Trends in forensic microbiology: From classical methods to deep learning

Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology

Balanced chromosomal rearrangements offer insights into coding and noncoding genomic features associated with developmental disorders

Balanced chromosomal rearrangements (BCRs), including inversions, translocations, and insertions, reorganize large sections of the genome and contribute substantial risk for developmental disorders (DDs). However, the rarity and lack of systematic screening for BCRs in the population has precluded unbiased analyses of the genomic features and mechanisms associated with risk for DDs versus normal developmental outcomes. Here, we sequenced and analyzed 1,420 BCR breakpoints across 710 individuals, including 406 DD cases and the first large-scale collection of 304 control BCR carriers. We found that BCRs were not more likely to disrupt genes in DD cases than controls, but were seven-fold more likely to disrupt genes associated with dominant DDs (21.3% of cases vs. 3.4% of controls; P = 1.60×10$^{−12}$). Moreover, BCRs that did not disrupt a known DD gene were significantly enriched for breakpoints that altered topologically associated domains (TADs) containing dominant DD genes in cases compared to controls (odds ratio [OR] = 1.43, P = 0.036). We discovered six TADs enriched for noncoding BCRs (false discovery rate < 0.1) that contained known DD genes (MEF2C, FOXG1, SOX9, BCL11A, BCL11B, and SATB2) and represent candidate pathogenic long-range positional effect (LRPE) loci. These six TADs were collectively disrupted in 7.4% of the DD cohort. Phased Hi-C analyses of five cases with noncoding BCR breakpoints localized to one of these putative LRPEs, the 5q14.3 TAD encompassing MEF2C, confirmed extensive disruption to local 3D chromatin structures and reduced frequency of contact between the MEF2C promoter and annotated enhancers. We further identified six genomic features enriched in TADs preferentially disrupted by noncoding BCRs in DD cases versus controls and used these features to build a model to predict TADs at risk for LRPEs across the genome. These results emphasize the potential impact of noncoding structural variants to cause LRPEs in unsolved DD cases, as well as the complex interaction of features associated with predicting three-dimensional chromatin structures intolerant to disruption

Analysis of influencing factors of herpes zoster-related neuropathic pain on the head and face

Objective To explore the influencing factors of herpes zoster neuralgia in order to provide reference for the diagnosis and the treatment of this disease. Methods We retrospectively analyzed 89 cases of craniofacial herpes zoster and 168 cases of non-craniofacial herpes zoster hospitalized in the First Affiliated Hospital of Wannan Medical College from January, 2019 to December, 2019. The demographic and clinical characteristics were compared between these two groups. Pearson analysis was used to determine the correlation between NLR and pain score and severity score of the skin lesions. Logistic regression was used to analyze the risk factors for herpes zoster neuralgia. Results There were no significant differences in age, gender, pain score and severity of skin lesions between the two groups when admitted to hospital. Patients with craniofacial herpes zoster had a higher rate of pustules, blood blister and necrosis than that with non-craniofacial herpes zoster (25.84% vs. 15.48%, χ2=4.05, P=0.044). Moreover, the NLR were higher in patients with craniofacial herpes zoster than that with non-craniofacial herpes zoster (4.11±1.62 vs. 2.35±1.51, t=6.27, P<0.05) at admission to hospital. NLR and severity of skin lesions were independent influencing factors for the severity of pain in acute phase of craniofacial herpes zoster (OR=1.758, 95%CI: 1.215~2.543 for NLR; OR=1.418, 95% CI: 1.034~1.944 for severity of skin lesions). The severity of skin lesions was an independent influencing factor for postherpetic neuralgia of craniofacial herpes zoster (OR=1.846, 95% CI: 1.167~2.922). Conclusions Patients with craniofacial herpes zoster have more severe inflammation. NLR and the severity of skin lesions are correlated with acute herpetic neuralgia. The severity of skin lesions is correlated with postherpetic neuralgia

Clinical manifestations and endoscopic presentations of gastric lymphoma: a multicenter seven year retrospective survey

Background and aim: To improve the diagnostic rate of gastric lymphoma by analyzing clinical and endoscopic features of patients with gastric lymphoma and suspected gastric lymphoma. Methods: Clinical and endoscopic records of 35 patients with gastric lymphoma (positive group) and 133 patients with suspected gastric lymphoma but subsequent non-malignant pathology (negative group) were analyzed retrospectively. Data from another 99 gastric lymphoma patients with malignant pathology but nonspecific endoscopy (endoscopy non-suspect group) were analyzed. Results: Abdominal pain was the predominant symptom reported in both the positive and negative lymphoma groups, representing 60.0 and 52.5%, respectively. No significant differences in age, sex and clinical manifestations in subjects from the two groups were found. In the positive group, 54.3% were ulcerative; 34.3%, infiltrative; 8.5%, polypoid; and 2.9%, granulonodular. In the negative group, 52.6% were infiltrative; 42.1%, ulcerative; 4.5%, granulonodular; and 0.75%, polypoid. The endoscopic results varied between the two groups (p < 0.05). In the non-suspect group, 66.7% were ulcerative; 17.2%, infiltrative; 14.1%, polypoid; and 2.0%, granulonodular. With regards to histology, diffuse large B cell lymphoma was the most common subtype. The sensitivity of endoscopy was 60% for detecting malignancy and 21% for gastric lymphoma. Conclusion: The present study suggests that gastric lymphoma and suspected gastric lymphoma have similar clinical features. Gastric lymphoma presented mainly as macroscopic ulcerative lesions, whereas suspected gastric lymphoma appeared mainly as infiltrative lesions. Although the diagnostic rate of gastric lymphoma was relatively low (21%), it can be identified by endoscopy (60%). To improve diagnosis, repetitive endoscopic biopsies should be performed and novel endoscopic techniques developed in the future

Data_Sheet_1_Postmortem submersion interval estimation of cadavers recovered from freshwater based on gut microbial community succession.docx

Microbial community succession during decomposition has been proven to be a useful tool for postmortem interval (PMI) estimation. Numerous studies have shown that the intestinal microbial community presented chronological changes after death and was stable in terrestrial corpses with different causes of death. However, the postmortem pattern of intestinal microbial community succession in cadavers retrieved from water remains unclear. For immersed corpses, the postmortem submersion interval (PMSI) is a useful indicator of PMI. To provide reliable estimates of PMSI in forensic investigations, we investigated the gut microbial community succession of corpses submersed in freshwater and explored its potential application in forensic investigation. In this study, the intestinal microbial community of mouse submersed in freshwater that died of drowning or CO2 asphyxia (i.e., postmortem submersion) were characterized by 16S rDNA amplification and high-throughput sequencing, followed by bioinformatic analyses. The results demonstrated that the chronological changes in intestinal bacterial communities were not different between the drowning and postmortem submersion groups. α-diversity decreased significantly within 14 days of decomposition in both groups, and the β-diversity bacterial community structure ordinated chronologically, inferring the functional pathway and phenotype. To estimate PMSI, a regression model was established by random forest (RF) algorithm based on the succession of postmortem microbiota. Furthermore, 15 genera, including Proteus, Enterococcus, and others, were selected as candidate biomarkers to set up a concise predicted model, which provided a prediction of PMSI [MAE (± SE) = 0.818 (± 0.165) d]. Overall, our present study provides evidence that intestinal microbial community succession would be a valuable marker to estimate the PMSI of corpses submerged in an aquatic habitat.</p

The neuroprotective mechanism of lithium after ischaemic stroke

Stroke causes degeneration and death of neurones leading to the loss of motor function and frequent occurrence of cognitive impairment and depression. Lithium (Li+), the archetypal mood stabiliser, is neuroprotective in animal models of stroke, albeit underlying mechanisms remain unknown. We discover that Li+ inhibits activation of nucleotide-binding oligomerisation domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasomes in the middle cerebral artery occlusion (MCAO) stroke model in mice. This action of Li+ is mediated by two signalling pathways of AKT/GSK3β/β-catenin and AKT/FoxO3a/β-catenin which converge in suppressing the production of reactive oxygen species (ROS). Using immunocytochemstry, MRI imaging, and cell sorting with subsequent mRNA and protein quantification, we demonstrate that Li+ decreases the infarct volume, improves motor function, and alleviates associated cognitive and depressive impairments. In conclusion, this study reveals molecular mechanisms of Li+ neuroprotection during brain ischaemia, thus providing the theoretical background to extend clinical applications of Li+ for treatment of ischemic stroke.</p

Ageing related thyroid deficiency increases brain-targeted transport of liver-derived ApoE4-laden exosomes leading to cognitive impairment

Alzheimer’s disease (AD) is the prevalent cause of dementia in the ageing world population. Apolipoprotein E4 (ApoE4) allele is the key genetic risk factor for AD, although the mechanisms linking ApoE4 with neurocognitive impairments and aberrant metabolism remains to be fully characterised. We discovered a significant increase in the ApoE4 content of serum exosomes in old healthy subjects and AD patients carrying ApoE4 allele as compared with healthy adults. Elevated exosomal ApoE4 demonstrated significant inverse correlation with serum level of thyroid hormones and cognitive function. We analysed effects of ApoE4-containing peripheral exosomes on neural cells and neurological outputs in aged or thyroidectomised young mice. Ageing-associated hypothyroidism as well as acute thyroidectomy augmented transport of liver-derived ApoE4 reach exosomes into the brain, where ApoE4 activated nucleotide-binding oligomerisation domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome by increasing cholesterol level in neural cells. This, in turn, affected cognition, locomotion and mood. Our study reveals pathological potential of exosomes-mediated relocation of ApoE4 from the periphery to the brain, this process can represent potential therapeutic target.</p

Additional file 1 of Acute ischemia induces spatially and transcriptionally distinct microglial subclusters

Additional file 1: Table S1. Quality control data for scRNA-seq and ST