Prenatal diagnosis of de novo (7;19)(q11.2;q13.3) translocation associated with a thick corpus callosum and Wilms tumor of the kidneys

We present a case of prenatal diagnosis of a de novo (7;19)(q11.2;q13.3) translocation associated with ultrasound features, including enlarged cisterna magna, normal vermis, thick corpus callosum, micrognathia, small and low-set ears and right hyperechogenic kidney. Karyotyping was performed at 24 weeks of gestation. Termination of pregnancy was accepted at the parents' request. Postmortem examination confirmed the prenatal findings, but revealed bilateral Wilms tumors of the kidneys. Parental karyotype was normal. Copyright © 2005 John Wiley & Sons, Ltd.     

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

药品和个人护理用品在固体基底中的检测方法和分布现状

药品和个人护理用品(Pharmaceuticals and personal care products,PPCPs)在环境中广泛存在,威胁生态环境和人类健康,受到越来越多的关注.本文综述了固体基底中PPCPs的检测方法,总结了国内外污泥、土壤、沉积物等基底中PPCPs的污染现状,并对PPCPs的进一步研究进行了展望.结果表明,PPCPs的检测方法朝多样化和趋优化的方向发展.污泥样品中PPCPs种类多、浓度高(μg·kg-1—mg·kg-1),土壤和沉积物中虽然浓度不高,但是总量不可小觑.目前,固体基底中的PPCPs还需要更全面和更广泛的研究.