Human sperm rotate with a conserved direction during free swimming in four dimensions.

Head rotation in human spermatozoa is essential for different swimming modes and fertilisation, as it links the molecular workings of the flagellar beat with sperm motion in three-dimensional (3D) space over time. Determining the direction of head rotation has been hindered by the symmetry and translucent nature of the sperm head, and by the fast 3D motion driven by the helical flagellar beat. Analysis has been mostly restricted to two-dimensional (2D) single focal plane image analysis, which enables tracking of head centre position but not tracking of head rotation. Despite the conserved helical beating of the human sperm flagellum, human sperm head rotation has been reported to be uni- or bi-directional, and even to intermittently change direction in a given cell. Here, we directly measure the head rotation of freely swimming human sperm using multi-plane 4D (3D+t) microscopy and show that: (1) 2D microscopy is unable to distinguish head rotation direction in human spermatozoa; (2) head rotation direction in non-capacitating and capacitating solutions, for both aqueous and viscous media, is counterclockwise (CCW), as seen from head to tail, in all rotating spermatozoa, regardless of the experimental conditions; and (3) head rotation is suppressed in 36% of spermatozoa swimming in non-capacitating viscous medium, although CCW rotation is recovered after incubation in capacitating conditions within the same viscous medium, possibly unveiling an unexplored aspect of the essential need of capacitation for fertilisation. Our observations show that the CCW head rotation in human sperm is conserved. It constitutes a robust and persistent helical driving mechanism that influences sperm navigation in 3D space over time, and thus is of critical importance in cell motility, propulsion of flagellated microorganisms, sperm motility assessments, human reproduction research, and self-organisation of flagellar beating patterns and swimming in 3D space.

Phylogenetic biogeography inference using dynamic paleogeography models and explicit geographic ranges.

To model distribution ranges, the most popular methods of phylogenetic biogeography divide Earth into a handful of predefined areas. Other methods use explicit geographic ranges, but unfortunately, these methods assume a static Earth, ignoring the effects of plate tectonics and the changes in the landscape. To address this limitation, I propose a method that uses explicit geographic ranges and incorporates a plate motion model and a paleolandscape model directly derived from the models used by geologists in their tectonic and paleogeographic reconstructions. The underlying geographic model is a high-resolution pixelation of a spherical Earth. Biogeographic inference is based on diffusion, approximates the effects of the landscape, uses a time-stratified model to take into account the geographic changes, and directly integrates over all probable histories. By using a simplified stochastic mapping algorithm, it is possible to infer the ancestral locations as well as the distance traveled by the ancestral lineages. For illustration, I applied the method to an empirical phylogeny of the Sapindaceae plants. This example shows that methods based on explicit geographic data, coupled with high-resolution paleogeographic models, can provide detailed reconstructions of the ancestral areas but also include inferences about the probable dispersal paths and diffusion speed across the taxon history. The method is implemented in the program PhyGeo.

Efficient computation of N-point correlation functions in D dimensions.

We present efficient algorithms for computing the N-point correlation functions (NPCFs) of random fields in arbitrary D-dimensional homogeneous and isotropic spaces. Such statistics appear throughout the physical sciences and provide a natural tool to describe stochastic processes. Typically, algorithms for computing the NPCF components have [Formula: see text] complexity (for a dataset containing n particles); their application is thus computationally infeasible unless N is small. By projecting the statistic onto a suitably defined angular basis, we show that the estimators can be written in a separable form, with complexity [Formula: see text] or [Formula: see text] if evaluated using a Fast Fourier Transform on a grid of size [Formula: see text]. Our decomposition is built upon the D-dimensional hyperspherical harmonics; these form a complete basis on the [Formula: see text] sphere and are intrinsically related to angular momentum operators. Concatenation of [Formula: see text] such harmonics gives states of definite combined angular momentum, forming a natural separable basis for the NPCF. As N and D grow, the number of basis components quickly becomes large, providing a practical limitation to this (and all other) approaches: However, the dimensionality is greatly reduced in the presence of symmetries; for example, isotropic correlation functions require only states of zero combined angular momentum. We provide a Julia package implementing our estimators and show how they can be applied to a variety of scenarios within cosmology and fluid dynamics. The efficiency of such estimators will allow higher-order correlators to become a standard tool in the analysis of random fields.

Spherical nucleic acids as an infectious disease vaccine platform.

SignificanceUsing SARS-CoV-2 as a relevant case study for infectious disease, we investigate the structure-function relationships that dictate antiviral spherical nucleic acid (SNA) vaccine efficacy. We show that the SNA architecture can be rapidly employed to target COVID-19 through incorporation of the receptor-binding domain, and that the resulting vaccine potently activates human cells in vitro and mice in vivo. Furthermore, when challenged with a lethal viral infection, only mice treated with the SNA vaccine survived. Taken together, this work underscores the importance of rational vaccine design for infectious disease to yield vaccines that elicit more potent immune responses to effectively fight disease.

Constructing ZnTe Spherical Quantum Well for Efficient Light Emission.

ZnTe colloidal semiconductor nanocrystals (NCs) have shown promise for light-emitting diodes (LEDs) and displays, because they are free from toxic heavy metals (Cd). However, so far, their low photoluminescence (PL) efficiency (∼30%) has hindered their applications. Herein, we devised a novel structure of ZnTe NCs with the configuration of ZnSe (core)/ZnTe (spherical quantum well, SQW)/ZnSe (shell). The inner layer ZnTe was grown at the surface of ZnSe core with avoiding using highly active and high-risk Zn sources. Due to the formation of coherently strained heterostructure which reduced the lattice mismatch, and the thermodynamic growth of ZnTe, the surface or interface defects were suppressed. A high PL efficiency of >60% was obtained for the green light-emitting ZnSe/ZnTe/ZnSe SQWs after ZnS outer layer passivation, which is the highest value for colloidal ZnTe-based NCs. This work paves the way for the development of novel semiconductor NCs for luminescent and display applications.

DNA Anchoring Strength Directly Correlates with Spherical Nucleic Acid-Based HPV E7 Cancer Vaccine Potency.

Vaccination for cancers arising from human papillomavirus (HPV) infection holds immense potential, yet clinical success has been elusive. Herein, we describe vaccination studies involving spherical nucleic acids (SNAs) incorporating a CpG adjuvant and a peptide antigen (E711-19) from the HPV-E7 oncoprotein. Administering the vaccine to humanized mice induced immunity-dependent on the oligonucleotide anchor chemistry (cholesterol vs (C12)9). SNAs containing a (C12)9-anchor enhanced IFN-γ production >200-fold, doubled memory CD8+ T-cell formation, and delivered more than twice the amount of oligonucleotide to lymph nodes in vivo compared to a simple admixture. Importantly, the analogous construct with a weaker cholesterol anchor performed similar to admix. Moreover, (C12)9-SNAs activated 50% more dendritic cells and generated T-cells cytotoxic toward an HPV+ cancer cell line, UM-SCC-104, with near 2-fold greater efficiency. These observations highlight the pivotal role of structural design, and specifically oligonucleotide anchoring strength (which correlates with overall construct stability), in developing efficacious therapeutic vaccines.

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.

BACKGROUND: Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge. RESULTS: Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs. CONCLUSIONS: Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer. AVAILABILITY AND IMPLEMENTATION: https://github.com/scutdy/SSO/blob/master/SEEI.zip .

Semi-analytic three-shell forward calculation for magnetoencephalography.

In previous studies, the magnetic lead field theorem in the quasi-static approximation was derived and used for the development of a method for the forward problem of MEG. It was applied and tested on a single-shell model of the human head and the question whether one shell is adequate enough for the calculation of the magnetic field is the main reason for this study. This forward method is based on the fundamental concept that one can calculate the lead field for MEG by decomposing it into two parts: the lead field of an arbitrary volume conductor that is already known and the gradient of basis functions that have to be harmonic, here derived from spherical harmonics. The problem then is reduced to evaluating the coefficients found in the basis functions. In this research we aim to improve the accuracy of the forward model, hence improving the localization accuracy in inverse methods by introducing a more detailed realistic head model. We here generalize the algorithm developed for a single-shell volume conductor to a three-shell volume conductor representing the brain, the skull and the skin with homogenous and isotropic conductivities in realistic ratios. The expansion to three shells could be tested as the three-shell algorithm is approaching the single-shell with high accuracy in special cases where three-shell solutions can also be calculated using a single-shell solution, especially for higher levels of expansion. The deviation in the calculation of the lead field is also evaluated when using three shells with realistic conductivities. The magnetic field turned out to differ to an important measurable extend in particular for deeper sources, making the three-shell algorithm substantially more accurate for these dipole locations.

Divergence beneath the Brillouin sphere and the phenomenology of prediction error in spherical harmonic series approximations of the gravitational field.

The Brillouin sphere is defined as the smallest sphere, centered at the origin of the geocentric coordinate system, that incorporates all the condensed matter composing the planet. The Brillouin sphere touches the Earth at a single point, and the radial line that begins at the origin and passes through that point is called the singular radial line. For about 60 years there has been a persistent anxiety about whether or not a spherical harmonic (SH) expansion of the external gravitational potential,V, will converge beneath the Brillouin sphere. Recently, it was proven that the probability of such convergence is zero. One of these proofs provided an asymptotic relation, called Costin's formula, for the upper bound,EN, on the absolute value of the prediction error,eN, of a SH series model,VN(θ,λ,r), truncated at some maximum degree,N=nmax. When the SH series is restricted to (or projected onto) a particular radial line, it reduces to a Taylor series (TS) in1/r. Costin's formula isEN≃BN-b(R/r)N, whereRis the radius of the Brillouin sphere. This formula depends on two positive parameters:b, which controls the decay of error amplitude as a function ofNwhenris fixed, and a scale factorB. We show here that Costin's formula derives from a similar asymptotic relation for the upper bound,Anon the absolute value of the TS coefficients,an, for the same radial line. This formula,An≃Kn-k, depends on degree,n, and two positive parameters,kandK, that are analogous tobandB. We use synthetic planets, for which we can compute the potential,V, and also the radial component of gravitational acceleration,gr=∂V/∂r, to hundreds of significant digits, to validate both of these asymptotic formulas. Let superscriptVrefer to asymptotic parameters associated with the coefficients and prediction errors for gravitational potential, and superscriptgto the coefficients and predictions errors associated withgr. For polyhedral planets of uniform density we show thatbV=kV=7/2andbg=kg=5/2almost everywhere. We show that the frequency of oscillation (around zero) of the TS coefficients and the series prediction errors, for a given radial line, is controlled by the geocentric angle,α, between that radial line and the singular radial line. We also derive useful identities connectingKV,BV,Kg, andBg. These identities are expressed in terms of quotients of the various scale factors. The only other quantities involved in these identities areαandR. The phenomenology of 'series divergence' and prediction error (whenr < R) can be described as a function of the truncation degree,N, or the depth,d, beneath the Brillouin sphere. For a fixedr⩽R, asNincreases from very low values, the upper error boundENshrinks until it reaches its minimum (best) value whenNreaches some particular or optimum value,Nopt. WhenN>Nopt, prediction error grows asNcontinues to increase. Eventually, whenN≫Nopt, prediction errors increase exponentially with risingN. If we fix the value ofNand allowR/rto vary, then we find that prediction error in free space beneath the Brillouin sphere increases exponentially with depth,d, beneath the Brillouin sphere. Becausebg=bV-1everywhere, divergence driven prediction error intensifies more rapidly forgrthan forV, both in terms of its dependence onNandd. If we fix bothNandd, and focus on the 'lateral' variations in prediction error, we observe that divergence and prediction error tend to increase (as doesB) as we approach high-amplitude topography.

Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation.

OBJECTIVES: Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross-sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)-based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. METHODS: Five different tractography methods were compared (three DTI-based and two CSD-based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver-operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. RESULTS: Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD-based compared to DTI-based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD-based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE < .05). CONCLUSIONS: CSD-based CST tractograms were more accurate than DTI-based ones when validated using DES-based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice.

Hydrogen bond energy estimation (H-BEE) in large molecular clusters: A Python program for quantum chemical investigations.

A procedure, derived from the fragmentation-based molecular tailoring approach (MTA), has been proposed and extensively applied by Deshmukh and Gadre for directly estimating the individual hydrogen bond (HB) energies and cooperativity contributions in molecular clusters. However, the manual fragmentation and high computational cost of correlated quantum chemical methods make the application of this method to large molecular clusters quite formidable. In this article, we report an in-house developed software for automated hydrogen bond energy estimation (H-BEE) in large molecular clusters. This user-friendly software is essentially written in Python and executed on a Linux platform with the Gaussian package at the backend. Two approximations to the MTA-based procedure, viz. the first spherical shell (SS1) and the Fragments-in-Fragments (Frags-in-Frags), enabling cost-effective, automated evaluation of HB energies and cooperativity contributions, are also implemented in this software. The software has been extensively tested on a variety of molecular clusters and is expected to be of immense use, especially in conjunction with correlated methods such as MP2, CCSD(T), and so forth.

Adhesive Nanoparticle-in-Microgel System with ROS Scavenging Capability and Hemostatic Activity for Postoperative Adhesion Prevention.

Postoperative adhesion is a noteworthy clinical complication in abdominal surgery due to the existing physical barriers are unsatisfactory and inefficient in preventing its occurrence. In this work, an elaborate nanoparticle-in-microgel system (nMGel) is presented for postoperative adhesion prevention. nMGel is facilely formed by crosslinking manganese dioxide (MnO2) nanoparticles-loaded gelatin microspheres with polydopamine using a modified emulsification-chemical crosslinking method, generating a nano-micron spherical hydrogel. After drying, powdery nMGel with sprayability can perfectly cover irregular wounds and maintains robust tissue adhesiveness even in a wet environment. Additionally, nMGel possesses prominent antioxidant and free radical scavenging activity, which protects cell viability and preserves cell biological functions in an oxidative microenvironment. Furthermore, nMGel displays superior hemostatic property as demonstrated in mouse tail amputation models and liver trauma models. Importantly, nMGel can be conveniently administrated in a mouse cecal defect model to prevent adhesion between the injured cecum and the peritoneum by reducing inflammation, oxidative stress, collagen synthesis, and angiogenesis. Thus, the bioactive nMGel offers a practical and efficient approach for ameliorating postsurgical adhesion.

Smart Stimuli-Responsive Spherical Nucleic Acids: Cutting-Edge Platforms for Biosensing, Bioimaging, and Therapeutics.

Spherical nucleic acids (SNAs) with exceptional colloidal stability, multiple modularity, and programmability are excellent candidates to address common molecular delivery-related issues. Based on this, the higher targeting accuracy and enhanced controllability of stimuli-responsive SNAs render them precise nanoplatforms with inestimable prospects for diverse biomedical applications. Therefore, tailored diagnosis and treatment with stimuli-responsive SNAs may be a robust strategy to break through the bottlenecks associated with traditional nanocarriers. Various stimuli-responsive SNAs are engineered through the incorporation of multifunctional modifications to meet biomedical demands with the development of nucleic acid functionalization. This review provides a comprehensive overview of prominent research in this area and recent advancements in the utilization of stimuli-responsive SNAs in biosensing, bioimaging, and therapeutics. For each aspect, SNA nanoplatforms that exhibit responsive behavior to both internal stimuli (including sequence, enzyme, redox reactions, and pH) and external stimuli (such as light and temperature) are highlighted. This review is expected to offer inspiration and guidance strategies for the rational design and development of stimuli-responsive SNAs in the field of biomedicine.

Enhancing Endosomal Escape and Gene Regulation Activity for Spherical Nucleic Acids.

The therapeutic potential of small interfering RNAs (siRNAs) is limited by their poor stability and low cellular uptake. When formulated as spherical nucleic acids (SNAs), siRNAs are resistant to nuclease degradation and enter cells without transfection agents with enhanced activity compared to their linear counterparts; however, the gene silencing activity of SNAs is limited by endosomal entrapment, a problem that impacts many siRNA-based nanoparticle constructs. To increase cytosolic delivery, SNAs are formulated using calcium chloride (CaCl2 ) instead of the conventionally used sodium chloride (NaCl). The divalent calcium (Ca2+ ) ions remain associated with the multivalent SNA and have a higher affinity for SNAs compared to their linear counterparts. Importantly, confocal microscopy studies show a 22% decrease in the accumulation of CaCl2 -salted SNAs within the late endosomes compared to NaCl-salted SNAs, indicating increased cytosolic delivery. Consistent with this finding, CaCl2 -salted SNAs comprised of siRNA and antisense DNA all exhibit enhanced gene silencing activity (up to 20-fold), compared to NaCl-salted SNAs regardless of sequence or cell line (U87-MG and SK-OV-3) studied. Moreover, CaCl2 -salted SNA-based forced intercalation probes show improved cytosolic mRNA detection.

From Structure to Application: The Evolutionary Trajectory of Spherical Nucleic Acids.

Since the proposal of the concept of spherical nucleic acids (SNAs) in 1996, numerous studies have focused on this topic and have achieved great advances. As a new delivery system for nucleic acids, SNAs have advantages over conventional deoxyribonucleic acid (DNA) nanostructures, including independence from transfection reagents, tolerance to nucleases, and lower immune reactions. The flexible structure of SNAs proves that various inorganic or organic materials can be used as the core, and different types of nucleic acids can be conjugated to realize diverse functions and achieve surprising and exciting outcomes. The special DNA nanostructures have been employed for immunomodulation, gene regulation, drug delivery, biosensing, and bioimaging. Despite the lack of rational design strategies, potential cytotoxicity, and structural defects of this technology, various successful examples demonstrate the bright and convincing future of SNAs in fields such as new materials, clinical practice, and pharmacy.

Nanostructurally Engineering Covalent Organic Frameworks for Boosting CO2 Photoreduction.

Herein, a series of imine-linked covalent organic frameworks (COFs) are developed with advanced ordered mesoporous hollow spherical nanomorphology and ultra-large mesopores (4.6 nm in size), named OMHS-COF-M (M = H, Co, and Ni). The ordered mesoporous hollow spherical nanomorphology is revealed to be formed via an Ostwald ripening mechanism based on a one-step self-templated strategy. Encouraged by its unique structural features and outstanding photoelectrical property, the OMHS-COF-Co material is applied as the photocatalyst for CO2-to-CO reduction. Remarkably, it delivers an impressive CO production rate as high as 15 874 µmol g-1 h-1, a large selectivity of 92.4%, and a preeminent cycling stability. From in/ex situ experiments and density functional theory (DFT) calculations, the excellent CO2 photoreduction performance is ascribed to the desirable cooperation of unique ordered mesoporous hollow spherical host and abundant isolated Co active sites, enhancing CO2 activation, and improving electron transfer kinetics as well as reducing the energy barriers for intermediates *COOH generation and CO desorption.

Maximum spherical mean value filtering for whole-brain QSM.

PURPOSE: To develop a tissue field-filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain-tissue erosion. THEORY AND METHODS: Residual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field-magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients. RESULTS: Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis. CONCLUSION: The mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV-filtered dipole inversion without eroding the volume of interest.

Spherical echo-planar time-resolved imaging (sEPTI) for rapid 3D quantitative T 2 * and susceptibility imaging.

PURPOSE: To develop a 3D spherical EPTI (sEPTI) acquisition and a comprehensive reconstruction pipeline for rapid high-quality whole-brain submillimeter T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification. METHODS: For the sEPTI acquisition, spherical k-space coverage is utilized with variable echo-spacing and maximum kx ramp-sampling to improve efficiency and signal incoherency compared to existing EPTI approaches. For reconstruction, an iterative rank-shrinking B0 estimation and odd-even high-order phase correction algorithms were incorporated into the reconstruction to better mitigate artifacts from field imperfections. A physics-informed unrolled network was utilized to boost the SNR, where 1-mm and 0.75-mm isotropic whole-brain imaging were performed in 45 and 90 s at 3 T, respectively. These protocols were validated through simulations, phantom, and in vivo experiments. Ten healthy subjects were recruited to provide sufficient data for the unrolled network. The entire pipeline was validated on additional five healthy subjects where different EPTI sampling approaches were compared. Two additional pediatric patients with epilepsy were recruited to demonstrate the generalizability of the unrolled reconstruction. RESULTS: sEPTI achieved 1.4 × $$ \times $$ faster imaging with improved image quality and quantitative map precision compared to existing EPTI approaches. The B0 update and the phase correction provide improved reconstruction performance with lower artifacts. The unrolled network boosted the SNR, achieving high-quality T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification with single average data. High-quality reconstruction was also obtained in the pediatric patients using this network. CONCLUSION: sEPTI achieved whole-brain distortion-free multi-echo imaging and T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification at 0.75 mm in 90 s which has the potential to be useful for wide clinical applications.

The effects of axonal beading and undulation on axonal diameter estimation from diffusion MRI: Insights from simulations in human axons segmented from three-dimensional electron microscopy.

The increasing availability of high-performance gradient systems in human MRI scanners has generated great interest in diffusion microstructural imaging applications such as axonal diameter mapping. Practically, sensitivity to axon diameter in diffusion MRI is attained at strong diffusion weightings b , where the deviation from the expected 1 / b scaling in white matter yields a finite transverse diffusivity, which is then translated into an axon diameter estimate. While axons are usually modeled as perfectly straight, impermeable cylinders, local variations in diameter (caliber variation or beading) and direction (undulation) are known to influence axonal diameter estimates and have been observed in microscopy data of human axons. In this study, we performed Monte Carlo simulations of diffusion in axons reconstructed from three-dimensional electron microscopy of a human temporal lobe specimen using simulated sequence parameters matched to the maximal gradient strength of the next-generation Connectome 2.0 human MRI scanner ( ≲ 500 mT/m). We show that axon diameter estimation is accurate for nonbeaded, nonundulating fibers; however, in fibers with caliber variations and undulations, the axon diameter is heavily underestimated due to caliber variations, and this effect overshadows the known overestimation of the axon diameter due to undulations. This unexpected underestimation may originate from variations in the coarse-grained axial diffusivity due to caliber variations. Given that increased axonal beading and undulations have been observed in pathological tissues, such as traumatic brain injury and ischemia, the interpretation of axon diameter alterations in pathology may be significantly confounded.

Precisely Designed Ultra-Small CoP Nanoparticles-Decorated Hollow Carbon Nanospheres as Highly Efficient Host in Lithium-Sulfur Batteries.

Designing porous carbon materials with metal phosphides as host materials holds promise for enhancing the cyclability and durability of lithium-sulfur (Li-S) batteries by mitigating sulfur poisoning and exhibiting high electrocatalytic activity. Nevertheless, it is urgent to precisely control the size of metal phosphides to further optimize the polysulfide conversion reaction kinetics of Li-S batteries. Herein, a subtlety regulation strategy was proposed to obtain ultra-small CoP nanoparticles-decorated hollow carbon nanospheres (CoP@C) by using spherical polyelectrolyte brush (SPB) as the template with stabilizing assistance from polydopamine coating, which also works as carbon source. Leveraging the electrostatic interaction between SPB and Co2+, ultra-small Co particles with sizes measuring 5.5±2.6 nm were endowed after calcination. Subsequently, through a gas-solid phosphating process, these Co particles were converted into CoP nanoparticles with significantly finer sizes (7.1±3.1 nm) compared to state-of-the-art approaches. By uniformly distributing the electrocatalyst nanoparticles on hollow carbon nanospheres, CoP@C facilitated the acceleration of Li-ion diffusion and enhanced the conversion reaction kinetics of polysulfides through adsorption-diffusion synergy. As a result, Li-S batteries utilizing the CoP@C/S cathode demonstrated an initial specific discharge capacity of 850.0 mAh g-1 at 1.0 C, with a low-capacity decay rate of 0.03 % per cycle.