Forensic Pathological Diagnosis of Acute and Old Myocardial Infarction Using Fourier Transform Infrared Spectroscopy / 法医学杂志

OBJECTIVES@#Fourier transform infrared spectroscopy (FTIR) was used to analyze myocardial infarction tissues at different stages of pathological change to achieve the forensic pathology diagnosis of acute and old myocardial infarction.@*METHODS@#FTIR spectra data of early ischemic myocardium, necrotic myocardium, and myocardial fibrous tissue in the left ventricular anterior wall of the sudden death group of atherosclerotic heart disease and the myocardium of the normal control group were collected using hematoxylin-eosin (HE) and immunohistochemistry (IHC) staining as a reference, and the data were analyzed using multivariate statistical analysis.@*RESULTS@#The mean normalized spectra of control myocardium, early ischemic myocardium and necrotic myocardium were relatively similar, but the mean second derivative spectra were significantly different. The peak intensity of secondary structure of proteins in early ischemic myocardium was significantly higher than in other types of myocardium, and the peak intensity of the α-helix in necrotic myocardium was the lowest. The peaks of amide Ⅰ and amide Ⅱ in the mean normalized spectra of myocardial fibrous tissue significantly shifted towards higher wave numbers, the peak intensities of amide Ⅱ and amide Ⅲ were higher than those of other types of myocardium, and the peak intensities at 1 338, 1 284, 1 238 and 1 204 cm-1 in the mean second derivative spectra were significantly enhanced. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) showed that FTIR could distinguish different types of myocardium.@*CONCLUSIONS@#FTIR technique has the potential to diagnose acute and old myocardial infarction, and provides a new basis for the analysis of the causes of sudden cardiac death.

Comparison among Four Deep Learning Image Classification Algorithms in AI-based Diatom Test / 法医学杂志

OBJECTIVES@#To select four algorithms with relatively balanced complexity and accuracy among deep learning image classification algorithms for automatic diatom recognition, and to explore the most suitable classification algorithm for diatom recognition to provide data reference for automatic diatom testing research in forensic medicine.@*METHODS@#The "diatom" and "background" small sample size data set (20 000 images) of digestive fluid smear of corpse lung tissue in water were built to train, validate and test four convolutional neural network (CNN) models, including VGG16, ResNet50, InceptionV3 and Inception-ResNet-V2. The receiver operating characteristic curve (ROC) of subjects and confusion matrixes were drawn, recall rate, precision rate, specificity, accuracy rate and F1 score were calculated, and the performance of each model was systematically evaluated.@*RESULTS@#The InceptionV3 model achieved much better results than the other three models with a balanced recall rate of 89.80%, a precision rate of 92.58%. The VGG16 and Inception-ResNet-V2 had similar diatom recognition performance. Although the performance of diatom recall and precision detection could not be balanced, the recognition ability was acceptable. ResNet50 had the lowest diatom recognition performance, with a recall rate of 55.35%. In terms of feature extraction, the four models all extracted the features of diatom and background and mainly focused on diatom region as the main identification basis.@*CONCLUSIONS@#Including the Inception-dependent model, which has stronger directivity and targeting in feature extraction of diatom. The InceptionV3 achieved the best performance on diatom identification and feature extraction compared to the other three models. The InceptionV3 is more suitable for daily forensic diatom examination.

Research Progress of Automatic Diatom Test by Artificial Intelligence / 法医学杂志

Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.

Application of Artificial Intelligence Automatic Diatom Identification System in Practical Cases / 法医学杂志

Objective To discuss the application of artificial intelligence automatic diatom identification system in practical cases, to provide reference for quantitative diatom analysis using the system and to validate the deep learning model incorporated into the system. Methods Organs from 10 corpses in water were collected and digested with diatom nitric acid; then the smears were digitally scanned using a digital slide scanner and the diatoms were tested qualitatively and quantitatively by artificial intelligence automatic diatom identification system. Results The area under the curve （AUC） of the receiver operator characteristic （ROC） curve of the deep learning model incorporated into the artificial intelligence automatic diatom identification system, reached 98.22% and the precision of diatom identification reached 92.45%. Conclusion The artificial intelligence automatic diatom identification system is able to automatically identify diatoms, and can be used as an auxiliary tool in diatom testing in practical cases, to provide reference to drowning diagnosis.

Relationship between Postmortem Interval and FTIR Spectroscopy Changes of the Rat Skin / 法医学杂志

Objective To infer postmortem interval （PMI） based on spectral changes of the dorsal skin of rats within 15 days postmortem using Fourier transform infrared （FTIR） spectroscopy. Methods The rats were sacrificed by cervical dislocation after anesthesia, and then placed at 25 ℃ and relative humidity of 50%. The FTIR spectral data collected from the dorsal skin at PMI points were modeled with machine learning technique. Results There was no significant difference of absorption peak location among all the PMI groups but their peak intensities changed as a function of PMIs. The model for PMI estimation was constructed using partial least squares （PLS） regression, reaching a R2 of 0.92 and a root mean square error （RMSE） of 1.30 d. As shown in variable importance for projection （VIP）, four spectral bands including 1 760-1 700 cm-1, 1 660-1 640 cm-1, 1 580-1 540 cm-1 and 1 460-1 420 cm-1 were determined as important contributions to model prediction. Conclusion Application of the FTIR technique to detect postmortem spectral changes of the rat skin provides a novel proposal for PMI estimation.

Determination of Electrocution Using Fourier Transform Infrared Microspectroscopy and Machine Learning Algorithm / 法医学杂志

Objective To analyze the differences among electrical damage, burns and abrasions in pig skin using Fourier transform infrared microspectroscopy （FTIR-MSP） combined with machine learning algorithm, to construct three kinds of skin injury determination models and select characteristic markers of electric injuries, in order to provide a new method for skin electric mark identification. Methods Models of electrical damage, burns and abrasions in pig skin were established. Morphological changes of different injuries were examined using traditional HE staining. The FTIR-MSP was used to detect the epidermal cell spectrum. Principal component method and partial least squares method were used to analyze the injury classification. Linear discriminant and support vector machine were used to construct the classification model, and factor loading was used to select the characteristic markers. Results Compared with the control group, the epidermal cells of the electrical damage group, burn group and abrasion group showed polarization, which was more obvious in the electrical damage group and burn group. Different types of damage was distinguished by principal component and partial least squares method. Linear discriminant and support vector machine models could effectively diagnose different damages. The absorption peaks at 2 923 cm-1, 2 854 cm-1, 1 623 cm-1, and 1 535 cm-1 showed significant differences in different injury groups. The peak intensity of electrical injury's 2 923 cm-1 absorption peak was the highest. Conclusion FTIR-MSP combined with machine learning algorithm provides a new technique to diagnose skin electrical damage and identification electrocution.

Effects of Temperature on FTIR Spectral Characteristics of Renal Tissue in Rats after Death / 法医学杂志

OBJECTIVES@#To analyse the Fourier transform infrared （FTIR） spectral data of renal tissue at different temperatures in rats after death, and to explore the effects of temperature on the FTIR spectral characteristics of renal tissue.@*METHODS@#The rats were sacrificed by cervical dislocation and placed at 4 ℃, 20 ℃ and 30 ℃. The FTIR spectral data of renal tissue were collected at different time points and analysed by data mining method.@*RESULTS@#The principal component analysis （PCA） results showed that there were significant trends of clustering in the samples of partial time point at 4 ℃, 20 ℃ and 30 ℃. Partial least square （PLS） regression models were established with the spectral data at three temperature groups. The performance of PLS regression models in 20 ℃ and 30 ℃ groups were more superior than that in 4 ℃ group, and the stability of the model in 20 ℃ group was better than that in 30 ℃ group.@*CONCLUSIONS@#There are differences in the FTIR spectral characteristics of renal tissue of rats after death at different temperatures. Temperature has a major impact on the performance of FTIR spectral PLS regression model. Therefore, in order to improve the accuracy of postmortem interval estimation, the effects of temperature on the model should be considered in the related study by spectral method.

Infrared Spectral Characteristics of Electrical Injuries on Swine Skin Caused by Different Voltages Based on Machine Learning Algorithms / 法医学杂志

Objective To explore infrared spectrum characteristics of different voltages induced electrical injuries on swine skin by using Fourier transform infrared-microspectroscopy (FTIR-MSP) combined with machine learning algorithms, thus to provide a reference to the identification of electrical skin injuries caused by different voltages.Methods Electrical skin injury model was established on swines.The skin was exposed to 110 V, 220 V and 380 V electric shock for 30 s and then samples were took, with normal skin tissues around the injuries as the control.Combined with the results of continuous section HE staining, the FTIR-MSP spectral data of the corresponding skin tissues were acquired.With the combination of machine learning algorithms such as principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), different spectral bands were selected (full band 4 000-1 000 cm-1and sub-bands 4 000-3 600 cm-1, 3 600-2 800 cm-1, 2 800-1 800 cm-1, and 1 800-1 000 cm-1), and various pretreatment methods were used such as orthogonal signal correction (OSC), standard normal variables (SNV), multivariate scatter correction (MSC), normalization, and smoothing.Thus, the model was optimized, and the classification effects were compared.Results Compared with simple spectrum analysis, PCA seemed to be better at distinguishing electrical shock groups from the control, but was not able to distinguish different voltages induced groups.PLS-DA based on the 3 600-2 800 cm-1band was used to identify the different voltages induced skin injuries.The OSC could further optimize the robustness of the 3 600-2 800 cm-1band model.Conclusion It is feasible to identify electrical skin injuries caused by different voltages by using FTIR-MSP technique along with machine learning algorithms.

Establishment of the Mathematical Model for PMI Estimation Using FTIR Spec-troscopy and Data Mining Method / 法医学杂志

Objective To analyse the relationship between Fourier transform infrared （FTIR） spectrum ofrat's spleen tissue and postmortem interval （PMI） for PMI estimation using FTIR spectroscopy combinedwith data mining method. Methods Rats were sacrificed by cervical dislocation, and the cadavers were placed at 20 ℃. The FTIR spectrum data of rats' spleen tissues were taken and measured at different time points. After pretreatment, the data was analysed by data mining method. Results The absorption peak intensity of rat's spleen tissue spectrum changed with the PMI, while the absorption peak position was unchanged. The results of principal component analysis （PCA） showed that the cumulative contribution rate of the first three principal components was 96%. There was an obvious clustering tendency for the spectrum sample at each time point. The methods of partial least squares discriminant analysis （PLS- DA） and support vector machine classification （SVMC） effectively divided the spectrum samples with different PMI into four categories （0-24 h, 48-72 h, 96-120 h and 144-168 h）. The determination coefficient （R2） of the PMI estimation model established by PLS regression analysis was 0.96, and the root mean square error of calibration （RMSEC） and root mean square error of cross validation （RMSECV） were 9.90 h and 11.39 h respectively. In prediction set, the R2 was 0.97, and the root mean square error of prediction （RMSEP） was 10.49 h. Conclusion The FTIR spectrum of the rat's spleen tissue can be effectively analyzed qualitatively and quantitatively by the combination of FTIR spectroscopy and data mining method, and the classification and PLS regression models can be established for PMI estimation.

Analysis of Differentially Expressed Proteins Distribution in the Rat Brains with DAI by MALDI-TOF-IMS / 法医学杂志

OBJECTIVES@#To establish the imaging mass spectrometry for analysis of differentially expressed proteins distribution in the rat brains with diffuse axonal injury （DAI） based on matrix assisted laser desorption/ionization-time of flight imaging mass spectrometry （MALDI-TOF-IMS）.@*METHODS@#MALDI-TOF-IMS scanning were conducted on the brains of DAI group and control group in the m/z range of 1 000 to 20 000 using AutoflexⅢ MALDI-TOF spectrometer. ClinProTool 2.2 software was used for statistical analysis on the data of two groups, and then the differentially expressed proteins were picked out to conduct imaging. The distribution of the proteins with different m/z in the rat brains was observed.@*RESULTS@#Five proteins with different m/z, including 4 963, 5 634, 6 253, 6 714 and 7 532, differentially expressed in the rat brains with DAI.@*CONCLUSIONS@#MALDI-TOF-IMS can be used for studying the differentially expressed proteins in rat brains with DAI and the analysis method is established for exploring the distribution of differentially expressed proteins in the rat brains with DAI using imaging mass spectrometry.

New Progress of MALDI-TOF-IMS in the Study of Proteomics / 法医学杂志

Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF-IMS) has been a classical technique for studying proteomics in present and a tool for analyzing the distribution of proteins and small molecules within biological tissue sections. MALDI-TOF-IMS can analyze multiple unknown compounds in biological tissue sections simultaneously through a single measurement which can obtain molecule imaging of the tissue while maintaining the integrity of cellular and molecules in tissue. In recent years, imaging mass spectrometry technique develops relatively quickly in all biomedical domain. This paper based on the relevant data and reviews the present developing level of MALDI-TOF-IMS, the principle of imaging mass spectrometry, methology and the prospect in forensic pathology.

Proteomic Analysis of Rat Brain Stem with DAI by MALDI-TOF-MS / 法医学杂志

OBJECTIVE@#To establish a diagnostic model for diffuse axonal injury (DAI) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). To screen the proteins or peptides associated with DAI for providing the biomarkers with theoretic foundation.@*METHODS@#Fifteen male Sprague-Dawley rats were randomly divided into DAI group (n = 10) and control group (n = 5). The protein or peptide expression profiles of rat brain stem were detected by MALDI-TOF-MS. ClinProTools 2.2 software was used to find specific peaks, and a diagnostic model was established by the genetic algorithm.@*RESULTS@#There were significant differences in 61 peaks of DAI group (P < 0.05), 9 peaks were down-regulated and 52 up-regulated. The diagnostic model was established based on 5 different peaks. The specificity and sensitivity of cross validation was 96.14% and 95.98%; while the specificity and sensitivity of blind validation showed was 73.33% and 70.00%, respectively.@*CONCLUSION@#A specific and sensitive diagnostic model of DAI can be established by MALDI-TOF-MS to provide a potential value for determining DAI in forensic practice.

Research Advances in Postmortem Chemistry / 法医学杂志

Postmortem chemistry is becoming more and more essential in routine forensic pathology and has made considerable progress over the past years. Biochemical analyses of vitreous humor, blood, urine and cerebrospinal fluid may provide important information in determining the cause of death or in elucidating forensic issues. Postmortem chemistry may be essential for the determination of cause of death when morphological methods (diabetes mellitus, alcoholic ketoacidosis and electrolytic disorders) cannot detect the pathophysiological changes involved in the death process. It can also provide many information in other forensic situations, including myocardial ischemia, sepsis, inflammation, infection, anaphylaxis and hormonal disturbances. The most recent relevant research advances on glucose metabolism, liver function, cardiac function, renal function, sepsis, inflammation, infection, anaphylaxis and hormonal aspect are hereby reviewed.

Fourier Transform Infrared Microspectroscopy of Rat Kidney with Regard to Fa- tal Hyperthermia / 法医学杂志

OBJECTIVE@#To observe the chemical groups changing in rat kidney with regard to fatal hyperthermia by Fourier transform infrared microspectroscopy (FTIR-MSP) and to provide a new method to diagnose fatal hyperthermia.@*METHODS@#Rats were sacrificed by hyperthermia, brainstem injury, massive hemorrhage and asphyxiation and divided into groups. The renal samples were dissected immediately after death. The data of infrared spectroscopy in glomerulus were measured by FTIR-MSP.@*RESULTS@#The absorbances of 3290, 3070, 2850, 1540 and 1396 cm(-1) significantly increased (P < 0.05), and the ratios of Al650/A3290 and A1650/A1540 significantly decreased (P < 0.05) in group of hyperthermia.@*CONCLUSION@#FTIR-MSP can analyze the changes of chemical groups of kidney as an auxiliary diagnosis for discriminating hyperthermia with other causes of death.

Application of MSCT in the identification and analysis of traffic accidents: 2 fatal cases / 法医学杂志

OBJECTIVE@#To explore the application value of multi-slice spiral computed tomography (MSCT) in traffic accidents through observing and analyzing the injury features of the accidents.@*METHODS@#Two fatal cases caused by traffic accidents were fully examined using MSCT, 3D imaging reconstruction and angiography through cardiac puncture. The features of traffic injury mechanism were analyzed through combination of MSCT and postmortem external examination.@*RESULTS@#In case 1, right cardiac rupture was found by MSCT and angiography through cardiac puncture. The cause of death was cardiac tamponade and right ventricular rupture due to the crush injury of chest in the traffic accident. In case 2, splenic rupture and intra-abdominal hemorrhage was found and caused by injury of left trunk by MSCT. The cause of death was hemorrhage and traumatic shock.@*CONCLUSION@#MSCT could observe skeletal injury, soft tissue injury, and hematologic disorder well. The combination use of MSCT and angiography through cardiac puncture provided assistance to the diagnosis of cardiovascular system injury.

Coronary angiography of in vitro porcine heart using MSCT / 法医学杂志

OBJECTIVE@#To establish standardized methods and parameters of the isolated heart coronary angiography through the experiment of in vitro porcine heart by MSCT.@*METHODS@#Based on different perfusion volume (50, 60 and 70 mL) and different perfusion-imaging time (5, 10 and 20 min), the in vitro porcine coronary artery was injected liposoluble and water-soluble contrast agents using remodel angiography equipment and scanned by MSCT. And the 3D image results were compared. The images were recorded and evaluated by 2 radiologists and analyzed by statistical software.@*RESULTS@#Liposoluble contrast agent affected the images by damaging and infiltrating the fats around the coronary artery, while the water-soluble contrast agent didn't affect the images. The groups with 60 mL or 70 mL perfusion and 5 min perfusion-imaging time had the best images.@*CONCLUSION@#The suitable parameters of the angiography lay the foundation of postmortem coronary angiography.

Severe hypokalemia due to combination use of dexamethasone and calcium gluconate for diabetics with infection: a case report / 法医学杂志

The combination use of dexamethasone and calcium gluconate can be applied to hypersensitivity. Severe hypokalemia is a usual complication of dexamethasone and calcium gluconate therapy, which occurs frequently with therapeutic use. Fatal cases, accidental and intentional, occur frequently in forensic practice. The current case report presented a 43-year-old man with diabetes mellitus with infection, to whom dexamethasone and calcium gluconate were administered in the private clinic. With the development of such clinical symptoms of severe hypokalemia as quadriplegia, he was confirmed to have severe hypokalemia through a biochemical test before dying of arrhythmia. And also it presented pathophysiologic mechanism underlying severe hypokalemia as well as suggestions for clinical practice regarding combination use of dexamethasone and calcium gluconate.

Analysis of biochemical markers in serum of guinea pigs after death caused by hypothermia / 法医学杂志

OBJECTIVE@#To explore the changes and rules of biochemical markers in serum of guinea pigs after death caused by hypothermia and to provide references for fatal hypothermia diagnosis by serum biochemical markers.@*METHODS@#Twenty guinea pigs were randomly divided into experimental group and control group. The guinea pigs in the experimental group were kept at -30 °C until death, while the ones in control group were decapitated after same survival intervals at 25 °C. The serum was extracted from the whole blood of right ventricular immediately. Subsequently, a series of serum biochemical markers were analyzed by auto bio-chemical analyzer.@*RESULTS@#The levels of glucose, uric acid, creatinine and urea nitrogen in the experimental group were significantly higher than those in control group, respectively (P<0.05). Compared with the control group, the levels of total protein and albumin were significantly lower in the experimental group (P<0.05). There were no significantly differences of the levels of other markers such as serum enzymes and ions observed between the two groups.@*CONCLUSION@#There are characteristic changes of some specific serum biochemical markers in fatal hypothermia, which may be potentially useful for auxiliary diagnosis of fatal hypothermia.

Changes of postmortem human blood biochemical indexes / 法医学杂志

OBJECTIVE@#To investigate and analyze the changes of postmortem human biochemical indexes.@*METHODS@#Subclavian venous blood samples were collected from 81 cases of traffic fatalities. Thirteen blood biochemical indexes including liver function (ALT, AST, TBIL and DBIL), renal function (UA and Cr), cardiac function (CK, CK-MB and LDH), electrolytes (K+, Na+ and Cl-), and glucose (GLU) were tested by Roche cobas c311 automatic biochemical analyzer. The descriptive analysis was made by SPSS 17.0 statistical software.@*RESULTS@#The values of ALT, AST, CK, CK-MB, LDH and K+ were higher than normal reference values with more fluctuations. The values of TBIL, DBIL, UA, Cr, Na+, Cl- and GLU were relatively stable with less fluctuations.@*CONCLUSION@#The postmortem human blood biochemical indexes of liver function, renal function, cardiac function, electrolytes and glucose could be affected by the factors, especially hemolysis and autolysis. The biochemical indexes, particularly enzymes, increased significantly with higher standard deviation.

STR profiling of genomic DNA from HE stained tissue sections / 法医学杂志

OBJECTIVE@#To develop a STR analysis method for analyzing DNA from stained tissue sections and to evaluate the capability of this protocol in forensic application.@*METHODS@#Eight kinds of HE stained human tissue, for example heart, liver, lung and intestine, were collected from two autopsy cases. The genomic DNA from those tissues was extracted using a QIAgen kit. DNA quantitation was performed using the TaqMan PCR method. The concentration of DNA isolated was determined based on Ct values. Internal positive controls (IPC) were used to monitor inhibitors. DNA amplifications were performed using Identifiler PCR Amplification kit. PCR products were analyzed on 3100-Avant Genetic Analyzer.@*RESULTS@#The concentrations of DNA obtained from all samples were greater than 1 ng/microL. PCR inhibition was not observed. However, DNA degradation, potentially due to the effect of residual formalin fixative, was observed among tissue samples stored for long periods of time.@*CONCLUSION@#Sufficient amounts of DNA were extracted from HE stained tissue sections. STR profiles were successfully generated. The number of genotype alleles detected decreased as sample storage time increased.