An Efficient Approach to Unsupervised Out-of-Distribution Detection with Variational Autoencoders

This paper is concerned with deep generative models (DGMs) for unsupervised out-of-distribution (OOD) detection. In particular, we focus on vanilla Variational Autoencoders (VAE) that use a standard normal prior distribution for the latent variables. These models have a smaller model size, enabling faster training and inference, making them well-suited for resource-limited applications compared to more complex DGMs. We propose a novel OOD score called Error Reduction (ER) specifically designed for vanilla VAE. ER incorporate the idea of reconstructing image inputs from their lossy counterparts and takes into account the Kolmogorov complexity of the images. Experimental results on diverse datasets demonstrate the superiority of our approach over baseline methods. Our code is available at: https://github.com/ZJLAB-AMMI/VAE4OOD.Comment: 5 page

Pharmacoeconomic analysis (CER) of Dulaglutide and Liraglutide in the treatment of patients with type 2 diabetes

AimTo evaluate the treatment effect Fand pharmacoeconomic value of Dugaglutide in women with type 2 diabetes.MethodsWomen (n=96) with type 2 diabetes recruited from June 2019 to December 2021 were randomized into two equal groups. The control group was treated with Liraglutide, and the observation group was treated with Dulaglutide, both for 24 weeks. The blood glucose levels, biochemical index, insulin resistance index (HOMA-IR), cost-effect ratio (CER), and drug safety were determined and compared between the two groups.ResultsBlood glucose levels, the biochemical index, and HOMA-IR were lower in both groups after the treatment (P < 0.05), and there was no statistical difference in the blood glucose levels, biochemical index and HOMA-IR between the two groups (P > 0.05). The CER levels did not differ statistically between the two groups (P > 0.05). Both the cost and the incidence of drug side effects during solution injection were lower in the observation group than in the control group after 24 weeks of treatment (P < 0.05).ConclusionBoth Dulaglutide and Liraglutide can reduce blood glucose levels, improve biochemical index, and HOMA-IR levels in women with type 2 diabetes. Dulaglutide is more cost-effective and safe.Clinical trial registrationhttps://www.chictr.org.cn/index.aspx, identifier ChiCTR1900026514

Association between fasting blood glucose and thyroid stimulating hormones and suicidal tendency and disease severity in patients with major depressive disorder

Thyroid dysfunction and diabetes are reported to be associated with depression. However, their role in the suicide risk in patients with major depressive disorder (MDD) is unclear. The purpose of this study was to investigate and compare thyroid dysfunction and diabetes between suicide attempters and non-suicide attempters in a large sample of first-episode drug-naïve (FEND) MDD patients. A descriptive study was conducted on 1279 Chinese outpatients with a diagnosis of first-episode MDD. Their sociodemographic information, blood levels of thyroid hormones, glucose, lipids and body mass index (BMI) parameters were collected. The positive subscales of the positive and negative syndrome scale (PANSS), Hamilton Anxiety Rating Scale (HAMA), Hamilton Depression Rating Scale (HAMD) were measured for psychotic, anxiety and depressive symptoms. Our results showed that compared with non-suicide attempters (P<0.01), suicide attempters had statistically higher scores on HAMD, HAMA and PANSS psychotic symptoms, as well as higher thyroid stimulating hormone (TSH) serum levels, glucose, anti-thyroglobulin (A-TG), anti-thyroid peroxidase (A-TPO), total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), systolic blood pressure and diastolic blood pressure (all with P<0.001). These results revealed that TSH, A-TG, A-TPO, TC, TG and LDL-C may be promising biomarkers of suicide risk in MDD, implying the importance of regular assessment of blood glucose level and thyroid function parameters for suicide prevention, along with possible treatment for impaired thyroid function and diabetes for the suicide intervention in MDD patients. Such patients with abnormal blood sugar and TSH must undergo thorough screening for suicidal ideation

Association between allergic conditions and risk of prostate cancer: A Prisma-Compliant Systematic Review and Meta-Analysis

Association between allergic conditions and prostate cancer risk has been investigated for many years. However, the results from available evidence for the association are inconsistent. We conducted a meta-analysis to evaluate the relationship between allergic conditions (asthma, atopy, hay fever and “any allergy”) and risk of prostate cancer. The PubMed and Embase databases were searched to screen observational studies meeting our meta-analysis criteria. Study selection and data extraction from included studies were independently performed by two authors. Twenty studies were considered eligible involving 5 case-control studies and 15 cohort studies. The summary relative risk (RR) for developing prostate cancer risk was 1.04 (95%CI: 0.92–1.17) for asthma, and 1.25 (95%CI: 0.74–2.10) for atopy, 1.04 (95%CI: 0.99–1.09) for hay fever, 0.96 (95%CI: 0.86–1.06) for any allergy. In the Subgroup and sensitivity analysis, similar results were produced. Little evidence of publication bias was observed. The present meta-analysis of observational studies indicates that no indication of an association between allergic conditions and risk of prostate cancer was found, and the meta-analysis does not support neither the original hypothesis of an overall cancer protective effect of allergic conditions, nor that of an opposite effect in the development of prostate cancer

Transposable elements cause the loss of self-incompatibility in citrus

Self-incompatibility (SI) is a widespread prezygotic mechanism for flowering plants to avoid inbreeding depression and promote genetic diversity. Citrus has an S-RNase-based SI system, which was frequently lost during evolution. We previously identified a single nucleotide mutation in Sm-RNase, which is responsible for the loss of SI in mandarin and its hybrids. However, little is known about other mechanisms responsible for conversion of SI to self-compatibility (SC) and we identify a completely different mechanism widely utilized by citrus. Here, we found a 786-bp miniature inverted-repeat transposable element (MITE) insertion in the promoter region of the FhiS2-RNase in Fortunella hindsii Swingle (a model plant for citrus gene function), which does not contain the Sm-RNase allele but are still SC. We demonstrate that this MITE plays a pivotal role in the loss of SI in citrus, providing evidence that this MITE insertion prevents expression of the S-RNase; moreover, transgenic experiments show that deletion of this 786-bp MITE insertion recovers the expression of FhiS2-RNase and restores SI. This study identifies the first evidence for a role for MITEs at the S-locus affecting the SI phenotype. A family-wide survey of the S-locus revealed that MITE insertions occur frequently adjacent to S-RNase alleles in different citrus genera, but only certain MITEs appear to be responsible for the loss of SI. Our study provides evidence that insertion of MITEs into a promoter region can alter a breeding strategy and suggests that this phenomenon may be broadly responsible for SC in species with the S-RNase system

Effect of Luteolin and Apigenin on the Expression of Oct-4, Sox2, and c-Myc in Dental Pulp Cells with In Vitro Culture

Introduction. Dental pulp cells (DPCs) are promising cell source for dental tissue regeneration. Recently, small molecules which optimize microenvironment or activate the reprogramming network provide a new way to enhance the pluripotency. Two promising bioflavonoids luteolin and apigenin were reported to enhance reprogramming efficiency in mouse embryonic fibroblast (MEF). However, their effect and underlying mechanism in cell fate determination of human DPCs remain unclear. Methods. To elucidate the effect of luteolin and apigenin on the cell fate determination of DPCs, we explored the cell proliferation, cell cycle, senescence, apoptosis, expression of pluripotency markers Oct-4, Sox2, and c-Myc, and multilineage differentiation capability of DPCs with luteolin or apigenin treatment. Results. We demonstrated that luteolin and apigenin inhibited cell proliferation, arrested DPCs in G2/M and S phase, and upregulated PI value and apoptosis. Moreover, luteolin and apigenin increased telomerase activity, maintained DPCs in a presenescent state, and activated the expression of Oct-4, Sox2, and c-Myc at a dose- and time-dependent pattern in DPCs even at late passages, albeit repressed lineage-specific differentiation. Conclusions. Addition of luteolin and apigenin in the culture medium might provide an effective way to maintain DPCs in an undifferentiated stage and inhibit lineage-specific differentiation

Evaluation of CBR of Graded Crushed Stone of Flexible Base Structural Layer Based on Discrete Element Model

In order to study the mechanical properties of graded crushed stone, the discrete element method is used to simulate the CBR test of graded crushed stone. Aiming at the composition structure of graded crushed stone material, the PFC3D simulation software is used to construct the test model, and the process of constructing the virtual specimen model of the graded crushed stone discrete element model is discussed in detail. A servo mechanism is used to control the speed of the wall in the software, so as to control the virtual confining pressure imposed on graded crushed stone by the wall and simulate the real CBR test environment. The micro-parameter calibration of the virtual test is carried out by comparing the indoor and virtual CBR specimens of a single particle size specimen and three groups of graded crushed stone specimens. The comparison result shows that the stress&ndash;strain characteristics of the graded crushed rock obtained by the discrete element simulation during the uniaxial penetration process have a high degree of similarity, which can verify the accuracy of the model establishment. With the increase in the penetration depth, the penetration force of the aggregates of various particle sizes gradually increases, and the penetration force and the penetration depth are basically linear, and when the particle size is greater than 9.5 mm, the increase in particle size has little effect on the CBR test results. Under the certain conditions, the contact stiffness of graded crushed stone particles with particle sizes of 4.75 mm, 9.5 mm, 13.2 mm, 16 mm, and 19 mm should be 0.88 &times; 107 (N/m), 0.98 &times; 107 (N/m), 1.10 &times; 107 (N/m), 1.25 &times; 107 (N/m), and 2.05 &times; 107 (N/m), respectively. The recommended value of the contact stiffness of the small spherical particles increases with the increase in the particle size. This model can provide a basis for studying the micromechanical state of graded crushed stone and physical mechanics tests

m6A modification patterns and tumor immune landscape in clear cell renal carcinoma

Background Recent studies have focused on the correlation between N6-methyladenosine (m6A) modification and specific tumor-infiltrating immune cells. However, the potential roles of m6A modification in the tumor immune landscape remain elusive.Methods We comprehensively evaluated the m6A modification patterns and tumor immune landscape of 513 clear cell renal cell carcinoma (ccRCC) patients, and correlated the m6A modification patterns with the immune landscape. The m6Ascore was established using principal component analysis. Multivariate Cox regression analysis was performed to evaluate the prognostic value of the m6Ascore.Results We identified three m6Aclusters—characterized by differences in Th17 signature, extent of intratumor heterogeneity, overall cell proliferation, aneuploidy, expression of immunomodulatory genes, overall somatic copy number alterations, and prognosis. The m6Ascore was established to quantify the m6A modification pattern of individual ccRCC patients. Further analyses revealed that the m6Ascore was an independent prognostic factor of ccRCC. Finally, we verified the prognostic value of the m6Ascore in the programmed cell death protein 1 (PD-1) blockade therapy of patients with advanced ccRCC.Conclusions This study demonstrated the correlation between m6A modification and the tumor immune landscape in ccRCC. The comprehensive evaluation of m6A modification patterns in individual ccRCC patients enhances our understanding of the tumor immune landscape and provides a new approach toward new and improved immunotherapeutic strategies for ccRCC patients

A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19)

Abstract This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: (1) Correlation between these two estimations; (2) Exploring the dynamic patterns using these two estimations between moderate and severe groups. The Spearman’s correlation coefficient between these two estimation methods was 0.920 (p < 0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19

scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, there lacks specific evaluation of correction efficacy for varying contamination levels. Here, we show that DecontX and CellBender under-correct highly contaminating genes, while SoupX and scAR over-correct lowly/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly contaminating genes while avoiding over-correction of other genes