针对射程不确定性的质子调强放疗鲁棒优化方法

目的 因治疗精度高、副作用小,质子调强放疗(IMPT)成为放疗领域的研究热点,但其精度对射程变化非常敏感。本研究提出一种针对射程不确定性的IMPT鲁棒优化方法用于减小射程偏差对放疗计划的影响。方法 首先建立鲁棒优化模型,目标函数采用二次型函数表达式,其中包含3种射程:射程增加、射程正常、射程缩短;每种射程对应的器官剂量贡献矩阵采用质子笔形束算法计算得到。对射程偏差进行离散化,每个射程的发生概率基于高斯分布函数得到。最后采用共轭梯度法优化出最优解,最优解使得靶区和危及器官实际剂量分布在射程偏差内尽量达到期望剂量。结果 采用AAPM TG-119号报告的3套模拟例题测试本研究方法的有效性:鼻咽癌病例、前列腺病例和“C”型病例。与常规IMPT优化结果对比,发现该方法对射程不确定性的敏感性更低。射程发生偏差时,鼻咽癌病例和前列腺病例的靶区和危及器官基本达到期望剂量,“C”型病例的靶区高剂量覆盖率和危及器官保护都有了提高。结论 针对射程不确定性,该方法可得到更高的靶区覆盖率,同时降低危及器官剂量。     

苯扎贝特治疗儿童ApoE Tokyo(Arg25Cys)突变型脂蛋白肾病1例

脂蛋白肾病(Lipoprotein glomerulopathy,LPG),1989年首次由日本学者Saito报道,LPG主要累及肾脏,且以肾小球病变为主[1]。几乎所有患者均有不同程度的蛋白尿,多数表现为肾病综合征,少数表现为轻微蛋白尿和镜下血尿,部分患者伴有不同程度的贫血及高血压,血脂异常易被忽略为肾病综合征的低蛋白血症所致。载脂蛋白E(apolipoprotein E,ApoE)增高是LPG血脂改变的主要特点[2-3]。LPG为一种与脂质代谢紊乱密切相关的肾脏疾病,目前世界范围内有报道的病例不足200例,儿童报道仅10余例[2]。本病进展缓慢,临床常误诊为原发性肾病综合征[4]。因此,为增强对LPG的认识,提高诊治水平,现分析1例确诊的儿童LPG临床资料,总结LPG的临床特点、诊断、治疗及预后。     

乌头地上部分非二萜生物碱类成分研究

目的对毛茛科乌头属药用植物乌头Aconitum carmichaelii地上部分进行化学成分研究。方法乌头干燥的茎叶用甲醇回流提取,所得的浸膏用1.5%HCl溶解,醋酸乙酯萃取得总粗提取物。粗提物用各种柱色谱进行分离纯化,经光谱数据(~1H-NMR、~(13)C-NMR、MS)进行结构鉴定。结果从乌头地上部分分离得到15个化合物,分别鉴定为3-羧基-吲哚(1)、corchoionol C(2)、β-谷甾醇-3-O-β-D-葡萄糖苷-6′-棕榈酸酯(3)、松脂素(4)、(+)-N-formylnorglaucine(5)、oxoglaucidaline(6)、海罂粟碱(7)、(+)-cataline(8)、山柰酚-7-O-α-L-鼠李糖苷(9)、山柰酚-3-O-β-(2″-乙酰基)-半乳糖苷(10)、megastigmane(11)、山柰酚-7-O-α-L-阿拉伯糖苷(12)、山柰酚-3-O-β-D-吡喃木糖苷(13)、山柰酚-3-O-β-D-葡萄糖苷(14)、槲皮素-3-O-β-D-半乳糖苷(15)。结论化合物1～15均为首次从该植物的地上部分中分离得到,其中化合物1～3、5、6、8～15为首次从乌头中分离得到。     

A Broad Learning System with Ensemble and Classification Methods for Multi-step-ahead Wind Speed Prediction

Cognitive Computation - Short-term wind speed prediction plays a significant role in the management of large-scale wind power plants. However, wind speed prediction is extremely complex and...     

A comparison of the relationships between psychosocial factors,occupational strain,and work ability among 4 ethnic teacher groups in China

The present study compared the level of occupational strain and work ability among Han, Hui, Uygur, Hui, and Kazakh teachers, and explored ethnic differences based on the associations of psychosocial factors at work, occupational strain, and work ability. A cross-sectional survey was conducted among 2,941 teachers in primary and secondary schools in Xinjiang Province, China. Psychosocial factors, occupational strain, and work ability were measured using the Occupation Stress Inventory—Revised Edition (OSI-R) and Work Ability Index. Han and Hui teachers experienced reduced work ability compared with Uygur and Kazakh teachers, and this finding was caused, in part, by exposure to psychosocial factors at work. The vocational and psychological strains caused by these factors play an important role in reduced work ability among all ethnic teacher groups. The findings indicate the importance of taking action to reduce occupational strain for promoting teachers' work ability in multiethnic workplaces.     

我国肺癌患者医院感染高危因素Meta分析

目的系统分析肺癌患者医院感染高危因素及合并症特征，为制订医院感染管理策略提供依据。方法检索中国生物医学文献数据库（CBM）、中国知识基础设施工程(CNKI),万方、维普、PubMed以及Embase数据库中肺癌患者医院感染相关文献，提取数据进行Meta分析。结果共纳入19篇文献，包括肺癌住院患者 8 069例，其中医院感染1 280例。医疗因素发生医院感染的Meta分析合并值：抗肿瘤治疗(放射治疗和化学治疗)、化学治疗次数(≥2次)、预防性使用抗菌药物、使用免疫抑制剂及侵入性操作OR及95%CI分别为3.13(1.82,5.39)、9.20(3.04,27.87)、3.23(1.77,5.91)、2.00(1.56,2.57)、2.28(1.81,2.88)；肺癌不同合并症发生医院感染的Meta分析合并值：肺部疾病、慢性阻塞性肺疾病(COPD)、糖尿病、肾功能不全、营养不良、低蛋白血症、中性粒细胞减少、白细胞减少症OR及95%CI分别为2.65(1.74,4.02)、2.40(1.76,3.27)、2.25(1.85,2.73)、2.56 (1.18,5.52)、5.51(1.70,17.89)、2.05(1.56,2.70)、3.38(1.40,8.18)、2.10 (1.22,3.62)。结论肺癌患者医院感染相关医疗及合并症因素复杂多样，抗肿瘤治疗、免疫抑制剂、预防性使用抗菌药物、侵入性操作、肺部疾病、COPD、糖尿病、肾功能不全、营养不良、低蛋白血症、中性粒细胞减少及白细胞减少等均为肺癌患者医院感染的高危因素。     

SARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut

BackgroundInfection fatality rate and infection hospitalization rate, defined as the proportion of deaths and hospitalizations, respectively, of the total infected individuals, can estimate the actual toll of coronavirus disease 2019 (COVID-19) on a community, as the denominator is ideally based on a representative sample of a population, which captures the full spectrum of illness, including asymptomatic and untested individuals.ObjectiveTo determine the COVID-19 infection hospitalization rate and infection fatality rate among the non-congregate population in Connecticut between March 1 and June 1, 2020.MethodsThe infection hospitalization rate and infection fatality rate were calculated for adults residing in non-congregate settings in Connecticut prior to June 2020. Individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies were estimated using the seroprevalence estimates from the recently conducted Post-Infection Prevalence study. Information on total hospitalizations and deaths was obtained from the Connecticut Hospital Association and the Connecticut Department of Public Health, respectively.ResultsPrior to June 1, 2020, nearly 113,515 (90% confidence interval [CI] 56,758-170,273) individuals were estimated to have SARS-CoV-2 antibodies, and there were 7792 hospitalizations and 1079 deaths among the non-congregate population. The overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% (90% CI, 4.58%-13.72%) and 0.95% (90% CI, 0.63%-1.90%), respectively, and there was variation in these rate estimates across subgroups; older people, men, non-Hispanic Black people, and those belonging to 2 of the counties had a higher burden of adverse outcomes, although the differences between most subgroups were not statistically significant.ConclusionsUsing representative seroprevalence estimates, the overall COVID-19 infection hospitalization rate and infection fatality rate were estimated to be 6.86% and 0.95%, respectively, among community residents in Connecticut.