Citations

Abstract The kinesin-5 motor protein KIF11 is crucial for mitotic spindle assembly, driving the separation of spindle poles through microtubule sliding. Src-family kinases phosphorylate KIF11 at multiple tyrosine residues within its motor domain, but the mechanistic consequences of these modifications remain unclear. Here, we dissect the role of phosphorylation at Y211 using phospho-mimetic (Y211E) and non-phosphorylatable mutants (Y211F) in biochemical, biophysical, and cellular assays. Optical trapping and Förster resonance energy transfer (FRET) analyses reveal that Y211 phosphorylation slows neck-linker docking, reducing motor velocity and force generation under load. In human cells, Y211E expression impairs bipolar spindle formation and decreases spindle pole separation velocity, while Y211F shortens steady-state spindle length. Fluorescence recovery after photobleaching (FRAP) analyses show that Y211E accelerates motor turnover on spindle microtubules, consistent with the mutant motor’s heightened load sensitivity. Together, these findings support a model in which Src-mediated phosphorylation at Y211 acts as a rheostat to tune KIF11 mechanochemistry and spindle assembly dynamics, linking cancer-relevant kinase signaling to mitotic force generation.

Abstract Background The Alzheimer's disease (AD) Braak staging is a key framework for classifying tau pathology progression in AD based on histopathological post‐mortem brain examinations. However, adapting it to PET imaging can be challenging due to differences in tracer uptake patterns and binding properties, which affect sensitivity, specificity, and regional staging. This study compares Braak staging across four tau PET tracers: Flortaucipir, MK6240, PI2620, and RO948. Methods We assessed 90 participants across the AD spectrum (46 CU, 31 MCI, 13 dementia; mean age 66.1 ± 7.8) using Aβ PET and four tau PET tracers: (Flortaucipir, MK6240, PI2620, and RO948). Braak positivity was defined based on Aβ− CU individuals (mean +2.5 SD, SUVR). To evaluate systematic bias and agreement between tracers, we computed pairwise differences at corresponding Braak stage estimates and applied the Bland‐Altman method to assess mean bias and limits of agreement. Additionally, Tau PET Braak region trajectories were modeled as functions of Aβ burden (Centiloid scale) using the Lowess method. Results Braak stage trajectories as a function of Aβ differ depending on the tracer and the sequential order of abnormality is highly variable. For instance, while for MK6240, RO948 and PI2620, Braak I is the first region to became abnormal, for Flortaucipir the earliest region to became abnormal is Braak IV (Figure 1). This variable pattern of abnormality impacts in the concordance of Braak staging between tracers with the highest Braak staging agreement resulting in concordance levels of approximately 70%. The highest levels of agreement between tracers usually happen at Braak 0 or Braak IV‐V, with intermediate stages showing very low concordance (Figure 2). The Bland‐Altman analysis identified wide limits of agreement, suggesting high variability and high tracer‐specific differences (Figure 3). On the other hand, it also identified that mean differences between tracers were small, indicating minimal systematic bias. Conclusion These preliminary findings reveal discrepancies in Braak staging when comparing Flortaucipir, MK6240, PI2620 and RO948. These findings suggest that while the tracers provide comparable stages on average, they may not be fully interchangeable in individual cases.

Background: For women in the United States desiring implant-based breast reconstruction, the maximum volume of commercially available silicone breast implants has, to date, been 800 cc. The authors evaluated the safety of Mentor larger-size MemoryGel Ultra-High Profile breast implants (≥930 cc) in women undergoing postmastectomy breast reconstruction. Methods: This 10-year, multicenter, open-label, prospective, investigational study assessed the safety and effectiveness of larger-volume implants in women undergoing postmastectomy 2-stage primary or revision reconstruction. Three-year Kaplan-Meier curves and multivariable Cox regression analyzed the association between patient and treatment characteristics and surgical outcomes. The BREAST-Q was used to assess effectiveness at 3 years. Results: A total of 400 women were enrolled (225 primary and 175 revision reconstruction). Mean body mass index was 35.8 kg/m 2 ; 81% had a body mass index greater than or equal to 30 kg/m 2 . At 3 years, the cumulative incidence of postoperative complications (excluding rupture) was 63.0% (95% confidence interval, 58.1% to 67.9%). The reoperation rate was 24.5% (95% CI, 20.4% to 29.1%), and the explantation rate was 15.8% (95% CI, 23.5% to 19.9%). Independent predictors of complications included radiation therapy and a history of smoking. There were no significant associations between postoperative complications and implant volume greater than or equal to 1135 cc or less than 1135 cc. BREAST-Q scores at year 3 showed significant improvements from baseline in Satisfaction with Breasts, Psychosocial Well-Being, Sexual Well-Being, and Physical Well-Being (all P < 0.0001). The mean score for Satisfaction with Outcome was 79.9. Conclusions: These 3-year results demonstrate that larger-volume silicone breast implants represent a safe and effective option for patients with larger breasts who are requesting postmastectomy implant-based reconstruction.

Background Patients with anti-leucine-rich glioma-inactivated 1 (anti-LGI1) autoimmune encephalitis (AIE) frequently present with faciobrachial dystonic seizures (FBDS), which are often under-detected due to their subtle motor features and lack of consistent EEG correlates. Conventional in-hospital monitoring and patient-reported seizure diaries are limited, particularly during nocturnal periods. In this pilot feasibility study, we evaluated the use of a wearable device (Empatica E4) to objectively monitor FBDS-related motor and autonomic activity in seven patients with anti-LGI1 AIE and four control subjects. Methods Wearable recordings included accelerometry (ACC), electrodermal activity (EDA), photoplethysmography (PPG) and skin temperature. A support vector machine-based algorithm was developed to identify disorder-related events using ACC and EDA features. Analyses were restricted to sleep periods to minimise confounding from voluntary movements. Results Pretreatment recordings from two patients (P1 and P2) showed significantly elevated motor event frequency, ACC magnitude and EDA activity compared to controls. Post-treatment recordings demonstrated marked reductions in these metrics, consistent with patient-reported clinical improvement. Other patients showed variable results depending on treatment timing and signal quality. Conclusion Our pilot study demonstrates the feasibility of using wearable technology for objective, real-world monitoring and assessment of patient status in anti-LGI1 AIE. Nocturnal monitoring offers a low-noise baseline for detecting seizure-related activity and may support earlier diagnosis, more accurate evaluation of treatment response and reduced reliance on resource-intensive inpatient evaluations. Future studies should expand monitoring to daytime periods and validate findings against conventional modalities such as video-EEG and electromyography polygraphy.

Abstract Objective This study aimed to evaluate how differences in case complexity affect information-processing burden, as measured by eye-tracking, as well as the efficiency of electronic health record (EHR) use among healthcare providers in the intensive care unit. Materials and Methods This cross-sectional study recruited providers from 4 U.S. medical centers that use 2 prominent EHR systems (Epic and Oracle). After reporting demographic information, participants reviewed 2 complex cases and 2 standard cases in their institution’s EHR system and then responded to 5 questions about each case, yielding a performance score. Information-processing burden was assessed by measuring the number of eye fixations via eye-tracking software. The efficiency of EHR use was assessed by measuring the task completion time, number of mouse clicks per minute, number of EHR screens viewed, and performance score. Results Eighty-one providers were included for analysis. Providers exhibited significantly more eye fixations (P &lt; .001) and longer task completion times (P &lt; .001) for complex cases than for standard cases. There were also significantly fewer mouse clicks per minute during complex cases (P &lt; .001). Reviewing a complex case first led to significantly more eye fixations (P = .015) and longer task completion times (P &lt; .01) than when a standard case was presented first. Case complexity did not significantly affect performance scores or the number of EHR screens viewed. Discussion Higher case complexity was shown to be associated with greater information-processing burden and less efficient EHR use. These findings have implications for enhancing the efficiency of EHR use, thereby leading to improved clinical decision-making and patient safety. Furthermore, reviewing complex cases first led to a greater information-processing burden, suggesting that providers could benefit from “warming up” with standard cases before reviewing complex cases.

Abstract Background: As with most Sub-Saharan African countries, Nigeria has a rising incidence of cancer, with disproportionate mortality rates. The financial burden of cancer care often results in catastrophic healthcare spending, leading to treatment refusal, disruption, and discontinuation. This is particularly significant in Nigeria, where nearly all patients are uninsured, and out-of-pocket costs often exceed households’ ability to pay. Financial Navigation Programs (FNPs) have been shown to mitigate treatment-related financial toxicity in cancer care and reduce treatment abandonment, but there is a paucity of high-quality data on this intervention in resource-constrained settings. Here, we present a randomized controlled trial to evaluate the impact of a novel FNP in Nigeria. Methods: We designed the COST-FIN trial, a multi-site pragmatic single-blinded randomized controlled trial of newly diagnosed (<6 weeks from diagnosis) adults (≥18 years) with breast, colorectal, or prostate cancer at two tertiary cancer centers in Nigeria. Participants (n=200) will be randomized (1:1) to either the intervention (FNP) or the control arm and followed for 12 months. Data on key individual, treatment, and financial parameters will be collected via structured interviews and chart abstraction at baseline, 3, 6, and 12-month follow-up. In addition, participants randomized to the FNP will receive a tailored financial literacy assessment, financial planning support, and enhanced access to resources by trained financial navigators. Primary and secondary outcomes are Financial Catastrophe (FC) and Financial Distress (FD), respectively. Exploratory outcomes will include cost-related non-adherence and cost-effectiveness of the program. An interim analysis will be conducted when 50% of the estimated accruals reach 6 months of follow-up, with crossover if compelling evidence of benefit is demonstrated at that time point. All participants will be followed for 12 months from recruitment. Discussion: This first-of-its-kind study will provide evidence on the role of FNP in potentially eliminating financial barriers to cancer care in Nigeria. Given the country’s renewed interest in cancer control through the passage of the National Cancer Control Plan, findings from this study have the potential to influence policy reform and set the stage for further studies to evaluate the scalability and implementation of similar interventions in resource-limited settings. Trial registration : ClinicalTrials.gov NCT06630962. Oct 8, 2024 (https://clinicaltrials.gov/study/NCT06630962)

Abstract Objective To measure the relative levels of signal and noise in expert diagnosis of epilepsy. Methods Twenty multinational epileptologists independently reviewed 50 vignettes of adult and pediatric patients presenting with suspected seizure(s) on two separate occasions with a ≥30‐day washout period. Experts provided a diagnosis of epilepsy or non‐epilepsy based on clinical information and, if requested, routine EEG and neuroimaging data. Cases had an established clinical diagnosis of epilepsy or non‐epilepsy based on capture of habitual paroxysmal events on video‐EEG or long‐term clinical follow‐up. Experts' judgments were analyzed to decompose variability into different sources: signal (objective differences between cases), level noise (experts' bias toward over/under‐diagnosis), pattern noise (experts' idiosyncratic reactions to specific case features), and occasion noise (inconsistency across occasions). Results The probability of an expert making a different diagnosis for a given case on two different occasions was 16%. The probability of two different experts making a different diagnosis for the same case was 26%. Signal (case “difficulty”) accounted for 66–69% of total variation, with 31–34% attributable to noise. Level noise was the largest contributor in the absence of EEG/neuroimaging results (23%), while pattern noise dominated when test results were available (24%). Occasion noise contributed relatively little (1%) but was still sufficient to cause diagnostic reversals in 16–22% between occasions. Significance The degree of noise in expert diagnosis of epilepsy is substantial, stemming primarily from physicians' idiosyncratic interpretations of case features and variable dispositions toward over‐ or under‐diagnosis. Strategies to improve reliability are needed, including standardized data collection protocols and structured decision algorithms. For “difficult cases,” where expert reliability and accuracy are lowest, our findings support current clinical practice which favors early referral for video‐EEG monitoring over reliance on diagnostic anchoring. This diagnostic pathway may become more accessible with advances in EEG technology (e.g., wearable devices) and artificial intelligence.