Anti-NMDA Receptor Encephalitis, Human Papillomavirus, and microRNA.

BACKGROUND: Anti-N-methyl-d-aspartate (Anti-NMDA) receptor encephalitis is a rare autoimmune disease, which is caused by antibodies attacking NMDA receptors in the brain. Previous studies revealed that this disorder might be induced by vaccination. Vaccination is the most useful strategy to prevent human or animal infectious diseases. MATERIALS AND METHODS: Although vaccines can produce immunity against diseases, at low risk, they may trigger serious adverse events. Anti-NMDA receptor encephalitis has been studied to be related to the H1N1 (influenza A virus subtype H1N1), tetanus/diphtheria/ pertussis and polio vaccine, Japanese encephalitis, yellow fever, and coronavirus disease 2019 (COVID-19) vaccination. Several cases have been reported that anti-NMDA receptor encephalitis could also be triggered by the human papillomavirus (HPV) vaccine. However, there is a lack of studies to investigate the underlying mechanism. RESULT: In this paper, the association between anti-NMDA receptor encephalitis and HPV vaccination is discussed in terms of their microRNA (miRNA) biomarkers. Phylogenetic tree and distance similarity analyses are used to explore the relationship between their miRNA biomarkers. The results show a higher degree of similarity between miRNA biomarkers associated with HPV and anti-NMDA receptor encephalitis or related vaccines when compared to the overall miRNAs. It indicates that while the risk of HPV triggering anti-NMDA receptor encephalitis is low, a connection between anti-NMDA receptor encephalitis and HPV vaccination cannot be ruled out. CONCLUSION: This finding suggests that in cases where individuals receiving HPV vaccination experience psychiatric or neurological symptoms, it should be considered to diagnose anti-NMDA receptor encephalitis, given the exclusion of other possible complications.

Beneficial medicinal effects and material applications of rose.

Rose is a beautiful and fragrant plant with a variety of medicinal and substance uses. Various parts of rose such as fruits, flowers, leaves, and bark can be used in various product development, including cosmetics, food, pharmaceuticals, and engineering. The medical benefits of roses include the treatment of inflammation, diabetes, dysmenorrhea, depression, stress, seizures, and aging. Rose water is precious beauty water for skin care and has antibacterial effects on various microbiota. The surface of a rose petal exhibits a hierarchical structure comprising microscale papillae, with each papilla further featuring intricate nanofolds. With this structural feature, rose petals have high water contact angles together with antagonistic wetting properties. The hierarchical structures of rose petals were shown to have anti-reflection and light-harvesting abilities, which have the potential to be materials for various electronic products. Rose petals are an excellent biomimetic/bioinspired material that can be applied to the popular material graphene. This paper reviews the medical function and material application of roses. During the COVID-19 pandemic, medical materials or food shortages have become a global issue. Natural biomaterials could be a good alternative. Roses, with so many benefits, definitely deserve more exploration and promotion.

The Potential of Collagen Treatment for Comorbid Diseases.

Collagen, the most abundant protein in our bodies, plays a crucial role in maintaining the structural integrity of various tissues and organs. Beyond its involvement in skin elasticity and joint health, emerging research suggests that collagen may significantly impact the treatment of complex diseases, particularly those associated with tissue damage and inflammation. The versatile functions of collagen, including skin regeneration, improving joint health, and increasing bone strength, make it potentially useful in treating different diseases. To the best of my knowledge, the strategy of using collagen to treat comorbid diseases has not been widely studied. This paper aims to explore the potential of collagen in treating comorbid diseases, including rheumatoid arthritis, osteoarthritis, osteoporosis, psoriatic arthritis, sarcopenia, gastroesophageal reflux, periodontitis, skin aging, and diabetes mellitus. Collagen-based therapies have shown promise in managing comorbidities due to their versatile properties. The multifaceted nature of collagen positions it as a promising candidate for treating complex diseases and addressing comorbid conditions. Its roles in wound healing, musculoskeletal disorders, cardiovascular health, and gastrointestinal conditions highlight the diverse therapeutic applications of collagen in the context of comorbidity management.

microRNA pathological mechanisms between Parkinson's disease, Alzheimer's disease, glaucoma and macular degeneration.

Reactive oxygen species (ROS) play an essential role in regulating various functions of organisms such as gene transcription, signalling transduction and immune response. However, overproduction of ROS can lead to oxidative stress, which is related to various ageing diseases including eye and brain degenerative diseases. Ocular measurements have recently been suggested as potential sources of biomarkers for the early detection of brain neurodegenerative diseases. MicroRNAs (miRNAs) are useful biomarkers for various diseases including degenerative diseases. miRNAs play an important role in the oxidative stress mechanisms of ageing diseases. In this paper, the role of miRNAs related to oxidative stress mechanisms in four ageing diseases, Parkinson's disease (PD), Alzheimer's disease (AD), glaucoma and age-related macular degeneration was reviewed. The common miRNA biomarkers related to the four diseases were also discussed. The results show that these eye and brain ageing diseases share many common miRNA biomarkers. It indicates that the ocular condition may be a prognostic biomarker for PD or AD patients. When a patient's eye condition changes, this can be a warning of a change in PD or AD status.

Biomaterials in Medical Applications.

Natural biomaterials are materials extracted from living organisms or their by-products [...].

The Human Pre-miRNA Distance Distribution for Exploring Disease Association.

MicroRNAs (miRNAs), playing an important role in cell differentiation, development, gene regulation, and apoptosis, have attracted much attention in recent years. miRNAs were shown to be involved in the mechanisms of various diseases, and certainly, they can be employed as useful disease biomarkers. The phylogenetic tree analysis of miRNA biomarkers is a useful tool to investigate the association between various diseases as well as the association between viruses and disease. In addition to the phylogenetic tree analysis, a more advanced study is to use the miRNA distance distribution to evaluate the similarity of the miRNA biomarkers. The mature miRNA distance distribution based on mature miRNA sequences has been derived. The averages of the pairwise distances of miRNA biomarkers for several associated diseases were shown to be smaller than the overall mean of all miRNAs, which indicates the high similarity of miRNA biomarkers for associated diseases. In addition to the mature miRNA, the precursor miRNA (pre-miRNA) may be more useful to explore the similarity of miRNAs because the mature miRNA duplex is released from the pre-miRNA. Therefore, in this study, the distance distributions based on human pre-miRNA stem-loop sequences were derived. The 1917 human miRNA stem-loop sequences in the miRBase dataset were used to derive the pre-miRNA distance distribution, and this is the first study to provide the distance distribution based on the human pre-miRNAs. The similarity of miRNA biomarkers for several associated diseases or vaccines was examined using the derived distribution, and the results show that the similarity of pre-miRNA biomarkers may be a feasible way to help explore the disease association.

The distance distribution of human microRNAs in MirGeneDB database.

MicroRNAs (miRNAs) are small single-stranded non-coding RNAs around 22 nucleotide lengths found in organisms, playing an important role in cell differentiation, development, gene regulation, and apoptosis. The distance of disease miRNA biomarkers has been used to explore the association between various diseases as well as the association between virus and disease in the literature. To date, there have been no studies on deriving the distribution of the pairwise distance of human miRNAs. As the pairwise distance of miRNA biomarkers might be a useful tool in studying the disease association, in this paper, the distance distributions of human miRNAs were derived such that they could be used to measure the closeness between miRNAs. Two distance models were used to calculate the pairwise distances of 567 Homo sapiens miRNA genes accessed from the MirGeneDB database. These miRNA pairwise distances were fitted by the normal distribution, gamma distribution, empirical cumulative distribution, and the kernel density estimation method. This is the first study to provide the distance distribution of human miRNAs. The similarity of miRNA biomarkers for several diseases was examined using the derived distributions.

Exploring the Causal Effect of Constipation on Parkinson's Disease Through Mediation Analysis of Microbial Data.

Background and Aims: Parkinson's disease (PD) is a worldwide neurodegenerative disease with an increasing global burden, while constipation is an important risk factor for PD. The gastrointestinal tract had been proposed as the origin of PD in Braak's gut-brain axis hypothesis, and there is increasing evidence indicating that intestinal microbial alteration has a role in the pathogenesis of PD. In this study, we aim to investigate the role of intestinal microbial alteration in the mechanism of constipation-related PD. Methods: We adapted our data from Hill-Burns et al., in which 324 participants were enrolled in the study. The 16S rRNA gene sequence data were processed, aligned, and categorized using DADA2. Mediation analysis was used to test and quantify the extent by which the intestinal microbial alteration explains the causal effect of constipation on PD incidence. Results: We found 18 bacterial genera and 7 species significantly different between groups of constipated and non-constipated subjects. Among these bacteria, nine genera and four species had a significant mediation effect between constipation and PD. All of them were short-chain fatty acid (SCFA)-producing bacteria that were substantially related to PD. Results from the mediation analysis showed that up to 76.56% of the effect of constipation on PD was mediated through intestinal microbial alteration. Conclusion: Our findings support that gut dysbiosis plays a critical role in the pathogenesis of constipation-related PD, mostly through the decreasing of SCFA-producing bacteria, indicating that probiotics with SCFA-producing bacteria may be promising in the prevention and treatment of constipation-related PD. Limitations: 1) Several potential confounders that should be adjusted were not provided in the original dataset. 2) Our study was conducted based on the assumption of constipation being the etiology of PD; however, constipation and PD may mutually affect each other. 3) Further studies are necessary to explain the remaining 23.44% effect leading to PD by constipation.

A Pilot Study Exploring the Association of Entacapone, Gut Microbiota, and the Subsequent Side Effects in Patients With Parkinson's Disease.

Background and Aims: Entacapone, one of the most common drugs distributed among patients with Parkinson's disease, is a peripherally acting catechol-O-methyltransferase (COMT) inhibitor that is used in addition to levodopa to control symptoms. However, there have been negative effects reported against entacapone, namely, gastrointestinal (GI) problems and drowsiness. In this pilot study, we aim to examine the hypothesis that the discomfort induced by entacapone might be originated from the shift of microbial composition by adjusting the effect of levodopa. Methods: The population in this pilot study consisted of 13 PD patients treated with levodopa only and 11 with both levodopa and entacapone. The 16S rRNA gene sequence data were processed, aligned, and categorized using the DADA2. Alpha diversity indices for Observed, Chao1, Shannon, and Simpson metrics were calculated with Phyloseq 1.32.0. Dissimilarities were calculated using unweighted unique fraction metrics (Unifrac), weighted Unifrac, and Canberra distance. Functional differences were calculated by PICRUSt2 based on the KEGG database. Results: Results of 16S rRNA sequencing analysis showed that while entacapone did not influence the species richness, the composition of the microbial community shifted considerably. Relative abundances of bacteria related to constipation and other GI disorders also altered significantly. Functional enrichment analysis revealed changes in the metabolic activity of alanine, aspartate, and glutamate. These amino acids are related to common side effects of entacapone such as auditory hallucinations, fatigue, and nightmare. Conclusion: Our findings provide testable hypothesis on the cause of unpleasant side effects of entacapone, which in the long run could possibly be reduced through gut microbiota manipulation.

COVID-19, Anti-NMDA Receptor Encephalitis and MicroRNA.

The coronavirus disease 2019 (COVID-19) pandemic has had an enormous impact on the world, affecting people's lifestyle, economy, and livelihood. Recently, with the development of vaccines, the number of infected cases has decreased. Many case reports have revealed that COVID-19 may induce other serious comorbidities such as anti-N-methyl-d-aspartate (anti-NMDA) receptor encephalitis. Anti-NMDA receptor encephalitis is an acute autoimmune disease that occurs more commonly in women than in men. To explore the association between COVID-19 and anti-NMDA receptor encephalitis, the microRNA (miRNA) biomarkers of COVID-19, anti-NMDA receptor encephalitis, and other related diseases from the literature are reviewed; then on the basis of these miRNA biomarkers, the relationship between COVID-19 and anti-NMDA receptor encephalitis is discussed. miRNAs are small non-coding RNAs that play important roles in cell differentiation, development, cell-cycle regulation, and apoptosis. miRNAs have been used as biological biomarkers for many diseases. The results in this study reveal that the relationship between anti-NMDA receptor encephalitis and COVID-19 infection or COVID-19 vaccination cannot be excluded; however, the risk that COVID-19 triggers the anti-NMDA receptor encephalitis is not high.

Multiple imputation confidence intervals for the mean of the discrete distributions for incomplete data.

Confidence intervals for the mean of discrete exponential families are widely used in many applications. Since missing data are commonly encountered, the interval estimation for incomplete data is an important problem. The performances of the existing multiple imputation confidence intervals are unsatisfactory. We propose modified multiple imputation confidence intervals to improve the existing confidence intervals for the mean of the discrete exponential families with quadratic variance functions. A simulation study shows that the coverage probabilities of the modified confidence intervals are closer to the nominal level than the existing confidence intervals when the true mean is near the boundaries of the parameter space. These confidence intervals are also illustrated with real data examples.

microRNA Biomarkers in Clinical Study.

MicroRNAs (miRNAs), short non-coding RNAs, are involved in the initiation and progression of many human diseases that also play a key role in immune response and drug metabolism modulation [...].

A Review of the Effects of Collagen Treatment in Clinical Studies.

Collagen, an abundant extracellular matrix protein, has been found to have a lot of pharmaceuticals, medicine, food, and cosmetics applications. Increased knowledge of collagen sources, extraction techniques, structure, and properties in the last decades has helped develop more collagen-based products and tissue engineering biomaterials. Collagen products have been playing an important role in benefiting the health of the human body, especially for aging people. In this paper, the effects of collagen treatment in different clinical studies including skin regeneration, bone defects, sarcopenia, wound healing, dental therapy, gastroesophageal reflux, osteoarthritis, and rheumatoid arthritis have been reviewed. The collagen treatments were significant in these clinical studies. In addition, the associations between these diseases were discussed. The comorbidity of these diseases might be closely related to collagen deficiency, and collagen treatment might be a good choice when a patient has more than one of these diseases, including the coronavirus disease 2019 (COVID-19). It concludes that collagen-based medication is useful in treating comorbid diseases and preventing complications.

MicroRNAs, Multiple Sclerosis, and Depression.

Multiple sclerosis (MS) is a chronic disease of the central nervous system that affects the brain and spinal cord. There are several disease courses in MS including relapsing-remitting MS (RRMS), primary progressive MS (PPMS), and secondary progressive MS (SPMS). Up to 50% of MS patients experience depressive disorders. Major depression (MD) is a serious comorbidity of MS. Many dysfunctions including neuroinflammation, peripheral inflammation, gut dysbiosis, chronic oxidative and nitrosative stress, and neuroendocrine and mitochondrial abnormalities may contribute to the comorbidity between MS and MD. In addition to these actions, medical treatment and microRNA (miRNA) regulation may also be involved in the mechanisms of the comorbidity between MS and MD. In the study, I review many common miRNA biomarkers for both diseases. These common miRNA biomarkers may help further explore the association between MS and MD.

MicroRNAs, Parkinson's Disease, and Diabetes Mellitus.

Parkinson's disease (PD) is a neurodegenerative disorder that affects 1% of the population over the age of 60. Diabetes Mellitus (DM) is a metabolic disorder that affects approximately 25% of adults over the age of 60. Recent studies showed that DM increases the risk of developing PD. The link between DM and PD has been discussed in the literature in relation to different mechanisms including mitochondrial dysfunction, oxidative stress, and protein aggregation. In this paper, we review the common microRNA (miRNA) biomarkers of both diseases. miRNAs play an important role in cell differentiation, development, the regulation of the cell cycle, and apoptosis. They are also involved in the pathology of many diseases. miRNAs can mediate the insulin pathway and glucose absorption. miRNAs can also regulate PD-related genes. Therefore, exploring the common miRNA biomarkers of both PD and DM can shed a light on how these two diseases are correlated, and targeting miRNAs is a potential therapeutic opportunity for both diseases.

Exploring the Association of Autism Spectrum Disorders and Constipation through Analysis of the Gut Microbiome.

Over the past two decades, research into the role of the gut microbiome in regulating the central nervous system has rapidly increased. Several neurodevelopmental diseases have been linked to the unbalance of gut microbiota, including autism. Children on the autism spectrum often suffer from gastrointestinal symptoms, including constipation, which is four times more prevalent than it is in children without autism spectrum disorders (ASD). Although studies in animals have shown the crucial role of the microbiota in key aspects of neurodevelopment, there is currently no consensus on how the alteration of microbial composition affects the pathogenesis of ASD, let alone how it exerts an impact on the following comorbidities. In our study, we were able to control the effects of constipation on gut dysbiosis and distinguish neuropathological-related and gastrointestinal-related bacteria in ASD patients separately. By analyzing published data, eight additional bacteria significantly altered in autistic individuals were identified in our study. All of them had a decreased relative abundance in ASD patients, except Lactobacillaceae and Peptostreptococcaceae. Eighteen and eleven bacteria were significantly correlated with ASD symptoms and constipation, respectively. Among those, six bacteria were overlapped between the groups. We have found another six bacteria highly associated with constipation status in ASD patients only. By conducting Welch's t-test, we were able to demonstrate the critical roles of microbes in ASD core and gastrointestinal symptoms and raised the hypotheses of their confounding and mediating effects on the relationship between the two symptoms.

The Association between Migraine and Depression based on miRNA Biomarkers and Cohort Studies.

BACKGROUND: An association between migraine and Major Depression (MD) has been revealed in a number of clinical studies. Both diseases have affected a large global population. More understanding of the comorbidity mechanism of these two diseases can shed light on developing new therapies for their treatment. METHODS: To the best of our knowledge, there have not been any researches in the literature based on microRNA (miRNA) biomarkers to investigate the relationship between MD and migraine. In this study, we have discussed the association between these two diseases based on their miRNA biomarkers. In addition to miRNA biomarkers, we have also demonstrated epidemiological evidence for their association based on Taiwan Biobank (TWB) data. RESULTS: Among the 12 migraine miRNA biomarkers, 11 are related to MD. Only miR-181a has no direct evidence to be involved in the mechanism of MD. In addition to the biological biomarker evidence, the statistical analysis using the large-scale epidemiologic data collected from TWB provides strong evidence on the relationship between MD and migraine. CONCLUSION: The evidence based on both molecular and epidemiological data reveals the significant association between MD and migraine. This result can help investigate the correlated underlying mechanism of these two diseases.

MicroRNA, Diabetes Mellitus and Colorectal Cancer.

Diabetes mellitus (DM) is an endocrinological disorder that is due to either the pancreas not producing enough insulin, or the body does not respond appropriately to insulin. There are many complications of DM such as retinopathy, nephropathy, and peripheral neuropathy. In addition to these complications, DM was reported to be associated with different cancers. In this review, we discuss the association between DM and colorectal cancer (CRC). CRC is the third most commonly diagnosed cancer worldwide that mostly affects older people, however, its incidence and mortality are rising among young people. We discuss the relationship between DM and CRC based on their common microRNA (miRNA) biomarkers. miRNAs are non-coding RNAs playing important functions in cell differentiation, development, regulation of cell cycle, and apoptosis. miRNAs can inhibit cell proliferation and induce apoptosis in CRC cells. miRNAs also can improve glucose tolerance and insulin sensitivity. Therefore, investigating the common miRNA biomarkers of both DM and CRC can shed a light on how these two diseases are correlated and more understanding of the link between these two diseases can help the prevention of both DM and CRC.

Exploring Diversity of COVID­19 Based on Substitution Distance.

BACKGROUND: The number of COVID-19 infections worldwide has reached 10 million. COVID­19 caused by SARS-CoV-2 is more contagious than SARS-CoV-1. There is a dispute about the origin of COVID-19. Study results showed that all SARS-CoV-2 sequences around the world share a common ancestor towards the end of 2019. METHODS: Virus sequences from COVID-19 samples at the early time should be less diversifiable than those from samples at the later time because there might be more mutations when the virus evolutes over time. The diversity of virus nucleotide sequences can be measured by the nucleotide substitution distance. To explore the diversity of SARS-CoV-2, we use different nucleotide substitution models to calculate the distances of SARS-CoV-2 samples from 3 different areas, China, Europe, and the USA. Then, we use these distances to infer the origin of COVID-19. RESULTS: It is known that COVID-19 originated in Wuhan China and then spread to Europe and the USA. By using different substitution models, the distances of SARS-CoV-2 samples from these areas are significantly different. By ANOVA testing, the p-value is less than 2.2e-16. The analyzed results in most substitution models show that China has the lowest diversity, followed by Europe and lastly by the USA. This outcome coincides with the virus transmission time order that SARS-CoV-2 starts in China, then outbreaks in Europe and finally in the USA. CONCLUSION: The magnitude of nucleotide substitution distance of SARS-CoV-2 is closely related to the transmission time order of SARS-CoV-2. This outcome reveals that the nucleotide substitution distance of SARS-CoV-2 may be used to infer the origin of COVID-19.