MOTIVATION: The inherent low contrast of electron microscopy (EM) datasets presents a significant challenge for rapid segmentation of cellular ultrastructures from EM data. This challenge is particularly prominent when working with high resolution big-datasets that are now acquired using electron tomography and serial block-face imaging techniques. Deep learning (DL) methods offer an exciting opportunity to automate the segmentation process by learning from manual annotations of a small sample of EM data. While many DL methods are being rapidly adopted to segment EM data no benchmark analysis has been conducted on these methods to date. RESULTS: We present EM-stellar, a platform that is hosted on Google Colab that can be used to benchmark the performance of a range of state-of-the-art DL methods on user-provided datasets. Using EM-Stellar we show that the performance of any DL method is dependent on the properties of the images being segmented. It also follows that no single DL method performs consistently across all performance evaluation metrics. AVAILABILITY: EM-stellar (code and data) is written in Python and is freely available under MIT license on GitHub (https://github.com/cellsmb/em-stellar). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for refractory depression, however, therapeutic outcomes vary. Mounting evidence suggests that clinical response relates to functional connectivity with the subgenual cingulate cortex (SGC) at the precise DLPFC stimulation site. Critically, SGC-related network architecture shows considerable interindividual variation across the spatial extent of the DLPFC, indicating that connectivity-based target personalization could potentially be necessary to improve treatment outcomes. However, to date accurate personalization has not appeared feasible, with recent work indicating that the intraindividual reproducibility of optimal targets is limited to 3.5 cm. Here we developed reliable and accurate methodologies to compute individualized connectivity-guided stimulation targets. In resting-state functional MRI scans acquired across 1,000 healthy adults, we demonstrate that, using this approach, personalized targets can be reliably and robustly pinpointed, with a median accuracy of ~2 mm between scans repeated across separate days. These targets remained highly stable, even after 1 year, with a median intraindividual distance between coordinates of only 2.7 mm. Interindividual spatial variation in personalized targets exceeded intraindividual variation by a factor of up to 6.85, suggesting that personalized targets did not trivially converge to a group-average site. Moreover, personalized targets were heritable, suggesting that connectivity-guided rTMS personalization is stable over time and under genetic control. This computational framework provides capacity for personalized connectivity-guided TMS targets to be robustly computed with high precision and has the flexibly to advance research in other basic research and clinical applications.

Pecha Kucha presentation for the SoTEL 2021 Symposium from the Bionic Limb project team at the University of Melbourne. https://sotel.nz

Background: Anterior cruciate ligament (ACL) injuries most commonly occur after a perturbation. Prophylactic knee braces (PKBs) are off-the-shelf braces designed to prevent and reduce the severity of knee injuries during sports, yet their effectiveness has been debated. Purpose: To identify differences in ACL agonist and antagonist muscle forces, during braced and unbraced conditions, while walking with the application of unexpected perturbations. Study Design: Controlled laboratory study. Methods: A total of 20 recreational athletes were perturbed during walking at a speed of 1.1 m/s, and motion analysis data were used to create patient-specific musculoskeletal models. Static optimization was performed to calculate the lower-limb muscle forces. Statistical parametric mapping was used to compare muscle forces between the braced and unbraced conditions during the stance phase of the perturbed cycle. Results: The brace reduced muscle forces in the quadriceps (QUADS), gastrocnemius (GAS), and soleus (SOL) but not in the hamstrings. The peak QUADS muscle force was significantly lower with the brace versus without at 49% to 60% of the stance phase (28.9 ± 12.98 vs 14.8 ± 5.06 N/kg, respectively; P < .001) and again at 99% of the stance phase (1.7 ± 0.4 vs 3.6 ± 0.13 N/kg, respectively; P = .049). The SOL muscle force peak was significantly lower with the brace versus without at 25% of the stance phase (1.9 ± 1.7 vs 4.6 ± 3.4 N/kg, respectively; P = .031) and at 39% of the stance phase (1.9 ± 1.4 vs 5.3 ± 5.6 N/kg, respectively; P = .007). In the GAS, there were no significant differences between conditions throughout the whole stance phase except between 97% and 100%, where the braced condition portrayed a smaller peak force (0.23 ± 0.13 vs 1.4 ± 1.1 N/kg for unbraced condition; P = .024). Conclusion: These findings suggested that PKBs that restrict knee hyperextension and knee valgus/varus motion can alter neuromuscular patterns, which result in a reduction of QUADS force. Clinical Relevance: Understanding the way PKBs alter muscle function and knee mechanics can provide invaluable information that will help in making decisions about their use. Further studies should investigate different types of braces and perturbations to evaluate the effectiveness of PKBs.

Filtering facepiece respirators (FFRs) and medical masks are widely used to reduce the inhalation exposure of airborne particulates and biohazardous aerosols. Their protective capacity largely depends on the fraction of these that are filtered from the incoming air volume. While the performance and physics of different filter materials have been the topic of intensive study, less well understood are the effects of mask sealing. To address this, we introduce an approach to calculate the influence of face-seal leakage on filtration ratio and fit factor based on an analytical model and a finite element method (FEM) model, both of which take into account time-dependent human respiration velocities. Using these, we calculate the filtration ratio and fit factor for a range of ventilation resistance values relevant to filter materials, 500-2500 Pa∙s∙m-1, where the filtration ratio and fit factor are calculated as a function of the mask gap dimensions, with good agreement between analytical and numerical models. The results show that the filtration ratio and fit factor are decrease markedly with even small increases in gap area. We also calculate particle filtration rates for N95 FFRs with various ventilation resistances and two commercial FFRs exemplars. Taken together, this work underscores the critical importance of forming a tight seal around the face as a factor in mask performance, where our straightforward analytical model can be readily applied to obtain estimates of mask performance.

The study of neurons is fundamental for basic neuroscience research and treatment of neurological disorders. In recent years ultrasound has been increasingly recognized as a viable method to stimulate neurons. However, traditional ultrasound transducers are limited in the scope of their application by self-heating effects, limited frequency range and cavitation effects during neuromodulation. In contrast, surface acoustic wave (SAW) devices, which are producing wavemodes with increasing application in biomedical devices, generate less self-heating, are smaller and create less cavitation. SAW devices thus have the potential to address some of the drawbacks of traditional ultrasound transducers and could be implemented as miniaturized wearable or implantable devices. In this mini review, we discuss the potential mechanisms of SAW-based neuromodulation, including mechanical displacement, electromagnetic fields, thermal effects, and acoustic streaming. We also review the application of SAW actuation for neuronal stimulation, including growth and neuromodulation. Finally, we propose future directions for SAW-based neuromodulation.

BACKGROUND: The combination of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) allows for non-invasive investigation of cortical response and connectivity in human cortex. This study aimed to examine the amplitudes and latencies of each TMS-evoked potential (TEP) component induced by single-pulse TMS (spTMS) to the left motor (M1) and dorsolateral prefrontal cortex (DLPFC) among healthy young participants (YNG), older participants (OLD), and patients with schizophrenia (SCZ). METHODS: We compared the spatiotemporal characteristics of TEPs induced by spTMS among the groups. RESULTS: Compared to YNG, M1-spTMS induced lower amplitudes of N45 and P180 in OLD and a lower amplitude of P180 in SCZ, whereas the DLPFC-spTMS induced a lower N45 in OLD. Further, OLD demonstrated latency delays in P60 after M1-spTMS and in N45-P60 over the right central region after left DLPFC-spTMS, whereas SCZ demonstrated latency delays in N45-P60 over the midline and right central regions after DLPFC-spTMS. CONCLUSIONS: These findings suggest that inhibitory and excitatory mechanisms mediating TEPs may be altered in OLD and SCZ. The amplitude and latency changes of TEPs with spTMS may reflect underlying neurophysiological changes in OLD and SCZ, respectively. The spTMS administered to M1 and the DLPFC can probe cortical functions by examining TEPs. Thus, TMS-EEG can be used to study changes in cortical connectivity and signal propagation from healthy to pathological brains.

BACKGROUND: The absorption, translocation, accumulation and excretion of substances are fundamental processes in all organisms including plants, and have been successfully studied using radiotracers labelled with 11C, 13N, 14C and 22Na since 1939. Sodium is one of the most damaging ions to the growth and productivity of crops. Due to the significance of understanding sodium transport in plants, a significant number of studies have been carried out to examine sodium influx, compartmentation, and efflux using 22Na- or 24Na-labeled salts. Notably, however, most of these studies employed destructive methods, which has limited our understanding of sodium flux and distribution characteristics in real time, in live plants. Positron emission tomography (PET) has been used successfully in medical research and diagnosis for decades. Due to its ability to visualise and assess physiological and metabolic function, PET imaging has also begun to be employed in plant research. Here, we report the use of a clinical PET scanner with a 22Na tracer to examine 22Na-influx dynamics in barley plants (Hordeum vulgare L. spp. Vulgare-cultivar Bass) under variable nutrient levels, alterations in the day/night light cycle, and the presence of sodium channel inhibitors. RESULTS: 3D dynamic PET images of whole plants show readily visible 22Na translocation from roots to shoots in each examined plant, with rates influenced by both nutrient status and channel inhibition. PET images show that plants cultivated in low-nutrient media transport more 22Na than plants cultivated in high-nutrient media, and that 22Na uptake is suppressed in the presence of a cation-channel inhibitor. A distinct diurnal pattern of 22Na influx was discernible in curves displaying rates of change of relative radioactivity. Plants were found to absorb more 22Na during the light period, and anticipate the change in the light/dark cycle by adjusting the sodium influx rate downward in the dark period, an effect not previously described experimentally. CONCLUSIONS: We demonstrate the utility of clinical PET/CT scanners for real-time monitoring of the temporal dynamics of sodium transport in plants. The effects of nutrient deprivation and of ion channel inhibition on sodium influx into barley plants are shown in two proof-of-concept experiments, along with the first-ever 3D-imaging of the light and dark sodium uptake cycles in plants. This method carries significant potential for plant biology research and, in particular, in the context of genetic and treatment effects on sodium acquisition and toxicity in plants.

Spectral analysis and neural field theory are used to investigate the role of local connections in brain connectivity matrices (CMs) that quantify connectivity between pairs of discretized brain regions. This work investigates how the common procedure of omitting such self-connections (i.e., the diagonal elements of CMs) in published studies of brain connectivity affects the properties of functional CMs (fCMs) and the mutually consistent effective CMs (eCMs) that correspond to them. It is shown that retention of self-connections in the fCM calculated from two-point activity covariances is essential for the fCM to be a true covariance matrix, to enable correct inference of the direct total eCMs from the fCM, and to ensure their compatibility with it; the deCM and teCM represent the strengths of direct connections and all connections between points, respectively. When self-connections are retained, inferred eCMs are found to have net inhibitory self-connections that represent the local inhibition needed to balance excitation via white matter fibers at longer ranges. This inference of spatially unresolved connectivity exemplifies the power of spectral connectivity methods, which also enable transformation of CMs to compact diagonal forms that allow accurate approximation of the fCM and total eCM in terms of just a few modes, rather than the full N2 CM entries for connections between N brain regions. It is found that omission of fCM self-connections affects both local and long-range connections in eCMs, so they cannot be omitted even when studying the large-scale. Moreover, retention of local connections enables inference of subgrid short-range inhibitory connectivity. The results are verified and illustrated using the NKI-Rockland dataset from the University of Southern California Multimodal Connectivity Database. Deletion of self-connections is common in the field; this does not affect case-control studies but the present results imply that such fCMs must have self-connections restored before eCMs can be inferred from them.

Nanoparticles provide a promising approach for the targeted delivery of therapeutic, diagnostic and imaging agents in the body. However, it is not yet fully understood how the physico-chemical properties of the nanoparticles influence cellular association and uptake. Cellular association experiments are routinely performed in an effort to determine how nanoparticle properties impact the rate of nanoparticle-cell association. To compare experiments in a meaningful manner, the association data must be normalized by the amount of nanoparticles that arrive at the cells, a measure referred to as the delivered dose. The delivered dose is calculated from a model of nanoparticle transport through fluid. A standard assumption is that all nanoparticles within the population are monodisperse, namely the nanoparticles have the same physico-chemical properties. We present a semi-analytic solution to a modified model of nanoparticle transport that allows for the nanoparticle population to be polydisperse. This solution allows us to efficiently analyse the influence of polydispersity on the delivered dose. Combining characterization data obtained from a range of commonly used nanoparticles and our model, we find that the delivered dose changes by more than a factor of 2 if realistic amounts of polydispersity are considered.

BACKGROUND: The topography of an implant surface can serve as a powerful signaling cue for attached cells and can enhance the quality of osseointegration. A series of improved implant surfaces functionalized with nanoscale structures have been fabricated using various methods. METHODS: In this study, using an H(2)O(2) process, we fabricated two size-controllable sawtooth-like nanostructures with different dimensions on a titanium surface. The effects of the two nano-sawtooth structures on rat bone marrow mesenchymal stem cells (BMMSCs) were evaluated without the addition of osteoinductive chemical factors. RESULTS: These new surface modifications did not adversely affect cell viability, and rat BMMSCs demonstrated a greater increase in proliferation ability on the surfaces of the nano-sawtooth structures than on a control plate. Furthermore, upregulated expression of osteogenic-related genes and proteins indicated that the nano-sawtooth structures promote osteoblastic differentiation of rat BMMSCs. Importantly, the large nano-sawtooth structure resulted in the greatest cell responses, including increased adhesion, proliferation, and differentiation. CONCLUSION: The enhanced adhesion, proliferation, and osteogenic differentiation abilities of rat BMMSCs on the nano-sawtooth structures suggest the potential to induce improvements in bone-titanium integration in vivo. Our study reveals the key role played by the nano-sawtooth structures on a titanium surface for the fate of rat BMMSCs and provides insights into the study of stem cell-nanostructure relationships and the related design of improved biomedical implant surfaces.