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PubMed1991

[Polypathology and co-morbidity: a dynamic way for describing morbidity in aged patients. Study of 100 patients, aged 80 and over, in a short-stay geriatric internal medicine unit].

Descriptive epidemiology has demonstrated the increase with age of the number of identifiable diseases per subject. However, the clinical relevance of this polypathology varies according to the type of affliction, and all pathologies are not necessarily implicated in all morbid events. This prospective study analyzed the length of hospitalization (mean stay: 17.26 +/- 10.52 days) of 100 subjects at least 80 years old (mean age: 85.2 +/- 4.35 yr). The mean total number of recognized diseases per patients was 4.12 +/- 1.83 (range: 1-10). The mean number of diseases concerned by the hospitalization studied was 3.13 +/- 1.60 (range: 1-9). Dynamic analysis of the morbidity of these patients led to their classification into two groups: a) co-morbid patients with several diseases among which interaction is not possible; and b) polymorbid patients with several diseases able to interact. In a polymorbid patient, a disease event can occur as the result of such an interaction (leading to multiple organ failure) or the evolution of a single entity. The number of diseases concerned by the hospitalization varied significantly according to the different models of morbidity, which reflect the different types of medical activity. The lengths of the hospital stay observed did not seem to be influenced by the morbidity model, thereby indicating the existence of other factors prolonging hospitalization. The data collected supported the validity of this approach to disease in the elderly whose objective is a new description of medical activity in this population.

Age Factors↗

PubMed2002

Patients with brain metastases: hope for recursive partitioning analysis (RPA) class 3.

PURPOSE: The objectives of the present study were (a) to validate the prognostic classification derived from recursive partitioning analysis (RPA) of the Radiation Therapy Oncology Group (RTOG); (b) to identify prognostic factors in class 3; (c) to examine the impact of treatment related variables on the prognosis in class 3. PATIENTS AND METHODS: Nine hundred and sixteen patients with brain metastases had resection and whole brain radiotherapy (WBRT, n = 257) or WBRT alone (n = 659) at our institution from 1985 to 2000. Patients were grouped into RPA classes 1, 2, and 3 (n = 67, 441, and 408, respectively). RESULTS: Median survival of the whole group was 3.4 months. Median survival in classes 1, 2, and 3 was 8.2, 4.9, and 1.8 months, respectively. In class 3, age (<65 years vs. > or =65 years, relative risk (RR) 0.75), status of the primary tumor (controlled vs. uncontrolled, RR 0.86), and the number of brain metastases (single vs. multiple, RR 0.76) were independent prognostic variables. We defined three prognostic subgroups: class 3a (n = 51): age <65 years, controlled primary tumor, single brain metastasis; class 3c (n = 44): age > or =65 years, uncontrolled primary tumor, multiple brain metastases; class 3b (n = 313): all other patients. Median survival in classes 3a, 3b, and 3c was 3.2, 1.9, and 1.2 months, respectively (P < 0.0001). Intra-class comparisons showed that resection followed by WBRT yielded significantly better survival compared with WBRT alone. CONCLUSION: Our results validate the RTOG RPA classification for patients with brain metastases. The variables age, status of the primary, and number of brain metastases allow the division of class 3 into prognostic subgroups. Even class 3 patients may benefit from more aggressive treatment strategies.

Adult↗

PubMedDate not supplied

Attribute clustering for grouping, selection, and classification of gene expression data.

This paper presents an attribute clustering method which is able to group genes based on their interdependence so as to mine meaningful patterns from the gene expression data. It can be used for gene grouping, selection, and classification. The partitioning of a relational table into attribute subgroups allows a small number of attributes within or across the groups to be selected for analysis. By clustering attributes, the search dimension of a data mining algorithm is reduced. The reduction of search dimension is especially important to data mining in gene expression data because such data typically consist of a huge number of genes (attributes) and a small number of gene expression profiles (tuples). Most data mining algorithms are typically developed and optimized to scale to the number of tuples instead of the number of attributes. The situation becomes even worse when the number of attributes overwhelms the number of tuples, in which case, the likelihood of reporting patterns that are actually irrelevant due to chances becomes rather high. It is for the aforementioned reasons that gene grouping and selection are important preprocessing steps for many data mining algorithms to be effective when applied to gene expression data. This paper defines the problem of attribute clustering and introduces a methodology to solving it. Our proposed method groups interdependent attributes into clusters by optimizing a criterion function derived from an information measure that reflects the interdependence between attributes. By applying our algorithm to gene expression data, meaningful clusters of genes are discovered. The grouping of genes based on attribute interdependence within group helps to capture different aspects of gene association patterns in each group. Significant genes selected from each group then contain useful information for gene expression classification and identification. To evaluate the performance of the proposed approach, we applied it to two well-known gene expression data sets and compared our results with those obtained by other methods. Our experiments show that the proposed method is able to find the meaningful clusters of genes. By selecting a subset of genes which have high multiple-interdependence with others within clusters, significant classification information can be obtained. Thus, a small pool of selected genes can be used to build classifiers with very high classification rate. From the pool, gene expressions of different categories can be identified.

Algorithms↗

PubMed1999

Quantitative follow-up of patients with multiple sclerosis using MRI: technical aspects.

A highly reproducible automated procedure for quantitative analysis of serial brain magnetic resonance (MR) images was developed for use in patients with multiple sclerosis (MS). The intracranial cavity (ICC) was identified on standard dual-echo spin-echo brain MR images using a supervised automated procedure. MR images obtained from one MS patient at 24 time points in the course of a 1-year follow-up were aligned with the images of one of the time points. Next, the contents of the ICC in each MR exam were segmented into four tissues, using a self-adaptive statistical algorithm. Misclassifications due to partial voluming were corrected using a combination of morphologic operators and connectivity criteria. Finally, a connectivity detection algorithm was used to separate the tissue classified as lesions into individual entities. Registration, classification of the contents of the ICC, and identification of individual lesions are fully automatic. Only identification of the ICC requires operator interaction. In each MR exam, the program estimated volumes for the ICC, gray matter (GM), white matter (WM), white matter lesions (WML), and cerebrospinal fluid (CSF). The reproducibility of the system was superior to that of supervised segmentation, as evidenced by the coefficient of variation: CSF supervised 45.9% vs. automated 7.7%, GM 16.0% vs. 1.4%, WM 15.7% vs. 1.3%, and WML 39.5% vs 52.0%. Our results demonstrate that this computerized procedure allows routine reproducible quantitative analysis of large serial MRI data sets.

Adult↗

PubMed2026

scSurv: a deep generative model for single-cell survival analysis.

MOTIVATION: Single-cell omics analysis has unveiled the heterogeneity of various cell types within tumors. However, no methodology currently reveals how this heterogeneity influences cancer patient survival at single-cell resolution. Here, we introduce scSurv, combining a Cox proportional hazards model with a deep generative model of single-cell transcriptome, to estimate individual cellular contributions to clinical outcomes. RESULTS: The accuracy of scSurv was validated using both simulated and real datasets. This method identifies cells associated with favorable or adverse prognoses and extracts genes correlated with their contribution levels. In melanoma, scSurv reproduces known prognostic macrophage classifications and facilitates hazard mapping through spatial transcriptomics in renal cell carcinoma. We also identified genes consistently associated with prognosis across multiple cancers and demonstrated the applicability of this method to infectious diseases. scSurv is a novel framework for quantifying the heterogeneity of individual cellular effects on clinical outcomes. AVAILABILITY: The implementation of scSurv is available on GitHub (https://github.com/3254c/scSurv) and Zenodo (https://doi.org/10.5281/zenodo.17793054).

Humans↗

PubMed2001

Prediction of progression of spinal deformity in Duchenne muscular dystrophy: a preliminary report.

STUDY DESIGN: Discriminatory power was statistically estimated for multiple combinations of risk indicators for the progression of spinal deformity in Duchenne muscular dystrophy (DMD). OBJECTIVE: To differentiate DMD cases in which spinal deformity will rapidly and severely progress from those with lesser progression of spinal deformity. SUMMARY OF BACKGROUND DATA: Early surgical intervention using instrumentation has recently been advocated for DMD patients to prevent the progression of spinal deformity. However, early determination of cases needing surgical intervention is difficult because of variations in the severity of the clinical courses of DMD patients. METHODS: Charts and spinal radiographs of 12 DMD patients were reviewed retrospectively. Patterns of progression in spinal deformity were classified into three types according to Oda's classification. Discriminant analysis was conducted to categorize the patients into either a severe progression group (type-1 and type-2 patients) or a less severe progression group (type-3 patients and patients without spinal deformity) on the basis of four predictors: 1) vital capacity at the age of 10 years, 2) the age at which ambulation ceased, 3) curve pattern of spinal scoliosis, and 4) Cobb angles of spinal scoliosis at the age of 10 years. RESULTS: Eleven of the twelve DMD patients showed spinal deformity. Three were classified as type 1, six were classified as type 2, and two were classified as type 3. The remaining patient showed no spinal deformity. Multiple discriminant analysis correctly predicted the severity of the clinical course of 91.7% of the DMD patients. Vital capacity at age 10 was found to be the strongest predictor among the variables. CONCLUSIONS: Through multiple discriminant analysis, the clinical course of spinal deformity in DMD patients was correctly predicted in 92% of subjects. This method would be useful to determine early which DMD cases need surgical intervention for treatment of spinal deformity.

Child↗

PubMed2002

Identifying disease modifying genes in multiple sclerosis.

Evidence is mounting that genetic variation influences not only susceptibility to multiple sclerosis (MS), but also its course and severity. Identification of disease modifying genes, however, poses unique challenges, especially on how to classify the course and outcome of the disease in ways that may be relevant to analysis of biological factors that might be influenced by genes. The power of the statistical approaches to detect small effects of individual genes in complex disorders such as MS is problematic, and approaches to estimate power must be appropriate for the data. Nonetheless, using contemporary schemes of classification, genetic variants that influence disease course have been found; in fact, a small number have been confirmed to influence disease course in two or more independent studies. This review addresses strategies relevant to identification of disease modifying genes in MS, and summarizes and critically evaluates the current state of knowledge in this area.

Apolipoproteins E↗

PubMed1994

The use of conserved cellulase family-specific sequences to clone cellulase homologue cDNAs from Fusarium oxysporum.

Five cDNAs from the cellulolytic fungi Fusarium oxysporum that code for five distinct cellulase homologues have been cloned and sequenced. The cloning strategy exploited the hydrophobic cluster analysis-based cellulase family classification of Henrissat and Bairoch [Biochem. J. 293 (1993) 781-788] to design degenerate oligodeoxyribonucleotides (oligos) that encoded amino-acid sequences conserved in an intra-family, but not inter-family, manner among cellulases from different species. Polymerase chain reaction (PCR) experiments using F. oxysporum genomic DNA primed with these 'family-specific' oligos were used to rapidly generate PCR fragments which were in turn used to probe cDNA libraries. Two distinct cDNAs coding for cellulase C-family homologues and one cDNA each coding for homologues to the B, F and K families, were isolated in this manner. This approach is an example of the power of multiple sequence analysis to generate cross-species, homology-based probes to rapidly clone homologues in a species of interest.

Amino Acid Sequence↗

PubMed1986

Congenital anomalies of the upper limb among the Japanese in Sapporo.

Nine hundred and forty three patients with nine hundred and fifty-five congenital upper limb anomalies are classified according to the Swanson's classification. Relative incidence of each type of anomaly, sex incidence, affected side, associated abnormalities and familial history are analysed. The occurrence of congenital upper limb anomalies is also compared with Chinese and Western studies. The characteristic feature in this series is that the incidence of typical syndactyly is not as high as expected. Two problems of Swanson's classification encountered in this analysis are discussed. One of the problems is the relation between polydactyly, syndactyly and typical cleft hand. The other is the relation between brachysyndactyly, atypical cleft hand and transverse deficiency.

Abnormalities, Multiple↗

PubMed2006

Circulating oxidized low-density lipoprotein is associated with echolucent plaques in the femoral artery independently of hsCRP in 61-year-old men.

OBJECTIVES: The aim of the study was to test the hypothesis that circulating markers of inflammation (high-sensitive C-reactive protein, hsCRP) and oxidative modification of lipids (oxidized low-density lipoprotein, oxLDL) were associated with the occurrence of echolucent rather than echogenic femoral artery plaques in a cross-sectional population based cohort of 513, 61-year-old men. BACKGROUND: The relationships between circulating oxLDL, hsCRP and the occurrence of echolucent plaques in the femoral artery have not previously been investigated. METHODS: The levels of circulating oxLDL and hsCRP were determined in plasma by ELISA. Plaque occurrence, size and echogenicity were measured by B-mode ultrasound in the right femoral artery. Assessment of plaque echogenicity was based on the classification (grades 1-4) proposed by Gray-Weale et al. RESULTS: A higher frequency of echolucent femoral plaques was observed in subjects with the metabolic syndrome and current smokers (p=0.01 and p<0.001, respectively) as well as with increasing levels of oxLDL and hsCRP (p=0.002 and p=0.005, respectively). In a multiple logistic regression analysis oxLDL and current smokers turned out to be independent associated with the presence of echolucent femoral artery plaques. CONCLUSIONS: The results of the present study support our hypothesis that circulating oxLDL is a marker of an unstable echolucent plaque phenotype in the femoral artery in man.

Arteritis↗

PubMedDate not supplied

Prospective analysis of office-based hysteroscopic sterilization.

STUDY OBJECTIVES: To evaluate the efficacy of performing the Essure hysteroscopic sterilization in an office-based setting. DESIGN: Prospective, longitudinal analysis (Canadian Task Force classification II-3). SETTING: University out-patient office. PATIENTS: All patients undergoing permanent sterilization in our outpatient office who opted for hysteroscopic sterilization were included. INTERVENTIONS: Hysteroscopic placement of the Essure device in an office-based setting with only non-steroidal antiinflammatory drugs and paracervical block. MEASUREMENTS AND MAIN RESULTS: Multiple data points were collected on each patient including demographic data, specific procedural information, and 12-week hysterosalpingogram data. Most of our patients were Hispanic and had an average body mass index of 30.3. Average time to perform the procedure was 12.4 minutes, with the steepest improvement in the first 13 cases. Bilateral placement of the device was successful in 98 (96%) of 102 patients. Of these patients 92 have 12-week hysterosalpingography results (6 patients were lost to follow-up), with 90 (98%) showing bilateral tubal occlusion. There were no intraprocedural or postprocedural complications. CONCLUSION: In our institution and in our experience, office-hysteroscopic placement of the Essure device is a feasible and effective approach for permanent sterilization.

Adult↗

PubMed1998

The use of sequence comparison to detect 'identities' in tRNA genes.

We have developed a computational method that detects 'identities' in tRNA genes by using principal component analysis to classify the sequences of bases in tRNA genes into groups of similar sequences and then comparing the distribution of sequences of bases, in order to extract characteristic bases that are conserved within a group but differ between groups. These classification and comparison procedures are applied recursively to classify the sequences into hierarchical groups, so that multiple levels of characteristic sites can be detected. By using this computational method, we were able to detect many characteristic sites in the T and D domains of tRNAs, as well as the characteristic sites that had already been detected experimentally. This suggests that bases not only in the contact regions but also in the elbow regions, which determine the structure and dynamics of the whole tRNA molecule, are important to the tRNA-aminoacyl tRNA synthetase recognition.

Amino Acyl-tRNA Synthetases↗

PubMed2006

SISYPHUS--structural alignments for proteins with non-trivial relationships.

With the increasing amount of structural data, the number of homologous protein structures bearing topological irregularities is steadily growing. These include proteins with circular permutations, segment-swapping, context-dependent folding or chameleon sequences that can adopt alternative secondary structures. Their non-trivial structural relationships are readily identified during expert analysis but their automatic identification using the existing computational tools still remains difficult or impossible. Such non-trivial cases of protein relationships are known to pose a problem to multiple alignment algorithms and to impede comparative modeling studies. They support a new emerging concept of evolutionary changeable protein fold, which creates practical difficulties for the hierarchical classifications of protein structures.To facilitate the understanding of, and to provide a comprehensive annotation of proteins with such non-trivial structural relationships we have created SISYPHUS ([Sigmaomeganuphiomicronzeta]--in Greek crafty), a compendium to the SCOP database. The SISYPHUS database contains a collection of manually curated structural alignments and their inter-relationships. The multiple alignments are constructed for protein structural regions that range from oligomeric biological units, or individual domains to fragments of different size. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations. The database is available from http://sisyphus.mrc-cpe.cam.ac.uk.

Databases, Protein↗

PubMed2002

Small cell lung carcinoma (SCLC): a clinicopathologic study of 100 cases with surgical specimens.

Separation of small cell lung carcinoma (SCLC) from nonsmall cell lung carcinoma (NSCLC) is a critical distinction to be made in the diagnosis of lung cancer. However, the diagnosis of SCLC is most commonly made on small biopsies and cytologic specimens, and practicing pathologists may not be familiar with all its morphologic guises and frequent combination with NSCLC elements, which may be seen in larger specimens. Following the most recent WHO classification of lung tumors and with the hope of identifying prognostic markers, we examined in detail the histology of 100 surgical biopsies or resections with a diagnosis of SCLC from the AFIP and pathology panel of the International Association for the Study of Lung Cancer (IASLC). Multiple clinical and histologic features were studied by Kaplan-Meier analysis. Neuroendocrine architectural patterns, including nested and trabecular growth, with peripheral palisading and rosette formation were common in SCLC. Necrosis and apoptotic debris was prominent in all cases, but crush artifact was infrequent. Cell size in surgical biopsy specimens appears larger than in bronchoscopic biopsy specimens and occasional cells may show prominent nucleoli and vesicular nuclear chromatin, but this does not preclude the diagnosis of SCLC. A high percentage of cases (28%) showed combinations with NSCLC, with large cell carcinoma the most common, followed by adenocarcinoma and squamous cell carcinoma. Because of the frequency of a few scattered large cells in SCLC, we arbitrarily recommend that at least 10% of the tumor show large cell carcinoma before subclassification as combined SC/LC. However, combined SCLC is easily recognized if the additional component consists of other NSCLC subtypes such as adenocarcinoma or squamous cell carcinoma, so no percentage requirement is needed. Stage remained the only predictor of prognosis.

Adult↗

PubMed1999

Molecular pathology of multiple endocrine neoplasia type I: two novel germline mutations and updated classification of mutations affecting MEN1 gene.

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterized by the combined development of tumors in several endocrine glands and other tissues. The MEN1 gene was recently identified and isolated by positional cloning. This gene was screened in two unrelated MEN1 Spanish kindreds (with four affected members and seven asymptomatic members) using single-strand conformation polymorphism, DNA sequencing, and restriction enzyme analysis. Two novel germline mutations were identified: a missense in exon 2 (H139R) and a splice-site in intron 9 (1461-2A>C). These findings allowed us to identify the MEN1 carriers among the seven asymptomatic members analyzed. An updated review of the mutations and polymorphisms found in the analysis of the MEN1 gene is provided. The report of all germline mutations causing MEN1 and easy access to this updated information are both of special diagnostic interest, because this greatly facilitates the task of attributing the disorder to a specific mutation found in a given MEN1 family. This is especially helpful in the critical differentiation of missense mutations from nonsynonymous polymorphisms that fit the pattern of segregation of the disease, but do not cause it.

Adolescent↗

PubMed2003

[The clinical diagnosis of melanoma].

EARLY DIAGNOSIS FOR EFFICIENT MANAGEMENT: The melanoma is a cutaneous tumour of poor prognosis and its incidence is increasing. Some risk factors are now well established ( field, phototype, family history) and its early discovery is clinically possible since the lesions are visible to the eye. When diagnosed early, the prognosis is clearly improved. CLINICAL FORMS OF VARYING PROGNOSIS: Depending on the clinical, histopathological and progressive differences, it is possible to distinguish a Superficial Spreading Melanoma (60 to 70%), nodular melanoma (10 to 15%), Dubreuilh's melanoma (5 to 10%) and acrolentigenous melanoma (5%). Apart from these 4 major clinical forms, there is also the sub-ungual melanoma and the mucosal melanoma. Particular situations may also exist: the discovery of metastasis without identification of cutaneous tumour, a melanoma in a pregnant woman or a child, a familial melanoma or multiple melanomas. THE ELEMENTS OF DIAGNOSIS: The semiological analysis of an often-pigmented lesion of the skin, relying on the ABCDE rule and the notion of rapid progression, is the first stage in the diagnostic approach. It is completed, following complete exeresis, by anatomopathological exploration (Breslow's index, existence of ulceration, signs of regression, Clark's classification, histological type and mitotic activity). Two further elements should also be taken into account: the results of a dermatoscopy and the analysis of the sentinel nodes.

Adult↗

PubMedDate not supplied

A morphologic analysis of the cells of ductal carcinoma of the breast and of adenocarcinoma of the ovary in pleural and abdominal effusions.

The cells in serous effusions from 14 cases of histologically proven ductal adenocarcinoma of the breast and from an equal number of proven adenocarcinomas of the ovary were morphologically analyzed, with quantitative values assigned to various cell parameters. The resulting data were then subjected to stepwise discriminant analysis. The presence of coarse chromatin proved to be the most significant discriminating factor, resulting in a correct classification of 100% of the mammary carcinomas (14 of 14) and 71.4% (10 of 14) of the ovarian carcinomas, for an overall rate of 85.7% correct classifications. When combined with other cell parameters, such as the presence of polygonal cells, multiple nucleoli and an isolated cell arrangement, the accuracy rate increased to 92.9% correct classifications. Ovarian carcinoma was more likely to have coarse chromatin and to occur in three-dimensional cell groups, in contrast to mammary carcinoma, which tended to have fine chromatin and more polygonal cell shapes and to occur more commonly in syncytial cell groups and as isolated cells.

Abdomen↗

PubMed2002

Multiple myeloma.

This update provides new insights into the biology, diagnosis, prognosis, and treatment of multiple myeloma (MM) and its complications. In Section I, Drs. John Shaughnessy, Jr., and Bart Barlogie first correlate global gene microarray expression profiling of patient MM samples with normal plasma cells to provide the basis for a developmental stage-based classification of MM. The powerful clinical utility of these analyses is illustrated in delineating mechanism of drug action, identifying novel therapeutic targets, and providing a molecular analysis not only of the tumor cell, but also of the tumor microenvironment, in MM. In Section II, Dr. Jean-Luc Harousseau reviews the rationale and current results of high dose therapy and autologous stem cell transplantation in MM, including optimal patient selection, prognostic factors, conditioning regimens, sources of stem cells, use of tandem transplantation, and maintenance therapy. He then provides an update on the results of allotransplantation approaches in MM, focusing on proposed methods to reduce toxicity and exploit the graft-versus-MM alloimmune effect by transplantation earlier in the disease course, T cell depletion, and nonmyeloablative transplantation. In Section III, Dr. G. David Roodman provides recent insights into the mechanisms of osteoclast activation, interactions between bone and MM cells, adhesive interactions in MM bone disease, and osteoblast suppression. These recent advances not only provide insights into pathogenesis of MM bone disease, but also form the framework for novel therapeutics. In Section IV, Dr. Kenneth Anderson provides an up-to-date discussion of the role of the bone marrow microenvironment in promoting growth, survival, drug resistance, and migration of MM cells and the signaling cascades mediating these sequelae. These studies provide the framework for evaluation of novel therapeutics targeting the MM cell-host interaction in vivo in animal models and in derived clinical trials.

Animals↗