Coexisting Angiomyolipoma and Renal Cell Carcinoma in a Kidney of an Elderly Woman: Case Report and Review of the Literature

Angiomyolipoma is a well described but relatively uncommon benign renal neoplasm composed of varying admixtures of mature adipose tissue, smooth muscle, and thick-walled blood vessels.[1] The incidence of angiomyolipoma is about 0.3% overall.[2] It frequently occurs in patients with tuberous sclerosis. Even more uncommon is the simultaneous occurrence of angiomyolipoma and renal cell cancer in the same kidney in a patient without tuberous sclerosis

Small molecule activators of SIRT1 replicate signaling pathways triggered by calorie restriction in vivo

<p>Abstract</p> <p>Background</p> <p>Calorie restriction (CR) produces a number of health benefits and ameliorates diseases of aging such as type 2 diabetes. The components of the pathways downstream of CR may provide intervention points for developing therapeutics for treating diseases of aging. The NAD⁺-dependent protein deacetylase SIRT1 has been implicated as one of the key downstream regulators of CR in yeast, rodents, and humans. Small molecule activators of SIRT1 have been identified that exhibit efficacy in animal models of diseases typically associated with aging including type 2 diabetes. To identify molecular processes induced in the liver of mice treated with two structurally distinct SIRT1 activators, SIRT501 (formulated resveratrol) and SRT1720, for three days, we utilized a systems biology approach and applied Causal Network Modeling (CNM) on gene expression data to elucidate downstream effects of SIRT1 activation.</p> <p>Results</p> <p>Here we demonstrate that SIRT1 activators recapitulate many of the molecular events downstream of CR <it>in vivo</it>, such as enhancing mitochondrial biogenesis, improving metabolic signaling pathways, and blunting pro-inflammatory pathways in mice fed a high fat, high calorie diet.</p> <p>Conclusion</p> <p>CNM of gene expression data from mice treated with SRT501 or SRT1720 in combination with supporting <it>in vitro </it>and <it>in vivo </it>data demonstrates that SRT501 and SRT1720 produce a signaling profile that mirrors CR, improves glucose and insulin homeostasis, and acts via SIRT1 activation <it>in vivo</it>. Taken together these results are encouraging regarding the use of small molecule activators of SIRT1 for therapeutic intervention into type 2 diabetes, a strategy which is currently being investigated in multiple clinical trials.</p

Anomalous nonlinear X-ray Compton scattering

X-ray scattering is typically used as a weak linear atomic-scale probe of matter. At high intensities, such as produced at free-electron lasers, nonlinearities can become important, and the probe may no longer be considered weak. Here we report the observation of one of the most fundamental nonlinear X-ray–matter interactions: the concerted nonlinear Compton scattering of two identical hard X-ray photons producing a single higher-energy photon. The X-ray intensity reached 4 × 1020 W cm−2, corresponding to an electric field well above the atomic unit of strength and within almost four orders of magnitude of the quantum-electrodynamic critical field. We measure a signal from solid beryllium that scales quadratically in intensity, consistent with simultaneous non-resonant two-photon scattering from nearly-free electrons. The high-energy photons show an anomalously large redshift that is incompatible with a free-electron approximation for the ground-state electron distribution, suggesting an enhanced nonlinearity for scattering at large momentum transfer

Anomalous nonlinear X-ray Compton scattering

X-ray scattering is typically used as a weak linear atomic-scale probe of matter. At high intensities, such as produced at free-electron lasers, nonlinearities can become important, and the probe may no longer be considered weak. Here we report the observation of one of the most fundamental nonlinear X-ray–matter interactions: the concerted nonlinear Compton scattering of two identical hard X-ray photons producing a single higher-energy photon. The X-ray intensity reached 4 × 1020 W cm−2, corresponding to an electric field well above the atomic unit of strength and within almost four orders of magnitude of the quantum-electrodynamic critical field. We measure a signal from solid beryllium that scales quadratically in intensity, consistent with simultaneous non-resonant two-photon scattering from nearly-free electrons. The high-energy photons show an anomalously large redshift that is incompatible with a free-electron approximation for the ground-state electron distribution, suggesting an enhanced nonlinearity for scattering at large momentum transfer

A phase I trial of SON-1010, a tumor-targeted, interleukin-12-linked, albumin-binding cytokine, shows favorable pharmacokinetics, pharmacodynamics, and safety in healthy volunteers

BackgroundThe benefits of recombinant interleukin-12 (rIL-12) as a multifunctional cytokine and potential immunotherapy for cancer have been sought for decades based on its efficacy in multiple mouse models. Unexpected toxicity in the first phase 2 study required careful attention to revised dosing strategies. Despite some signs of efficacy since then, most rIL-12 clinical trials have encountered hurdles such as short terminal elimination half-life (T½), limited tumor microenvironment targeting, and substantial systemic toxicity. We developed a strategy to extend the rIL-12 T½ that depends on binding albumin in vivo to target tumor tissue, using single-chain rIL-12 linked to a fully human albumin binding (FHAB) domain (SON-1010). After initiating a dose-escalation trial in patients with cancer (SB101), a randomized, double-blind, placebo-controlled, single-ascending dose (SAD) phase 1 trial in healthy volunteers (SB102) was conducted.MethodsSB102 (NCT05408572) focused on safety, tolerability, pharmacokinetic (PK), and pharmacodynamic (PD) endpoints. SON-1010 at 50-300 ng/kg or placebo administered subcutaneously on day 1 was studied at a ratio of 6:2, starting with two sentinels; participants were followed through day 29. Safety was reviewed after day 22, before enrolling the next cohort. A non-compartmental analysis of PK was performed and correlations with the PD results were explored, along with a comparison of the SON-1010 PK profile in SB101.ResultsParticipants receiving SON-1010 at 100 ng/kg or higher tolerated the injection but generally experienced more treatment-emergent adverse effects (TEAEs) than those receiving the lowest dose. All TEAEs were transient and no other dose relationship was noted. As expected with rIL-12, initial decreases in neutrophils and lymphocytes returned to baseline by days 9-11. PK analysis showed two-compartment elimination in SB102 with mean T½ of 104 h, compared with one-compartment elimination in SB101, which correlated with prolonged but controlled and dose-related increases in interferon-gamma (IFNγ). There was no evidence of cytokine release syndrome based on minimal participant symptoms and responses observed with other cytokines.ConclusionSON-1010, a novel presentation for rIL-12, was safe and well-tolerated in healthy volunteers up to 300 ng/kg. Its extended half-life leads to a prolonged but controlled IFNγ response, which may be important for tumor control in patients.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT05408572, identifier NCT05408572

The Stakes in Bayh-Dole: Public Values Beyond the Pace of Innovation

Evaluation studies of the Bayh-Dole Act are generally concerned with the pace of innovation or the transgressions to the independence of research. While these concerns are important, I propose here to expand the range of public values considered in assessing Bayh-Dole and formulating future reforms. To this end, I first examine the changes in the terms of the Bayh-Dole debate and the drift in its design. Neoliberal ideas have had a definitive influence on U.S. innovation policy for the last thirty years, including legislation to strengthen patent protection. Moreover, the neoliberal policy agenda is articulated and justified in the interest of “competitiveness.” Rhetorically, this agenda equates competitiveness with economic growth and this with the public interest. Against that backdrop, I use Public Value Failure criteria to show that values such as political equality, transparency, and fairness in the distribution of the benefits of innovation, are worth considering to counter the “policy drift” of Bayh-Dole

Schumpeter and Venture Finance: Radical Theorist, Broke Investor and Enigmatic Teacher

Schumpeter's relation to venture finance constitutes a fascinating yet so far unacknowledged chapter of his biography and financial history. Presenting new historical evidence and pointing out connections that have so far escaped attention, we first discuss Schumpeter's venture theory of money and banking, then his personal history as a broke investor in Vienna, and finally his influence on the emerging venture industry during his later years at Harvard. We show how the theoretical vision inspired his failed effort as a venture investor in the 1920s, and provided a powerful intellectual frame for the later development of venture finance in the 1940s

Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data