Dissecting the microbial community structure of internal organs during the early postmortem period in a murine corpse model.

BACKGROUND: Microorganisms distribute and proliferate both inside and outside the body, which are the main mediators of decomposition after death. However, limited information is available on the postmortem microbiota changes of extraintestinal body sites in the early decomposition stage of mammalian corpses. RESULTS: This study investigated microbial composition variations among different organs and the relationship between microbial communities and time since death over 1 day of decomposition in male C57BL/6 J mice by 16S rRNA sequencing. During 1 day of decomposition, Agrobacterium, Prevotella, Bacillus, and Turicibacter were regarded as time-relevant genera in internal organs at different timepoints. Pathways associated with lipid, amino acid, carbohydrate and terpenoid and polyketide metabolism were significantly enriched at 8 h than that at 0.5 or 4 h. The microbiome compositions and postmortem metabolic pathways differed by time since death, and more importantly, these alterations were organ specific. CONCLUSION: The dominant microbes differed by organ, while they tended toward similarity as decomposition progressed. The observed thanatomicrobiome variation by body site provides new knowledge into decomposition ecology and forensic microbiology. Additionally, the microbes detected at 0.5 h in internal organs may inform a new direction for organ transplantation.

Accurate identification of traumatic lung injury (TLI) by ATR-FTIR spectroscopy combined with chemometrics.

Traumatic lung injury (TLI), which is a common mechanical injury, is receiving increasing attention because of its serious hazards. In forensic practices, accurately identifying TLI is of great importance for investigations and case trials. The main goal of this research was to identify TLI utilizing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics. The macroscopic appearance of lung tissue showed that identifying TLI in lung tissue at the decomposition stage is not feasible by only visualization, and significant pulmonary hypostasis was observed in the lungs regardless of whether the lung tissue was injured. Average spectra and principal component analysis (PCA) suggested that the biochemical difference between injured lung tissue samples from the TLI group and noninjured lung tissue samples from the negative control group was mainly attributed to the different structures and contents of proteins. Partial least squares discriminant analysis (PLS-DA) was then utilized to identify TLI with an accuracy of 96.4% and 98.6% based on the training set and the test set, respectively. Next, we focused on samples that were misclassified in the model and proposed that the misclassification could be caused by the pulmonary hypostasis effect. Therefore, two additional PCA and PLS-DA models were created to identify the pulmonary hypostatic areas between the TLI group and the negative control group and the nonpulmonary hypostatic areas between the TLI group and the negative control group. The PCA results indicated that the biochemical difference between the two groups was still associated with proteins, and the two PLS-DA models achieved 100% accuracy based on both the training and test sets. This result indicated that when pulmonary hypostasis was considered and the lung tissue was divided into pulmonary hypostatic areas and nonpulmonary hypostatic areas for separate comparisons, TLI identification was achieved with a greater accuracy than that obtained when the two areas were combined. This research confirms that the combined application of ATR-FTIR spectroscopy and chemometrics can be utilized to accurately identify TLI.

BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference.

The time since deposition (TSD) of a bloodstain, i.e., the time of a bloodstain formation is an essential piece of biological evidence in crime scene investigation. The practical usage of some existing microscopic methods (e.g., spectroscopy or RNA analysis technology) is limited, as their performance strongly relies on high-end instrumentation and/or rigorous laboratory conditions. This paper presents a practically applicable deep learning-based method (i.e., BloodNet) for efficient, accurate, and costless TSD inference from a macroscopic view, i.e., by using easily accessible bloodstain photos. To this end, we established a benchmark database containing around 50,000 photos of bloodstains with varying TSDs. Capitalizing on such a large-scale database, BloodNet adopted attention mechanisms to learn from relatively high-resolution input images the localized fine-grained feature representations that were highly discriminative between different TSD periods. Also, the visual analysis of the learned deep networks based on the Smooth Grad-CAM tool demonstrated that our BloodNet can stably capture the unique local patterns of bloodstains with specific TSDs, suggesting the efficacy of the utilized attention mechanism in learning fine-grained representations for TSD inference. As a paired study for BloodNet, we further conducted a microscopic analysis using Raman spectroscopic data and a machine learning method based on Bayesian optimization. Although the experimental results show that such a new microscopic-level approach outperformed the state-of-the-art by a large margin, its inference accuracy is significantly lower than BloodNet, which further justifies the efficacy of deep learning techniques in the challenging task of bloodstain TSD inference. Our code is publically accessible via https://github.com/shenxiaochenn/BloodNet. Our datasets and pre-trained models can be freely accessed via https://figshare.com/articles/dataset/21291825.

An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics.

Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions.

Pathological and ATR-FTIR spectral changes of delayed splenic rupture and medical significance.

Traumatic delayed splenic rupture often follows by a "latent period" without typical symptoms after injury. During this period, though there are no obvious symptoms, the injury is still present and changing. In this study, we constructed an SD rat model of delayed splenic rupture; evaluated the model by HE staining, Perl's staining, Masson trichrome staining and immunohistochemical staining; observed the pathological changes of spleen tissue in delayed splenic rupture at different times after splenic injury; we found that pathological change of injured tissues were different from non-injured, and has phases-change patterns, it can be roughly divided into three phases: 2-7 d, 10-14 d, and 18-28.We then investigated the relationship between the pathological changes and FTIR spectroscopy by chemometric methods. The main distinction of injured and non-injured tissue was the protein secondary structure of amide I, and the main distinctions of different phases of delayed splenic rupture were protein secondary structures and content of amide I and amide II.A classification model developed by SVM-DA was used to infer three phases (2-7 days, 10-12 days and 14-28 days). According to the most probable class, the accuracy of external validation is 96.7%. The results indicate that FTIR spectroscopy combined with various types of pathological staining has a potential for forensic identification and can provide theoretical support and diagnostic reference on clinical persistent injury.

Identifying traumatic brain injury (TBI) by ATR-FTIR spectroscopy in a mouse model.

Traumatic brain injury (TBI) is one of the most common mechanical injuries and plays a significant role in forensic practice. For cadavers, however, accurate diagnosis of TBI becomes a more and more challenging task as the level of decomposition increases. Our main purpose was to investigate whether TBI in putrefied mouse cadavers can be identified by Fourier Transform Infrared (FT-IR). The method proposed by Feeney et al. was used to establish the mouse TBI model. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) modeling were used to distinguish fresh and putrefied brain tissues. Then, we established two PLS-DA models to identify injured area samples in fresh and putrefied brain tissue samples. The accuracy of the two models were 100% and 92.5%. Our preliminary research has proved that the use of FT-IR spectroscopy combined with chemometrics can identify TBI more quickly and accurately in cadavers, providing crucial evidence for judicial proceedings.

Network pharmacology analysis reveals neuroprotection of Gynostemma pentaphyllum (Thunb.) Makino in Alzheimer' disease.

BACKGROUND: Alzheimer's disease (AD) is one of the most common neurodegenerative disorders in the world, but still lack of effective drug treatment. Gynostemma Pentaphyllum (Thunb.) Makino (GpM), a Chinese medicinal herb, plays important roles in anti-inflammation, anti-oxidative stress and anti-tumor, which has been reported to ameliorate cognitive impairment of AD. However, the neuroprotective mechanism of GpM remains unclear. This study aims to investigate the targets and possible signaling pathways of GpM in the treatment of AD. METHODS: Active compounds of GpM and their putative target proteins were selected from Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. AD-associated targets were identified from GeneCards, the Online Mendelian Inheritance in Man (OMIM) database and the Therapeutic Target Database (TTD). The intersecting targets of GpM and AD were identified and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were carried out to analyze the mechanism of them. Compound-target-pathway (CTP) network and protein-protein interaction (PPI) network were constructed and analyzed to elucidate the correlation between compounds, proteins and pathways. Molecular docking was performed to further demonstrate the possibility of GpM for AD. RESULTS: A total of 13 active compounds of GpM, 168 putative target proteins of compounds and 722 AD-associated targets were identified. Eighteen intersecting targets of GpM and AD were found and the epidermal growth factor receptor (EGFR), interleukin-1 beta (IL-1ß), interleukin-6 (IL-6), nitric oxide synthase in endothelial (NOS3) and serum paraoxonase/arylesterase 1 (PON1) were selected as the primary targets of GpM in the treatment of AD. The neuroprotective effect of GPM was related to a variety of pathways, including amoebiasis, HIF-1 signaling pathway, cytokine-cytokine receptor interaction and so on. CONCLUSIONS: Our findings elucidate the active compounds, targets and pathways of GpM involved in effects of anti-AD. The novel mechanism of GpM against AD provides more treatment options for AD.

The Efficacy Mechanism of Epigallocatechin Gallate against Pre-Eclampsia based on Network Pharmacology and Molecular Docking.

Pre-eclampsia (PE), a pregnancy complication, affects 3-5% of all pregnancies worldwide and is the main cause of maternal and perinatal morbidity. However, there is no drug which can clearly slow this disease progression. Epigallocatechin gallate (EGCG), a natural compound extracted from green tea, has been found to enhance the treatment efficacy of oral nifedipine against pregnancy-induced severe PE. This study aims to clarify the potential targets and pharmacological mechanisms of EGCG in treatment of PE. We used Traditional Chinese Medicine Systems Pharmacology database and Gene Cards database to obtain 179 putative target proteins of EGCG, 550 PE-related hub genes and 39 intersecting targets between EGCG and PE. By using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, we got the gene entries and enrichment pathways closely related to the intersecting targets. The top 10 enrichment pathways were pathway in cancer, proteoglycans in cancer, HIF-1 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, bladder cancer, hepatitis B, IL-17 signaling pathway, toxoplasmosis, PI3K-Akt signaling pathway. Furthermore, compound-target-pathway (CTP) and protein-protein interaction (PPI) network analysis were employed to explore the interaction of the top twelve targets for EGCG in treating PE. Molecular docking analysis showed combinations between these targets and EGCG, and the interaction between EGCG and the targets IL-6 and EGFR was confirmed by using molecular dynamic simulation. In conclusion, these findings hint the underlying mechanism of EGCG in the treatment of PE and point out directions in further studies on PE.

The COVID-19 pandemic, consumption and sovereign credit risk: Cross-country evidence.

Many recent studies investigate the economic effect of the COVID-19 pandemic in multiple aspects, while whether and how the sovereign credit risk reacts to the shock is still underexplored. Using a sample of forty developed and developing countries and employing staggered difference-in-differences models, we find that the sovereign credit risk measured by sovereign credit default swap spreads significantly increases after the COVID-19 pandemic outbreak, and the adverse effect is more pronounced for short-term credit risk. The reason is that the pandemic causes severe concerns about aggregate consumption contraction in addition to the fiscal capacity and the volatility of exports. We also find that fiscal stimuli stabilizing consumer spending alleviate the adverse effect of the COVID-19 pandemic, while debt relief does not matter. Overall, practitioners and policy makers should attach more importance to consumption and its recovery during the pandemic when making decisions.

Protection of Vasoactive Intestinal Peptide on the Blood-Brain Barrier Dysfunction Induced by Focal Cerebral Ischemia in Rats.

OBJECTIVE: To investigate the effects of vasoactive intestinal peptide on the blood brain barrier function after focal cerebral ischemia in rats. MATERIALS AND METHODS: Rats were intracerebroventricular injected with vasoactive intestinal peptide after a two hours middle cerebral artery occlusion. Functional outcome was studied with the neurological severity score. The brain edema and the infarction were evaluated via histology. The blood brain barrier permeability was assessed using Evans Blue dye injection method. We also measure the apoptosis of brain microvascular endothelial cells and brain levels of B-cell leukemia-2 protein by immunohistochemical analysis and western blotting, respectively. RESULTS: In contrast to the cases treated with vehicle at 72 h after middle cerebral artery occlusion, the treatment with vasoactive intestinal peptide significantly (P < 0.05) reduced the neurological severity score, the brain edema and infarct volume. The Evans Blue leakage and brain water content were obviously reduced (P < 0.05) in vasoactive intestinal peptide-treated rats compared with those of control rats at 72 and 96 h after stroke. In addition, vasoactive intestinal peptide decreased the numbers of terminal deoxynucleotidyl transferase-mediated dUTP-nick end labeling positive endothelial cells and increased the protein levels of B-cell leukemia-2 in the ischemic hemisphere at 72 h after ischemia. CONCLUSIONS: Our data suggest that treatment with vasoactive intestinal peptide ameliorates the blood brain barrier function, contributing to reduce in brain damage both morphologically and functionally in the ischemic rat. This amelioration may be associated with attenuation in apoptosis of brain microvascular endothelial cells by increased B-cell leukemia-2 expression.

Species identification of teeth of human and non-human.

Species identification is very important in forensic science case. However, the existing methods in forensic practice to identifying the species of bone and teeth are not objective, accurate or brief enough. We have reported the classification of bone species by Fourier transform infrared (FT-IR) and chemometric methods. Here we further use this method to realize the rapid detection of teeth species. 50 teeth samples from human and non-human (bovine, dog, rat, rabbit) were used in this study. Uncontrolled environment conditions were set to simulate real forensic casework. Teeth sample were prepared by grinding powder and pressed into KBr tablet, then the spectral data were collected. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used in the study. The internal and external validations of PLS-DA results were 97.1% and 93.3% accuracy, respectively. The results illustrate that FT-IR spectroscopy be used as a practical tool to identify species of unknown teeth.

Identification of myocardial fibrosis by ATR-FTIR spectroscopy combined with chemometrics.

Different degrees of myocardial fibrosis can often be observed in sudden cardiac death cases, so that the identification of myocardial fibrosis is an important step in forensics to identify cardiac death. Previous methods are restricted by complex algorithms, high cost, low sensitivity and high requirements. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an efficient and rapid method to identify tissue types, which has been used increasingly in forensics. This study aims to identify novel biophysical biomarkers of myocardial fibrosis and establish a prediction model by using ATR-FTIR analysis combined with chemometrics. A total of 129 tissue blocks taken from human hearts were cut into slices, and then ATR-FTIR spectroscopy and hematoxylin and eosin (HE) staining were performed. By using HE staining, the samples were divided into the experimental group (with myocardial fibrosis) and the control group (without myocardial fibrosis). The chemometrics classification results showed that the sensitivity and specificity of the training dataset were 0.91 and 1.0 respectively, and the sensitivity and specificity of the predictive dataset were 0.862 and 0.900. This study demonstrated that ATR-FTIR spectroscopy combined with chemometrics is a novel method for identifying myocardial fibrosis.

Analysis of Postmortem Intestinal Microbiota Successional Patterns with Application in Postmortem Interval Estimation.

Microorganisms play a vital role in the decomposition of vertebrate remains in natural nutrient cycling, and the postmortem microbial succession patterns during decomposition remain unclear. The present study used hierarchical clustering based on Manhattan distances to analyze the similarities and differences among postmortem intestinal microbial succession patterns based on microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns were obtained. Generally, the normal intestinal flora in the cecum was gradually decreased with changes in the living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied upon oxygen consumption. Furthermore, a random forest regression model was developed to predict the postmortem interval based on the microbial succession trend dataset. The model demonstrated a mean absolute error of 20.01 h and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and the Lachnospiraceae NK4A136 group were considered significant biomarkers for this model according to the ranked list. The present study explored microbial succession patterns in terms of relative abundances and variety, aiding in the prediction of postmortem intervals and offering some information on microbial behaviors in decomposition ecology.

A network pharmacology study on mechanism of resveratrol in treating preeclampsia via regulation of AGE-RAGE and HIF-1 signalling pathways.

Background: Preeclampsia (PE) is a hypertensive disorder of pregnancy that threatens the lives of millions of pregnant women and their babies worldwide. Without effective medications, there are thousands of maternal and child mortalities every year. Resveratrol (RSV), a non-flavonoid polyphenol extracted from multiple plants, has shown positive effects in treating hypertension, cardiovascular disorders, and even PE. This study aimed to explore the pharmacological mechanism of RSV in treating PE by using network pharmacology and bioinformatics. Methods: With the use of multiple databases, 66 intersecting targets were obtained from the 347 putative targets of RSV and 526 PE-related genes. Then, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted to investigate the functions of the intersecting targets. The protein-protein interaction network and target-pathway network were drawn and analyzed to illustrate the correlation between targets and pathways. Finally, molecular docking was conducted to calculate the binding energy between RSV and core targets. Results: The results showed that the core targets of RSV were IL6, TNF, IL1B, VEGFA, STAT3, and EGFR. There existed good binding between RSV and IL6, TNF, IL1B, VEGFA, and EGFR. In addition, we found that RSV mainly functioned in the AGE-RAGE and HIF-1 signaling pathways, which are associated with the occurrence and development of PE. Conclusion: In conclusion, our findings indicated that RSV has the effects of regulating angiogenesis and anti-inflammation and can be a candidate medicine for treating PE.

Identification of antemortem and postmortem fractures in a complex environment by FTIR spectroscopy based on a rabbit tibial fracture self-control model.

The identification of antemortem and postmortem fractures is a critical and challenging task for forensic researchers. Based on our preliminary studies, we explored whether the combination of Fourier transform infrared spectroscopy (FTIR) and chemometrics can identify antemortem and postmortem fractures in complex environments. The impacts of the four environments on the bone spectrum were analyzed by principal component analysis (PCA). It was found that the bone degradation rate in the submerged and ground surface (GS) environments was higher than that in the buried and constant temperature and moisture (CTM) environments. Additionally, the bone degradation rate in buried environment higher than that in the CTM environment. The average spectrum, PCA and partial least squares discriminant analysis (PLS-DA) results all revealed that there were significant differences between the antemortem fracture and the remaining three groups in a complex environment. Compared with the antemortem fracture, the antemortem fracture control (AFC) and postmortem fracture control (PFC) tended to be more similar to the postmortem fracture. According to the loading plot, amide I and amide II were the main components that contributed to the identification of the antemortem fracture, AFC, postmortem fracture, and PFC. Finally, we established a differential model for the antemortem and postmortem fractures (an accuracy of 96.9%), and a differentiation model for the antemortem fracture, AFC, postmortem fracture, and PFC (an accuracy of 87.5%). In conclusion, FTIR spectroscopy is a reliable tool for the identification of antemortem and postmortem fractures in complex environments.

In vitro ubiquitination and degradation of bacteria-purified human histone H2B by the nucleoli fractions.

Histones are the main components of chromatin, and the protein levels of histones significantly affect chromatin assembly. Here, we describe detailed protocols for histone H2B purification from bacteria and for the separation of nucleolar fractions and cytoplasmic and nucleoplasmic fractions. Finally, the in vitro ubiquitination and degradation of H2B by distinct cellular fractions are described. For complete details on the use and execution of this protocol, please refer to Liu et al. (2021).

Grape seed proanthocyanidins improves depression-like behavior by alleviating oxidative stress and NLRP3 activation in the hippocampus of prenatally-stressed female offspring rats.

Over several decades, there is a growing evidence, which has shown that prenatal stress (PS) contributes to depression in offspring. Grape seed proanthocyanidins (GSPs), which contain dimers, trimers, oligomers of catechin and epicatechin, are known to possess antidepressant effects. The present study aimed to investigate the mechanism of antidepressant effects of GSPs on female juvenile prenatally stressed offspring rats. The results showed that the female juvenile offspring rats exposed to PS exhibited depression-like behavior manifested as longer immobility time and lesser consumption of sucrose solution. Prenatal stress reduced the number of hippocampal neurons and increased the level of the reactive oxygen species (ROS) in the hippocampus of the female juvenile offspring rats. Furthermore, the expression of PYD domains-containing protein 3 (NLRP3) and its downstream cytokines, Caspase-1, and interleukin-1ß (IL-1ß), were increased in the hippocampus of the female juvenile offspring rats exposed to PS. Administration of GSPs not only improved depression-like behavior and enhanced the number of hippocampal neurons, but also abated excessive ROS generation and inhibited the activation of the NLRP3-Caspase-1 signaling pathway. Taken together, GSPs counteract PS-induced hippocampal neuron loss and depression-like behavior by alleviating oxidative stress and NLRP3 activation. The present study provides a new insight for GSPs as an effective therapeutic agent for adolescent depression.

Species identification of semen stains by ATR-FTIR spectroscopy.

Semen stains are the most important biological evidence when identifying the aggressor in sexual assault cases. Current detecting assays of semen stains species identification were not confirmative enough. In this study, we investigated the potential of species identification of semen stains by using attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy combined with advanced chemometrics methods. The effect of substrates types and time since deposition (TSD) were considered in the study. A partial least squares-discriminant analysis (PLS-DA) classification model was established which demonstrated complete separation between human and other species (rabbit, dog, boar, bull, and ram). Validation was conducted which showed prediction abilities with 100% accuracy. Additionally, we found species identification could be achieved without sperm cells which proved ability of spectroscopic methods detecting the semen samples from the case of azoospermia. This work provides a powerful and practical tool for species identification of semen stains in real forensic casework.

Identification of antemortem, perimortem and postmortem fractures by FTIR spectroscopy based on a rabbit tibial fracture model.

The identification of antemortem, perimortem and postmortem fractures is very important for forensic pathologists and anthropologists. However, traditional methods are subjective, time-consuming, and have low accuracy, which do not fundamentally solve the problem. In this study, we utilized Fourier transform infrared (FTIR) spectroscopy and chemometrics to identify antemortem, perimortem and postmortem fractures in a rabbit tibial fracture model. Based on the results of the principal component analysis (PCA), changes in the ante-perimortem fracture repair process are mainly associated with protein variations, while postmortem fractures are more likely to result in lipid changes during degradation. Then, a partial least squares discriminant analysis (PLS-DA) was performed to assess the classification ability of the training and predictive datasets, with classification accuracies of 88.9% and 86.7%, respectively. According to the latent variable 1 (LV1) loading plot, amide I and amide II (proteins) are mostly classified as ante-perimortem and postmortem fractures. In conclusion, FTIR spectroscopy is a reliable tool to identify antemortem, perimortem and postmortem fractures. FTIR has the advantages of rapid, objective and strong discrimination. and shows great potential for analyzing forensic cases under actual natural conditions.