Background: Osteoarthritis (OA) currently seems
inevitable and unavoidable for a large swath of the
population .its etiology relates to a strong ,but
complex ,non mendelian genetic basis ,combined
with mechanical and metabolic factors that cause
molecular alterations the end results of which
affect the whole joint .Glucosamine and
chondrotin sulfate alone or in combination may be
of benefit to a subgroup of individuals who have
knee pain due to OA.
Glucosamine has been shown to alter cartiage turn
over in patients with OA undergoing physical
training
Aim of the study: To find the validity of
glucosamine chondrotin sulfate in treatment of
grade 1 and 2 OA.
Methods: the sample of 280 patients (418 knee)
were divided in to two groups , group A (132
patient) treated by classical methods by
glucosamine chondrotin sulfate for one year. For
both groups different parameters were used
including pain stiffness effusion crepitus and genu
varum and different radiological findings and we
used MRI for evaluation pre and post treatment
Result: Female/ male ratio was 2.89 the highest
age group was ( 60-69) year regarding the clinical
presentation of patients the commonest clinical
presentation were pain and stiffness and the MRI
finding including bone marrow edema shows good
indicator for response to treatment .
Conclusion: Pain ,stiffness and crepitus were
common presentation of OARelief of pain
andstiffness were related to decrease of effusion
and bone marrow edema which is the result of
using nonsteroidal anti-inflammatory drugs with
glucosamine chondroitin sulfate more than when
non steroidal anti- inflammatory drugs alone.
چکیدهی بحث
به نظر میآید که عالم هستی ، بر مسألهی « حرکت» استوار دارد ، و روح ، همیشه دنبال دگرگونی و تکامل و برتری میگردد. حرکت ، همهی چیزها در عالم إمکان را در بر میگیرد. حرکت در بنیادهای فکر مولانا جای مهمی دارد .اشعار مولانا مقدار زیادی از پویایی و حرکت برخوردارست، و از آنجایی که فعل ، عنصر تکانبخش جمله ، و کانون دلالت است ، ترجیح دادیم - علاوه بر دیگر عنا
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
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