Body representation in infants: Categorical boundaries of body parts as assessed by somatosensory mismatch negativity.

There is growing interest in developing and using novel measures to assess how the body is represented in human infancy. Various lines of evidence with adults and older children show that tactile perception is modulated by a high-level representation of the body. For instance, the distance between two points of tactile stimulation is perceived as being greater when these points cross a joint boundary than when they are within a body part, suggesting that the representation of the body is structured with joints acting as categorical boundaries between body parts. Investigating the developmental origins of this categorical effect has been constrained by infants' inability to verbally report on the properties of tactile stimulation. Here we made novel use of an infant brain measure, the somatosensory mismatch negativity (sMMN), to explore categorical aspects of tactile body processing in infants aged 6-7 months. Amplitude of the sMMN elicited by tactile stimuli across the wrist boundary was significantly greater than for stimuli of equal distance that were within the boundary, suggesting a categorical effect in body processing in infants. We suggest that an early-appearing, structured representation of the body into 'parts' may play a role in mapping correspondences between self and other

Preventing P-gp Ubiquitination Lowers Aβ Brain Levels in an Alzheimer\u27s Disease Mouse Model

One characteristic of Alzheimer’s disease (AD) is excessive accumulation of amyloid-β (Aβ) in the brain. Aβ brain accumulation is, in part, due to a reduction in Aβ clearance from the brain across the blood-brain barrier. One key element that contributes to Ab brain clearance is P-glycoprotein (P-gp) that transports Aβ from brain to blood. In AD, P-gp protein expression and transport activity levels are significantly reduced, which impairs Aβ brain clearance. The mechanism responsible for reduced P-gp expression and activity levels is poorly understood. We recently demonstrated that Aβ40 triggers P-gp degradation through the ubiquitin-proteasome pathway. Consistent with these data, we show here that ubiquitinated P-gp levels in brain capillaries isolated from brain samples of AD patients are increased compared to capillaries isolated from brain tissue of cognitive normal individuals. We extended this line of research to in vivo studies using transgenic human amyloid precursor protein (hAPP)-overexpressing mice (Tg2576) that were treated with PYR41, a cell-permeable, irreversible inhibitor of the ubiquitinactivating enzyme E1. Our data show that inhibiting P-gp ubiquitination protects the transporter from degradation, and immunoprecipitation experiments confirmed that PYR41 prevented P-gp ubiquitination. We further found that PYR41 treatment prevented reduction of P-gp protein expression and transport activity levels and substantially lowered Aβ brain levels in hAPP mice. Together, our findings provide in vivo proof that the ubiquitin-proteasome system mediates reduction of blood-brain barrier P-gp in AD and that inhibiting P-gp ubiquitination prevents P-gp degradation and lowers Aβ brain levels. Thus, targeting the ubiquitin-proteasome system may provide a novel therapeutic approach to protect blood-brain barrier P-gp from degradation in AD and other Aβ-based pathologies

Layered architecture for quantum computing

We develop a layered quantum computer architecture, which is a systematic framework for tackling the individual challenges of developing a quantum computer while constructing a cohesive device design. We discuss many of the prominent techniques for implementing circuit-model quantum computing and introduce several new methods, with an emphasis on employing surface code quantum error correction. In doing so, we propose a new quantum computer architecture based on optical control of quantum dots. The timescales of physical hardware operations and logical, error-corrected quantum gates differ by several orders of magnitude. By dividing functionality into layers, we can design and analyze subsystems independently, demonstrating the value of our layered architectural approach. Using this concrete hardware platform, we provide resource analysis for executing fault-tolerant quantum algorithms for integer factoring and quantum simulation, finding that the quantum dot architecture we study could solve such problems on the timescale of days.Comment: 27 pages, 20 figure

Whole exome sequencing to identify genetic causes of short stature

BACKGROUND/AIMS: Short stature is a common reason for presentation to pediatric endocrinology clinics. However, for most patients, no cause for the short stature can be identified. As genetics plays a strong role in height, we sought to identify known and novel genetic causes of short stature. METHODS: We recruited 14 children with severe short stature of unknown etiology. We conducted whole exome sequencing of the patients and their family members. We used an analysis pipeline to identify rare non-synonymous genetic variants that cause the short stature. RESULTS: We identified a genetic cause of short stature in 5 of the 14 patients. This included cases of floating-harbor syndrome, Kenny-Caffey syndrome, the progeroid form of Ehlers-Danlos syndrome, as well as 2 cases of the 3-M syndrome. For the remaining patients, we have generated lists of candidate variants. CONCLUSIONS: Whole exome sequencing can help identify genetic causes of short stature in the context of defined genetic syndromes, but may be less effective in identifying novel genetic causes of short stature in individual families. Utilized in the clinic, whole exome sequencing can provide clinically relevant diagnoses for these patients. Rare syndromic causes of short stature may be underrecognized and underdiagnosed in pediatric endocrinology clinics

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.

Initial results from sequencing studies suggest that there are relatively few low-frequency (<5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency-large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant-common phenotype associations-11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (<5%), respectively, low frequency-large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P < 1 × 10(-06) (false discovery rate ∼5%)] and one of eight biomarker associations at P < 8 × 10(-10). Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect

Deletion of the dominant autoantigen in NZB mice with autoimmune hemolytic anemia : Effects on autoantibody and T-helper responses

Peer reviewedPublisher PD

Racial variation in baseline characteristics and wait times among patients undergoing bariatric surgery

BACKGROUND: Although bariatric surgery is the most effective treatment for obesity and weight-related comorbid diseases, utilization rates are disproportionately low among non-white patients. We sought to understand if variation in baseline characteristics or access to care exists between white and non-white patients. METHODS: Using a statewide bariatric-specific data registry, we evaluated all patients who underwent bariatric surgery between 2006 and 2020 and completed a preoperative baseline questionnaire, which included a question about self-identification of race. Patient characteristics, co-morbidities, and time from initial preoperative clinic evaluation to date of surgery were compared among racial groups. RESULTS: A total of 73,141 patients met inclusion criteria with 18,741 (25.5%) self-identified as non-white. These included Black/African American (n = 11,904), Hispanic (n = 3448), Asian (n = 121), Native Hawaiian/Pacific Islander (n = 41), Middle Eastern (n = 164), Multiple (n = 2047) and other (n = 608). Non-white males were the least represented group, accounting for only 4% of all bariatric cases performed. Non-white patients were more likely to be younger (43.0 years vs. 46.6 years, p \u3c 0.0001), disabled (16% vs. 11.4%, p \u3c 0.0001) and have Medicaid (8.4% vs. 3.8%, p \u3c 0.0001) when compared to white patients, despite having higher rates of college education (78.0% vs. 76.6, p \u3c 0.0001). In addition, median time from initial evaluation to surgery was also longer among non-white patients (157 days vs. 127 days, p \u3c 0.0001), despite having higher rates of patients with a body mass index above 50 kg/m(2) (39.0% vs. 33.2%, p \u3c 0.0001). CONCLUSIONS: Non-white patients undergoing bariatric surgery represent an extremely diverse group of patients with more socioeconomic disadvantages and longer wait times when compared to white patients despite presenting with higher rates of severe obesity. Current guidelines and referral patterns for bariatric surgery may not be equitable and need further examination when considering the management of obesity within diverse populations to reduce disparities in care-of which non-white males are particularly at risk

Evidence for Sub-Chandrasekhar Type Ia Supernovae from Stellar Abundances in Dwarf Galaxies

There is no consensus on the progenitors of Type Ia supernovae (SNe Ia) despite their importance for cosmology and chemical evolution. We address this question using our previously published catalogs of Mg, Si, Ca, Cr, Fe, Co, and Ni abundances in dwarf galaxy satellites of the Milky Way (MW) to constrain the mass at which the white dwarf (WD) explodes during a typical SN Ia. We fit a simple bi-linear model to the evolution of [X/Fe] with [Fe/H], where X represents each of the elements mentioned above. We use the evolution of [Mg/Fe] coupled with theoretical supernova yields to isolate what fraction of the elements originated in SNe Ia. Then, we infer the [X/Fe] yield of SNe Ia for all of the elements except Mg. We compare these observationally inferred yields to recent theoretical predictions for two classes of Chandrasekhar-mass (M_(Ch)) SN Ia as well as sub-M_(Ch) SNe Ia. Most of the inferred SN Ia yields are consistent with all of the theoretical models, but [Ni/Fe] is consistent only with sub-M_(Ch) models. We conclude that the dominant type of SN Ia in ancient dwarf galaxies is the explosion of a sub-M_(Ch) WD. The MW and dwarf galaxies with extended star formation histories have higher [Ni/Fe] abundances, which could indicate that the dominant class of SN Ia is different for galaxies where star formation lasted for at least several Gyr

Isolation of Cerebral Capillaries from Fresh Human Brain Tissue

Understanding blood-brain barrier function under physiological and pathophysiological conditions is critical for the development of new therapeutic strategies that hold the promise to enhance brain drug delivery, improve brain protection, and treat brain disorders. However, studying the human blood-brain barrier function is challenging. Thus, there is a critical need for appropriate models. In this regard, brain capillaries isolated from human brain tissue represent a unique tool to study barrier function as close to the human in vivo situation as possible. Here, we describe an optimized protocol to isolate capillaries from human brain tissue at a high yield and with consistent quality and purity. Capillaries are isolated from fresh human brain tissue using mechanical homogenization, density-gradient centrifugation, and filtration. After the isolation, the human brain capillaries can be used for various applications including leakage assays, live cell imaging, and immune-based assays to study protein expression and function, enzyme activity, or intracellular signaling. Isolated human brain capillaries are a unique model to elucidate the regulation of the human blood-brain barrier function. This model can provide insights into central nervous system (CNS) pathogenesis, which will help the development of therapeutic strategies for treating CNS disorders