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Biomedical subjects

S Samuel

Publications and source records attributed to S Samuel.

At least 91 records · Page 5Linked to original sources
PubMedDate not supplied

Non-myeloablative allogeneic stem cell transplantation focusing on immunotherapy of life-threatening malignant and non-malignant diseases.

Allogeneic bone marrow transplantation (BMT) represents an important therapeutic tool for treatment of otherwise incurable malignant and non-malignant diseases. Until recently, myeloablative regimens were considered mandatory for eradication of all undesirable host-derived hematopoietic elements. Our preclinical and ongoing clinical studies indicated that much more effective eradication of host immunohematopoietic system cells could be achieved by adoptive allogeneic cell therapy with donor lymphocyte infusion (DLI) following BMT. Thus, eradication of blood cancer cells, especially in patients with CML can be frequently accomplished despite complete resistance of such tumor cells to maximally tolerated doses of chemoradiotherapy. Our cumulative experience suggested that graft versus leukemia (GVL) effects might be a useful tool for eradication of otherwise resistant tumor cells of host origin. The latter working hypothesis suggested that effective BMT procedures may be accomplished without lethal conditioning of the host, using new well tolerated non-myeloablative regimen, thus possibly minimizing immediate and late side effects related to myeloablative procedures considered until recently mandatory for conditioning of BMT recipients. Recent clinical data that will be presented suggests that safe non-myeloablative stem cell transplantation (NST), with no major toxicity can replace the conventional BMT. Thus, NST may provide an option for cure for a large spectrum of clinical indications in children and elderly individuals without lower or upper age limit, while minimizing procedure-related toxicity and mortality.

Acute Disease↗
PubMedDate not supplied

The concept of identity: developmental origins, phenomenology, clinical relevance, and measurement.

The aim of this paper is a thorough explication of the concept of identity. We have synthesized the scattered psychiatric and psychoanalytic literature on the topic to shed light on the historical origins, development, phenomenology, clinical relevance, and methods of assessing identity. Our review revealed that: (1) The concept of identity has persisted over eight decades. (2) Identity originates in the earliest interplay of the infant's temperament with the mother's attitude, gains structure from primitive introjections, refines itself through later selective identifications, acquires filiation and generational continuity in passage through the Oedipus complex, and arrives at its more or less final shape through synthesis of contradictory identifications and greater individuation during adolescence. It remains subject to further refinements during young adulthood, midlife, and even old age. (3) A cohesive identity comprises a realistic body image, subjective self-sameness, consistent attitudes, temporality, gender, authenticity, and ethnicity. (4) Disturbance of identity suggests psychopathology, with greater identity disturbance being associated with more-severe conditions (e.g., severe personality disorders, multiple personality, psychosis). (5) Clinical and psychometric assessment is therefore relevant and might indicate treatment strategies and outcome expectations. Findings from the literature are elucidated, and areas needing further research are identified.

Adolescent↗
PubMedDate not supplied

Predicting the duration of the first stage of spontaneous labor using a neural network.

To create a neural network that predicts the length of the first stage of term labor. Two hundred patients with gestations > or = 36 weeks, in spontaneous active labor are the study group: 159 for training and 41 for testing; 4 training set patients had second-stage cesarean section for obstructed labor. The network is designed with Brainmaker MacIntosh 1.0 (California Scientific Software). Inputs are uterine activity, estimated fetal weight, position, station, and gestational age; maternal parity, age, height, weight, membrane status, and cervical dilatation. Actual first stages are regressed on those predicted by the network or by a standard partogram set. Differences between actual first stage lengths and those predicted by the neural network or partogram are compared with t-tests; while the proportions of first stages accurately predicted within 1 or 2 h are compared for both methods with chi-square tests. The network trained in 4 h (1388 runs) to a 0.15 tolerance. The network predictions have significantly higher correlation (r = 0.88) than do standard partograms (r = 0.35) with actual first stage durations. Mean differences between predicted and actual first stages are significantly lower for network output than with partograms; these differences increased with first stages exceeding 3 h; 100% of trained network values are within 2 h of actual first stage length. The network performs similarly for a new set of 41 previously unseen labors. This neural network predicts the length of the first stage of spontaneous labor and uses inputs readily available to obstetricians. It outperforms typical partograms for estimating this important feature of normal labor. Future application for intrapartum prognosis could be based on this successful design.

Artificial Intelligence↗