Predicting the role of the human gut microbiome in type 1 diabetes using machine-learning methods.

Gut microbes is a crucial factor in the pathogenesis of type 1 diabetes (T1D). However, it is still unclear which gut microbiota are the key factors affecting T1D and their influence on the development and progression of the disease. To fill these knowledge gaps, we constructed a model to find biomarker from gut microbiota in patients with T1D. We first identified microbial markers using Linear discriminant analysis Effect Size (LEfSe) and random forest (RF) methods. Furthermore, by constructing co-occurrence networks for gut microbes in T1D, we aimed to reveal all gut microbial interactions as well as major beneficial and pathogenic bacteria in healthy populations and type 1 diabetic patients. Finally, PICRUST2 was used to predict Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways and KO gene levels of microbial markers to investigate the biological role. Our study revealed that 21 identified microbial genera are important biomarker for T1D. Their AUC values are 0.962 and 0.745 on discovery set and validation set. Functional analysis showed that 10 microbial genera were significantly positively associated with D-arginine and D-ornithine metabolism, spliceosome in transcription, steroid hormone biosynthesis and glycosaminoglycan degradation. These genera were significantly negatively correlated with steroid biosynthesis, cyanoamino acid metabolism and drug metabolism. The other 11 genera displayed an inverse correlation. In summary, our research identified a comprehensive set of T1D gut biomarkers with universal applicability and have revealed the biological consequences of alterations in gut microbiota and their interplay. These findings offer significant prospects for individualized management and treatment of T1D.

MicroRNA-575 targets Derlin 1 to regulate proliferation, migration and invasion of human thyroid cancer cells.

Introduction: This study was undertaken to examine the expression of miR-575 in thyroid cancer tissues and to explore its therapeutic potential. Material and methods: Expression analysis was carried out by qRT-PCR. The MTT assay was used for cell viability. DAPI and annexin V/PI assays were used to detect apoptosis. Wound healing and Transwell assays were used for cell migration and invasion respectively. Western blot analysis was used to determine the expression of proteins. Results: The results showed significant downregulation of miR-575 in thyroid cancer tissues and cell lines. The role of miR-575 was deciphered by overexpression of miR-575 in MDA-T32 and MDA-T68 thyroid cancer cells. The results showed that overexpression of miR-575 caused significant inhibition of the proliferation of the MDA-T32 and MDA-T68 cells via induction of apoptotic cell death. The expression of Bax was also enhanced while that of Bax was decreased upon miR-575 overexpression in MDA-T32 and MDA-T68 cells. Additionally, miR-575 overexpression inhibited the migration and invasion of the MDA-T32 and MDA-T68 thyroid cancer cells. Bioinformatic approaches and the dual luciferase assay indicated Derlin 1 (DERL1) to be the potential target of miR-575 in thyroid cancer. DERL1 was significantly upregulated in thyroid cancer tissues and cell lines and overexpression of miR-575 caused suppression of DERL1 in MDA-T68 cells. Silencing of DERL1 inhibited the proliferation of the MDA-T68 cells while overexpression of DERL1 could abolish the effects of miR-575 overexpression on the proliferation of MDA-T68 thyroid cancer cells. Conclusions: miR-575 may be used as a therapeutic target for thyroid cancer treatment.

Unifying colors by primes.

RGB and CYMK are two major coloring schemes currently available for light colors and pigment colors, respectively. Both systems use letter-based color codes that require a large range of values to represent different colors. The problem is that these two systems are hard to use for manipulating any operations involving combinations of colors, and they lack the capacity for inter-changeability or unification. Based on prime number theory and Goldbach's conjecture, this study presents a universal color system (C235) using a number-based structure to encode, compute and unify all colors on a color wheel. The proposed C235 system offers a unified representation for the efficient encoding and effective manipulation of color. It can be applied to designing a high-rate LCD system and colorizing objects with multiple attributes and DNA codons, opening the door to manipulating colors and lights for even broader applications.

Corrigendum: Characteristics of the Fractional Amplitude of Low-Frequency Fluctuation in Ocular Hypertension Patients: A Resting-State fMRI Study.

[This corrects the article DOI: 10.3389/fmed.2021.687420.].

Study of normal-tension glaucoma based on OCTA and VBM-DARTEL analysis.

The aim of the present study was to investigate the detection value of optical coherence tomography angiography (OCTA) and voxel-based morphometry with diffeomorphic anatomical registration through exponentiated lie algebra (VBM-DARTEL) in normal-tension glaucoma (NTG), as well as the correlation between the two functional indicators. A total of 30 patients (15 males, 15 females) with NTG and 30 (15 males, 15 females) age-, sex- and education-matched healthy controls underwent OCTA and 3.0 T MRI scanning. The OCTA technique was used to scan the optic disc area of all subjects and measure the density of blood vessels around the optic disc; 3.0 T MRI scanning was used to obtain MRI images of the brain structure and the VBM-DARTEL method was applied for image processing using Matlab7.11R2010b (MathWorks). Imaging data were compared between the groups using two-samples t-tests to identify differences in the density of blood vessels around the optic disc and the change in brain parenchyma. Correlation analysis was used to explore associations between the density of blood vessels around the optic disc and the change in brain parenchyma in NTG. The results indicated that the vascular density around the optic disc in the NTG group was significantly decreased compared with that in the control group; the vascular density was decreased with disease progression. The difference between the two groups was statistically significant (P<0.05). The VBM-DARTEL analysis indicated that the volume of the left middle frontal gyrus, right superior frontal gyrus, right precuneus, right angular gyrus and right middle occipital gyrus was decreased, whereas the volume of the right anterior central gyrus was increased. The area under the receiver operating characteristic curve for the local volume difference in brain parenchyma to predict the diagnosis of NTG was >0.7. The area of brain parenchyma reduction was positively correlated with the density of blood vessels around the optic disc (P<0.05), whereas the right anterior central gyrus was negatively correlated with vascular density. In conclusion, OCTA and VBM-DARTEL technology may facilitate non-invasive monitoring of changes in NTG structure and function, and provide non-invasive diagnostic imaging support in the early stage of the disease. These advantages are of great importance in the diagnosis and follow-up of NTG.

Multiresidue screening of pesticides in Panax Ginseng C. A. Meyer by ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

In this study, an efficient screening method based on a modified quick, easy, cheap, effective, rugged, and safe extraction method combined with ultra-high-performance liquid chromatography coupled to tandem quadrupole time-of-flight mass spectrometry was established for the determination of 90 pesticides residues in Panax Ginseng. The accuracy of the method was then verified by analyzing the false positive rate and the screening detection limit in Ginseng. The results revealed that the screening detection limit of 33 of 90 pesticide residues were 0.01 mg·kg-1 , 22 species were 0.05 mg·kg-1 , 11 species were 0.10 mg·kg-1 , 8 species were 0.20 mg·kg-1 , and another 16 species were greater than 0.20 mg·kg-1 . A total of 73 pesticides were ultimately suitable to be practically applied for rapid analysis of pesticide residues in Ginseng. Finally, the established method was used to analyze the pesticide residues in 35 Ginseng samples available on the market. And the residual of dimethomorph, azoxystrobin, tebuconazole, and pyraclostrobin was relatively severe in Ginseng samples. This work expanded the range of pesticides detected and provided a rapid, effective method for pesticides screening in Ginseng.

Characteristics of the Fractional Amplitude of Low-Frequency Fluctuation in Ocular Hypertension Patients: A Resting-State fMRI Study.

Background: The fractional amplitude of low-frequency fluctuation (fALFF) method has been underutilized in research on the pathogenesis and clinical manifestations of ocular hypertension (OH). Purpose: This study uses resting state functional magnetic resonance imaging (rs-fMRI) and fALFF to investigate the nature of spontaneous brain activity in OH patients and the relationship, if any, between changes in activity and clinical features. Materials and Methods: A total of 18 subjects (9 females and 9 males) with ocular hypertension (OH) and 18 healthy controls (HCs) matched for gender, age, and educational level were recruited to this study. All participants underwent an rs-fMRI scan, and spontaneous brain activity was assessed using the fALFF method. Receiver operating characteristic curves were plotted to investigate differences between OH and HC groups. Results: The fALFF values of OH patients were significantly higher in the left precuneus lobe (LP), compared with the same region in controls (P < 0.05). Conversely, values in the left anterior cingulate lobe (LAC), were significantly lower (P < 0.05) in OH than in controls. However, no significant association was found between the mean fALFF values and clinical characteristics in either brain area. Conclusion: High spontaneous activity in two brain areas may reflect neuropathological mechanisms underpinning visual impairment in OH patients.

Use of rsfMRI-fALFF for the detection of changes in brain activity in patients with normal-tension glaucoma.

BACKGROUND: We know little about the changes of brain activity in patients with normal-tension glaucoma (NTG). PURPOSE: To investigate the altered spontaneous brain activity in patients with NTG through the resting state functional magnetic resonance imaging-fractional amplitude of low-frequency fluctuation (rsfMRI-fALFF) technique, and to explore the relationship with optical coherence tomography (OCT) and field of vision. MATERIAL AND METHODS: Twenty patients with NTG and 20 healthy controls (HCs) (matched for sex, age, and level of education) were enrolled. Spontaneous cerebral activity variations were investigated using the rsfMRI-fALFF technique in all individuals. The average fALFF values of patients with NTG and HCs were compared. RESULTS: Compared with HCs, patients with NTG had significantly lower fALFF values in the right angular gyrus and precuneus; however, higher fALFF values in the brain regions were not observed. The values showed statistically significant negative correlation with those of the retinal nerve fiber layer (right angular gyrus: r = -0.607, P = 0.010; right precuneus: r = -0.504, P = 0.020). There was no significant correlation between the fALFF value and cup-disc ratio (right angular gyrus: r = 0.158, P = 0.494; right precuneus: r = -0.087, P = 0.706), mean deviation (right angular gyrus: r = 0.096, P = 0.468; right precuneus: r = 0.026, P = 0.845), and pattern SD value (right angular gyrus: r = 0.064, P = 0.626; right precuneus: r = -0.145, P = 0.268). CONCLUSION: Abnormal spontaneous activities were detected in numerous brain regions of patients with NTG, which may provide useful information for understanding the dysfunction in NTG. These activity changes in brain regions may be used as effective clinical indicators for NTG.

Long non-coding RNA PCAT29 regulates the growth, migration and invasion of human triple-negative breast cancer cells.

PURPOSE: A number of studies have provided concrete evidence about the role of Long noncoding RNAs (LncRNAs) in the development and progression of cancer. As such LncRNAs are believed to exhibit the potential to be used as therapeutic targets for the treatment of cancer. This study was undertaken to investigate the role and therapeutic implication of LncRNA PCAT29 in triple-negative breast cancer. METHODS: The breast cancer cell lines MDA-MB-231, MDA-MB-436, BT20, HCC70 and HCC38 and non-cancer cell line MB157 were used in this study. Gene expression analysis was performed by qRT-PCR. Cell proliferation was monitored by MTT and colony formation assays. Apoptosis was detected by annexin V/propidium iodide (PI) assay. Cell migration and Invasion was detected by wound heal and transwell assays. RESULTS: The expression of LncRNA PCAT29 was significantly suppressed in the breast cancer tissues and the triple-negative breast cancer cell lines. PCAT29 overexpression caused inhibition of the proliferation rate and colony formation of the MDA-MB-231 cells. The proliferation of MD-MB-231 cells was inhibited by apoptotic cell death which was accompanied by elevation of Bax and depletion of Bcl-2 expression. The wound healing assay showed that PCAT29 caused remarkable inhibition of the MDA-MB-231 cell migration. The transwell assay showed that PCAT29 overexpression resulted in 65% inhibition of the MDA-MB-231 cell invasion. CONCLUSION: PCAT29 regulates the proliferation, migration and invasion of breast cancer cells and may point to a novel therapeutic target in triple-negative breast cancer.

Dietary Phytoncide Supplementation Improved Growth Performance and Meat Quality of Finishing Pigs.

We conducted this 10-wk experiment to evaluate the effects of dietary phytoncide, Korean pine extract as phytogenic feed additive (PFA), on growth performance, blood characteristics, and meat quality in finishing pigs. A total of 160 pigs ([Landrace×Yorkshire]×Duroc, body weight (BW) = 58.2±1.0 kg) were randomly allocated into 1 of 4 treatments according to their BW and sex, 10 replicate pens per treatment with 4 pigs per pen were used (2 barrows and 2 gilts). Dietary treatments were: CON, control diet; PT2, CON+0.02% PFA; PT4, CON+0.04% PFA; PT6, CON+0.06% PFA. Overall, average daily gain (ADG) was higher in PT4 (p<0.05) than in PT6, average daily feed intake (ADFI) was lower in PT6 than in CON (p<0.05). Besides ADFI decreased linearly (p<0.05) with the increased level of phytoncide and gain:feed ratio in PT4 treatment was higher (p<0.05) than CON treatment. During 5 to 10 weeks and overall, quadratic (p<0.05) effect was observed in ADG among the treatments. At the end of this experiment, pigs fed with PT4 diet had a greater (p<0.05) red blood cell concentration compared to the pigs fed CON diet. Water holding capacity increased linearly (p<0.05) with the increased level of phytoncide supplementation. Moreover, firmness, redness, yellowness, and drip loss at day 3 decreased linearly (p<0.05) with the increase in the level of phytoncide supplementation. In conclusion, inclusion of phytoncide could enhance growth performance without any adverse effects on meat quality in finishing pigs.

A DIAMOND method of inducing classification rules for biological data.

Identifying the classification rules for patients, based on a given dataset, is an important role in medical tasks. For example, the rules for estimating the likelihood of survival for patients undergoing breast cancer surgery are critical in treatment planning. Many well-known classification methods (as decision tree methods and hyper-plane methods) assume that classes can be separated by a linear function. However, these methods suffer when the boundaries between the classes are non-linear. This study presents a novel method, called DIAMOND, to induce classification rules from datasets containing non-linear interactions between the input data and the classes to be predicted. Given a set of objects with some classes, DIAMOND separates the objects into different cubes, and assigns each cube to a class. Via the unions of these cubes, DIAMOND uses mixed-integer programs to induce classification rules with better rates of accuracy, support and compact. This study uses three practical datasets (Iris flower, HSV patients, and breast cancer patients) to illustrate the advantages of DIAMOND over some current methods.

Induction of multiple criteria optimal classification rules for biological and medical data.

To induce critical classification rules from observed data is a major task in biological and medical research. A classification rule is considered to be useful if it is optimal and simultaneously satisfies three criteria: is highly accurate, has a high rate of support, and is highly compact. However, current classification methods, such as rough set theory, neural networks, ID3, etc., may only induce feasible rules instead of optimal rules. In addition, the rules found by current methods may only satisfy one of the three criteria. This study proposes a multi-criteria model to induce optimal classification rules with better rates of accuracy, support and compactness. A linear multi-objective programming model for inducing classification rules is formulated. Two practical data sets, one of HSV patients results and another of European barn swallows, are tested. The results illustrate that the proposed method can induce better rules than current methods.

A linear programming approach for identifying a consensus sequence on DNA sequences.

MOTIVATION: Maximum-likelihood methods for solving the consensus sequence identification (CSI) problem on DNA sequences may only find a local optimum rather than the global optimum. Additionally, such methods do not allow logical constraints to be imposed on their models. This study develops a linear programming technique to solve CSI problems by finding an optimum consensus sequence. This method is computationally more efficient and is guaranteed to reach the global optimum. The developed method can also be extended to treat more complicated CSI problems with ambiguous conserved patterns. RESULTS: A CSI problem is first formulated as a non-linear mixed 0-1 optimization program, which is then converted into a linear mixed 0-1 program. The proposed method provides the following advantages over maximum-likelihood methods: (1) It is guaranteed to find the global optimum. (2) It can embed various logical constraints into the corresponding model. (3) It is applicable to problems with many long sequences. (4) It can find the second and the third best solutions. An extension of the proposed linear mixed 0-1 program is also designed to solve CSI problems with an unknown spacer length between conserved regions. Two examples of searching for CRP-binding sites and for FNR-binding sites in the Escherichia coli genome are used to illustrate and test the proposed method. AVAILABILITY: A software package, Global Site Seer for the Microsoft Windows operating system is available by http://www.iim.nctu.edu.tw/~cjfu/gss.htm

A diagnostic reasoning and optimal treatment model for bacterial infections with fuzzy information.

This study proposes an optimization model for optimal treatment of bacterial infections. Using an influence diagram as the knowledge and decision model, we can conduct two kinds of reasoning simultaneously: diagnostic reasoning and treatment planning. The input information of the reasoning system are conditional probability distributions of the network model, the costs of the candidate antibiotic treatments, the expected effects of the treatments, and extra constraints regarding belief propagation. Since the prevalence of the pathogens and infections are determined by many site-by-site factors, which are not compliant with conventional approaches for approximate reasoning, we introduce fuzzy information. The output results of the reasoning model are the likelihood of a bacterial infection, the most likely pathogen(s), the suggestion of optimal treatment, the gain of life expectancy for the patient related to the optimal treatment, the probability of coverage associated with the antibiotic treatment, and the cost-effect analysis of the treatment prescribed.