22 hours ago · 1. Introduction. Systemic lupus erythematosus (SLE), a complex autoimmune disease that often involves multiple organ systems, is characterized by the production of a large number of autoantibodies, extensive deposition of immune complexes, and abnormalities of the innate and adaptive immune responses. [] At present, the pathogenesis and detailed etiology of … >> Go To The Portal
The transcription factors of hub genes. A red node indicates the hub gene and a gray node indicates the transcription factor. Table 2 Transcription factor analysis of key differentially expressed genes. TFs Genes
In the current study, we also identified a number of TFs that have close interactions with the hub DEGs. Interferon regulatory factor 1 (IRF1) is a member of a family of transcription factors that regulates the expression of interferons. It is believed that the IFN system plays a key role in the pathogenesis of SLE.
Click the Data Fields tab and check the data you want to include on the report. Click OK to close the Patient Report View. When you are prompted to choose a create/merge option, select Create Data File ONLY.
We used the GEO2R tool to identify the differentially expressed genes (DEGs) in SLE-related datasets retrieved from the Gene Expression Omnibus (GEO). In addition, we also identified the biological functions of the DEGs by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis.
By utilizing the WGCNA algorithm, genes with similar co-expression patterns are classified into a set of modules, in which the most central genes could be further identified as hub genes.
In a co-expression network, Maximal Clique Centrality (MCC) algorithm was reported to be the most effective method of finding hub nodes (25). The MCC of each node was calculated by CytoHubba, a plugin in Cytoscape (25). In this study, the genes with the top 10 MCC values were considered as hub genes.
RNA sequencing (RNA-Seq) uses the capabilities of high-throughput sequencing methods to provide insight into the transcriptome of a cell. Compared to previous Sanger sequencing- and microarray-based methods, RNA-Seq provides far higher coverage and greater resolution of the dynamic nature of the transcriptome.
Hub genes were defined as the genes with connectivity (degree) greater than 10 in the genetic interaction network and, incidentally, are the top 10% genes of highest connectivity (see Supplementary Fig. S3 and Supplementary Table S3 for the distribution of connectivities of genes in the genetic interaction network).
In cytoscape, you can use "network analyzer" which will be available as default and run "analyze network". It will calculate all properties of network. Hubs are the nodes with higher (more) degree i.e., nodes with more connections. Just sort the output list by degree and you can identify hub nodes.
RNA-seq can tell us which genes are turned on in a cell, what their level of transcription is, and at what times they are activated or shut off. This allows scientists to understand the biology of a cell more deeply and assess changes that may indicate disease.
For most RNA‐seq studies, the data analyses consist of the following key steps [5, 6]: (1) quality check and preprocessing of raw sequence reads, (2) mapping reads to a reference genome or transcriptome, (3) counting reads mapped to individual genes or transcripts, (4) identification of differential expression (DE) ...
DNA utilizes four bases, adenine (A), guanine (G), cytosine (C), and thymine (T), in its code. RNA also uses four bases. However, instead of using 'T' as DNA does, it uses uracil (U). Therefore, if your DNA sequence is 3' T C G T T C A G T 5', the mRNA sequence would be 5' A G C A A G U C A 3'.
On the clinical side, treatment providers need instruments with which to assess the quality of treatment provision, as well as the progress of their clients during treatment. Their motivation is the same as that among researchers: Such instruments are seen as essential elements in the effort to improve clinical care.
Proximal outcome variables (Rosen and Proctor 1981; panel VII in figure 1) refer to cognitions, attitudes, personality variables, or behaviors that, according to the treatment theory under investigation, should be affected by the treatment provided, and should , in turn, lead to positive ultimate outcomes (e.g., abstinence or reduced alcohol consumption). An Institute of Medicine (1989) panel found that “little research has been devoted to the short–term impact of specific [alcoholism treatment] program components” (p. 159), and suggested that such short–term gains could be studied quite readily. Proximal outcome variables can be assessed at any point between treatment entry and the assessment of ultimate outcomes. When assessed during treatment, proximal outcomes constitute an important method that clinicians can use to assess patients’ treatment progress. For researchers, proximal outcomes, assessed during or after treatment, are key components in treatment process analyses.
The quality of alcohol treatment is determined, not only by the therapeutic techniques applied, but also by the characteristics of individual treatment providers (panel III in figure 1). In particular, this domain of variables refers to within–program variation in provider characteristics (aggregate, program–level staff characteristics are considered in panel II). Gerstein (1991) argued that “the competence, quality, and continuity of individual caregivers are likely to be critical elements in explaining the differential effectiveness of [substance abuse] treatment programs” (p. 139). In the alcohol treatment field, the few studies that have been conducted (e.g., W.R. Miller et al. 1980; Valle 1981; McLellan et al. 1988; Sanchez–Craig et al. 1991; Project MATCH Research Group 1998; for reviews, see Najavits and Weiss 1994; Najavits et al. 2000) indicate that therapist characteristics play an important role in determining clients’ treatment retention and outcomes.
2001#N#Description: This multidimensional instrument assesses five treatment approaches: psychodynamic or interpersonal, cognitive–behavioral, family systems or dynamics, 12–step, and case management. For each of the first four modalities, items assess beliefs underlying the approach, practices appropriate in individual therapy, and practices appropriate in group therapy. Case management is an individual approach, so no group practices items were included. In addition, items were developed to tap general “group techniques” (e.g., “encouraging peer social support”) and “practical counseling” (e.g.,“developing rapport and trust”). The instrument consists of 48 items that assess 14 subscales. Construct validity was supported by the results of a confirmatory factor analysis in which subscale items loaded on the factor they were intended to assess, but not on other factors. Corresponding belief and practice subscales correlated highly, except for case management. Cronbach alphas for all subscales except psychodynamic and family systems beliefs were above 0.50 and most were over 0.70 (Kasarabada et al. 2001, p. 287). The fact that some of the subscales consist of only three items contributed to low internal consistency estimates.
Measure: National Drug and Alcoholism Treatment Unit Survey (NDATUS)#N#Citation: Office of Applied Studies 1991#N#Description: The NDATUS is a brief questionnaire (five pages) that covers (a) the overall organization and structure of programs (ownership, funding sources and levels, organizational setting, capacity in different treatment settings using different treatment modalities, hours of operation, etc.), (b) staffing and staff characteristics, (c) services (e.g., methadone dosages), (d) policies, and (e) clients and client characteristics. The 1989 NDATUS was augmented in 1990 by the Drug Services Research Survey (DSRS) (Office of Applied Studies 1992 a, 1992 b) to obtain additional data in the areas of facility organization and staff, client data, services, and costs and charges. Using data from the 1991 NDATUS, Rodgers and Barnett (2000) found that private, for–profit substance abuse treatment programs tended to be smaller and more likely to provide treatment in only one setting. Public programs and nonprofit programs generally had more treatment staff; Federal and for–profit programs had more psychologists and physicians. In 1992, the NDATUS evolved into the Uniform Facility Data Set (UFDS), sponsored by the Office of Applied Studies.
Ultimate outcomes (panel VIII in figure 1) refer to the end points that the treatment is supposed to effect. All treatment programs for alcohol use disorders attempt to impact drinking behavior, with many seeking to eliminate it entirely and others seeking to limit it to levels that do not cause adverse consequences. Some programs also seek to have a broader impact on patient functioning by effecting improvements in such life areas as employment, social functioning, physical health, and/or psychological functioning (for an in–depth discussion of outcome assessment, see Tonigan’s chapter in this Guide ). Treatment process models may specify different dimensions of treatment that should impact different areas of patients’ functioning.
Click the Data Fields tab and check the data you want to include on the report. Click OK to close the Patient Report View. Click Create/ Merge. When you are prompted to choose a create/merge option, select Create Data File ONLY. Click OK to close the Create/Merge Options. Click View List.
The Patient Report (by Filters) option in Dentrix makes it easy for you to create custom reports and find specific patient data. When you generate reports using this feature, you can specify which information you want to see on the report, so you don’t have to search through information you don’t need to find the information you want.#N#You can use the Patient Report (by Filters) to find information you need that can’t be found in the regular Dentrix reports or to create one report that contains pieces of information that are given on several different reports.#N#To run the Patient Report (by Filters)
This is known as histologic (tissue) examination and is usually the best way to tell if cancer is present. The pathologist may also examine cytologic (cell) material.
The tissue removed during a biopsy or surgery must be cut into thin sections, placed on slides, and stained with dyes before it can be examined under a microscope. Two methods are used to make the tissue firm enough to cut into thin sections: frozen sections and paraffin-embedded (permanent) sections.
For example, the pathology report may include information obtained from immunochemical stains (IHC). IHC uses antibodies to identify specific antigens on the surface of cancer cells. IHC can often be used to: Determine where the cancer started.
All tissue samples are prepared as permanent sections, but sometimes frozen sections are also prepared. Permanent sections are prepared by placing the tissue in fixative (usually formalin) to preserve the tissue, processing it through additional solutions, and then placing it in paraffin wax.
The pathologist sends a pathology report to the doctor within 10 days after the biopsy or surgery is performed. Pathology reports are written in technical medical language. Patients may want to ask their doctors to give them a copy of the pathology report and to explain the report to them. Patients also may wish to keep a copy ...
In most cases, a doctor needs to do a biopsy or surgery to remove cells or tissues for examination under a microscope. Some common ways a biopsy can be done are as follows: A needle is used to withdraw tissue or fluid.
An endoscope (a thin, lighted tube) is used to look at areas inside the body and remove cells or tissues. Surgery is used to remove part of the tumor or the entire tumor. If the entire tumor is removed, typically some normal tissue around the tumor is also removed. Tissue removed during a biopsy is sent to a pathology laboratory, ...
Though ideally we should have a clear diagnosis before starting treatment, such certainty is not always possible. Sometimes this uncertainty can be resolved by using the treatment as the test that confirms the diagnosis.
As illustrated in figure 1 ⇓, a “test of treatment” is one strategy for the final stage of arriving at a diagnosis. It is appropriate when a single diagnosis is highly probable but not certain, when an available treatment works for most patients if the diagnosis is correct, and when there is a measurable short term outcome or surrogate.
As with every diagnostic test, the test of treatment can have both false negative and false positive results. If a test of treatment has been assessed against a diagnostic “gold standard” it is possible to quantify the accuracy of the test (table ⇑ ).
Since tests of treatment can easily lead to an inappropriate diagnosis, assessment of response to treatment should be more rigorous than in treatments where diagnosis is “certain.” A test of treatment has several potentially remediable problems. False positives can arise because of spontaneous remission of the condition or from placebo effects.
This series aims to set out a diagnostic strategy and illustrate its application with a case.