Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenarios, alternative molecular methods are required. An example of this is the detection of menstrual fluid and vaginal material, which are not able to be identified using conventional techniques. Endpoint reverse-transcription PCR (RT-PCR) is currently used for this purpose to amplify body fluid specific messenger RNA (mRNA) transcripts in forensic casework. Real-time quantitative reverse-transcription PCR (RT-qPCR) is a similar method but utilises fluorescent markers to generate quantitative results in the form of threshold cycle (Cq) values. Despite the uncertainty surrounding body fluid identification, most interpretation guidelines utilise categorical statements. Probabilistic modelling is more realistic as it reflects biological variation as well as the known performance of the method. This research describes the application of various machine learning models to single-source mRNA profiles obtained by RT-qPCR and assesses their performance. Multinomial logistic regression (MLR), Naïve Bayes (NB), and linear discriminant analysis (LDA) were used to discriminate between the following body fluid categories: saliva, circulatory blood, menstrual fluid, vaginal material, and semen. We identified that the performance of MLR was somewhat improved when the quantitative dataset of the original Cq values was used (overall accuracy of approximately 0.95) rather than presence/absence coded data (overall accuracy of approximately 0.94). This indicates that the quantitative information obtained by RT-qPCR amplification is useful in assigning body fluid class. Of the three classification methods, MLR performed the best. When we utilised receiver operating characteristic curves to observe performance by body fluid class, it was clear that all methods found difficulty in classifying menstrual blood samples. Future work will involve the modelling of body fluid mixtures, which are common in samples analysed as part of sexual assault investigations.

Degradation of human mRNA transcripts over time as an indicator of the time since deposition (TsD) in biological crime scene traces.

Knowledge about the age of a stain, also termed as time since deposition (TsD), would provide law-enforcing authorities with valuable information for the prosecution of criminal offenses. Yet, there is no reliable method for the inference / assessment of TsD available. The aim of this study was to gain further insight into the RNA degradation pattern of forensically relevant body fluids and to find candidate markers for TsD estimation. Blood, menstrual blood, saliva, semen and vaginal secretion samples were exposed to indoor (dark, room temperature) and outdoor (exposed to sun, wind, etc. but protected from rain) conditions for up to 1.5 years. Based on expression and degradation analyses, we were able to identify body fluid specific signatures and RNA degradation patterns. The indoor samples showed a marked drop in RNA integrity after 6 months, while the outdoor samples were difficult to interpret and therefore excluded for some of the analyses. Up to 4 weeks, indoor samples showed more stable and less degrading transcripts than outdoor samples. Stable transcripts tended to be significantly shorter than degrading ones or transcripts, which are neither degrading nor stable. We reinforced the body fluid specific and the housekeeping gene nature of previously reported markers. With an unbiased approach, we selected stable and degrading genes for each body fluid in the short term and assessed their integrity during extended storage. We identified several stable and degrading gene transcripts, which could be tested in a targeted assay to assess the TsD interval e.g. by analyzing the ratio of degrading vs stable transcripts. In conclusion, we were able to detect RNA degradation patterns in samples being aged up to 1.5 years and identified several candidate markers, which could be evaluated for TsD estimation.

Identification of coding region SNPs from specific and sensitive mRNA biomarkers for the deconvolution of the semen donor in a body fluid mixture.

mRNA markers provide a very promising method for the identification of human body fluids or tissues in the context of forensic investigations. Previous studies have shown that different body fluids can be distinguished from each other according to their specific mRNA biomarkers. In this study, we evaluated eight semen-specific mRNA markers (KLK3, NKX3-1, CKB, KLK2, PRAC1, SEMG1, TGM4, and SORD) that encompass 12 coding single nucleotide polymorphisms (cSNPs) to identify the semen contributor in a mixed stain. Five highly specific and sensitive mRNA markers for blood, menstrual blood, saliva, vaginal secretions, and skin were also incorporated into the PCR system as body fluid-positive controls. Reverse transcription polymerase chain reaction (RT-PCR), multiplex PCR and SNaPshot mini-sequencing assays were established for the identification of semen-specific mRNA. The amplicon size ranged from 133 to 337 bp. The semen-specific system was examined against blood, menstrual blood, saliva, vaginal secretions, and skin swabs. The eight mRNA biomarkers were semen-specific and could be successfully typed in laboratory-generated mixtures composed of different body fluids supplemented with 1 ng of semen cDNA. This system possessed a high sensitivity that ranged from 1:10-1:100 for detecting trace amounts of semen in semen-containing body fluid mixtures. Additionally, our results demonstrated that the cSNPs polymorphisms included in the mRNA markers were concordant with genomic DNA (gDNA). Despite the presence of other body fluids, the system exhibited high sensitivity and specificity to the semen in the mixture. In future studies, we will add other cSNPs from the semen-specific genes using massively parallel sequencing to further improve our system.

Calculating LRs for presence of body fluids from mRNA assay data in mixtures.

Messenger RNA (mRNA) profiling can identify body fluids present in a stain, yielding information on what activities could have taken place at a crime scene. To account for uncertainty in such identifications, recent work has focused on devising statistical models to allow for probabilistic statements on the presence of body fluids. A major hurdle for practical adoption is that evidentiary stains are likely to contain more than one body fluid and current models are ill-suited to analyse such mixtures. Here, we construct a likelihood ratio (LR) system that can handle mixtures, considering the hypotheses H1: the sample contains at least one of the body fluids of interest (and possibly other body fluids); H2: the sample contains none of the body fluids of interest (but possibly other body fluids). Thus, the LR-system outputs an LR-value for any combination of mRNA profile and set of body fluids of interest that are given as input. The calculation is based on an augmented dataset obtained by in silico mixing of real single body fluid mRNA profiles. These digital mixtures are used to construct a probabilistic classification method (a 'multi-label classifier'). The probabilities produced are subsequently used to calculate an LR, via calibration. We test a range of different classification methods from the field of machine learning, ways to preprocess the data and multi-label strategies for their performance on in silico mixed test data. Furthermore, we study their robustness to different assumptions on background levels of the body fluids. We find logistic regression works as well as more flexible classifiers, but shows higher robustness and better explainability. We test the system's performance on lab-generated mixture samples, and discuss practical usage in case work.

Lactoferrin levels in cervical fluid from in vitro fertilization (IVF) patients - correlation with IVF parameters.

Since our previous results suggest that lactoferrin (LF) might have roles in the reproductive process and that its levels might change in the female tract as a response to various factors, the aim of this investigation was to assess whether LF levels in cervical secretions correlate with reproductive parameters from in vitro fertilization (IVF) patients. Cervical fluid samples were obtained from 34 women under 40 years old enrolled for assisted reproduction techniques, and LF concentration was measured. The mean total protein concentration in all cervical fluid samples was 842.8 ± 116.9 µg/mL. The mean concentration of LF was 0.73 ± 0.06 ng LF/µg of total proteins. We observed that higher LF levels in cervical fluid correlated with lower IVF rates when all patients were analyzed; this negative correlation was also sustained when only patients ≥35 years were studied. The mean LF concentration in cervical fluid was significantly lower among patients with normal IVF rates than in those with values 50% or less. Using a LF cutoff value of 0.83 ng/µg of total proteins, the study revealed a significant association between the LF levels below 0.83 ng/µg of total proteins and IVF rates above 50%. LF levels in cervical mucus could potentially be used as a marker of fertilization outcome.

mRNA profiling of mock casework samples: Results of a FoRNAP collaborative exercise.

In recent years, forensic mRNA profiling has increasingly been used to identify the origin of human body fluids. By now, several laboratories have implemented mRNA profiling and also use it in criminal casework. In 2018 the FoRNAP (Forensic RNA Profiling) group was established among a number of these laboratories with the aim of sharing experiences, discussing optimization potential, identifying challenges and suggesting solutions with regards to mRNA profiling and casework. To compare mRNA profiling methods and results a collaborative exercise was organized within the FoRNAP group. Seven laboratories from four countries received 16 stains, comprising six pure body fluid / tissue stains and ten mock casework samples. The laboratories were asked to analyze the provided stains with their in-house method (PCR/CE or MPS) and markers of choice. Five laboratories used a DNA/RNA co-extraction strategy. Overall, up to 11 mRNA markers per body fluid were analyzed. We found that mRNA profiling using different extraction and analysis methods as well as different multiplexes can be applied to casework-like samples. In general, high input samples were typed with high accuracy by all laboratories, regardless of the method used. Irrespective of the analysis strategy, samples of low input or mixed stains were more challenging to analyze and interpret since, alike to DNA profiling, a higher number of markers dropped out and/or additional unexpected markers not consistent with the cell type in question were detected. It could be shown that a plethora of different but valid analysis and interpretation strategies exist and are successfully applied in the Forensic Genetics community. Nevertheless, efforts aiming at optimizing and harmonizing interpretation approaches in order to achieve a higher consistency between laboratories might be desirable in the future. The simultaneous extraction of DNA alongside RNA showed to be an effective approach to identify not only the body fluid present but also to identify the donor(s) of the stain. This allows investigators to gain valuable information about the origin of crime scene samples and the course of events in a crime case.

A new method to detect methylation profiles for forensic body fluid identification combining ARMS-PCR technique and random forest model.

A set of DNA methylation markers was detected and evaluated to identify body fluids using the amplification refractory mutation system-PCR (ARMS-PCR) and random forest algorithm. In this study, four multiplex DNA methylation reactions composed of 22 promising methylation markers were used to identify regular forensic body fluids, including venous blood, saliva, semen, menstrual blood, and vaginal fluid. The ARMS-specific primers were used to amplify the candidate markers, and then the methylation values of each CpG site were detected through capillary electrophoresis (CE). The DNA methylation patterns of 22 highly informative methylation markers were consistent with previously reported results to a certain extent. To our knowledge, our study is a new method to apply the ARMS-PCR technique and random forest model to detect DNA methylation patterns and identify the type of body fluids in forensic science, thus providing a new method for forensic body fluid identification. Moreover, we proved that this method is robust, applicable and effective for identifying body fluids using the random forest model. The accuracy to predict all body fluids reached up to 0.9966. We firmly believe that this method will have a great potential in the detection of methylation profiles at the molecular level.

Identification of five types of forensic body fluids based on stepwise discriminant analysis.

Peripheral blood, menstrual blood, semen, saliva and vaginal secretions are the five most common body fluids found at crime scenes, and the identification of these five body fluids is of great significance to the reconstruction of a crime scene and resolution of the case. However, accurate identification of these five body fluids is still a challenge. To address this problem, a mathematical model for differentiating five types of forensic body fluids based on the differential expression characteristics of multiple miRNAs in five body fluids (peripheral blood, menstrual blood, semen, saliva and vaginal secretions) was developed. A total of 350 forensic body fluids (70 of each type) were collected and tested, and relative expression of 10 miRNAs (miR-451a, miR-205-5p, miR-203-3p, miR-214-3p, miR-144-3p, miR-144-5p, miR-654-5p, miR-888-5p, miR-891a-5p, miR-124a-3p) in all samples was detected by SYBR Green real-time qPCR. Three hundred samples (60 samples of each body fluid) were used as the training set to screen meaningful identification markers by stepwise discriminant analysis, and a discriminant function was established. Fifty samples (10 samples of each body fluid) were used as a validation set to examine the accuracy of the model, and 25 samples (the types of samples were unknown to the experimenter) were used for a blind test. Except for miR-144-3p, the other miRNAs were selected to construct discriminant analysis models. The self-validation accuracy of the model was 99.7 %, cross-validation accuracy was 99.3 %, accuracy of the identification validation set was 100 %, and accuracy of the blind test result was 100 %. This study provides a reliable and accurate identification strategy for five common body fluids (peripheral blood, menstrual blood, semen, saliva, and vaginal secretions) in forensic medicine.

The addition of Lactobacillus spp. negatively affects Mycoplasma bovis viability in bovine cervical mucus.

BACKGROUND: Mycoplasma bovis is an important pathogen for the cattle industry worldwide causing significant economic losses. Several transmission routes, including those related to reproduction, have been described. Indeed, the pathogen can colonize the female reproductive tract after artificial insemination (AI) with contaminated semen. Lactobacillus spp.-based probiotics have been used for vaginal dysbiosis treatment in women and cows although their role in controlling cervico-vaginal infections due to M. bovis is unknown. The objective of the present work is to assess the viability of M. bovis (PG45, NCTC 10131) in experimentally contaminated cervical mucus after the addition of Lactobacillus spp. at different concentrations as a competing agent and pH acidifier. RESULTS: The addition of probiotic at a concentration higher than 108 colony forming units (CFU/mL had a detrimental effect (P < 0.05) on mycoplasma viability in cervical mucus. This coincided with a significant LAB growth and an important decrease in pH from 8.4 to 5.6 (P < 0.05). However, after the addition of less concentrated probiotic, M. bovis survival was not affected and there was no significant LAB growth despite the drop of pH from 8.4 to 6.73 (P < 0.05). CONCLUSION: The addition of concentrations higher than 108 CFU/mL of Lactobacillus spp. negatively affects M. bovis viability in bovine cervical mucus under in vitro conditions. Although the effect observed on the pathogen viability seems to be related to the pH decrease after LAB proliferation in cervical mucus, further studies are necessary to elucidate if other factors are implicated. Nevertheless, the administration of Lactobacillus spp.-based probiotics might be used in the future to control M. bovis proliferation in the cervico-vaginal tract of cows.

Cervical-Vaginal Mucin in Fertility Assessment: CA125 as a Predictor of the Fertile Phase of the Normal Menstrual Cycle.

: To evaluate the cervical-vaginal mucin, CA125, as a measure of fertility and possible method for natural family planning (NFP). Cervical-vaginal fluid (CVF) swab samples have been previously used to measure CA125, 'Qvaginal CA125 levels', as a function of time of cycle relative to Day 0, the first day of positive urine LH (luteinizing hormone). Data from 15 women, 20 cycles were used with an algorithm to establish the Fertile Start Day (FSD) for the cycles. The FSD was determined as either the second consecutive day of ≥20% Qvaginal CA125 rise or the first day of ≥400% rise. The interval, (FSD to Day +3), was used as the theoretical window of fertility, and conception rates assuming abstinence during this predicted period of fertility were computed using published day-specific probabilities of conception (PoC). The mean FSD was Day -4.8 ± 0.5 (SE), 95% CI (-5.9, -3.7). The estimated pregnancy failure rate (PFR) with abstinence during [FSD, +3] was 10.7% ± 2.0% (SE), 95% CI (6.9%, 14.8%); with exclusion of one cycle with very low levels of Qvaginal CA125, the estimated PFR was 9.8% ± 1.9%, 95% CI (6.3%, 13.8%). Furthermore, the day-specific Qvaginal CA125 values were normalized to the respective peak Qvaginal CA125 for each cycle, and a mean normalized day-specific Qvaginal CA125 plot was generated. The first derivative of the mean normalized day-specific Qvaginal CA125 plot showed a significant increase between Day -4.5 and Day -3.5, which correlated with the mean FSD. A Qvaginal CA125-based method holds promise as a means to identify the start of the fertile window and may prove useful in NFP, especially when combined with available home hormonal fertility awareness kits.

Development of a multiplex system for the identification of forensically relevant body fluids.

Currently, mRNA profiling is widely investigated for forensic body fluid identification, while it is still required to advance the approach for those casework samples of limited quantity or low quality. The inclusion of circular RNAs (circRNAs) can facilitate the detection of mRNA markers in forensic body fluid identification. In this study, a multiplex assay for forensic body fluid identification (F18plex assay) was developed by incorporating 14 tissue-specific mRNA markers with circRNAs expression, 2 mRNA markers with high abundance and 2 housekeeping markers for the discrimination of the most common forensic body fluids, including blood, menstrual blood, saliva, vaginal secretion, semen and urine. The markers employed in the F18plex assay show similar specificity to previous reports. Additionally, even if all linear transcripts were completely erased, the expected markers in target biofluids could still be identified, which should help the discrimination of those aged biological stains. Results from sensitivity testing and the detection of mixtures demonstrate good sensitivity of the multiplex assay. Generally, full biomarker profiles could be obtained with ≥1 µl of blood, saliva, or semen, and ≥1 ng of total RNAs from menstrual blood, vaginal secretion, or urine samples, respectively, using this multiplex assay under the established conditions. Collectively, the newly established multiplex assay can assist in determining the biological origin of forensic stains.

Identification of nasal mucosa markers for forensic mRNA body fluid determination.

Biological fluids are commonly encountered as a form of evidence within forensic science, and can often provide important information relating to events which may have occurred. Over the years, significant advancements have been made with DNA profiling techniques, allowing for links to be made between an individual and cellular material recovered from a crime scene. While this DNA analysis can aid in linking an individual to a crime, it can often be beneficial to also determine the body fluid source of the DNA obtained from the sample in question for case context. One increasing area within the forensic field is the use of mRNA profiling for the identification of body fluids. The analysis of gene expression patterns can give information on cell function, and ultimately the body fluid source of the DNA in a sample. Over time this has led to the development of mRNA reverse transcriptase PCR assays to detect body fluid specific RNA transcripts for casework. During the use of these techniques nasal mucosa has been observed to give rise to false positive results. We report here on the identification of promising markers using RNA sequencing for the detection of nasal mucosa, with the aim to incorporate these markers into existing assays to assist in the identification of nasal mucosa and to assist in the interpretation of possible false positive results.

Get it off, but keep it: Efficient cleaning of hair shafts with parallel DNA extraction of the surface stain.

The analysis of hair samples is a common task in forensic investigations. Material transferred to the surface of a hair during a crime challenges the analysis as it has to be removed efficiently. However, the removal of the stain can also lead to a loss of information on stain contributors. DNA analysis of the stain itself might thus be helpful for the forensic investigation. The aim of this study was the examination of different methods to remove common biological surface stains completely from human hair shafts without hampering the parallel DNA extraction of the cleaned hair shaft and the isolated surface stain (blood, saliva, vaginal secretion, semen, and skin flocks). Four different methods of cleaning (water, lysis buffer, swabbing, NaClO) were compared to their cleaning efficiency as well as their success of mtDNA analysis of three hair donors and the original five stains on the hair. In order to test the suitability of this procedure for future analysis methods, a selection of samples were also sequenced with MPS. Additionally, nuclear DNA analysis of the stain DNA was performed using a screening STR assay to test the potential success for detection of a STR profile. The most efficient removal of the stain was achieved using NaClO, however compromising further analysis of the stain DNA. The best results for cleaning and parallel stain analysis were obtained using a swab moistened with 0.5 % SDS for surface cleaning. Especially water failed to remove stains efficiently, leading to a high amount of mixed mtDNA in the DNA extracts. MPS showed an increased sensitivity for detection of minute mixtures.

Sodium alginate potentiates antioxidants, cryoprotection and antibacterial activities of egg yolk extender during semen cryopreservation in buffalo.

The study was conducted to determine effects of sodium alginate on sperm during cryopreservation. Each ejaculate (n = 20) of five buffalo bulls (3-5 years) were divided into six equal fractions and diluted using egg yolk based extender supplemented with different concentrations of sodium alginate and cryopreserved. Frozen-thawed semen samples were evaluated using the CASA, hypo-osmotic swelling test, cervical mucus penetration capacity test, and chlortetracycline fluorescence assay (CTC). Phosphorylation of tyrosine containing proteins and malondialdehyde concentration of sperm membrane were evaluated using immunoblotting and thiobarbituric acid reactive substance assay respectively. The semen extender's anioxidative capacities were estimated by conducting 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays, metal chelating capacity by assessing ferrozine and antibacterial capacity using agar plate methods. Supplementation of sodium alginate in extender improved sperm longevity, plasma membrane integrity as well as capacity to transit through the cervical mucus. Supplementation of extender with sodium alginate minimises the phase transition of sperm membranes and phosphorylation of tyrosine containing proteins during cryopreservation. Malondialdehyde concentration of sperm was less in sodium alginate-treated sperm as compared with control samples. The results indicated that sodium alginate increased antioxidant capacity of semen extender. Supplementation with sodium alginate also improved the metal chelating capacity and antibacterial properties of the extender. In conclusion, supplementation of extender with sodium alginate enhances free radical scavenging, metal reduction and chelating capacities to protect sperm during cryopreservation.

Immunohistochemical staining of skin-expressed proteins to identify exfoliated epidermal cells for forensic purposes.

The determination of cell type in biological casework samples would be helpful to identify the type of body fluids and interpret the DNA source in forensic laboratories. Exfoliated epidermal cells are considered to be a reasonable source of touch DNA; therefore, we developed and assessed an immunohistochemistry (IHC) procedure for identifying exfoliated epidermal cells as a screening test of touch DNA samples. Among five candidate protein markers investigated in this study, keratin 10 and kallikrein-related peptidase 5 were strongly expressed in the stratum corneum layer of the skin; however, their specificity was insufficient to identify epidermal cells. In contrast, IHC for corneodesmosin (CDSN), desmocollin 1 (DSC1), and filaggrin (FLG) was considered to be applicable because of their detectability and specificity on skin swab samples. Actually, CDSN and DSC1 could be good markers for exfoliated epidermal cells on touched contact traces that were contaminated with many unidentified impurities. Besides, positivity for FLG on mock casework samples appeared to be lower than for the other markers, which might be caused by its instability. Finally, the relationship between positivity for IHC and DNA yield was analyzed using skin swab samples. Although it was difficult to determine these correlations quantitatively because of the heterogeneous distribution of cells and the presence of cell-free DNA, the DNA-quantifiable samples analyzed in this study contained at least some of IHC-positive epidermal cells. In conclusion, IHC detection of skin-enriched proteins, especially CDSN and DSC1, could be useful for screening samples that have been handled or touched by someone before DNA analysis.

Expression profile analysis of piwi-interacting RNA in forensically relevant biological fluids.

During the last decade, RNA profiling has emerged as one of the fastest developed methods for discriminating forensically relevant biological samples. As a category of small non-coding RNA, piwi-interacting RNA (piRNA) has recently been proposed to be differentially expressed in different types of body fluids, which indicates that its potential in forensic science is worth exploring. In this study, small RNA from 6 types of biological samples (venous blood, menstrual blood, saliva, semen, vaginal secretions and skin) was prepared and sequenced in order to characterize the expression pattern of piRNA using Ion S5 XL platform. Multiple bioinformatic methods were applied to make interpretation of the massively parallel sequencing data and identify representative biomarkers. A total of 376 piRNAs were initially identified after normalization and filtering. Hierarchical clustering and partial least squares-discriminant analysis (PLS-DA) revealed that their expression profiles exhibited an acceptable discriminating ability for most biological samples. Besides, a panel consists of 37 piRNA candidates was subsequently established for further analysis. The results suggested that with the optimal number of PLS components, the marker-reduced panel was sufficient to construct a PLS-DA model with the same performance as that can be achieved by the entire 376 piRNAs (classification error rate = 0.04). In addition, 5 targeted candidates were further selected for validation. TaqMan RT-qPCR assay results verified the potential of 3 piRNAs (piR-hsa-27622, piR-hsa-1207 and piR-hsa-27493) in distinguishing venous blood and menstrual blood, as well as 2 piRNA (piR-hsa-27493 and piR-hsa-26591) for the discrimination of saliva and vaginal secretions, which emphasized the feasibility of our biomarker selection approach. In brief, our study expanded the amount of potential piRNA biomarkers and demonstrated that the expression features of piRNA could provide valuable information for discriminating forensically relevant biological samples.

Transcription and microbial profiling of body fluids using a massively parallel sequencing approach.

Analysis of biological evidence typically begins with a preliminary screening for the presence of biological fluids, traditionally with enzymatic or immunologic tests and of late by RNA profiling. The goal of this study was to create a whole transcriptome protocol, to view potential degradation effects in forensically relevant body fluids. Total RNA from fresh and aged blood, menstrual blood, saliva, semen, skin and vaginal secretion was analyzed with a massively parallel sequencing method. Two RNA-Seq library protocols with and without rRNA depletion were tested and compared. The rRNA depletion step had a negative influence on the sequencing quality and on the downstream analyses. From the human and bacterial RNA sequences, source-specific signatures could be identified. Aged samples showed in general a higher level of RNA degradation and decreased bacterial diversity. In summary, we could show that transcriptional profiling and metagenome analysis are powerful tools to provide additional information about the trace evidence.

Menstrual cycle-dependent alterations in glycosylation: a roadmap for defining biomarkers of favorable and unfavorable mucus.

OBJECTIVE: To understand glycosylation of endocervical proteins at different times throughout the menstrual cycle in naturally cycling women and in women using hormonal or non-hormonal contraceptive methods, in order to characterize biochemical fingerprints of favorable and unfavorable cervical mucus. DESIGN: Lectin/antibody-probed protein blot analysis of endocervical mucus samples collected onto ophthalmologic sponges (wicks) from two groups: a longitudinal cohort of naturally cycling women at three time points in their menstrual cycles (discovery cohort), and a cross-sectional cohort of women on hormonal or non-hormonal contraceptive methods (validation cohort). SETTING: Participants were recruited from the San Francisco Bay Area from 2010 to 2016. PATIENT(S): Women with regular cycles not using hormonal or intrauterine device (IUD) contraceptives were recruited for the longitudinal cohort (n = 8). Samples from women using levonorgestrel-containing combined oral contraceptives (n = 16), levonorgestrel containing IUDs (n = 14), copper IUDs (n = 17), depo-medroxyprogesterone acetate (DMPA) (n = 15), and controls (n = 13) were used for validation. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Detection of specific glycosylation patterns on lectin/antibody probed protein blots. RESULT(S): Two lectins (Lens culinaris agglutinin and Lycopersicon esculentum [tomato lectin]), and the antibody MECA-79 demonstrated consistent cycle-dependent changes in protein binding. The glycan-binding patterns of the levonorgestrel-containing contraceptives were generally similar to each other and to those from women in the luteal phase. The DMPA samples showed slightly different binding patterns. CONCLUSION(S): We identified molecular signatures of unfavorable mucus from women in the luteal phase and on hormonal contraceptives. Further characterization of these biomarkers may be useful in contraceptive development and in evaluation of infertility.

Predicting the origin of stains from whole miRNome massively parallel sequencing data.

In this study, we have screened the six most relevant forensic body fluids / tissues, namely blood, semen, saliva, vaginal secretion, menstrual blood and skin, for miRNAs using a whole miRNome massively parallel sequencing approach. We applied partial least squares (PLS) and linear discriminant analysis (LDA) to predict body fluids based on the expression of the miRNA markers. We estimated the prediction accuracy for models including different subsets of miRNA markers to identify the minimum number of markers needed for sufficient prediction performance. For one selected model consisting of 9 miRNA markers we calculated their importance for prediction of each of the six different body fluid categories.