Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

直肠癌淋巴结转移的深度神经网络评判研究进展

正目前,临床上对于直肠癌常用的影像评估方法有MRI、螺旋CT、PET-CT、直肠腔内超声(ERUS)等。而MRI作为首选检查方式,对肿瘤位置、浸润深度、淋巴结转移、血管侵犯、环周切缘及周围器官侵犯等方面的评估均具有明显优势~([1-2])。通过MRI诊断淋巴结的方法通常是影像科医师逐层浏览每一幅图像,从中识别淋巴结的形状、界限及密度来判断,这种传统方式耗时较长且存在主观偏倚,导致     

Evaluating the inhibitory potential of Withania somnifera on platelet aggregation and inflammation enzymes: An in vitro and in silico study

Context Withania somnifera (L.) Dunal is traditionally used for treating various ailments, but lacks scientific evaluation.

Objective This study evaluates Withania somnifera (WS) for its effect on platelet activity and inflammatory enzymes.

Materials and methods Aqueous and ethanolic (1:1) leaf extracts were subjected to in vitro indirect haemolytic activity using Naja naja venom, human platelet aggregation was quantified for lipid peroxidation using arachidonic acid (AA) as agonist and 5-lipoxygenase (5-LOX) levels were determined using standard spectrometric assays. Further, molecular docking was performed by the ligand fit method using molegro software package (Molegro ApS, Aarhus, Denmark).

Results The study found that aqueous and ethanol extracts have very negligible effect (15%) with an IC₅₀ value of 13.8?mg/mL on PLA₂ from Naja naja venom. Further, extracts of WS also had very little effect (18%) with an IC₅₀ value of 16.6?mg/mL on malondialdehyde (MDA) formation. However, a 65% inhibition of 5-LOX with an IC₅₀ value of 0.92?mg/mL was observed in 1:1 ethanol extracts. The same was evident from SAR model with the active ingredient withaferin A binding predominantly on Phe 77, Tyr 98, Arg 99, Asp 164, Leu 168, Ser 382, Arg 395, Tyr 396 and Tyr 614 with an atomic contact energy value of??128.96 compared to standard phenidone (?103.61). Thus, the current study validates the application of WS for inflammatory diseases.

Conclusion This study reveals the inhibitory potential of W. somnifera on inflammatory enzymes and platelet aggregation. Thus, WS can serve as a newer, safer and affordable medicine for inflammatory diseases.     

左乙拉西坦治疗小儿癫痫的影响分析

目的研究左乙拉西坦治疗小儿癫痫的疗效以及对智力的影响。方法在本院2017年4月-2019年5月收治的小儿癫痫患儿中选取74例开展研究,按照随机数表法分两组观察组和对照组,观察组37例,对照组37例,对照组采用奥卡西平进行治疗,观察组采用左乙拉西坦进行治疗,对比观察组与对照组组的治疗总有效率和智力评分变化。结果观察组与对照组比较,观察组的治疗总有效率较高,智力评分明显较高,两项对比差异有统计学意义(P <0.05)。结论左乙拉西坦治疗小儿癫痫有较好的治疗效果,治疗总有效率较高,且对患儿的智力有明显的改善作用,在实际临床小儿癫痫的治疗中具有较高的运用价值。     

经食管实时三维超声心动图评价房性心律失常对二尖瓣结构和功能的影响

目的:应用经食管实时三维超声心动图(RT-3D-TEE)技术,探讨房性心律失常对二尖瓣结构和功能的影响.方法:选取2018年6月~2019年6月本院收治的房性心律失常拟行射频消融的患者49例纳入观察组,另外选取21例正常窦性心律者作为对照组,所有患者均行经胸超声心电图(TTE)和经食管实时三维超声心动图(RT-3D-TEE)检查,将两组患者的瓣环投影面积(A2D)、瓣环周长(C3D)、瓣环高度(H)、瓣环前后径(DAP)、瓣环前外侧至后内侧直径(DAIPm)、左室射血分数(LVEF)、左心房前后径(Lad)等参数进行比较,并分别计算对合面积和对合指数,之后采取二项Logistic回归分析或逐步线性回归对各参数及临床因素与对合指数的相关性进行分析.结果:两组患者在LVEF和对合面积方面的比较无明显差异(P>0.05),在A2D、C3D、H、DA、PDAIPm、Lad方面的比较,房性心律失常组患者明显高于正常窦性心律组患者(P<0.05),且观察组患者的对合指数明显降低(P<0.05).将49例观察组患者以不同心律失常类型分为持续性房颤、阵发性房颤、房扑、混合型房性心律失常4个亚组,采用单因素方差分析,发现在LVEF、C3D、Lad、对合指数方面的比较,各亚组间无明显差异(P>0.05).采用二项Logistic回归分析发现,女性是导致对合指数低的危险因素,另外对合指数较低、房性心律失常是导致二尖瓣返流的重要因素.结论:房性心律失常对患者二尖瓣的A2D、C3D、H、DA、PDAIPm、Lad等都会造成较大影响,从而降低对合指数,影响二尖瓣的正常功能,导致二尖瓣返流的发生.     

行为-结构化-关系干预模式对短期住院孤独症谱系障碍儿童的疗效分析

目的 探讨以行为-结构化-关系(BSR)干预模式对短期住院孤独症谱系障碍(ASD)儿童的干预疗效,为改善ASD儿童的预后提供参考依据。方法 选取2015年12月－2016年12月确诊为ASD的2~6岁儿童141例,随机分为治疗组和对照组。治疗组ASD儿童均接受BSR模式的短期课程训练,训练课程包括个别辅导、游戏课、运动课、音乐课等,每天训练时间6 h,持续1个月;对照组ASD儿童处于干预等待,接受随访观察和评估。所有ASD儿童干预前、后均接受儿童心理教育评估(第三版)(PEP-3)来进行各方面能力变化的评估。结果 治疗组、对照组干预前各副测验的原积分差异无统计学意义(P>0.05)。两组ASD儿童干预后认知、语言理解、模仿、情感表达、社会互动、行为特征-非语言、适应行为的原积分比较,差异均有统计学意义(t=2.41、2.02、4.14、3.69、4.42、2.69、2.96,P<0.05);但小肌肉、大肌肉、自理的原积分比较,差异无统计学意义(t=-1.13、-1.05、-0.84,P>0.05)。结论 BSR干预模式能够有效改善短期住院ASD儿童的预后,可推广用于儿童ASD的治疗。     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.