Sub-bundle based analysis reveals the role of human optic radiation in visual working memory.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

Association of proton-density fat fraction with osteoporosis: a systematic review and meta-analysis.

This study aimed to evaluate the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, assessing its effectiveness as a biomarker for osteoporosis. A systematic review was conducted by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a mean difference of 11.04 (95% CI: 9.17 to 12.92, Z=11.52, P < 0.00001). Measuring PDFF via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care. OBJECTIVE: This study aims to assess the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, evaluating its effectiveness as a biomarker for osteoporosis. MATERIALS AND METHODS: This systematic review was carried out by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. RESULTS: Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a (MD = 11.04, 95% CI: 9.17 to 12.92, Z = 11.52, P < 0.00001). Subgroup analyses indicated that diagnostic methods, gender, and echo length did not significantly impact the PDFF-osteoporosis association. CONCLUSION: PDFF measurement via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care.

MRGazer: decoding eye gaze points from functional magnetic resonance imaging in individual space.

Objective. Eye-tracking research has proven valuable in understanding numerous cognitive functions. Recently, Freyet alprovided an exciting deep learning method for learning eye movements from functional magnetic resonance imaging (fMRI) data. It employed the multi-step co-registration of fMRI into the group template to obtain eyeball signal, and thus required additional templates and was time consuming. To resolve this issue, in this paper, we propose a framework named MRGazer for predicting eye gaze points from fMRI in individual space.Approach. The MRGazer consists of an eyeball extraction module and a residual network-based eye gaze prediction module. Compared to the previous method, the proposed framework skips the fMRI co-registration step, simplifies the processing protocol, and achieves end-to-end eye gaze regression.Main results. The proposed method achieved superior performance in eye fixation regression (Euclidean error, EE = 2.04°) than the co-registration-based method (EE = 2.89°), and delivered objective results within a shorter time (∼0.02 s volume-1) than prior method (∼0.3 s volume-1).Significance. The MRGazer is an efficient, simple, and accurate deep learning framework for predicting eye movement from fMRI data, and can be employed during fMRI scans in psychological and cognitive research. The code is available athttps://github.com/ustc-bmec/MRGazer.

An unrolled neural network for accelerated dynamic MRI based on second-order half-quadratic splitting model.

The reconstruction of dynamic magnetic resonance images from incomplete k-space data has sparked significant research interest due to its potential to reduce scan time. However, traditional iterative optimization algorithms fail to faithfully reconstruct images at higher acceleration factors and incur long reconstruction time. Furthermore, end-to-end deep learning-based reconstruction algorithms suffer from large model parameters and lack robustness in the reconstruction results. Recently, unrolled deep learning models, have shown immense potential in algorithm stability and applicability flexibility. In this paper, we propose an unrolled deep learning network based on a second-order Half-Quadratic Splitting(HQS) algorithm, where the forward propagation process of this framework strictly follows the computational flow of the HQS algorithm. In particular, we propose a degradation-sense module by associating random sampling patterns with intermediate variables to guide the iterative process. We introduce the Information Fusion Transformer(IFT) to extract both local and non-local prior information from image sequences, thereby removing aliasing artifacts resulting from random undersampling. Finally, we impose low-rank constraints within the HQS algorithm to further enhance the reconstruction results. The experiments demonstrate that each component module of our proposed model contributes to the improvement of the reconstruction task. Our proposed method achieves comparably satisfying performance to the state-of-the-art methods and it exhibits excellent generalization capabilities across different sampling masks. At the low acceleration factor, there is a 0.7% enhancement in the PSNR. Furthermore, when the acceleration factor reached 8 and 12, the PSNR achieves an improvement of 3.4% and 5.8% respectively.

A novel method for highly linear gradient coil design based on stream function.

BACKGROUND: Magnetoencephalography (MEG) and magnetic resonance imaging (MRI) are non-invasive imaging techniques that offer effective means for disease diagnosis. A more straightforward and optimized method is presented for designing gradient coils which are pivotal parts of the above imaging systems. PURPOSE: A novel design method based on stream function combining an optimization algorithm is proposed to obtain highly linear gradient coil. METHODS: Two-dimensional Fourier expansion of the current field on the surface where the coil is located and the equipotential line of the expansion term superposition according to the number of turns of the coil are used to represent the coil shape. Particle swarm optimization is utilized to optimize the coil shape while linearity and field uniformity are used as parameters to evaluate the coil performance. Through this method, the main parameters such as input current distribution region, coil turns, desired magnetic field strength, expansion order and iteration times can be combined in a given solution space to optimize coil design. RESULTS: Simulation results show that the maximum linearity spatial deviation of the designed bi-planar x-gradient coil compared with that of target field method is reduced from 14% to 0.54%, and that of the bi-planar z-gradient coil is reduced from 8.98% to 0.52%. Similarly, that of the cylindrical x-gradient coil is reduced from 2% to 0.1%, and that of the cylindrical z-gradient coil is reduced from 0.87% to 0.45%. The similar results are found in the index of inhomogeneity error. Moreover, it has also been verified experimentally that the result of measured magnetic field is consist with simulated result. CONCLUSIONS: The proposed method provides a straightforward way that simplifies the design process and improves the linearity of designed gradient coil, which could be beneficial to realize better magnetic field in engineering applications.

Janus Flexible Device with Microcone Channels for Sampling and Analysis of Biological Microfluidics.

Controlling the spontaneous directional transport of droplets plays an important role in the application of microchemical reactions and microdroplet detection. Although the relevant technologies have been widely studied, the existing spontaneous droplet transport strategies still face problems of complex structure, single function, and poor flexibility. Inspired by the spontaneous droplet transport strategy in nature, an asymmetric wettability surface with microcone channels (AWS-MC) is prepared on a flexible fabric by combining surface modification and femtosecond laser manufacturing technology. On this surface, the capillary force and Laplace pressure induced by the wettability gradient and the geometric structure gradient drive the droplet transport from the hydrophobic surface to the hydrophilic surface. Notably, droplets in adjacent hydrophilic regions do not exchange substances even if the gap in the hydrophilic region is only 1 mm, which provides an ideal platform for numerous detections by a single drop. The droplet transport strategy does not require external energy and can adapt to the manipulation of various droplet types. Application of this surface in the blood of organisms is demonstrated. This work provides an effective method for microdroplet-directed self-transport and microdroplet detection.

Navigating Exploitative Traps: Unveiling the Uncontrollable Reward Seeking of Individuals With Internet Gaming Disorder.

BACKGROUND: Internet gaming disorder (IGD) involves an imbalance in the brain's dual system, characterized by heightened reward seeking and diminished cognitive control, which lead to decision-making challenges. The exploration-exploitation strategy is key to decision making, but how IGD affects this process is unclear. METHODS: To investigate the impact of IGD on decision making, a modified version of the 2-armed bandit task was employed. Participants included 41 individuals with IGD and 44 healthy control individuals. The study assessed the strategies used by participants in the task, particularly focusing on the exploitation-exploration strategy. Additionally, functional magnetic resonance imaging was used to examine brain activation patterns during decision-making and estimation phases. RESULTS: The study found that individuals with IGD demonstrated greater reliance on exploitative strategies in decision making due to their elevated value-seeking tendencies and decreased cognitive control. Individuals with IGD also displayed heightened activation in the presupplementary motor area and the ventral striatum compared with the healthy control group in both decision-making and estimation phases. Meanwhile, the prefrontal cortex showed more inhibition in individuals with IGD than in the healthy control group during exploitative strategies. This inhibition decreased as cognitive control diminished. CONCLUSIONS: The imbalance in the development of the dual system in individuals with IGD may lead to an overreliance on exploitative strategies. This imbalance, marked by increased reward seeking and reduced cognitive control, contributes to difficulties in decision making and value-related behavioral processes in individuals with IGD.

Abnormalities in subcortical function and their treatment response in Wilson's disease.

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson's disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD.

MLMFNet: A multi-level modality fusion network for multi-modal accelerated MRI reconstruction.

Magnetic resonance imaging produces detailed anatomical and physiological images of the human body that can be used in the clinical diagnosis and treatment of diseases. However, MRI suffers its comparatively longer acquisition time than other imaging methods and is thus vulnerable to motion artifacts, which ultimately lead to likely failed or even wrong diagnosis. In order to perform faster reconstruction, deep learning-based methods along with traditional strategies such as parallel imaging and compressed sensing come into play in recent years in this field. Meanwhile, in order to better analyze the diseases, it is also often necessary to acquire images in the same region of interest under different modalities, which yield images with different contrast levels. However, most of these aforementioned methods tend to use single-modal images for reconstruction, neglecting the correlation and redundancy information embedded in MR images acquired with different modalities. While there are works on multi-modal reconstruction, the information is yet to be efficiently explored. In this paper, we propose an end-to-end neural network called MLMFNet, which helps the reconstruction of the target modality by using information from the auxiliary modality across feature channels and layers. Specifically, this is highlighted by three components: (I) An encoder based on UNet with a single-stream strategy that fuses auxiliary and target modalities; (II) a decoder that tends to multi-level features from all layers of the encoder, and (III) a channel attention module. Quantitative and qualitative analyses are performed on a public brain dataset and knee brain dataset, which show that the proposed method achieves satisfying results in MRI reconstruction within the multi-modal context, and also demonstrate its effectiveness and potential to be used in clinical practice.

Modulations of resting-static functional connectivity on insular by electroacupuncture in subjective tinnitus.

Objective: To explore the modulations of electroacupuncture in subjective tinnitus (ST) by comparing the difference of functional connectivity (FC) in ST patients and healthy volunteers between the insular (INS) and the whole brain region. Methods: A total of 34 ST patients were selected into electroacupuncture group (EG) and 34 age- and sex-matched normal subjects were recruited into control group (CG). The EG received acupuncture at SI19 (Tinggong), GB11 (Touqiaoyin), TE17 (Yifeng), GV20 (Baihui), GV15 (Yamen), GV14 (Dazhui), SJ13 (Zhongzhu), among which the points of SI19 and GB11 were connected to the electroacupuncture instrument with the density wave of 2/50 Hz, and 3 treatments per week for 10 sessions in total. The severity of tinnitus was evaluated by Tinnitus Handicap Inventory (THI), the hearing status was recorded using pure tone audiometry, and resting-state functional magnetic resonance imaging (rs-fMRI) was performed on the brain before and after treatment, the CG received no intervention yet only rs-fMRI data were collected. Results: With the electroacupuncture treatment, the total THI score, average air conduction threshold of patients of EG were significantly lower than before (p < 0.01), and the total effective rate was 88.24%. Compared with CG, FC of ST patients between INS and left superior temporal gyrus and right hippocampal significantly decreased before treatment, while FC of ST patients between INS and right superior frontal gyrus, left middle frontal gyrus and right anterior cuneus significantly decreased after treatment (voxel p < 0.001, cluster p < 0.05, corrected with GRF). FC of ST patients between the INS and right middle frontal gyrus, left superior frontal gyrus and right paracentral lobule showed a significant decrease after treatment (voxel p < 0.001, cluster p < 0.05, corrected with GRF). In addition, THI score in EG was negatively correlated with the reduction of FC value in INS-left superior frontal gyrus before treatment (r = -0.41, p = 0.017). Therefore, this study suggests that abnormal FC of INS may be one of the significant central mechanisms of ST patients and can be modulated by electroacupuncture. Discussion: Electroacupuncture treatment can effectively reduce or eliminate tinnitus symptoms in ST patients and improve the hearing by decreasing FC between the INS and the frontal and temporal brain regions.

Abnormal occipital and frontal activity during voluntary convergence in intermittent exotropia: A task-fMRI study.

Intermittent exotropia (IXT) is characterized by intermittently outward deviation of the eye and involved with vergence dysfunction. This study aimed to investigate the brain areas related to voluntary convergence and cortical activation changes between IXT patients and normal subjects. A total of 21 subjects, including 11 IXT patients and 10 age- and sex-matched normal subjects, were recruited for this study. A voluntary convergence task was employed, with changes in brain function measured by functional magnetic resonance imaging (fMRI). Correlations between cortical activation and clinical measurements were conducted by Pearson's correlation analysis. fMRI results showed that during voluntary convergence, the medial frontal gyrus (MFG) and bilateral occipital cortex were activated in the normal group, whereas only activation of the occipital cortex in IXT patients. Compared with the normal, IXT patients showed hypo-activation of both the MFG and cuneus during the task. The activation of MFG was negatively correlated to the duration of IXT. This study demonstrates that both MFG and occipital cortex may participate in voluntary convergence in normal subjects, while IXT patients have an aberrant cortical function of the MFG and cuneus, and the duration of IXT likely influences the severity of MFG. These findings may provide valuable insights for understanding the relationship between convergence and IXT.

Separable amygdala activation patterns in the evaluations of robots.

Given the increasing presence of robots in everyday environments and the significant challenge posed by social interactions with robots, it is crucial to gain a deeper understanding into the social evaluations of robots. One potentially effective approach to comprehend the fundamental processes underlying controlled and automatic evaluations of robots is to probe brain response to different perception levels of robot-related stimuli. Here, we investigate controlled and automatic evaluations of robots based on brain responses during viewing of suprathreshold (duration: 200 ms) and subthreshold (duration: 17 ms) humanoid robot stimuli. Our behavioral analysis revealed that despite participants' self-reported positive attitudes, they held negative implicit attitudes toward humanoid robots. Neuroimaging analysis indicated that subthreshold presentation of humanoid robot stimuli elicited significant activation in the left amygdala, which was associated with negative implicit attitudes. Conversely, no significant left amygdala activation was observed during suprathreshold presentation. Following successful attenuation of negative attitudes, the left amygdala response to subthreshold presentation of humanoid robot stimuli decreased, and this decrease correlated positively with the reduction in negative attitudes. These findings provide evidence for separable patterns of amygdala activation between controlled and automatic processing of robots, suggesting that controlled evaluations may influence automatic evaluations of robots.

Effects of a periodic intermittent theta burst stimulation in Alzheimer's disease.

Background: Previous studies have demonstrated that excitatory repetitive transcranial magnetic stimulation (rTMS) can improve the cognitive function of patients with Alzheimer's disease (AD). Intermittent theta burst stimulation (iTBS) is a novel excitatory rTMS protocol for brain activity stimulation with the ability to induce long-term potentiation-like plasticity and represents a promising treatment for AD. However, the long-term effects of iTBS on cognitive decline and brain structure in patients with AD are unknown. Aims: We aimed to explore whether repeating accelerated iTBS every three months could slow down the cognitive decline in patients with AD. Methods: In this randomised, assessor-blinded, controlled trial, iTBS was administered to the left dorsolateral prefrontal cortex (DLPFC) of 42 patients with AD for 14 days every 13 weeks. Measurements included the Montreal Cognitive Assessment (MoCA), a comprehensive neuropsychological battery, and the grey matter volume (GMV) of the hippocampus. Patients were evaluated at baseline and after follow-up. The longitudinal pipeline of the Computational Anatomy Toolbox for SPM was used to detect significant treatment-related changes over time. Results: The iTBS group maintained MoCA scores relative to the control group (t=3.26, p=0.013) and reduced hippocampal atrophy, which was significantly correlated with global degeneration scale changes. The baseline Mini-Mental State Examination (MMSE) score, apolipoprotein E genotype and Clinical Dementia Rating were indicative of MoCA scores at follow-up. Moreover, the GMV of the left (t=0.08, p=0.996) and right (t=0.19, p=0.977) hippocampus were maintained in the active group but significantly declined in the control group (left: t=4.13, p<0.001; right: t=5.31, p<0.001). GMV change in the left (r=0.35, p=0.023) and right (r=0.36, p=0.021) hippocampus across the intervention positively correlated with MoCA changes; left hippocampal GMV change was negatively correlated with global degeneration scale (r=-0.32, p=0.041) changes. Conclusions: DLPFC-iTBS may be a feasible and easy-to-implement non-pharmacological intervention to slow down the progressive decline of overall cognition and quality of life in patients with AD, providing a new AD treatment option. Trial registration number: NCT04754152.

A Reliable Approach for Fabricating Tissue-Mimicking Phantoms with Designated Dielectric Properties from 16 MHz to 3 GHz.

Tissue-mimicking dielectric phantoms are widely used to mimic the relative permittivity and conductivity of human tissues in various medical applications. The artificial material combinations determine the characterization of dialectic phantoms. However, a method that reliably determined the composition of artificial materials with designed values of dielectric properties and frequency is still lacking. In this work, we propose a method that easily determine the compositions of phantom to mimic the human tissues from 16 MHz to 3 GHz.

Modeling Colorectal Cancer-Induced Liver Portal Vein Microthrombus on a Hepatic Lobule Chip.

Colorectal cancer is one of the most common malignant tumors. At the advanced stage of colorectal cancer, cancer cells migrate with the blood to the liver from the hepatic portal vein, eventually resulting in a portal vein tumor thrombus (PVTT). To date, the progression of the early onset of PVTT [portal vein microthrombus (PVmT) induced by tumors] is unclear. Herein, we developed an on-chip PVmT model by loading the spheroid of colorectal cancer cells into the portal vein of a hepatic lobule chip (HLC). On the HLC, the progression of PVmT was presented, and early changes in metabolites of hepatic cells and in structures of hepatic plates and sinusoids induced by PVmT were analyzed. We replicated intrahepatic angiogenesis, thickened blood vessels, an increased number of hepatocytes, disordered hepatic plates, and decreased concentrations of biomarkers of hepatic cell functions in PVmT progression on a microfluidic chip for the first time. In addition, the combined therapy of thermo-ablation and chemo-drug for PVmT was preliminarily demonstrated. This study provides a promising method for understanding PVTT evolution and offers a valuable reference for PVTT therapy.

Breast intervention device for low-field MRI with a customized unilateral coil.

With the incidence of breast cancer rising to the top among female malignant tumors, magnetic resonance images guided breast biopsy intervention and minimally invasive treatment have developed as a clinically practical research issue. High field studies have shown the diagnostic value of breast MRI, but the examination costs greatly exceed those of competing conventional mammography. In this case, low-field MRI cannot merely provide typical MRI contrast, but also significantly reduce the cost of diagnosis and treatment for breast cancer patients. This work describes a unilateral breast coil and prototype intervention device, which provides a customized solution for low-field MRI-guided breast intervention. Results demonstrate that the low-field MRI breast intervention device facilitates medical intervention procedures. And the designed positioning device can locate the target lesion within 2-3 mm accuracy. Phantom tests with the customized unilateral coil indicate that the open loops perform as well as the 4-channel commercial closed breast coil, presenting a relatively good SNR (signal-to-noise ratio) and uniformity characteristics. MR scanning images of the volunteer breast using the breast intervention coil also show high SNR, which lays a foundation for further implementation of image-guided breast interventional minimally invasive surgery with the low-field MRI system.

Live Imaging of 3D Hanging Drop Arrays through Manipulation of Light-Responsive Pyroelectric Slippery Surface and Chip Adhesion.

Three-dimensional (3D) hanging drop cell culture is widely used in organoid culture because of its lack of selection pressure and rapid cell aggregation. However, current hanging drop technology has limitations, such as a dependence on complex microfluidic transport channels or specific capillary force templates for drop formation, which leads to unchangeable drop features. These methods also hinder live imaging because of space and complexity constraints. Here, we have developed a hanging drop construction method and created a flexible 3D hanging drop construction platform composed of a manipulation module and an adhesion module. Their harmonious operation allows for the easy construction of hanging drops of varying sizes, types, and patterns. Our platform produces a cell hanging drop chip with small sizes and clear fields of view, thereby making it compatible with live imaging. This platform has great potential for personalized medicine, cancer and drug discovery, tissue engineering, and stem cell research.

Spontaneous Separation of Immiscible Organic Droplets on Asymmetric Wedge Channels with Hierarchical Microchannels.

Spontaneous separation of immiscible organic droplets has substantial research implications for environmental protection and resource regeneration. Compared to the widely explored separation of oil-water mixtures, there are fewer reports on separating mixed organic droplets on open surfaces due to the low surface tension differences. Efficient separation of mixed organic liquids by exploiting the rapid spontaneous transport of droplets on open surfaces remains a challenge. Here, through the fusion of inspiration from the fast droplet transport capability of Sarracenia trichome and the asymmetric wedge channel structure of shorebird beaks, this work proposes a spine with hierarchical microchannels and wedge channels (SHMW). Due to the synergistic effect of capillary force and asymmetric Laplace force, the SHMW can rapidly separate mixed organic droplets into two pure phases without requiring additional energy. In particular, the self-spreading of the oil solution on the open channel surface is utilized to amplify the surface energy difference between two droplets, and SHMW achieves the pickup of oil droplets floating on the surface of the organic solution. The maximum separation efficiency on 3-SHMW can reach 99.63%, and it can also realize the antigravity separation of mixed organic droplets with a surface tension difference as low as 0.87 mN·m-1. Furthermore, SHMW performs controllable separation, oil droplet pickup, and continuous separation and collection of mixed organic droplets. It is expected that this cooperative structure composed of hierarchical microchannels and wedge channels will be realized in resource recovery or chemical reactions in industrial production processes.

On-Chip Label-Free Sorting of Living and Dead Cells.

With the emergence of various cutting-edge micromachining technologies, lab on a chip is growing rapidly, but it is always a challenge to realize the on-chip separation of living cells from cell samples without affecting cell activity and function. Herein, we report a novel on-chip label-free method for sorting living and dead cells by integrating the hypertonic stimulus and tilted-angle standing surface acoustic wave (T-SSAW) technologies. On a self-designed microfluidic chip, the hypertonic stimulus is used to distinguish cells by producing volume differences between living and dead cells, while T-SSAW is used to separate living and dead cells according to the cell volume difference. Under the optimized operation conditions, for the sample containing 50% of living human umbilical vein endothelial cells (HUVECs) and 50% of dead HUVECs treated with paraformaldehyde, the purity of living cells after the first separation can reach approximately 80%, while after the second separation, it can be as high as 93%; furthermore, the purity of living cells after separation increases with the initial proportion of living cells. In addition, the chip we designed is safe for cells and can robustly handle cell samples with different cell types or different causes of cell death. This work provides a new design of a microfluidic chip for label-free sorting of living and dead cells, greatly promoting the multi-functionality of lab on a chip.

A depth-of-interaction rebinning method based on both geometric and activity weights.

BACKGROUND AND OBJECTIVE: For positron emission tomography (PET) scanners with depth-of-interaction (DOI) measurement, the DOI rebinning method that utilizes DOI information to process the projection data is critical to image quality. Current DOI rebinning methods map coincidence events onto the rebinned sinogram based on the correlation of lines of response (LOR). This study aims to incorporate prior radioactivity distribution of the imaging object into DOI rebinning to obtain better image quality. METHODS: A DOI rebinning method based on both geometric and activity weights was proposed to assign coincidence events to the rebinned sinogram defined by a virtual ring. The geometric weights, representing the correlation between LORs, were calculated based on the areas of intersection. The activity weights, reflecting the activity distribution of the imaging object, were derived from the previous reconstructed image. RESULTS: Monte Carlo simulation data from four phantoms, including the image quality phantom, Derenzo phantom, and two rat-like ROBY phantoms, was used to evaluate the proposed method. The recovery coefficient (RC), contrast recovery coefficient (CRC), structural similarity index measure (SSIM), and peak signal-to-noise ratio (PSNR) were used as image quality metrics. Compared to other DOI rebinning methods, the proposed method achieved the highest RC (maximum improvement of 32%) and CRC at the same noise level and was also optimal in terms of the SSIM and PSNR. Meanwhile, incorporating the prior activity distribution into DOI rebinning also improved the image reconstruction speed. CONCLUSIONS: This work developed a new DOI rebinning method combining the correlation of LORs with the prior activity distribution, achieving relatively optimal image quality and reconstruction speed. Furthermore, it still needs to be evaluated on the actual equipment.