VPMCD: variable interaction modeling approach for class discrimination in biological systems

Data classification algorithms applied for class prediction in computational biology literature are data specific and have shown varying degrees of performance. Different classes cannot be distinguished solely based on interclass distances or decision boundaries. We propose that inter-relations among the features be exploited for separating observations into specific classes. A new variable predictive model based class discrimination (VPMCD) method is described here. Three well established and proven data sets of varying statistical and biological significance are utilized as benchmark. The performance of the new method is compared with advanced classification algorithms. The new method performs better during different tests and shows higher stability and robustness. The VPMCD is observed to be a potentially strong classification approach and can be effectively extended to other data mining applications involving biological systems.     

Learning the drug target-likeness of a protein

Current drug discovery and development approaches rely extensively on the identification and validation of appropriate targets; for example, those with marketable and robust therapeutics. Wide-ranging efforts have been directed at this problem and various approaches have been developed to identify disease-associated genes as candidates. In this work, we show with statistical significance that successful drug targets, in addition to their linkage to disease, share common characteristics that are disease-independent. For example, marked differences in functional category, tissue specificity, and sequence variability are observed between known targets and average proteins. These results lead to an interesting hypothesis: potentially good drug targets shall have some desired properties, which we refer to as "drug target-likeness" that are beyond their disease-associations. Because of the limited availability of comprehensive protein characteristics data, we tried to learn the drug target-likeness property at the sequence level. Results show that a support vector machine model is able to accurately distinguish targets from nontargets entirely with sequence features. It is our hope that these encouraging results will invite future systematic proteomic scale experiments to gather necessary protein characteristics data for the accurate and predictive definition of "drug target-likeness", providing a new perspective toward understanding and pursuing effective therapeutics.     

Adhesive thermosensitive gels for local delivery of viral vectors

Local delivery of viral vectors can enhance the efficacy of therapies by selectively affecting necessary tissues and reducing the required vector dose. Pluronic F127 is a thermosensitive polymer that undergoes a solution–gelation (sol–gel) transition as temperature increases and can deliver vectors without damaging them. While pluronics can be spread over large areas, such as the surface of an organ, before gelation, they lack sufficient adhesivity to remain attached to some tissues, such as the surface of the heart or mucosal surfaces. Here, we utilized blends of pluronic F127 and polycarbophil (PCB), a mucoadhesive agent, to provide the necessary adhesivity for local delivery of viral vectors to the cardiac muscle. The effects of PCB concentration on adhesive properties, sol–gel temperature transition and cytocompatibility were evaluated. Rheological studies showed that PCB decreased the sol–gel transition temperature at concentrations >1% and increased the adhesive properties of the gel. Furthermore, these gels were able to deliver viral vectors and transduce cells in vitro and in vivo in a neonatal mouse apical resection model. These gels could be a useful platform for delivering viral vectors over the surface of organs where increased adhesivity is required.     

Machine Learning in Healthcare

Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. Although, skepticism remains regarding the practical application and interpretation of results from ML-based approaches in healthcare settings, the inclusion of these approaches is increasing at a rapid pace. Here we provide a brief overview of machine learning-based approaches and learning algorithms including supervised, unsupervised, and reinforcement learning along with examples. Second, we discuss the application of ML in several healthcare fields, including radiology, genetics, electronic health records, and neuroimaging. We also briefly discuss the risks and challenges of ML application to healthcare such as system privacy and ethical concerns and provide suggestions for future applications.     

Application of partial restriction procedure in both shotgun and non-random strategies for nucleotide sequencing

Partial digestion of a target DNA fragment with 4-bp-recognition restriction enzymes followed by a forced ligation to an M13 vector was employed for the construction of a subfragment library. The library can be used for either shotgun or non-random nucleotide sequencing. Application of the partial digests generated with the 4-bp recognition restriction enzymes instead of DNase I in the improved non-random strategy for nucleotide sequencing (Li and Wu, 1987) made the procedure as easy as that of the random strategy. The library can also be used in shotgun nucleotide sequencing directly, and few self-ligated subfragments were found. The usefulness of this procedure was demonstrated by the sequencing of a goat 6.5-kb EcoRI fragment, which is located 5' to the globin gene.     

A vector with the downstream box of the initiation codon can highly enhance protein expression in Escherichia coli

An expression vector, pET-DB, with a perfectly matching downstream box of the initiation codon has been constructed on the basis of the pET system. Any gene of interest can then be inserted into the vector. Four genes were used to test the expression efficiency of the vector. The results show that the vector pET-DB can further increase protein expression level at least up to 35–70% as compared with the initial T7 expression system, indicating that the downstream box can enhance protein expression in Escherichia coli.     

The poultry red mite,Dermanyssus gallinae,a potential vector of Erysipelothrix rhusiopathiae causing erysipelas in hens

Erysipelas is a bacterial disease caused by Erysipelothrix rhusiopathiae, which may infect swine as well as several other species of mammals and birds, including domestic fowl. In poultry, erysipelas may cause sudden high mortality due to septicemia. This communication describes the first isolation of E. rhusiopathiae from the haematophagous poultry red mite, Dermanyssus gallinae DeGeer (Acari: Dermanyssidae), that was collected on three farms where hen erysipelas was diagnosed. The bacteria were isolated from the integument as well as from the interior of the mites. Serotypes 1a and 1b of E. rhusiopathiae found in the mites corresponded with those isolated from the diseased birds. These findings imply that D. gallinae is a potential vector of E. rhusiopathiae. The current lack of effective measures to control D. gallinae causes recurring mite problems in poultry facilities once afflicted by this parasite. Consequently, mites containing E. rhusiopathiae may act as reservoir hosts of this bacterium, allowing it to persist in the poultry house between flock cycles as a source of infection for the replacement pullets. The zoonotic potentials of both E. rhusiopathiae and D. gallinae should also be considered.     

Monitoring of Ubiquitin-proteasome Activity in Living Cells Using a Degron (dgn)-destabilized Green Fluorescent Protein (GFP)-based Reporter Protein

Proteasome is the main intracellular organelle involved in the proteolytic degradation of abnormal, misfolded, damaged or oxidized proteins ^{1, 2}. Maintenance of proteasome activity was implicated in many key cellular processes, like cell''s stress response ³, cell cycle regulation and cellular differentiation ⁴ or in immune system response ⁵. The dysfunction of the ubiquitin-proteasome system has been related to the development of tumors and neurodegenerative diseases ^{4, 6}. Additionally, a decrease in proteasome activity was found as a feature of cellular senescence and organismal aging ^{7, 8, 9, 10}. Here, we present a method to measure ubiquitin-proteasome activity in living cells using a GFP-dgn fusion protein. To be able to monitor ubiquitin-proteasome activity in living primary cells, complementary DNA constructs coding for a green fluorescent protein (GFP)–dgn fusion protein (GFP–dgn, unstable) and a variant carrying a frameshift mutation (GFP–dgnFS, stable ¹¹) are inserted in lentiviral expression vectors. We prefer this technique over traditional transfection techniques because it guarantees a very high transfection efficiency independent of the cell type or the age of the donor. The difference between fluorescence displayed by the GFP–dgnFS (stable) protein and the destabilized protein (GFP-dgn) in the absence or presence of proteasome inhibitor can be used to estimate ubiquitin-proteasome activity in each particular cell strain. These differences can be monitored by epifluorescence microscopy or can be measured by flow cytometry.     

表达鸡传染性支气管炎病毒JS/95/03株S1蛋白的重组杆状病毒构建

The recombinant baculovirus expressing S1 glycoprotein of nephropathogenic strain JS/95/03 of infectious bronchitis virus was generated by using the Bac-to-Bac baculovirus expression system.The BamH I-Sal Ⅰ fragment containing S1 gene from the recombinant plasmid pMDJS9503S1 was purified and cloned in frame into the baculovirus transposing vector pFASTBAC HTa under the polyhedrin gene promoter.The recombinant transposing plasmid pFASTJS9503S1 was screened and then transformed into Escherichia coli DH10BAC.The resulting recombinant bacmid rBacmidJS9503S1 was transfected into cells of the insect Spodoptera frugiperda(Sf9)and the recombinant baculoviruse rAcJS9503S1 was obtained.The lysates of cells infected with rAcJS9503S1 were analyzed by SDS-PAGE and the expressed product of S1 gene was detected by Western bloting and immunofluorescence assay(IFA).The results showed the recombinant baculovirus was fully capable of expressing S1 glycoprotein of JS/95/03.Maybe owing to the incomplete glycosylation in insect cells,the S1 gene product had a Mr of only 61000.In immunofluorescence test and Western blotting,the expressed product could react with polycolonal antibody against IBV M41 strain,indicating it possessed the antigenic properties specific for native S1 glycoprotein.     

酪氨酸羟化酶和左旋芳香族氨基酸脱羧酶基因的细胞表达及活性检测

由于在帕金森病中合成多巴胺所需的酪氨酸羟化酶(tyrosine hydroxylase,TH)和左旋芳香族氨基酸脱羧酶(aromatic L-amino acid decarboxylase,AADC)活性明显降低,所以补充多巴胺合成酶成为基因治疗帕金森病研究的主要手段。我们分别构建了重组逆转录病毒载体pLHCX／TH及pLNCX2／AADC,通过脂质体介导将带有目的基因的载体分别转到包装细胞PA317中,经筛选得到产病毒的细胞PA317／TH和PA317／AADC,采用免疫组化、原位杂交方法检测目的基因表达;细胞经裂解后进行的酶促反应产物多巴胺以高压液相电化学方法检测证明所克隆的T‘H及AADC基因具有功能活性;这两种基因工程改造细胞可以完成酶促动力学的功能,使L-dopa及多巴胺产生明显增加。本研究为用TH和AADC双基因对帕金森病进行基因治疗提供了一定的依据。