Study on drowning deaths in water Liu Chao
To compare the application effect of microwave digestion - vacuum filtration - automated scanning electron microscopy （MD-VF-Auto SEM） method and plankton gene multiplex PCR system in the diagnosis of drowning.
Lung, liver and kidney tissue of 10 non-drowning cases and 50 drowning cases were prepared for further MD-VF-Auto SEM method analysis and plankton gene multiplex PCR system analysis. The positive detection rate of the two methods in each tissue was calculated.
The positive rate of the MD-VF-Auto SEM method detecting diatoms in drowning cases was 100%, and few diatoms were detected in the liver and kidney tissues of 6 non-drowning cases. By using the plankton gene multiplex PCR system, the diatom positive rate of drowning cases was 84%, and all the non-drowning cases were negative. There were significant differences in the positive rate of the liver, kidney tissues between MD-VF-Auto SEM method and plankton gene multiplex PCR system （P<0.05）, as well as the total positive rate of cases. However, no significant differences were found in the positive rates of lung tissues （P>0.05）.
MD-VF-Auto SEM method is more sensitive than plankton gene multiplex PCR system in diatom test. But the plankton gene multiplex PCR system can also detect plankton other than diatoms. Combination of the two methods can provide a more reliable basis for the diagnosis of drowning.
To retrospectively analyze diatom test cases of corpses in water and discuss the value of quantitative analysis of diatoms in the diagnosis of drowning.
A total of 490 cases of water-related death were collected. They were divided into drowning group and postmortem immersion group according to the cause of death. Diatoms in lung, liver, kidney tissue and water sample were analyzed quantitatively by microwave digestion-vacuum filtration-automated scanning electron microscopy （MD-VF-Auto SEM） method. The ratios of content of diatoms in lung tissue and water sample （CL/CD） were calculated.
The results of diatom test for three organs （lung, liver and kidney） were all positive in 400 cases （85.5%）; the content of diatom in lung, liver, kidney tissues, and water samples of drowning group were （113 235.9±317 868.1）, （26.7±75.6）, （23.3±52.2） and （12 113.3±21 760.0） cells/10 g, respectively; the species of diatom were （7.5±2.8）, （2.6±1.9）, （2.9±2.1） and （8.9±3.0） types, respectively; the CL/CD of drowning group and postmortem immersion group were （100.6±830.7） and （0.3±0.4）, respectively.
Quantitative analysis of diatoms can provide supportive evidence for the diagnosis of drowning, and the parameter CL/CD can be introduced into the analysis to make a more accurate diagnosis of drowning.
To study the annual variation of diatoms in Zhangweixin River, to provide theoretical support by using diatom examination to estimate the time and place of the corpse entering water, and to establish a diatom database.
Samples were taken from 4 sampling sites in Decheng section of Zhangweixin River for 12 consecutive months. Non-metric multi-dimensional scaling （NMDS） analysis was performed on the species and content of diatom samples. Based on the sampling site of Tianqu Road, Sprensen similarity coefficient analysis was conducted with the data of other 3 sites in Decheng section and Leling section of Zhangweixin River and Ningjin section in previous studies.
The number of diatom species was positively correlated with diatom content. The average diatom content in different months ranged from 1 054 to 13 041/10 mL, and the species composition ranged from 8 to 16, with differences in dominant species. The similarity coefficient of diatom species within 2 km were all higher than 0.956 52， which could not be distinguished effectively. The similarity coefficients of Leling section and Ningjin section were 0.736 84 and 0.588 24 respectively, which could be effectively distinguished.
The species and content of diatom vary in different months in Zhangweixin River, and the composition of diatom species is different in different basins, which can provide reference for estimating the time and place of the corpse entering water in the river.
The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval （PMSI） estimation and the cause of death determination.
The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group （n=50） and a postmortem （CO2 suffocation） immediately submersion group （n=50）. Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest （RF） algorithm was used to screen several biomarkers to establish a model.
PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error （MAE） of the model was 0.847 h.
The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.
To study the phenomenon of pulmonary hypostasis in corpses of various causes of death， and to explore the potential value of this phenomenon in assisting forensic pathological diagnosis of drowning.
A total of 235 cases with clear cause of death through systematic autopsy were collected from January 2011 to June 2021 in Guangzhou. According to the location of body discovery, the cases were divided into the water body group （97 cases） and the non-water body group （138 cases）, and the water body group was further divided into the water drowning group （90 cases） and the water non-drowning group （7 cases）. Non-water body group was further divided into the non-water drowning group （1 case） and the non-water non-drowning group （137 cases）. Three senior forensic pathologists independently reviewed autopsy photos to determine whether there was hypostasis in the lungs. The detection rate of pulmonary hypostasis was calculated.
The detection rate of pulmonary hypostasis in the water drowning group （90 cases） was 0， and the negative rate was 100%. The detection rate of pulmonary hypostasis in the water non-drowning group （7 cases） was 100% and the negative rate was 0. The detection rate of pulmonary hypostasis in the water body group and in the non-water body group （after excluding 2 cases, 136 cases were calculated） was 7.22% and 87.50%， respectively. There were statistically significant differences in the detection rate of pulmonary hypostasis between water body group and non-water body group, and between water drowning group and water non-drowning group （P<0.05）.
The disappearance of pulmonary hypostasis can be used as a specific cadaveric sign to assist in the forensic pathological diagnosis of drowning.
To study the effects of temperature and time for diatoms digestion and find out suitable digestive temperature and time.
Eighty pieces of liver tissues were collected, each piece of tissue was 2 g, and 2 mL Pearl River water was added to each piece of tissue. The digestion temperature was set at 100 ℃, 120 ℃, 140 ℃, 160 ℃, 180 ℃ and the digestion time was set at 40, 50, 60, 70, 80 min. The liver tissue and water mixture were divided into 8 portions in each group. All the samples were tested by microwave digestive - vacuum filtration - automated scanning electron microscopy method. The quantity of diatom recovered and the quality of residue on the membrane were recorded.
When the digestion time was set to 60 min, there were statistically significant differences in the number of diatoms recovered at different temperatures （P<0.05）. The maximum number of diatoms recovered was （28 797.50±6 009.67） at 140 ℃, and the minimum residue was （0.60±0.28） mg at 180 ℃. When the digestion temperature was set at 140 ℃, there were statistically significant differences in the number of diatoms recovered at different digestion times （P<0.05）. The number of diatoms recovered was the highest at 40 min, it was up to （20 650.88±1 950.29）, and the residue quality of each group had no statistical significance among different digestion time groups（P>0.05）.
The effect of diatom digestion is related to temperature and time. When the digestion temperature was 140 ℃ and the digestion time was 40, 50 and 60 min, it is favorable for diatom test.
To explore the application values of diatom artificial intelligence （AI） search system in the diagnosis of drowning.
The liver and kidney tissues of 12 drowned corpses were taken and were performed with the diatom test, the view images were obtained by scanning electron microscopy （SEM）. Diatom detection and forensic expert manual identification were carried out under the thresholds of 0.5, 0.7 and 0.9 of the diatom AI search system, respectively. Diatom recall rate， precision rate and image exclusion rate were used to detect and compare the efficiency of diatom AI search system.
There was no statistical difference between the number of diatoms detected in the target marked by the diatom AI search system and the number of diatoms identified manually （P>0.05）; the recall rates of the diatom AI search system were statistically different under different thresholds （P<0.05）; the precision rates of the diatom AI system were statistically different under different thresholds（P<0.05）， and the highest precision rate was 53.15%; the image exclusion rates of the diatom AI search system were statistically different under different thresholds （P<0.05）， and the highest image exclusion rate was 99.72%. For the same sample， the time taken by the diatom AI search system to identify diatoms was only 1/7 of that of manual identification.
Diatom AI search system has a good application prospect in drowning cases. Its automatic diatom search ability is equal to that of experienced forensic experts, and it can greatly reduce the workload of manual observation of images.
To explore the application value of virtual autopsy to obtain key evidence information on drowned corpses and its application value of virtual autopsy in the diagnosis of drowning.
In this study, 7 corpses were selected as the research objects. The image data of corpses were collected by computed tomography （CT） before conventional autopsy. The characteristics of corpses were observed through image reading, combined with virtual measurement indexes, and compared with 15 non-drowned corpses.
The postmortem CT of drowning showed the more fluid in respiratory tract than the non-drowning， and ground-glass opacities in the lung. The statistical volume of fluid in the sinus （maxillary sinus and sphenoid sinus） was （10.24±4.70） mL in drowning cases and （2.02±2.45） mL in non-drowning cases. The average CT value of fluid in the sinus， left atrial blood and gastric contents in drowning cases were （15.91±17.20）, （52.57±9.24） and （10.33±12.81） HU， respectively， which were lower than those in non-drowning cases （P<0.05）.
The comprehensive consideration of multiple characteristic image manifestations and the virtual measurement indexes are helpful to the forensic pathological diagnosis of drowning. Virtual autopsy can be used as an auxiliary method in the forensic diagnosis of drowning.
To study whether diatoms can enter the body through the lymphatic system of the digestive tract.
Twenty experimental rabbits were divided into the test group and the control group randomly, and intragastric administration was performed with 20 mL water sample from the Pearl River and 20 mL ultrapure water, respectively. After 30 min, lymph, lungs， livers and kidneys were extracted for the diatom test. The concentration, size and type of diatoms were recorded.
The concentration of diatoms of the test group was higher than that of the control group （P<0.05）. In the test group, Stephanodiscus, Coscinodiscus, Cyclotella, Melosira， Nitzschia， Synedra， Cymbella, and Navicula were detected; in the control group， Stephanodiscus, Coscinodiscus and Cyclotella were detected. The long diameter and the short diameter of diatoms of the test group were higher than those of the control group （P<0.05）. In the test group, 1-2 diatoms were detected in 3 lung samples and 2 liver samples, which were Stephanodiscus or Cyclotella, and no diatoms were detected in the kidney samples; in the control group, 1-2 diatoms were detected in 2 lung samples and 3 liver samples, which were Stephanodiscus or Coscinodiscus, and no diatoms were detected in the kidney samples.
Diatoms can enter the body through the lymphatic fluid, which is one of the reasons for the presence of diatoms in tissues and organs of non-drowning cadavers.
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.
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.
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.
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.
To explore the research hotspots and development trends of the field of forensic drowning from 1991 to 2020 by bibliometrics methods.
Based on Web of Science， CNKI database， Wanfang Data knowledge service platform， python 3.9.2， CiteSpace 5.8.R3, Gephi 0.9.2, etc. were used to analyze the publishing trends， countries/regions， institutions， authors and topics of the study on drowning.
A total of 631 English literature were obtained， including 59 articles from Chinese authors， and 386 Chinese literature were obtained. The Chinese and English journals with the largest number of related literatures were Chinese Journal of Forensic Science （80 articles） and Forensic Science International （106 articles）， respectively. Japan published the most articles in English， and China ranked third. Osaka City Univ （Japan，28 articles） published the most English articles，and Guangzhou Forens Sci Inst （China，22 articles） ranked second. Among Chinese literature， Guangzhou Forens Sci Inst （32 articles） published the most. The topic analysis of Chinese and English literature showed that diatom examination， virtual autopsy， postmortem biochemical examination， the nature of death， and postmortem submersion interval were the hot spots of current research， but English literature had more studies on new technologies and methods， while Chinese literature was more inclined to practice， application and experience summary.
The number of literature in forensic medicine on drowning is relatively stable. The scope of international and domestic collaborations in this field is still limited. The automated examination of diatoms， the establishment of diatom DNA barcodes and virtual autopsy will be the most important research hotspots in the coming period and are expected to achieve breakthroughs in drowning diagnosis， drowning location inference， postmortem submersion interval estimation， etc.
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.
Study on drowning deaths in water
