Cumulative Lead Dose and Cognitive Function in Adults: A Review of Studies That Measured Both Blood Lead and Bone Lead

OBJECTIVE: We review empirical evidence for the relations of recent and cumulative lead dose with cognitive function in adults. DATA SOURCES: A systematic search of electronic databases resulted in 21 environmental and occupational studies from 1996 to 2006 that examined and compared associations of recent (in blood) and cumulative (in bone) lead doses with neurobehavioral outcomes. DATA EXTRACTION: Data were abstracted after consideration of exclusion criteria and quality assessment, and then compiled into summary tables. CONCLUSIONS: At exposure levels encountered after environmental exposure, associations with bio-markers of cumulative dose (mainly lead in tibia) were stronger and more consistent than associations with blood lead levels. Similarly, in studies of former workers with past occupational lead exposure, associations were also stronger and more consistent with cumulative dose than with recent dose (in blood). In contrast, studies of currently exposed workers generally found associations that were more apparent with blood lead levels; we speculate that the acute effects of high, recent dose may mask the chronic effects of cumulative dose. There is moderate evidence for an association between psychiatric symptoms and lead dose but only at high levels of current occupational lead exposure or with cumulative dose in environmentally exposed adults

The Genomic Signature of Crop-Wild Introgression in Maize

The evolutionary significance of hybridization and subsequent introgression has long been appreciated, but evaluation of the genome-wide effects of these phenomena has only recently become possible. Crop-wild study systems represent ideal opportunities to examine evolution through hybridization. For example, maize and the conspecific wild teosinte Zea mays ssp. mexicana, (hereafter, mexicana) are known to hybridize in the fields of highland Mexico. Despite widespread evidence of gene flow, maize and mexicana maintain distinct morphologies and have done so in sympatry for thousands of years. Neither the genomic extent nor the evolutionary importance of introgression between these taxa is understood. In this study we assessed patterns of genome-wide introgression based on 39,029 single nucleotide polymorphisms genotyped in 189 individuals from nine sympatric maize-mexicana populations and reference allopatric populations. While portions of the maize and mexicana genomes were particularly resistant to introgression (notably near known cross-incompatibility and domestication loci), we detected widespread evidence for introgression in both directions of gene flow. Through further characterization of these regions and preliminary growth chamber experiments, we found evidence suggestive of the incorporation of adaptive mexicana alleles into maize during its expansion to the highlands of central Mexico. In contrast, very little evidence was found for adaptive introgression from maize to mexicana. The methods we have applied here can be replicated widely, and such analyses have the potential to greatly informing our understanding of evolution through introgressive hybridization. Crop species, due to their exceptional genomic resources and frequent histories of spread into sympatry with relatives, should be particularly influential in these studies

Algorithms to predict cerebral malaria in murine models using the SHIRPA protocol

<p>Abstract</p> <p>Background</p> <p><it>Plasmodium berghei </it>ANKA infection in C57Bl/6 mice induces cerebral malaria (CM), which reproduces, to a large extent, the pathological features of human CM. However, experimental CM incidence is variable (50-100%) and the period of incidence may present a range as wide as 6-12 days post-infection. The poor predictability of which and when infected mice will develop CM can make it difficult to determine the causal relationship of early pathological changes and outcome. With the purpose of contributing to solving these problems, algorithms for CM prediction were built.</p> <p>Methods</p> <p>Seventy-eight <it>P. berghei</it>-infected mice were daily evaluated using the primary SHIRPA protocol. Mice were classified as CM+ or CM- according to development of neurological signs on days 6-12 post-infection. Logistic regression was used to build predictive models for CM based on the results of SHIRPA tests and parasitaemia.</p> <p>Results</p> <p>The overall CM incidence was 54% occurring on days 6-10. Some algorithms had a very good performance in predicting CM, with the area under the receiver operator characteristic (_auROC) curve ≥ 80% and positive predictive values (PV+) ≥ 95, and correctly predicted time of death due to CM between 24 and 72 hours before development of the neurological syndrome (_auROC = 77-93%; PV+ = 100% using high cut off values). Inclusion of parasitaemia data slightly improved algorithm performance.</p> <p>Conclusion</p> <p>These algorithms work with data from a simple, inexpensive, reproducible and fast protocol. Most importantly, they can predict CM development very early, estimate time of death, and might be a valuable tool for research using CM murine models.</p

Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Background Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials. Methods We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality). Findings Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5–14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21·4% for NACT versus 15·9% for adjuvant chemotherapy (5·5% increase [95% CI 2·4–8·6]; rate ratio 1·37 [95% CI 1·17–1·61]; p=0·0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38·2% for NACT vs 38·0% for adjuvant chemotherapy; rate ratio 1·02 [95% CI 0·92–1·14]; p=0·66), breast cancer mortality (34·4% vs 33·7%; 1·06 [0·95–1·18]; p=0·31), or death from any cause (40·9% vs 41·2%; 1·04 [0·94–1·15]; p=0·45). Interpretation Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered—eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy

Application of virtual reality (VR) technology for medical practitioners in type and screen (T&S) training

202208 bcwwSelf-fundedPublished24 month

Quantum-inspired algorithms for solving low-rank linear equation systems with logarithmic dependence on the dimension

We present two efficient classical analogues of the quantum matrix inversion algorithm [16] for low-rank matrices. Inspired by recent work of Tang [27], assuming length-square sampling access to input data, we implement the pseudoinverse of a low-rank matrix allowing us to sample from the solution to the problem Ax = b using fast sampling techniques. We construct implicit descriptions of the pseudo-inverse by finding approximate singular value decomposition of A via subsampling, then inverting the singular values. In principle, our approaches can also be used to apply any desired “smooth” function to the singular values. Since many quantum algorithms can be expressed as a singular value transformation problem [15], our results indicate that more low-rank quantum algorithms can be effectively “dequantised” into classical length-square sampling algorithms