. Firstly, the physicochemical properties of the NEBL are elaborated from the perspective of the base fluid and nanoadditive phase. Secondly, the excellent grinding performance of the NEBL is clarified by its distinctive film formation, heat transfer, and multiple-field mobilization capacity. Nanoparticles with high thermal conductivity and excellent extreme-pressure film-forming properties significantly improved the high-temperature and extreme-friction conditions in the grinding zone. Furthermore, the sustainability of applying small amounts of NEBL to grinding is systematically evaluated, providing valuable insights for the industry. Finally, perspectives are proposed to address the engineering and scientific bottlenecks of NEBL. This review aims to contribute to the understanding of the effective mechanisms of NEBL and the development of green grinding technologies.

Objectives:Despite the development of various cancer treatment methods, chemotherapy remains the most common approach for treating cancer. The risk of tumors acquiring resistance to chemotherapy remains a significant hurdle to the successful treatment of various types of cancer. Therefore, overcoming or predicting multidrug resistance in clinical treatment is essential. The detection of circulating tumor cells (CTCs) is an important component of liquid biopsy and the diagnosis of cancer. This study aims to test the feasibility of single-cell bioanalyzer (SCB) and microfluidic chip technology in identifying patients with cancer resistant to chemotherapy and propose new methods to provide clinicians with new choices. Methods:In this study, we used rapidly isolated viable CTCs from the patient blood samples method combined with SCB technology and a novel microfluidic chip, to predict whether patients with cancer are resistant to chemotherapy. SCB and microfluidic chip were used to select single CTCs, and the accumulation of chemotherapy drug was fluorescently measured in real time on these cells in the absence and presence of permeability-glycoprotein inhibitors. Results:Initially, we successfully isolated viable CTCs from the blood samples of patients. Additionally, the present study accurately predicted the response of 4 lung cancer patients to chemotherapeutic drugs. In addition, the CTCs of 17 patients with breast cancer diagnosed at Zhuhai Hospital of Traditional Chinese and Western Medicine were assessed. The results indicated that 9 patients were sensitive to chemotherapeutic drugs, 8 patients were resistant to a certain degree, and only 1 was completely resistant to chemotherapy. Conclusion:The present study indicated that the SCB technology could be used as a prognostic assay to evaluate the CTCs response to available drugs and guide physicians to treatment options that are most likely to be effective.

Pleural effusion (PE) is a common manifestation of tuberculosis (TB) and malignant tumors but tuberculous PE (TPE) is difficult to distinguish from malignant PE (MPE), especially by noninvasive detection indicators. This study aimed to find effective detection indices in blood and PE for differentiating TB from a malignant tumor. A total of 815 patients who were diagnosed with TB or cancer in Hubei Shiyan Taihe Hospital from 2014 to 2017 were collected. Amongst them, 717 were found to have PE by thoracoscopy. Clinical characteristics, patients’ blood parameters and PE indicator information were summarized for analysis. Patients with MPE had higher percentages to be bloody and negative of Rivalta test in PE than those with TPE. For clinical indicators, comparison of the specific parameters in blood showed that 18 indicators were higher in the TPE group than in the MPE group. By contrast, 12 indicators were higher in the MPE group than in the TPE group (P < .01). In addition, in PE tests, 3 parameters were higher in the TPE group, whereas other 4 parameters were higher in the MPE group (P < .01). Then, for clinical diagnosing practice, ROC analysis and principal component analysis were applied. The top 6 relevant indicators with area under curve over 0.70 were screened out as follows: hydrothorax adenosine dehydrogenase (pADA, 0.90), hydrothorax high-sensitivity C reactive protein (0.79), percentage of blood monocyte (sMONp, 0.75), blood high-sensitivity C reactive protein (sHsCRP, 0.73), erythrocyte sedimentation rate (0.71) and blood D-dimer (0.70). Moreover, logistic regression model revealed that a specific combination of 3 biomarkers, namely, pADA, sMONp and sHsCRP, could enhance the distinguishment of TB from malignant tumor with PE (area under curve = 0.944, 95% confidence interval = 0.925–0.964). The diagnostic function of the top single marker pADA in patients from different groups was analyzed and it was found to maintain high specificity and sensitivity. The 6 indicators, namely, pADA, hydrothorax high-sensitivity C reactive protein, sMONp, sHsCRP, sESR and blood D-dimer, showed significant diagnostic value for clinicians. Further, the combination of pADA, sMONp and sHsCRP has high accuracy for differential diagnosis for the first time. Most interestingly, the single marker pADA maintained high specificity and sensitivity in patients with different statuses and thus has great value for rapid and accurate diagnosis of suspected cases.

Exact Method (EX) has been recently proposed to handle the dynamic sensor bias estimation based on the local track estimates at different times, which only apply to fixed platform sensors. On the basis of EX algorithm, an new algorithm is presented to derive the dynamic sensor bias estimation in networked 3-D mobile sensor system based on the local track estimates at different times, which is called MEX algorithm for short. To testify the correctness and validity of the proposed algorithm, the simulations were carried out. And the result shows that the MEX algorithm can effectively estimate sensor measurement biases and attitude angle biases.

Secondary amyloid A amyloidosis, a lethal complication, is induced when acute or chronic infection coexists with over-secretion of the serum amyloid A 1 (SAA1) protein and deposition in key internal organs. Previously, using the whole-exome sequencing method, we identified a novel deleterious mutation SAA1.2in rheumatoid arthritis (RA) patients. However, the role of SAA1 in RA pathogenesis and its complications remains unknown. The purpose of this study was to determine the pathogenetic roles of SAA1 protein isoforms in RA progression. We modified an experimental adenovirus infection protocol to introduce SAA1.2gene alleles into the knee joints of mice and used SAA1.3and SAA1.5as controls. Micro-computed tomography analysis was applied to determine changes in bone morphology and density. Immunohistochemical (IHC) analysis, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and real-time polymerase chain reaction (RT-PCR) were used to investigate disease progression and cytokine alterations in the course of adenoviral SAA-induced knee joint inflammation and bone destruction. We found that the arthritis-inducing effect of SAA1.2transcription in the knee joints and mutant SAA1 protein secretion in blood resulted in the stimulation of immune responses, leading to CD8+T cell and pro-inflammatory cytokine elevation, such as interleukin (IL)-6, IL-22, matrix metalloproteinase (MMP)-3, MMP-9, with subsequent synovial inflammation and bone destruction. These findings indicate that SAA1 protein isoforms, particularly SAA1.2, play a significant role in the induction and progression of RA and may have potential value in the early diagnosis and severity prediction of RA.

Based on the theory of spherical distributions, a multivariate version of 's T3-plot (MT3-plot) to detect non-multinormality is proposed. New critical bands for the MT3-plot based on a Kolmogorov-Smirnov type statistic are recommended to substitute Ghosh's critical bands in multivariate cases. Monte Carlo study on the choice of the projection directions gives the conclusion that the power of the MT3-plot based on the proposed Kolmogorov-Smirnov type statistic against severe non-multinormality is generally high regardless of high dimension if the projection direction is properly chosen. An application of the MT3-plot to two real-life data sets verifies the efficiency of the MT3 in finding evidence of non-multinormality in high-dimensional data analysis.

•Early diagnosis could improve lung cancer survival rate.•The availability of blood-based screening could increase lung cancer patient uptake.•An interdisciplinary mechanism combines metabolomics and machine learning methods.•Metabolic biomarkers could be potential screening biomarkers for early detection of lung cancer.•Naïve Bayes is recommended as an exploitable tool for early lung tumor prediction.