Prediction of viral pneumonia based on machine learning models analyzing pulmonary inflammation index scores.

OBJECT: To obtain Pulmonary Inflammation Index scores from imaging chest CT and combine it with clinical correlates of viral pneumonia to predict the risk and severity of viral pneumonia using a computer learning model. METHODS: All patients with suspected viral pneumonia on CT examination admitted to The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University from December 2022 to March 2023 were retrospectively selected. The respiratory viruses were monitored by RT-PCR and categorized into patients with viral pneumonia and those with non-viral pneumonia. The extent of lung inflammation was quantified according to the Pulmonary Inflammation Index score (PII). Information on patient demographics, comorbidities, laboratory tests, pathogenetic testing, and radiological data were collected. Five machine learning models containing Random Forest(RF), Radial Basis Function Neural Network (RBFNN), Support Vector Machine (SVM), K Nearest Neighbour Algorithm (KNN), and Kernel Ridge Regression (KRR) were used to predict the risk of onset and severity of viral pneumonia based on the clinically relevant factors or PII. RESULTS: Among the five models, the SVM model performed best in ACC (76.75 %), SN (73.99 %), and F1 (72.42 %) and achieved a better area under the receiver operating characteristic curve (ROC) (0.8409) when predicting the risk of developing viral pneumonia. RF had the best overall classification accuracy in predicting the severity of viral pneumonia, especially in predicting pneumonia with a PII classification of grade I, the RF model achieved an accuracy of 98.89%. CONCLUSION: Machine learning models are valuable in assessing the risk of viral pneumonia. Meanwhile, machine learning models confirm the importance in predicting the severity of viral pneumonia through PII. The establishment of machine learning models for predicting the risk and severity of viral pneumonia promotes the further development of machine learning in the medical field.

Identification of key candidate genes and biological pathways in neuropathic pain.

BACKGROUND: Neuropathic pain is a common chronic pain, characterized by spontaneous pain and mechanical allodynia. The incidence of neuropathic pain is on the rise due to infections, higher rates of diabetes and stroke, and increased use of chemotherapy drugs in cancer patients. At present, due to its pathophysiological process and molecular mechanism remaining unclear, there is a lack of effective treatment and prevention methods in clinical practice. Now, we use bioinformatics technology to integrate and filter hub genes that may be related to the pathogenesis of neuropathic pain, and explore their possible molecular mechanism by functional annotation and pathway enrichment analysis. METHODS: The expression profiles of GSE24982, GSE2884, GSE2636 and GSE30691 were downloaded from the Gene Expression Omnibus（GEO）database, and these datasets include 93 neuropathic pain Rattus norvegicus and 59 shame controls. After the four datasets were all standardized by quantiles, the differentially expressed genes (DEGs) between NPP Rattus norvegicus and the shame controls were finally identified by the robust rank aggregation (RRA) analysis method. In order to reveal the possible underlying biological function of DEGs, the Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis of DEGs were performed. In addition, a Protein-protein Interaction (PPI) network was also established. At the end of our study, a high throughput sequencing dataset GSE117526 was used to corroborate our calculation results. RESULTS: Through RRA analysis of the above four datasets GSE24982, GSE2884, GSE2636, and GSE30691, we finally obtained 231 DEGs, including 183 up-regulated genes and 47 down-regulated genes. Arranging 231 DEGs in descending order according to |log2 fold change (FC)|, we found that the top 20 key genes include 14 up-regulated genes and 6 down-regulated genes. The most down-regulated hub gene abnormal expressed in NPP was Egf17 (P-value = 0.008), Camk2n2 (P-value = 0.002), and Lep (P-value = 0.02), and the most up-regulated hub gene abnormal expressed in NPP was Nefm (P-value = 1.08E-06), Prx (P-value = 2.68E-07), and Stip1 (P-value = 4.40E-07). In GO functional annotation analysis results, regulation of ion transmembrane transport (GO:0034765; P-value = 1.45E-09) was the most remarkable enriched for biological process, synaptic membrane (GO:0097060; P-value = 2.95E-08) was the most significantly enriched for cellular component, channel activity (GO:0015267; P-value = 2.44E-06) was the most prominent enriched for molecular function. In KEGG pathway enrichment analysis results, the top three notable enrichment pathways were Neuroactive ligand-receptor interaction (rno04080; P-value = 3.46E-08), Calcium signaling pathway (rno04020; P-value = 5.37E-05), and Osteoclast differentiation (rno04380; P-value = 0.000459927). Cav1 and Lep appeared in the top 20 genes in both RRA analysis and PPI analysis, while Nefm appeared in RRA analysis and datasets GSE117526 validation analysis, so we finally identified these three genes as hub genes. CONCLUSIONS: Our research identified the hub genes and signal pathways of neuropathic pain, enriched the pathophysiological mechanism of neuropathic pain to some extent, and provided a possible basis for the targeted therapy of neuropathic pain.

Microbial community associated with ectomycorrhizal Russula symbiosis and dominated nature areas in southern China.

Russula griseocarnosa is one of the uncultivable important mycorrhizal edible fungi. Currently, there is a limited insight into the dynamic composition of the microbial communities associated with Russula. Here, the microbiota in the root and mycorrhizosphere from Russula-Fagaceae nature areas of Fujian province were identified by Illumina MiSeq high-throughput sequencing. First, we compared three types of fungal communities associated with Russula-Fagaceae root mycelia-running stage (stage-1), Russula sporocarping stage-2 (stage-2) and Russula-free Fagaceae root (stage-3). Fungal diversity negatively correlated with Russula. Russula, Tomentella and Lactarius were core EcM in Fagaceae roots. A total of eight genera, including Boletus, are likely a positive indicator of Russula sporocarp production in Russula-Fagaceae roots, while Tomentella and Elaphomyces for Russula symbiosis. Secondly, analysis of fungal and bacterial communities within rhizosphere soils from the three stages revealed six genera, including Dacryobolus and Acidocella, as possible indicator species associated with sporocarping in Russula. Elaphomyces, Tomentella, Sorangium, Acidicaldus, Acidobacterium and Haliangium occurred more frequently in the Russula rhizosphere. Furthermore, operational taxonomic unit (OTU) network analysis showed a positive correlation between Russula,Tomentella, Elaphomyces and Sorangium. Overall, our results revealed a relationship between micro-community and Russula, which may provide a new strategy for improving Russula symbiosis and sporocarp production.

Opportunities and barriers for providing HIV testing through community health centers in mainland China: a nationwide cross-sectional survey.

BACKGROUND: Primary care may be an avenue to increase coverage of HIV testing but it is unclear what challenges primary healthcare professionals in low- and middle-income countries face. We describe the HIV testing practices in community health centres (CHCs) and explore the staff's attitude towards further development of HIV testing services at the primary care level in China. METHODS: We conducted a national, cross-sectional survey using a stratified random sample of CHCs in 20 cities in 2015. Questionnaires were completed by primary care doctors and nurses in CHCs, and included questions regarding their demographics, clinical experience and their views on the facilitators and barriers to offering HIV testing in their CHC. Multivariate logistic regression was conducted to examine the association between staff who would offer HIV testing and their sociodemographic characteristics. RESULTS: A total of 3580 staff from 158 CHCs participated. Despite the majority (81%) agreeing that HIV testing was an important part of healthcare, only 25% would provide HIV testing when requested by a patient. The majority (71%) were concerned about reimbursement, and half (47%) cited lack of training as a major barrier. Almost half (44%) believed that treating people belonging to high-risk populations would scare other patients away, and 6% openly expressed their dislike of people belonging to high-risk populations. Staff who would offer HIV testing were younger (adjusted odds ratio (aOR) 0.97 per year increase in age, 95% confidence interval (CI):0.97-0.98); trained as a doctor compared to a nurse (aOR 1.79, 95%CI:1.46-2.15); held a bachelor degree or above (aOR 1.34, 95%CI:1.11-1.62); and had previous HIV training (aOR 1.55, 95%CI:1.27-1.89). CONCLUSIONS: Improving HIV training of CHC staff, including addressing stigmatizing attitudes, and improving financial reimbursement may help increase HIV testing coverage in China.

Characterization of the Adult Head Transcriptome and Identification of Migration and Olfaction Genes in the Oriental Armyworm Mythimna separate.

The oriental armyworm Mythimna separate is an economically important insect with a wide distribution and strong migratory activity. However, knowledge about the molecular mechanisms regulating the physiological and behavioural responses of the oriental armyworm is scarce. In the present study, we took a transcriptomic approach to characterize the gene network in the adult head of M. separate. The sequencing and de novo assembly yielded 63,499 transcripts, which were further assembled into 46,459 unigenes with an N50 of 1,153 bp. In the head transcriptome data, unigenes involved in the 'signal transduction mechanism' are the most abundant. In total, 937 signal transduction unigenes were assigned to 22 signalling pathways. The circadian clock, melanin synthesis, and non-receptor protein of olfactory gene families were then identified, and phylogenetic analyses were performed with these M. separate genes, the model insect Bombyx mori and other insects. Furthermore, 1,372 simple sequence repeats of 2-6 bp in unit length were identified. The transcriptome data represent a comprehensive molecular resource for the adult head of M. separate, and these identified genes can be valid targets for further gene function research to address the molecular mechanisms regulating the migratory and olfaction genes of the oriental armyworm.

[The soft tissue change of Angle's Class II division 1 malocclusion patients with vertical growth pattern after tooth extraction orthodontic treatment].

OBJECTIVE: This study is to evaluate the soft tissue change of Angle's Class II division 1 malocclusion patients with vertical growth pattern after tooth extraction orthodontic treatment, and to provide experimental results to help to make orthodontic treatment plan and treatments. METHODS: 38 Angle's Class II division 1 malocclusion patients with vertical growth pattern and with tooth extraction orthodontic treatment were included in this study. The pre- and post-treatment cephalometric X-rays were made and 26 measurement items were measured. The change value of pre- and post-treatment, youngsters and adults were compared. RESULTS: TUL-EP, TLL-EP, upper and lower lip position, Stoms-Stomi, U1-Ptm were reduced after treatment. Upper lip sulcus and flange thickness, upper and lower lip length, upper and lower lip inclination angle, nasolabial angle, Z angle, mentolabial sulcus inclination angle were enlarged after treatment. The upper lip sulcus thickness, lower lip length and A'-Ptm of adolescent were enlarged, but adult were on the contrary. The change of upper lip length, mentolabial sulcus inclination angle and U1-Ptm between adolescent and adult was statistically different. CONCLUSION: The best treatment period of patients with Angle's Class II division 1 malocculsion with vertical growth pattern was in the rapid growth and development period of adolescent.

[Study of mandibular anterior alveolar bone thickness in subjects with different facial skeletal types].

OBJECTIVE: To study the association of vertical facial skeletal types and sagittal facial skeletal types with anterior alveolar bone thickness. METHODS: Among 168 cases with malocclusion in early permanent dentition stage, 93 patients were male and 75 patients were female. All patients (aged 10-14 years) were divided into 9 groups by different facial skeletal types, mandibular anterior alveolar bone thickness in patients' lateral cephalometric films were measured. ANOVA were performed to measurement results with the SPSS 13.0 statistical software. RESULTS: Though sagittal facial skeletal types were the same, there were significant differences between different vertical facial types groups. The order was low-angle group, average-angle group and high-angle group according to the size. A high-angle individual often had a thin anterior alveolar bone while a low-angle individual often had the opposite morphology character. There was no statistical significance between skeletal type I, II and III. But group of skeletal type III also had a thin alveolar bone thickness which had no significant difference with high-angle group. Low-angle group III had no significant difference with average-angle group I and II in alveolar bone thickness. CONCLUSION: Sagittal facial skeletal types have little influence on anterior alveolar morphology, but the vertical facial skeletal types have strong connection with anterior alveolar bone thickness.