Vibrational spectroscopic study of the copper silicate mineral ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O

Ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O is a mineral named after the Ajo district of Arizona. Raman and infrared spectroscopy were used to characterise the molecular structure of ajoite. The structure of the mineral shows disorder which is reflected in the difficulty of obtaining quality Raman spectra. The Raman spectrum is characterised by a broad spectral profile with a band at 1048 cm-1 assigned to the ν1 (A1g) symmetric stretching vibration. Strong bands at 962, 1015 and 1139 cm-1 are assigned to the ν3 SiO4 antisymmetric stretching vibrations. Multiple ν4 SiO4 vibrational modes indicate strong distortion of the SiO4 tetrahedra. Multiple AlO and CuO stretching bands are observed. Raman spectroscopy and confirmed by infrared spectroscopy clearly shows that hydroxyl units are involved in the ajoite structure. Based upon the infrared spectra, water is involved in the ajoite structure, probably as zeolitic water.

Inhibition of guinea-pig renal [Na + K]-ATPase by normotensive human plasma : effects of a high sodium diet

The effect of plasma taken from normotensive humans, while on a low and high sodium diet, on [Na + K]-ATPase and 3H-ouabain binding was measured in tubules from guinea-pig kidneys. Plasma from the high sodium, compared to the low sodium, diet period: (a) inhibited [Na + K]-ATPase activity; (b) decreased 3H-ouabain affinity for binding sites; (c) increased the number of available 3H-ouabain binding sites; (d) decreased [Na + K]-ATPase turnover (activity/3H-ouabain binding sites). The inhibition of [Na + K]-ATPase suggests an increase in a (possible) natriuretic factor. The decreased affinity of 3H-ouabain binding suggests an endogenous ouabainoid, which may be the natriuretic factor.

Book review: "English for telecoms and information technology" by T. Ricca and M. Duckworth; "English for legal professionals" by A. Frost; "English for the pharmaceutical industry" by M. Buchler, K. Jaehnig, G. Matzig, and T. Weindler; "English for cabin crews" by S. Ellis and L. Lansford; and "English for negotiating" by C. Lafond, S. Vine, and B. Welch.

This review examines five books in the Oxford Business English Express Series, including "English for telecoms and information technology" by T. Ricca and M. Duckworth; "English for legal professionals" by A. Frost; "English for the pharmaceutical industry" by M. Buchler, K. Jaehnig, G. Matzig, and T. Weindler; "English for cabin crews" by S. Ellis and L. Lansford; and "English for negotiating" by C. Lafond, S. Vine, and B. Welch.

Problem solving in the primary school (K-2)

This article focuses on problem solving activities in a first grade classroom in a typical small community and school in Indiana. But, the teacher and the activities in this class were not at all typical of what goes on in most comparable classrooms; and, the issues that will be addressed are relevant and important for students from kindergarten through college. Can children really solve problems that involve concepts (or skills) that they have not yet been taught? Can children really create important mathematical concepts on their own – without a lot of guidance from teachers? What is the relationship between problem solving abilities and the mastery of skills that are widely regarded as being “prerequisites” to such tasks?Can primary school children (whose toolkits of skills are limited) engage productively in authentic simulations of “real life” problem solving situations? Can three-person teams of primary school children really work together collaboratively, and remain intensely engaged, on problem solving activities that require more than an hour to complete? Are the kinds of learning and problem solving experiences that are recommended (for example) in the USA’s Common Core State Curriculum Standards really representative of the kind that even young children encounter beyond school in the 21st century? … This article offers an existence proof showing why our answers to these questions are: Yes. Yes. Yes. Yes. Yes. Yes. And: No. … Even though the evidence we present is only intended to demonstrate what’s possible, not what’s likely to occur under any circumstances, there is no reason to expect that the things that our children accomplished could not be accomplished by average ability children in other schools and classrooms.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

K from zeolite : glasshouse trial for testing K availability to the plants

MesoLite, a zeolite material manufactured by NanoChem Holdings Pty Ltd is made by caustic reaction of kaolin at temperatures between 80-95°C. This material has a moderate surface area (9~12 m2/g) and very high cation exchange capacity (500meq/100g). To measure the availability of K in K-MesoLite to plants, wheat was grown with K-MesoLite or a soluble fertiliser (e.g. KCl) in non-leached pots in a glasshouse. The weights and elemental compositions of the plants were compared after four weeks growth. Plants grown with K-MesoLite were slightly larger than those grown with KCl. The elemental compositions of the plants were similar except for Si, which was significantly higher in the plants grown with K-MesoLite than in those fertilised with KCl. K from K-MesoLite is readily available to plants.

Infrared and Raman spectroscopic characterization of the phosphate mineral leucophosphite - K(Fe3+)2(PO4)2(OH)·2(H2O)

The phosphate mineral leucophosphite K(Fe2)3þ(PO4)2(OH) · 2H2O has been characterized by SEM-EDS, Raman, and infrared spectro- scopic measurements. The mineral is predominantly a K and Fe phosphate with some minor substitution of Al in the Fe3þ site. Raman bands at 994 and 1058 cm-1 are assigned to the symmetric stretching modes of PO3- and HPO2- units. The Raman bands at 1104, 1135, and 1177 cm-1 are assigned to the PO3- and HPO2- antisymmetric stretching modes. Raman and infrared spectra in the 2600–3800 cm-1 region show a complex set of overlapping bands, which may be resolved into the component bands. The Raman bands observed at 3325, 3355, and 3456 cm-1 are attributed to water stretching vibrations, and in the infrared spectrum, bands at 3237, 3317, and 3453 cm-1 are assigned to water stretching bands.

Teaching and learning family and consumer sciences through K-W-L charts

While much of the control and many of the activities found in today’s classrooms have been placed in the hands of the learners and learning has become inquiry-based, there remains a need for teachers to use teaching tools that would facilitate this student-centered teaching process. This article identifies the K-W-L Chart as one such tool and follows a case study of four Kuwaiti ‘Family and Consumer Sciences’ teaching / learning events to evaluate their ability to enhance the learning outcomes of eight students. The research was designed from a qualitative, multi-tiered design approach and was assessed through a constant comparative method of data analysis of interview responses, classroom observations and worksheet-assessments. The results showed that the use of K-W-L Charts influenced the teachers and learners toward a more inquiry-based approach and facilitated a more student-centered and collaborative learning environment, raising the level of interest and the amount of personal input given by the students.

Integrated genomic characterization of endometrial carcinoma

We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.

Book review: "Ideologies of Breast Cancer : Feminist Perspectives" Edited by Laura K. Potts. New York: St. Martin’s Press

Laura K. Potts’s edited collection of research on the meanings of breast cancer includes authors from the United Kingdom, the United States, and Canada whose perspectives draw on literary criticism, sociology, psychology, and cultural studies among others. The research employs various methodological approaches—for example, media analysis (Saywell et al.), autobiographical narratives (Potts), and analysis of social activism (Fishman)—to elucidate the multiple dimensions and diversity of breast cancer experiences. The first of two parts, “Meanings of Breast Cancer,” presents the problematical relationship between biomedicine and women’s constructions of breast cancer knowledge, the sexualized and maternalized breast in the print media about breast cancer, environmental risks to women’s health in the Bay Area of San Francisco, and women’s narratives of breast cancer and situating the self. In part 2, “Discourses of Risk and Breast Cancer,” examination of the discourses of prevention and risks to health are taken up in relation to breast cancer screening, the problem of prophylactic mastectomy for hereditary breast cancer, and environmental activism...

Functional analysis of missense variants in the TRESK (KCNK18) K+ channel

A loss of function mutation in the TRESK K2P potassium channel (KCNK18), has recently been linked with typical familial migraine with aura. We now report the functional characterisation of additional TRESK channel missense variants identified in unrelated patients. Several variants either had no apparent functional effect, or they caused a reduction in channel activity. However, the C110R variant was found to cause a complete loss of TRESK function, yet is present in both sporadic migraine and control cohorts, and no variation in KCNK18 copy number was found. Thus despite the previously identified association between loss of TRESK channel activity and migraine in a large multigenerational pedigree, this finding indicates that a single non-functional TRESK variant is not alone sufficient to cause typical migraine and highlights the genetic complexity of this disorder. Migraine is a common, disabling neurological disorder with a genetic, environmental and in some cases hormonal component. It is characterized by attacks of severe, usually unilateral and throbbing headache, can be accompanied by nausea, vomiting and photophobia and is clinically divided into two main subtypes, migraine with aura (MA) when a migraine is accompanied by transient and reversible focal neurological symptoms and migraine without aura (MO)1. The multifactorial and clinical heterogeneity of the disorder have considerably hindered the identification of common migraine susceptibility genes and most of our current understanding comes from the studies of familial hemiplegic migraine (FHM), a rare monogenic autosomal dominant form of MA2. So far, the three susceptibility genes that have been convincingly identified in FHM families all encode ion channels or transporters: CACNA1A encoding the α1 subunit of the Cav2.1 calcium channel3, SCN1A encoding the Nav1.1 sodium channel4 and ATP1A2 encoding the α2 subunit of the Na+/K+ pump5. It is believed that mutations in these genes may lead to increased efflux of glutamate and potassium in the synapse and thereby cause migraine by rendering the brain more susceptible to cortical spreading depression (CSD)6 which is thought to play a role in initiating a migraine attack7,8. However, these genes have not to date been implicated in common forms of migraine9. Nevertheless, current opinion suggests that typical migraine, like FHM, is also disorder of neuronal excitability, ion homeostasis and neurotransmitter release10,11,12. Mutations in the SLC4A4 gene encoding the sodium-bicarbonate cotransporter NBCe1, have recently been implicated in several different forms of migraine13, and a variety of genes involved in glutamate homeostasis (PGCP, MTDH14 and LRP115) and a cation channel (TRPM8)15 have also recently been implicated in migraine via genome-wide association studies. Ion channels are therefore highly likely to play an important role in the pathogenesis of typical migraine. TRESK (KCNK18), is a member of the two-pore domain (K2P) family of potassium channels involved in the control of cellular electrical excitability16. Regulation of TRESK activity by the calcium-dependent phosphatase calcineurin17, as well as its expression in dorsal root ganglia (DRG)18 and trigeminal ganglia (TG)19,20 has led to a proposed role for this channel in a variety of pain pathways. In a recent study, a frameshift mutation (F139Wfsx24) in TRESK was identified in a large multigenerational pedigree where it co-segregated perfectly with typical MA and a significant genome-wide linkage LOD score of 3.0. Furthermore, functional analysis revealed that this mutation caused a complete loss of TRESK function and that the truncated subunit was also capable of down regulating wild-type channel function. This therefore highlighted KCNK18 as potentially important candidate gene and suggested that TRESK dysfunction might play a possible role in the pathogenesis of familial migraine with visual aura20. Additional screening for KCNK18 mutations in unrelated sporadic migraine and control cohorts also identified a number of other missense variants; R10G, A34V, C110R, S231P and A233V20. The A233V variant was found only in the control cohort, whilst A34V was identified in a single Australian migraine proband for which family samples were not available, but it was not detected in controls. By contrast, the R10G, C110R, and S231P variants were found in both migraineurs and controls in both cohorts. In this study, we have investigated the functional effect of these variants to further probe the potential association of TRESK dysfunction with typical migraine.

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk��� clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Genome-wide association study identifies a possible susceptibility locus for endometrial cancer

Background: Genome-wide association studies (GWAS) have identified more than 100 genetic loci for various cancers. However, only one is for endometrial cancer. Methods: We conducted a three-stage GWAS including 8,492 endometrial cancer cases and 16,596 controls. After analyzing 585,963 single-nucleotide polymorphisms (SNP) in 832 cases and 2,682 controls (stage I) from the Shanghai Endometrial Cancer Genetics Study, we selected the top 106 SNPs for in silico replication among 1,265 cases and 5,190 controls from the Australian/British Endometrial Cancer GWAS (stage II). Nine SNPs showed results consistent in direction with stage I with P < 0.1. These nine SNPs were investigated among 459 cases and 558 controls (stage IIIa) and six SNPs showed a direction of association consistent with stages I and II. These six SNPs, plus two additional SNPs selected on the basis of linkage disequilibrium and P values in stage II, were investigated among 5,936 cases and 8,166 controls from an additional 11 studies (stage IIIb). Results: SNP rs1202524, near the CAPN9 gene on chromosome 1q42.2, showed a consistent association with endometrial cancer risk across all three stages, with ORs of 1.09 [95% confidence interval (CI), 1.03–1.16] for the A/G genotype and 1.17 (95% CI, 1.05–1.30) for the G/G genotype (P = 1.6 × 10−4 in combined analyses of all samples). The association was stronger when limited to the endometrioid subtype, with ORs (95% CI) of 1.11 (1.04–1.18) and 1.21 (1.08–1.35), respectively (P = 2.4 × 10−5). Conclusions: Chromosome 1q42.2 may host an endometrial cancer susceptibility locus. Impact: This study identified a potential genetic locus for endometrial cancer risk

Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.