Forensic-Pathological Analysis of Blunt Cardiac Rupture Involving the Relationship between Injury and Disease: 2 Cases Report and Review of the Literature

Blunt cardiac rupture is a characteristic of high death rates and rapid death process. But sometimes it is hard to find out the cause of cardiac rupture of traumatized patients, especially when it relates the relationship between injury and disease. In the 2 cases reported herein, both of the 2 patients had pre-existent cardiac pathological changes when suffered from traumatic injury. Our aim is to evaluate autopsy findings from a medicolegal point of view, and offer our proposals on how to deal with this sort of cases.

Using Non-Additive Measure for Optimization-Based Nonlinear Classification

Over the past few decades, numerous optimization-based methods have been proposed for solving the classification problem in data mining. Classic optimization-based methods do not consider attribute interactions toward classification. Thus, a novel learning machine is needed to provide a better understanding on the nature of classification when the interaction among contributions from various attributes cannot be ignored. The interactions can be described by a non-additive measure while the Choquet integral can serve as the mathematical tool to aggregate the values of attributes and the corresponding values of a non-additive measure. As a main part of this research, a new nonlinear classification method with non-additive measures is proposed. Experimental results show that applying non-additive measures on the classic optimization-based models improves the classification robustness and accuracy compared with some popular classification methods. In addition, motivated by well-known Support Vector Machine approach, we transform the primal optimization-based nonlinear classification model with the signed non-additive measure into its dual form by applying Lagrangian optimization theory and Wolfes dual programming theory. As a result, 2n – 1 parameters of the signed non-additive measure can now be approximated with m (number of records) Lagrangian multipliers by applying necessary conditions of the primal classification problem to be optimal. This method of parameter approximation is a breakthrough for solving a non-additive measure practically when there are relatively small number of training cases available (mn-1). Furthermore, the kernel-based learning method engages the nonlinear classifiers to achieve better classification accuracy. The research produces practically deliverable nonlinear models with the non-additive measure for classification problem in data mining when interactions among attributes are considered.

Thermodynamically stable ionic liquid microemulsions pioneer pathways for topical delivery and peptide application

Copper peptides(GHK-Cu)are a powerful hair growth promoter with minimal side effects when compared with minoxidil and finasteride;however,challenges in delivering GHK-Cu topically limits their non-invasive applications.Using theoretical calculations and pseudo-ternary phase diagrams,we designed and constructed a thermodynamically stable ionic liquid(IL)-based microemulsion(IL-M),which integrates the high drug solubility of ILs and high skin permeability of microemulsions,thus improving the local delivery of copper peptides by approximately three-fold while retaining their biological function.Experiments in mice validated the effectiveness of our proposed IL-M system.Furthermore,the exact effects of the IL-M system on the expression of growth factors,such as vascular endothelial growth factor,were revealed,and it was found that microemulsion increased the activation of the Wnt/β-catenin signaling pathway,which includes factors involved in hair growth regulation.Overall,the safe and non-invasive IL microemulsion system developed in this study has great potential for the clinical treatment of hair loss.

A survey of immersive visualization:Focus on perception and interaction

Immersive visualization utilizes virtual reality,mixed reality devices,and other interactive devices to create a novel visual environment that integrates multimodal perception and interaction.This technology has been maturing in recent years and has found broad applications in various fields.Based on the latest research advancements in visualization,this paper summarizes the state-of-theart work in immersive visualization from the perspectives of multimodal perception and interaction in immersive environments,additionally discusses the current hardware foundations of immersive setups.By examining the design patterns and research approaches of previous immersive methods,the paper reveals the design factors for multimodal perception and interaction in current immersive environments.Furthermore,the challenges and development trends of immersive multimodal perception and interaction techniques are discussed,and potential areas of growth in immersive visualization design directions are explored.

Research progress in the estimation of the postmortem interval by Chinese forensic scholars

The determination of time since death or the postmortem interval(PMI)is one of the most important and frequently asked questions in forensic medicine.Medicolegal scholars and forensic pathologists around the world have studied the estimation of PMI extensively in the past,and many novel methods and advanced technologies have now been applied in the field.For several centuries,Chinese forensic examiners have also worked on the estimation of the PMI,and there are a large number of excellent studies published in Chinese rather than in English,and these are not easily accessible or known internationally.Therefore we have conducted a review of relevant studies published by Chinese forensic scholars in the last few decades.The scope of this review is to provide a concise summary of the current progress in the estimation of PMI by Chinese forensic researchers using molecular biology,spectroscopic technology,entomological methods,energy changes,thanatochemistry and other methods.

Estimation of the age of human semen stains by attenuated total reflection Fourier transform infrared spectroscopy:a preliminary study

Semen stain is one of the most important biological evidence at sexual crime scenes.Age estimation of human semen stains plays an important role in forensic work,and it is rarely studied due to lack of well-established methods.In this study,the technique called attenuated total reflection Fourier transform infrared spectroscopy(ATR-FTIR)coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates:glass slides,tissues and fabric made of regenerated cellulose fibres up to 6 d.Partial least squares regression(PLSR)was used in conjunction with spectral analysis for age estimation,and the results generated high R2 values(cross-validation:0.81,external validation:0.74)but a narrow margin of error for root mean square error(RMSE)(RMSE of cross-validation:0.77 d,RMSE of prediction:1.02 d).Additionally,our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study.Our results indicate that ATR-FTIR,combined with chemometric methods,shows great potential as a convenient and efficient tool for age estimation of semen stains.Moreover,the method could be applied to routine forensic investigations in the future.

Recent advances in synthetic carbohydrate-based human immunodeficiency virus vaccines

An effective vaccine for human immunodeficiency virus(HIV) is urgently needed to prevent HIV infection and progression to acquired immune deficiency syndrome(AIDS). As glycosylation of viral proteins becomes better understood, carbohydrate-based antiviral vaccines against special viruses have attracted much attention. Significant efforts in carbohydrate synthesis and immunogenicity research have resulted in the development of multiple carbohydrate-based HIV vaccines. This review summarizes recent advances in synthetic carbohydrate-based vaccines design strategies and the applications of these vaccines in the prevention of HIV.

Multiple regression analysis of the craniofacial region of Chinese Han people using linear and angular measurements based on MRI

The purpose of this study was to measure the craniofacial region of Chinese Han people in the linear and angular dimensions,and to analyse the effects on sex,age and body parameters(height and weight).All 250 individuals(86 males,164 females)underwent a three-dimensional magnetic resonance imaging(MRI)scan,and the MRI data were imported into VG Studio MAX 2.2 software.Each linear and angular measurement in the craniofacial region was processed directly.Using SPSS 20.0 software,nine multiple regression equations were constructed,and all the adjusted R^(2) values were statistically significant(0.031-0.311).Multiple regression analysis showed that most craniofacial measurements of Chinese people were significantly correlated with height,weight or age.The multiple regression equations constructed will be helpful in anthropometric analysis and forensic inference.

Estimation of Postmortem Interval Using Attenuated Total Reflectance:Fourier Transform Infrared Spectroscopy in Adipose Tissues

Estimation of postmortem interval(PMI)is vitally important in forensic investigations.Although many studies have examined the chemical changes of various tissues over time,no reports using spectroscopic methods in adipose tissue are available.In this study,attenuated total reflectance-Fourier transform infrared(ATR-FTIR)spectroscopy was utilized to collect comprehensive biochemical information from human adipose tissues in vitro at different times.Thereafter,mice were used as samples for in vivo experiments for more detailed studies on PMI.Then,partial least squares(PLS)model for PMI estimation was established based on the acquired spectral dataset of mouse samples.The spectral variable associated with C=O arising from lipids and free fatty acids was most susceptible to PMI.Moreover,the PLS model appeared to achieve a satisfactory prediction with a root mean square error of cross‑validation of 1.78 days,and the reliability of the model was determined in an external validation set with a root mean square error of prediction of 1.87 days.The study shows the possibility of application of ATR-FTIR methods in PMI estimation using adipose tissue.