John Case

Bio: John Case is an academic researcher from University UCINF. The author has contributed to research in topics: Computable function & Computational learning theory. The author has an hindex of 33, co-authored 173 publications receiving 5471 citations. Previous affiliations of John Case include Rush University Medical Center & The College of New Jersey.

In vivo cyclooxygenase expression in synovial tissues of patients with rheumatoid arthritis and osteoarthritis and rats with adjuvant and streptococcal cell wall arthritis.

Abstract: Cyclooxygenase (COX), or prostaglandin (PG) H synthase, plays a role in inflammatory diseases, but very limited data exist on the regulation of COX in vivo. We, therefore, studied the in vivo expression of COX in synovia from patients with rheumatoid arthritis (RA) and osteoarthritis (OA), as well as joints of rats with streptococcal cell wall (SCW) and adjuvant arthritis. Extensive and intense intracellular COX immunostaining, which correlated with the extent and intensity of mononuclear cell infiltration, was observed in cells throughout RA synovia. Significantly less or equivocal staining was noted in OA and normal human synovia. Similarly, COX immunostaining was equivocal in the joints of normal and arthritis-resistant F344/N rats. In contrast, high level expression developed rapidly in euthymic female Lewis (LEW/N) rats throughout the hindlimb joints and overlying tissues including skin, preceding or paralleling clinically apparent experimental arthritis. COX was expressed in the joints of athymic LEW.rnu/rnu rats 2-4 d after injection of SCW or adjuvant but was not sustained. Physiological doses of antiinflammatory glucocorticoids, but not progesterone, suppressed both arthritis and COX expression in LEW/N rats. These observations suggest that, in vivo, (a) COX expression is upregulated in inflammatory joint diseases, (b) the level of expression is genetically controlled and is a biochemical correlate of disease severity, (c) sustained high level up-regulation is T cell dependent, and (d) expression is down-regulated by antiinflammatory glucocorticoids.

Nonrandom evolution of end-stage osteoarthritis of the lower limbs

Abstract: Objective Patients with unilateral hip or knee replacements for end-stage osteoarthritis (OA) are at high risk for future progression of OA in other joints of the lower extremities, often requiring additional joint replacements. Although the risks of future surgery in the contralateral cognate joints (i.e., contralateral hip replacement after an initial hip replacement) have been evaluated, the evolution of end-stage hip OA to OA involving the knee joints, and vice versa (i.e., noncognate progression) has not been investigated. Because characterization of OA progression in noncognate joints may shed light on the pathogenesis of multijoint OA, we investigated the pattern of evolution of end-stage lower extremity OA in a large, clinical cohort. Methods Total joint replacement (TJR) was selected as a marker of end-stage OA, and a database comprising all lower extremity TJRs performed at a large referral center between 1981 and 2001 was accessed. Of the 5,894 patients identified, 486 patients with idiopathic OA who underwent hip replacement and 414 who underwent initial knee replacement were analyzed to determine the relative likelihood of subsequent TJRs. Patients with the systemic inflammatory arthropathy, rheumatoid arthritis (RA), were evaluated as a control population because RA progression is not considered to be a primarily mechanically mediated process. Results The contralateral cognate joint was the most common second joint to undergo replacement in both the OA and the RA groups. However, in OA patients for whom the second TJR was in a noncognate joint, that joint was >2-fold more likely to be on the contralateral limb than on the ipsilateral limb (hip to knee P < 0.001; knee to hip P = 0.013). In contrast, among the RA cohort, the evolution was random and no laterality for noncognate TJR was observed at either the hip or the knee (P = 0.782). Conclusion This characterization of end-stage lower extremity OA demonstrates that the disease evolves nonrandomly; after 1 joint is replaced, the contralateral limb is significantly more likely to show progression of OA than is the ipsilateral limb. Thus, OA in 1 weight-bearing joint appears to influence the evolution of OA in other joints. The absence of such laterality in RA suggests that OA progression may be mediated by extrinsic factors such as altered joint loading.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

Abstract: Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Matrix Metalloproteinases: A Review

Abstract: Matrix metalloproteinases (MMPs) are a family of nine or more highly homologous Zn(++)-endopeptidases that collectively cleave most if not all of the constituents of the extracellular matrix. The present review discusses in detail the primary structures and the overlapping yet distinct substrate specificities of MMPs as well as the mode of activation of the unique MMP precursors. The regulation of MMP activity at the transcriptional level and at the extracellular level (precursor activation, inhibition of activated, mature enzymes) is also discussed. A final segment of the review details the current knowledge of the involvement of MMP in specific developmental or pathological conditions, including human periodontal diseases.

Transforming growth factor beta in tissue fibrosis.

Abstract: Progressive fibrosis in the kidney, liver, lung, heart, bone marrow, and skin is both a major cause of suffering and death and an important contributor to the cost of health care. All of this is li...