Wonderings to research questions: Engaging patients in long COVID research prioritization within a learning health system.

Background: An integral component of research within a learning health system is patient engagement at all stages of the research process. While there are well-defined best practices for engaging with patients on predetermined research questions, there is little specific methodology for engaging patients at the stage of research question formation and prioritization. Further, with an emerging disease such as Long COVID, population-specific strategies for meaningful engagement have not been characterized. Methods: The COVID-19 Focused Virtual Patient Engagement Studio (CoVIP studio) was a virtual panel created to facilitate patient-centered studies surrounding the effects of long-term COVID ("Long COVID") also known as post-acute SARS-CoV-2 syndrome (PASC). A diverse group of panelists was recruited and trained in several different areas of knowledge, competencies, and abilities regarding research and Long COVID. A three-step approach was developed that consisted of recording panelists' broad wonderings to generate patient-specific research questions. Results: The "wonderings" discussed in panelists' training sessions were analyzed to identify specific populations, interventions, comparators, outcomes, and timeframes (PICOT) elements, which were then used to create a survey to identify the elements of greatest importance to the panel. Based on the findings, 10 research questions were formulated using the PICOT format. The panelists then ranked the questions on perceived order of importance and distributed one million fictional grant dollars between the five chosen questions in the second survey. Through this stepwise prioritization process, the project team successfully translated panelists' research wonderings into investigable research questions. Conclusion: This methodology has implications for the advancement of patient-engaged prioritization both within the scope of Long COVID research and in research on other rare or emerging diseases.

A parabrachial hub for the prioritization of survival behavior.

Long-term sustained pain in the absence of acute physical injury is a prominent feature of chronic pain conditions. While neurons responding to noxious stimuli have been identified, understanding the signals that persist without ongoing painful stimuli remains a challenge. Using an ethological approach based on the prioritization of adaptive survival behaviors, we determined that neuropeptide Y (NPY) signaling from multiple sources converges on parabrachial neurons expressing the NPY Y1 receptor to reduce sustained pain responses. Neural activity recordings and computational modeling demonstrate that activity in Y1R parabrachial neurons is elevated following injury, predicts functional coping behavior, and is inhibited by competing survival needs. Taken together, our findings suggest that parabrachial Y1 receptor-expressing neurons are a critical hub for endogenous analgesic pathways that suppress sustained pain states.

"I realized I was not alone": A mixed-methods investigation of the implementation of Ubuntu groups to reduce burnout and social isolation in an allopathic medical School in the Southeastern United States.

PURPOSE/BACKGROUND: Healthcare providers experience higher rates of workplace burnout, a reality highlighted by the COVID-19 pandemic. In response, small groups, inspired by South African philosophy, Ubuntu, were introduced to decrease burnout and social isolation and build community and belonging. This study examines how participation in these groups can impact these measures. METHODS: In this mixed-methods study, trained facilitators led small groups that utilized story-sharing to foster connections within the group and broader community. Quantitative and qualitative data were analyzed separately and merged to identify convergence. RESULTS: Three main qualitative themes emerged: 1) seeking and building connections and community, 2) curiosity, learning, and growing, and 3) open-hearted and thriving. These themes were linked to quantitative outcomes, showing a statistically significant decrease in social isolation among staff/faculty and students. Furthermore, faculty/staff exhibited reduced burnout compared to students, while students reported increased feelings of belonging. CONCLUSION: Participation in Ubuntu groups positively influenced students' sense of belonging, reduced faculty/staff burnout, and alleviated social isolation for all participants. Future research should explore the potential of this intervention to further promote wellness on medical campuses. Programs emphasizing the well-being of individuals, including faculty, staff, and students, are crucial for supporting the overall health of medical communities and the wider society.

Neural heterogeneity controls computations in spiking neural networks.

The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does this neural heterogeneity influence macroscopic neural dynamics, and how might it contribute to neural computation? In this work, we use a mean-field model to investigate computation in heterogeneous neural networks, by studying how the heterogeneity of cell spiking thresholds affects three key computational functions of a neural population: the gating, encoding, and decoding of neural signals. Our results suggest that heterogeneity serves different computational functions in different cell types. In inhibitory interneurons, varying the degree of spike threshold heterogeneity allows them to gate the propagation of neural signals in a reciprocally coupled excitatory population. Whereas homogeneous interneurons impose synchronized dynamics that narrow the dynamic repertoire of the excitatory neurons, heterogeneous interneurons act as an inhibitory offset while preserving excitatory neuron function. Spike threshold heterogeneity also controls the entrainment properties of neural networks to periodic input, thus affecting the temporal gating of synaptic inputs. Among excitatory neurons, heterogeneity increases the dimensionality of neural dynamics, improving the network's capacity to perform decoding tasks. Conversely, homogeneous networks suffer in their capacity for function generation, but excel at encoding signals via multistable dynamic regimes. Drawing from these findings, we propose intra-cell-type heterogeneity as a mechanism for sculpting the computational properties of local circuits of excitatory and inhibitory spiking neurons, permitting the same canonical microcircuit to be tuned for diverse computational tasks.

Hypernegative GABAA Reversal Potential in Pyramidal Cells Contributes to Medial Prefrontal Cortex Deactivation in a Mouse Model of Neuropathic Pain.

Deactivation of the medial prefrontal cortex (mPFC) has been broadly reported in both neuropathic pain models and human chronic pain patients. Several cellular mechanisms may contribute to the inhibition of mPFC activity, including enhanced GABAergic inhibition. The functional effect of GABAA(γ-aminobutyric acid type A)-receptor activation depends on the concentration of intracellular chloride in the postsynaptic neuron, which is mainly regulated by the activity of Na-K-2Cl cotransporter isoform 1 (NKCC1) and K-Cl cotransporter isoform 2 (KCC2), 2 potassium-chloride cotransporters that import and extrude chloride, respectively. Recent work has shown that the NKCC1-KCC2 ratio is affected in numerous pathological conditions, and we hypothesized that it may contribute to the alteration of mPFC function in neuropathic pain. We used quantitative in situ hybridization to assess the level of expression of NKCC1 and KCC2 in the mPFC of a mouse model of neuropathic pain (spared nerve injury), and we found that KCC2 transcript is increased in the mPFC of spared nerve injury mice while NKCC1 is not affected. Perforated patch recordings further showed that this results in the hypernegative reversal potential of the GABAA current in pyramidal neurons of the mPFC. Computational simulations suggested that this change in GABAA reversal potential is sufficient to significantly reduce the overall activity of the cortical network. Thus, our results identify a novel pathological modulation of GABAA function and a new mechanism by which mPFC function is inhibited in neuropathic pain. Our data also help explain previous findings showing that activation of mPFC interneurons has proalgesic effect in neuropathic, but not in control conditions. PERSPECTIVE: Chronic pain is associated with the presence of depolarizing GABAA current in the spinal cord, suggesting that pharmacological NKCC1 antagonism has analgesic effects. However, our results show that in neuropathic pain, GABAA current is actually hyperinhibitory in the mPFC, where it contributes to the mPFC functional deactivation. This suggests caution in the use of NKCC1 antagonism to treat pain.

PyRates-A code-generation tool for modeling dynamical systems in biology and beyond.

The mathematical study of real-world dynamical systems relies on models composed of differential equations. Numerical methods for solving and analyzing differential equation systems are essential when complex biological problems have to be studied, such as the spreading of a virus, the evolution of competing species in an ecosystem, or the dynamics of neurons in the brain. Here we present PyRates, a Python-based software for modeling and analyzing differential equation systems via numerical methods. PyRates is specifically designed to account for the inherent complexity of biological systems. It provides a new language for defining models that mirrors the modular organization of real-world dynamical systems and thus simplifies the implementation of complex networks of interacting dynamic entities. Furthermore, PyRates provides extensive support for the various forms of interaction delays that can be observed in biological systems. The core of PyRates is a versatile code-generation system that translates user-defined models into "backend" implementations in various languages, including Python, Fortran, Matlab, and Julia. This allows users to apply a wide range of analysis methods for dynamical systems, eliminating the need for manual translation between code bases. PyRates may also be used as a model definition interface for the creation of custom dynamical systems tools. To demonstrate this, we developed two extensions of PyRates for common analyses of dynamic models of biological systems: PyCoBi for bifurcation analysis and RectiPy for parameter fitting. We demonstrate in a series of example models how PyRates can be used in combination with PyCoBi and RectiPy for model analysis and fitting. Together, these tools offer a versatile framework for applying computational modeling and numerical analysis methods to dynamical systems in biology and beyond.

Patient and Care Team Perspectives on Social Determinants of Health Screening in Primary Care: A Qualitative Study.

Importance: Health systems in the US are increasingly screening for social determinants of health (SDOH). However, guidance incorporating stakeholder feedback is limited. Objective: To examine patient and care team experiences in early implementation of SDOH screening in primary care. Design, Setting, and Participants: This qualitative study included cross-sectional analysis of SDOH screenings during primary care visits from February 22 to May 10, 2022, primary care team member interviews from July 6, 2022, to March 8, 2023, and patient stakeholder engagement on June 30, 2022. The setting was a large southeastern US health care system. Eligible patients were aged 18 years or older with completed visits in primary care. Exposure: Screening for SDOH in primary care. Main outcomes and Measures: Multivariable logistic regression evaluated patient (eg, age, race and ethnicity) and care team characteristics (eg, practice type), and screening completeness. Interviews contextualized the quantitative analysis. Results: There were 78 928 visits in practices conducting any SDOH screening. The population with visits had a mean (SD) age of 57.6 (18.1) years; 48 086 (60.9%) were female, 12 569 (15.9%) Black, 60 578 (76.8%) White, and 3088 (3.9%) Hispanic. A total of 54 611 visits (69.2%) were with a doctor of medicine and 13 035 (16.5%) with a nurse practitioner. Most had no SDOH questions answered (75 298 [95.4%]) followed by all questions (2976 [3.77%]). Logistic regression analysis found that clinician type, patient race, and primary payer were associated with screening likelihood: for clinician type, nurse practitioner (odds ratio [OR], 0.13; 95% CI, 0.03-0.62; P = .01) and physician assistant (OR, 3.11; 95% CI, 1.19-8.10; P = .02); for patient race, Asian (OR, 1.69; 95% CI, 1.25-2.28; P = .001); Black (OR, 1.49; 95% CI, 1.10-2.01; P = .009); or 2 or more races (OR, 1.48; 95% CI, 1.12-1.94; P = .006); and for primary payer, Medicaid (OR, 0.62; 95% CI, 0.48-0.80; P < .001); managed care (OR, 1.17; 95% CI, 1.07-1.29; P = .001); uninsured or with Access Health (OR, 0.26; 95% CI, 0.10-0.67; P = .005), and Tricare (OR, 0.71; 95% CI, 0.55-0.92; P = .01). Interview themes included barriers (patient hesitancy, time and resources for screening and referrals, and number of questions/content overlap) and facilitators (communication, practice champions, and support for patient needs). Conclusions and Relevance: This qualitative study presents potential guidance regarding factors that could improve SDOH screening within busy clinical workflows.

From monkeys to humans: observation-basedEMGbrain-computer interface decoders for humans with paralysis.

Objective. Intracortical brain-computer interfaces (iBCIs) aim to enable individuals with paralysis to control the movement of virtual limbs and robotic arms. Because patients' paralysis prevents training a direct neural activity to limb movement decoder, most iBCIs rely on 'observation-based' decoding in which the patient watches a moving cursor while mentally envisioning making the movement. However, this reliance on observed target motion for decoder development precludes its application to the prediction of unobservable motor output like muscle activity. Here, we ask whether recordings of muscle activity from a surrogate individual performing the same movement as the iBCI patient can be used as target for an iBCI decoder.Approach. We test two possible approaches, each using data from a human iBCI user and a monkey, both performing similar motor actions. In one approach, we trained a decoder to predict the electromyographic (EMG) activity of a monkey from neural signals recorded from a human. We then contrast this to a second approach, based on the hypothesis that the low-dimensional 'latent' neural representations of motor behavior, known to be preserved across time for a given behavior, might also be preserved across individuals. We 'transferred' an EMG decoder trained solely on monkey data to the human iBCI user after using Canonical Correlation Analysis to align the human latent signals to those of the monkey.Main results. We found that both direct and transfer decoding approaches allowed accurate EMG predictions between two monkeys and from a monkey to a human.Significance. Our findings suggest that these latent representations of behavior are consistent across animals and even primate species. These methods are an important initial step in the development of iBCI decoders that generate EMG predictions that could serve as signals for a biomimetic decoder controlling motion and impedance of a prosthetic arm, or even muscle force directly through functional electrical stimulation.

Using adversarial networks to extend brain computer interface decoding accuracy over time.

Existing intracortical brain computer interfaces (iBCIs) transform neural activity into control signals capable of restoring movement to persons with paralysis. However, the accuracy of the 'decoder' at the heart of the iBCI typically degrades over time due to turnover of recorded neurons. To compensate, decoders can be recalibrated, but this requires the user to spend extra time and effort to provide the necessary data, then learn the new dynamics. As the recorded neurons change, one can think of the underlying movement intent signal being expressed in changing coordinates. If a mapping can be computed between the different coordinate systems, it may be possible to stabilize the original decoder's mapping from brain to behavior without recalibration. We previously proposed a method based on Generalized Adversarial Networks (GANs), called 'Adversarial Domain Adaptation Network' (ADAN), which aligns the distributions of latent signals within underlying low-dimensional neural manifolds. However, we tested ADAN on only a very limited dataset. Here we propose a method based on Cycle-Consistent Adversarial Networks (Cycle-GAN), which aligns the distributions of the full-dimensional neural recordings. We tested both Cycle-GAN and ADAN on data from multiple monkeys and behaviors and compared them to a third, quite different method based on Procrustes alignment of axes provided by Factor Analysis. All three methods are unsupervised and require little data, making them practical in real life. Overall, Cycle-GAN had the best performance and was easier to train and more robust than ADAN, making it ideal for stabilizing iBCI systems over time.

Massage therapy in palliative care populations: a narrative review of literature from 2012 to 2022.

BACKGROUND AND OBJECTIVE: Patients living with serious illness are often eligible for palliative care and experience physical symptoms including pain or dyspnea and psychological distress that negatively impacts health-related quality of life and other outcomes. Such patients often benefit from massage therapy to reduce symptom burden and improve quality of life when such treatment is available. At present, no synthesis or review exists exploring massage therapy specifically provided with palliative care patient populations. This review is needed because those with serious illness are a growing and important vulnerable population. Massage therapy is used frequently and in many healthcare delivery contexts, but the body of research has not led to its systematic integration or broad acceptance. METHODS: PubMed search for clinical research focused on massage therapy for palliative care-eligible populations from 2012 and 2022. Search terms included keywords: massage, massage therapy, serious illness, advanced illness, and palliative care. KEY CONTENT AND FINDINGS: Thirteen unique articles were identified through the PubMed database search and from a manual review of references. Study designs of included articles were one pilot, one quasi-experimental single-arm study, one mixed-methods study, two qualitative (both with hospital-based palliative care populations), seven randomized controlled trials, and one retrospective cohort analysis in a major Veterans Health Administration health care facility. CONCLUSIONS: Variability was found in study design, scope, sample size, and outcomes for related articles published in the last ten years. Few eligible interventions reflected real-world massage therapy delivery suggesting more clinical research is needed to examine massage provided by massage therapists trained to work with palliative care populations. Gaps in the current body of existing evidence supports the need for this review and recommendations for the direction of future related research.

Antipsychotic drug efficacy correlates with the modulation of D1 rather than D2 receptor-expressing striatal projection neurons.

Elevated dopamine transmission in psychosis is assumed to unbalance striatal output through D1- and D2-receptor-expressing spiny-projection neurons (SPNs). Antipsychotic drugs are thought to re-balance this output by blocking D2 receptors (D2Rs). In this study, we found that amphetamine-driven dopamine release unbalanced D1-SPN and D2-SPN Ca2+ activity in mice, but that antipsychotic efficacy was associated with the reversal of abnormal D1-SPN, rather than D2-SPN, dynamics, even for drugs that are D2R selective or lacking any dopamine receptor affinity. By contrast, a clinically ineffective drug normalized D2-SPN dynamics but exacerbated D1-SPN dynamics under hyperdopaminergic conditions. Consistent with antipsychotic effect, selective D1-SPN inhibition attenuated amphetamine-driven changes in locomotion, sensorimotor gating and hallucination-like perception. Notably, antipsychotic efficacy correlated with the selective inhibition of D1-SPNs only under hyperdopaminergic conditions-a dopamine-state-dependence exhibited by D1R partial agonism but not non-antipsychotic D1R antagonists. Our findings provide new insights into antipsychotic drug mechanism and reveal an important role for D1-SPN modulation.

"I Don't Want to Go to Work": A Mixed-Methods Analysis of Healthcare Worker Experiences from the Front- and Side-Lines of COVID-19.

During the COVID-19 pandemic, healthcare workers (HCW) were categorized as "essential" and "non-essential", creating a division where some were "locked-in" a system with little ability to prepare for or control the oncoming crisis. Others were "locked-out" regardless of whether their skills might be useful. The purpose of this study was to systematically gather data over the course of the COVID-19 pandemic from HCW through an interprofessional lens to examine experiences of locked-out HCW. This convergent parallel mixed-methods study captured perspectives representing nearly two dozen professions through a survey, administered via social media, and video blogs. Analysis included logistic regression models of differences in outcome measures by professional category and Rapid Identification of Themes from Audio recordings (RITA) of video blogs. We collected 1299 baseline responses from 15 April 2020 to 16 March 2021. Of those responses, 12.1% reported no signs of burnout, while 21.9% reported four or more signs. Qualitative analysis identified four themes: (1) professional identity, (2) intrinsic stressors, (3) extrinsic factors, and (4) coping strategies. There are some differences in the experiences of locked-in and locked-out HCW. This did not always lead to differing reports of moral distress and burnout, and both groups struggled to cope with the realities of the pandemic.

Macroscopic dynamics of neural networks with heterogeneous spiking thresholds.

Mean-field theory links the physiological properties of individual neurons to the emergent dynamics of neural population activity. These models provide an essential tool for studying brain function at different scales; however, for their application to neural populations on large scale, they need to account for differences between distinct neuron types. The Izhikevich single neuron model can account for a broad range of different neuron types and spiking patterns, thus rendering it an optimal candidate for a mean-field theoretic treatment of brain dynamics in heterogeneous networks. Here we derive the mean-field equations for networks of all-to-all coupled Izhikevich neurons with heterogeneous spiking thresholds. Using methods from bifurcation theory, we examine the conditions under which the mean-field theory accurately predicts the dynamics of the Izhikevich neuron network. To this end, we focus on three important features of the Izhikevich model that are subject here to simplifying assumptions: (i) spike-frequency adaptation, (ii) the spike reset conditions, and (iii) the distribution of single-cell spike thresholds across neurons. Our results indicate that, while the mean-field model is not an exact model of the Izhikevich network dynamics, it faithfully captures its different dynamic regimes and phase transitions. We thus present a mean-field model that can represent different neuron types and spiking dynamics. The model comprises biophysical state variables and parameters, incorporates realistic spike resetting conditions, and accounts for heterogeneity in neural spiking thresholds. These features allow for a broad applicability of the model as well as for a direct comparison to experimental data.

Striatal ensemble activity in an innate naturalistic behavior.

Self-grooming is an innate, naturalistic behavior found in a wide variety of organisms. The control of rodent grooming has been shown to be mediated by the dorsolateral striatum through lesion studies and in-vivo extracellular recordings. Yet, it is unclear how populations of neurons in the striatum encode grooming. We recorded single-unit extracellular activity from populations of neurons in freely moving mice and developed a semi-automated approach to detect self-grooming events from 117 hours of simultaneous multi-camera video recordings of mouse behavior. We first characterized the grooming transition-aligned response profiles of striatal projection neuron and fast spiking interneuron single units. We identified striatal ensembles whose units were more strongly correlated during grooming than during the entire session. These ensembles display varied grooming responses, including transient changes around grooming transitions or sustained changes in activity throughout the duration of grooming. Neural trajectories computed from the identified ensembles retain the grooming related dynamics present in trajectories computed from all units in the session. These results elaborate striatal function in rodent self-grooming and demonstrate that striatal grooming-related activity is organized within functional ensembles, improving our understanding of how the striatum guides action selection in a naturalistic behavior.

Brain biopsy in neurological disease of unknown etiology: A single-center 12-year retrospective analysis.

There are no international guidelines for brain biopsy in neurological disease of unknown etiology, yet most practicing neurologists will encounter difficult cases in which biopsy is considered. This patient cohort is heterogenous, and it is unclear in which circumstances biopsy is most useful. We performed an audit of brain biopsies reviewed in our neuropathology department from 2010 to 2021. Of 9,488 biopsies, 331 biopsies undertaken for an undiagnosed neurological disease were identified. Where documented, the commonest symptoms were hemorrhage, encephalopathy, and dementia. 29% of biopsies were non-diagnostic. The most common clinically relevant findings on biopsy were infection, cerebral amyloid angiopathy with or without angiitis, and demyelination. Rarer conditions included CNS vasculitis, non-infectious encephalitis, and Creutzfeldt Jakob Disease. We highlight the value of brain biopsy in the workup of cryptogenic neurological disease despite recent advances in less invasive diagnostics.

An approximate line attractor in the hypothalamus encodes an aggressive state.

The hypothalamus regulates innate social behaviors, including mating and aggression. These behaviors can be evoked by optogenetic stimulation of specific neuronal subpopulations within MPOA and VMHvl, respectively. Here, we perform dynamical systems modeling of population neuronal activity in these nuclei during social behaviors. In VMHvl, unsupervised analysis identified a dominant dimension of neural activity with a large time constant (>50 s), generating an approximate line attractor in neural state space. Progression of the neural trajectory along this attractor was correlated with an escalation of agonistic behavior, suggesting that it may encode a scalable state of aggressiveness. Consistent with this, individual differences in the magnitude of the integration dimension time constant were strongly correlated with differences in aggressiveness. In contrast, approximate line attractors were not observed in MPOA during mating; instead, neurons with fast dynamics were tuned to specific actions. Thus, different hypothalamic nuclei employ distinct neural population codes to represent similar social behaviors.

Determining massage dose-response to improve cancer-related symptom cluster of pain, fatigue, and sleep disturbance: A 7-arm randomized trial in palliative cancer care.

BACKGROUND: The efficacy of various massage doses in palliative cancer care settings is still debated, and no specific protocol is available. AIM: Evaluating response to various massage doses for symptom cluster of pain-fatigue-sleep. DESIGN: A 7-arm randomized-controlled trial with weekly massage for 4 weeks depending on the prescribed dose (15-, 30-, or 60-min; 2× or 3×/week) and a 4-week follow-up. The intensities of pain, fatigue, and sleep disturbance were measured using a 0-10 scale at nine-timepoint; baseline, weekly during the intervention, and the follow-up period. Then, the mean scores of the three symptoms were calculated as the symptom cluster intensity at each timepoint. IRCT.ir IRCT20150302021307N5. SETTING/PARTICIPANTS: Adults with cancer (n = 273) who reported all three symptoms at three oncology centers in Iran. RESULTS: The odds of clinical improvement (at least 30% reduction in symptom cluster intensity from baseline) increased with dose-escalation significantly [(OR = 17.37; 95% CI = 3.87-77.90 for 60-min doses); (OR = 11.71; 95% CI = 2.60-52.69, for 30-min doses); (OR = 4.36; 95% CI = 0.94-20.32, for 15-min doses)]. The effect durability was significantly shorter at 15-min doses compared to 30- and 60-min doses. The odds of improvement for doses 3×/week was not significant compared to doses 2×/week (OR = 12.27 vs OR = 8.34); however, the effect durability for doses 3×/week was significantly higher. CONCLUSIONS: The findings indicated that dose-escalation increases the efficacy of massage for the pain-fatigue-sleep symptom cluster. Although the 60-min doses were found to be more effective, the 30-min doses can be considered more practical because they are less costly and time-consuming. Our findings can be helpful to develop massage guidelines in palliative care settings. TRIAL REGISTRATION: Iranian Registry of Clinical Trials, IRCT20150302021307N5.

Proteases, protease inhibitors and radiation carcinogenesis.

PURPOSE: The purpose of the studies described in this mini review article was to identify nontoxic compounds that could prevent or suppress the radiation induced malignant transformation of cells and be useful as human cancer preventive agents. CONCLUSIONS: (1) Many different types of potential anticarcinogenic substances were evaluated initially for their abilities to prevent or suppress radiation induced malignant transformation in vitro, and certain anticarcinogenic protease inhibitors (APIs) were observed to be the most powerful anticarcinogenic agents at suppressing this surrogate endpoint biomarker of radiation carcinogenesis. (2) Within the category of APIs, those that inhibited the activity of chymotrypsin were effective at far lower molar concentrations than other APIs. The soybean-derived protease inhibitor known as the Bowman-Birk inhibitor (BBI) is a particularly powerful chymotrypsin inhibitor that is able to prevent radiation induced transformation in vitro (at concentrations down to nanomolar levels) as well as radiation induced carcinogenesis in vivo without toxicity. (3) There were many other unusual characteristics of APIs that led to the selection of one of these APIs, BBI, as the most appropriate compound for us to develop as a human cancer preventive agent. As one example, the APIs have an irreversible effect on carcinogenesis, while the effects are reversible for most anticarcinogenic agents when they are removed from carcinogenesis assay systems. (4) Numerous studies were performed in attempts to determine the potential mechanisms by which the APIs could prevent or suppress radiation induced carcinogenesis in in vitro and in vivo systems, and the results of these studies are described in this review article. The APIs and the proteases which interact with them appear to play important roles in radiation carcinogenesis. (5) Preparations for human trials using BBI began decades ago. The cost of preparing purified BBI was far too high to consider performing human trials with this agent, so BBI Concentrate (BBIC), a soybean extract enriched in BBI, was developed for the specific purpose of performing human trials with BBI. BBIC achieved Investigational New Drug (IND) Status with the Food and Drug Administration in April,1992, and human BBIC trials began at that time. (6) Several human trials were performed using BBIC and they indicated many potentially beneficial health effects produced by BBIC administration to people in various forms (e.g. tablets). 7) It is hypothesized that BBI takes the place of α-1-antichymotrypsin, an important regulatory compound in the human body, and helps to maintain homeostasis.

Patient Goals for Living with Rheumatoid Arthritis: A Qualitative Study.

Rheumatoid arthritis is highly individualized in terms of its flare ups and periods of remission. Each patient's unique experience requires a high level of personalization in terms of treatment making it necessary to understand what their goals for living are. This study explores patient perceptions on how the burden of RA shapes patients' goals for living and their preferences for symptom and side-effect management within the United States. Fifteen patients diagnosed with RA with varying lengths of diagnosis were interviewed. A thematic analysis was conducted to construct a conceptual framework. Emerging themes identified disease burdens as: (1) inability to perform essential needs, (2) negative feelings about disease, and (3) its influence on relationships. These burdens shaped desired goals for living which guided the symptom and side-effect priorities the patient wanted managed. Practitioners should consider patient goals and preferences in conjunction with disease progression when engaging in treatment decisions.