Alzheimer’s disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults.Pathogenic factors,such as oxidative stress,an increase in acetylcholinester...Alzheimer’s disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults.Pathogenic factors,such as oxidative stress,an increase in acetylcholinesterase activity,mitochondrial dysfunction,genotoxicity,and neuroinflammation are present in this syndrome,which leads to neurodegeneration.Neurodegenerative pathologies such as Alzheimer’s disease are considered late-onset diseases caused by the complex combination of genetic,epigenetic,and environmental factors.There are two main types of Alzheimer’s disease,known as familial Alzheimer’s disease(onset<65 years)and late-onset or sporadic Alzheimer’s disease(onset≥65 years).Patients with familial Alzheimer’s disease inherit the disease due to rare mutations on the amyloid precursor protein(APP),presenilin 1 and 2(PSEN1 and PSEN2)genes in an autosomaldominantly fashion with closely 100%penetrance.In contrast,a different picture seems to emerge for sporadic Alzheimer’s disease,which exhibits numerous non-Mendelian anomalies suggesting an epigenetic component in its etiology.Importantly,the fundamental pathophysiological mechanisms driving Alzheimer’s disease are interfaced with epigenetic dysregulation.However,the dynamic nature of epigenetics seems to open up new avenues and hope in regenerative neurogenesis to improve brain repair in Alzheimer’s disease or following injury or stroke in humans.In recent years,there has been an increase in interest in using natural products for the treatment of neurodegenerative illnesses such as Alzheimer’s disease.Through epigenetic mechanisms,such as DNA methylation,non-coding RNAs,histone modification,and chromatin conformation regulation,natural compounds appear to exert neuroprotective effects.While we do not purport to cover every in this work,we do attempt to illustrate how various phytochemical compounds regulate the epigenetic effects of a few Alzheimer’s disease-related genes.展开更多
Parkinson’s disease is a common neurodegenerative disease with movement disorders associated with the intracytoplasmic deposition of aggregate proteins such asα-synuclein in neurons.As one of the major intracellular...Parkinson’s disease is a common neurodegenerative disease with movement disorders associated with the intracytoplasmic deposition of aggregate proteins such asα-synuclein in neurons.As one of the major intracellular degradation pathways,the autophagy-lysosome pathway plays an important role in eliminating these proteins.Accumulating evidence has shown that upregulation of the autophagy-lysosome pathway may contribute to the clearance ofα-synuclein aggregates and protect against degeneration of dopaminergic neurons in Parkinson’s disease.Moreover,multiple genes associated with the pathogenesis of Parkinson’s disease are intimately linked to alterations in the autophagy-lysosome pathway.Thus,this pathway appears to be a promising therapeutic target for treatment of Parkinson’s disease.In this review,we briefly introduce the machinery of autophagy.Then,we provide a description of the effects of Parkinson’s disease–related genes on the autophagy-lysosome pathway.Finally,we highlight the potential chemical and genetic therapeutic strategies targeting the autophagy–lysosome pathway and their applications in Parkinson’s disease.展开更多
Introduction: Omicron is a highly divergent variant of concern (VOCs) of a severe acute respiratory syndrome SARS-CoV-2. It carries a high number of mutations in its spike protein hence;it is more transmissible in the...Introduction: Omicron is a highly divergent variant of concern (VOCs) of a severe acute respiratory syndrome SARS-CoV-2. It carries a high number of mutations in its spike protein hence;it is more transmissible in the community by immune evasion mechanisms. Due to mutation within S gene, most Omicron variants have reported S gene target failure (SGTF) with some commercially available PCR kits. Such diagnostic features can be used as markers to screen Omicron. However, Whole Genome Sequencing (WGS) is the only gold standard approach to confirm novel microorganisms at genetically level as similar mutations can also be found in other variants that are circulating at low frequencies worldwide. This Retrospective study is aimed to assess RT-PCR sensitivity in the detection of S gene target failure in comparison with whole genome sequencing to detect variants of Omicron. Methods: We have analysed retrospective data of SARS-CoV-2 positive RT-PCR samples for S gene target failure (SGTF) with TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) and combined with sequencing technologies to study the emerged pattern of SARS-CoV-2 variants during third wave at the tertiary care centre, Surat. Results: From the first day of December 2021 till the end of February 2022, a total of 321,803 diagnostic RT-PCR tests for SARS-CoV-2 were performed, of which 20,566 positive cases were reported at our tertiary care centre with an average cumulative positivity of 6.39% over a period of three months. In the month of December 21 samples characterized by the SGTF (70/129) were suggestive of being infected by the Omicron variant and identified as Omicron (B.1.1.529 lineage) when sequence. In the month of January, we analysed a subset of samples (n = 618) with SGTF (24%) and without SGTF (76%) with Ct values Conclusions: During the COVID-19 pandemic, it took almost more than 15 days to diagnose infection and identify pathogen by sequencing technology. In contrast to that molecular assay provided quick identification with the help of SGTF phenomenon within 5 hours of duration. This strategy helps scientists and health policymakers for the quick isolation and identification of clusters. That ultimately results in a decreased transmission of pathogen among the community.展开更多
The E3 ubiquitin ligase,carboxyl terminus of heat shock protein 70(Hsp70)interacting protein(CHIP),also functions as a co-chaperone and plays a crucial role in the protein quality control system.In this study,we aimed...The E3 ubiquitin ligase,carboxyl terminus of heat shock protein 70(Hsp70)interacting protein(CHIP),also functions as a co-chaperone and plays a crucial role in the protein quality control system.In this study,we aimed to investigate the neuroprotective effect of overexpressed CHIP on Alzheimer’s disease.We used an adeno-associated virus vector that can cross the blood-brain barrier to mediate CHIP overexpression in APP/PS1 mouse brain.CHIP overexpression significantly ameliorated the performance of APP/PS1 mice in the Morris water maze and nest building tests,reduced amyloid-βplaques,and decreased the expression of both amyloid-βand phosphorylated tau.CHIP also alleviated the concentration of microglia and astrocytes around plaques.In APP/PS1 mice of a younger age,CHIP overexpression promoted an increase in ADAM10 expression and inhibitedβ-site APP cleaving enzyme 1,insulin degrading enzyme,and neprilysin expression.Levels of HSP70 and HSP40,which have functional relevance to CHIP,were also increased.Single nuclei transcriptome sequencing in the hippocampus of CHIP overexpressed mice showed that the lysosomal pathway and oligodendrocyte-related biological processes were up-regulated,which may also reflect a potential mechanism for the neuroprotective effect of CHIP.Our research shows that CHIP effectively reduces the behavior and pathological manifestations of APP/PS1 mice.Indeed,overexpression of CHIP could be a beneficial approach for the treatment of Alzheimer’s disease.展开更多
Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many diseases.Employing machine learning(ML)in the prediction of many diseases based on GE data has been a flourishin...Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many diseases.Employing machine learning(ML)in the prediction of many diseases based on GE data has been a flourishing research area.However,some diseases,like Alzheimer’s disease(AD),have not received considerable attention,probably owing to data scarcity obstacles.In this work,we shed light on the prediction of AD from GE data accurately using ML.Our approach consists of four phases:preprocessing,gene selection(GS),classification,and performance validation.In the preprocessing phase,gene columns are preprocessed identically.In the GS phase,a hybrid filtering method and embedded method are used.In the classification phase,three ML models are implemented using the bare minimum of the chosen genes obtained from the previous phase.The final phase is to validate the performance of these classifiers using different metrics.The crux of this article is to select the most informative genes from the hybrid method,and the best ML technique to predict AD using this minimal set of genes.Five different datasets are used to achieve our goal.We predict AD with impressive values forMultiLayer Perceptron(MLP)classifier which has the best performance metrics in four datasets,and the Support Vector Machine(SVM)achieves the highest performance values in only one dataset.We assessed the classifiers using sevenmetrics;and received impressive results,allowing for a credible performance rating.The metrics values we obtain in our study lie in the range[.97,.99]for the accuracy(Acc),[.97,.99]for F1-score,[.94,.98]for kappa index,[.97,.99]for area under curve(AUC),[.95,1]for precision,[.98,.99]for sensitivity(recall),and[.98,1]for specificity.With these results,the proposed approach outperforms recent interesting results.With these results,the proposed approach outperforms recent interesting results.展开更多
Over the past three decades, genomic and epigenetic sciences have identified more than 70 genes involved in the molecular pathophysiology of Alzheimer’s disease (AD). DNA methylation, abnormal histone and chromatin r...Over the past three decades, genomic and epigenetic sciences have identified more than 70 genes involved in the molecular pathophysiology of Alzheimer’s disease (AD). DNA methylation, abnormal histone and chromatin regulation and the action of various miRNAs induce AD. The identification of mutated genes has paved the way for the development of diagnostic kits and the initiation of gene therapy trials. However, despite major advances in neuroscience research, there is yet no suitable treatment for AD. Therefore, the early diagnosis of this neurodegenerative disease raises several ethical questions, including the balance between the principle of non-maleficence and the principle of beneficence. The aims of this research were to present the genomic and ethical aspects of AD, and to highlight the ethical principles involved in its presymptomatic diagnosis and therapy. A systematic review of the literature in PubMed, Google Scholar and Science Direct was carried out to outline the genomic aspects and ethical principles relating not only to the presymptomatic diagnosis of AD, but also to its gene therapy. A total of 16 publications were selected. AD is a multifactorial disease that can be genetically classified into Sporadic Alzheimer’s Disease and Familial Alzheimer’s Disease based on family history. Gene therapy targeting specific disease-causing genes is a promising therapeutic strategy. Advancements in artificial intelligence applications may enable the prediction of AD onset several years in advance. While early diagnosis of AD may empower patients with full decision competence for early decision-making, it also carries implications for the patient’s family members, who are at risk of developing the disease, potentially becoming a source of confusion or anxiety. AD has a significant impact on the life of individuals at risk and their families. Given the absence of disease modifying therapy, genetic screening and early diagnosis for this condition raise ethical issues that must be carefully considered in the context of fundamental bioethical principles, including autonomy, beneficence, non-maleficence, and justice.展开更多
Toxic aggregated amyloid-βaccumulation is a key pathogenic event in Alzheimer’s disease.Treatment approaches have focused on the suppression,deferral,or dispersion of amyloid-βfibers and plaques.Gene therapy has ev...Toxic aggregated amyloid-βaccumulation is a key pathogenic event in Alzheimer’s disease.Treatment approaches have focused on the suppression,deferral,or dispersion of amyloid-βfibers and plaques.Gene therapy has evolved as a potential therapeutic option for treating Alzheimer’s disease,owing to its rapid advancement over the recent decade.Small interfering ribonucleic acid has recently garnered considerable attention in gene therapy owing to its ability to down-regulate genes with high sequence specificity and an almost limitless number of therapeutic targets,including those that were once considered undruggable.However,lackluster cellular uptake and the destabilization of small interfering ribonucleic acid in its biological environment restrict its therapeutic application,necessitating the development of a vector that can safeguard the genetic material from early destruction within the bloodstream while effectively delivering therapeutic genes across the bloodbrain barrier.Nanotechnology has emerged as a possible solution,and several delivery systems utilizing nanoparticles have been shown to bypass key challenges regarding small interfering ribonucleic acid delivery.By reducing the enzymatic breakdown of genetic components,nanomaterials as gene carriers have considerably enhanced the efficiency of gene therapy.Liposomes,polymeric nanoparticles,magnetic nanoparticles,dendrimers,and micelles are examples of nanocarriers that have been designed,and each has its own set of features.Furthermore,recent advances in the specific delivery of neurotrophic compounds via gene therapy have provided promising results in relation to augmenting cognitive abilities.In this paper,we highlight the use of different nanocarriers in targeted gene delivery and small interfering ribonucleic acid-mediated gene silencing as a potential platform for treating Alzheimer’s disease.展开更多
Sea cucumber Holothuria leucospilota is one of the most widespread tropical holothurian species.In this study,eukaryotic organism composition in foregut and hindgut contents of H.leucospilota and surrounding sediments...Sea cucumber Holothuria leucospilota is one of the most widespread tropical holothurian species.In this study,eukaryotic organism composition in foregut and hindgut contents of H.leucospilota and surrounding sediments was assessed by 18S rRNA gene high-throughput sequencing.Eukaryon richness and diversity in the habitat sediments were significantly higher than those in foregut and hindgut contents of the sea cucumbers(P<0.05).The foregut content group,hindgut content group,and marine sediment group sequences were respectively assigned to 18.20±1.32,19.40±1.03,and 21.80±0.37 phyla.In the foregut contents,Nematoda(20.18%±9.59%),Mollusca(16.12%±10.49%),Chlorophyta(10.04%±4.85%),Annelida(8.72%±10.93%),Streptophyta(8.46%±4.65%),and Diatomea(5.99%±2.01%)were the predominant phyla,which showed the eukaryotic food sources of H.leucospilota were primarily belong to the above phyla.The predominant phyla in the hindgut contents were Streptophyta(45.55%±17.32%),Mollusca(4.93%±4.82%),Arthropoda(5.37%±3.08%),Diatomea(3.88%±2.34%),and Chlorophyta(3.79%±1.59%);and Annelida(37.80%±17.00%),Arthropoda(24.49%±12.53%),Platyhelminthes(7.14%±3.02%),Nematoda(4.14%±0.91%),and Diatomea(5.11%±1.35%)had large contents in the sediments.The comparatively high content of Paris genus in phylum Streptophyta in foregut contents indicated that land plants were one of the primary food sources of H.leucospilota,however the significantly higher contents of Streptophyta in hindgut contents than that in foregut contents might suggest a large part of the terrigenous detritus ingested might not be digested by H.leucospilota.UPGMA and PCoA analysis revealed that eukaryotic organism composition differed significantly between foregut contents of H.leucospilota and ambient sediments,indicating selective feeding feature of H.leucospilota.This study provided useful references for artificial feed of tropical sea cucumbers and enhanced understanding of the ecological roles of detritus-feeding macrobenthos.展开更多
Goji berry(Lycium barbarum L.)is substantially dependent on nitrogen fertilizer application,which can signifi-cantly enhance fruit yield and Goji berry industrial development in Ningxia,China.This study aimed to analyz...Goji berry(Lycium barbarum L.)is substantially dependent on nitrogen fertilizer application,which can signifi-cantly enhance fruit yield and Goji berry industrial development in Ningxia,China.This study aimed to analyze the functions of differential nitrogen application rates including low(N1),medium(N2),and high(N3)levels in soil microbial community structure(bacterial and fungal)at 2 diverse soil depths(0-20,20-40 cm)through high-throughput sequencing technology by targeting 16S RNA gene and ITS1&ITS2 regions.All the observed physicochemical parameters exhibited significant improvement(p<0.05)with increased levels of nitrogen and the highest values for most parameters were observed at N2.However,pH decreased(p<0.05)gradually.The alpha and beta diversity analyses for bacterial and fungal communities’metagenome displayed more similarities than differences among all groups.The top bacterial and fungal phyla and genera suggested no obvious(p>0.05)differences among three group treatments(N1,N2,and N3).Furthermore,the functional enrichment analysis demonstrated significant(p<0.05)enrichment of quorum sensing,cysteine and methionine metabolism,and transcriptional machinery for bacterial communities,while various saprotrophic functional roles for fungal communities.Conclusively,moderately reducing the use of N-supplemented fertilizers is conducive to increasing soil nitrogen utilization rate,which can contribute to sustainable agriculture practices through improved soil quality,and microbial community structure and functions.展开更多
In this editorial,we comment on the article by Wang et al.This manuscript explores the potential synergistic effects of combining zanubrutinib,a novel oral inhibitor of Bruton’s tyrosine kinase,with high-dose methotr...In this editorial,we comment on the article by Wang et al.This manuscript explores the potential synergistic effects of combining zanubrutinib,a novel oral inhibitor of Bruton’s tyrosine kinase,with high-dose methotrexate(HD-MTX)as a therapeutic intervention for primary central nervous system lymphoma(PCNSL).The study involves a retrospective analysis of 19 PCNSL patients,highlighting clinicopathological characteristics,treatment outcomes,and genomic biomarkers.The results indicate the combination’s good tolerance and strong antitumor activity,with an 84.2%overall response rate.The authors emphasize the potential of zanubrutinib to modulate key genomic features of PCNSL,particularly mutations in myeloid differentiation primary response 88 and cluster of differentiation 79B.Furthermore,the study investigates the role of circulating tumor DNA in cerebrospinal fluid for disease surveillance and treatment response monitoring.In essence,the study provides valuable insights into the potential of combining zanubrutinib with HD-MTX as a frontline therapeutic regimen for PCNSL.The findings underscore the importance of exploring alternative treatment modalities and monitoring genomic and liquid biopsy markers to optimize patient outcomes.While the findings suggest promise,the study’s limitations should be considered,and further research is needed to establish the clinical relevance of this therapeutic approach for PCNSL.展开更多
BACKGROUND Thalidomide is an effective treatment for refractory Crohn’s disease(CD).However,thalidomide-induced peripheral neuropathy(TiPN),which has a large individual variation,is a major cause of treatment failure...BACKGROUND Thalidomide is an effective treatment for refractory Crohn’s disease(CD).However,thalidomide-induced peripheral neuropathy(TiPN),which has a large individual variation,is a major cause of treatment failure.TiPN is rarely predictable and recognized,especially in CD.It is necessary to develop a risk model to predict TiPN occurrence.AIM To develop and compare a predictive model of TiPN using machine learning based on comprehensive clinical and genetic variables.METHODS A retrospective cohort of 164 CD patients from January 2016 to June 2022 was used to establish the model.The National Cancer Institute Common Toxicity Criteria Sensory Scale(version 4.0)was used to assess TiPN.With 18 clinical features and 150 genetic variables,five predictive models were established and evaluated by the confusion matrix receiver operating characteristic curve(AUROC),area under the precision-recall curve(AUPRC),specificity,sensitivity(recall rate),precision,accuracy,and F1 score.RESULTS The top-ranking five risk variables associated with TiPN were interleukin-12 rs1353248[P=0.0004,odds ratio(OR):8.983,95%confidence interval(CI):2.497-30.90],dose(mg/d,P=0.002),brainderived neurotrophic factor(BDNF)rs2030324(P=0.001,OR:3.164,95%CI:1.561-6.434),BDNF rs6265(P=0.001,OR:3.150,95%CI:1.546-6.073)and BDNF rs11030104(P=0.001,OR:3.091,95%CI:1.525-5.960).In the training set,gradient boosting decision tree(GBDT),extremely random trees(ET),random forest,logistic regression and extreme gradient boosting(XGBoost)obtained AUROC values>0.90 and AUPRC>0.87.Among these models,XGBoost and GBDT obtained the first two highest AUROC(0.90 and 1),AUPRC(0.98 and 1),accuracy(0.96 and 0.98),precision(0.90 and 0.95),F1 score(0.95 and 0.98),specificity(0.94 and 0.97),and sensitivity(1).In the validation set,XGBoost algorithm exhibited the best predictive performance with the highest specificity(0.857),accuracy(0.818),AUPRC(0.86)and AUROC(0.89).ET and GBDT obtained the highest sensitivity(1)and F1 score(0.8).Overall,compared with other state-of-the-art classifiers such as ET,GBDT and RF,XGBoost algorithm not only showed a more stable performance,but also yielded higher ROC-AUC and PRC-AUC scores,demonstrating its high accuracy in prediction of TiPN occurrence.CONCLUSION The powerful XGBoost algorithm accurately predicts TiPN using 18 clinical features and 14 genetic variables.With the ability to identify high-risk patients using single nucleotide polymorphisms,it offers a feasible option for improving thalidomide efficacy in CD patients.展开更多
Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desir...Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.展开更多
文摘Alzheimer’s disease is a progressive neurodegenerative disorder and the most common cause of dementia that principally affects older adults.Pathogenic factors,such as oxidative stress,an increase in acetylcholinesterase activity,mitochondrial dysfunction,genotoxicity,and neuroinflammation are present in this syndrome,which leads to neurodegeneration.Neurodegenerative pathologies such as Alzheimer’s disease are considered late-onset diseases caused by the complex combination of genetic,epigenetic,and environmental factors.There are two main types of Alzheimer’s disease,known as familial Alzheimer’s disease(onset<65 years)and late-onset or sporadic Alzheimer’s disease(onset≥65 years).Patients with familial Alzheimer’s disease inherit the disease due to rare mutations on the amyloid precursor protein(APP),presenilin 1 and 2(PSEN1 and PSEN2)genes in an autosomaldominantly fashion with closely 100%penetrance.In contrast,a different picture seems to emerge for sporadic Alzheimer’s disease,which exhibits numerous non-Mendelian anomalies suggesting an epigenetic component in its etiology.Importantly,the fundamental pathophysiological mechanisms driving Alzheimer’s disease are interfaced with epigenetic dysregulation.However,the dynamic nature of epigenetics seems to open up new avenues and hope in regenerative neurogenesis to improve brain repair in Alzheimer’s disease or following injury or stroke in humans.In recent years,there has been an increase in interest in using natural products for the treatment of neurodegenerative illnesses such as Alzheimer’s disease.Through epigenetic mechanisms,such as DNA methylation,non-coding RNAs,histone modification,and chromatin conformation regulation,natural compounds appear to exert neuroprotective effects.While we do not purport to cover every in this work,we do attempt to illustrate how various phytochemical compounds regulate the epigenetic effects of a few Alzheimer’s disease-related genes.
基金supported by the National Natural Science Foundation of China,No.82101340(to FJ).
文摘Parkinson’s disease is a common neurodegenerative disease with movement disorders associated with the intracytoplasmic deposition of aggregate proteins such asα-synuclein in neurons.As one of the major intracellular degradation pathways,the autophagy-lysosome pathway plays an important role in eliminating these proteins.Accumulating evidence has shown that upregulation of the autophagy-lysosome pathway may contribute to the clearance ofα-synuclein aggregates and protect against degeneration of dopaminergic neurons in Parkinson’s disease.Moreover,multiple genes associated with the pathogenesis of Parkinson’s disease are intimately linked to alterations in the autophagy-lysosome pathway.Thus,this pathway appears to be a promising therapeutic target for treatment of Parkinson’s disease.In this review,we briefly introduce the machinery of autophagy.Then,we provide a description of the effects of Parkinson’s disease–related genes on the autophagy-lysosome pathway.Finally,we highlight the potential chemical and genetic therapeutic strategies targeting the autophagy–lysosome pathway and their applications in Parkinson’s disease.
文摘Introduction: Omicron is a highly divergent variant of concern (VOCs) of a severe acute respiratory syndrome SARS-CoV-2. It carries a high number of mutations in its spike protein hence;it is more transmissible in the community by immune evasion mechanisms. Due to mutation within S gene, most Omicron variants have reported S gene target failure (SGTF) with some commercially available PCR kits. Such diagnostic features can be used as markers to screen Omicron. However, Whole Genome Sequencing (WGS) is the only gold standard approach to confirm novel microorganisms at genetically level as similar mutations can also be found in other variants that are circulating at low frequencies worldwide. This Retrospective study is aimed to assess RT-PCR sensitivity in the detection of S gene target failure in comparison with whole genome sequencing to detect variants of Omicron. Methods: We have analysed retrospective data of SARS-CoV-2 positive RT-PCR samples for S gene target failure (SGTF) with TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) and combined with sequencing technologies to study the emerged pattern of SARS-CoV-2 variants during third wave at the tertiary care centre, Surat. Results: From the first day of December 2021 till the end of February 2022, a total of 321,803 diagnostic RT-PCR tests for SARS-CoV-2 were performed, of which 20,566 positive cases were reported at our tertiary care centre with an average cumulative positivity of 6.39% over a period of three months. In the month of December 21 samples characterized by the SGTF (70/129) were suggestive of being infected by the Omicron variant and identified as Omicron (B.1.1.529 lineage) when sequence. In the month of January, we analysed a subset of samples (n = 618) with SGTF (24%) and without SGTF (76%) with Ct values Conclusions: During the COVID-19 pandemic, it took almost more than 15 days to diagnose infection and identify pathogen by sequencing technology. In contrast to that molecular assay provided quick identification with the help of SGTF phenomenon within 5 hours of duration. This strategy helps scientists and health policymakers for the quick isolation and identification of clusters. That ultimately results in a decreased transmission of pathogen among the community.
基金supported by the National Natural Science Foundation of China,Nos.91849115 and U1904207(to YX),81974211 and 82171247(to CS)Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences,No.2020-PT310-01(to YX).
文摘The E3 ubiquitin ligase,carboxyl terminus of heat shock protein 70(Hsp70)interacting protein(CHIP),also functions as a co-chaperone and plays a crucial role in the protein quality control system.In this study,we aimed to investigate the neuroprotective effect of overexpressed CHIP on Alzheimer’s disease.We used an adeno-associated virus vector that can cross the blood-brain barrier to mediate CHIP overexpression in APP/PS1 mouse brain.CHIP overexpression significantly ameliorated the performance of APP/PS1 mice in the Morris water maze and nest building tests,reduced amyloid-βplaques,and decreased the expression of both amyloid-βand phosphorylated tau.CHIP also alleviated the concentration of microglia and astrocytes around plaques.In APP/PS1 mice of a younger age,CHIP overexpression promoted an increase in ADAM10 expression and inhibitedβ-site APP cleaving enzyme 1,insulin degrading enzyme,and neprilysin expression.Levels of HSP70 and HSP40,which have functional relevance to CHIP,were also increased.Single nuclei transcriptome sequencing in the hippocampus of CHIP overexpressed mice showed that the lysosomal pathway and oligodendrocyte-related biological processes were up-regulated,which may also reflect a potential mechanism for the neuroprotective effect of CHIP.Our research shows that CHIP effectively reduces the behavior and pathological manifestations of APP/PS1 mice.Indeed,overexpression of CHIP could be a beneficial approach for the treatment of Alzheimer’s disease.
文摘Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many diseases.Employing machine learning(ML)in the prediction of many diseases based on GE data has been a flourishing research area.However,some diseases,like Alzheimer’s disease(AD),have not received considerable attention,probably owing to data scarcity obstacles.In this work,we shed light on the prediction of AD from GE data accurately using ML.Our approach consists of four phases:preprocessing,gene selection(GS),classification,and performance validation.In the preprocessing phase,gene columns are preprocessed identically.In the GS phase,a hybrid filtering method and embedded method are used.In the classification phase,three ML models are implemented using the bare minimum of the chosen genes obtained from the previous phase.The final phase is to validate the performance of these classifiers using different metrics.The crux of this article is to select the most informative genes from the hybrid method,and the best ML technique to predict AD using this minimal set of genes.Five different datasets are used to achieve our goal.We predict AD with impressive values forMultiLayer Perceptron(MLP)classifier which has the best performance metrics in four datasets,and the Support Vector Machine(SVM)achieves the highest performance values in only one dataset.We assessed the classifiers using sevenmetrics;and received impressive results,allowing for a credible performance rating.The metrics values we obtain in our study lie in the range[.97,.99]for the accuracy(Acc),[.97,.99]for F1-score,[.94,.98]for kappa index,[.97,.99]for area under curve(AUC),[.95,1]for precision,[.98,.99]for sensitivity(recall),and[.98,1]for specificity.With these results,the proposed approach outperforms recent interesting results.With these results,the proposed approach outperforms recent interesting results.
文摘Over the past three decades, genomic and epigenetic sciences have identified more than 70 genes involved in the molecular pathophysiology of Alzheimer’s disease (AD). DNA methylation, abnormal histone and chromatin regulation and the action of various miRNAs induce AD. The identification of mutated genes has paved the way for the development of diagnostic kits and the initiation of gene therapy trials. However, despite major advances in neuroscience research, there is yet no suitable treatment for AD. Therefore, the early diagnosis of this neurodegenerative disease raises several ethical questions, including the balance between the principle of non-maleficence and the principle of beneficence. The aims of this research were to present the genomic and ethical aspects of AD, and to highlight the ethical principles involved in its presymptomatic diagnosis and therapy. A systematic review of the literature in PubMed, Google Scholar and Science Direct was carried out to outline the genomic aspects and ethical principles relating not only to the presymptomatic diagnosis of AD, but also to its gene therapy. A total of 16 publications were selected. AD is a multifactorial disease that can be genetically classified into Sporadic Alzheimer’s Disease and Familial Alzheimer’s Disease based on family history. Gene therapy targeting specific disease-causing genes is a promising therapeutic strategy. Advancements in artificial intelligence applications may enable the prediction of AD onset several years in advance. While early diagnosis of AD may empower patients with full decision competence for early decision-making, it also carries implications for the patient’s family members, who are at risk of developing the disease, potentially becoming a source of confusion or anxiety. AD has a significant impact on the life of individuals at risk and their families. Given the absence of disease modifying therapy, genetic screening and early diagnosis for this condition raise ethical issues that must be carefully considered in the context of fundamental bioethical principles, including autonomy, beneficence, non-maleficence, and justice.
基金supported by the Intramural Research Program National Institute on Aginq,NIH。
文摘Toxic aggregated amyloid-βaccumulation is a key pathogenic event in Alzheimer’s disease.Treatment approaches have focused on the suppression,deferral,or dispersion of amyloid-βfibers and plaques.Gene therapy has evolved as a potential therapeutic option for treating Alzheimer’s disease,owing to its rapid advancement over the recent decade.Small interfering ribonucleic acid has recently garnered considerable attention in gene therapy owing to its ability to down-regulate genes with high sequence specificity and an almost limitless number of therapeutic targets,including those that were once considered undruggable.However,lackluster cellular uptake and the destabilization of small interfering ribonucleic acid in its biological environment restrict its therapeutic application,necessitating the development of a vector that can safeguard the genetic material from early destruction within the bloodstream while effectively delivering therapeutic genes across the bloodbrain barrier.Nanotechnology has emerged as a possible solution,and several delivery systems utilizing nanoparticles have been shown to bypass key challenges regarding small interfering ribonucleic acid delivery.By reducing the enzymatic breakdown of genetic components,nanomaterials as gene carriers have considerably enhanced the efficiency of gene therapy.Liposomes,polymeric nanoparticles,magnetic nanoparticles,dendrimers,and micelles are examples of nanocarriers that have been designed,and each has its own set of features.Furthermore,recent advances in the specific delivery of neurotrophic compounds via gene therapy have provided promising results in relation to augmenting cognitive abilities.In this paper,we highlight the use of different nanocarriers in targeted gene delivery and small interfering ribonucleic acid-mediated gene silencing as a potential platform for treating Alzheimer’s disease.
基金Supported by the National Natural Science Foundation of China(Nos.42166005,42076097)the Hainan Provincial Key Research and Development Program(No.ZDYF2021XDNY130)+1 种基金the Natural Science Foundation of Hainan Province(No.321RC1023)the State Key Laboratory of Marine Resource Utilization in South China Sea Open Project(No.MRUKF2021008)。
文摘Sea cucumber Holothuria leucospilota is one of the most widespread tropical holothurian species.In this study,eukaryotic organism composition in foregut and hindgut contents of H.leucospilota and surrounding sediments was assessed by 18S rRNA gene high-throughput sequencing.Eukaryon richness and diversity in the habitat sediments were significantly higher than those in foregut and hindgut contents of the sea cucumbers(P<0.05).The foregut content group,hindgut content group,and marine sediment group sequences were respectively assigned to 18.20±1.32,19.40±1.03,and 21.80±0.37 phyla.In the foregut contents,Nematoda(20.18%±9.59%),Mollusca(16.12%±10.49%),Chlorophyta(10.04%±4.85%),Annelida(8.72%±10.93%),Streptophyta(8.46%±4.65%),and Diatomea(5.99%±2.01%)were the predominant phyla,which showed the eukaryotic food sources of H.leucospilota were primarily belong to the above phyla.The predominant phyla in the hindgut contents were Streptophyta(45.55%±17.32%),Mollusca(4.93%±4.82%),Arthropoda(5.37%±3.08%),Diatomea(3.88%±2.34%),and Chlorophyta(3.79%±1.59%);and Annelida(37.80%±17.00%),Arthropoda(24.49%±12.53%),Platyhelminthes(7.14%±3.02%),Nematoda(4.14%±0.91%),and Diatomea(5.11%±1.35%)had large contents in the sediments.The comparatively high content of Paris genus in phylum Streptophyta in foregut contents indicated that land plants were one of the primary food sources of H.leucospilota,however the significantly higher contents of Streptophyta in hindgut contents than that in foregut contents might suggest a large part of the terrigenous detritus ingested might not be digested by H.leucospilota.UPGMA and PCoA analysis revealed that eukaryotic organism composition differed significantly between foregut contents of H.leucospilota and ambient sediments,indicating selective feeding feature of H.leucospilota.This study provided useful references for artificial feed of tropical sea cucumbers and enhanced understanding of the ecological roles of detritus-feeding macrobenthos.
基金This work was funded by Ningxia Hui Autonomous Region Key Research and Development Project(2021BEF02004),Central Finance Forestry Reform and Development Fund“Forest Seed Cultivation”.
文摘Goji berry(Lycium barbarum L.)is substantially dependent on nitrogen fertilizer application,which can signifi-cantly enhance fruit yield and Goji berry industrial development in Ningxia,China.This study aimed to analyze the functions of differential nitrogen application rates including low(N1),medium(N2),and high(N3)levels in soil microbial community structure(bacterial and fungal)at 2 diverse soil depths(0-20,20-40 cm)through high-throughput sequencing technology by targeting 16S RNA gene and ITS1&ITS2 regions.All the observed physicochemical parameters exhibited significant improvement(p<0.05)with increased levels of nitrogen and the highest values for most parameters were observed at N2.However,pH decreased(p<0.05)gradually.The alpha and beta diversity analyses for bacterial and fungal communities’metagenome displayed more similarities than differences among all groups.The top bacterial and fungal phyla and genera suggested no obvious(p>0.05)differences among three group treatments(N1,N2,and N3).Furthermore,the functional enrichment analysis demonstrated significant(p<0.05)enrichment of quorum sensing,cysteine and methionine metabolism,and transcriptional machinery for bacterial communities,while various saprotrophic functional roles for fungal communities.Conclusively,moderately reducing the use of N-supplemented fertilizers is conducive to increasing soil nitrogen utilization rate,which can contribute to sustainable agriculture practices through improved soil quality,and microbial community structure and functions.
文摘In this editorial,we comment on the article by Wang et al.This manuscript explores the potential synergistic effects of combining zanubrutinib,a novel oral inhibitor of Bruton’s tyrosine kinase,with high-dose methotrexate(HD-MTX)as a therapeutic intervention for primary central nervous system lymphoma(PCNSL).The study involves a retrospective analysis of 19 PCNSL patients,highlighting clinicopathological characteristics,treatment outcomes,and genomic biomarkers.The results indicate the combination’s good tolerance and strong antitumor activity,with an 84.2%overall response rate.The authors emphasize the potential of zanubrutinib to modulate key genomic features of PCNSL,particularly mutations in myeloid differentiation primary response 88 and cluster of differentiation 79B.Furthermore,the study investigates the role of circulating tumor DNA in cerebrospinal fluid for disease surveillance and treatment response monitoring.In essence,the study provides valuable insights into the potential of combining zanubrutinib with HD-MTX as a frontline therapeutic regimen for PCNSL.The findings underscore the importance of exploring alternative treatment modalities and monitoring genomic and liquid biopsy markers to optimize patient outcomes.While the findings suggest promise,the study’s limitations should be considered,and further research is needed to establish the clinical relevance of this therapeutic approach for PCNSL.
基金National Natural Science Foundation of China,No.81973398,No.81730103,No.81573507 and No.82020108031The National Key Research and Development Program,No.2017YFC0909300 and No.2016YFC0905001+5 种基金Guangdong Provincial Key Laboratory of Construction Foundation,No.2017B030314030 and No.2020B1212060034Science and Technology Program of Guangzhou,No.201607020031National Engineering and Technology Research Center for New Drug Druggability Evaluation(Seed Program of Guangdong Province),No.2017B090903004The 111 Project,No.B16047China Postdoctoral Science Foundation,No.2019M66324,No.2020M683140 and No.2020M683139Natural Science Foundation of Guangdong Province,No.2022A1515012549 and No.2023A1515012667.
文摘BACKGROUND Thalidomide is an effective treatment for refractory Crohn’s disease(CD).However,thalidomide-induced peripheral neuropathy(TiPN),which has a large individual variation,is a major cause of treatment failure.TiPN is rarely predictable and recognized,especially in CD.It is necessary to develop a risk model to predict TiPN occurrence.AIM To develop and compare a predictive model of TiPN using machine learning based on comprehensive clinical and genetic variables.METHODS A retrospective cohort of 164 CD patients from January 2016 to June 2022 was used to establish the model.The National Cancer Institute Common Toxicity Criteria Sensory Scale(version 4.0)was used to assess TiPN.With 18 clinical features and 150 genetic variables,five predictive models were established and evaluated by the confusion matrix receiver operating characteristic curve(AUROC),area under the precision-recall curve(AUPRC),specificity,sensitivity(recall rate),precision,accuracy,and F1 score.RESULTS The top-ranking five risk variables associated with TiPN were interleukin-12 rs1353248[P=0.0004,odds ratio(OR):8.983,95%confidence interval(CI):2.497-30.90],dose(mg/d,P=0.002),brainderived neurotrophic factor(BDNF)rs2030324(P=0.001,OR:3.164,95%CI:1.561-6.434),BDNF rs6265(P=0.001,OR:3.150,95%CI:1.546-6.073)and BDNF rs11030104(P=0.001,OR:3.091,95%CI:1.525-5.960).In the training set,gradient boosting decision tree(GBDT),extremely random trees(ET),random forest,logistic regression and extreme gradient boosting(XGBoost)obtained AUROC values>0.90 and AUPRC>0.87.Among these models,XGBoost and GBDT obtained the first two highest AUROC(0.90 and 1),AUPRC(0.98 and 1),accuracy(0.96 and 0.98),precision(0.90 and 0.95),F1 score(0.95 and 0.98),specificity(0.94 and 0.97),and sensitivity(1).In the validation set,XGBoost algorithm exhibited the best predictive performance with the highest specificity(0.857),accuracy(0.818),AUPRC(0.86)and AUROC(0.89).ET and GBDT obtained the highest sensitivity(1)and F1 score(0.8).Overall,compared with other state-of-the-art classifiers such as ET,GBDT and RF,XGBoost algorithm not only showed a more stable performance,but also yielded higher ROC-AUC and PRC-AUC scores,demonstrating its high accuracy in prediction of TiPN occurrence.CONCLUSION The powerful XGBoost algorithm accurately predicts TiPN using 18 clinical features and 14 genetic variables.With the ability to identify high-risk patients using single nucleotide polymorphisms,it offers a feasible option for improving thalidomide efficacy in CD patients.
文摘Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.
