Indiana University East

Stereotactic biopsies are essential for obtaining accurate histopathological analysis to guide treatment decisions for deep-seated brain lesions. Manually guided methods, while commonly used and highly precise, can be limited by potential inaccuracies and insufficient tissue sampling. The emerging robot-assisted (RA) techniques offer enhanced precision and could address these limitations for improved accuracy. We aimed to compare safety and effectiveness of RA stereotactic biopsies to traditional techniques. We conducted a systematic search of PubMed, Embase, and Web of Science using terms related to robotic biopsies and intracranial lesions. Eligible studies compared robot-assisted procedures to traditional techniques. Data extracted included diagnostic yield, complication rates, and accuracy. Quality assessment of studies was performed with the ROBINS-I tool, and a random-effects model meta-analysis was performed. Five studies were included, encompassing 913 patients (robot-assisted n = 434, traditional n = 479). Robot-assisted biopsies demonstrated higher diagnostic yield (OR 2.06, 95% CI [1.01,4.21], p = 0.04), and improved trajectory accuracy, with entry point error (EPE) reduced by 0.42 mm (95% CI [-0.59,-0.26], p < 0.001) and target point error (TPE) reduced by 0.93 mm (95% CI [-1.80,-0.06], p < 0.01). There were no significant differences in the incidence of complications or operative time. RA stereotactic biopsies may improve diagnostic yield and accuracy in targeting intracranial lesions without increasing complication rates or operative time. The limited number of studies and potential biases suggest a need for further high-quality, prospective research to ascertain these findings.

Adaptive optics (AO) is a powerful method for correcting dynamic aberrations in numerous applications. When applied to the eye, it enables cellular-resolution retinal imaging and enhanced visual performance and stimulation. Most ophthalmic AO systems correct dynamic aberrations up to 1−2 Hz, the commonly-known cutoff frequency for correcting ocular aberrations. However, this frequency may be grossly underestimated for more clinically relevant scenarios where the medical impact of AO will be greatest. Unfortunately, little is known about the aberration dynamics in these scenarios. A major bottleneck has been the lack of sufficiently fast AO systems to measure and correct them. We develop an ultrafast ophthalmic AO system that increases AO bandwidth by ~30× and improves aberration power rejection magnitude by 500×. We demonstrate that this much faster ophthalmic AO is possible without sacrificing other system performances. We find that the discontinuous-exposure AO-control scheme runs 32% slower yet achieves 53% larger AO bandwidth than the commonly used continuous-exposure scheme. Using the ultrafast system, we characterize ocular aberration dynamics in six clinically-relevant scenarios and find their power spectra to be 10−100× larger than normal. We show that ultrafast AO substantially improves aberration correction and retinal imaging performance in these scenarios compared with conventional AO.

The Covid-19 pandemic changed how individuals socialized and communicated. This study looks at the impact that the Covid-19 pandemic had on individuals’ communication methodologies and the way that change in communication had on interpersonal relationships. Also, the study investigates how constructs of socialization changed due to covid-19 and changes in communication. Individuals (N = 230) participated in an online survey and answered open-ended questions about their socialization practices during the initial Covid-19 lockdown. Using In Vivo coding, the participants gave thematic responses. Individuals discussed the change in communication and the amount of communication. Participants also discussed how this change of communication impacted the quality of socializing and the effect on socializing. The participants also disclosed how the pandemic impacted their interpersonal relationships. The study shows the negative impact that Covid-19 had on the socialization and communication of individuals. Research should look longitudinally at the impact this will have on generations. More mental health resources for individuals whom Covid-19 negatively impacts in terms of being able to socialize and have healthy interpersonal relationships.

Background Social determinants of health have been shown to influence individual mental health and overall well-being. Additionally, populations that experience stigma and/or discrimination because of race, class, gender, or another identity group experience disproportionately higher rates of mental health disorders than populations that do not experience such marginalization. One way to address upstream social determinants that influence mental health is through systems change initiatives. In 2019, Indiana implemented a statewide Regional Prevention System (RPS) focused on systems change to promote mental health and prevent substance misuse. Methods We developed a semi-structured interview guide to collect insights about the RPS implementation and sustainability. Potential participants were identified based on their role as an active regional coordinator (n = 9). We conducted qualitative interviews with all 9 regional coordinators in Indiana. Interview recordings were transcribed and coded using an a priori coding framework based on constructs from the Theory of Innovation Implementation and the Consolidated Framework for Implementation Research. Results Insights about the RPS implementation process are presented across four domains: innovation, system-level, organization-level, and sustainability. In terms of implementation barriers, coordinators encountered hesitancy and distrust from community members, which they had to overcome to gain buy-in. They also described stigma, including community and individual social norms towards mental health and substance misuse, as barriers that challenged efforts to engage community members in the RPS. Facilitators of implementation included having established community infrastructure and external partnerships. In communities without existing infrastructure to support prevention efforts, particularly rural communities, the implementation process took longer but community members welcomed the additional support and valued the new communication platforms created by the RPS. On sustainability, coordinators provided examples of communities that were able to obtain grant funding in support of prevention initiatives launched through the RPS. Conclusion The process of implementing and sustaining prevention efforts through the RPS varied across communities. Prioritizing the delivery of systems-change efforts in underserved communities that are ready for change, rather than statewide efforts, may offer a better strategy for addressing disparities in the social determinants of health that influence mental health and substance misuse.

Sex chromosomes have evolved hundreds of times across the flowering plant tree of life; their recent origins in some members of this clade can shed light on the early consequences of suppressed recombination, a crucial step in sex chromosome evolution. Amborella trichopoda, the sole species of a lineage that is sister to all other extant flowering plants, is dioecious with a young ZW sex determination system. Here we present a haplotype-resolved genome assembly, including highly contiguous assemblies of the Z and W chromosomes. We identify a ~3-megabase sex-determination region (SDR) captured in two strata that includes a ~300-kilobase inversion that is enriched with repetitive sequences and contains a homologue of the Arabidopsis METHYLTHIOADENOSINE NUCLEOSIDASE (MTN1-2) genes, which are known to be involved in fertility. However, the remainder of the SDR does not show patterns typically found in non-recombining SDRs, such as repeat accumulation and gene loss. These findings are consistent with the hypothesis that dioecy is derived in Amborella and the sex chromosome pair has not significantly degenerated.

Object Re-identification (Re-ID) aims to identify specific objects across different times and scenes, which is a widely researched task in computer vision. For a prolonged period, this field has been predominantly driven by deep learning technology based on convolutional neural networks. In recent years, the emergence of Vision Transformers has spurred a growing number of studies delving deeper into Transformer-based Re-ID, continuously breaking performance records and witnessing significant progress in the Re-ID field. Offering a powerful, flexible, and unified solution, Transformers cater to a wide array of Re-ID tasks with unparalleled efficacy. This paper provides a comprehensive review and in-depth analysis of the Transformer-based Re-ID. In categorizing existing works into Image/Video-Based Re-ID, Re-ID with limited data/annotations, Cross-Modal Re-ID, and Special Re-ID Scenarios, we thoroughly elucidate the advantages demonstrated by the Transformer in addressing a multitude of challenges across these domains. Considering the trending unsupervised Re-ID, we propose a new Transformer baseline, UntransReID, achieving state-of-the-art performance on both single/cross modal tasks. For the under-explored animal Re-ID, we devise a standardized experimental benchmark and conduct extensive experiments to explore the applicability of Transformer for this task and facilitate future research. Finally, we discuss some important yet under-investigated open issues in the large foundation model era, we believe it will serve as a new handbook for researchers in this field. A periodically updated website will be available at https://github.com/mangye16/ReID-Survey.

The extent to which bullying victimization is associated with an increased risk of obsessive-compulsive disorder (OCD) has received little empirical attention. This longitudinal, population-based, genetically informative study examined whether self-reported bullying victimization at age 15 was associated with a clinical diagnosis of OCD in the Swedish National Patient Register and with self-reported obsessive-compulsive symptoms (OCS) at ages 18 and 24 in 16,030 twins from the Child and Adolescent Twin Study in Sweden. Using a discordant twin design, including monozygotic (MZ) and dizygotic (DZ) twins, each twin was compared with their co-twin, allowing a strict control of genetic and environmental confounding. At the population level, adjusting for birth year and sex, each standard deviation (SD) increase in bullying victimization was associated with a 32% increase in the odds of an OCD diagnosis (OR, 1.32; 95% CI, 1.21–1.44), of 0.13 SD in OCS at age 18 (β, 0.13; 95% CI, 0.11–0.16), and of 0.11 SD in OCS at age 24 (β, 0.11; 95% CI, 0.07–0.16). While associations tended to persist in the within DZ-twin comparison models, the estimates attenuated and were no longer statistically significant in the within MZ-twin comparisons. These results suggest that the association between bullying victimization and OCD/OCS is likely due to genetic confounding and therefore incompatible with a strong causal effect. Other mechanisms, such as evocative gene-environment correlations, are more plausible explanations for the observed associations.

One of the neurobiological correlates of alcohol use disorder (AUD) is the disruption of striatal dopaminergic function. Although regional differences in dopamine (DA) tone/function have been well studied, interregional relationships (represented as inter‐subject covariance) have not been investigated and may offer a novel avenue for understanding DA tone. Positron emission tomography (PET) data with [¹¹C]raclopride in 22 social drinking controls and 17 AUD participants were used to generate group‐level striatal covariance (partial Pearson correlation) networks, which were compared edgewise as well as on global network metrics and community structure. An exploratory analysis examined the impact of tobacco cigarette use status. Striatal covariance was validated in an independent publicly available [¹⁸F]fallypride PET sample of healthy volunteers. Striatal covariance of control participants from both data sets showed a clear bipartition of the network into two distinct communities, one in the anterior and another in the posterior striatum. This organization was disrupted in the AUD participants' network, which showed significantly lower network metrics compared with the control participants' network. Stratification by cigarette use suggests differential consequences on group covariance networks. This work demonstrates that network neuroscience can quantify group differences in striatal DA and that its interregional interactions offer new insight into the consequences of AUD.

Background Older adults commonly experience chronic medical conditions and are at risk of cognitive impairment as a result of age, chronic comorbidity, and medications prescribed to manage multiple chronic conditions. Anticholinergic medications are common treatments for chronic conditions and have been repeatedly associated with poor cognitive outcomes, including delirium and dementia, in epidemiologic studies. However, no study has definitively evaluated the causal relationship between anticholinergics and cognition in a randomized controlled trial design. Utilizing our prior experience in deprescribing anticholinergic medications in various clinical environments, we designed an outpatient deprescribing intervention to prospectively test the potential causal relationship between anticholinergics and cognition in primary care older adults. Methods This cluster randomized clinical trial will be conducted to evaluate the impact of an anticholinergic deprescribing intervention compared to usual care on outcomes of cognition and safety in primary care older adults. Participants will include those aged 65 years and over, receiving primary care in the greater Indianapolis area, using a strong anticholinergic within the last 2 weeks or with evidence of high-risk exposure in the past year. Those excluded will have a diagnosis of Alzheimer’s disease or related dementia, or serious mental illness. The trial plans to enroll 344 participants who will be cluster-randomized at the level of primary care physician to avoid contamination. Participants will complete outcome assessments every 6 months up to 2 years by blinded outcome assessors. The primary outcome of the study is a composite measure of cognition that includes domains assessing executive cognitive function, language, and memory. Secondary outcomes include patient-reported measures of pain intensity, depression, anxiety, sleep disturbance, and health-related quality of life. Discussion The R2D2 trial will be the largest and longest prospective randomized trial testing the impact of an anticholinergic-specific deprescribing intervention on cognition in primary care older adults. Results could influence deprescribing methodology and provide new insight on the relationship between anticholinergics and cognition. Trial registration ClinicalTrials.gov NCT04270474. Registered on February 17, 2020.

Context/objective: The objective of this study was to examine the implications of shelter-in-place (SIP) during the COVID-19 pandemic on secondary health conditions (SHC), loneliness, social isolation, social connectedness, anxiety, and positive affect and well-being (PAWB) among community-dwelling adults with spinal cord injury (SCI). Design: An online exploratory cross-sectional descriptive design. Participants: 131 community-dwelling adults with SCI. Outcome measures: UCLA Loneliness Scale, SCI-QOL - Anxiety and PAWB. Results: Respondents were approximately 33 years old, mostly male and Caucasian. More than half reported being married, living with their spouse in a home with modifications, or living in a household of three or more people. More than half reported experiencing more pain during SIP but not experiencing more of any other SHC than before SIP. On average, participants experienced a moderate level of loneliness, severe anxiety, and higher levels of PAWB during SIP. Conclusion: Respondents reported that they experienced more pain, loneliness, and anxiety while at the same time reporting higher PAWB. Future research should focus on understanding the nuances of the seemingly counterintuitive relationship described here to develop better ways to support community-dwelling adults with SCI during public health emergencies and SIP.

Retinal pigment epithelium (RPE) cells are essential for normal retinal function. Morphological defects in these cells are associated with a number of retinal neurodegenerative diseases. Owing to the cellular resolution and depth-sectioning capabilities, individual RPE cells can be visualized in vivo with adaptive optics-optical coherence tomography (AO-OCT). Rapid, cost-efficient, and objective quantification of the RPE mosaic’s structural properties necessitates the development of an automated cell segmentation algorithm. This paper presents a deep learning-based method with partial annotation training for detecting RPE cells in AO-OCT images with accuracy better than human performance. We have made the code, imaging datasets, and the manual expert labels available online.

Economic data are often contaminated by measurement errors and truncated by ranking. This paper shows that the classical measurement error model with independent and additive measurement errors is identified nonparametrically using only two order statistics of repeated measurements. The identification result confirms a hypothesis by Athey and Haile (2002) for a symmetric ascending auction model with unobserved heterogeneity. Extensions allow for heterogeneous measurement errors, broadening the applicability to additional empirical settings, including asymmetric auctions and wage offer models. We adapt an existing simulated sieve estimator and illustrate its performance in finite samples.

BACKGROUND Pharmacological inhibition of megalin (also known as LRP2 [low-density lipoprotein receptor-related protein-2]) attenuates atherosclerosis in hypercholesterolemic mice. Since megalin is abundant in renal proximal tubule cells (PTCs), the purpose of this study was to determine whether PTC-specific deletion of megalin reduces hypercholesterolemia-induced atherosclerosis in mice. METHODS Female Lrp2 f/f mice were bred with male Ndrg1 - Cre ERT2 +/0 mice to develop PTC-LRP2 +/+ and PTC-LRP2 −/− littermates. To study atherosclerosis, all mice were bred to an LDL (low-density lipoprotein) receptor −/− background and fed a Western diet to induce atherosclerosis. RESULTS PTC-specific megalin deletion did not attenuate atherosclerosis in LDL receptor −/− mice in either sex. Serendipitously, we discovered that PTC-specific megalin deletion led to interstitial infiltration of CD68+ cells and tubular atrophy. The pathology was only evident in male PTC-LRP2 −/− mice fed a Western diet but not in mice fed a normal laboratory diet. Renal pathologies were also observed in male PTC-LRP2 −/− mice in an LDL receptor +/+ background fed the same Western diet, demonstrating that the renal pathologies were dependent on diet and not on hypercholesterolemia. In contrast, female PTC-LRP2 −/− mice had no apparent renal pathologies. In vivo multiphoton microscopy demonstrated that PTC-specific megalin deletion dramatically diminished ALB (albumin) accumulation in PTCs within 10 days of Western diet feeding. RNA-sequencing analyses demonstrated the upregulation of inflammation-related pathways in the kidney. CONCLUSIONS PTC-specific megalin deletion does not affect atherosclerosis but leads to tubulointerstitial nephritis in mice fed a Western diet, with severe pathologies in male mice.

Background Heart rate variability (HRV) analysis has shown promise as a valuable complementary tool for clinical assessment in trauma cases. This study aims to evaluate the utility of HRV in monitoring different severities of hemorrhagic shock (HS) and its correlation with traditional hemodynamic and metabolic parameters. Methods Male Sprague–Dawley rats were divided into different experimental groups, including those with and without vagotomy, and were exposed to different classes of decompensatory HS. To induce varying severities of HS, volume resuscitation was delayed by gradually returning 0%, 20%, or 50% of the shed blood volume at the end of the compensation phase, referred to as 0% DFR, 20% DFR, and 50% DFR class, respectively. Hemodynamic parameters were monitored, and HRV was calculated. Levels of TNF-α and IL-10 were determined in lung tissue at the end of the experiments. Correlations between HRV, hemodynamic parameters, inflammatory gene expression and arterial blood gas variables were evaluated. Results HRV showed increased power of the low-frequency (LF) and respiratory sinus arrhythmia (RSA) in all groups during the hypotension phase of HS (Nadir 1). Subdiaphragmatic vagotomy blunted the increase in the LF component in the Nadir 1. After volume resuscitation, systolic blood pressure (SBP), RSA and LF returned to baseline in the 0% DFR and 20% DFR classes. However, animals in 50% DFR class exhibited a reduced SBP and LF and lower pH. Notably, strong correlations were found between LF and SBP as well as tissue hypoperfusion markers. The expression of TNF-α in the lung was increased in all HS groups, while this gene expression was significantly higher in the vagotomized animals. Conclusion The alterations in HRV components were found to be significantly correlated with the hemodynamic and metabolic status of the animals, while showing no association with inflammatory responses. Additionally, the intervention of subdiaphragmatic vagotomy significantly impacted both HRV components and inflammatory responses. Collectively, these findings suggest the potential of HRV components for the assessment of the presence and severity of HS.

Leveraging the polarization property of light to evaluate the birefringence of tissues as well as changes due to pathological conditions has been gaining interest over the past two decades with the introduction of different variants of optical coherence tomography (OCT) including polarization-sensitive OCT (PS-OCT) and cross-polarization OCT (CP-OCT). Because OCT sources are partially polarized, PS-OCT and CP-OCT generally require a linear polarizer and polarization-maintaining fibers to enable a linearly polarized input beam into the interferometer. While recent studies have suggested using an unpolarized input beam to reduce the system’s complexity, the effect of unpolarized light on the point spread function (PSF) of OCT has not been fully studied. This work proposed a mathematical framework to evaluate the contribution of unpolarized light to the PSF of OCT. Simulation and experiments were performed for three OCT sources to assess the validity of the proposed model. Overall, simulations were in good agreement with experiments and revealed that unpolarized light introduced two additional reflectors into the reflectivity profile of the source, which were more pronounced in the cross-polarization configuration. This additional information can lead to misinterpretation of the birefringence of tissues in PS-OCT and CP-OCT. Their effect on image quality was evaluated in ex vivo corneal imaging of porcine eyeballs.

Specific Emitter Identification (SEI) has been put forward as an Internet of Things (IoT) Physical Layer Security (PLS) approach for its abilities to detect, characterize, and identify wireless emitters by exploiting distinct, inherent, and unintentional features in their transmitted signals. Since its introduction, a significant amount of work has been conducted; however, most assume the emitters are passive and their identifying signal features are immutable and challenging to mimic. This suggests the emitters are reluctant and incapable of developing and implementing effective SEI countermeasures; however, Deep Learning (DL) has been shown capable of learning emitter-specific features directly from their raw in-phase and quadrature signal samples, while Software-Defined Radios (SDRs) are capable of manipulating these signal samples. Based on these capabilities, it is fair to question the ease at which an emitter can effectively mimic the SEI features of another or manipulate its own to hinder or defeat SEI. This work considers SEI mimicry using three signal features mimicking countermeasures; “off-the-self” DL; two SDRs of different sizes, weights, power, and cost (SWaP-C); handcrafted and DL-based SEI processes, and assessment of an SEI mimicry countermeasure in a “coffee shop” deployment. Our results show “off-the-shelf” DL algorithms, and SDR enables SEI mimicry; however, adversary success is hindered by: (i) the use of decoy emitter preambles, (ii) the use of a denoising autoencoder and (iii) SDR SWaP-C constraints.