A mixed methods evaluation of patient perspectives on the implementation of an electronic health record-integrated patient-reported symptom and needs monitoring program in cancer care.

BACKGROUND: As cancer centers have increased focus on patient-centered, evidenced-based care, implementing efficient programs that facilitate effective patient-clinician communication remains critical. We implemented an electronic health record-integrated patient-reported symptom and needs monitoring program ('cPRO' for cancer patient-reported outcomes). To aid evaluation of cPRO implementation, we asked patients receiving care in one of three geographical regions of an academic healthcare system about their experiences. METHODS: Using a sequential mixed-methods approach, we collected feedback in two waves. Wave 1 included virtual focus groups and interviews with patients who had completed cPRO. In Wave 2, we administered a structured survey to systematically examine Wave 1 themes. All participants had a diagnosed malignancy and received at least 2 invitations to complete cPRO. We used rapid and traditional qualitative methods to analyze Wave 1 data and focused on identifying facilitators and barriers to cPRO implementation. Wave 2 data were analyzed descriptively. RESULTS: Participants (n = 180) were on average 62.9 years old; were majority female, White, non-Hispanic, and married; and represented various cancer types and phases of treatment. Wave 1 participants (n = 37) identified facilitators, including cPRO's perceived value and favorable usability, and barriers, including confusion about cPRO's purpose and various considerations for responding. High levels of clinician engagement with, and patient education on, cPRO were described as facilitators while low levels were described as barriers. Wave 2 (n = 143) data demonstrated high endorsement rates of cPRO's usability on domains such as navigability (91.6%), comprehensibility (98.7%), and relevance (82.4%). Wave 2 data also indicated low rates of understanding cPRO's purpose (56.7%), education from care teams about cPRO (22.5%), and discussing results of cPRO with care teams (16.3%). CONCLUSIONS: While patients reported high value and ease of use when completing cPRO, they also reported areas of confusion, emphasizing the importance of patient education on the purpose and use of cPRO and clinician engagement to sustain participation. These results guided successful implementation changes and will inform future improvements.

Let's talk about sex: Mechanisms of neural sexual differentiation in Bilateria.

In multicellular organisms, sexed gonads have evolved that facilitate release of sperm versus eggs, and bilaterian animals purposefully combine their gametes via mating behaviors. Distinct neural circuits have evolved that control these physically different mating events for animals producing eggs from ovaries versus sperm from testis. In this review, we will describe the developmental mechanisms that sexually differentiate neural circuits across three major clades of bilaterian animals-Ecdysozoa, Deuterosomia, and Lophotrochozoa. While many of the mechanisms inducing somatic and neuronal sex differentiation across these diverse organisms are clade-specific rather than evolutionarily conserved, we develop a common framework for considering the developmental logic of these events and the types of neuronal differences that produce sex-differentiated behaviors. This article is categorized under: Congenital Diseases > Stem Cells and Development Neurological Diseases > Stem Cells and Development.

A spiking neural network with continuous local learning for robust online brain machine interface.

Objective.Spiking neural networks (SNNs) are powerful tools that are well suited for brain machine interfaces (BMI) due to their similarity to biological neural systems and computational efficiency. They have shown comparable accuracy to state-of-the-art methods, but current training methods require large amounts of memory, and they cannot be trained on a continuous input stream without pausing periodically to perform backpropagation. An ideal BMI should be capable training continuously without interruption to minimize disruption to the user and adapt to changing neural environments.Approach.We propose a continuous SNN weight update algorithm that can be trained to perform regression learning with no need for storing past spiking events in memory. As a result, the amount of memory needed for training is constant regardless of the input duration. We evaluate the accuracy of the network on recordings of neural data taken from the premotor cortex of a primate performing reaching tasks. Additionally, we evaluate the SNN in a simulated closed loop environment and observe its ability to adapt to sudden changes in the input neural structure.Main results.The continuous learning SNN achieves the same peak correlation (ρ=0.7) as existing SNN training methods when trained offline on real neural data while reducing the total memory usage by 92%. Additionally, it matches state-of-the-art accuracy in a closed loop environment, demonstrates adaptability when subjected to multiple types of neural input disruptions, and is capable of being trained online without any prior offline training.Significance.This work presents a neural decoding algorithm that can be trained rapidly in a closed loop setting. The algorithm increases the speed of acclimating a new user to the system and also can adapt to sudden changes in neural behavior with minimal disruption to the user.

A Novel, Possibly Pathogenic, COL4A1 Gene Variant (c.3698G>A) in a Family With Childhood Epilepsy and Leukoencephalopathy.

This case report explores the clinical presentation and genetic findings of a 44-year-old male with a history of pediatric epilepsy. The patient's daughter, recently diagnosed with autism, underwent genetic testing, revealing a variant of uncertain significance (VUS) in the type IV collagen alpha 1 (COL4A1) gene. The male patient reported a spectrum of neurological symptoms, including chronic migraines, exertional weakness, and sensory disturbances. Detailed neurological examination findings were within normal limits, but a brain MRI unveiled confluent deep white matter T2/fluid-attenuated inversion recovery (FLAIR) signal abnormalities with basal ganglia involvement. Genetic testing identified a novel COL4A1 gene variant, c.3698G>A (p.Gly1233Glu), in the patient, which was also carried by his daughter. The nature and clinical implications of this VUS in the context of the family's clinical history are discussed in this case report, emphasizing the potential significance of this genetic variant in understanding the etiology of the patient's neurologic symptoms. Further research and correlation with clinical findings are needed to elucidate whether this is a pathogenic variant.

Breast Cancer Phenotypes in Africa: A Scoping Review and Meta-Analysis.

PURPOSE: Africans have been associated with more aggressive forms of breast cancer (BC). However, there is a lack of data regarding the incidence and distribution of different subtypes on the basis of phenotypic classification. This scoping review and meta-analysis was undertaken to determine the distribution pattern of BC phenotypes (luminal, human epidermal growth factor receptor 2 [HER2]+, and triple-negative breast cancer [TNBC]) across the African region. METHODS: Four online databases (PubMed, Scopus, ProQuest, and EBSCOhost) were accessed to identify studies published between 2000 and 2022 reporting the representation of receptor status (estrogen receptor, progesterone receptor, and HER2) in African patients with BC. Furthermore, the meta-analysis was carried out using a random-effects model and pooled using the inverse variance method and logit transformation. 95% CI and I2 statistics were calculated using the Clopper-Pearson method to estimate between-study heterogeneity. RESULTS: A total of 2,734 records were retrieved, of which 2,133 were retained for further screening. After the screening, 63 studies were finally selected for the scoping review and meta-analysis. The pooled frequency of luminal, HER2-positive (HER2+), and TNBC was estimated at 56.30%, 12.61%, and 28.10%, respectively. Northern Africa had the highest frequency of the luminal subtype, while West Africa showed higher frequencies of HER2+ and TNBC subtypes. The review also had a representation of only 24 countries in Africa. CONCLUSION: Our results highlight the disparity in the representation of molecular subtypes among the people in different regions of Africa. There is a need to incorporate routine molecular subtyping into the management of African patients with BC.

Wildfire and cattle legacies on gradients of soil nitrogen underlie patterns of annual brome invasion.

Human activities are increasing wildfires and livestock activity in arid ecosystems with potential implications for the spread of invasive grasses. The objective of this study was to test whether fire history and cattle activity alter soil resource gradients, thereby affecting patterns of Bromus rubens L. (red brome) invasion. Six paired burned and unburned transect lines (1-km long) were established in the northeast Mojave Desert along the boundaries of four independent wildfire scars. At 100-m transect increment points, we measured the distance to the two nearest cowpats, and two random points and measured the density, height, biomass, and seed production of red brome, soil moisture and inorganic nitrogen (N). Cattle activity was 29% greater along burned transects compared to unburned transects (P < 0.05). Red brome height, density, and seed production were 11-34% greater along burned transects than unburned transects (P < 0.05). Red brome height, biomass, density, and seed production were twofold to tenfold greater next to cowpats compared to random points (P < 0.05). Soils along burned transects and beneath cowpats had greater soil inorganic N (P < 0.05), which was positively correlated with red brome density, height, biomass, and seed production (R2 = 0.60-0.85, P < 0.0001). Transgenerational effects were evident as seeds from red brome next to cowpats had 27% higher germination than seeds collected from random points. Positive responses of red brome to increased inorganic N related to fire and cattle activity may contribute fine fuel infill that drives invasive grass-fire cycles in deserts.

Gestational weight gain among pregnant women in Ibadan, Nigeria: Pattern, predictors and pregnancy outcomes.

BACKGROUND: Gestational weight gain (GWG) is a risk factor for adverse pregnancy outcomes, future obesity and chronic diseases among women. However, has not received much attention in many low and middle-income countries such as Nigeria. We investigated the pattern, associated factors and pregnancy outcomes of GWG in Ibadan, Nigeria, using the Ibadan Pregnancy Cohort Study (IbPCS). METHODOLOGY: The IbPCS is a multicentre prospective cohort study conducted among 1745 pregnant women recruited from four health facilities in Ibadan, Nigeria. GWG, the primary outcome, was categorised according to the Institute of Medicine's classification into insufficient, adequate and excessive weight gain. Pregnancy outcomes were the secondary outcome variables. Logistic regression analysis (Adjusted odds ratios and 95% confidence interval CI) was used to examine associations, and Poisson regression analyses were used to investigate associations with outcomes. RESULTS: Only 16.9% of women had optimal GWG, 56.8% had excessive GWG, and 26.9% had insufficient GWG. Excessive GWG was associated with high income '> #20,000-' (AOR: 1.64, 95% CI: 1.25-2.17), being overweight (AOR: 2.12, 95% CI: 1.52-2.95) and obese (AOR: 1.47, 95% CI: 1.02-2.13) after adjusting for confounders. In contrast, increased odds of insufficient GWG have associated women with depression (AOR: 1.70, 95% CI 1.17-2.47). There was no significant association between inappropriate GWG and pregnancy outcomes However, there was an increased odds for postpartum haemorrhage (AOR: 2.44, 95% CI 1.14-5.22) among women with obesity and excessive GWG. CONCLUSIONS: Excessive GWG was the most typical form of GWG among our study participants and was associated with high maternal income, and being overweight or obese. GWG needs to be monitored during antenatal care, and interventions that promote appropriate GWG should be implemented among pregnant women in Nigeria.

Elucidating a locus coeruleus-dentate gyrus dopamine pathway for operant reinforcement.

Animals can learn to repeat behaviors to earn desired rewards, a process commonly known as reinforcement learning. While previous work has implicated the ascending dopaminergic projections to the basal ganglia in reinforcement learning, little is known about the role of the hippocampus. Here, we report that a specific population of hippocampal neurons and their dopaminergic innervation contribute to operant self-stimulation. These neurons are located in the dentate gyrus, receive dopaminergic projections from the locus coeruleus, and express D1 dopamine receptors. Activation of D1 + dentate neurons is sufficient for self-stimulation: mice will press a lever to earn optogenetic activation of these neurons. A similar effect is also observed with selective activation of the locus coeruleus projections to the dentate gyrus, and blocked by D1 receptor antagonism. Calcium imaging of D1 + dentate neurons revealed significant activity at the time of action selection, but not during passive reward delivery. These results reveal the role of dopaminergic innervation of the dentate gyrus in supporting operant reinforcement.

Anatomical adaptation of water-stressed Eugenia uniflora using green synthesized silver nanoparticles and melatonin.

Cell and sub-cellular anatomical adjustments are adaptations utilized by plants to tolerate abiotic stress. Both melatonin and Morinda lucida-silver nanoparticles (ML-AgNPs) are recognized as bio-stimulants. The study examined the morphological changes and adaptive characteristics of these bio-stimulants under water-stress Eugenia uniflora. Twenty-four hours was spent priming the seeds with melatonin (0.06 mg/L), ML-AgNPs (0.06 mg/L), and a mixture (1:1) of the two. The seeds were sown and subjected to water stress for 7 days. The leaves, stems, and roots of water-stressed E. uniflora were sectioned, dried, and examined using a microscope. Drought stress led to the production of non-glandular trichomes on the abaxial and the transformation of paracytic stomata into diacytic stomata. During water stress, melatonin enlarges intercellular gaps and stomata, increases sponge and palisade parenchyma, and thickens epidermis (stem and root) and fibers. The ML-AgNPs diminished the size of mesophyll, intercellular gaps, stomata, and stem fiber. The ML-AgNPs increased the size of bulliform cells and activated the mechanical resistance features of sclerophyllous leaves (thick-celled epidermis and sclerieds) and ray parenchyma (root and stem). Equally, Melatonin and ML-AgNPs increased stem and root anatomical characteristics (xylem, bark, pith, cortex, epidermis, and vascular bundles). Stomata of E. uniflora are susceptible to alterations and undergo cell division into two new stomata (stomatogensis) in response to varying conditions (melatonin and ML-AgNPs). Melatonin adopted a strategy for maintaining a high plant water status, possibly by osmoregulation, whereas E. uniflora primed with ML-AgNPs survived by minimizing transpirational water loss through morphological changes.

Landlords' rental businesses before and after the COVID-19 pandemic: Evidence from a National Cross-Site Survey.

This paper uses a survey of over 2500 rental property owners in ten cities across the United States to determine the impact of the COVID-19 pandemic on landlords' rent collection and business behavior. Our findings show that yearly rent collection was down significantly in 2020 relative to 2019-both within and across rental markets-and that an increasing number of owners have a large share of their portfolio behind on rent. Small owners and owners of color faced the highest exposure to deep tenant arrears in 2020, challenges they were also more likely to face prior to pandemic. Our findings show that owner business practices changed dramatically in 2020, with a higher share of landlords granting tenants rent extensions or forgiving back rent during the pandemic relative to prior. However, many owners also disinvested in their rental properties through deferred maintenance, missed mortgage payments, and property sale listings. Landlords of color pursued disinvestment strategies during the pandemic at an elevated rate compared to white landlords. Owners of properties in neighborhoods with more non-white residents were both more likely to experience decreased rent collection and more likely to pursue evictions and rental late fees holding constant rental payment rates, implying the pandemic has disproportionately affected renters in communities of color. Overall, our findings highlight the strain the pandemic has placed on the housing stock, which has implications for the long-term viability and affordability of many of these units. More concerningly, our results show that households of color-which have been disproportionately affected by the pandemic in other domains-were more likely to face punitive measures from landlords in both 2019 and 2020, suggesting the pandemic has exacerbated existing racial inequality in housing markets.

Improved sub-seasonal forecasts to support preparedness action for meningitis outbreak in Africa.

West African countries are hit annually by meningitis outbreaks which occur during the dry season and are linked to atmospheric variability. This paper describes an innovative co-production process between the African Centre of Meteorological Applications for Development (ACMAD; forecast producer) and the World Health Organisation Regional Office for Africa (WHO AFRO; forecast user) to support awareness, preparedness and response actions for meningitis outbreaks. Using sub-seasonal to seasonal (S2S) forecasts, this co-production enables ACMAD and WHO AFRO to build initiative that increases the production of useful climate services in the health sector. Temperature and relative humidity forecasts are combined with dust forecasts to operationalize a meningitis early warning system (MEWS) across the African meningitis belt with a two-week lead time. To prevent and control meningitis, the MEWS is produced from week 1 to 26 of the year. This study demonstrates that S2S forecasts have good skill at predicting dry and warm atmospheric conditions precede meningitis outbreaks. Vigilance levels objectively defined within the MEWS are consistent with reported cases of meningitis. Alongside developing a MEWS, the co-production process provided a framework for analysis of climate and environmental risks based on reanalysis data, meningitis burden, and health service assessment, to support the development of a qualitative roadmap of country prioritization for defeating meningitis by 2030 across the WHO African region. The roadmap has enabled the identification of countries most vulnerable to meningitis epidemics, and in the context of climate change, supports plans for preventing, preparing, and responding to meningitis outbreaks.

Who was at risk for COVID-19 late in the US pandemic? Insights from a population health machine learning model.

Notable discrepancies in vulnerability to COVID-19 infection have been identified between specific population groups and regions in the USA. The purpose of this study was to estimate the likelihood of COVID-19 infection using a machine-learning algorithm that can be updated continuously based on health care data. Patient records were extracted for all COVID-19 nasal swab PCR tests performed within the Providence St. Joseph Health system from February to October of 2020. A total of 316,599 participants were included in this study, and approximately 7.7% (n = 24,358) tested positive for COVID-19. A gradient boosting model, LightGBM (LGBM), predicted risk of initial infection with an area under the receiver operating characteristic curve of 0.819. Factors that predicted infection were cough, fever, being a member of the Hispanic or Latino community, being Spanish speaking, having a history of diabetes or dementia, and living in a neighborhood with housing insecurity. A model trained on sociodemographic, environmental, and medical history data performed well in predicting risk of a positive COVID-19 test. This model could be used to tailor education, public health policy, and resources for communities that are at the greatest risk of infection.

Inclusion strategies in multi-stakeholder dialogues: The case of a community-based participatory research on immunization in Nigeria.

BACKGROUND: Community-Based Participatory Research (CBPR) has been used to address health disparities within several contexts by actively engaging communities. Though dialogues are recognized as a medium by which community members and other actors can make their voices heard through processes that support shared-decision making, power asymmetries often impede the achievement of this objective. Traditionally such relationship asymmetries exist between communities, health workers, and other professionals resulting in the exclusion of communities from decision making in participatory practices and dialogues. This study aimed to explore the experiences in the dialogues between different groups within communities, health workers and local government officials in a CBPR project on immunization in Nigeria. We adapted the framework by Elberse et al. (2011) to structure the possible exclusion mechanisms that could exist in dialogues between the three groups and we set up inclusion strategies to diminish the inequalities as much as possible. METHODS AND FINDINGS: This is an exploratory and descriptive case study, using qualitative methods. Data was collected through observation and semi-structured interviews (SSI) with dialogue participants. All 24 participants in the multi-stakeholder dialogues were interviewed. Inclusion strategies involved creating enabling circumstances; influencing behaviour; and influencing use of language. Verbal and circumstantial strategies were of limited value in reducing exclusion. Behavioural inclusion strategies created more awareness of the importance of inclusion; and enabled different community stakeholders to direct their influences towards achieving the collective goals of the collaboration. An important learning is that if evidence is used in the dialogues, even when exclusion of certain individuals occurs, the outcomes could still favour them. A key issue is the difference between participation and representation and the need for more efficient ways of carrying out such interactive processes to ensure that the participation of the vulnerable groups is not merely symbolic. The study makes a case for the use of 'boundary spanners' in this dynamic-these are 'elite' individuals (or community champions) who can be a voice for the minorities and who could have the opportunity to influence decision making. CONCLUSION: CBPR can enable local governments to develop effective partnerships with health workers and communities to achieve health-related goals even in the presence of asymmetries in relationships. Inclusion strategies in dialogues can improve participation and enable shared decision making, however exclusion of vulnerable groups may still occur. Intra-community dynamics and socio-cultural contexts can drive exclusion and less privileged community members require proper representation to enable their issues to be captured effectively.

Fungi as veritable tool in bioremediation of polycyclic aromatic hydrocarbons-polluted wastewater.

Polycyclic aromatic hydrocarbons of diverse forms have found application in different industries and man heavily depends on these compounds for various purposes. Thus, tonnes of thousands of polycyclic aromatic hydrocarbons are released into various water bodies yearly, resulting in pollution with great effects on aquatic lives, man, and the ecosystem at large. Hydrocarbon pollutions in wastewater are remediated by some physical and chemical methods with most of these techniques leaving a different form of harmful byproducts after the remediation. Furthermore, several species of fungi are important in the microbial bioremediation of polycyclic aromatic hydrocarbon in wastewater as they are capable of using these compounds as their source of carbon and energy in the presence of oxygenase. Fungal bioremediation is cost-effective, safer, and ecologically friendly, in addition to fungi producing polycyclic aromatic hydrocarbon degradative enzymes in high amounts, both intracellularly and extracellularly. Although optimizing the growth requirement of fungi in the field is a major challenge, current advances in the application of fungi in bioremediation address this. This review discusses in detail the technology of fungal bioremediation of polycyclic aromatic hydrocarbon in wastewater and its beneficial roles to man and the ecosystem. The benefits of remediating polycyclic aromatic hydrocarbon-polluted water with fungi and their metabolites via nanotechnology, immobilization, genomic manipulation, and other technologies to generate value-added products are highlighted in this manuscript. Information in this review will provide useful important insights to researchers and industrial professionals in the bioremediation of polycyclic aromatic hydrocarbon.

GPU-I-TASSER: a GPU accelerated I-TASSER protein structure prediction tool.

MOTIVATION: Accurate and efficient predictions of protein structures play an important role in understanding their functions. Iterative Threading Assembly Refinement (I-TASSER) is one of the most successful and widely used protein structure prediction methods in the recent community-wide CASP experiments. Yet, the computational efficiency of I-TASSER is one of the limiting factors that prevent its application for large-scale structure modeling. RESULTS: We present I-TASSER for Graphics Processing Units (GPU-I-TASSER), a GPU accelerated I-TASSER protein structure prediction tool for fast and accurate protein structure prediction. Our implementation is based on OpenACC parallelization of the replica-exchange Monte Carlo simulations to enhance the speed of I-TASSER by extending its capabilities to the GPU architecture. On a benchmark dataset of 71 protein structures, GPU-I-TASSER achieves on average a 10× speedup with comparable structure prediction accuracy compared to the CPU version of the I-TASSER. AVAILABILITY AND IMPLEMENTATION: The complete source code for GPU-I-TASSER can be downloaded and used without restriction from https://zhanggroup.org/GPU-I-TASSER/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fungi as veritable tool in current advances in nanobiotechnology.

Fungi have great prospects for synthesis, applications and developing new products in nanotechnology. In recent times, fungi use in nanotechnology is gaining more attention because of the ecological friendly state of their metabolite-mediated nanoparticles, their safety, amenability and applications in diverse fields. The diversity of the metabolites such as enzymes, polysaccharide, polypeptide, protein and other macro-molecules has made fungi a veritable tool for nanoparticles synthesis. Mechanism of fungal nano-biosynthesis from the molecular perspective has been extensively studied through various investigations on its green synthesized metal nanoparticles. Fungal nanobiotechnology has been applied in agricultural, medical and industrial sectors for goods and services improvement and delivery to mankind. Agriculturally, it has found applications in plant disease management and production of environmentally friendly, non-toxic insecticides, fungicides to enhance agricultural production in general. Medically, diagnosis and treatment of diseases, especially of microbial origin have been improved with fungal nanoparticles through more efficient drug delivery systems with great benefits to pharmaceutical industries. This review therefore explored fungal nanobiotechnology; mechanism of synthesis, characterization and potential applications in various fields of human endeavours for goods and services delivery.

Using participatory action research to improve immunization utilization in areas with pockets of unimmunized children in Nigeria.

BACKGROUND: In 2005, Nigeria adopted the Reaching Every Ward strategy to improve vaccination coverage for children 0-23 months of age. By 2015, Ogun state had full coverage (100%) in 12 of its 20 local government areas, but eight had pockets of unimmunized children, with the highest burden (37%) in Remo North. A participatory action research (PAR) approach was used to facilitate implementation of local solutions to contextual barriers to immunization in Remo North. This article assesses and seeks to explain the outcomes of the PAR implemented in Remo North to understand whether and possibly how it improved immunization utilization. METHODS: The PAR intervention took place from 2016 to 2017. It involved two (4-month) cycles of dialogue and action between community members, frontline health workers and local government officials in two wards of Remo North, facilitated by the research team. The PAR was assessed using a pre/post-intervention-only design with mixed methods. These included household surveys of caregivers of 215 and 213 children, respectively, 25 semi-structured interviews with stakeholders involved in immunization service delivery and 16 focus group discussions with community members. Data were analysed using the Strategic Advisory Group of Experts (SAGE) vaccine hesitancy framework. RESULTS: Collaboration among the three stakeholder groups enabled the development and implementation of solutions to identified problems related to access to and use of immunization services. At endline, assessment by card for children older than 9 months revealed a significant increase in those fully immunized, from 60.7% at baseline to 90.9% (p < .05). A significantly greater number of caregivers visited fixed government health facilities for routine immunization at endline (83.2%) than at baseline (54.2%) (p < .05). The reasons reported by caregivers for improved utilization of routine immunization services were increased community mobilization activities and improved responsiveness of the health workers. Spillover effects into maternal health services enhanced the use of immunization services by caregivers. Spontaneous scale-up of actions occurred across Remo North due to the involvement of local government officials. CONCLUSION: The PAR approach achieved contextual solutions to problems identified by communities. Collection and integration of evidence into discussions/dialogues with stakeholders can lead to change. Leveraging existing structures and resources enhanced effectiveness.

From reaction kinetics to dementia: A simple dimer model of Alzheimer's disease etiology.

Oligomers of the amyloid ß-protein (Aß) have been implicated in the pathogenesis of Alzheimer's disease (AD) through their toxicity towards neurons. Understanding the process of oligomerization may contribute to the development of therapeutic agents, but this has been difficult due to the complexity of oligomerization and the metastability of the oligomers thus formed. To understand the kinetics of oligomer formation, and how that relates to the progression of AD, we developed models of the oligomerization process. Here, we use experimental data from cell viability assays and proxies for rate constants involved in monomer-dimer-trimer kinetics to develop a simple mathematical model linking Aß assembly to oligomer-induced neuronal degeneration. This model recapitulates the rapid growth of disease incidence with age. It does so through incorporation of age-dependent changes in rates of Aß monomer production and elimination. The model also describes clinical progression in genetic forms of AD (e.g., Down's syndrome), changes in hippocampal volume, AD risk after traumatic brain injury, and spatial spreading of the disease due to foci in which Aß production is elevated. Continued incorporation of clinical and basic science data into the current model will make it an increasingly relevant model system for doing theoretical calculations that are not feasible in biological systems. In addition, terms in the model that have particularly large effects are likely to be especially useful therapeutic targets.