Merged magnetic resonance and light sheet microscopy of the whole mouse brain.

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 µm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 µm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 µm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

Homologous chromosome pairing: The linchpin of accurate segregation in meiosis.

Meiosis is a specialized cell division that occurs in sexually reproducing organisms, generating haploid gametes containing half the chromosome number through two rounds of cell division. Homologous chromosomes pair and prepare for their proper segregation in subsequent divisions. How homologous chromosomes recognize each other and achieve pairing is an important question. Early studies showed that in most organisms, homologous pairing relies on homologous recombination. However, pairing mechanisms differ across species. Evidence indicates that chromosomes are dynamic and move during early meiotic stages, facilitating pairing. Recent studies in various model organisms suggest conserved mechanisms and key regulators of homologous chromosome pairing. This review summarizes these findings and compare similarities and differences in homologous chromosome pairing mechanisms across species.

Efficient assembly and anti-tumor evaluation of novel polycyclic [1,2-a]-fused indoles.

Structurally diverse cyclopenta[4,5]pyrrolo[1,2-a]indoles heterocycles were smoothly constructed in good to excellent yields (up to 99 %) with excellent diastereoselectivities (>19:1 dr) through a novel and facile strategy based on BF3-catalyzed Friedel-Crafts alkylation/Aldol/Dehydrative cyclization cascade reaction. The anti-proliferative activity of these newly synthesized polycyclic indoles was screened, and all the functionalized reductive derivatives exhibited favorable anti-tumor activity. Notably, compound 4ae displayed the remarkable inhibitory activity against MCF-7 and HeLa cells with IC50 values of 4.62 µM and 7.71 µM, respectively. Mechanistically, the representative compound 4ae could effectively induce apoptosis of MCF-7 cells in crediting to up-regulate the relative expression of apoptotic protein BAX/Bcl-2, subsequently activate Pro-caspase 9 and cleave PARP, simultaneously block the cell cycle through down- and up-regulate the expression of cyclin B1 and p53, respectively. Moreover, compound 4ae also exhibited promising antineoplastic efficacy in subcutaneous MCF-7 xenograft mice which manifest significant shrunken tumors conspicuous nuclear apoptotic signal and minimal systemic toxicity. This strategy not only established a novel and efficient method for the assembly of structurally complex indole heterocycles, but also provided a series of compounds possessing attractive anti-cancer activity, which holds immense potential for future biomedical applications.

Analyzing clustered continuous response variables with ordinal regression models.

Continuous response data are regularly transformed to meet regression modeling assumptions. However, approaches taken to identify the appropriate transformation can be ad hoc and can increase model uncertainty. Further, the resulting transformations often vary across studies leading to difficulties with synthesizing and interpreting results. When a continuous response variable is measured repeatedly within individuals or when continuous responses arise from clusters, analyses have the additional challenge caused by within-individual or within-cluster correlations. We extend a widely used ordinal regression model, the cumulative probability model (CPM), to fit clustered, continuous response data using generalized estimating equations for ordinal responses. With the proposed approach, estimates of marginal model parameters, cumulative distribution functions , expectations, and quantiles conditional on covariates can be obtained without pretransformation of the response data. While computational challenges arise with large numbers of distinct values of the continuous response variable, we propose feasible and computationally efficient approaches to fit CPMs under commonly used working correlation structures. We study finite sample operating characteristics of the estimators via simulation and illustrate their implementation with two data examples. One studies predictors of CD4:CD8 ratios in a cohort living with HIV, and the other investigates the association of a single nucleotide polymorphism and lung function decline in a cohort with early chronic obstructive pulmonary disease.

Comparative genomic analysis reveals the potential transmission of Vibrio parahaemolyticus from freshwater food to humans.

Vibrio parahaemolyticus is an increasingly important foodborne pathogen that cause acute gastroenteritis in humans. However, the prevalence and transmission of this pathogen in freshwater food remains unclear. This study aimed to determine the molecular characteristics and genetic relatedness of V. parahaemolyticus isolates obtained from freshwater food, seafood, environmental, and clinical samples. A total of 138 (46.6%) isolates were detected from 296 food and environmental samples, and 68 clinical isolates from patients. Notably, V. parahaemolyticus was more prevalent in freshwater food (56.7%, 85/150) than in seafood (38.8%, 49/137). Virulence phenotype analyses revealed that the high motility of isolates from freshwater food (40.0%) and clinical isolates (42.0%) was higher than that of isolates from seafood (12.2%), whereas the biofilm-forming capacity of freshwater food isolates (9.4%) was lower than that of seafood (22.4%) and clinical isolates (15.9%). Virulence genes analysis showed that 46.4% of the clinical isolates contained the tdh gene encoding thermostable direct hemolysin (TDH) and only two freshwater food isolates contained the trh gene encoding TDH-related hemolysin (TRH). Multilocus sequence typing (MLST) analysis divided the 206 isolates into 105 sequence types (STs), including 56 (53.3%) novel STs. ST2583, ST469, and ST453 have been isolated from freshwater food and clinical samples. Whole-genome sequence (WGS) analyses revealed that the 206 isolates were divided into five clusters. Cluster II contained isolates from freshwater food and clinical samples, whereas the other clusters contained isolates from seafood, freshwater food, and clinical samples. In addition, we observed that ST2516 had the same virulence pattern, with a close phylogenetic relationship to ST3. The increased prevalence and adaption of V. parahaemolyticus in freshwater food is a potential cause of clinical cases closely related to the consumption of V. parahaemolyticus contaminated freshwater food.

Dynamic wavelength calibration based on synchrosqueezed wavelet transform.

With the developments of the tunable laser source (TLS), there are increasing demands for high-resolution dynamic wavelength calibration in recent years. Considering mutual constraints between wide measurement range and high calibration resolution, we propose a dynamic wavelength calibration method based on an auxiliary Mach-Zehnder interferometer (MZI) and the synchrosqueezed wavelet transform (SSWT). Our proposed method can achieve a calibration resolution of 5 fm and a tuning range of 10 nm. Moreover, the measurement range and spatial resolution of the optical frequency domain reflectometer (OFDR) system are improved to ∼80 m and ∼mm, respectively. Our proposed approach can substantially reduce the subtle spectrum distortion (tens of fm) in coherent optical spectrum analyzer (COSA) systems.

Nonlinear correction of a laser scanning interference system based on a fiber ring resonator.

The laser scanning interferometry system has been successfully applied to many measurement fields because of its efficient measurement ability. However, the practical application ability of this measurement method is restricted due to the laser tuning nonlinearity. In this paper, the fiber ring resonator is equidistant in the frequency domain, which is used as the external clock signal to resample the main interference signal so as to realize the equifrequency sampling of the laser scanning interference system and correct the tuning nonlinearity. The final experimental result shows that this method can effectively reduce the phase noise caused by tuning nonlinearity and improve the performance of the system.

Generalized Cross-Correlation Strain Demodulation Method Based on Local Similar Spectral Scanning.

Optical fiber measurement technology is widely used in the strength testing of buildings, the health testing of industrial equipment, and the minimally invasive surgery of modern medical treatment due to its characteristics of free calibration, high precision, and small size. This paper presents an algorithm that can improve the range and stability of strain measurements in order to solve the problems of the small range and measurement failure of optical fiber strain sensors based on optical frequency-domain reflectometry (OFDR). Firstly, a Rayleigh scattering model based on the refractive index perturbation of an optical fiber is proposed to study the characteristics of Rayleigh scattering and to guide the strain demodulation algorithm based on the spectral shift. Secondly, a local similar scanning method that can maintain a high similarity by monitoring local Rayleigh scattering signals (LSs) before and after strain is proposed. Thirdly, a generalized cross-correlation algorithm is proposed to detect spectral offset, solving the problem of demodulation failure in the case of a Rayleigh scattering signal with a low signal-to-noise ratio. Experiments show that the proposed method still has high stability when the spatial resolution is 3 mm. The measurement precision is 6.2 µÎµ, which proves that the multi-peaks or pseudo-peaks of the traditional algorithm in the case of a large strain, the high spatial resolution, and the poor signal-to-noise ratio are solved, and the stability of the strain measurement process is improved.

High resolution coherent spectral analysis method based on Brillouin scattering in an optical fiber.

High-resolution optical spectral analysis method is of significant importance for those who want to explore the physical world from the frequency domain. Aiming at the resolution degradation of classical coherent optical spectrum analysis (COSA) caused by the mirror phenomenon, this paper modifies the COSA system by introducing two homologous Brillouin scattering beams to serve as the pre-filter and local oscillator (LO), respectively. The central frequencies of the pre-filtered signal and the LO are locked by the Brillouin frequency shifts of those two Brillouin scattering beams. By means of this modification, the pre-filtered signal is located at either the upper-frequency-shifted side or the lower-frequency-shifted sides of the LO but could not exist on both sides of the LO. The proposed method could cancel the mirror phenomenon and thus improve the systematic resolution to 1.3 MHz in theory and 2 MHz in practice.

Enhanced dielectric and conductivity properties of carbon-coated SiC nanocomposites in the terahertz frequency range.

C-coated SiC nanocomposites (SiC@C NCs) were one-step synthesized under a mixture atmosphere of Ar and CH4 using a DC arc-discharge plasma method. The microstructure of the composites could be controlled by varying the volume ratio of Ar and CH4. A strong response to the terahertz (THz) field was observed due to the existence of a graphite shell. The dielectric properties of SiC@C NCs can be enhanced by altering the thickness of the graphite shell. The thicker graphite shell results in a stronger absorption of THz waves and an enhanced real part of conductivity. Fitting the measured conductivity data using the Drude-Smith model reveals that the carrier transport in the SiC@C NCs and its counterpart, the SiC nanoparticles, is dominated by backscattering. The SiC@C NCs with enhanced conductivity are believed to be fundamental materials for various functionalized optoelectronic devices.

Prevalence and Characteristics of Salmonella spp. from a Pig Farm in Shanghai, China.

Salmonella spp. is a major foodborne pathogen that is distributed among most pork production chains worldwide. This study aimed to investigate the dynamic changes in Salmonella spp. along the pig breeding process monthly from April 2018 to March 2019 in a pig farm in Shanghai, China, and identify the potential critical control points during the production. In total, 239 Salmonella spp. isolates were obtained from 1389 samples, in which Salmonella were detected from 26.3% (222/843) of fecal samples, 7.1% (17/240) of feed samples, and 0.0% (0/306) of both water and insect samples. Seven different serotypes were identified, with the predominant serotype being Salmonella Derby (21.8%), followed by Salmonella Typhimurium (18.8%), Salmonella Rissen (16.3%), Salmonella Mbandaka (12.6%), and Salmonella 1,4,[5],12:i:- (11.8%). Most probable number (MPN) analysis revealed that the load of Salmonella spp. gradually increased along the pig production chain, while the highest number of Salmonella spp. isolates was at the fattening stage (MPN value, 11-15 MPN/g). The pulsed-field gel electrophoresis showed that both Salmonella Typhimurium and Salmonella Derby isolates were grouped to six clusters. The antimicrobial resistance analyzed demonstrated that 80.0% of the isolates were of multidrug resistance and resistant to sulfamethoxazole (84.5%), lincomycin (89.4%), ampicillin (96.9%), oxytetracycline (93.8%), and tetracycline (95.1%). We further evaluated the Salmonella spp. Resistance to quaternary ammonium compounds (QACs) showed an increasing trend along with the testing period indicating that the use of QACs could induce the resistance of Salmonella spp. to QACs. Our study confirmed the dynamic changes in Salmonella spp. over time and space in this pig farm and identified feed and the fattening house as the key points for the prevention and control of Salmonella spp. contamination.

An empirical comparison of two novel transformation models.

Continuous response variables are often transformed to meet modeling assumptions, but the choice of the transformation can be challenging. Two transformation models have recently been proposed: semiparametric cumulative probability models (CPMs) and parametric most likely transformation models (MLTs). Both approaches model the cumulative distribution function and require specifying a link function, which implicitly assumes that the responses follow a known distribution after some monotonic transformation. However, the two approaches estimate the transformation differently. With CPMs, an ordinal regression model is fit, which essentially treats each continuous response as a unique category and therefore nonparametrically estimates the transformation; CPMs are semiparametric linear transformation models. In contrast, with MLTs, the transformation is parameterized using flexible basis functions. Conditional expectations and quantiles are readily derived from both methods on the response variable's original scale. We compare the two methods with extensive simulations. We find that both methods generally have good performance with moderate and large sample sizes. MLTs slightly outperformed CPMs in small sample sizes under correct models. CPMs tended to be somewhat more robust to model misspecification and outcome rounding. Except in the simplest situations, both methods outperform basic transformation approaches commonly used in practice. We apply both methods to an HIV biomarker study.

The dynamic recruitment of LAB proteins senses meiotic chromosome axis differentiation in C. elegans.

During meiosis, cohesin and meiosis-specific proteins organize chromatin into an axis-loop architecture, coordinating homologous synapsis, recombination, and ordered chromosome segregation. However, how the meiotic chromosome axis is assembled and differentiated with meiotic progression remains elusive. Here, we explore the dynamic recruitment of two long arms of the bivalent proteins, LAB-1 and LAB-2, in Caenorhabditis elegans. LAB proteins directly interact with the axis core HORMA complexes and weak interactions contribute to their recruitment. LAB proteins phase separate in vitro, and this capacity is promoted by HORMA complexes. During early prophase, synapsis oppositely regulates the axis enrichment of LAB proteins. After the pachytene exit, LAB proteins switch from a reciprocal localization pattern to a colocalization pattern, and the normal dynamic pattern of LAB proteins is altered in meiotic mutants. We propose that LAB recruitment senses axis differentiation, and phase separation of meiotic structures helps subdomain establishment and accurate segregation of the chromosomes.

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain.

We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 µm resolution (∼ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

Effects of Tai Chi on Lung Function, Exercise Capacity and Psychosocial Outcomes in Patients With Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials.

Objectives: To explore whether tai chi can improve lung function, exercise capacity, and health-related outcomes in patients with chronic obstructive pulmonary disease (COPD). Methods: The PubMed, Embase, Cochrane Central Register of Controlled Trials, Chinese National Knowledge Infrastructure (CNKI), Wanfang, and China Science and Technology Journal Database (VIP) databases were searched from inception to January 5, 2023. The methodological quality of the included studies was evaluated according to the Cochrane Handbook for Systematic Reviews of Interventions criteria. Results: A total of 1430 participants from 20 randomized controlled trials were included in this review. The results indicated significant effects of tai chi on FEV1, 6WMD, anxiety, and quality of life (p < 0.01), but not on FEV1%, FEVI/FVC, depression, and social support. Conclusions: Tai chi might be a potential alternative therapy to improve FEV1, 6WMD, anxiety, and quality of life for patients with COPD.

Asymptotic Properties for Cumulative Probability Models for Continuous Outcomes.

Regression models for continuous outcomes frequently require a transformation of the outcome, which is often specified a priori or estimated from a parametric family. Cumulative probability models (CPMs) nonparametrically estimate the transformation by treating the continuous outcome as if it is ordered categorically. They thus represent a flexible analysis approach for continuous outcomes. However, it is difficult to establish asymptotic properties for CPMs due to the potentially unbounded range of the transformation. Here we show asymptotic properties for CPMs when applied to slightly modified data where bounds, one lower and one upper, are chosen and the outcomes outside the bounds are set as two ordinal categories. We prove the uniform consistency of the estimated regression coefficients and of the estimated transformation function between the bounds. We also describe their joint asymptotic distribution, and show that the estimated regression coefficients attain the semiparametric efficiency bound. We show with simulations that results from this approach and those from using the CPM on the original data are very similar when a small fraction of the data are modified. We reanalyze a dataset of HIV-positive patients with CPMs to illustrate and compare the approaches.

A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology.

Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues in a mouse model by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and both global and regional deformations. 4. Implement stereological protocols for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cell densities of one brain region in less than 1 min and is highly replicable in cortical and subcortical gray matter regions and structures throughout the brain. This method demonstrates the advantage of not requiring an extensive amount of training data, achieving a F1 score of approximately 0.9 with just 20 training nuclei. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57BL/6J cases and 2 BXD strains. The data represent the variability among specimens for the same brain region and across regions within the specimen. Neuronal densities estimated with our workflow are within the range of values in previous classical stereological studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications for studies of how genetics, environment, and development across the lifespan impact cell numbers in the CNS.

A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology.

Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or can be a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues of by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label all neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and morphological deformations. 4. Implement novel protocol for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cells density of one brain region in less than 1 min and is highly replicable to cortical and subcortical gray matter regions and structures throughout the brain. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57B6/6J and 2 BXD strains. The data represent the variability among cases for the same brain region and across regions within case. Our data are consistent with previous studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications in how genetics, environment, and development across the lifespan impact brain structure.