How to calculate the dose of chemotherapy

Body surface area-dosing does not account for the complex processes of cytotoxic drug elimination. This leads to an unpredictable variation in effect. Overdosing is easily recognised but it is possible that unrecognised underdosing is more common and may occur in 30% or more of patients receiving standard regimen. Those patients who are inadvertently underdosed are at risk of a significantly reduced anticancer effect. Using published data, it can be calculated that there is an almost 20% relative reduction in survival for women receiving adjuvant chemotherapy for breast cancer as a result of unrecognised underdosing. Similarly, the cure rate of cisplatin-based chemotherapy for advanced testicular cancer may be reduced by as much as 10%. The inaccuracy of body surface area-dosing is more than an inconvenience and it is important that methods for more accurate dose calculation are determined, based on the known drug elimination processes for cytotoxic chemotherapy. Twelve rules for dose calculation of chemotherapy are given that can be used as a guideline until better dose-calculation methods become available. Consideration should be given to using fixed dose guidelines independent of body surface area and based on drug elimination capability, both as a starting dose and for dose adjustment, which may have accuracy, safety and financial advantages

Predators reduce extinction risk in noisy metapopulations

Background Spatial structure across fragmented landscapes can enhance regional population persistence by promoting local “rescue effects.” In small, vulnerable populations, where chance or random events between individuals may have disproportionately large effects on species interactions, such local processes are particularly important. However, existing theory often only describes the dynamics of metapopulations at regional scales, neglecting the role of multispecies population dynamics within habitat patches. Findings By coupling analysis across spatial scales we quantified the interaction between local scale population regulation, regional dispersal and noise processes in the dynamics of experimental host-parasitoid metapopulations. We find that increasing community complexity increases negative correlation between local population dynamics. A potential mechanism underpinning this finding was explored using a simple population dynamic model. Conclusions Our results suggest a paradox: parasitism, whilst clearly damaging to hosts at the individual level, reduces extinction risk at the population level

Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck:Bayesian probability versus neural network

Purpose: The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least-squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM-NET, and a version of the neural network modified to increase consistency, IVIM-NETmod. Methods: Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient (Formula presented.), perfusion fraction (Formula presented.), and pseudo-diffusion coefficient (Formula presented.)) from each fit method were determined in the tonsils and in the pterygoid muscles. Within-subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. Results: The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of (Formula presented.) in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM-NET, and 11.2% for IVIM-NETmod. However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM-NET were 15% for both (Formula presented.) and (Formula presented.), and 94% for (Formula presented.); for IVIM-NETmod, these values improved to 5%, 9%, and 62%, respectively. Conclusion: Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck

No Benefit from Chronic Lithium Dosing in a Sibling-Matched, Gender Balanced, Investigator-Blinded Trial Using a Standard Mouse Model of Familial ALS

Background: In any animal model of human disease a positive control therapy that demonstrates efficacy in both the animal model and the human disease can validate the application of that animal model to the discovery of new therapeutics. Such a therapy has recently been reported by Fornai et al. using chronic lithium carbonate treatment and showing therapeutic efficacy in both the high-copy SOD1G93A mouse model of familial amyotrophic lateral sclerosis (ALS), and in human ALS patients. Methodology/Principal Findings: Seeking to verify this positive control therapy, we tested chronic lithium dosing in a sibling-matched, gender balanced, investigator-blinded trial using the high-copy (average 23 copies) SOD1G93A mouse (n = 27–28/group). Lithium-treated mice received single daily 36.9 mg/kg i.p. injections from 50 days of age through death. This dose delivered 1 mEq/kg (6.94 mg/kg/day lithium ions). Neurological disease severity score and body weight were determined daily during the dosing period. Age at onset of definitive disease and survival duration were recorded. Summary measures from individual body weight changes and neurological score progression, age at disease onset, and age at death were compared using Kaplan-Meier and Cox proportional hazards analysis. Our study did not show lithium efficacy by any measure. Conclusions/Significance: Rigorous survival study design that includes sibling matching, gender balancing, investigato

Reconstructing the three-dimensional GABAergic microcircuit of the striatum

A system's wiring constrains its dynamics, yet modelling of neural structures often overlooks the specific networks formed by their neurons. We developed an approach for constructing anatomically realistic networks and reconstructed the GABAergic microcircuit formed by the medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) of the adult rat striatum. We grew dendrite and axon models for these neurons and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. The MSN dendrite models predicted that half of all dendritic spines are within 100 mu m of the soma. The constructed networks predict distributions of gap junctions between FSI dendrites, synaptic contacts between MSNs, and synaptic inputs from FSIs to MSNs that are consistent with current estimates. The models predict that to achieve this, FSIs should be at most 1% of the striatal population. They also show that the striatum is sparsely connected: FSI-MSN and MSN-MSN contacts respectively form 7% and 1.7% of all possible connections. The models predict two striking network properties: the dominant GABAergic input to a MSN arises from neurons with somas at the edge of its dendritic field; and FSIs are interconnected on two different spatial scales: locally by gap junctions and distally by synapses. We show that both properties influence striatal dynamics: the most potent inhibition of a MSN arises from a region of striatum at the edge of its dendritic field; and the combination of local gap junction and distal synaptic networks between FSIs sets a robust input-output regime for the MSN population. Our models thus intimately link striatal micro-anatomy to its dynamics, providing a biologically grounded platform for further study

Are mice good models for human neuromuscular disease? Comparing muscle excursions in walking between mice and humans

The mouse is one of the most widely used animal models to study neuromuscular diseases and test new therapeutic strategies. However, findings from successful pre-clinical studies using mouse models frequently fail to translate to humans due to various factors. Differences in muscle function between the two species could be crucial but often have been overlooked. The purpose of this study was to evaluate and compare muscle excursions in walking between mice and humans

Seasonal variations in the diagnosis of childhood cancer in the United States

Seasonal trends in month of diagnosis have been reported for childhood acute lymphoblastic leukaemia (ALL) and non-Hodgkin's lymphoma (NHL). This seasonal variation has been suggested to represent an underlying viral aetiology for these malignancies. Some studies have shown the highest frequency of diagnoses in the summer months, although this has been inconsistent. Data from the Children's Cancer Group and the Pediatric Oncology Group were analysed for seasonal incidence patterns. A total of 20 949 incident cancer cases diagnosed in the USA from 1 January 1989 through 31 December 1991 were available for analyses. Diagnosis-specific malignancies available for evaluation included ALL, acute myeloid leukaemia (AML), Hodgkin's disease, NHL, rhabdomyosarcoma, neuroblastoma, retinoblastoma, osteosarcoma, Wilms' tumour, retinoblastoma, Ewings' sarcoma, central nervous system (CNS) tumours and hepatoblastoma. Overall, there was no statistically significant seasonal variation in the month of diagnosis for all childhood cancers combined. For diagnosis-specific malignancies, there was a statistically significant seasonal variation for ALL (P = 0.01; peak in summer), rhabdomyosarcoma (P = 0.03; spring/summer) and hepatoblastoma (P = 0.01; summer); there was no seasonal variation in the diagnosis of NHL. When cases were restricted to latitudes greater than 40° (‘north’), seasonal patterns were apparent only for ALL and hepatoblastoma. Notably, 33% of hepatoblastoma cases were diagnosed in the summer months. In contrast, for latitudes less than 40° (‘south’), only CNS tumours demonstrated a seasonal pattern (P = 0.002; winter). Although these data provide modest support for a summer peak in the diagnosis of childhood ALL, any underlying biological mechanisms that account for these seasonal patterns are likely complex and in need of more definitive studies. © 1999 Cancer Research Campaig

Amyotrophic Lateral Sclerosis Is Associated with Hypolipidemia at the Presymptomatic Stage in Mice

OBJECTIVE: To demonstrate that hypolipidemia is a typical feature of the mouse model of amyotrophic lateral sclerosis (ALS) and to assess the association between hypolipidemia and disease stage, dietary intake, and sex. METHODS: We compared daily dietary intake, body weight, and serumlipid and glucose levels in ALS mice and wild-type controls at different stages of the disease. FINDINGS: Total cholesterol low-density lipoprotein (LDL) and LDL/high-density lipoprotein (HDL) ratio were significantly lower in ALS mice compared with controls. Subgroup analysis revealed that the incidence of hypolipidemia was significantly greater in male, but not female, ALS mice compared with control mice and that hypolipidemia was present at the presymptomatic stage of the disease. This hypolipidemia can be found without a decrease in the serum levels of other energy sources, such as glucose, in the presymptomatic stage. CONCLUSIONS: Hypolipidemia is present at the presymptomatic stage of the ALS mouse model in the absence of malnutrition, significant neuromuscular degeneration or regeneration, and respiratory difficulty. Our findings suggest that hypolipidemia might be associated with the pathomechanism of ALS and/or lipid-specific metabolism rather than simply an epiphenomenon of neuromuscular degeneration or energy imbalance

The usefulness of growth hormone treatment for psychological status in young adult survivors of childhood leukaemia: an open-label study

-1 SD) were included in the study. A final group of 13 patients (9 males and 4 females), mean age 23.7 ± 2.9 years (range 20 – 29.7) completed a 2-year treatment with GH. IQ and neuropsychological performance were assessed at pre-treatment (T1) and after one (T2) and two (T3) years. ANOVA was performed with assessment at T1, T2 and T3 as repeated measurements factor. Relations between test score changes and changes of IGF-I levels were determined by calculating the Pearson correlation coefficient. Results Scores on the cognitive tests were in the normal range. Verbal short- and long-term memory performance decreased between T1 and T2, and increased between T2 and T3. Performance at T3 was not significantly different from that at T1. Performance for sustained attention improved from T1 to T2 and from T1 to T3. Visual-spatial memory was improved after one year of GH treatment. A significant positive correlation was found for Δ IGF-I (T2-T1) with difference scores of visual-spatial memory (T2-T1 and T3-T1), indicating that IGF-I increase after one year of GH treatment is associated with increase in cognitive-perceptual performance at month 12 and 24. Conclusion Since the level of intellectual functioning of our patient cohort was in the normal range the present finding that GH treatment has negative effects on verbal memory and positive on attention and visual-spatial memory warrants similar studies in other groups of ALL survivors. Also, a lower dose of GH should be determined inducing as much IGF as needed to improve verbal as well as visual cognitive functions. The present findings indicate that more knowledge is needed before GH treatment may be recommended to enhance cognitive functions in ALL survivors

Targeted emission reductions from global super-polluting power plant units

There are more than 30,000 biomass- and fossil-fuel-burning power plants now operating worldwide, reflecting a tremendously diverse infrastructure, which ranges in capacity from less than a megawatt to more than a gigawatt. In 2010, 68.7% of electricity generated globally came from these power plants, compared with 64.2% in 1990. Although the electricity generated by this infrastructure is vital to economic activity worldwide, it also produces more CO2 and air pollutant emissions than infrastructure from any other industrial sector. Here, we assess fuel- and region-specific opportunities for reducing undesirable air pollutant emissions using a newly developed emission dataset at the level of individual generating units. For example, we find that retiring or installing emission control technologies on units representing 0.8% of the global coal-fired power plant capacity could reduce levels of PM2.5 emissions by 7.7–14.2%. In India and China, retiring coal-fired plants representing 1.8% and 0.8% of total capacity can reduce total PM2.5 emissions from coal-fired plants by 13.2% and 16.0%, respectively. Our results therefore suggest that policies targeting a relatively small number of ‘super-polluting’ units could substantially reduce pollutant emissions and thus the related impacts on both human health and global climate