Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other common conditions such as common cold and Influenza, making early screening and diagnosis are crucial goals for health practitioners. The aim of the study was to use machine learning (ML), an artificial neural network (ANN) and a simple statistical test to identify SARS-CoV-2 positive patients from full blood counts without knowledge of symptoms or history of the individuals. The dataset included in the analysis and training contains anonymized full blood counts results from patients seen at the Hospital Israelita Albert Einstein, at São Paulo, Brazil, and who had samples collected to perform the SARS-CoV-2 rt-PCR test during a visit to the hospital. Patient data was anonymised by the hospital, clinical data was standardized to have a mean of zero and a unit standard deviation. This data was made public with the aim to allow researchers to develop ways to enable the hospital to rapidly predict and potentially identify SARS-CoV-2 positive patients.We find that with full blood counts random forest, shallow learning and a flexible ANN model predict SARS-CoV-2 patients with high accuracy between populations on regular wards (AUC = 94–95%) and those not admitted to hospital or in the community (AUC = 80–86%). Here, AUC is the Area Under the receiver operating characteristics Curve and a measure for model performance. Moreover, a simple linear combination of 4 blood counts can be used to have an AUC of 85% for patients within the community. The normalised data of different blood parameters from SARS-CoV-2 positive patients exhibit a decrease in platelets, leukocytes, eosinophils, basophils and lymphocytes, and an increase in monocytes.SARS-CoV-2 positive patients exhibit a characteristic immune response profile pattern and changes in different parameters measured in the full blood count that are detected from simple and rapid blood tests. While symptoms at an early stage of infection are known to overlap with other common conditions, parameters of the full blood counts can be analysed to distinguish the viral type at an earlier stage than current rt-PCR tests for SARS-CoV-2 allow at present. This new methodology has potential to greatly improve initial screening for patients where PCR based diagnostic tools are limited.     

miR-375在变应性鼻炎小鼠鼻黏膜上皮细胞凋亡中的调控作用

目的探讨miR-375在变应性鼻炎小鼠鼻黏膜上皮细胞凋亡和炎症反应中的调控作用。方法运用卵清蛋白(OVA)致敏的小鼠变应性鼻炎模型,使用实时定量PCR(qRT-PCR)、蛋白质印迹试验(Western Blot)、酶联免疫吸附试验(ELISA)、免疫组织化学检测鼻黏膜上皮细胞内miR-375、JAK2、细胞凋亡相关蛋白(JAK2蛋白,裂解的蛋白酶3(Cleaved caspase 3),聚[ADP-核糖]聚合酶裂解酶(Cleaved PARP),蛋白酶3(Caspase 3),聚[ADP-核糖]聚合酶(PARP),p-STAT3蛋白,STAT3蛋白和β肌动蛋白(β-actin))和血浆IL-6、TNF-α、IL-10的表达水平。结果miR-375在变应性鼻炎小鼠的鼻黏膜上皮细胞中表达降低,而JAK2表达增高;JAK2蛋白、p-STAT3蛋白和裂解的蛋白酶3均在OVA组表达增高;给OVA致敏的变应性鼻炎小鼠注射miR-375模拟物可以导致血清IL-6、TNF-α的分泌下降,而IL-10分泌增加,该作用可以被带有过表达JAK2的腺病毒感染后而减弱。结论miR-375/JAK2调控通路存在于变应性鼻炎鼻黏膜上皮细胞中,并通过JAK2/STAT3信号通路调控细胞的凋亡和炎症反应,miR-375在变应性鼻炎的病程中有保护性机制。     

IDS 基因同义突变致黏多糖贮积症Ⅱ型一家系报告

目的探讨黏多糖贮积症Ⅱ型(MPSⅡ)的临床表现及基因变异。方法分析1例MPSⅡ先证者及其家系成员的临床资料、基因检测及艾杜糖-2-硫酸酯酶活性检测结果。结果先证者,男,15岁,体格发育障碍、听力下降。影像学示脑室系统扩大,椎骨、肋骨等骨发育不良。尿黏多糖阳性。IDS的8号外显子同义突变(c.1122CT)。先证者及其母亲的艾杜糖-2-硫酸酯酶活性分别为0、6.96 nmol/(4h·mg)。诊断为MPSⅡ。家系中有6例患者及1例疑似者,全为男性,除先证者外,还有1例存活,其余4例夭折。1例疑似者于孕7月余时产前诊断脑积水终止妊娠。检测到5例女性携带者。结论先证者经艾杜糖-2-硫酸酯酶活性检测和基因检测确诊为MPSⅡ,发现多名女性致病基因携带者及男性患者。     

Beta-naphthoflavone inhibits LPS-induced inflammation in BV-2 cells via AKT/Nrf-2/HO-1-NF-κB signaling axis

Numerous studies have shown that over-activation of microglia could cause neuroinflammation and release pro-inflammatory mediators, which could result in neurodegenerative diseases, like Parkinson’s disease, Alzheimer’s disease etc. Beta-naphthoflavone (BNF) has anti-oxidant and anti-inflammatory effects in borderline tissues, but BNF has not been reported the effect associated with neuroinflammation. Therefore, the purpose of this experiment is to inquiry the impact and mechanism of BNF on neuroinflammation. The results indicated that BNF significantly inhibited the production of pro-inflammatory mediators (inducible nitric-oxide synthase (iNOS), Cyclooxygenase-2 (COX-2), tumor necrosis factor-α (TNF-α) andinterleukin-6 (IL-6)) in LPS-exposed BV-2 cells. Analysis of western blot results found that BNF accelerated the activation of AKT/Nrf-2/HO-1 signaling pathway and suppressed NF-κB pathway activation. Further study showed that BNF inhibited activation of NF-κB pathway via promoting HO-1, and SnPP IX (a HO-1 inhibitor) could inhibit anti-inflammatory function of BNF. We also found that BNF reduced the apoptosis rate of Human neuroblastoma cells (SHSY5Y) and mouse hippocampal neuron cell line (HT22) by inhibiting release of inflammatory mediators in LPS-exposed BV2 cells. In a word, our results suggested that BNF could inhibit inflammatory response via AKT/Nrf-2/HO-1-NF-κB signaling axis in BV-2 cells and exerts neuroprotective impact via inhibiting the activation of BV2 cells.     

Cetuximab enhances the efficiency of irinotecan through simultaneously inhibiting the MAPK signaling and ABCG2 in colorectal cancer cells

BackgroundThe present study sought to investigate the combined effects of cetuximab and irinotecan on colorectal cancer cells as well as the mechanisms underlying their anti-cancer effects.Material and methodsHigh performance liquid chromatography, Hoechst staining assay, and western blotting analysis were used to detect intracellular drug concentrations, cell apoptosis, and protein expression in the presence of cetuximab, irinotecan, and the combination of both.ResultsCetuximab was found to increase intracellular concentrations of irinotecan as well as cytotoxicity by inhibiting the epidermal growth factor receptor and, by extension, the downstream RAS-RAF-MEK-ERK signaling pathway. Cetuximab therefore induced apoptosis and improved the effect of irinotecan in colorectal cancer cells. It was also shown that cetuximab inhibited the drug efflux activity of ABCG2. In combination with irinotecan, cetuximab can both significantly induce cell apoptosis by inhibiting the RAS-RAF-MEK-ERK signaling pathway and improve the effects of irinotecan by decreasing drug efflux through the inhibition of ABCG2.ConclusionThese features contribute to its anti-cancer potential.