Biomarkers Screening and Mechanisms Analysis of the Restraint Stress-Induced Myocardial Injury in Hyperlipidemia ApoE-/- Mice.

OBJECTIVES: To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE-/- mice. METHODS: The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE-/- mice. Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers. RESULTS: Proteomic analysis showed that there were 43 significantly up-regulated and 58 significantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group. Among them, GBP2, TAOK3, TFR1 and UCP1 were biomarkers with great diagnostic potential. KEGG pathway enrichment analysis indicated that ferroptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model. The mmu_circ_0001567/miR-7a/Tfr-1 and mmu_circ_0001042/miR-7a/Tfr-1 might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model. CONCLUSIONS: Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferroptosis. Four potential biomarkers are selected for myocardial injury diagnosis, providing a new direction for sudden cardiac death (SCD) caused by hyperlipidemia combined with the restraint stress.

Zwitterion-Lubricated Hydrogel Microspheres Encapsulated with Metformin Ameliorate Age-Associated Osteoarthritis.

Chondrocyte senescence and reduced lubrication play pivotal roles in the pathogenesis of age-related osteoarthritis (OA). In the present study, highly lubricated and drug-loaded hydrogel microspheres are designed and fabricated through the radical polymerization of sulfobetaine (SB)-modified hyaluronic acid methacrylate using microfluidic technology. The copolymer contains a large number of SB and carboxyl groups that can provide a high degree of lubrication through hydration and form electrostatic loading interactions with metformin (Met@SBHA), producing a high drug load for anti-chondrocyte senescence. Mechanical, tribological, and drug release analyses demonstrated enhanced lubricative properties and prolonged drug dissemination of the Met@SBHA microspheres. RNA sequencing (RNA-seq) analysis, network pharmacology, and in vitro assays revealed the extraordinary capacity of Met@SBHA to combat chondrocyte senescence. Additionally, inducible nitric oxide synthase (iNOS) has been identified as a promising protein modulated by Met in senescent chondrocytes, thereby exerting a significant influence on the iNOS/ONOO-/P53 pathway. Notably, the intra-articular administration of Met@SBHA in aged mice ameliorated cartilage senescence and OA pathogenesis. Based on the findings of this study, Met@SBHA emerges as an innovative and promising strategy in tackling age-related OA serving the dual function of enhancing joint lubrication and mitigating cartilage senescence.

Targeting endothelial PDGFR-ß facilitates angiogenesis-associated bone formation through the PAK1/NICD axis.

The intricate orchestration of osteoporosis (OP) pathogenesis remains elusive. Mounting evidence suggests that angiogenesis-driven osteogenesis serves as a crucial foundation for maintaining bone homeostasis. This study aimed to explore the potential of the endothelial platelet-derived growth factor receptor-ß (PDGFR-ß) in mitigating bone loss through its facilitation of H-type vessel formation. Our findings demonstrate that the expression level of endothelial PDGFR-ß is reduced in samples obtained from individuals suffering from OP, as well as in ovariectomy mice. Depletion of PDGFR-ß in endothelial cells ameliorates angiogenesis-mediated bone formation in mice. The regulatory influence of endothelial PDGFR-ß on H-type vessels is mediated through the PDGFRß-P21-activated kinase 1-Notch1 intracellular domain signaling cascade. In particular, the endothelium-specific enhancement of PDGFR-ß facilitates H-type vessels and their associated bone formation in OP. Hence, the strategic targeting of endothelial PDGFR-ß emerges as a promising therapeutic approach for the management of OP in the near future.

Wnt activation disturbs cell competition and causes diffuse invasion of transformed cells through NF-κB-MMP21 pathway.

Normal epithelial cells exert their competitive advantage over RasV12-transformed cells and eliminate them into the apical lumen via cell competition. However, the internal or external factors that compromise cell competition and provoke carcinogenesis remain elusive. In this study, we examine the effect of sequential accumulation of gene mutations, mimicking multi-sequential carcinogenesis on RasV12-induced cell competition in intestinal epithelial tissues. Consequently, we find that the directionality of RasV12-cell extrusion in Wnt-activated epithelia is reversed, and transformed cells are delaminated into the basal lamina via non-cell autonomous MMP21 upregulation. Subsequently, diffusively infiltrating, transformed cells develop into highly invasive carcinomas. The elevated production of MMP21 is elicited partly through NF-κB signaling, blockage of which restores apical elimination of RasV12 cells. We further demonstrate that the NF-κB-MMP21 axis is significantly bolstered in early colorectal carcinoma in humans. Collectively, this study shows that cells with high mutational burdens exploit cell competition for their benefit by behaving as unfit cells, endowing them with an invasion advantage.

Endothelial PDGF-BB/PDGFR-ß signaling promotes osteoarthritis by enhancing angiogenesis-dependent abnormal subchondral bone formation.

The mechanisms that coordinate the shift from joint homeostasis to osteoarthritis (OA) remain unknown. No pharmacological intervention can currently prevent the progression of osteoarthritis. Accumulating evidence has shown that subchondral bone deterioration is a primary trigger for overlying cartilage degeneration. We previously found that H-type vessels modulate aberrant subchondral bone formation during the pathogenesis of OA. However, the mechanism responsible for the elevation of H-type vessels in OA is still unclear. Here, we found that PDGFR-ß expression, predominantly in the CD31hiEmcnhi endothelium, was substantially elevated in subchondral bones from OA patients and rodent OA models. A mouse model of OA with deletion of PDGFR-ß in endothelial cells (ECs) exhibited fewer H-type vessels, ameliorated subchondral bone deterioration and alleviated overlying cartilage degeneration. Endothelial PDGFR-ß promotes angiogenesis through the formation of the PDGFR-ß/talin1/FAK complex. Notably, endothelium-specific inhibition of PDGFR-ß by local injection of AAV9 in subchondral bone effectively attenuated the pathogenesis of OA compared with that of the vehicle-treated controls. Based on the results from this study, targeting PDGFR-ß is a novel and promising approach for the prevention or early treatment of OA.

Non-degradable autophagic vacuoles are indispensable for cell competition.

Cell competition is a process by which unwanted cells are eliminated from tissues. Apical extrusion is one mode whereby normal epithelial cells remove transformed cells, but it remains unclear how this process is mechanically effected. In this study, we show that autophagic and endocytic fluxes are attenuated in RasV12-transformed cells surrounded by normal cells due to lysosomal dysfunction, and that chemical manipulation of lysosomal activity compromises apical extrusion. We further find that RasV12 cells deficient in autophagy initiation machinery are resistant to elimination pressure exerted by normal cells, suggesting that non-degradable autophagic vacuoles are required for cell competition. Moreover, in vivo analysis revealed that autophagy-ablated RasV12 cells are less readily eliminated by cell competition, and remaining transformed cells destroy ductal integrity, leading to chronic pancreatitis. Collectively, our findings illuminate a positive role for autophagy in cell competition and reveal a homeostasis-preserving function of autophagy upon emergence of transformed cells.

Non/mini-invasive monitoring of diabetes-induced myocardial damage by Fourier transform infrared spectroscopy: Evidence from biofluids.

Early identification of diabetic cardiomyopathy (DCM) can help clinicians develop targeted treatment plans and forensic pathologists make accurate postmortem diagnoses. In the present study, diabetes-induced metabolic abnormalities in the myocardium and biofluids (plasma, urine, and saliva) of db/db mice of various ages (7, 12, and 21 weeks) were investigated by attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results indicated that the diabetic and control groups had significantly different changes in the function groups of lipids, phosphate macromolecules (mostly nucleic acids), protein compositions and conformations, and carbohydrates (primarily glucose) in the myocardium and biofluids. The prediction model for quantifying DCM severity was developed on db/db mice's myocardial spectra using a genetic algorithm (GA)-partial least squares (PLS) regression method. Following that, the linear correlations between the predicted values for DCM severity and spectra for db/db biofluids were evaluated using the GA-PLS regression algorithm. The results showed there were good linear correlations between the predicted values for DCM severity and spectra for plasma (R2 = 0.929), saliva (R2 = 0.967), urine (R2 = 0.954), and combination of plasma and saliva (R2 = 0.980). This study provides a novel perspective on detecting diabetes-related biofluid and cardiac metabolic abnormalities and demonstrates the potential of biofluid infrared spectro-diagnostic models for non/mini-invasive assessment of DCM.

Investigation of early biochemical alterations in myocardia of the diabetic db/db mice by FTIR microspectroscopy combined with machine learning.

Diabetic cardiomyopathy (DbCM) is a serious complication of diabetes that affects about 12% of the diabetic population. Sensitive detection of diabetes-induced biochemical changes in the heart before symptoms appear can assist clinicians in developing targeted treatment plans and forensic pathologists in making accurate postmortem diagnoses. The Fourier transform infrared (FTIR) spectroscopy-based approach allows for the analysis of the sample biomolecular composition and variations. In the current study, the myocardial tissues of mouse models of type 2 diabetes mellitus (T2DM) at various ages (7, 12, and 21 weeks) were analyzed using FTIR microspectroscopy (FTIRM) in combination with machine learning algorithms. The carbonyl esters, olefinic=CH and CH2 groups of lipids, total lipids, saccharides, and ß-sheet to α-helix conformational transition in proteins increased significantly in diabetic mice myocardial tissues compared to healthy mice. Furthermore, partial least-squares discriminant analysis and random forest-guided partial least-squares discriminant analysis revealed the time-dependent progression of the spectral lipidomic profiles during the development of DbCM. Finally, a random forest classifier was developed for diagnosing DbCM, with 97.1% accuracy. This study demonstrates that FTIRM is a novel method for monitoring early biochemical changes in the myocardia of mice with T2DM.

Post-mortem evaluation of the pathological degree of myocardial infarction by Fourier transform infrared microspectroscopy.

In clinical and forensic investigations, accurate post-mortem diagnosis of the pathological degree of myocardial infarction (MI) is critical. However, because of the observer variability, the diagnosis cannot be made objectively. Many studies have shown that Fourier transform infrared (FTIR) microspectroscopy is non-invasive, observer-independent, and label-free when analyzing biological tissues. In this study, we used FTIR microspectroscopy in combination with intelligent algorithms to identify the pathological phases in human infarcted cardiac tissues, including ischemia, necrotic, granulation, and fibrotic stages. First, a comparison of infrared spectra corresponding to infarcted tissue pathological categories revealed various spectral properties. The results of unsupervised principal component analysis (PCA) revealed a clear distinction between these four pathological stages and the normal stage. Then, to identify these five stages, an automatic artificial neural network (ANN) classifier was effectively created. Finally, two-dimensional pseudo-color images of two infarcted cardiac tissue sections visualized via the ANN classifier showed great agreement with their histological images. These findings demonstrate that FTIR microspectroscopy has the potential for the post-mortem evaluation of the pathological degree of MI.

Fourier-transform infrared microspectroscopy of pulmonary edema fluid for postmortem diagnosis of diabetic ketoacidosis.

Determination of the cause of death for diabetic ketoacidosis (DKA), a common and fatal acute complication of diabetes mellitus, is a challenging forensic task owing to the lack of characteristic morphological findings at autopsy. In this study, Fourier-transform infrared (FTIR) microspectroscopy coupled with chemometrics was employed to characterize biochemical differences in pulmonary edema fluid from different causes of death to supplement conventional methods and provide an efficient postmortem diagnosis of DKA. With this aim, FTIR spectra in three different situations (DKA-caused death, other causes of death with diabetes history, and other causes of death without diabetes history) were measured. The results of principal component analysis indicated different spectral profiles between these three groups, which mainly exhibited variations in proteins. Subsequently, two binary classification models were established using an algorithm of partial least squares discriminant analysis (PLS-DA) to determine whether decedents had diabetes and whether the diabetic patients died from DKA. Satisfactory prediction results of PLS-DA models demonstrated good differentiation among these three groups. Therefore, it is feasible to make a postmortem diagnosis of DKA and detect diabetes history via FTIR microspectroscopic analysis of the pulmonary edema fluid.

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

Semen stain is one of the most important biological evidence at sexual crime scenes. Age estimation of human semen stains plays an important role in forensic work, and it is rarely studied due to lack of well-established methods. In this study, the technique called attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates: glass slides, tissues and fabric made of regenerated cellulose fibres up to 6 d. Partial least squares regression (PLSR) was used in conjunction with spectral analysis for age estimation, and the results generated high R 2 values (cross-validation: 0.81, external validation: 0.74) but a narrow margin of error for root mean square error (RMSE) (RMSE of cross-validation: 0.77 d, RMSE of prediction: 1.02 d). Additionally, our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study. Our results indicate that ATR-FTIR, combined with chemometric methods, shows great potential as a convenient and efficient tool for age estimation of semen stains. Moreover, the method could be applied to routine forensic investigations in the future.

Identifying muscle hemorrhage in rat cadavers with advanced decomposition by FT-IR microspectroscopy combined with chemometrics.

The identification of muscle hemorrhage in a cadaver that is in an advanced stage of decomposition is an important but challenging task. Our study investigated whether Fourier transform infrared (FT-IR) microspectroscopy in conjunction with chemometrics could identify muscle hemorrhage using rat cadavers with advanced decomposition. In this study, an intramuscular blood injection method, instead of a mechanical injury method, was used to construct a muscle hemorrhage model, and the modeling idea of muscle hemorrhage identification was to discriminate and classify hemoglobin-leaking myofibrils from negative myofibrils. First, the optical images of hematoxylin/eosin (H&E) stained hemorrhagic muscle at different postmortem intervals (PMIs) were observed and showed that the morphological features of whole erythrocytes disappeared since the PMI of 4 d. Subsequently, principle component analysis (PCA) was performed and indicated that the biochemical differences in protein structures between fresh erythrocytes and myofibrils can be detected by the IR spectroscopic method. Ultimately, several classification models based on the partial least square discriminant analysis (PLS-DA) algorithm were successfully constructed for different PMIs and PMI ranges and achieved great prediction performances in external validations. This preliminary study demonstrates the feasibility of using FT-IR microspectroscopy combined with chemometrics as a potential approach for identifying muscle hemorrhage in cadavers with advanced decomposition for offering vital evidences in judicial process.

Determination of causes of death via spectrochemical analysis of forensic autopsies-based pulmonary edema fluid samples with deep learning algorithm.

This study investigated whether infrared spectroscopy combined with a deep learning algorithm could be a useful tool for determining causes of death by analyzing pulmonary edema fluid from forensic autopsies. A newly designed convolutional neural network-based deep learning framework, named DeepIR and eight popular machine learning algorithms, were used to construct classifiers. The prediction performances of these classifiers demonstrated that DeepIR outperformed the machine learning algorithms in establishing classifiers to determine the causes of death. Moreover, DeepIR was generally less dependent on preprocessing procedures than were the machine learning algorithms; it provided the validation accuracy with a narrow range from 0.9661 to 0.9856 and the test accuracy ranging from 0.8774 to 0.9167 on the raw pulmonary edema fluid spectral dataset and the nine preprocessing protocol-based datasets in our study. In conclusion, this study demonstrates that the deep learning-equipped Fourier transform infrared spectroscopy technique has the potential to be an effective aid for determining causes of death.

Postmortem Diagnosis of Fatal Hypothermia by Fourier Transform Infrared Spectroscopic Analysis of Edema Fluid in Formalin-Fixed, Paraffin-Embedded Lung Tissues.

The goal of this study was to investigate whether pulmonary edema could become a specific diagnostic marker for fatal hypothermia using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics. The spectral profile analysis indicated that hypothermia fatalities associated with pulmonary edema fluid contained more ß-sheet protein conformational structures than the control causes of death, which included sudden cardiac death, brain injury, cerebrovascular disease, mechanical asphyxiation, intoxication, and drowning. Subsequently, the results of principal component analysis (PCA) further revealed that the content of ß-sheet protein conformational structures in the pulmonary edema fluid was the main discriminatory marker between fatal hypothermia and the other causes of death. Ultimately, a robust postmortem diagnostic model for fatal hypothermia using a partial least-squares discriminant analysis (PLS-DA) algorithm was constructed. Pulmonary edema fluid spectra collected from eight new forensic autopsy cases that did not participate in the construction of the diagnostic model were predicted using the model. The results showed the causes of death of all these eight cases were correctly classified. In conclusion, this preliminary study demonstrates that FTIR spectroscopy in combination with chemometrics could be a promising approach for the postmortem diagnosis of fatal hypothermia.

Postmortem diagnosis of fatal hypothermia/hyperthermia by spectrochemical analysis of plasma.

Postmortem diagnosis of extreme-weather-related deaths is a challenging forensic task. Here, we present a state-of-the-art study that employed attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy in combination with Chemometrics for postmortem diagnosis of fatal hypothermia/hyperthermia by biochemical investigation of plasma in rats. The results of principal component analysis (PCA) and spectral analysis revealed that plasma samples from the fatal hypothermia, fatal hyperthermia, and control groups, are substantially different from each other based on the spectral variations associated with the lipid, carbohydrate and nucleic acid components. Two partial least squares-discriminant analysis (PLS-DA) classification models (hypothermia-nonhypothermia and hyperthermia-nonhyperthermia binary models) with a 100% accuracy rate were constructed. Subsequently, internal cross-validation was performed to assess the robustness of these two models, which resulted in 98.1 and 100% accuracy. Ultimately, classification predictions of 42 unknown plasma samples were performed by these two models, and both models achieved 100% accuracy. Additionally, our results demonstrated that hemolysis and postmortem hypothermic/hyperthermic effects did not weaken the prediction ability of these two classification models. In summary, this work demonstrates ATR-FTIR spectroscopy's great potential for postmortem diagnosis of fatal hypothermia/hyperthermia.

Biochemical detection of fatal hypothermia and hyperthermia in affected rat hypothalamus tissues by Fourier transform infrared spectroscopy.

It is difficult to determinate the cause of death from exposure to fatal hypothermia and hyperthermia in forensic casework. Here, we present a state-of-the-art study that employs Fourier-transform infrared (FTIR) spectroscopy to investigate the hypothalamus tissues of fatal hypothermic, fatal hyperthermic and normothermic rats to determine forensically significant biomarkers related to fatal hypothermia and hyperthermia. Our results revealed that the spectral variations in the lipid, protein, carbohydrate and nucleic acid components are highly different for hypothalamuses after exposure to fatal hypothermic, fatal hyperthermic and normothermic conditions. In comparison with the normothermia group, the fatal hypothermia and hyperthermia groups contained higher total lipid amounts but were lower in unsaturated lipids. Additionally, their cell membranes were found to have less motional freedom. Among these three groups, the fatal hyperthermia group contained the lowest total proteins and carbohydrates and the highest aggregated and dysfunctional proteins, while the fatal hypothermia group contained the highest level of nucleic acids. In conclusion, this study demonstrates that FTIR spectroscopy has the potential to become a reliable method for the biochemical characterization of fatal hypothermia and hyperthermia hypothalamus tissues, and this could be used as a postmortem diagnostic feature in fatal hypothermia and hyperthermia deaths.

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectral prediction of postmortem interval from vitreous humor samples.

Evaluation of postmortem interval (PMI) is of paramount importance to guide criminal investigations, especially when witnesses are not found. However, accurate PMI estimation is a challenging task in the forensic community due to the limitations of existing methods. The study aims to investigate the potential of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy for predicting PMI based on vitreous humor (VH). VH samples were collected from 72 rabbits in the range of 0-48 h postmortem at a 6-h interval. Their FTIR spectra were normalized by the extended multiplicative signal correction (RMSC) and divided into calibration and validation sets. After analysis of the absorption bands, the Bayesian ridge regression (BRR), support vector regression (SVR), and artificial neural network (ANN) methods were established by the calibration set using a 10-fold cross-validation that was further used to predict the PMI in the validation set. The validity of the models was assessed by a permutation test. The current study demonstrated that multiple macromolecules in the VH samples were reflected in a FTIR spectrum, and the spectral absorption bands at 1313 and 925 cm-1 were highly correlated with PMI. The three models allowed generalization to the validation set due to similar R2 and errors between the calibration and validation tests. The highest accuracy with R2 = 0.983 and error = 2.018 h was achieved by the ANN model in the validation test. The results suggest that ATR-FTIR spectroscopy may be useful for VH analysis in order to predict PMI in the future. Graphical abstract ᅟ.

Identification of Pulmonary Edema in Forensic Autopsy Cases of Sudden Cardiac Death Using Fourier Transform Infrared Microspectroscopy: A Pilot Study.

Many studies have proven the usefulness of biofluid-based infrared spectroscopy in the clinical domain for diagnosis and monitoring the progression of diseases. Here we present a state-of-the-art study in the forensic field that employed Fourier transform infrared microspectroscopy for postmortem diagnosis of sudden cardiac death (SCD) by in situ biochemical investigation of alveolar edema fluid in lung tissue sections. The results of amide-related spectral absorbance analysis demonstrated that the pulmonary edema fluid of the SCD group was richer in protein components than that of the neurologic catastrophe (NC) and lethal multiple injuries (LMI) groups. The complementary results of unsupervised principle component analysis (PCA) and genetic algorithm-guided partial least-squares discriminant analysis (GA-PLS-DA) further indicated different global spectral band patterns of pulmonary edema fluids between these three groups. Ultimately, a random forest (RF) classification model for postmortem diagnosis of SCD was built and achieved good sensitivity and specificity scores of 97.3% and 95.5%, respectively. Classification predictions of unknown pulmonary edema fluid collected from 16 cases were also performed by the model, resulting in 100% correct discrimination. This pilot study demonstrates that FTIR microspectroscopy in combination with chemometrics has the potential to be an effective aid for postmortem diagnosis of SCD.

Species identification of bloodstains by ATR-FTIR spectroscopy: the effects of bloodstain age and the deposition environment.

In this study, we investigated the potential of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy combined with advanced chemometrics for species identification of bloodstains similar to evidence obtained from real crime scenes. Two partial least squares-discriminant analysis classification models (a human-mammal-domestic fowl trilateral model and a species-specific model) were established. The models demonstrated complete separation among the three classes (human, mammal, and domestic fowl) and distinguished six species (human, rat, rabbit, dog, chicken, and duck). Validation was subsequently conducted to evaluate the robustness of these two models, which resulted in 100 and 94.2% accuracy; even human bloodstains placed in an outdoor environment for up to 107 days were successfully identified. Additionally, all bloodstains were positively identified as blood using the squared Euclidean cosine method by comparing the spectra with those of non-blood substances that had a similar appearance or easily produced false positives. These results demonstrate that ATR-FTIR spectroscopy combined with chemometrics can be a powerful tool for species identification of bloodstains.

Identification of pulmonary edema in forensic autopsy cases of fatal anaphylactic shock using Fourier transform infrared microspectroscopy.

Anaphylaxis is a rapid allergic reaction that may cause sudden death. Currently, postmortem diagnosis of anaphylactic shock is sometimes difficult and often achieved through exclusion. The aim of our study was to investigate whether Fourier transform infrared (FTIR) microspectroscopy combined with pattern recognition methods would be complementary to traditional methods and provide a more accurate postmortem diagnosis of fatal anaphylactic shock. First, the results of spectral peak area analysis showed that the pulmonary edema fluid of the fatal anaphylactic shock group was richer in protein components than the control group, which included mechanical asphyxia, brain injury, and acute cardiac death. Subsequently, principle component analysis (PCA) was performed and showed that the anaphylactic shock group contained more turn and α-helix protein structures as well as less tyrosine-rich proteins than the control group. Ultimately, a partial least-square discriminant analysis (PLS-DA) model combined with a variables selection method called the genetic algorithm (GA) was built and demonstrated good separation between these two groups. This pilot study demonstrates that FTIR microspectroscopy has the potential to be an effective aid for postmortem diagnosis of fatal anaphylactic shock.