Golgi Apparatus in Airway Secretory Cells

https://openworks.mdanderson.org/sumexp22/1068/thumbnail.jp

Flocculation of Reactive Blue 19 (RB19) using Alum and the Effects of Catalysts Addition

There are a variety of primary coagulants which can be used in a water treatment plant. One of the earliest, and still the most extensively used, is aluminum sulfate, also known as alum. Aluminum Sulfate (Alum) is one of the most commonly used flocculent in waste water treatment processes. Effectiveness of Alum in flocculation process is determined by many factors such as the effluents pH, flocculent dose as well as the use of catalyst to improve efficiency rate of flocculation. Hence special attention to these factors especially the use of catalyst has been brought about by this study. Experiments were carried out using Reactive Blue 19 Dye as the contaminant of waste water and two catalysts namely Calcium Hydroxide (CaOH2) and Poly Aluminum Chloride (PACl) were evaluated. The results obtained proved that indeed after addition of catalysts, removal efficiency rates of Alum can be increased up to 25% using Calcium Hydroxide and up to 35% using Poly Aluminum Chloride compared to Alum alone. The optimum conditions for this study were at pH 5.5 ~7.5, 300 mg/L of Alum 30seconds of rapid mixing time with 300 rpm , 30rpm of mixing rate for 5 minutes and 30 minutes of settling time. Moreover, Alum showed the highest performance under these conditions and using 50 mg/L PACl as catalyst with 98.52% of COD reduction and 90.60% of color reduction. In conclusion, Alum with the support of PACl as catalyst is an effective coagulant, which can reduce the level of COD and Dye Color in Reactive Blue 19 contaminated wastewater

Laser Spectroscopic Studies of the E 1£+ State of the MgO Molecule

The E1Σ+ ‘Rydberg' state of 24Mg16O has been characterized by two-color resonance-enhanced two-photon ionization (R2PI) spectroscopy in the 36 000–40 000 cm−1 region. Several rotationally resolved bands, assigned consistently to 24Mg16O(E1Σ+←X1Σ+) vibronic transitions, have been analyzed. The effective Bv′(v′=0−8) constants determined exhibit an unusual variation with v′. Possible causes of this variation are discussed. Estimated spectroscopic constants for the E1Σ+ state are reported

C-reactive protein mediates the effect of apolipoprotein E on cytomegalovirus infection

http://deepblue.lib.umich.edu/bitstream/2027.42/61299/1/AielloNguyen,C-reactiveproteienmediatestheeffect.pd

Racial Bias Beliefs Related to COVID-19 Among Asian Americans, Native Hawaiians, and Pacific Islanders: Findings From the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS)

Background: During the COVID-19 pandemic, there have been increased reports of racial biases against Asian American and Native Hawaiian and Pacific Islander individuals. However, the extent to which different Asian American and Native Hawaiian and Pacific Islander groups perceive and experience (firsthand or as a witness to such experiences) how COVID-19 has negatively affected people of their race has not received much attention. Objective: This study used data from the COVID-19 Effects on the Mental and Physical Health of Asian Americans and Pacific Islanders Survey Study (COMPASS), a nationwide, multilingual survey, to empirically examine COVID-19-related racial bias beliefs among Asian American and Native Hawaiian and Pacific Islander individuals and the factors associated with these beliefs. Methods: COMPASS participants were Asian American and Native Hawaiian and Pacific Islander adults who were able to speak English, Chinese (Cantonese or Mandarin), Korean, Samoan, or Vietnamese and who resided in the United States during the time of the survey (October 2020 to May 2021). Participants completed the survey on the web, via phone, or in person. The Coronavirus Racial Bias Scale (CRBS) was used to assess COVID-19-related racial bias beliefs toward Asian American and Native Hawaiian and Pacific Islander individuals. Participants were asked to rate the degree to which they agreed with 9 statements on a 5-point Likert scale (ie, 1=strongly disagree to 5=strongly agree). Multivariable linear regression was used to examine the associations between demographic, health, and COVID-19-related characteristics and perceived racial bias. Results: A total of 5068 participants completed the survey (mean age 45.4, SD 16.4 years; range 18-97 years). Overall, 73.97% (3749/5068) agreed or strongly agreed with ≥1 COVID-19-related racial bias belief in the past 6 months (during the COVID-19 pandemic). Across the 9 racial bias beliefs, participants scored an average of 2.59 (SD 0.96, range 1-5). Adjusted analyses revealed that compared with Asian Indians, those who were ethnic Chinese, Filipino, Hmong, Japanese, Korean, Vietnamese, and other or multicultural had significantly higher mean CRBS scores, whereas no significant differences were found among Native Hawaiian and Pacific Islander individuals. Nonheterosexual participants had statistically significant and higher mean CRBS scores than heterosexual participants. Compared with participants aged ≥60 years, those who were younger (aged \u3c30, 30-39, 40-49, and 50-59 years) had significantly higher mean CRBS scores. US-born participants had significantly higher mean CRBS scores than foreign-born participants, whereas those with limited English proficiency (relative to those reporting no limitation) had lower mean CRBS scores. Conclusions: Many COMPASS participants reported racial bias beliefs because of the COVID-19 pandemic. Relevant sociodemographic contexts and pre-existing and COVID-19-specific factors across individual, community, and society levels were associated with the perceived racial bias of being Asian during the pandemic. The findings underscore the importance of addressing the burden of racial bias on Asian American and Native Hawaiian and Pacific Islander communities among other COVID-19-related sequelae

Fragmentation branching ratios of highly excited hydrocarbon molecules CnH and their cations CnH+ (n<4)

We have measured fragmentation branching ratios of neutral CnH and CnH+ cations produced in high velocity (4.5 a.u) collisions between incident CnH+ cations and helium atoms. Electron capture gives rise to excited neutral species CnH and electronic excitation to excited cations CnH+. Thanks to a dedicated set-up, based on coincident detection of all fragments, the dissociation of the neutral and cationic parents were recorded separately and in a complete way. For the fragmentation of CnH, the H-loss channel is found to be dominant, as already observed by other authors. By contrast, the H-loss and C-loss channels equally dominate the two-fragment break up of CnH+ species. For these cations, we provide the first fragmentation data (n > 2). Results are also discussed in the context of astrochemistry

The state of ambient air quality in Pakistan—a review

Background and purpose: Pakistan, during the last decade, has seen an extensive escalation in population growth, urbanization, and industrialization, together with a great increase in motorization and energy use. As a result, a substantial rise has taken place in the types and number of emission sources of various air pollutants. However, due to the lack of air quality management capabilities, the country is suffering from deterioration of air quality. Evidence from various governmental organizations and international bodies has indicated that air pollution is a significant risk to the environment, quality of life, and health of the population. The Government has taken positive steps toward air quality management in the form of the Pakistan Clean Air Program and has recently established a small number of continuous monitoring stations. However, ambient air quality standards have not yet been established. This paper reviews the data being available on the criteria air pollutants: particulate matter (PM), sulfur dioxide, ozone, carbon monoxide, nitrogen dioxide, and lead. Methods: Air pollution studies in Pakistan published in both scientific journals and by the Government have been reviewed and the reported concentrations of PM, SO2, O3, CO, NO2, and Pb collated. A comparison of the levels of these air pollutants with the World Health Organization air quality guidelines was carried out. Results: Particulate matter was the most serious air pollutant in the country. NO2 has emerged as the second high-risk pollutant. The reported levels of PM, SO2, CO, NO2, and Pb were many times higher than the World Health Organization air quality guidelines. Only O3 concentrations were below the guidelines. Conclusions: The current state of air quality calls for immediate action to tackle the poor air quality. The establishment of ambient air quality standards, an extension of the continuous monitoring sites, and the development of emission control strategies are essential. © Springer-Verlag 2009

An approach to addressing governance from a health system framework perspective

As countries strive to strengthen their health systems in resource constrained contexts, policy makers need to know how best to improve the performance of their health systems. To aid these decisions, health system stewards should have a good understanding of how health systems operate in order to govern them appropriately. While a number of frameworks for assessing governance in the health sector have been proposed, their application is often hindered by unrealistic indicators or they are overly complex resulting in limited empirical work on governance in health systems. This paper reviews contemporary health sector frameworks which have focused on defining and developing indicators to assess governance in the health sector. Based on these, we propose a simplified approach to look at governance within a common health system framework which encourages stewards to take a systematic perspective when assessing governance. Although systems thinking is not unique to health, examples of its application within health systems has been limited. We also provide an example of how this approach could be applied to illuminate areas of governance weaknesses which are potentially addressable by targeted interventions and policies. This approach is built largely on prior literature, but is original in that it is problem-driven and promotes an outward application taking into consideration the major health system building blocks at various levels in order to ensure a more complete assessment of a governance issue rather than a simple input-output approach. Based on an assessment of contemporary literature we propose a practical approach which we believe will facilitate a more comprehensive assessment of governance in health systems leading to the development of governance interventions to strengthen system performance and improve health as a basic human right

Identifying patients with diabetes and the earliest date of diagnosis in real time: an electronic health record case-finding algorithm

BACKGROUND: Effective population management of patients with diabetes requires timely recognition. Current case-finding algorithms can accurately detect patients with diabetes, but lack real-time identification. We sought to develop and validate an automated, real-time diabetes case-finding algorithm to identify patients with diabetes at the earliest possible date. METHODS: The source population included 160,872 unique patients from a large public hospital system between January 2009 and April 2011. A diabetes case-finding algorithm was iteratively derived using chart review and subsequently validated (n = 343) in a stratified random sample of patients, using data extracted from the electronic health records (EHR). A point-based algorithm using encounter diagnoses, clinical history, pharmacy data, and laboratory results was used to identify diabetes cases. The date when accumulated points reached a specified threshold equated to the diagnosis date. Physician chart review served as the gold standard. RESULTS: The electronic model had a sensitivity of 97%, specificity of 90%, positive predictive value of 90%, and negative predictive value of 96% for the identification of patients with diabetes. The kappa score for agreement between the model and physician for the diagnosis date allowing for a 3-month delay was 0.97, where 78.4% of cases had exact agreement on the precise date. CONCLUSIONS: A diabetes case-finding algorithm using data exclusively extracted from a comprehensive EHR can accurately identify patients with diabetes at the earliest possible date within a healthcare system. The real-time capability may enable proactive disease management