Acetylcholinesterase Involvement in Apoptosis

To date, more than 40 different types of cells from primary cultures or cell lines have shown AChE expression during apoptosis and after the induction apoptosis by different stimuli. It has been well-established that increased AChE expression or activity is detected in apoptotic cells after apoptotic stimuli in vitro and in vivo, and AChE could be therefore used as a marker of apoptosis. AChE is not an apoptosis initiator, but the cells in which AChE is overexpressed undergo apoptosis more easily than controls. Interestingly, cells with downregulated levels of AChE are not sensitive to apoptosis induction and AChE deficiency can protect against apoptosis. Some tumor cells do not express AChE, but when AChE is introduced into a tumor cell, the cells cease to proliferate and undergo apoptosis more readily. Therefore, AChE can be classified as a tumor suppressor gene. AChE plays a pivotal role in apoptosome formation, and silencing of the AChE gene prevents caspase-9 activation, with consequent decreased cell viability, nuclear condensation, and poly (adenosine diphosphate-ribose) polymerase cleavage. AChE is translocated into the nucleus, which may be an important event during apoptosis. Several questions still need to be addressed, and further studies that address the non-classical function of AChE in apoptosis are needed

H-Diplo Roundtable XXI-28 on Tworek. News from Germany: the competition to control world communications, 1900-1945

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The Impact of Disability Benefits on Labor Supply: Evidence from the VA's Disability Compensation Program

Combining administrative data from the US Army, Department of Veterans Affairs, and Social Security Administration, we analyze the effect of the VA's Disability Compensation (DC) program on veterans' labor force participation and earnings. We study the 2001 Agent Orange decision, a unique policy change that expanded DC eligibility for Vietnam veterans who served in theater but did not expand eligibility to other veterans of this era, to assess the causal effects of DC enrollment. We estimate that benefits receipt reduced veterans' labor force participation by 18 percentage points, though measured income net of transfer income rose on average.United States. Social Security Administration (grant #10-P-98363-1-05 to the National Bureau of Economic Research as part of the SSA Retirement Research Consortium

Multi-Parameter Aerosol Scattering Sensor

This work relates to the development of sensors that measure specific aerosol properties. These properties are in the form of integrated moment distributions, i.e., total surface area, total mass, etc., or mathematical combinations of these moment distributions. Specifically, the innovation involves two fundamental features: a computational tool to design and optimize such sensors and the embodiment of these sensors in actual practice. The measurement of aerosol properties is a problem of general interest. Applications include, but are not limited to, environmental monitoring, assessment of human respiratory health, fire detection, emission characterization and control, and pollutant monitoring. The objectives for sensor development include increased accuracy and/or dynamic range, the inclusion in a single sensor of the ability to measure multiple aerosol properties, and developing an overall physical package that is rugged, compact, and low in power consumption, so as to enable deployment in harsh or confined field applications, and as distributed sensor networks. Existing instruments for this purpose include scattering photometers, direct-reading mass instruments, Beta absorption devices, differential mobility analyzers, and gravitational samplers. The family of sensors reported here is predicated on the interaction of light and matter; specifically, the scattering of light from distributions of aerosol particles. The particular arrangement of the sensor, e.g. the wavelength(s) of incident radiation, the number and location of optical detectors, etc., can be derived so as to optimize the sensor response to aerosol properties of practical interest. A key feature of the design is the potential embodiment as an extremely compact, integrated microsensor package. This is of fundamental importance, as it enables numerous previously inaccessible applications. The embodiment of these sensors is inherently low maintenance and high reliability by design. The novel and unique features include the underlying computational underpinning that allows the optimization for specific applications, and the physical embodiment that affords the construction of a compact, durable, and reliable integrated package. The advantage appears in the form of increased accuracy relative to existing instruments, and the applications enabled by the physical attributes of the resulting configuratio

Multi-Parameter Scattering Sensor and Methods

Methods, detectors and systems detect particles and/or measure particle properties. According to one embodiment, a detector for detecting particles comprises: a sensor for receiving radiation scattered by an ensemble of particles; and a processor for determining a physical parameter for the detector, or an optimal detection angle or a bound for an optimal detection angle, for measuring at least one moment or integrated moment of the ensemble of particles, the physical parameter, or detection angle, or detection angle bound being determined based on one or more of properties (a) and/or (b) and/or (c) and/or (d) or ranges for one or more of properties (a) and/or (b) and/or (c) and/or (d), wherein (a)-(d) are the following: (a) is a wavelength of light incident on the particles, (b) is a count median diameter or other characteristic size parameter of the particle size distribution, (c) is a standard deviation or other characteristic width parameter of the particle size distribution, and (d) is a refractive index of particles

Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.

BACKGROUND: Prognostic stratification is the cornerstone of management in nonmetastatic prostate cancer (PCa). However, existing prognostic models are inadequate-often using treatment outcomes rather than survival, stratifying by broad heterogeneous groups and using heavily treated cohorts. To address this unmet need, we developed an individualised prognostic model that contextualises PCa-specific mortality (PCSM) against other cause mortality, and estimates the impact of treatment on survival. METHODS AND FINDINGS: Using records from the United Kingdom National Cancer Registration and Analysis Service (NCRAS), data were collated for 10,089 men diagnosed with nonmetastatic PCa between 2000 and 2010 in Eastern England. Median follow-up was 9.8 years with 3,829 deaths (1,202 PCa specific). Totals of 19.8%, 14.1%, 34.6%, and 31.5% of men underwent conservative management, prostatectomy, radiotherapy (RT), and androgen deprivation monotherapy, respectively. A total of 2,546 men diagnosed in Singapore over a similar time period represented an external validation cohort. Data were randomly split 70:30 into model development and validation cohorts. Fifteen-year PCSM and non-PCa mortality (NPCM) were explored using separate multivariable Cox models within a competing risks framework. Fractional polynomials (FPs) were utilised to fit continuous variables and baseline hazards. Model accuracy was assessed by discrimination and calibration using the Harrell C-index and chi-squared goodness of fit, respectively, within both validation cohorts. A multivariable model estimating individualised 10- and 15-year survival outcomes was constructed combining age, prostate-specific antigen (PSA), histological grade, biopsy core involvement, stage, and primary treatment, which were each independent prognostic factors for PCSM, and age and comorbidity, which were prognostic for NPCM. The model demonstrated good discrimination, with a C-index of 0.84 (95% CI: 0.82-0.86) and 0.84 (95% CI: 0.80-0.87) for 15-year PCSM in the UK and Singapore validation cohorts, respectively, comparing favourably to international risk-stratification criteria. Discrimination was maintained for overall mortality, with C-index 0.77 (95% CI: 0.75-0.78) and 0.76 (95% CI: 0.73-0.78). The model was well calibrated with no significant difference between predicted and observed PCa-specific (p = 0.19) or overall deaths (p = 0.43) in the UK cohort. Key study limitations were a relatively small external validation cohort, an inability to account for delayed changes to treatment beyond 12 months, and an absence of tumour-stage subclassifications. CONCLUSIONS: 'PREDICT Prostate' is an individualised multivariable PCa prognostic model built from baseline diagnostic information and the first to our knowledge that models potential treatment benefits on overall survival. Prognostic power is high despite using only routinely collected clinicopathological information.The Urology Foundatio