Association between Traumatic Subarachnoid Hemorrhage and Acute Respiratory Failure in Moderate-to-Severe Traumatic Brain Injury Patients.

Acute respiratory failure (ARF) with a high incidence among moderate-to-severe traumatic brain injury (M-STBI) patients plays a pivotal role in worsening neurological outcomes. Traumatic subarachnoid hemorrhage (tSAH) is highly prevalent in M-STBI, which is associated with significant adverse outcomes. In this retrospective cohort study, we aimed to explore the association between the severity of the tSAH and ARF in the M-STBI population. A total of 771 subjects were reviewed. Clinical and neuroimaging data of M-STBI patients were retrospectively collected, and ARF was ascertained retrospectively based on their electronic medical record. The degree of tSAH was classified according to Fisher's criteria, and the grade of tSAH was dichotomized to a low Fisher grade (Fisher grade 1-2) and a high Fisher grade (Fisher grade 3-4). After exclusion procedures, the data of 695 M-STBI patients were analyzed. A total of 284 (30.8%) had a high Fisher grade on admission. The overall rate of ARF within 48 h upon admission was 34.4% (239/695); it was 29.5% (142/481) and 46.3% (99/214) for the low and high Fisher groups, respectively. In a full cohort, a high Fisher grade was associated with ARF after adjusting for age, gender, GCS, smoking history, comorbidities, multiple injuries, characteristics of TBI, and pulmonary factors (OR 1.78; 95% CI, 1.11-2.85, p = 0.016). This result remained robust in the comparisons after PSM (71/132, 42.8% vs. 53/132, 31.9%; OR, 1.59; 95% CI, 1.02-2.49, p = 0.042). A high Fisher SAH grade exposure on admission is associated with ARF in M-STBI patients.

Machine Learning Model for Predicting Acute Respiratory Failure in Individuals With Moderate-to-Severe Traumatic Brain Injury.

Background: There is a high incidence of acute respiratory failure (ARF) in moderate or severe traumatic brain injury (M-STBI), worsening outcomes. This study aimed to design a predictive model for ARF. Methods: Adult patients with M-STBI [3 ≤ Glasgow Coma Scale (GCS) ≤ 12] with a definite history of brain trauma and abnormal head on CT images, obtained from September 2015 to May 2017, were included. Patients with age >80 years or <18 years, multiple injuries with TBI upon admission, or pregnancy (in women) were excluded. Two models based on machine learning extreme gradient boosting (XGBoost) or logistic regression, respectively, were developed for predicting ARF within 48 h upon admission. These models were evaluated by out-of-sample validation. The samples were assigned to the training and test sets at a ratio of 3:1. Results: In total, 312 patients were analyzed including 132 (42.3%) patients who had ARF. The GCS and the Marshall CT score, procalcitonin (PCT), and C-reactive protein (CRP) on admission significantly predicted ARF. The novel machine learning XGBoost model was superior to logistic regression model in predicting ARF [area under the receiver operating characteristic (AUROC) = 0.903, 95% CI, 0.834-0.966 vs. AUROC = 0.798, 95% CI, 0.697-0.899; p < 0.05]. Conclusion: The XGBoost model could better predict ARF in comparison with logistic regression-based model. Therefore, machine learning methods could help to develop and validate novel predictive models.

[Study on Immunophenotypes and Gene of Acute Lymphoblastic Leukemia--Review].

Transplantation-associated thrombotic microangiopathy (TA-TMA) is one of the fatal complications of hematopoietic stem cell transplantation(HSCT). The pathogenesis of TA-TMA has not been fully elucidated. The latest researches show that the abnormal activation of the complement system may lead to widespread endothelial injury which may play an important role in the pathogenesis of this disease. Incontrotable hypertension, proteinuria, increase of soluble C5b-9 concentration and early pericardial effusion are the risk factors of TA-TMA . In this review, the latest advances of pathogenesis, early diagnosis, treatment and other aspects of the progress of TA-TMA are summarized, so as to provide new ideas to early diagnosis and treatment in TA-TMA.

Self-Assembled Curved Macroporous Photonic Crystal-Based Surfactant Detectors.

Surfactants are extensively used as detergents, dispersants, and emulsifiers. Thus, wastewater containing high-concentration surfactants discharged to the environment pose a serious threat to the ecosystem. Unfortunately, conventional detection methods for surfactants suffer from the use of sophisticated instruments and cannot perform detections for various surfactants by a single analysis. The article reports the development of simple and sensitive surfactant detection using doctor-blade-coated three-dimensional curved macroporous photonic crystals on a cylindrical rod. The photonic crystals exhibit different hydrophobicities at various angular positions after surface modification. The penetration of aqueous surfactant solutions in the interconnected macropores causes red-shift as well as reduction in amplitude in the optical stop bands, resulting in surfactant detection with visible readout. The correlation between the surface tension, as well as the solution-infiltrated angular position, and the concentration of aqueous surfactant solutions has also been investigated in this study.

Self-Assembled Hierarchical Arrays for Colored Retroreflective Coatings.

This study reports a self-assembly technology for fabricating retroreflection coatings with hierarchical nano-/microstructures, which are inspired by the binary periodic structures found in the compound eyes of insects. Silica colloidal crystals of adjustable thicknesses are assembled on encountering glass microbeads using a Langmuir-Blodgett-like approach in a layer-by-layer manner. The as-assembled hierarchical structures exhibit a brilliant color caused by Bragg diffraction from the crystalline lattice of silica colloidal crystals on glass microbeads. The resultant coating is capable of reflecting light in the opposite direction of the incident light. Moreover, the dependence of the silica particle size, the colloidal crystal thickness, and the incident angle on the retroreflective properties are investigated in this study.

[Using Excess Activated Sludge Treated 4-Chlorophenol Contained Waste Water to Cultivate Chlorella vulgaris].

Using different rations of sludge extracts and supernate from 4-Chlorophenol (4-CP) simulated wastewater's excess sludge after centrifugation to cultivate the Chlorella vulgaris to achieve the goal of excess sludge utilization together with chlorella cultivating. The experiments were performed in 500 mL flasks with different rations of sludge extracts & BG-11 and supernate & BG-11 in a light growth chamber respectively. Number of algal cells, Chlorophyll, enzyme activity, oil and water total nitrogen (TN), total phosphorus (TP), total organic carbon (TOC), toxicity index were investigated. Result showed that the nutrition supplies and toxicity in the excess sludge were removed efficiently via Chlorella vulgaris, the removal rates of TN and TP were at least 40% and 90% respectively; After 10 days cultivation, the density growth of 50% sludge extracts was 20 times higher of the beginning while its chlorophyll content was lower than that of the blank group. Sludge extracts could promote the proliferation of algae, but were not conducive to the synthesis of chlorophyll. The quantity of SOD in per cell showed Chlorella vulgaris gave a positive response via stimulation from toxicant in sludge extracts and supernate. The best time for collecting chlorella vulgaris was the fifth day of cultivation, taking neutral oil accumulation as the evaluating indicator for its utilization combined with the removal of supplies and toxicity.

Epidemiological studies of esophageal cancer in the era of genome-wide association studies.

Esophageal cancer (EC) caused about 395000 deaths in 2010. China has the most cases of EC and EC is the fourth leading cause of cancer death in China. Esophageal squamous cell carcinoma (ESCC) is the predominant histologic type (90%-95%), while the incidence of esophageal adenocarcinoma (EAC) remains extremely low in China. Traditional epidemiological studies have revealed that environmental carcinogens are risk factors for EC. Molecular epidemiological studies revealed that susceptibility to EC is influenced by both environmental and genetic risk factors. Of all the risk factors for EC, some are associated with the risk of ESCC and others with the risk of EAC. However, the details and mechanisms of risk factors involved in the process for EC are unclear. The advanced methods and techniques used in human genome studies bring a great opportunity for researchers to explore and identify the details of those risk factors or susceptibility genes involved in the process of EC. Human genome epidemiology is a new branch of epidemiology, which leads the epidemiology study from the molecular epidemiology era to the era of genome wide association studies (GWAS). Here we review the epidemiological studies of EC (especially ESCC) in the era of GWAS, and provide an overview of the general risk factors and those genomic variants (genes, SNPs, miRNAs, proteins) involved in the process of ESCC.