Citations

ABSTRACT There is an increasing need for biomarkers of senescent cell burden to facilitate the selection of participants for clinical trials. p16 Ink4a is encoded by the CDKN2A locus, which produces five variant transcripts in humans, two of which encode homologous p16 proteins: p16 Inka4a , encoded by p16_variant 1 , and p16ɣ, encoded by p16_variant 5. While distinct quantitative polymerase chain reaction primers can be designed for p16_variant 5, primers for p16_variant 1 also measure p16_variant 5 ( p16_variant 1 + 5 ). In a recent clinical trial evaluating the effects of the senolytic combination, dasatinib + quercetin (D + Q), on bone metabolism in postmenopausal women, we found that women in the highest tertile for T‐cell expression of p16_variant 5 had the most robust skeletal responses to D + Q. Importantly, the assessment of p16_variant 5 was more predictive of these responses than p16_variant 1 + 5 . Here, we demonstrate that in vitro, p16_variant 1 + 5 increased rapidly (Week 1) following the induction of DNA damage, whereas p16_variant 5 increased later (Week 4), suggesting that p16_variant 5 becomes detectable only when the abundance of senescent cells reaches some threshold. Further analysis identified a SASP panel in plasma that performed as well in identifying postmenopausal women with a positive skeletal response to D + Q. Collectively, our findings provide further support for the T‐cell p16_variant 5 assay as a biomarker for selecting participants in clinical trials of senolytic interventions. In addition, our data indicate that correlated plasma SASP markers could be used in lieu of the more technically challenging T‐cell p16 assay. Trial Registration: ClinicalTrials.gov identifier: NCT04313634.

Cancer immunotherapy—including immune checkpoint inhibition (ICI) and adoptive cell therapy (ACT)—has become a standard, potentially curative treatment for a subset of advanced solid and liquid tumors. However, most patients with cancer do not benefit from the rapidly evolving improvements in the understanding of principal mechanisms determining cancer immune responsiveness (CIR); including patient-specific genetically determined and acquired factors, as well as intrinsic cancer cell biology. Though CIR is multifactorial, fundamental concepts are emerging that should be considered for the design of novel therapeutic strategies and related clinical studies. Recent advancements as well as novel approaches to address the limitations of current treatments are discussed here, with a specific focus on ICI and ACT.

Purpose: Delivering optimal care to patients with seizures and epilepsy requires all EEGs to be interpreted accurately and reliably. This study investigated neurology professionals' opinions on the ideal standards for EEG in clinical care. Methods: We developed an anonymous e-survey targeting practicing and trainee neurologists focused on participants' demographics, clinical practice characteristics, and views on optimal EEG standards of care—including whether an EEG certification test is needed and whether postresidency/fellowship training in EEG/epilepsy is necessary for neurologists who interpret outpatient/routine EEGs in practice. The survey was hosted by the Neurology Clinical Practice—Practice Current, and it was distributed online through the American Academy of Neurology, American Epilepsy Society, American Clinical Neurophysiology Society, and International League Against Epilepsy, and through social media. Results: Two hundred eighty-three responses were included: 119 from EEG/epilepsy-trained neurologists, 83 from non-EEG/epilepsy-trained neurologists, 75 from trainees, and 6 from advanced care providers. Most participants (78%) agreed that “an objective certification test of ability to interpret EEGs is needed for all those who interpret EEGs in clinical practice.” Most participants (71%) believed that outpatient/routine EEGs may be read only by neurologists with EEG/epilepsy training; this opinion was more prevalent among EEG/epilepsy-trained (83%) versus non-EEG/epilepsy-trained neurologists (55%). Conclusions: Our neurology community should discuss the need to develop and implement a certification test of ability for all neurologists who wish to interpret EEGs in clinical practice. In addition, it is imperative to improve in-residency EEG education to ensure that neurology graduates achieve EEG competence before entering the workforce.

PURPOSE There is limited cancer clinical research in sub-Saharan African countries despite the significant burden of cancers. The primary objective of this strengths, weaknesses, opportunities, and threats (SWOT) analysis was to understand and document factors affecting the successful implementation of prostate cancer (CaP) clinical research in Nigeria. METHODS The research team used a qualitative design involving International Registry of Men with Advanced Prostate Cancer (IRONMAN) study team members as participants from four regional sites in Nigeria. One-hour listening sessions were conducted via Zoom at each site, focusing on SWOT related to the IRONMAN study. All sessions were recorded, transcribed, and analyzed. Themes were inductively coded and then synthesized across all four sites. RESULTS The study teams identified several strengths and weaknesses in conducting the IRONMAN study at their respective sites. Key strengths included access to robust patient population for recruitment and the availability of essential resources, such as lab space, clinical knowledge, and adequate staffing. Weaknesses centered on the social determinants of health that hinder patient participation, such as transportation challenges, distance to clinics, limited access to care, and insufficient biorepository space for sample storage. A prominent opportunity identified was the potential for Nigerian institutions to engage in more clinical research, particularly multisite global trials. Threats included difficulties in retaining research staff and political instability. CONCLUSION This study highlights the promising research opportunities in Nigeria. The lessons learned from the IRONMAN study provide valuable insights into the feasibility of conducting CaP clinical research and trials tailored to the needs of Black men in sub-Saharan Africa. These findings offer a roadmap for future research efforts, with the potential to expand clinical trials and improve health outcomes across the region.

Abstract Nerve conduction F-wave studies contain crucial information about subclinical motor dysfunction that can be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making waveform interpretation challenging. Artificial intelligence techniques can extract time–frequency features to provide new insights into ALS diagnosis and prognosis. A retrospective analysis was performed on F-wave responses from 46 802 patients. Discrete wavelet transforms were applied to time-series waveform responses after stimulating ulnar, median, fibular and tibial nerves. Wavelet coefficient statistics, onset age, sex and body mass index were features for training a Gradient Boosting Machine model on 40 095 patients (5329 diagnosed with motor neuron disease). Model performance was tested on responses from 689 ALS patients meeting Gold Coast criteria and 689 age- and sex-matched controls. An exploratory analysis examined model performance on cohorts of patients with inclusion body myositis, cervical radiculopathy, lumbar radiculopathy or peripheral neuropathy, which can mimic ALS symptoms. Factors affecting survival were estimated through Cox proportional hazards regression. The model trained using wavelet features on the full waveform had 90% recall, 87% precision and 88% accuracy. Similar model performance was measured using features from only the M-wave or F-wave. Classification probabilities for ALS patients were statistically different from the diagnoses mimicking ALS symptoms (P < 0.001, ANOVA, Tukey’s post hoc test). Higher model classification probabilities of ALS, older age at onset, and family history of ALS alone or with frontotemporal dementia were factors decreasing survival. Longer diagnostic delay and upper limb onset site were factors increasing survival. Model scores two standard deviations below the mean had 4 months increased survival (two standard deviations below had 3 months decreased survival). Artificial intelligence techniques extracted important information from F-wave responses to estimate a patient’s likelihood of ALS and their survival risks. Although the model can make predictions at a specific decision threshold as presented here, the true strength of such a model lies in its ability to provide probabilities about whether a patient is likely to have ALS in comparison to other mimicking diagnoses, such as inclusion body myositis, cervical or lumbar radiculopathy or peripheral neuropathy. These probabilities provide clinicians with additional information that they can use to make the final diagnosis with greater confidence and precision. Integrating such a model into the clinical workflow could help clinicians to diagnose ALS sooner and manage treatment based on estimated survival, which might improve outcomes and the quality of life of patients.

This cross-sectional study of online fundraising campaigns for medical expenses conducted in India examines the distribution of fundraisers by amount raised and disease type.