Digital rock is an emerging area of rock physics, which involves scanning reservoir rocks using X-ray micro computed tomography (XCT) scanners and using it for various petrophysical computations and evaluations. The acquired micro CT projections are used to reconstruct the X-ray attenuation maps of the rock. The image reconstruction problem can be solved by utilization of analytical (such as Feldkamp–Davis–Kress (FDK) algorithm) or iterative methods. Analytical schemes are typically computationally more efficient and hence preferred for large datasets such as digital rocks. Iterative schemes like maximum likelihood expectation maximization (MLEM) are known to generate accurate image representation over analytical scheme in limited data (and/or noisy) situations, however iterative schemes are computationally expensive. In this work, we have parallelized the forward and inverse operators used in the MLEM algorithm on multiple graphics processing units (multi-GPU) platforms. The multi-GPU implementation involves dividing the rock volumes and detector geometry into smaller modules . Each of the module was passed onto different GPU to enable computation of forward and inverse operations. We observed an acceleration of  The high-resolution representation enables us to obtain various physical properties like elasticity, transport and electrical related to the rock. These digital rock physics problems require high-resolution volumetric data to accurately resolve small pores2. One of the approaches to obtain these high resolution three-dimensional (3D) representation of the pore-phase and mineral-phase in the rock is through micro X-ray computed tomography  transmit through the rock-samples in a cone-beam configuration and are detected using a two-dimensional flat panel detector/CCD-camera in a trans-illumination mode. The sample is then rotated to obtain tomographic measurements (projections) at various angles.Digital rock is an emerging area in rock physics which aims to quantify elastic moduli, permeability, resistivity and elastic-wave velocity using high resolution representation of complex pore geometry in the rock5. The aim of reconstruction process is to convert the information contained in acquired projections to X-ray attenuation coefficient maps which represent different phases of the rock geometry such as pore, grain, clay, minerals, and their respective boundaries2. The 3D reconstruction is typically performed using direct backprojection  methods, like Feldkamp–Davis–Kress (FDK) algorithm due to its lower computational footprint6. However, analytical methods are known to generate 3D volumes that are not quantitative in nature7. Recent emphasis has been on developing iterative methods, which have demonstrated potential in resolving the 3D rock volumes with higher quantitative accuracy compared to analytical methods7. These methods also help to incorporate prior information for improving the reconstruction quality and for dynamic tomography of time resolved processes in porous media. Iterative methods tend to be computationally expensive compared to analytical methods, making them less attractive while working with large datasets8. Iterative reconstruction techniques involve matching the measured tomographic data with the signals predicted by the model in an iterative fashion8. Hence iterative methods require repeated computation of forward and inverse operators, making it computationally challenging for large dataset that commonly arise in digital rock analysis.The obtained tomographic measurements are used to reconstruct three-dimensional volumetric information of the scanned rock7. However the SART reconstruction was restricted to volumes of size 7. The main aim of this work is to enable iterative reconstruction with large-scale digital rock data. Earlier works have parallelized iterative reconstruction algorithms on graphics processing units (GPU), wherein the matrix operations was parallelized on GPU environments9. Other approach included developing multi-threaded approach for each ray to accelerate forward projection operations on GPU environment10, which is different from the block based decomposition proposed in this work. Further three-dimensional ordered sub-set expectation maximization approach was proposed in the context of PET11, however this approach was working with small imaging volumes. A detailed review on developments of GPU based parallelization for image reconstruction problems can be found in Ref.12. Since SART scheme was developed on single-GPU platform, performing reconstruction at higher resolution is prohibited due to limited available on-board memory on single GPU. Note that MLEM approach is statistical in nature and used routinely in positron emission tomography (PET) as opposed to SART where the data is typically noisy. Further, building a system matrix for large-scale three-dimensional problems is not feasible due to the memory overhead associated with storing the matrix, hence our work parallelized the MLEM reconstruction using forward/inverse operators. In this work, we have utilized MLEM approach for resolving three-dimensional volumes of rock samples. Further the MLEM scheme was parallelized on multiple graphics processing units (multi-GPU) platforms. Specifically, the most time-consuming operations in the MLEM algorithm was the forward and inverse operators, these operators were parallelized on multi-GPU architecture, to provide much needed acceleration for MLEM algorithm.Iterative reconstruction in computed tomography is performed by algebraic schemes , simultaneous iterative reconstruction technique (SIRT)) and statistical schemes (maximum likelihood expectation maximization (MLEM), ordered subset expectation maximization (OSEM)). Earlier works in digital rock have deployed SART and reported high accuracy compared to the FDK approachThe paper is organized by initially explaining the materials and methods developed. Next section elaborates on the results pertaining to the comparison of FDK and MLEM approaches. This is followed by a discussion section of the observed results, lastly the manuscript briefly explains the conclusions and possible future work.MLEM approach involves two operations, namely forward projection (forward operator) and backprojection (inverse operator).f be the object being scanned and 6,u, w, v are local detector coordinates with unit vectors given as d indicates the source to detector distance).Modelling the penetration of X-rays through the rock using cone-beam configuration can be achieved using Radon operator. Let 6,P is the projection at an angle 13. The FDK algorithm backprojects the detected 2D projections onto 3D volume along with the scaling factors (which are based on source to detector distance and source to object distance). The 2D projection gets backprojected onto the 3D volume. The overall FDK based reconstruction can be written as8,kth iteration and i and j. The above equation can be elaborated as,FP and BP indicates the forward projection and backprojection operations explained in earlier section wherein the variables image and Experimental Projection are in three dimensions while performing the forward and back projection.MLEM approach involves maximizing the log likelihood function of Poisson statistics. MLEM can provide accurate quantitative reconstructions compared to analytical techniques in the limited data situations. The formulation for MLEM type approach can be written as13. Note that building the system matrix is not feasible for digital rock problems, because the number of measurements are As stated earlier, our work parallelized the MLEM algorithm using the forward and inverse operators as opposed to using the system matrix approach. The forward and inverse operators are implemented based on linear interpolation operations between the projection space and the imaging volume rather than using a matrix operatorFigure The mathematical equations used for forward operation is13) to reconstruct the three dimensional imaging volume of To obtain the cone-beam CT (CBCT) data of the rock sample, rock samples were scanned with the Xradia 520 Versa Zeiss micro-CT scanner. A CCD based detector was used to capture the projections obtained by rotating the rock sample over 3200 viewing angles for a 360 degrees rotation to capture 3201 projections. The detector array was having a configuration of The CT projection data acquired from the Zeiss scanner was used to reconstruct the three-dimensional rock volume using multi-GPU and multi-core CPU architectures. The results pertaining to multi-GPU implementation along the Y–Z and X–Y planes are indicated in Figs. The computational comparison for single iteration of MLEM, which involves computing the forward and inverse operations was shown in Fig. Next, we also investigated the choice of overlap size on the quality of the reconstructed rock images. To this end, MLEM reconstructions  seems to be amplified using the FDK approach compared to the MLEM approach  toolbox was also developed to run iterative reconstruction on MATLAB-based CUDA solvers9. Note that TIGRE toolbox was capable of running these algorithms on single GPU cards9, which may not be helpful to run large-scale problems relevant to digital rock platforms. Obtaining high-resolution reconstruction with sub-micron resolution is the need of the hour for digital rock platforms to enable geologists to accurately resolve pore-scale distribution which plays crucial role in mercury injection capillary pressure and other transport properties16. However, with the current available hardware, this would not be possible requiring more advances in GPU hardware to enable increased on-board GPU memory for performing these memory-intensive computations. It is important to note that the proposed method is scalable, since we were able to run multi-GPU accelerated MLEM algorithm on rocks having different sizes i.e. Earlier works have developed analytical solvers like FDK on multi-GPU framework19. Further the CT reconstruction seems to have beam-hardening effects  and the reconstruction accuracy that could be achieved. Our analysis indicated that having an overlap size of approximately equal to entclass1pt{minimaIt is also important to note that per core cost of GPU is much lesser compared to CPU. Overall given the cost effectiveness of GPU, it is always desirable to implement the advanced reconstruction algorithms especially involving large high-resolution CT data, in scenarios like digital rock, in the multi-GPU environment both from cost-effectiveness as well as computational time. This work has shown the advantage of multi-GPU environment and have paved a way for deploying advanced reconstruction methods for digital rock. As part of future work, the multi-GPU codes could be further accelerated by implementing this methodology in light-weight programming languages like C alongside CUDA, and implementing custom-made kernels to parallelize forward projection and back projection operations. Note that the main bottleneck is scalability to larger volumes with minimum latency, which can be addressed by implementing parallelization operations using C programming in CUDA framework.Digital rock involves reconstructing large three-dimensional imaging volumes of rock samples at high-resolution which influence evaluation of various petrophysical properties. These large CT datasets are typically reconstructed using analytical schemes as model based iterative solvers are computationally intractable due to huge computational complexity associated with their implementation on multi-core CPUs. In this work, we have parallelized the MLEM algorithm on multi-GPU architecture to enable much needed scalability for using iterative reconstruction algorithms for digital rock implementation. Each iteration of MLEM involves performing one forward and one inverse operation which are the main computational bottlenecks, hence we have parallelized these operations on multi-GPU platform. Specifically, the rock volume and detector array were divided into many modules  and each module was transferred to different GPU cards to enable accelerated computation of forward and back-projection operations. The operations on each card are load balanced reducing any latency in their implementation. The results indicated that the proposed multi-GPU implementation was approximately thirty times faster than multi-core CPU implementation. Further the error between multi-GPU and multi-core CPU implementation was minimal, making the multi-GPU implementation attractive for further investigation of iterative methods for digital rock applications.Supplementary Information.


Automatic identification of interventional devices in X-ray (XR) fluoroscopy offers the potential of improved navigation during transcatheter endovascular procedures. This paper presents a prototype implementation of fully automatic 3D reconstruction of a cryo-balloon catheter during pulmonary vein isolation (PVI) procedures by deep learning approaches.We employ convolutional neural networks (CNN) to automatically identify the cryo-balloon XR marker and catheter shaft in 2D fluoroscopy during PVI. Training data are generated exploiting established semiautomatic techniques, including template-matching and analytical graph building. A first network of U-net architecture uses a single grayscale XR image as input and yields the mask of the XR marker. A second network of the similar architecture is trained using the mask of the XR marker as additional input to the grayscale XR image for the segmentation of the cryo-balloon catheter shaft mask. The structures automatically identified in two 2D images with different angulations are then used to reconstruct the cryo-balloon in 3D.Automatic identification of the XR marker was successful in 78% of test cases and in 100% for the catheter shaft. Training of the model for prediction of the XR marker mask was successful with 3426 training samples. Incorporation of the XR marker mask as additional input for the model predicting the catheter shaft allowed to achieve good training result with only 805 training samples. The average prediction time per frame was 14.47 ms for the XR marker and 78.22 ms for the catheter shaft. Localization accuracy for the XR marker yielded on average 1.52 pixels or 0.56 mm.In this paper, we report a novel method for automatic detection and 3D reconstruction of the cryo-balloon catheter shaft and marker from 2D fluoroscopic images. Initial evaluation yields promising results thus indicating the high potential of CNNs as alternatives to the current state-of-the-art solutions. Atrial fibrillation is a common heart arrhythmia associated with an increased risk of stroke. The current state-of-the-art treatment option is minimally invasive catheter ablation. Cryo-balloon catheters isolate a pulmonary vein by freezing the tissue annularly around its ostium using liquid nitrogen injected into the balloon device. The planning of cryo-balloon ablations of atrial fibrillation is a crucial task for a physician as determining the correct size of the balloon catheter is required for successful isolation of each pulmonary vein (PV). The radio-opaque marker of the cryo-balloon localized in the biplane X-ray (XR) fluoroscopy facilitates the verification of the balloon catheter position with respect to the preoperative data set of the left atrium . FurtherAlthough convolutional neural networks (CNN) are extensively used for catheter detection and tracking, a large amount of annotated training data is required for all deep learning approaches for pixel-level segmentation. Manual pixel-level labeling is laborious and time-consuming; thus, methods reducing the required manual interaction will greatly facilitate the development of CNN models for semantic segmentation .In this work, we propose to use networks of similar encoder-decoder U-net architecture to detect separately the XR marker and the cryo-balloon catheter shaft in the XR images from cryo-balloon pulmonary vein isolation (PVI) procedures. For training of the networks, semiautomatically annotated training data were used. The annotated training data for marker prediction were used additionally to the catheter shaft training data for further improvement of prediction capability and simultaneous reduction of the required amount of training data.marker) and the cryo-balloon catheter shaft (U-netshaft) separately in the XR images from PVI procedures. The adapted U-net model consists of a convolutional part downsampled with the maxpool layer and strided transposed convolutional upsampling part in combination with dropout regularization and residual connection to the output and was previously described by our group [marker) or 4 (U-netshaft) samples per pass with the adaptive moment estimation algorithm. U-netmarker uses a lossless grayscale XR image as input and predicts the radio-opaque marker as a mask (maskmarker). U-netshaft consists of two inputs: current lossless grayscale XR image and maskmarker, and predicts the catheter shaft mask (maskshaft). The implemented algorithm showing the annotation and training steps with corresponding inputs/outputs, as well as predicted outputs of both models is sketched in Fig. The proposed method utilizes an adapted CNN model of the well-known U-net architecture to segment the radio-opaque marker  were used to train/validate the U-netshaft. A total of 508 XR images (13 biplane runs from 4 patients) were used for testing both models.Eighty-nine fluoroscopic runs from 15 different PVI patients acquired on biplane C-arm X-ray system  were used for development and evaluation of the proposed method. Two patients’ data were acquired in monoplane mode , 13 patients’ data—in biplane mode . A total of 3426 XR images of 512 × 512 pixels resolution  were successfully annotated and used for training/validation of U-netmarker) was created by thresholding the signal intensity values of the XR image  was created from a centerline model build similarly as described in [Catheter shaft binary mask , including the balloon ellipsoid, catheter shaft with tip, and radio-opaque marker Fig. . With thSince no 3D data were available as ground truth, the result of 3D reconstruction was back-projected into the image planes and the deviation of the re-projected XR marker and direction vector was calculated using the Euclidean distance between the seed points and re-projected reconstructed XR markers.The XR marker of the cryo-balloon could be visually detected in 394 (78% of cases) test samples, whereas 3426 image samples were used for training and validation. A total of 805 training/validation samples were required to achieve 100% visual detectability of the catheter shaft . This is most likely due to the very limited availability of similar training data in which proper annotation was neither successful with the automatic approach nor manually. Moreover, the approach to uniquely identify the respective XR marker and catheter shaft in case of multiple detected regions in the predicted masks should be developed.3D reconstruction of the cryo-balloon was successful by combining the 3D reconstruction of the XR marker using epipolar geometry with the reconstruction of the 3D directional vector of the catheter shaft. For successful 3D reconstruction, detection of the XR marker and catheter shaft in both views should be guaranteed by the neural networks. The accuracy of the reconstruction method is limited by the calibration accuracy of the biplane XR system and is restricted to no or very low catheter shaft angulation, as only a direction vector fitted to the centerline spline is considered for reconstruction.


BRCA1/2 mutations have a higher risk of developing breast and ovarian cancer compared to women of the general population. Various preventive options are available to deal with the increased risk of developing cancer. These include intensified breast cancer screening and risk-reducing bilateral mastectomy and salpingo-oophorectomy. The choice of a preventive option can lead to increased decisional conflict. To support these women in their decision-making process, two evidence-based decision aids were developed in an upstream research process and adapted to the German healthcare context. These will be evaluated within a randomised controlled trial (RCT) in terms of their effects on decision-making, women’s level of information and psychological outcome variables.Women with BRCA1/2 mutations (A) without a history of cancer or (B) with a history of unilateral breast cancer who have received post-test genetic counselling will be enrolled. Upon study consent, women will be randomly assigned to either the intervention or the control group. All participants will receive standard care including a physician’s letter summarising the counselling content. After baseline data collection (t0), the intervention group receives the respective decision aid while the control group receives standard care only. The primary outcome variable assessed at a 3-month follow-up (t1) is the change of extent in decisional conflict . Secondary outcome variables comprise the stage of decision-making, self-reported symptoms of anxiety, depression and stress due to the genetic test result, and knowledge regarding cancer risks and preventive options. At t1, the extent of preparation for decision-making and acceptability of the decision aids will also be examined. Another secondary outcome variable assessed at 6-month follow-up (t2) is the extent of decision regret.A sample of 310 women carrying BRCA1/2 mutation carriers in Germany to be evaluated regarding their effectiveness and acceptability in clinical use within an RCT. Subsequently, they are to be integrated into the care concept of the centres of the German Consortium for Hereditary Breast and Ovarian Cancer and the affiliated breast centres.These will be the first decision aids available for DRKS00015823. Retrospectively registered on 14 June 2019DRKS  The order of the items has been modified to group similar items (see BRCA1 or BRCA2 gene face a high risk of developing breast cancer (BC) and ovarian cancer (OC). The average cumulative life-time risk for BC increases with age . The recruitment of the study participants started in January 2019. The recruitment closed on 30 September 2021.


Nonpharmacological interventions targeting putative network mechanisms of major depressive disorder (MDD) may represent novel treatments. This mechanistic study investigates how a video game-like intervention, designed to improve cognitive control network (CCN) functioning by targeting multitasking, influences the CCN of middle-aged and older adults with MDD. The sample consisted of 34 adults aged 45–75 with SCID-defined diagnosis of MDD, Hamilton depression rating scale scores ≥20, and a deficit in cognitive control. Participants were instructed to play at home for 20–25 min per day, at least 5 times per week, for 4 weeks. Evidence of target engagement was defined a priori as >2/3 of participants showing CCN improvement. CCN engagement was defined as a change in a Z score of ≥0.5 on functional magnetic resonance imaging (fMRI) in activation and functional connectivity of the CCN during task-based and resting-state fMRI, respectively. 74% of participants showed a change in activation of the CCN, and 72% showed an increase in resting-state functional connectivity. Sixty-eight percent demonstrated improved cognitive control function, measured as either improvement on sustained attention or working memory performance or reduced self-reported symptoms of apathy on the frontal systems behavioral scale (FrsBe). Participants also reported a significant reduction in mood symptoms measured by PHQ-9. A remotely deployed neuroscience-informed video game-like intervention improves both CCN functions and mood in middle-aged and older adults with MDD. This easily-disseminated intervention may rescue CCN dysfunction present in a substantial subset of middle-aged and older adults with MDD. Even when standard treatments improve mood symptoms, many individuals, especially older adults, are left with persistent executive dysfunction7 that is associated with disability7, and increased risk of depression recurrence9. Thus far, alternative pharmacologic approaches designed to target comorbid executive dysfunction demonstrate limited efficacy10. Likewise, psychotherapy we optimized to treat individuals suffering from major depressive disorder (MDD) with executive dysfunction improved mood symptoms12, but not executive dysfunction13. Novel strategies are needed that target persistent dysfunction among individuals with MDD.At least one-third of individuals treated with antidepressant medications or psychotherapy do not achieve adequate response, even after multiple treatments trials18. The CCN, comprised of the dorsal anterior cingulate cortex (dACC), dorsolateral prefrontal cortices, and posterior parietal cortices support the flexible maintenance of goal-directed behavior in the face of changing internal and environmental demands20. Nonpharmacological interventions that aim to rescue CCN network dysfunctions could therefore represent a promising, personalized approach for the large subset of individuals with MDD who have an inefficient CCN and are often less likely to benefit from standard treatments.Executive dysfunction present in older individuals with MDD appears to reflect inefficient functioning of the cognitive control network (CCN)13. In that study, individuals over the age of 60 in a major depressive episode were randomized to problem-solving therapy (PST), efficacious psychotherapy for older adults with depression, or digital intervention. Although the two groups showed a similar improvement in depression, only the group randomized to the multitasking game-like condition showed significant improvement in working memory and sustained attention performance13.One method to target CCN dysfunction applies digital cognitive interventions designed to improve CCN functions through the repetitive engagement of the network. We conducted a preliminary, proof of concept RCT of a video game-like intervention designed to target the CCN by improving age-related deficits in multitasking21. That is they may show clinical benefit without demonstrating how an intervention engages the hypothesized target. In the present study, we aimed to determine whether an algorithmically delivered video game-like intervention targeting multitasking can modulate CCN function in middle-aged and older adults with MDD. We hypothesized that after 4 weeks of training with this intervention at least 2/3 of participants would show a significant improvement in focal activation of the anterior CCN and an increase in functional connectivity of the CCN at rest. In addition, we assessed whether improvement in CCN functioning would be reflected in a similar degree and frequency of improvement demonstrated on either measure of cognitive control performance as assessed by a visual continuous performance task (CPT) and a delayed recognition working memory task or decreased complaints on the apathy subscale of the frontal systems behavior scale (FrSBe)22.The results of this pilot RCT shed limited light on the mechanism of action of the intervention. In fact, nearly all non-pharmacologic intervention studies in MDD focus on demonstrating efficacy, without confirming target engagementThis study was the proof-of-concept phase of a two-phase clinical trial to evaluate mechanisms of action of the video game-like intervention, specifically engagement of CCN as measured by functional magnetic resonance imaging (fMRI), computerized sustained attention, and working memory tasks, and self-reported symptoms of apathy. The study used a single-arm, open-label design. Measures of CCN target engagement were administered at baseline/pre-intervention and week 4/post-intervention with analysis that focused on changes in CCN function over 4 weeks.23, conducted by a study clinician. Eligibility required baseline Hamilton depression rating scale24 scores ≥20 . Participants were required to demonstrate a deficit in cognitive control, defined as >1 standard deviation (SD) below the mean for their age and education on at least one of the following: Stroop Color Word Interference25, Trail Making Part B26, or FrSBe22. Participants were either not currently on antidepressants or on a stable dose for at least 12 weeks, with no intent to change dose during study participation. Individuals were excluded if they had a mini-mental state examination (MMSE)27 score >1 SD below the mean for their age and education level, or a contraindication to MRI. Individuals with a history of neurologic illnesses, psychosis or mania, or acute medical illnesses were also excluded.Participants were adults aged 45–75. Prior to study entry, MDD diagnosis was confirmed by Structured Clinical Interview for DSM-V (SCID)All participants provided written informed consent, as per the study protocol approved by the IRBs of Weill Cornell Medicine, University of Washington, and the Nathan Kline Institute.28. The game begins with an assessment of the participants’ multi-tasking cost, i.e., tests of reaction time alone, navigation alone, and then the two domains combined. This sets the level of difficulty for each participant, personalizing the training experience. Improvement throughout the intervention transports the participant to different visual “worlds”, designed to immerse the player and enhance the depth of engagement and compliance. Frequent performance assessments are embedded in the program to determine the level of improvement during training and adaptively set a therapeutic regimen based on the participant’s performance. Thus, the participant is challenged to continue to improve upon their own performance to reach the next level. The same adaptive mechanics utilized in the assessment are employed in the training sessions which keep the player at ~80% accuracy.The intervention is a self-guided therapeutic video game-like intervention  that involves a combination of visuomotor and perceptual discrimination tasks intended to adaptively treat multi-tasking deficiencies29 to assess depressive symptoms as part of safety and mood monitoring.The intervention relied on at-home use of the therapeutic video game, delivered via Apple iPad, and 4 weekly in-person visits with a Masters or PhD-level care manager who provided instruction and technical support for participation in the intervention. At each study visit the participants completed the patient health questionnaire-9 (PHQ-9)During the first session, care managers introduced the game, observed participants’ completion of a practice session, and set an action plan with participants to ensure regular gameplay. During the weekly follow-up sessions, care managers reviewed the adherence and action plan and a dashboard within the application tracking performance and time played. They worked with participants to adjust the action plan as needed if adherence was low, defined as less than 5 days of gameplay.The intervention required 20–25 min of gameplay for a minimum of 5 days and up to 7 days per week. The game locked after five sessions per day.The MRI, computerized cognitive control tasks, and self-report measures of CCN function were collected at baseline and following 4 weeks of the intervention.CCN circuitry was measured by assessing focal activation of the anterior CCN using task-based fMRI during a Stroop/Flanker task and resting-state functional connectivity (rsFC) of the CCN. Details related to scanning parameters, image acquisition, and preprocessing steps are described in the Supplementary Information.25 target word and two surrounding Flanker30 words. They responded to the ink color of the central target word with a button press while ignoring multiple sources of cognitive interference: what the word says and the surrounding distractor word. The main contrast of interest for the task-based MRI analyses focused on the congruency of the Stroop targets: congruent  vs. incongruent . See Supplementary Fig. Participants viewed three color words on the screen: the central congruent or incongruent StroopFollowing preprocessing of the task-based data, we extracted percent signal activation during the Stroop/Flanker task in regions of the anterior portion of the CCN: middle frontal gyrus (MFG) and dACC from baseline to week 4 MRI. Beta values were extracted for incongruent trials only since they had the highest cognitive control load. Our z-scored measure of target engagement for task-based activation was calculated as follows: (week 4 incongruent MFG and dACC activation − baseline MFG and dACC activation)/baseline SD of MFG and dACC activation. The mean and SD of the extracted beta values were calculated within-region.We conducted a seed-based rsFC analysis to investigate the change in connectivity among nodes of the anterior portion of the CCN  following 4 weeks of the intervention.To examine target engagement, we measured within-CCN connectivity between MFG and dACC. Following preprocessing of the resting-state data, we extracted correlation coefficients between these regions at baseline and week 4 of EVO with 4 mm spherical seeds placed bilaterally in the MFG  and the dACC . Our z-scored measure of target engagement for the rsFC analysis was calculated as follows: /baseline SD of partial correlation between MFG and dACC.31; (2) a continuous performance test (CPT)32, a measure of sustained attention.Two cognitive tasks were used to measure target engagement of the CCN: (1) a delayed recognition working memory task 28 and calculated Z-scores as follows: (week 4 ignore distractor RT − baseline ignore distractor RT)/baseline SD of ignoring distractor RT.The AID includes aspects of visual information processing that are held constant  while other task demands are manipulated. Our analysis focused on the “ignore distractor” (ID) condition, during which participants are instructed to ignore the distracting face while maintaining the representation of the cue face. We analyzed RT during this condition32, a 23-min, fixed interval, visual CPT that we modeled after the test of variable attention (TOVA)33. Participants were instructed to respond to the target (white square at the top edge of the screen) and to ignore the non-target (white square at the bottom edge of the screen). We analyzed response time in the sustained attention condition (target stimuli appears in 22% of trails) and calculated Z-scores as follows: (week 4 sustained attention RT − baseline sustained attention RT)/baseline SD of sustained attention RT.We used a CPT22, a self-report scale that measures executive function. We examined the apathy subscale to capture cognitive symptoms that are likely not represented in the other cognitive measures. We analyzed the FrSBe apathy subscale and calculated z-scores as follows: (week 4 score − baseline score)/baseline SD of the score.We used the apathy subscale of the FrSBe35. We determined that 66% of the sample would need to show significant improvement in the CCN on fMRI (task-based activation and rsFC) and either CCN task performance or self-reported symptoms of cognitive control. Significant improvement was defined as Z-scores ≥ 0.5 for pre- to post-EVO change in CCN task-based activation and functional connectivity, as well as CPT and/or AID performance, or FrSBe self-report score.The primary purpose of this phase of the clinical trial was to establish whether or not the intervention engaged the hypothesized CCN target. We defined the go/no-go criteria a priori, informed by other proof-of-concept trial methodologySecondary analyses of CCN circuitry included exploratory whole-brain analyses of Stroop/Flanker task performance pre- and post-EVO, as well as whole-brain seed-based exploration of changes in rsFC from pre- to post-EVO. The methodological details of these analyses are described in Supplementary Information. We also explored the association between changes in rsFC and post-intervention performance and self-reported CCN function with correlational analyses comparing the Z-scored change in rsFC pre- to post-EVO to post-EVO performance on the CPT and AID tasks and post-EVO self-reported FrSBe scores. These results are reported as Pearson’s correlation coefficients.Exploratory analysis of depression outcomes consisted of repeated measures ANOVA to determine changes in mood over time, the proportion of participants exhibiting response (defined as a 50% decrease in PHQ-9 scores from baseline to 4 weeks), and remission (defined as a PHQ-9 score of less than 5 at 4 weeks).N = 24) of the sample was female, aged 45–75 years . The mean education level was 15.8 years (SD = 2.2) and the mean MMSE score was 28.9 (SD = 1.0). At the baseline visit, the mean HAM-D score was 24.4 (SD = 4.9). All subjects completed 4 weeks of the intervention.Forty-one individuals were enrolled in the trial. Seven participants were excluded from the analysis . To assess connectivity, we extracted correlation coefficients between MFG and dACC seeds Fig.  at baselTwenty-three of the 34 participants (68%) showed an improvement ≥0.5 on our composite Z-score of CCN performance (on the AID and/or the CPT task) after 4 weeks of video game use. Participants were significantly faster from pre- to post-intervention on the ignore distractor condition of the AID and the sustained attention condition of the CPT Fig. a, b.Fig.Z-score of self-reported CCN symptoms (on the AID and/or the CPT task) after 4 weeks of EVO. Self-reported apathy was significantly reduced pre- to post-intervention  showed an improvement ≥0.5 on our composite ion Fig. .For exploratory subgroup analyses examining relationships of gender, age, and duration of gameplay to target engagement, see Supplementary Table Task-based activation following 4 weeks of therapeutic video game useTo explore the pattern of whole-brain activation following use of the intervention, we assessed activation of incongruent relative to congruent Stroop/Flanker trials A group contrast map showing all incongruent trials minus all congruent (collapsed across Flanker similarity) trials at week 4 revealed a positive cluster  surviving cluster correction, located in the right MFG . Increased rsFC following EVO was also observed between the right MFG seed and two clusters: one located in the right inferior frontal gyrus (IFG)  and one located in the right superior temporal gyrus (STG) . Significant clusters are displayed in Fig. r(23) = 0.44, p = 0.03; Fig. r(24) = −0.22, p = 0.28; Fig. r(24) = −0.44, p = 0.02; Fig. We observed change in rsFC of the CCN following 4 weeks of video gameplay was associated with post-intervention scores on behavioral and self-report measures of CCN target engagement. Specifically, pre- to post-EVO change in rsFC between R MFG and R STG was associated with greater working memory ability (measured by AID performance in the “ignore distractor” condition) post-intervention , sustained attention or working memory performance , and self-reported behavioral symptoms of cognitive control disturbance . Specifically, we found that a digital therapeutic strategy designed to improve cognitive control abilities  improved brain-based focal activation and rsFC functional connectivity on fMRI of the CCN in more than 70% of our sample of middle-aged and older adults with MDD and cognitive control dysfunction. In parallel, we identified significant improvements in performance and self-reported CCN functions in 68% of participants. Taken together, these convergent results demonstrate target engagement of the CCN.13. However, that study could not address the mechanism of action. Here, we demonstrate that improvement in executive functions and depression may be the results of a change in activation and functional connectivity of CCN, validating this novel treatment target.These findings extend our prior proof-of-concept randomized controlled trial conducted in an elderly sample of individuals suffering from a major depressive episode. That trial demonstrated similar antidepressant efficacy for the game intervention and PST, but only the former was associated with improvement in cognitive control performance40, in which response rates after 8 weeks of antidepressant medication treatment have been reported to be between 25% and 60%40.As in the prior study, our exploratory analyses found this gamified intervention to have a significant impact on mood after 4 weeks of treatment. More than half of those treated met the criteria for symptomatic response, and one quarter for remission. Notably, this is a sample characterized with risk factors for poor response to antidepressant treatment44. Recent meta-analyses of prior cognitive training interventions showed a small to moderate effect size for symptom improvement (0.43) in depression45. The majority of these trials have been relatively small and, with few exceptions43, have not directly interrogated the underlying neural mechanisms tied to improved mood-based symptoms. In this study, the intervention was designed to selectively improve CCN functions that are both susceptible to effects of normal aging and predictive of poor antidepressant response in older individuals with MDD. The current findings, in conjunction with our previous results, suggest that the engagement of the CCN through repeated cognitive stimulation may be a central mechanism for rescuing dysfunctional brain networks that contribute to both the mood and cognitive symptoms in many suffering from MDD.Our study adds to a growing literature indicating that gamified interventions may impact depressive symptoms46, whereas this approach may not be effective for individuals whose depression may be mediated by deficits in other brain networks47. Preliminary analyses suggest age and gender may be potential moderators of target engagement. However, In light of the modest sample size and risk for type 1 and type 2 error, such associations require confirmation in larger studies.We note several caveats. Although we demonstrate significant changes in CCN functions using converging methodologies, without a control group we cannot state with confidence that these changes are attributable to the intervention until it is compared to an active, equally engaging control. Further, the modest sample size requires replication of the target engagement findings. Likewise, changes in mood could be a function of regularly engaging in an entertaining activity or receiving weekly visits with a care manager. Participants completed the AID and CPT tasks at baseline and week 4 of the study so practice effects may account for some of the improvement in performance following treatment. We also cannot assess the specificity of effect—i.e., whether the similar benefit would be observed in individuals with MDD but without executive dysfunction. It is possible that only those with dysfunction in the CCN will benefit from an intervention designed to target this deficitThis study suggests that a remotely deployed neuroscience-informed video game-like intervention improves both CCN functions and mood in middle-aged and older adults with MDD. This phase of a two-phase clinical trial focused on the ability of a video game-like intervention designed to improve multitasking to engage the CCN. The next steps require confirmation of engagement of the CCN target in a randomized trial that includes an expectancy-matched video game control played at the same frequency and duration as the experimental intervention. Subsequent investigation in a larger cohort will also be required to identify whether particular patient subgroups benefit differentially in terms of both CCN function and mood symptoms. Nevertheless, this study underscores the importance of the CCN as a target for interventions aimed at the treatment of MDD, addressing symptoms that are frequently resistant to traditional antidepressant treatments in mid-to-late adulthood.Supplemental Material


Laser micro-welding is increasingly being used to produce electrically conductive joints within a battery module of an automotive battery pack. To understand the joint strength of these laser welds at an early design stage, micro-joints are required to be modelled. Additionally, structural modelling of the battery module along with the electrical interconnects is important for understanding the crash safety of electric vehicles. Fusion zone based micro-modelling of laser welding is not a suitable approach for structural modelling due to the computational inefficiency and the difficulty of integrating with the module model. Instead, a macro-model which computationally efficient and easy to integrate with the structural model can be useful to replicate the behaviour of the laser weld. A macro-modelling approach was adopted in this paper to model the mechanical behaviour of laser micro-weld. The simulations were based on 5 mm diameter circular laser weld and developed from the experimental data for both the lap shear and T-peel tests. This modelling approach was extended to obtain the joint strengths for 3 mm diameter circular seams, 5 mm and 10 mm linear seams. The predicted load–displacement curves showed a close agreement with the test data. Electric vehicles (EVs), hybrid/plug-in hybrid electric vehicles (HEVs/PHEVs) are increasingly being used to replace traditional fossil fuel-based automotive vehicles in order to minimise the generation of greenhouse gases ,2,3. ThiThe choice of joining technique largely depends on the ability to satisfy several requirements including (i) joining dissimilar materials; (ii) joining highly conductive and reflective materials; (iii) overcoming the challenge of multi-layered stack-ups; (iv) obtaining high joint strength and low joint resistance; and (v) producing the joint with low heat input or high thermal fatigue resistance . ResearcThe interconnection joints are an integral part of the battery module together with the cells and ancillary components. Structural FE models are being developed to represent the battery cells , batteryThe aforesaid research gap is addressed in this paper by fulfilling the following objectives: (i) macro-modelling of laser micro-joints to evaluate the joint strength; (ii) experimental laser micro-joining to produce dissimilar joints; and (iii) verify and validate the model by performing lap shear and T-peel tests.In general, the Lithium-ion (Li-ion) cylindrical cell case is made of nickel-plated steel, such as Hilumin which is an electro nickel-plated, diffusion annealed steel strip for battery applications where low contact resistance and high corrosion resistance are needed. Nickel-plated copper strips are commonly used as tabs to connect the cylindrical cells to the busbar. Therefore, Hilumin and copper of 0.3 mm thickness were used in this experimental investigation and their corresponding chemical compositions are given in The stress–strain behaviour of the parent materials was determined using a 40 mm gauge length sample tested at a quasi-static speed of 2 mm/min . The geoPulsed laser welding was carried out using an IPG 150W Quasi-CW IR laser  having a maximum peak power of 1.5 kW. A wobble head was integrated within the optical chain to facilitate laser beam oscillation and the mode of operation was quasi-continuous wave (QCW) at an infrared (IR) wavelength of 1070 nm. The laser optics were mounted on an X-Y gantry system and the spot size at the focus was approximately 28 µm in diameter. A fixture was used to ensure intimate contact between the sheets by eliminating any part-to-part gap. The laser set-up with the fixture configuration is shown in After carrying out the laser micro-welding, samples were tested to obtain the lap shear and T-peel strengths. The lap shear and T-peel tests were performed using an Instron 3367 static test frame  with a 30 kN load capacity and cross-head speed of 2 mm/min and 20 mm/min, respectively. A higher test speed was applied to perform the T-peel tests in order to minimise the unexpected dynamic effect for weld failure . The peaThe parent materials were modelled as sheet metal parts using shell elements. Solid brick elements provide more accurate results in comparison with shell elements as they are more suitable to calculate stress in all the three directions. Therefore, a solid hexahedral mesh was used to model the weld zone. The LS-DYNA platform  was usedIt can be observed that an elastic spring was added to the static grip of both the lap shear and T-peel specimen to replicate the load cell behaviour during the experimental tests. Additionally, the model was composed of static grip, moving grip, lower part, upper part and circular weld. In line with experimental measurement, the static grip and lower deformable parts were modelled with Hilumin material properties whereas the upper deformable part and moving grip were assigned the copper material properties. Standard Belytschko-Tsay membrane formulation was used to model shell elements used in the four sheet metal parts . An initial mesh sensitivity analysis was performed to select the appropriate mesh size and it was observed that a rectangular mesh size of 0.5 mm was suitable for both the lap shear and T-peel modelling since a further reduction in element size did not have a significant impact on the results. As mentioned earlier, the weld was modelled as a solid hexahedral mesh, however, a single layer of solid elements was not sufficient to obtain a stable model as excessive deformation with early element deletion was obtained. To overcome this issue, a 2 × 2 layer of solid elements varying in size from 0.15 mm to 0.2 mm was sufficient to replicate the welding behaviour . A close-up of the joint mesh for the lap shear model is shown in The static and moving grips were modelled as rigid bodies where the static grip was constrained with all 6 degree of freedoms (DOFs) and the moving grip was displaced in the loading direction with a velocity profile. To simulate the base material and weld zone, five different material data cards were used which are Hilumin rigid body for static grip, Hilumin deformable body for the lower part, copper rigid body for moving grip, copper deformable body for upper part and fusion zone material card for weld seam see . These mThe laser micro-welding was performed using the process parameters described in Laser micro-welded joint strength and failure prediction are considered a high priority from a design perspective. Macro-modelling approach was adopted in this study without sacrificing the reliability of welding behaviour prediction. The base material properties were obtained from suppliers as well as by performing tensile tests. For example, the hardening curves of the copper and steel base material were obtained from the tensile tests. In contrast, fusion zone or weld zone hardening curves were derived from the base materials based on the hardness change. Therefore, the hardening curve for the weld zone was defined as The results obtained from the T-peel simulation are given in Similar to the T-peel test, the load–displacement curves obtained from the lap shear test and the corresponding simulation model are shown in The developed macro-model was validated using additional tests considering a 3 mm diameter circular laser micro-welded seam, as shown in The macro-model was used to predict the joint strength for linear stitches of 5 mm and 10 mm length as shown in Macro-modelling of laser micro-joints predicts similar load–displacement behaviour to that obtained in physical tests.Joint fusion zone characteristics are suitable for confirming weld quality and can be further used to obtain knowledge about hardness changes for identifying the key flow stress behaviour of the fusion zone.Lap shear and T-peel tests confirmed that macro-model can be used for predicting the maximum load and failure in a computationally efficient way.By using the macro-model, maximum joint strength can be predicted within ±7% or lower of the experimentally obtained maximum load. However, further investigations are required to quantify the localised fracture strain based on the weld shape/geometry.This paper investigated a macro-modelling approach to represent laser micro-welds for electric vehicle battery application where the macro-model can be used to integrate with a large-scale structural model. Laser micro-joints were produced using copper and Hilumin steel of 0.3 mm tabs in lap shear and T-peel configurations. This study has demonstrated the following:In conclusion, this paper has confirmed the suitability of macro-modelling for predicting joint strength at the early design stage. Further work is needed to integrate the macro-model in a battery module to replicate the accurate behaviour of the battery module.


Access to effective communication is critical to the conversations that occur at end-of-life and represents an unaddressed need within palliative care. These challenges may disproportionately affect persons with dementia (PWD). Hearing loss is one of the most common comorbidities among PWD and is independently associated with neuropsychiatric symptoms. However, relatively little is known about the potential impact of hearing loss on PWD at end-of-life. We examined last month of life (LML) data from 971 proxies of deceased PWD from the National Health and Aging Trends Study (2011-2020). Hearing difficulty was associated with increased anxiety/sadness in PWD, χ2(1)=4.596, p=.032, such that 65.6% of persons with hearing difficulty reported anxiety/sadness in the LML. Binary logistic regression found that hearing difficulty was significantly associated with increased anxiety/sadness . Interventions that optimize communication for PWD may be a meaningful approach to improving the end-of-life experience.


Self-injection locking to an external fiber cavity is an efficient technique enabling drastic linewidth narrowing of semiconductor lasers. Recently, we constructed a simple dual-frequency laser source that employs self-injection locking of a DFB laser in the external ring fiber cavity and Brillouin lasing in the same cavity. The laser performance characteristics are on the level of the laser modules commonly used with BOTDA. The use of a laser source operating two frequencies strongly locked through the Brillouin resonance simplifies the BOTDA system, avoiding the use of a broadband electrooptical modulator (EOM) and high-frequency electronics. Here, in a direct comparison with the commercial BOTDA, we explore the capacity of our low-cost solution for BOTDA sensing, demonstrating distributed measurements of the Brillouin frequency shift in a 10 km sensing fiber with a 1.5 m spatial resolution. Distributed optical fiber sensors show superior advantages over their electronic counterparts due to their high sensitivity to external disturbances and low loss transmission, which are important for remote sensing . Unlike An alternative solution for a dual-frequency laser potentially suitable for BOTDA applications was reported recently . The priIn this paper, we explore the potential of this low-cost laser solution for operation with the Brillouin optical time domain analyzer (BOTDA) . We presOur experimental BOTDA configuration is shown in The beating between two laser outputs is characterized by a stable radio-frequency (RF) spectrum with 290 Hz -linewidth and fixed peak frequency at The BOTDA built in the laboratory is a simple modification of the traditional pump-probe setup . The las used in  for the To evaluate the performance of the laser operation with the built BOTDA, we built a fiber testing line similar to that commonly used with BOTDAs for their calibration. The 10 km length testing line shown in The testing experiments were performed with our BOTDA setup and then repeated with the commercial BOTDA system (OZ-optics) set to operate with a pump pulse of 15 ns. Note that the operating wavelength of the commercial BOTDA is 1550 nm, so the BFS data measured with this device are presented here with a scaling factor of 1550/1535. The experimental results are shown in In order to accurately estimate the BFS distribution along the sensing fiber, the Brillouin gain spectrum (BGS) was measured at each fiber location. At each fiber point, the radio frequency  profile . Figure In conclusion, we used a simple dual-frequency laser configuration operated with BOTDA. The use of the laser operating two fixed frequencies significantly simplified the BOTDA system and allows excluding the broadband EOM (and high-power high-frequency microwave generator supplying the EOM) from the traditional BOTDA configuration based on a single narrowband laser source. These relatively high-cost devices constitute a significant part of the BOTDA system value. Additionally, the laser operation mechanism enabling self-stabilized generation of the Brillouin wave does not employ rather an expensive wavelength locking circuit, being a part of the Brillouin lasers offered for BOTDA sensing earlier . Instead


Although first described over a hundred years ago, tissue optical clearing is undergoing renewed interest due to numerous advances in optical clearing methods, microscopy systems, and three-dimensional (3-D) image analysis programs. These advances are advantageous for intact mouse tissues or pieces of human tissues because samples sized several millimeters can be studied. Optical clearing methods are particularly useful for studies of the neuroanatomy of the central and peripheral nervous systems and tissue vasculature or lymphatic system. Using examples from solvent- and aqueous-based optical clearing methods, the mouse and human pancreatic structures and networks will be reviewed in 3-D for neuro-insular complexes, parasympathetic ganglia, and adipocyte infiltration as well as lymphatics in diabetes. Optical clearing with multiplex immunofluorescence microscopy provides new opportunities to examine the role of the nervous and circulatory systems in pancreatic and islet functions by defining their neurovascular anatomy in health and diabetes. Heterogeneity of the human pancreas is well accepted in terms of islet endocrine cell proportions and mass in healthy people and for lobularity in islet beta-cell losses and frequency of infiltrated islets in patients in type 1 diabetes (T1D) . Patientin situ hybridization-compatible tissue hydrogel (CLARITY), and passive CLARITY technique (PACT)  , 63–65.The original CLARITY manuscript by Chung et al.  describeDespite their differences in chemical and/or optical properties, the organic solvent, aqueous reagent, and electrophoresis-assisted clearing methods all extend our view of neurovascular networks (>>100 µm) with 3-D microscopy compared with the images acquired from classic IHC and H&E histology (3-5 µm in thickness). To apply tissue clearing, the key question is whether a specific clearing technique changes the sample chemical and/or cellular environment that causes artifacts in signal detection. For example, in CLARITY, the use of sodium dodecyl sulfate (SDS) treatment and electrophoresis to remove cellular membranes is likely to disturb membrane receptor proteins. Thus, studies of the nerve-receptor association in space will be better accepted if a passive aqueous-based clearing method  is employed compared with CLARITY. Likewise, leukocytes and their vascular receptor association in space will be better examined in an aqueous environment, because disturbing the membranes for 3-D imaging may create false negative results in signal detection. However, we need to stress that the false negative result may also come from scattering in deep-tissue imaging. Thus, adding a positive control in the specimen  can help investigators monitor the resolving power  across the optical depth in deep-tissue pancreatic and islet imaging.Volumetric microscopy has also paralleled optical clearing methods with advancements in confocal, multiphoton and lightsheet microscopes. Advantages of the lightsheet microscopes are faster scanning speeds, reduced photobleaching, and good resolution at high tissue penetration depths. When access to lightsheet microscopes is not feasible, confocal microscopy provides an excellent alternative with single-cell resolution. While any type of fluorescent microscope can be used to image optically-cleared tissue, the microscope imaging chamber must be able to accommodate the size of the sample and the stage configuration and imaging depth are dependent on the working distance of the objective. Most images can be obtained with regular air objectives between ×2 and ×20 magnifications. Specialized objectives for optically cleared samples over larger distances are available from multiple vendors such as Olympus and Zeiss. Users of optical clearing methods and advanced microscopy need also consider data storage requirements for both image acquisition and analysis. Additional storage space for the imaging microscope is required as well as additional memory and processing speed for image analysis workstations. The opensource software Fiji/ImageJ can be used for 2-D stitching and basic 3-D adjustments . Zeiss ZChallenges related to optical clearing are relatively few. Acquisition of high-quality samples is important as for any down-stream application based on fixed samples. Fixation with 4% paraformaldehyde or 10% formalin is commonly employed in many laboratories. Cardiac perfusion is recommended for rodent studies in most part to remove red blood cells and their inherent high autofluorescence. However, immersion fixation is a reasonable alternative for rodents and the only method available for human biosamples. As for traditional immunolocalization, the duration of fixation is ideally kept to a minimum to avoid over-fixation of tissue antigens. Many primary antibodies utilized for formalin-fixed paraffin embedded samples work well for optical clearing and those tested in our laboratory are provided as a reference Table 2.Equipment utilized in optical clearing is generally found in any modern molecular pathology laboratory and include access to fume hoods, refrigeration or ovens, rocker plates, and other ancillary small equipment for immunostaining and clearing steps. Microscope and image analysis software are two aspects to be considered before conducting clearing studies as this will influence sample size and numbers of channels for multiplex staining and analysis. As costs for multiphoton and lightsheet microscopes decrease, access to these microscopes will increase whether through institutional shared resources, subcontract, or collaboration. Image analysis expertise is also limited and laboratory staff become proficient in the software available to them. Expense of commercial 3-D software analysis programs is high. Finally, the greatest hurdle may be the large image file sizes achieved by these methods. Here too, limiting the number of antigens needs to be balanced with the rarity of the sample since reiterative staining is difficult.This introduction on optical clearing and imaging provides a basic starting point for studies on human and mouse pancreas in health and diabetes. We will now show examples of application of different clearing methods to demonstrate the versatility of optical clearing in human and mouse pancreas for determination of normal states and changes found with diabetes.Human pancreata not suitable for clinical purposes were collected from nondiabetic, brain-dead organ donors after written informed consent from legal representative or next of kin and were processed by the Network for Pancreatic Organ donors with Diabetes (nPOD) program at the University of Florida (UF) Diabetes Institute using methods previously reported . The nPO((Passive CLARITY (PACT) provides for good tissue transparency and multiplex immunolabeling is quite feasible with image analysis such as using the open software Neurite tracer program in ImageJ Figure 1. Schwann, 71. In , 73. Unl . Opticalclearing Figure 5clearing .Unlike the fatty liver, in which lipid droplets accumulate in the cytoplasm in the hepatocytes, pancreatic fatty infiltration involves the fat cells (adipocytes) ectopically developing and accumulating in and around the pancreatic lobules alongside the exocrine and endocrine tissues. The fat content in the pancreas increases with age  and is din vivo information for cross-sectional or longitudinal studies, they cannot resolve the cellular structures of fats and the pancreatic exocrine and endocrine tissues. At the cellular level, the classic microtome-based histology with H&E staining can identify the adipocytes and their association with blood vessels, acini, ducts, and islets with µm-level resolution. However, due to the hydrophobicity of fats and their weak mechanical connection with the pancreatic lobules, both microtome slicing and dewaxing (xylene wash) of the paraffin-embedded pancreas may create artifacts on the locations of adipocytes, affecting the analysis of the peri- and/or intra-lobular adipocyte association.Clinically, magnetic resonance imaging (MRI) and computed tomography (CT) are the preferred imaging modalities to detect and quantify the pancreatic fats , 98–102.Modern 3-D histology with aqueous-based optical clearing alleviates the abovementioned technical concern by maintaining the native hydrophilicity of the tissue and avoiding the microtome slicing in sample preparation . This isThe lymphatic drainage of pancreas is achieved by an intricate network of lymphatic vessels and nodes, in which the immune cells reside. The open-ended lymphatic network collects the interstitial fluids for water and lipid absorption and recycling  and for immune surveillance . When pa+ T lymphocytes in the lymph node (positive control) and around the islets. The latter provides a clear target for examination of the islet under immune attack, featuring vasodilation and the packing of T lymphocytes in the lymphatic vessels  that can be acquired from optically cleared pancreas samples to investigate experimental insulitis.As can be seen in in vitro experiments examining acinar-ductal metaplasia. Advances in understanding failure of islet beta-cells in diabetes requires a wholistic examination of islets in their native environment as afforded by optical clearing and new findings are anticipated related to the role of the nervous, immune, and vascular systems in beta-cell biology from such studies.Both standard and modified optical clearing methods are well suited for studies of 3-D structure-function relationships for human and mouse pancreas and use readily available chemicals and imaging equipment. These methods are particularly advantageous for studies of diabetes due to known islet heterogeneity requiring examination of numerous islets and pancreas regions. Optical clearing methods can also be used in investigations of pancreatic cancer using patient or rodent samples or MC-T and S-CT designed the studies, performed experiments, prepared figures, and edited and revised the manuscript. All authors contributed to the article and approved the submitted version.Funding provided by NIH 1R01DK122160, UC4 DK104155, U54 DK127823 and OT2 OD023861, Helmsley Charitable Trust 2015PG-T1D052 and JDRF 47-2014-1 and 2-SRA-2019-697-S-B to MC-T and Taiwan National Health Research Institutes (NHRI-EX109-10922EI) and Ministry of Science and Technology (MOST 108-2314-B-007-006-MY2) to S-CT.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Kidney Injury Test (KIT) Stone-Score provides an objective measure of stone burden. Unlike urinary supersaturation the KIT Stone-Scores assess underlying stone disease rather than urinary solute composition. We report a case of a 43-year-old woman with no history of nephrolithiasis who underwent an elective, voluntary KIT assay and was diagnosed with a large staghorn renal stone after an unanticipated markedly elevated score. This clinical scenario highlights the potential future use of the non-invasive urinary KIT assay as a reliable non‐invasive tool to detect and monitor urinary stone disease. •KIT assay consists of a panel of six urinary biomarkers measured on a random urine sample.•Healthy asymptomatic patient was diagnosed with an unanticipated staghorn kidney stone after an elevated elective KIT assay.•For healthy patients, the threshold for the KIT Stone-Score was determined to be less than or equal to 30.•Urinary KIT normalized 6-months post-operatively.•KIT assay predicts the future risk of recurrence and risk stratify kidney stone patients. Radiation exposure may become significant when taking into consideration the imaging required in the diagnosis and follow-up of kidney stones.The Kidney Injury Test (KIT) assay consists of a panel of six urinary biomarkers and has been validated for early detection of kidney injury and nephrolithiasis.2A 43-year-old female with no previous personal or familial history of kidney stones underwent an elective KIT urinary test as part of a non-stone former control group for a separate unrelated study. Surprisingly, her urine KIT assay revealed six abnormally elevated proteins with a combined KIT Stone-Score of 75 . She hadA follow-up CT scan identified a residual stone fragment (10 mm) in the right lower pole with resolution of the previous hydronephrosis B. A seco3Repeat patient exposure to radiation from scans and their associated costs are particularly problematic in patients with recurrent stone disease. Patients may benefit from a non-invasive detection test like the KIT urine assay as an alternative means of diagnostic workup to ascertain presence of urolithiasis and assess for recurrence.The novel KIT assay used random forest modeling to identify the relationship between biomarkers for detection of CKD with high sensitivity.The KIT Score could risk-stratify stone recurrence and provide an objective measure of kidney stone burden with a lower limit of detection of 2 mm. In this case report, a healthy asymptomatic woman with no prior history of nephrolithiasis was found to have a markedly elevated KIT Stone-Score with a remarkable cfDNA of 465.37 ng/mL. Subsequent workup identified a complete staghorn stone, that with time could have led to loss of kidney function if left untreated. After a PCNL and URS-LL that rendered her stone free, her urinary KIT normalized 6-months post-operatively .We compared the peri- and post-procedural abnormal KIT levels from our case report to urine samples from healthy non-stone formers and a patient with history of recurrent kidney stones . The patCurrently, there are various biomarkers that have shown potential in detecting urinary calculi. In a prospective study, Castiglione et al. showed that high serum dephosphorylated and uncarboxylated Matrix-Gla-protein (dpucMGP) was associated with less kidney stone formation after adjustment for age, race, and sex.4The urinary KIT test detected the presence of a large staghorn stone in an otherwise completely asymptomatic patient. The KIT Stone-Score levels corrected appropriately after surgical intervention. Further larger studies are needed to highlight the utility of the KIT assay as a reliable non‐invasive tool in the detection and monitoring of kidney stone disease.Consent: Patient informed consent was obtained using the UCSF-IRB approval number (CHR #14–14533).None.M.M.S. is an inventor of the KIT Assay, IP for which is exclusively owned by the Regents, University of California San Francisco and licensed to NephroSant . R.S is a consultant for NephroSant.


Slow earthquakes including tremor and slow-slip events are recent additions to the conventional earthquake family and have a close link to megathrust earthquakes. Slow earthquakes along the Cascadia subduction zone display a diverse behavior at different spatiotemporal scales and an intriguing increase of events frequency with depth. However, what causes such variability, especially the depth-dependent behavior is not well understood. Here we build on a heterogeneous asperities-in-matrix fault model that incorporates differential pore pressure in a rate-and-state friction framework to investigate the underlying processes of the observed episodic tremor and slow-slip (ETS) variability. We find that the variations of effective normal stress (pore pressure) is one important factor in controlling ETS behavior. Our model reproduces the full complexity of ETS patterns and the depth-frequency scaling that agree quantitatively well with observations, suggesting that fault zone heterogeneities can be one viable mechanism to explain a broad spectrum of transient fault behaviors. Here, the authors combine the geological and seismological constraints of the Cascadia Subduction Zone and develop a 3D rate and state friction model. By considering depth-dependent variations of differential pore pressure following a simple linear profile, the model reproduces the full spectrum of the observed ETS complexity. Despite slow or weak signature, SSE and NVT are shown to play an important role in earthquake dynamics and hazard estimation due to its potential link to megathrust earthquakes3. SSE and NVT activities are sensitive to stress perturbations due to their low stress drop nature7. Stress perturbations from earthquakes or other sources can impact SSE occurrence9. The broad-scale nucleation processes of megathrust earthquakes10 has been suggested to affect nearby SSE and tremor patterns, making them potential candidates for precursory monitoring of future large earthquakes3.Recent advances in seismology and geodesy have led to many new findings of unconventional slow earthquakes such as slow-slip event (SSE) and non-volcanic tremor (NVT). SSE, mainly discovered through geodetic measurements, has much slower slip rate (centimeters to meters per year) and slow propagation speed (kilometers per day) compared to regular earthquakes, and does not emit detectable seismic signals. NVT is known for its seismic yet weak, non-impulsive nature. SSE and tremor are mostly found at young subduction zones around the worldhttps://hazards.uw.edu/geology/m9). Tremor and SSE in CSZ are often spatially and temporally correlated and referred to as episodic tremor and slow-slip (ETS)14. ETS events in CSZ mostly occur in the seismic-aseismic transition zone (thereafter referred to as ETS zone) between the shallow seismogenic and deep creeping regions over a depth range of ~25–55 km. ETS in CSZ displays clear along-strike variation with northern, middle, and southern segments15  “Individual tremor” . Individual tremor is very common in the southern segment, sometimes seen in the northern segment but rarely observed in the middle segment. Here the depth boundaries of ~38 and ~46 km are used as the first-order approximation to characterize the ETS types at depth.Cascadia subduction zone (CSZ) is one of the closely monitored subduction zone faults due to its potential for magnitude 9 megathrust earthquake and catastrophic tsunami hazard that can affect populated urban centers along its thousand-kilometer-long margin  with depth along the entire subduction margin . Typically, only the larger ETS can propagate into an area at a shallow depth while the smaller arrested ETS events occur almost exclusively at the deeper portion of the ETS zone . Similarly, the deep ETS events can occur in the form of arrested or propagating, and occasionally cascade into major ETS events, just like the self-arresting earthquakes evolving into runaway earthquakes26. One standing question is whether the ETS is controlled by the same physical mechanism as regular earthquakes. Recent studies suggest that slow earthquakes in CSZ follow the similar scaling law as regular earthquakes and display pulse-like ruptures similar to seismic ruptures20.Most studies so far have focused on the major ETS and regard other types as background27. Others simulate various SSE behaviors without accompanying tremor30. The third group consists of models being able to reproduce ETS with both SSE and tremor. Early efforts attempt to reproduce ETS without prescribing any physical tremor asperities33. Later the asperity-in-matrix (AIM) model, supported by the geological observations of exhumed subduction fault zone materials comprised of competent phacoides embedded in incompetent background matrix35, was proposed to consider actual tremor “asperities”  from which tremors naturally originate. The AIM models have shown great potential for reproducing rich phenomena of slow earthquakes in Japan37. More recently, one-dimensional (1-D) AIM model was developed to successfully reproduce some notable ETS features in CSZ such as the large-scale forward migration and rapid tremor reversals (RTRs)38. Nevertheless, so far no model is able to explain the full spectrum of observed ETS complexity, especially the depth-dependent ETS pattern and the relation and evolution of small to large ETS.Despite the improved observations, our understanding of ETS behaviors and underlying mechanics is still limited. In particular, what physical models can self-consistently explain the hierarchical ETS distribution and evolution? Over the past decade, significant modeling efforts have been made with attempts to capture some characteristics of ETS. Some aim to reproduce tremor character and certain scaling relation, but not actual spatiotemporal patterns and associated SSE40, and a conceptual model41 that suggests temperature-dependent healing and permeability reduction in silica-rich fault gouge via dissolution–precipitation creep could lead to the decrease of overall effective normal stress with depth, affecting the depth-dependent ETS phenomena. Here we combine the geological, seismological constraints in CSZ, and develop a 3-dimensional (3-D) rate-and-state friction AIM model to investigate the complex spatiotemporal ETS patterns. We show by considering depth-dependent variations of differential pore pressure following a simple linear profile, our model is able to reproduce the full spectrum of the observed ETS complexity including depth-dependent ETS distributions in Cascadia. These results provide important insights into the origination and evolution of ETS and suggest possible connection between slow and regular earthquakes.We hypothesize that the along-dip variations of the differential pore pressure  of the asperities and/or the background matrix can be one plausible candidate for the observed along-dip ETS variability in CSZ. This hypothesis is motivated by the strong correlation between ETS behaviors and stress condition as shown by previous studiesWe incorporate 3-D complexity into our previous 1-D along-strike AIM model by taking into account the depth-dependent frictional properties and stress conditions. The fundamentals of rate-and-state friction and technical model details can be found in the Methods section. Our model consists of a planar 2-D fault embedded in 3-D elastic medium. The ETS zone is represented by heterogeneous velocity-weakening (VW) tremor asperities embedded within velocity-strengthening (VS) matrix, as illustrated in Fig. 42. The linear model, as a natural extension of spatially averaged bi-modular model, has a linear decrease of effective normal stress with depth. We find that simulated major ETS events in the linear model have a slightly shorter interval of around 1.2 years. The linear model not only features a more natural stress profile, but also reproduces a much richer set of ETS events with various magnitudes and depth . Most simulated ETS events propagate along strike either bilaterally with a dominant branch or nearly unilaterally probably due to heterogeneous material properties and stress residuals from previous events. We also noticed some interesting variations of major ETS, e.g., the “colliding” ETS in which two ETS branches nucleated at similar time and propagates toward each other and eventually collide  frequency so more tremor activities can be recorded during each ETS event. The parameters and initial conditions are based on the result of the first 4 years simulation reported previously. The results are summarized in Figs. ion Fig.  of each mentclass2pt{minim model 12 km. Extr model 12 km. ExtrIn summary, for the first time, our depth-dependent AIM model with linear stress variation is able to reproduce the full hierarchy of ETS behaviors, ranging from small individual tremor, to arrested and runaway deep ETS, to the characteristic major ETS, as well as the exponential depth-frequency scaling, all in good quantitative agreement with the spatiotemporal ETS patterns observed in Cascadia. Our model suggests that fault zone heterogeneities in terms of frictional properties and effective normal stress as a result of differential pore pressure is a viable mechanism underlying the broad spectrum of the ETS variabilities in CSZ.In this study, we develop a 3-D rate-and-state AIM model with simple linear depth-dependent stress profile and employ it in multi-cycle simulations to investigate the hierarchical ETS in CSZ. Our model is constrained by geological, geodetic, and seismological observations and inspired by previous conceptual and numerical models. To our best knowledge, this physically sound model is the first in the community that reproduces the full spectrum of observed tremor and slow-slip complexity in Cascadia with the potential applicability to slow earthquake processes worldwide.44. The low effective stress is a necessary condition for slow rupture processes such as SSE and relatively short recurrence interval of ETS, making them susceptible to the variation in stress conditions. Previous studies show tremor and SSE can be modulated by small stress perturbation such as tidal stress45 or tectonic stressing3 and reference therein. Our model quantitatively demonstrates that the change of ETS frequency and size with depth is a result of a systematic decrease of effective normal stress. Such change of effective normal stress with depth could result from the temperature- (thus depth-) dependence of healing and gouge permeability reduction due to progressive silica deposition in overlying forearc crust, leading to fluid overpressure buildup and reduced effective fault normal stress41. Our model highlights the need to explicitly consider the resultant stress conditions as controlled by forearc structure in modeling ETS and megathrust faulting behaviors.Our model results suggest that the overall effective normal stress of the ETS zone can be as low as several to a fraction of MPa, consistent with near-lithostatic pore-fluid pressure in the ETS zone as a result of fluids sealing due to low gouge permeability4, while ETS nucleation in the uniform model does not have clear preference despite the same loading conditions. We attribute the realistic ETS nucleation in both bi-modular and linear model to the joint contribution of lower effective normal stress  and continuous loading at the deeper part of ETS zone. As the depth dependence of effective normal stress results in the relative shear strength decrease with depth, tremor asperities at depth tend to be weaker and fail more often than asperities up-dip. It is possible that the shear strength decrease with depth could also associate with friction decrease as a function of depth4. However, lack of constraints on frictional parameters makes it difficult further testing this interpretation. Instead, our AIM model demonstrates that the depth variation of effective normal stress can be one major controlling factor affecting fault zone strength and ETS variations, supported by available geological and seismic observations41.In our bi-modular and linear model, we observed that ETS consistently nucleates from the deeper part of ETS zone in agreement with real-world observations48 might indicate a high degree of stress heterogeneity contributing to cascading interaction of tremor asperities and resultant tremor swarm. In this model, transient stress heterogeneities as a result of heterogeneous stress drop of asperities from past ETS history can sometimes couple with local variation of asperity strength to cause tremor-less slip23, in which reduced slip rate is sustained without incurring seismic asperity rupture.In addition to the depth dependence of fault zone properties, other factors in our model such as the asperity distribution and their interaction can also contribute to the ETS variability and evolution. For example, RTRs seem to favor the low stress region of ETS zone . But more recently slow earthquakes are found to actually follow the similar scaling relation as conventional earthquakes50. The similarities between slow and regular earthquakes and their similar scaling laws suggest that they might have a close connection and share the similar dynamic properties and mechanism. Luo and Ampuero25 use a simplified two-degree-of-freedom model to demonstrate that slow earthquakes and regular earthquakes are transformable depending on the evolution of stress condition . The interplay of VW and VS materials jointly affects ETS behaviors with slow (SSE) to fast (NVT) signature.Our heterogeneous AIM fault model consists of alternating VS–VW materials (VS fault matrix with embedded VW tremor asperities) and differential effective normal stress56 (see last subsection for details). As shown in Fig. 38). All the asperities have the same constitutive parameters (25) ranging from 0.2 to 1.0 , thereafter referred as “uniform model.” The second is a model with two connected ETS zones, the shallower ETS region (above 40 km depth) has the same setting as the uniform model, whereas the deeper ETS region (below 40 km depth) has 1/10 effective normal stress of the shallower counterpart  so that the deeper ETS region is expected to have weaker but more frequent ETS events, thereafter referred as “bi-modular model.” The third model considers effective normal stress of the VS background and VW tremor asperities as a linear function of depth: from 30 to 50 km of 1–0.1 MPa for VS background and 20–2 MPa for the VW tremor asperities. We refer this model as “linear model.” Details of model settings can be referred to Fig. 437, we consider it a good first-order approximation. Various 3 and 105Rate-and-state numerical simulations of the three ETS models are performed with QDYN for 4 years each so that multiple occurrences of major ETS can be captured. We then analyze the ETS patterns produced by each model discarding the first year of output (“warm-up” period) to mitigate the effects of the initial conditions. We detect tremor using a simple velocity threshold 43. Here we conveniently use total moment 67G is shear modulus, A is the rupture area, and The magnitudes for ETS and tremor (LFE) in the real world are important yet challenging to determine6869. For ETS events, we estimated Mw ~ 4.5–6.0.We then estimate the moment magnitude  under the quasi-dynamic approximation (quasi-static elasticity combined with radiation damping) on faults governed by rate-and-state friction and embedded in elastic media. QDYN includes various forms of rate-and-state friction and state evolution laws, and handles non-planar fault geometry in 3-D and 2-D media, as well as spring-block simulations. Loading is controlled by remote displacement, steady creep or oscillatory load. In 3-D it handles free surface effects in a half-space, including normal stress coupling. The medium surrounding the fault is linear, isotropic, and elastic, and may be uniform or (in 2-D) contain a damaged layer. QDYN implements adaptive time stepping, shared, and distribute memory parallelization (OpenMP/MPI), and can deal with multi-scale earthquake cycle simulations with fine details in both time and space. It is equipped with user-friendly MATLAB and Python interfaces and graphical output utilities. QDYN is published56 and available at https://github.com/ydluo/qdyn. More details and instruction can be found there.We utilize software QDYNSupplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4