Differential regulation of G protein-coupled receptor-associated proteins in the caudate and the putamen of cynomolgus macaques following chronic ethanol drinking.

The dorsal striatum is composed of the caudate nucleus and the putamen in human and non-human primates. These two regions receive different cortical projections and are functionally distinct. The caudate is involved in the control of goal-directed behaviors, while the putamen is implicated in habit learning and formation. Previous reports indicate that ethanol differentially influences neurotransmission in these two regions. Because neurotransmitters primarily signal through G protein-coupled receptors (GPCRs) to modulate neuronal activity, the present study aimed to determine whether ethanol had a region-dependent impact on the expression of proteins that are involved in the trafficking and function of GPCRs, including G protein subunits and their effectors, protein kinases, and elements of the cytoskeleton. Western blotting was performed to examine protein levels in the caudate and the putamen of male cynomolgus macaques that self-administered ethanol for 1 year under free access conditions, along with control animals that self-administered an isocaloric sweetened solution under identical operant conditions. Among the 18 proteins studied, we found that the levels of one protein (PKCß) were increased, and 13 proteins (Gαi1/3, Gαi2, Gαo, Gß1γ, PKCα, PKCε, CaMKII, GSK3ß, ß-actin, cofilin, α-tubulin, and tubulin polymerization promoting protein) were reduced in the caudate of alcohol-drinking macaques. However, ethanol did not alter the expression of any proteins examined in the putamen. These observations underscore the unique vulnerability of the caudate nucleus to changes in protein expression induced by chronic ethanol exposure. Whether these alterations are associated with ethanol-induced dysregulation of GPCR function and neurotransmission warrants future investigation.

An introduction to bayesian spatial smoothing methods for disease mapping: modeling county firearm suicide mortality rates.

This article introduces bayesian spatial smoothing models for disease mapping-a specific application of small area estimation where the full universe of data is known-to a wider audience of public health professionals using firearm suicide as a motivating example. Besag, York, and Mollié (BYM) Poisson spatial and space-time smoothing models were fitted to firearm suicide counts for the years 2014-2018. County raw death rates in 2018 ranged from 0 to 24.81 deaths per 10 000 people. However, the highest mortality rate was highly unstable, based on only 2 deaths in a population of approximately 800, and 80.5% of contiguous US counties experienced fewer than 10 firearm suicide deaths and were thus suppressed. Spatially smoothed county firearm suicide mortality estimates ranged from 0.06 to 4.05 deaths per 10 000 people and could be reported for all counties. The space-time smoothing model produced similar estimates with narrower credible intervals as it allowed counties to gain precision from adjacent neighbors and their own counts in adjacent years. bayesian spatial smoothing methods are a useful tool for evaluating spatial health disparities in small geographies where small numbers can result in highly variable rate estimates, and new estimation techniques in R software have made fitting these models more accessible to researchers.

Evaluating the privacy properties of telephone metadata.

Since 2013, a stream of disclosures has prompted reconsideration of surveillance law and policy. One of the most controversial principles, both in the United States and abroad, is that communications metadata receives substantially less protection than communications content. Several nations currently collect telephone metadata in bulk, including on their own citizens. In this paper, we attempt to shed light on the privacy properties of telephone metadata. Using a crowdsourcing methodology, we demonstrate that telephone metadata is densely interconnected, can trivially be reidentified, and can be used to draw sensitive inferences.

Geogenomic Segregation and Temporal Trends of Human Pathogenic Escherichia coli O157:H7, Washington, USA, 2005-20141.

The often-noted and persistent increased incidence of Escherichia coli O157:H7 infections in rural areas is not well understood. We used a cohort of E. coli O157:H7 cases reported in Washington, USA, during 2005-2014, along with phylogenomic characterization of the infecting isolates, to identify geographic segregation of and temporal trends in specific phylogenetic lineages of E. coli O157:H7. Kernel estimation and generalized additive models demonstrated that pathogen lineages were spatially segregated during the period of analysis and identified a focus of segregation spanning multiple, predominantly rural, counties for each of the main clinical lineages, Ib, IIa, and IIb. These results suggest the existence of local reservoirs from which humans are infected. We also noted a secular increase in the proportion of lineage IIa and IIb isolates. Spatial segregation by phylogenetic lineage offers the potential to identify local reservoirs and intervene to prevent continued transmission.

The use of notable protagonists in dermatology clinical cases: A quasi-randomized controlled trial.

BACKGROUND: Educators have attempted several methods to create more entertaining problem-based learning (PBL) experiences and more engaging PBL patients. To this end, our study compared the use of unique, memorable PBL characters with generic, unmemorable characters. METHODS: This prospective quasi-randomized controlled study utilized 476 university students. All subjects read ten medical cases that focused on dermatological illnesses. Cases were identical for everyone except subjects were allocated to have notable protagonists (NP) (i.e. cartoon characters or celebrities) or generic protagonists (GP) as patients in their cases. Surveys and tests were completed immediately, 7-10 days later, and 28-31 days later. RESULTS: There were no significant differences in post-test scores at any point between the groups. The only significant difference with regard to the subjective learning experience was for the entertainment level of the cases. The NP mean was 64.1±24.2, whereas the GP mean was 56.0±24.6 (t[444]=3.52, P=0.0005). The NP group also had a significantly higher proportion of subjects who researched dermatology/medicine topics after reading the cases (10.6% versus 2.7%, χ²(1,N=215)=5.47, P=0.02). CONCLUSIONS: The current study found that cases utilizing NPs, while still preserving the same educational value as cases using GPs, can provide a more entertaining learning experience and stimulate outside learning.

Meta-analysis on the effect of text message reminders for HIV-related compliance.

For the treatment of HIV, compliance in regard to appointment attendance and medication usage is critical. Various methods have been attempted to increased HIV care compliance, and a method that has inspired many published studies is text message reminders. We conducted a meta-analysis of the literature from inception through May 2016 using the following databases: Pubmed, Embase, CINAHL, Web of Science, and Cochrane. Examples of terms used in the search included exploded versions of "HIV, "AIDS", "cell phone", "SMS", "text message", "reminder". After abstract and manuscript review, articles were discussed with co-author and included based on consensus. We excluded qualitative analyses, observational studies without an intervention, and studies without a control or pre-intervention group. We used random-effects models to calculate odds ratios (OR) and standardized mean differences (SMDs) for the text message intervention. Thirty-four unique studies were found and included in the meta-analysis. For the seven articles relating to non-attendance, text message reminders significantly reduced the rates of non-attendance (OR, 0.66; 95% CI, 0.48-0.92; P = .01; I2 = 52%). For the 20 articles on drug adherence, text message reminders significantly increased adherence (SMD, 0.87; 95% CI, 0.06-1.68; P = .04; I2 = 99%). For the 11 articles with physiologic measures (CD4 count or viral load), text message reminders led to significant improvement (SMD, 1.53; 95% CI, 0.52-2.55; P = .003; I2 = 99%). This meta-analysis reveals that text message reminders are a promising intervention that can be used to increase HIV care compliance when logistically feasible. Further study should focus on which populations benefit the most from this intervention, and successful implementers could create an established technological infrastructure for other clinics to adopt when seeking to boost compliance.

Seasonality of acquisition of respiratory bacterial pathogens in young children with cystic fibrosis.

BACKGROUND: Seasonal variations are often observed for respiratory tract infections; however, limited information is available regarding seasonal patterns of acquisition of common cystic fibrosis (CF)-related respiratory pathogens. We previously reported differential seasonal acquisition of Pseudomonas aeruginosa in young children with CF and no such variation for methicillin-susceptible Staphylococcus aureus acquisition. The purpose of this study was to describe and compare the seasonal incidence of acquisition of other respiratory bacterial pathogens in young children with CF. METHODS: We conducted a retrospective study to describe and compare the seasonal incidence of methicillin-resistant Staphylococcus aureus (MRSA), Stenotrophomonas maltophilia, Achromobacter xylosoxidans, and Haemophilus influenzae acquisition in young CF patients residing in the U.S. using the Cystic Fibrosis Foundation National Patient Registry, 2003-2009. Log-linear overdispersed Poisson regression was used to evaluate seasonal acquisition of each of these pathogens. RESULTS: A total of 4552 children met inclusion criteria. During follow-up 910 (20%), 1161 (26%), 228 (5%), and 2148 (47%) children acquired MRSA, S. maltophilia, A. xylosoxidans and H. influenzae, respectively. Compared to winter season, MRSA was less frequently acquired in spring (Incidence Rate Ratio [IRR]: 0.79; 95% Confidence Interval [CI]: 0.65, 0.96) and summer (IRR: 0.69; 95% CI: 0.57, 0.84) seasons. Similarly, a lower rate of A. xylosoxidans acquisition was observed in spring (IRR: 0.59; 95% CI: 0.39, 0.89). For H. influenzae, summer (IRR: 0.88; 95% CI: 0.78, 0.99) and autumn (IRR: 0.78; 95% CI: 0.69, 0.88) seasons were associated with lower acquisition rates compared to winter. No seasonal variation was observed for S. maltophilia acquisition. CONCLUSION: Acquisition of CF-related respiratory pathogens displays seasonal variation in young children with CF, with the highest rate of acquisition for most pathogens occurring in the winter. Investigation of factors underlying these observed associations may contribute to our understanding of the aetiology of these infections and guide future infection control strategies.

Air pollution exposure is associated with MRSA acquisition in young U.S. children with cystic fibrosis.

BACKGROUND: The role of air pollution in increasing susceptibility to respiratory tract infections in the cystic fibrosis (CF) population has not been well described. We recently demonstrated that chronic PM2.5 exposure is associated with an increased risk of initial Pseudomonas aeruginosa acquisition in young children with CF. The purpose of this study was to determine whether PM2.5 exposure is a risk factor for acquisition of other respiratory pathogens in young children with CF. METHODS: We conducted a retrospective study of initial acquisition of methicillin susceptible and methicillin resistant Staphylococcus aureus (MSSA and MRSA), Stenotrophomonas maltophilia and Achromobacter xylosoxidans in U.S. children <6 years of age with CF using the CF Foundation Patient Registry, 2003-2009. Multivariable Weibull regression with interval-censored outcomes was used to evaluate the association of PM2.5 concentration in the year prior to birth and risk of acquisition of each organism. RESULTS: During follow-up 63%, 17%, 24%, and 5% of children acquired MSSA, MRSA, S. maltophilia, and A. xylosoxidans, respectively. A 10 µg/m3 increase in PM2.5 exposure was associated with a 68% increased risk of MRSA acquisition (Hazard Ratio: 1.68; 95% Confidence Interval: 1.24, 2.27). PM2.5 was not associated with acquisition of other respiratory pathogens. CONCLUSIONS: Fine particulate matter is an independent risk factor for initial MRSA acquisition in young children with CF. These results support the increasing evidence that air pollution contributes to pulmonary morbidities in the CF community.

Enforcement Provisions of Indoor Tanning Bans for Minors: An Analysis of the First 6 US States.

Several states have passed legislation banning minors from indoor tanning; however, concern has been raised regarding enforcement. We explored the statutes pertaining to enforcement in the first 6 US states to pass legislation banning minors younger than 18 years from indoor tanning. The findings reflect significant variability in enforcement provisions across the 6 states. Further investigations are needed to determine whether the statutes are successful in curbing indoor tanning among youths and ultimately whether indoor tanning bans among minors help to reduce skin cancer incidence.

Nodular melanoma serendipitously detected by airport full body scanners.

BACKGROUND: Nodular melanoma is the most dangerous form of melanoma and often evades early detection. METHODS: We present a frequently traveling businessman whose nodular melanoma was detected by airport full body scanners. RESULTS: For about 20 flights over 2 months, the airport full body scanners singled out an area on his left lower leg for a pat-down. Dermatologic examination discovered a nodular melanoma in this area, and after surgical excision, the man traveled without incident. CONCLUSION: This case raises the possibility of using full body imaging in the detection of melanomas, especially of the nodular subtype. In its current form, full body scanning would most likely not be sensitive or specific enough to become a recommended screening tool. Nonetheless, for travelers with areas repeatedly singled out by the machines without a known justification, airport scanners could serve as incidental free screening for suspicious nodular lesions that should prompt dermatologist referral.

The impact of indoor tanning legislation: newspaper coverage of the risks of indoor tanning before and after the California indoor tanning ban for minors.

On June 1, 2011, the California Senate passed a bill banning minors from indoor tanning. We aimed to determine whether the bill's passage was associated with longer-term media coverage regarding skin protection and the risks associated with indoor tanning. Articles from 31 English-language California newspapers between June 2010-May 2011 (PRE) and June 2011-May 2012 (POST) were searched using terms related to skin protection. Ninety articles were found for in-depth coding and analysis. There were more skin protection articles in the POST period than in the PRE period (57 vs 33; p < .05). In addition, there were more POST articles mentioning the risks of indoor tanning (33 vs 10; p < .001), and a POST article was more likely to mention the risks (58 vs 30%; p < .05). The higher number of POST articles mentioning the risks persisted throughout all quarters. Therefore, the California indoor tanning ban was associated with increased longer-term news coverage of skin protection and the risks associated with indoor tanning. This finding has potential influence on the many states that are considering comparable legislation.

Differential geographical risk of initial Pseudomonas aeruginosa acquisition in young US children with cystic fibrosis.

Pseudomonas aeruginosa is the sentinel respiratory pathogen in cystic fibrosis patients. We conducted a retrospective study to examine whether state of residence affected risk of P. aeruginosa acquisition among US children under 6 years of age with cystic fibrosis by using data from the Cystic Fibrosis Foundation National Patient Registry, 2003-2009. The outcome was time to first isolation of P. aeruginosa from a respiratory culture. We used a Bayesian hierarchical Weibull regression model with interval-censored outcomes. Spatial random effects, included at the state level and modeled using an intrinsic conditional autoregressive prior, allowed estimation of the residual spatial correlation. The regression portion of the model was adjusted for demographic and disease characteristics potentially affecting P. aeruginosa acquisition. A total of 3,608 children met the inclusion criteria and were followed for an average of 2.1 (standard deviation, 1.6) years. P. aeruginosa was cultured in 1,714 (48%) subjects. There was a moderately elevated spatial residual relative risk. An estimated 95% credible interval for the residual hazard ratio under 1 of the fitted models was 0.64-1.57; the strongest positive association was observed in the Southern states. The fact that risk for P. aeruginosa acquisition displayed spatial dependence suggests that regional factors, such as climate, may play an important role in P. aeruginosa acquisition.

Neighborhood socioeconomic position and tuberculosis transmission: a retrospective cohort study.

BACKGROUND: Current understanding of tuberculosis (TB) genotype clustering in the US is based on individual risk factors. This study sought to identify whether area-based socioeconomic status (SES) was associated with genotypic clustering among culture-confirmed TB cases. METHODS: A retrospective cohort analysis was performed on data collected on persons with incident TB in King County, Washington, 2004-2008. Multilevel models were used to identify the relationship between area-level SES at the block group level and clustering utilizing a socioeconomic position index (SEP). RESULTS: Of 519 patients with a known genotyping result and block group, 212 (41%) of isolates clustered genotypically. Analyses suggested an association between lower area-based SES and increased recent TB transmission, particularly among US-born populations. Models in which community characteristics were measured at the block group level demonstrated that lower area-based SEP was positively associated with genotypic clustering after controlling for individual covariates. However, the trend in higher clustering odds with lower SEP index quartile diminished when additional block-group covariates. CONCLUSIONS: Results stress the need for TB control interventions that take area-based measures into account, with particular focus on poor neighborhoods. Interventions based on area-based characteristics, such as improving case finding strategies, utilizing location-based screening and addressing social inequalities, could reduce recent rates of transmission.

Risk factors for diarrhea hospitalization in Bangladesh, 2000-2008: a case-case study of cholera and shigellosis.

BACKGROUND: Cholera and shigellosis are endemic on the Indian subcontinent. Our objective was to identify cholera-specific risk factors distinct from shigellosis risk factors. METHODS: We conducted a case-case study among hospitalized diarrheal patients, comparing those with cholera and shigellosis in International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) hospitals in Matlab (rural) and Dhaka (urban) between January 1, 2000 and December 31, 2008. RESULTS: Multivariable Poisson regression models revealed that having more than nine years of education, compared to no education, was associated with a 39% (adjusted Risk Ratio [aRR] = 0.61, 95% confidence interval [CI]: 0.40-0.93) decreased risk for cholera hospitalization in Matlab and a 16% (aRR = 0.84, 95% CI: 0.75-0.94) decreased risk in Dhaka. Having a family member with diarrhea in the past seven days increased cholera hospitalization risk by 17% (aRR = 1.17, 95% CI: 1.09-1.26) in Matlab. CONCLUSIONS: Further studies are needed to elucidate the pathway through which education impacts cholera risk in order to create targeted interventions in cholera-endemic areas. Interventions seeking to reduce transmission and facilitate hygienic practices among family members of index cases with diarrhea should be considered, especially in rural cholera endemic settings.

Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part I. Epidemiology, high-risk groups, clinical strategies, and diagnostic technology.

While most cancers have shown both decreased incidence and mortality over the past several decades, the incidence of melanoma has continued to grow, and mortality has only recently stabilized in the United States and in many other countries. Certain populations, such as men >60 years of age and lower socioeconomic status groups, face a greater burden from disease. For any given stage and across all ages, men have shown worse melanoma survival than women, and low socioeconomic status groups have increased levels of mortality. Novel risk factors can help identify populations at greatest risk for melanoma and can aid in targeted early detection. Risk assessment tools have been created to identify high-risk patients based on various factors, and these tools can reduce the number of patients needed to screen for melanoma detection. Diagnostic techniques, such as dermatoscopy and total body photography, and new technologies, such as multispectral imaging, may increase the accuracy and reliability of early melanoma detection.

Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part II. Screening, education, and future directions.

New evidence has accumulated over the past several years that supports improved melanoma outcomes associated with both clinician and patient screening. Population-based and workplace studies conducted in Australia and the Unites States, respectively, have shown decreases in the incidence of thick melanoma and overall melanoma mortality, and a year-long statewide screening program in Germany has shown a nearly 50% reduction in mortality 5 years after the screening ended. Current melanoma screening guidelines in the United States are inconsistent among various organizations, and therefore rates of both physician and patient skin examinations are low. As policymaking organizations update national screening recommendations in the United States, the latest research reviewed in part II of this continuing medical education article should be considered to establish the most effective recommendations. Patient and provider education will be necessary to ensure that appropriate patients receive recommended screening.

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives.

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing healthcare delivery. By harnessing machine learning algorithms, natural language processing, and computer vision, AI enables the analysis of complex medical data. The integration of AI into healthcare systems aims to support clinicians, personalize patient care, and enhance population health, all while addressing the challenges posed by rising costs and limited resources. As a subdivision of computer science, AI focuses on the development of advanced algorithms capable of performing complex tasks that were once reliant on human intelligence. The ultimate goal is to achieve human-level performance with improved efficiency and accuracy in problem-solving and task execution, thereby reducing the need for human intervention. Various industries, including engineering, media/entertainment, finance, and education, have already reaped significant benefits by incorporating AI systems into their operations. Notably, the healthcare sector has witnessed rapid growth in the utilization of AI technology. Nevertheless, there remains untapped potential for AI to truly revolutionize the industry. It is important to note that despite concerns about job displacement, AI in healthcare should not be viewed as a threat to human workers. Instead, AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks. By automating routine and repetitive tasks, AI can alleviate the burden on healthcare professionals, allowing them to dedicate more attention to patient care and meaningful interactions. However, legal and ethical challenges must be addressed when embracing AI technology in medicine, alongside comprehensive public education to ensure widespread acceptance.

The Role of ArtificiaI Intelligence in Brain Tumor Diagnosis: An Evaluation of a Machine Learning Model.

This research study explores of the effectiveness of a machine learning image classification model in the accurate identification of various types of brain tumors. The types of tumors under consideration in this study are gliomas, meningiomas, and pituitary tumors. These are some of the most common types of brain tumors and pose significant challenges in terms of accurate diagnosis and treatment. The machine learning model that is the focus of this study is built on the Google Teachable Machine platform (Alphabet Inc., Mountain View, CA). The Google Teachable Machine is a machine learning image classification platform that is built from Tensorflow, a popular open-source platform for machine learning. The Google Teachable Machine model was specifically evaluated for its ability to differentiate between normal brains and the aforementioned types of tumors in MRI images. MRI images are a common tool in the diagnosis of brain tumors, but the challenge lies in the accurate classification of the tumors. This is where the machine learning model comes into play. The model is trained to recognize patterns in the MRI images that correspond to the different types of tumors. The performance of the machine learning model was assessed using several metrics. These include precision, recall, and F1 score. These metrics were generated from a confusion matrix analysis and performance graphs. A confusion matrix is a table that is often used to describe the performance of a classification model. Precision is a measure of the model's ability to correctly identify positive instances among all instances it identified as positive. Recall, on the other hand, measures the model's ability to correctly identify positive instances among all actual positive instances. The F1 score is a measure that combines precision and recall providing a single metric for model performance. The results of the study were promising. The Google Teachable Machine model demonstrated high performance, with accuracy, precision, recall, and F1 scores ranging between 0.84 and 1.00. This suggests that the model is highly effective in accurately classifying the different types of brain tumors. This study provides insights into the potential of machine learning models in the accurate classification of brain tumors. The findings of this study lay the groundwork for further research in this area and have implications for the diagnosis and treatment of brain tumors. The study also highlights the potential of machine learning in enhancing the field of medical imaging and diagnosis. With the increasing complexity and volume of medical data, machine learning models like the one evaluated in this study could play a crucial role in improving the accuracy and efficiency of diagnoses. Furthermore, the study underscores the importance of continued research and development in this field to further refine these models and overcome any potential limitations or challenges. Overall, the study contributes to the field of medical imaging and machine learning and sets the stage for future research and advancements in this area.

Biomechanical Effects of Seizures on Cerebral Dynamics and Brain Stress.

Epilepsy is one of the most common neurological disorders globally, affecting about 50 million people, with nearly 80% of those affected residing in low- and middle-income countries. It is characterized by recurrent seizures that result from abnormal electrical brain activity, with seizures varying widely in manifestation. The exploration of the biomechanical effects that seizures have on brain dynamics and stress levels is relevant for the development of more effective treatments and protective strategies. This study uses a blend of experimental data and computational simulations to assess the brain's physical response during seizures, particularly focusing on the behavior of cerebrospinal fluid and the resulting mechanical stresses on different brain regions. Notable findings show increases in stress, predominantly in the posterior gyri and brainstem, during seizures and an evidence of brain displacement relative to the skull. These observations suggest a dynamic and complex interaction between the brain and skull, with maximum shear stress regions demonstrating the limited yet essential protective role of the CSF. By providing a deeper understanding of the mechanical changes occurring during seizures, this research supports the goal of advancing diagnostic tools, informing more targeted treatment interventions, and guiding the creation of customized therapeutic strategies to enhance neurological care and protect against the adverse effects of seizures.