Comment on recent modeling studies of astrocyte-neuron metabolic interactions.

Recent years have seen a surge in mathematical modeling of the various aspects of neuron-astrocyte interactions, and the field of brain energy metabolism is no exception in that regard. Despite the advent of biophysical models in the field, the long-lasting debate on the role of lactate in brain energy metabolism is still unresolved. Quite the contrary, it has been ported to the world of differential equations. Here, we summarize the present state of this discussion from the modeler's point of view and bring some crucial points to the attention of the non-mathematically proficient reader.

Thyroid hormone reduces the loss of axotomized sensory neurons in dorsal root ganglia after sciatic nerve transection in adult rat.

We have shown that a local administration of thyroid hormones (T3) at the level of transected rat sciatic nerve induced a significant increase in the number of regenerated axons. To address the question of whether local administration of T3 rescues the axotomized sensory neurons from death, in the present study we estimated the total number of surviving neurons per dorsal root ganglion (DRG) in three experimental group animals. Forty-five days following rat sciatic nerve transection, the lumbar (L4 and L5) DRG were removed from PBS-control, T3-treated as well as from unoperated rats, and serial sections (1 microm) were cut. The physical dissector method was used to estimate the total number of sensory neurons in the DRGs. Our results revealed that in PBS-control rats transection of sciatic nerve leads to a significant (P < 0.001) decrease in the mean number of sensory neurons (8743.8 +/- 748.6) compared with the number of neurons in nontransected ganglion (mean 13,293.7 +/- 1368.4). However, administration of T3 immediately after sciatic nerve transection rescues a great number of axotomized neurons so that their mean neuron number (12,045.8 +/- 929.8) is not significantly different from the mean number of neurons in the nontransected ganglion. In addition, the volume of ganglia showed a similar tendency. These results suggest that T3 rescues a high number of axotomized sensory neurons from death and allows these cells to grow new axons. We believe that the relative preservation of neurons is important in considering future therapeutic approaches of human peripheral nerve lesion and sensory neuropathy.

Comparison of C-reactive protein and white blood cell count with differential in neonates at risk for septicaemia.

We prospectively compared the diagnostic value of C-reactive protein (CRP) and white blood cell counts for detection of neonatal septicaemia. Sensitivity and specifity in receiver operating characteristics, and positive and negative predictive value of CRP and white blood cell count were compared in 195 critically ill preterm and term newborns clinically suspected of infection. Blood cultures were positive in 33 cases. During the first 3 days after birth CRP elevation (sensitivity 75%, specifity 86%), leukopenia (67%/90%), neutropenia (78%/80%) and immature to total neutrophil count (I/T) ratio (78%/73%) were good diagnostic parameters, as opposed to band forms with absolute count (84%/66%) or percentage (79%/71%), thrombocytopenia (65%/57%) and toxic granulations (44%/94%). Beyond 3 days of age elevated CRP (88%/87%) was the best parameter. Increased total (84%/66%) or percentage band count (79%/71%) were also useful. Leukocytosis (74%/56%), increased neutrophils (67%/65%), I/T ratio (79%/47%), thrombocytopenia (65%/57%) and toxic granulations had a low specifity. The positive predictive value of CRP was 32% before and 37% after 3 days of age, that of leukopenia was 37% in the first 3 days. CONCLUSION: During the first 3 days of life CRP, leukopenia and neutropenia were comparably good tests while after 3 days of life CRP was the best single test in early detection of neonatal septicaemia. Serial CRP estimations confirm the diagnosis, monitor the course of infection and the efficacy of antibiotic treatment.

CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland.

BACKGROUND: Estimates of the decrease in CD4(+) cell counts in untreated patients with human immunodeficiency virus (HIV) infection are important for patient care and public health. We analyzed CD4(+) cell count decreases in the Cape Town AIDS Cohort and the Swiss HIV Cohort Study. METHODS: We used mixed-effects models and joint models that allowed for the correlation between CD4(+) cell count decreases and survival and stratified analyses by the initial cell count (50-199, 200-349, 350-499, and 500-750 cells/microL). Results are presented as the mean decrease in CD4(+) cell count with 95% confidence intervals (CIs) during the first year after the initial CD4(+) cell count. RESULTS: A total of 784 South African (629 nonwhite) and 2030 Swiss (218 nonwhite) patients with HIV infection contributed 13,388 CD4(+) cell counts. Decreases in CD4(+) cell count were steeper in white patients, patients with higher initial CD4(+) cell counts, and older patients. Decreases ranged from a mean of 38 cells/microL (95% CI, 24-54 cells/microL) in nonwhite patients from the Swiss HIV Cohort Study 15-39 years of age with an initial CD4(+) cell count of 200-349 cells/microL to a mean of 210 cells/microL (95% CI, 143-268 cells/microL) in white patients in the Cape Town AIDS Cohort > or =40 years of age with an initial CD4(+) cell count of 500-750 cells/microL. CONCLUSIONS: Among both patients from Switzerland and patients from South Africa, CD4(+) cell count decreases were greater in white patients with HIV infection than they were in nonwhite patients with HIV infection.

Imported Swine Count, July 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, August 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, September 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, October 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, November 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, December 2010

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, January 2011

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, February 2011

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, March 2011

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, April 2011

The imported swine court report monthly by the Department of Agricultural.

Imported Swine Count, May 2011

The imported swine court report monthly by the Department of Agricultural.