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.

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.

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.

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.

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.

Livestock, pathogens, vectors, and their environment: A causal inference-based approach to estimating the pathway-specific effect of livestock on human African trypanosomiasis risk.

Livestock are important reservoirs for many zoonotic diseases, however the effects of livestock on human and environmental health extend well beyond direct disease transmission. In this retrospective ecological cohort study we use pre-existing data and the parametric g-formula, which imputes potential outcomes to quantify mediation, to estimate three hypothesized mechanisms by which livestock can influence human African trypanosomiasis (HAT) risk: the reservoir effect, where infected cattle and pigs are a source of infection to humans; the zooprophylactic effect, where preference for livestock hosts exhibited by the tsetse fly vector of HAT means that their presence protects humans from infection; and the environmental change effect, where livestock keeping activities modify the environment in such a way that habitat suitability for tsetse flies, and in turn human infection risk, is reduced. We conducted this study in four high burden countries: at the point level in Uganda, Malawi, and Democratic Republic of Congo (DRC), and at the county level in South Sudan. Our results indicate cattle and pigs play a reservoir role for the rhodesiense form (rHAT) in Uganda (rate ratio (RR) 1.68, 95% CI 0.84, 2.82 for cattle; RR 2.16, 95% CI 1.18, 3.05 for pigs), however zooprophylaxis outweighs this effect for rHAT in Malawi (RR 0.85, 95% CI 0.68, 1.00 for cattle, RR 0.38, 95% CI 0.21, 0.69 for pigs). For the gambiense form (gHAT) we found evidence that pigs may be a competent reservoir (RR 1.15, 95% CI 0.92, 1.72 in Uganda; RR 1.25, 95% CI 1.11, 1.42 in DRC). Statistical significance was reached for rHAT in Malawi (pigs and cattle) and Uganda (pigs only) and for gHAT in DRC (pigs and cattle). We did not find compelling evidence of an environmental change effect (all effect sizes close to 1).

CTLA4 mRNA is downregulated by miR-155 in regulatory T cells, and reduced blood CTLA4 levels are associated with poor prognosis in metastatic melanoma patients.

Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) is an immune checkpoint expressed in regulatory T (Treg) cells and activated T lymphocytes. Despite its potential as a treatment strategy for melanoma, CTLA-4 inhibition has limited efficacy. Using data from The Cancer Genome Atlas (TCGA) melanoma database and another dataset, we found that decreased CTLA4 mRNA was associated with a poorer prognosis in metastatic melanoma. To investigate further, we measured blood CTLA4 mRNA in 273 whole-blood samples from an Australian cohort and found that it was lower in metastatic melanoma than in healthy controls and associated with worse patient survival. We confirmed these findings using Cox proportional hazards model analysis and another cohort from the US. Fractionated blood analysis revealed that Treg cells were responsible for the downregulated CTLA4 in metastatic melanoma patients, which was confirmed by further analysis of published data showing downregulated CTLA-4 surface protein expression in Treg cells of metastatic melanoma compared to healthy donors. Mechanistically, we found that secretomes from human metastatic melanoma cells downregulate CTLA4 mRNA at the post-transcriptional level through miR-155 while upregulating FOXP3 expression in human Treg cells. Functionally, we demonstrated that CTLA4 expression inhibits the proliferation and suppressive function of human Treg cells. Finally, miR-155 was found to be upregulated in Treg cells from metastatic melanoma patients compared to healthy donors. Our study provides new insights into the underlying mechanisms of reduced CTLA4 expression observed in melanoma patients, demonstrating that post-transcriptional silencing of CTLA4 by miRNA-155 in Treg cells may play a critical role. Since CTLA-4 expression is downregulated in non-responder melanoma patients to anti-PD-1 immunotherapy, targeting miRNA-155 or other factors involved in regulating CTLA4 expression in Treg cells without affecting T cells could be a potential strategy to improve the efficacy of immunotherapy in melanoma. Further research is needed to understand the molecular mechanisms regulating CTLA4 expression in Treg cells and identify potential therapeutic targets for enhancing immune-based therapies.

Does a One Health approach to human African trypanosomiasis control hasten elimination? A stochastic compartmental modeling approach.

BACKGROUND: . In response to large strides in the control of human African trypanosomiasis (HAT), in the early 2000s the WHO set targets for elimination of both the gambiense (gHAT) and rhodesiense (rHAT) forms as a public health (EPHP) problem by 2020, and elimination of gHAT transmisson (EOT) by 2030. While global EPHP targets have been met, and EOT appears within reach, current control strategies may fail to achieve gHAT EOT in the presence of animal reservoirs, the role of which is currently uncertain. Furthermore, rHAT is not targeted for EOT due to the known importance of animal reservoirs for this form. METHODS: . To evaluate the utility of a One Health approach to gHAT and rHAT EOT, we built and parameterized a compartmental stochastic model, using the Institute for Disease Modeling's Compartmental Modeling Software, to six HAT epidemics: the national rHAT epidemics in Uganda and Malawi, the national gHAT epidemics in Uganda and South Sudan, and two separate gHAT epidemics in Democratic Republic of Congo distinguished by dominant vector species. In rHAT foci the reservoir animal sub-model was stratified on four species groups, while in gHAT foci domestic swine were assumed to be the only competent reservoir. The modeled time horizon was 2005-2045, with calibration performed using HAT surveillance data and Optuna. Interventions included insecticide and trypanocide treatment of domestic animal reservoirs at varying coverage levels. RESULTS: . Validation against HAT surveillance data indicates favorable performance overall, with the possible exception of DRC. EOT was not observed in any modeled scenarios for rHAT, however insecticide treatment consistently performed better than trypanocide treatment in terms of rHAT control. EOT was not observed for gHAT at 0% coverage of domestic reservoirs with trypanocides or insecticides, but was observed by 2030 in all test scenarios; again, insecticides demonstrated superior performance to trypanocides. CONCLUSIONS: EOT likely cannot be achieved for rHAT without control of wildlife reservoirs, however insecticide treatment of domestic animals holds promise for improved control. In the presence of domestic animal reservoirs, gHAT EOT may not be achieved under current control strategies.

The effect of livestock density on Trypanosoma brucei gambiense and T. b. rhodesiense: A causal inference-based approach.

Domestic and wild animals are important reservoirs of the rhodesiense form of human African trypanosomiasis (rHAT), however quantification of this effect offers utility for deploying non-medical control activities, and anticipating their success when wildlife are excluded. Further, the uncertain role of animal reservoirs-particularly pigs-threatens elimination of transmission (EOT) targets set for the gambiense form (gHAT). Using a new time series of high-resolution cattle and pig density maps, HAT surveillance data collated by the WHO Atlas of HAT, and methods drawn from causal inference and spatial epidemiology, we conducted a retrospective ecological cohort study in Uganda, Malawi, Democratic Republic of the Congo (DRC) and South Sudan to estimate the effect of cattle and pig density on HAT risk. For rHAT, we found a positive effect for cattle (RR 1.61, 95% CI 0.90, 2.99) and pigs (RR 2.07, 95% CI 1.15, 2.75) in Uganda, and a negative effect for cattle (RR 0.88, 95% CI 0.71, 1.10) and pigs (RR 0.42, 95% CI 0.23, 0.67) in Malawi. For gHAT we found a negative effect for cattle in Uganda (RR 0.88, 95% CI 0.50, 1.77) and South Sudan (RR 0.63, 95% CI 0.54, 0.77) but a positive effect in DRC (1.17, 95% CI 1.04, 1.32). For pigs, we found a positive gHAT effect in both Uganda (RR 2.02, 95% CI 0.87, 3.94) and DRC (RR 1.23, 95% CI 1.10, 1.37), and a negative association in South Sudan (RR 0.66, 95% CI 0.50, 0.98). These effects did not reach significance for the cattle-rHAT effect in Uganda or Malawi, or the cattle-gHAT and pig-gHAT effects in Uganda. While ecological bias may drive the findings in South Sudan, estimated E-values and simulation studies suggest unmeasured confounding and underreporting are unlikely to explain our findings in Malawi, Uganda, and DRC. Our results suggest cattle and pigs may be important reservoirs of rHAT in Uganda but not Malawi, and that pigs-and possibly cattle-may be gHAT reservoirs.

A time-series approach to mapping livestock density using household survey data.

More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo, and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.

Trends in Sociodemographic Disparities in Colorectal Cancer Staging and Survival: A SEER-Medicare Analysis.

INTRODUCTION: Race, ethnicity, and socioeconomic status are known to influence staging and survival in colorectal cancer (CRC). It is unclear how these relationships are affected by geographic factors and changes in insurance coverage for CRC screening. We examined the temporal trends in the association between sociodemographic and geographic factors and staging and survival among Medicare beneficiaries. METHODS: We identified patients 65 years or older with CRC using the 1991-2010 Surveillance, Epidemiology, and End Results-Medicare database and extracted area-level sociogeographic data. We constructed multinomial logistic regression models and the Cox proportional hazards models to assess factors associated with CRC stage and survival in 4 periods with evolving reimbursement and screening practices: (i) 1991-1997, (ii) 1998-June 2001, (iii) July 2001-2005, and (iv) 2006-2010. RESULTS: We observed 327,504 cases and 102,421 CRC deaths. Blacks were 24%-39% more likely to present with distant disease than whites. High-income areas had 7%-12% reduction in distant disease. Compared with whites, blacks had 16%-21% increased mortality, Asians had 32% lower mortality from 1991 to 1997 but only 13% lower mortality from 2006 to 2010, and Hispanics had 20% reduced mortality only from 1991 to 1997. High-education areas had 9%-12% lower mortality, and high-income areas had 5%-6% lower mortality after Medicare began coverage for screening colonoscopy. No consistent temporal trends were observed for the associations between geographic factors and CRC survival. DISCUSSION: Disparities in CRC staging and survival persisted over time for blacks and residents from areas of low socioeconomic status. Over time, staging and survival benefits have decreased for Asians and disappeared for Hispanics.

Attitudes and practice among dermatologists regarding indoor tanning.

The aim of this study was to explore dermatologists' practices and attitudes related to educating and counseling their adolescent patients about indoor tanning. An online survey was carried out with a convenience sample of 100 dermatologists. Findings indicated that the majority of the dermatologists are actively engaged in discussing tanning bed use and sun protection with their adolescent patients. Most expressed positive attitudes toward educating patients on the risks of tanning bed use. Limited time was the most commonly reported barrier for the lack of discussion regarding indoor tanning. Of note, more than half of the dermatologists (65%) had patients suffering from tanning addiction. For tanning-addicted patients, dermatologists can encourage lifestyle changes, the use of sunless tanning products, and referrals when the patient's needs extend beyond the scope of the dermatologist.

'Pain Behavior': What My Pain Treatment Got Wrong.

A haunting experience with untreated pain leads one researcher to demand better education about and treatment for pain.

Diffuse cutaneous breast cancer metastases resembling subcutaneous nodules with no surface changes.

Cutaneous metastases typically occur in only a small minority of breast cancer patients. Clinical appearance can vary, but lesions often present as isolated dermal nodules with superficial discoloration or a change in texture on the chest ipsilateral to the primary breast malignancy. We report the case of a woman with metastatic adenocarcinoma of the breast presenting with diffuse cutaneous nodules with no surface changes. The nodules were almost undetectable clinically and had minimal elevation, making them difficult to detect, especially without palpation. A punch biopsy showed positive cytokeratin immunostaining consistent with the markers for the primary breast cancer. A review of the literature on cutaneous metastases from breast adenocarcinomas also is provided.

Association of Skin Examination Behaviors and Thinner Nodular vs Superficial Spreading Melanoma at Diagnosis.

Importance: Early melanoma detection strategies include skin self-examination (SSE), physician skin examination (PSE), and promotion of patient knowledge about skin cancer. Objective: To investigate the association of SSE, PSE, and patient attitudes with the detection of thinner superficial spreading melanoma (SSM) and nodular melanoma (NM), the latter of which tends to elude early detection. Design, Setting, and Participants: This cross-sectional, questionnaire-based, multicenter study identified patients with newly diagnosed cutaneous melanoma at 4 referral hospital centers in the United States, Greece, and Hungary. Among 920 patients with a primary invasive melanoma, 685 patients with SSM or NM subtype were included. Interventions: A standardized questionnaire was used to record sociodemographic information, SSE and PSE practices, and patient perceptions in the year prior to diagnosis. Main Outcomes and Measures: Data were analyzed according to histologic thickness, with a 2-mm cutoff for thinner SSM and NM. Results: Of 685 participants (mean [SD] age, 55.6 [15.1] years; 318 [46%] female), thinner melanoma was detected in 437 of 538 SSM (81%) and in 40 of 147 NM (27%). Patients who routinely performed SSE were more likely to be diagnosed with thinner SSM (odds ratio [OR], 2.61; 95% CI, 1.14-5.40) but not thinner NM (OR, 2.39; 95% CI, 0.84-6.80). Self-detected clinical warning signs (eg, elevation and onset of pain) were markers of thicker SSM and NM. Whole-body PSE was associated with a 2-fold increase in detection of thinner SSM (OR, 2.25; 95% CI, 1.16-4.35) and thinner NM (OR, 2.67; 95% CI, 1.05-6.82). Patient attitudes and perceptions focusing on increased interest in skin cancer were associated with the detection of thinner NM. Conclusions and Relevance: Our findings underscore the importance of complementary practices by patients and physicians for the early detection of melanoma, including regular whole-body PSE, SSE, and increased patient awareness.

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.