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Pulse steroids therapy is widely used to treat flare-ups of autoimmune diseases, such as systemic lupus erythematosus. The main assumption is that severe inflammation caused by an autoimmune disease must be aggressively quelled before it causes further damage. We present a series of 9 cases that explore the use of high-dose pulse steroids in hypoxemic respiratory failure. We used high-dose steroids to alter the outcome of some patients, using commonly accepted protocols such as 6 mg of dexamethasone via IV, baricitinib, and tocilizumab. The outcome of each case is discussed. The patients were treated with 500 mg of high-dose methylprednisolone via IV for 3 days, followed by 250 mg via IV for 3 days; followed by 12 or 6 mg of dexamethasone was administered daily by mouth or IV. A retrospective review of patients who received a computerized tomography pulmonary angiogram showed that these patients had organizing pneumonia features. Eight out of nine cases had a favorable outcome.

Objectives: The purpose of this study was to determine the patterns of autonomic nerve activity in congestive heart failure (CHF)., Background: The relationship between autonomic nerve activity and cardiac arrhythmias in CHF is unclear., Methods: We implanted radiotransmitters in 6 dogs for continuous (24/7) simultaneous monitoring of left stellate ganglion nerve activity (SGNA), vagal nerve activity (VNA), and electrocardiography before and after pacing-induced CHF., Results: Congestive heart failure increased both SGNA and VNA. The SGNA but not VNA manifested a circadian variation pattern. There was extensive sinus node fibrosis. We analyzed 2,263 episodes of prolonged (>3 s) sinus pauses (PSP) and 1,420 long (>10 s) episodes of paroxysmal atrial tachycardia (PAT). Most (95.3%) PSP episodes occurred at night, and 56% were preceded by a short burst of SGNA that induced transient sinus tachycardia. Long PAT episodes were typically (83%) induced by simultaneous SGNA and VNA discharge, followed by VNA withdrawal. Premature ventricular contractions and ventricular tachycardia were preceded by elevated SGNA., Conclusions: The reduction of sympathovagal balance at night in ambulatory dogs was due to reduced sympathetic discharge rather than a net increase of vagal discharge. The tachybrady syndrome in CHF might be triggered by an intermittent short burst of SGNA that resulted in tachycardia and sinus node suppression. Simultaneous sympathovagal discharge is a cause of long PAT episodes. These data indicate that there is an association between the specific patterns of autonomic nerve discharges and cardiac arrhythmia during CHF.

A tissue-based biosensor is described for screening chemical compounds that rapidly affect the nervous system. The proposed sensor is an extension of a previous work on cultured hippocampal slices [Biosens. Bioelectron. 16 (2001) 491]. The detection of the chemical compounds is based on a novel quantification method of short-term plasticity (STP) of the CA1 system in acute hippocampal slices, using random electrical impulse sequences as inputs and population spike (PS) amplitudes as outputs. STP is quantified by the first and the second order kernels using a variant of the Volterra modeling approach. This approach is more specific and time-efficient than the conventional paired pulse and fixed frequency train methods [J. Neurosci. Methods 2 (2002) 111]. Describing the functional state of the biosensor, the kernels changed accordingly as chemical compounds were added. The second order kernel was decomposed into nine Laguerre functions. The corresponding Laguerre coefficients along with the first order kernel were used as features for classification purposes. The biosensor was tested using picrotoxin (100 microM), trimethylopropane phosphate (10 microM), tetraethylammonium (4 mM), valproate (5 mM), carbachol (5 mM), DAP5 (25 microM), CNQX (3 microM), and DNQX (0.15, 1.5, 3, 5 and 10 microM). Each chemical compound gave a different feature profile corresponding to its pharmacological class. The first order kernel and the Laguerre coefficients formed the input to an artificial neural network (ANN) comprised of a single layer of perceptrons. The ANN was able to classify each tested compound into its respective class.