Modulation of deep neural circuits with sonogenetics.

Noninvasive control of neuronal activity in the deep brain can be illuminating for probing brain function and treating dysfunctions. Here, we present a sonogenetic approach for controlling distinct mouse behavior with circuit specificity and subsecond temporal resolution. Targeted neurons in subcortical regions were made to express a mutant large conductance mechanosensitive ion channel (MscL-G22S), enabling ultrasound to trigger activity in MscL-expressing neurons in the dorsal striatum and increase locomotion in freely moving mice. Ultrasound stimulation of MscL-expressing neurons in the ventral tegmental area could activate the mesolimbic pathway to trigger dopamine release in the nucleus accumbens and modulate appetitive conditioning. Moreover, sonogenetic stimulation of the subthalamic nuclei of Parkinson's disease model mice improved their motor coordination and mobile time. Neuronal responses to ultrasound pulse trains were rapid, reversible, and repeatable. We also confirmed that the MscL-G22S mutant is more effective to sensitize neurons to ultrasound compared to the wild-type MscL. Altogether, we lay out a sonogenetic approach which can selectively manipulate targeted cells to activate defined neural pathways, affect specific behaviors, and relieve symptoms of neurodegenerative disease.

The mechanosensitive ion channel Piezo1 contributes to ultrasound neuromodulation.

Transcranial low-intensity ultrasound is a promising neuromodulation modality, with the advantages of noninvasiveness, deep penetration, and high spatiotemporal accuracy. However, the underlying biological mechanism of ultrasonic neuromodulation remains unclear, hindering the development of efficacious treatments. Here, the well-known Piezo1 was studied through a conditional knockout mouse model as a major mediator for ultrasound neuromodulation ex vivo and in vivo. We showed that Piezo1 knockout (P1KO) in the right motor cortex of mice significantly reduced ultrasound-induced neuronal calcium responses, limb movement, and muscle electromyogram (EMG) responses. We also detected higher Piezo1 expression in the central amygdala (CEA), which was found to be more sensitive to ultrasound stimulation than the cortex was. Knocking out the Piezo1 in CEA neurons showed a significant reduction of response under ultrasound stimulation, while knocking out astrocytic Piezo1 showed no-obvious changes in neuronal responses. Additionally, we excluded an auditory confound by monitoring auditory cortical activation and using smooth waveform ultrasound with randomized parameters to stimulate P1KO ipsilateral and contralateral regions of the same brain and recording evoked movement in the corresponding limb. Thus, we demonstrate that Piezo1 is functionally expressed in different brain regions and that it is an important mediator of ultrasound neuromodulation in the brain, laying the ground for further mechanistic studies of ultrasound.

Gene Doping Control Analysis of Human Erythropoietin Transgene in Equine Plasma by PCR-Liquid Chromatography High-Resolution Tandem Mass Spectrometry.

Gene doping involves the misuse of genetic materials to alter an athlete's performance, which is banned at all times in both human and equine sports. Quantitative polymerase chain reaction (qPCR) assays have been used to control the misuse of transgenes in equine sports. Our laboratory recently developed and implemented duplex as well as multiplex qPCR assays for transgenes detection. To further advance gene doping control, we have developed for the first time a sensitive and definitive PCR-liquid chromatography high-resolution tandem mass spectrometry (PCR-LC-HRMS/MS) method for transgene detection with an estimated limit of detection of below 100 copies/mL for the human erythropoietin (hEPO) transgene in equine plasma. The method involved magnetic-glass-particle-based extraction of DNA from equine plasma prior to PCR amplification with 2'-deoxyuridine 5'-triphosphate (dUTP) followed by treatments with uracil DNA glycosylase and hot piperidine for selective cleavage to give small oligonucleotide fragments. The resulting DNA fragments were then analyzed by LC-HRMS/MS. The applicability of this method has been demonstrated by the successful detection of hEPO transgene in a blood sample collected from a gelding (castrated male horse) that had been administered the transgene. This novel approach not only serves as a complementary method for transgene detection but also paves the way for developing a generic PCR-LC-HRMS/MS method for the detection of multiple transgenes.

SM03, an Anti-CD22 Antibody, Converts Cis-to-Trans Ligand Binding of CD22 against α2,6-Linked Sialic Acid Glycans and Immunomodulates Systemic Autoimmune Diseases.

SM03, an anti-CD22 recombinant IgG1 mAb, is currently in a phase III clinical trial for the treatment of rheumatoid arthritis (NCT04312815). SM03 showed good safety and efficacy in phase I systemic lupus erythematosus and phase II moderate to severe rheumatoid arthritis clinical trials. We propose the success of SM03 as a therapeutic to systemic autoimmune diseases is through the utilization of a novel mechanism of action unique to SM03. CD22, an inhibitory coreceptor of the BCR, is a potential immunotherapeutic target against autoimmune diseases. SM03 could disturb the CD22 homomultimeric configuration through disrupting cis binding to α2,6-linked sialic acids, induce rapid internalization of CD22 from the cell surface of human B cells, and facilitate trans binding between CD22 to human autologous cells. This in turn increased the activity of the downstream immunomodulatory molecule Src homology region 2 domain-containing phosphatase 1 (SHP-1) and decreased BCR-induced NF-κB activation in human B cells and B cell proliferation. This mechanism of action gives rationale to support the significant amelioration of disease and good safety profile in clinical trials, as by enabling the "self" recognition mechanism of CD22 via trans binding to α2,6 sialic acid ligands on autologous cells, SM03 specifically restores immune tolerance of B cells to host tissues without affecting the normal B cell immune response to pathogens.

Activation of N-Methyl-D-aspartate receptor contributed to the ultrasonic modulation of neurons in vitro.

Ultrasound stimulation is increasingly used to investigate brain function and treat brain diseases due to its high level of safety and precise spatiotemporal resolution. Therefore, it is crucial to understand the underlying mechanisms involved in ultrasound brain stimulation. In this study, we investigate the role of NMDA receptors in mediating the effects of ultrasound on primary hippocampal neurons in mice. Our results show that ultrasound alone can activate heterologous NMDA receptor subunits, including NR1A, NR2A, and NR2B, in 293T cells, as well as endogenous NMDA receptors in primary neurons. This activation leads to an influx of calcium and an increase in nuclear c-Fos expression in primary neurons that have not been pre-treated with an NMDA receptor inhibitor. In conclusion, our findings demonstrate that NMDA receptors contribute to neuronal activation by ultrasound stimulation in vitro, providing insight into the molecular mechanisms of ultrasound neuromodulation and a new mediator for the sonogenetics technique.

Theoretical Simulations of Kinetic Isotope Effects on Decarboxylation of 3-Carboxybenzisoxazole.

Kinetic isotope effect values on the decarboxylation of 3-carboxybenzisoxazole have been computed using the second-order Kleinert's variational perturbation theory in the framework of Feynman's path integrals along with the potential energy surface obtained at the MP2/6-31+G(d) level. Good agreement with the experimental data was obtained, demonstrating that this novel computational approach for computing KIE values of organic reaction is a viable alternative to the traditional method employing the Bigeleisen equation and harmonic vibrational frequencies. Compared with the experimental measurements, consideration of anharmonicity and tunneling effects can significantly improve the calculated KIE values, reducing the root-mean-square deviation from 1.19 % for traditional method to 0.20 % for path-integral method.

A semiparametric joint model for cluster size and subunit-specific interval-censored outcomes.

Clustered data frequently arise in biomedical studies, where observations, or subunits, measured within a cluster are associated. The cluster size is said to be informative, if the outcome variable is associated with the number of subunits in a cluster. In most existing work, the informative cluster size issue is handled by marginal approaches based on within-cluster resampling, or cluster-weighted generalized estimating equations. Although these approaches yield consistent estimation of the marginal models, they do not allow estimation of within-cluster associations and are generally inefficient. In this paper, we propose a semiparametric joint model for clustered interval-censored event time data with informative cluster size. We use a random effect to account for the association among event times of the same cluster as well as the association between event times and the cluster size. For estimation, we propose a sieve maximum likelihood approach and devise a computationally-efficient expectation-maximization algorithm for implementation. The estimators are shown to be strongly consistent, with the Euclidean components being asymptotically normal and achieving semiparametric efficiency. Extensive simulation studies are conducted to evaluate the finite-sample performance, efficiency and robustness of the proposed method. We also illustrate our method via application to a motivating periodontal disease dataset.

PENALIZED REGRESSION FOR MULTIPLE TYPES OF MANY FEATURES WITH MISSING DATA.

Recent technological advances have made it possible to measure multiple types of many features in biomedical studies. However, some data types or features may not be measured for all study subjects because of cost or other constraints. We use a latent variable model to characterize the relationships across and within data types and to infer missing values from observed data. We develop a penalized-likelihood approach for variable selection and parameter estimation and devise an efficient expectation-maximization algorithm to implement our approach. We establish the asymptotic properties of the proposed estimators when the number of features increases at a polynomial rate of the sample size. Finally, we demonstrate the usefulness of the proposed methods using extensive simulation studies and provide an application to a motivating multi-platform genomics study.

Penalized estimation of a class of single-index varying-coefficient models for integrative genomic analysis.

Recent technological advances have made it possible to collect high-dimensional genomic data along with clinical data on a large number of subjects. In the studies of chronic diseases such as cancer, it is of great interest to integrate clinical and genomic data to build a comprehensive understanding of the disease mechanisms. Despite extensive studies on integrative analysis, it remains an ongoing challenge to model the interaction effects between clinical and genomic variables, due to high dimensionality of the data and heterogeneity across data types. In this paper, we propose an integrative approach that models interaction effects using a single-index varying-coefficient model, where the effects of genomic features can be modified by clinical variables. We propose a penalized approach for separate selection of main and interaction effects. Notably, the proposed methods can be applied to right-censored survival outcomes based on a Cox proportional hazards model. We demonstrate the advantages of the proposed methods through extensive simulation studies and provide applications to a motivating cancer genomic study.

Semiparametric regression analysis of doubly-censored data with applications to incubation period estimation.

The incubation period is a key characteristic of an infectious disease. In the outbreak of a novel infectious disease, accurate evaluation of the incubation period distribution is critical for designing effective prevention and control measures . Estimation of the incubation period distribution based on limited information from retrospective inspection of infected cases is highly challenging due to censoring and truncation. In this paper, we consider a semiparametric regression model for the incubation period and propose a sieve maximum likelihood approach for estimation based on the symptom onset time, travel history, and basic demographics of reported cases. The approach properly accounts for the pandemic growth and selection bias in data collection. We also develop an efficient computation method and establish the asymptotic properties of the proposed estimators. We demonstrate the feasibility and advantages of the proposed methods through extensive simulation studies and provide an application to a dataset on the outbreak of COVID-19.

Analysis of clustered interval-censored data using a class of semiparametric partly linear frailty transformation models.

A flexible class of semiparametric partly linear frailty transformation models is considered for analyzing clustered interval-censored data, which arise naturally in complex diseases and dental research. This class of models features two nonparametric components, resulting in a nonparametric baseline survival function and a potential nonlinear effect of a continuous covariate. The dependence among failure times within a cluster is induced by a shared, unobserved frailty term. A sieve maximum likelihood estimation method based on piecewise linear functions is proposed. The proposed estimators of the regression, dependence, and transformation parameters are shown to be strongly consistent and asymptotically normal, whereas the estimators of the two nonparametric functions are strongly consistent with optimal rates of convergence. An extensive simulation study is conducted to study the finite-sample performance of the proposed estimators. We provide an application to a dental study for illustration.

SEMIPARAMETRIC LATENT-CLASS MODELS FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA.

In long-term follow-up studies, data are often collected on repeated measures of multivariate response variables as well as on time to the occurrence of a certain event. To jointly analyze such longitudinal data and survival time, we propose a general class of semiparametric latent-class models that accommodates a heterogeneous study population with flexible dependence structures between the longitudinal and survival outcomes. We combine nonparametric maximum likelihood estimation with sieve estimation and devise an efficient EM algorithm to implement the proposed approach. We establish the asymptotic properties of the proposed estimators through novel use of modern empirical process theory, sieve estimation theory, and semiparametric efficiency theory. Finally, we demonstrate the advantages of the proposed methods through extensive simulation studies and provide an application to the Atherosclerosis Risk in Communities study.

Pulmonary Complications in Premature Infants Using a Beractant or Poractant for Respiratory Distress Syndrome: A Retrospective Cohort Study.

OBJECTIVE: Premature infants are at the risk of developing respiratory distress syndrome (RDS). Beractants and poractants are two commonly used natural surfactants. This retrospective cohort study aims to compare the incidence of pulmonary complications between beractant and poractant treatment groups. STUDY DESIGN: This study evaluated 29 patients treated with beractant and 49 patients treated with poractant. The primary outcome was the incidence of air leak syndrome (ALS) and pulmonary hemorrhage. Secondary outcomes included mortality and pulmonary outcomes, such as mechanical ventilation duration, oxygen dependence duration, fraction of inspired oxygen, and mean airway pressure (MAP) requirement. Logistic regression analyses were conducted to identify independent risk factors for significant primary outcomes. RESULTS: No significant difference was found in the demographics between the two groups. A significantly higher incidence of pulmonary hemorrhage was observed in the poractant group (14.3 vs. 0.0%, p = 0.038). The difference in the incidence of ALS between the groups was insignificant (p = 0.536). Logistic regression for the incidence of pulmonary hemorrhage identified coagulopathy as the only significant independent risk factor (odds ratio 39.855, 95% confidence interval [2.912-545.537]; p = 0.006). Secondary outcomes in both treatment groups were similar, except that patients in the poractant group had a higher MAP before surfactant therapy (9 vs. 8 cmH2O, p < 0.001). CONCLUSION: This study showed a significantly higher incidence of pulmonary hemorrhage in the poractant group. Coagulopathy was identified as an independent risk factor for pulmonary hemorrhage. Future long-term prospective studies are essential to establish the temporal and causal relationships between coagulopathy and pulmonary hemorrhage in premature infants receiving surfactant therapy for RDS; hence, there is the need for a screening protocol before surfactant administration. KEY POINTS: · A higher incidence of pulmonary hemorrhage was found in the poractant group.. · Coagulopathy was the only significant risk factor that was related to the incidence of pulmonary hemorrhage.. · A screening protocol might be useful to avoid pulmonary hemorrhage in infants receiving surfactant..

Chiral Symmetry Breaking for Deterministic Switching of Perpendicular Magnetization by Spin-Orbit Torque.

Symmetry breaking is a characteristic to determine which branch of a bifurcation system follows upon crossing a critical point. Specifically, in spin-orbit torque (SOT) devices, a fundamental question arises: how can the symmetry of the perpendicular magnetic moment be broken by the in-plane spin polarization? Here, we show that the chiral symmetry breaking by the antisymmetric Dzyaloshinskii-Moriya interaction (DMI) can induce the deterministic SOT switching of the perpendicular magnetization. By introducing a gradient of saturation magnetization or magnetic anisotropy, the dynamic noncollinear spin textures are formed under the current-driven SOT, and thus, the chiral symmetry of these dynamic spin textures is broken by the DMI, resulting in the deterministic magnetization switching. We introduce a strategy to induce an out-of-plane (z) gradient of magnetic properties as a practical solution for the wafer-scale manufacture of SOT devices.

Marginal analysis of current status data with informative cluster size using a class of semiparametric transformation cure models.

This research is motivated by a periodontal disease dataset that possesses certain special features. The dataset consists of clustered current status time-to-event observations with large and varying cluster sizes, where the cluster size is associated with the disease outcome. Also, heavy censoring is present in the data even with long follow-up time, suggesting the presence of a cured subpopulation. In this paper, we propose a computationally efficient marginal approach, namely the cluster-weighted generalized estimating equation approach, to analyze the data based on a class of semiparametric transformation cure models. The parametric and nonparametric components of the model are estimated using a Bernstein-polynomial based sieve maximum pseudo-likelihood approach. The asymptotic properties of the proposed estimators are studied. Simulation studies are conducted to evaluate the performance of the proposed estimators in scenarios with different degree of informative clustering and within-cluster dependence. The proposed method is applied to the motivating periodontal disease data for illustration.

Comparison of the Efficiency and Usability of Aerosol Box and Intubation Tent on Intubation of a Manikin Using Personal Protective Equipment: A Randomized Crossover Study.

BACKGROUND: The aerosol box and intubation tent are improvised barrier-enclosure devices developed during the novel coronavirus pandemic to protect health care workers from aerosol transmission. OBJECTIVE: Using time to intubation as a crude proxy, we aimed to compare the efficiency and usability of the aerosol box and intubation tent in a simulated manikin. METHODS: This was a single-center, randomized, crossover manikin study involving 28 participants (9 anesthetists, 16 emergency physicians, and 3 intensivists). Each participant performed rapid sequence intubations in a random sequence of three different scenarios: 1) no device use; 2) aerosol box; 3) intubation tent. We compared the time to intubation between different scenarios. RESULTS: The median total intubation time with no device use, aerosol box, and intubation tent were 23.7 s (interquartile range [IQR] 19.4-28.4 s), 30.9 s (IQR 24.1-52.5 s), and 26.0 s (IQR 22.1-30.8 s), respectively. Post hoc analysis showed a significantly longer intubation time using the aerosol box compared with no device use (p < 0.001) and compared with the intubation tent (p < 0.001). The difference between the intubation tent and no device use was not significant. The first-pass intubation success rate did not differ between the groups. Only aerosol box use had resulted in breaches of personal protective equipment. Participants considered intubation with the intubation tent more favorable than the aerosol box. CONCLUSIONS: The intubation tent seems to have a better barrier-enclosure design than the aerosol box, with a reasonable balance between efficiency and usability. Further evaluation of its efficacy in preventing aerosol dispersal and in human studies are warranted prior to recommendation of widespread adoption.

Deterministic Spin-Orbit Torque Switching by a Light-Metal Insertion.

Spin-orbit torque (SOT) switching of magnetization is a promising emerging technology for nonvolatile spintronic memory and logic applications. However, deterministic switching of perpendicular magnetization with SOTs requires an additional symmetry breaking, which is typically provided by an external magnetic field, making it impractical for applications. In this work, we disclose that by the insertion of a slightly asymmetric light-metal layer at the heavy metal-ferromagnet interface of SOT heterostructures, current-induced out-of-plane effective magnetic fields are introduced that enable deterministic switching without an external magnetic field. We obtain uniform perpendicular magnetic anisotropy and switching current density despite the asymmetry of the light-metal layer, and we show the scalability of our approach by studying device sizes that differ by 2 orders of magnitude. Our work provides a practical route for utilization of SOTs for magnetization switching on the wafer scale and paves the way for the practical application of SOT-based technology.

Label-free Proteomics for Discovering Biomarker Candidates for Controlling Krypton Misuse in Castrated Horses (Geldings).

Recent advances in label-free quantitative proteomics may support its application in identifying and monitoring biomarkers for the purpose of doping control in equine sports. In this study, we developed a workflow of label-free quantitative proteomics to propose plasma protein biomarkers in horses after administration with krypton (Kr), a potential erythropoiesis-stimulating agent. Plasma proteomes were profiled by using nanoliquid chromatography-high-resolution mass spectrometry. An in-house mass spectral library consisting of 1121 proteins was compiled using samples collected from geldings (castrated horses) in the administration trial and geldings in training. A data-independent acquisition method was used to quantify an array of plasma proteins across plasma samples from the administration trial. Statistical analyses proposed a profile of 83 biomarker candidates that successfully differentiated Kr-administered samples from control samples, with the ability to detect Kr exposure for up to 13 days (the last sample collected in the administration trial). The model also correctly classified 32 in-training geldings as untreated controls. This is significantly longer than the 1 h detection time of plasma Kr using headspace gas chromatography-tandem mass spectrometry. Bioinformatic analyses enriched biomarker candidates relevant to complement activation and iron metabolism. The upregulation of transferrin receptor protein 1, one of the candidates related to iron metabolism, in plasma after Kr administration was validated by selected reaction monitoring of corresponding peptides. These results have demonstrated label-free quantitative proteomics as a promising approach to propose plasma protein biomarkers to enhance doping control. Data are available via ProteomeXchange with identifier PXD017262.

Direct Evidence of Void-Induced Structural Relaxations in Colloidal Glass Formers.

Particle dynamics in supercooled liquids are often dominated by stringlike motions in which lines of particles perform activated hops cooperatively. The structural features triggering these motions, crucial in understanding glassy dynamics, remain highly controversial. We experimentally study microscopic particle dynamics in colloidal glass formers at high packing fractions. With a small polydispersity leading to glass-crystal coexistence, a void in the form of a vacancy in the crystal can diffuse reversibly into the glass and further induces stringlike motions. In the glass, a void takes the form of a quasivoid consisting of a few neighboring free volumes and is transported by the stringlike motions it induces. In fully glassy systems with a large polydispersity, similar quasivoid actions are observed. The mobile particles cluster into stringlike or compact geometries, but the compact ones can be further broken down into connected sequences of strings, establishing their general importance.

Theoretical Simulations of Heavy-Atom Kinetic Isotope Effects in Aliphatic Claisen Rearrangement.

The aliphatic Claisen rearrangement of allyl vinyl ether has attracted great interest for its broad applications in chemical synthesis and biosynthesis. Although it is well agreed that this reaction proceeds via a concerted, "chair-like" transition state, certain inconsistencies of kinetic isotope effect (KIE) data between experimental measurements and theoretical simulations or between independent experiments indicate that the nature and mechanism of this important reaction need to be investigated in more detail. In order to verify two independent sets of experimental data, we present theoretical calculations on heavy-atom KIE values of alipahtic Claisen rearrangement, using our recently developed path-integral method with the second-order Kleinert's variational perturbation theory, which goes beyond the traditional method for computing KIE values by employing the Bigeleisen equation. Amazingly, the results demonstrate that both sets of experimental measurements are correct, while the inconsistency originates from the fact that the aliphatic Claisen rearrangement undergoes similar but different mechanisms in gas and solution phases. Different experimental conditions will alter the actual reactant state by tuning the population distribution of reactant conformers. According to the comparison between experimental and theoretical results, a more clear reaction mechanism of aliphatic Claisen rearrangement is revealed.