Study on drowning deaths in water Liu Chao
Drowning is the death caused by asphyxiation due to fluid blocking the airway. In the practice of forensic medicine， it is the key to determine whether the corpse was drowned or entered the water after death. At the same time， the drowning site inference and postmortem submersion interval （PMSI） play an important role in the investigating the identity of the deceased, narrowing the investigation scope, and solving the case. Based on diatoms testing， molecular biology， imaging and artificial intelligence and other technologies， domestic and foreign forensic scientists have done relative research in the identification of the cause of death， drowning site inference and PMSI， and achieved certain results in forensic medicine application. In order to provide a reference for future study of bodies in the water， this paper summarizes the above research contents.
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.
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.
Diatom detection is an important method for identifying drowning and throwing corpses after death and inferring the drowning sites in forensic examination of corpses in water. In recent years,high-throughput sequencing technology has achieved rapid development and has been widely used in research related to diatom taxonomic investigations. This paper reviews the research status and prospects of high-throughput sequencing technology and its application in forensic diatom detection.
To examine the effect of improving diatom DNA extraction by glass bead - vortex oscillation method.
The DNeasy PowerSoil Pro kit was used as control, two plant DNA extraction kits with different principles （New Plant genomic DNA extraction kit and Plant DNA Isolation kit） and one whole blood DNA extraction kit （whole blood genomic DNA extraction kit） were selected to extract diatom DNA from lung tissue and water sample of the same drowning case. The combination of mass ratio of glass beads with different sizes and vortex oscillation time was designed, and the optimal DNA extraction conditions were selected with the addition of glass beads oscillation. The extracted products of the conventional group and the modified group were directly electrophoretic and detected by diatom specific PCR. Finally, all the extracts were quantified by qPCR, and the Ct values of different groups were statistically analyzed.
When the frequency of vortex oscillation was 3 000 r/min, the optimal combination of DNA extraction was vortex oscillation for 4 min, and the mass ratio of large glass beads to small glass beads was 1∶1. The DNeasy PowerSoil Pro kit was used as a reference, and the Ct value of 10 mL water sample was greater than that of 0.5 g tissue. The Ct values of the other three kits used for plant DNA extraction decreased after the glass beads-vortex oscillation method was used, and the Ct values of the tissues before and after the improvement were statistically significant （P<0.05）. The whole blood genomic DNA extraction kit used in this study could successfully extract diatom DNA, the extraction of water samples was close to DNeasy PowerSoil Pro kit, after the modified method was applied to tissue samples, the difference in Ct value was statistically significant （P<0.05）. However, when the three kits were used to extract diatom DNA from water samples, Ct values before and after the improvement were only statistically significant in New Plant genomic DNA extraction kit group （P<0.05）.
The improved glass bead-vortex oscillation method can improve the extraction efficiency of diatom DNA from forensic materials, especially from tissue samples, by plant and blood DNA extraction kits.
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.
To study the relationship between water temperature and floating time of aquatic cadavers， providing a reference for more precise positioning and searching for floating corpses.
The floating model of guinea pig after drowning at 17-30 ℃ was established, and the floating times of carcasses were recorded. The collected data of 32 floating corpse cases in the Pearl River were sorted out and analyzed according to the floating time of corpses corresponding to each degree of water temperature. The relationship models between water temperature and the floating time of guinea pig carcass, and between that and the floating time of real cases were established.
The floating time of the cadaver was negatively correlated with water temperature. The power function fitting equation of the relationship between floating time and water temperature of guinea pig carcass was y=1×1015x-10.530（R2=0.871, P<0.01）， and the power function fitting equation of the relationship between corpse floating time and water temperature was y=3×106x-3.467（R2=0.802, P<0.01）.
It is found that average floating cadaver time has a power function with water temperature， which provides a reference for locating floating cadavers and establishing search models.
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 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.
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 construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model.
A total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts’ annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate.
The mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold.
The YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.
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.
Study on drowning deaths in water
