Exploring the Landscape of Intracranial Aneurysms in South America: A Comprehensive Narrative Review Intracranial Aneurysms in South America.

Exploring the landscape of intracranial aneurysms in South America unravels a complex interplay of epidemiological factors, clinical manifestations, and therapeutic challenges. The study methodically conducts a comprehensive literature review spanning the years 2003 to 2023, focusing on English-language articles obtained from diverse databases to elucidate the multifaceted nature of intracranial aneurysms in the region. Results and discussions categorize outcomes into positive domains, emphasizing successful treatments, favorable recoveries, and high survival rates, while also shedding light on negative aspects such as residual aneurysms and complications. The research illuminates significant gaps in pathological typing of intracranial aneurysms and exposes challenges in healthcare accessibility, notably the disparities in neurosurgical resources. Management challenges, including constrained infrastructure access, a neurosurgeon shortage, and gender disparities, are underscored. Transitioning to future prospects, the study advocates for strategic interventions, proposing expanded neurosurgical training, multidisciplinary approaches, improved funding, enhanced access to care, and fostering international collaborations. The study concludes by emphasizing the pivotal role of collaborative efforts, intensified training programs, and global partnerships in propelling intracranial aneurysm management forward in South America, ultimately contributing to enhanced patient outcomes across the region.

Racial disparities in EEG research and their implications for our understanding of the maternal brain.

Racial disparities in maternal health are alarming and persistent. Use of electroencephalography (EEG) and event-related potentials (ERPs) to understand the maternal brain can improve our knowledge of maternal health by providing insight into mechanisms underlying maternal well-being, including implications for child development. However, systematic racial bias exists in EEG methodology-particularly for Black individuals-and in psychological and health research broadly. This paper discusses these biases in the context of EEG/ERP research on the maternal brain. First, we assess the racial/ethnic diversity of existing ERP studies of maternal neural responding to infant/child emotional expressions, using papers from a recent meta-analysis, finding that the majority of mothers represented in this research are of White/European ancestry and that the racially and ethnically diverse samples that are present are limited in terms of geography. Therefore, our current knowledge base in this area may be biased and not generalizable across racially diverse mothers. We outline factors underlying this problem, beginning with the racial bias in EEG equipment that systematically excludes individuals of African descent, and also considering factors specific to research with mothers. Finally, we highlight recent innovations to EEG hardware to better accommodate diverse hairstyles and textures, and other important steps to increase racial and ethnic representativeness in EEG/ERP research with mothers. We urge EEG/ERP researchers who study the maternal brain-including our own research group-to take action to increase racial diversity so that this research area can confidently inform understanding of maternal health and contribute to minimizing maternal health disparities.

Embracing robotic surgery in low- and middle-income countries: Potential benefits, challenges, and scope in the future.

Robotic surgery has applications in many medical specialties, including urology, general surgery, and surgical oncology. In the context of a widespread resource and personnel shortage in Low- and Middle-Income Countries (LMICs), the use of robotics in surgery may help to reduce physician burnout, surgical site infections, and hospital stays. However, a lack of haptic feedback and potential socioeconomic factors such as high implementation costs and a lack of trained personnel may limit its accessibility and application. Specific improvements focused on improved financial and technical support to LMICs can help improve access and have the potential to transform the surgical experience for both surgeons and patients in LMICs. This review focuses on the evolution of robotic surgery, with an emphasis on challenges and recommendations to facilitate wider implementation and improved patient outcomes.

Reductions in muscle coactivation and metabolic cost during visuomotor adaptation.

We often have to adapt our movements as we interact with a variety of objects in various conditions on a daily basis. Evidence suggests that motor adaptation relies on a process that minimizes error and effort; however, much of this evidence involved adapting to novel dynamics with physical perturbations to counteract. To examine the generality of the process of minimizing error and effort during motor adaptation, we used a visuomotor adaptation task that did not involve dynamic perturbations. We investigated the time courses of muscle activity, coactivation, and metabolic cost as subjects reached to a target with a visuomotor rotation. We wanted to determine whether subjects would modulate muscle activity, coactivation, and metabolic cost during a visuomotor adaptation task. Interestingly, subjects increased muscle coactivation early during visuomotor adaptation when there were large cursor-trajectory errors but no physical perturbations to reject. As adaptation progressed, muscle activity and coactivation decreased. Metabolic cost followed a similar time course. When the perturbation was removed, typical after-effects were observed: trajectory error increased and then was reduced quickly. This was accompanied by increases in muscle activity, coactivation, and metabolic cost, along with subsequent rapid reductions. These results demonstrate that subjects modulate muscle activity, coactivation, and metabolic cost similarly across different forms of motor adaptation. Overall, our findings suggest that minimization of error and effort may be a general process underlying various forms of motor adaptation.

Older adults learn less, but still reduce metabolic cost, during motor adaptation.

The ability to learn new movements and dynamics is important for maintaining independence with advancing age. Age-related sensorimotor changes and increased muscle coactivation likely alter the trial-and-error-based process of adapting to new movement demands (motor adaptation). Here, we asked, to what extent is motor adaptation to novel dynamics maintained in older adults (≥65 yr)? We hypothesized that older adults would adapt to the novel dynamics less well than young adults. Because older adults often use muscle coactivation, we expected older adults to use greater muscle coactivation during motor adaptation than young adults. Nevertheless, we predicted that older adults would reduce muscle activity and metabolic cost with motor adaptation, similar to young adults. Seated older (n = 11, 73.8 ± 5.6 yr) and young (n = 15, 23.8 ± 4.7 yr) adults made targeted reaching movements while grasping a robotic arm. We measured their metabolic rate continuously via expired gas analysis. A force field was used to add novel dynamics. Older adults had greater movement deviations and compensated for just 65% of the novel dynamics compared with 84% in young adults. As expected, older adults used greater muscle coactivation than young adults. Last, older adults reduced muscle activity with motor adaptation and had consistent reductions in metabolic cost later during motor adaptation, similar to young adults. These results suggest that despite increased muscle coactivation, older adults can adapt to the novel dynamics, albeit less accurately. These results also suggest that reductions in metabolic cost may be a fundamental feature of motor adaptation.

Reduction of metabolic cost during motor learning of arm reaching dynamics.

It is often assumed that the CNS controls movements in a manner that minimizes energetic cost. While empirical evidence for actual metabolic minimization exists in locomotion, actual metabolic cost has yet to be measured during motor learning and/or arm reaching. Here, we measured metabolic power consumption using expired gas analysis, as humans learned novel arm reaching dynamics. We hypothesized that (1) metabolic power would decrease with motor learning and (2) muscle activity and coactivation would parallel changes in metabolic power. Seated subjects made horizontal planar reaching movements toward a target using a robotic arm. The novel dynamics involved compensating for a viscous curl force field that perturbed reaching movements. Metabolic power was measured continuously throughout the protocol. Subjects decreased movement error and learned the novel dynamics. By the end of learning, net metabolic power decreased by ~20% (~0.1 W/kg) from initial learning. Muscle activity and coactivation also decreased with motor learning. Interestingly, distinct and significant reductions in metabolic power occurred even after muscle activity and coactivation had stabilized and movement changes were small. These results provide the first evidence of actual metabolic reduction during motor learning and for a reaching task. Further, they suggest that muscle activity may not explain changes in metabolic cost as completely as previously thought. Additional mechanisms such as more subtle features of arm muscle activity, changes in activity of other muscles, and/or more efficient neural processes may also underlie the reduction in metabolic cost during motor learning.

Assessment of factors that contribute to decreased quality of life in Gynecologic Oncology Group ovarian cancer trials.

BACKGROUND: The objective of this study was to assess which quality-of-life (QOL) line items on the Functional Assessment of Cancer Therapy-Ovarian (FACT-O) were associated with low QOL in women who were receiving chemotherapy for ovarian cancer. METHODS: Patients with stage III or IV ovarian cancer on Gynecologic Oncology Group Protocols 152 and 172 who underwent primary surgery followed by intravenous paclitaxel and cisplatin completed the FACT-O. The FACT scale includes the 4 domains of physical, functional, social, and emotional well being (PWB, FWB, SWB, EWB, respectively). Women who had overall FACT-O scores in the lowest quartile (Q1) were compared with women in the upper 3 quartiles (Q2-Q4). The proportions of women in each group that selected the 2 worst categories for each item were compared. The level of significance was set at P<.005. RESULTS: Before Cycle 4, 361 patients (86.4%) provided valid QOL assessments. For PWB, a significantly greater proportion of women in Q1 versus Q2 through Q4 selected the 2 worst categories of several physical symptoms (nausea, pain, feeling ill, and being bothered by the side effects of treatment). For FWB, significant differences included being able to work, being content with the quality of their life, and sleeping well. For EWB, there were significant differences in feeling nervous and worrying about dying. There were virtually no differences between groups in SWB. Low interest in sex was reported by 56% to 88% of all patients (Q1-Q4). CONCLUSIONS: A large proportion of women with FACT-O scores in the lowest quartile reported problems that potentially were amenable to clinical interventions, such as symptom management and psychosocial support.

Combined genetic assessment of transforming growth factor-beta signaling pathway variants may predict breast cancer risk.

There is growing evidence that common variants of the transforming growth factor-beta (TGF-beta) signaling pathway may modify breast cancer risk. In vitro studies have shown that some variants increase TGF-beta signaling, whereas others have an opposite effect. We tested the hypothesis that a combined genetic assessment of two well-characterized variants may predict breast cancer risk. Consecutive patients (n = 660) with breast cancer from the Memorial Sloan-Kettering Cancer Center (New York, NY) and healthy females (n = 880) from New York City were genotyped for the hypomorphic TGFBR1*6A allele and for the TGFB1 T29C variant that results in increased TGF-beta circulating levels. Cases and controls were of similar ethnicity and geographic location. Thirty percent of cases were identified as high or low TGF-beta signalers based on TGFB1 and TGFBR1 genotypes. There was a significantly higher proportion of high signalers (TGFBR1/TGFBR1 and TGFB1*CC) among controls (21.6%) than cases (15.7%; P = 0.003). The odds ratio [OR; 95% confidence interval (95% CI)] for individuals with the lowest expected TGF-beta signaling level (TGFB1*TT or TGFB1*TC and TGFBR1*6A) was 1.69 (1.08-2.66) when compared with individuals with the highest expected TGF-signaling levels. Breast cancer risk incurred by low signalers was most pronounced among women after age 50 years (OR, 2.05; 95% CI, 1.01-4.16). TGFBR1*6A was associated with a significantly increased risk for breast cancer (OR, 1.46; 95% CI, 1.04-2.06), but the TGFB1*CC genotype was not associated with any appreciable risk (OR, 0.89; 95% CI, 0.63-1.21). TGFBR1*6A effect was most pronounced among women diagnosed after age 50 years (OR, 2.20; 95% CI, 1.25-3.87). This is the first study assessing the TGF-beta signaling pathway through two common and functionally relevant TGFBR1 and TGFB1 variants. This approach may predict breast cancer risk in a large subset of the population.