A Soft-Fiber Bioelectronic Device with Axon-Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities.

Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long-standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high-quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium-sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network-in-liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300 kPa), low specific impedance (579 kΩ µm2), and high electrical conductivity (32 700 S m-1) - ≈1-3 times higher than hydrogels. Stable single-unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

Genome assembly of redclaw crayfish (Cherax quadricarinatus) provides insights into its immune adaptation and hypoxia tolerance.

BACKGROUND: The introduction of non-native species is a primary driver of biodiversity loss in freshwater ecosystems. The redclaw crayfish (Cherax quadricarinatus) is a freshwater species that exhibits tolerance to hypoxic stresses, fluctuating temperatures, high ammonia concentration. These hardy physiological characteristics make C. quadricarinatus a popular aquaculture species and a potential invasive species that can negatively impact tropical and subtropical ecosystems. Investigating the genomic basis of environmental tolerances and immune adaptation in C. quadricarinatus will facilitate the development of management strategies of this potential invasive species. RESULTS: We constructed a chromosome-level genome of C. quadricarinatus by integrating Nanopore and PacBio techniques. Comparative genomic analysis suggested that transposable elements and tandem repeats drove genome size evolution in decapod crustaceans. The expansion of nine immune-related gene families contributed to the disease resistance of C. quadricarinatus. Three hypoxia-related genes (KDM3A, KDM5A, HMOX2) were identified as being subjected to positive selection in C. quadricarinatus. Additionally, in vivo analysis revealed that upregulating KDM5A was crucial for hypoxic response in C. quadricarinatus. Knockdown of KDM5A impaired hypoxia tolerance in this species. CONCLUSIONS: Our results provide the genomic basis for hypoxic tolerance and immune adaptation in C. quadricarinatus, facilitating the management of this potential invasive species. Additionally, in vivo analysis in C. quadricarinatus suggests that the role of KDM5A in the hypoxic response of animals is complex.

Transformer-Based Visual Segmentation: A Survey.

Visual segmentation seeks to partition images, video frames, or point clouds into multiple segments or groups. This technique has numerous real-world applications, such as autonomous driving, image editing, robot sensing, and medical analysis. Over the past decade, deep learning-based methods have made remarkable strides in this area. Recently, transformers, a type of neural network based on self-attention originally designed for natural language processing, have considerably surpassed previous convolutional or recurrent approaches in various vision processing tasks. Specifically, vision transformers offer robust, unified, and even simpler solutions for various segmentation tasks. This survey provides a thorough overview of transformer-based visual segmentation, summarizing recent advancements. We first review the background, encompassing problem definitions, datasets, and prior convolutional methods. Next, we summarize a meta-architecture that unifies all recent transformer-based approaches. Based on this meta-architecture, we examine various method designs, including modifications to the meta-architecture and associated applications. We also present several specific subfields, including 3D point cloud segmentation, foundation model tuning, domain-aware segmentation, efficient segmentation, and medical segmentation. Additionally, we compile and re-evaluate the reviewed methods on several well-established datasets. Finally, we identify open challenges in this field and propose directions for future research. The project page can be found at https://github.com/lxtGH/Awesome-Segmentation-With-Transformer.

Neural Prompt Search.

The size of vision models has grown exponentially over the last few years, especially after the emergence of Vision Transformer. This has motivated the development of parameter-efficient tuning methods, such as learning adapter layers or visual prompt tokens, which allow a tiny portion of model parameters to be trained whereas the vast majority obtained from pre-training are frozen. However, designing a proper tuning method is non-trivial: one might need to try out a lengthy list of design choices, not to mention that each downstream dataset often requires custom designs. In this paper, we view the existing parameter-efficient tuning methods as "prompt modules" and propose Neural prOmpt seArcH (NOAH), a novel approach that learns, for large vision models, the optimal design of prompt modules through a neural architecture search algorithm, specifically for each downstream dataset. By conducting extensive experiments on over 20 vision datasets, we demonstrate that NOAH (i) is superior to individual prompt modules, (ii) has good few-shot learning ability, and (iii) is domain-generalizable. The code and models are available at https://github.com/ZhangYuanhan-AI/NOAH.

Dual Modification Strategy for Enhanced Cycling and Rate Performance of Ni-Rich Cathode Materials in Lithium-Ion Batteries.

A great challenge in the commercialization process of layered Ni-rich cathode material LiNixCoyMn1-x-yO2 (NCM, x ≥ 80%) for lithium-ion batteries is the surface instability, which is exacerbated by the increase in nickel content. The high surface alkalinity and unavoidable cathode/electrolyte interface side reactions result in significant decrease for the capacity of NCM material. Surface coating and doping are common and effective ways to improve the electrochemical performance of Ni-rich cathode material. In this study, an in situ reaction is induced on the surface of secondary particles of NCM material to construct a stable lithium sulfate coating, while achieving sulfur doping in the near surface region. The synergistic modification of lithium sulfate coating and lattice sulfur doping significantly reduced the content of harmful residual lithium compounds (RLCs) on the surface of NCM material, suppressed the side reactions between the cathode material surface and electrolyte and the degradation of surface structure of the NCM material, effectively improved the rate capability and cycling stability of the NCM material.

Class-Incremental Learning: A Survey.

Deep models, e.g., CNNs and Vision Transformers, have achieved impressive achievements in many vision tasks in the closed world. However, novel classes emerge from time to time in our ever-changing world, requiring a learning system to acquire new knowledge continually. Class-Incremental Learning (CIL) enables the learner to incorporate the knowledge of new classes incrementally and build a universal classifier among all seen classes. Correspondingly, when directly training the model with new class instances, a fatal problem occurs - the model tends to catastrophically forget the characteristics of former ones, and its performance drastically degrades. There have been numerous efforts to tackle catastrophic forgetting in the machine learning community. In this paper, we survey comprehensively recent advances in class-incremental learning and summarize these methods from several aspects. We also provide a rigorous and unified evaluation of 17 methods in benchmark image classification tasks to find out the characteristics of different algorithms empirically. Furthermore, we notice that the current comparison protocol ignores the influence of memory budget in model storage, which may result in unfair comparison and biased results. Hence, we advocate fair comparison by aligning the memory budget in evaluation, as well as several memory-agnostic performance measures. The source code is available at https://github.com/zhoudw-zdw/CIL_Survey/.

Treatment of myelofibrosis with refractory anemia with luspatercept: a multicenter Chinese study.

Myelofibrosis is a rare and often fatal hematological neoplasm, and the treatment of myelofibrosis-associated anemia remains suboptimal, with no improved therapies. Luspatercept was shown to display some efficacy in a phase 2 clinical trial for Myelofibrosis with anemia, yet relevant research are limited. Threrfore, data from patients diagnosed with refractory anemic primary or post-essential thrombocythemia/polycythemia vera myelofibrosis, who were treated with luspatercept for at least 9 weeks, were retrospectively collected. Eighteen patients with myelofibrosis treated with luspatercept were enrolled. Median age was 68 years (range, 44-80 years), and 27.8% were males. Ten (55.6%) were transfusion-dependent. Ten (55.6%) were Dynamic International Prognostic Scoring System intermediate-1, and eight (44.4%) were intermediate-2. The median follow-up was 7 (4-16) months. Erythroid response occurred in eight patients (44.4%) at week 12, four patients (30.8%) at week 24, and nine (50%) at the end of follow-up. Patients who were transfusion-dependent and not transfusion-dependent had similar HI-E responses, at different time points (P > 0.05). Patients had a significantly higher hemoglobin level at 12 weeks, 24 weeks, and at the end of follow-up, than at baseline (P = 0.001, P = 0.021, and P = 0.005, respectively). Treatment-related adverse events occurred in five (16.7%) patients, with no serious adverse events. Two (11.1%) patients relapsed at weeks 15 and 31. One patient progressed to acute myeloid leukemia. No patients had died by the end of follow-up. Luspatercept induced a good response in patients with anemic myelofibrosis, with a low relapse rate and good tolerance.

Manganese(II) promotes prebiotically plausible non-enzymatic RNA ligation reactions.

Using different prebiotically plausible activating reagents, the RNA ligation yield was significantly increased in the presence of Mn(II). The mechanism of the activation reaction has been investigated using 5'-AMP as an analogue.

Prevalence and associated factors of depression in postmenopausal women: a systematic review and meta-analysis.

BACKGROUND: Depression is a prevalent mental health problem in postmenopausal women. Given its significant impact on the quality of life and overall well-being of postmenopausal women, there is need for a comprehensive review and meta-analysis of the existing research globally. This systematic review and meta-analysis evaluated the global prevalence of depression and potential associated factors in postmenopausal women. METHODS: The Cochrane Library, PubMed, EMBASE, Web of Science, MEDLINE, and PsycINFO databases were systematically searched from inception to March 22, 2023. The meta-analysis used the random-effects model to calculate the prevalence of depression rates and associated factors. In addition, subgroup analysis and sensitivity analysis were performed. Publication bias was assessed using funnel plots, Egger's test, and nonparametric trim-and-fill tests. RESULTS: The meta-analysis included 50 studies that involved 385,092 postmenopausal women. The prevalence of depression in postmenopausal women was 28.00% (95% CI, 25.80-30.10). Among the factors relevant to depression among postmenopausal women, marital status (OR: 2.03, 95%CI: 1.33-3.11), history of mental illness (OR: 2.31, 95%CI: 1.50-3.57), chronic disease (OR: 3.13, 95%CI: 2.20-4.44), menstrual cycle (OR: 1.42, 95%CI: 1.17-1.72), abortion numbers (OR: 1.59, 95%CI: 1.40-1.80), menopausal symptoms (OR: 2.10, 95%CI: 1.52-2.90), and hormone replacement therapy (OR: 1.76, 95%CI: 1.31-2.35) were risk factors, while physical activity (OR: 0.56, 95%CI: 0.53-0.59), number of breastfed infants (OR: 0.43, 95%CI: 0.19-0.97), menopause age (OR: 0.44, 95%CI: 0.37-0.51) were preventive factors. CONCLUSIONS: This study demonstrated that the prevalence of postmenopausal depression is high, and some risk factors and protective factors associated with it have been identified. It is necessary to improve screening and management and optimize prevention and intervention strategies to reduce the harmful effects of postmenopausal depression.

A Biodegradable Fiber Calcium Ion Sensor by Covalently Bonding Ionophores on Bioinert Nanoparticles.

Implantable sensors, especially ion sensors, facilitate the progress of scientific research and personalized healthcare. However, the permanent retention of implants induces health risks after sensors fulfill their mission of chronic sensing. Biodegradation is highly anticipated; while; biodegradable chemical sensors are rare due to concerns about the leakage of harmful active molecules after degradation, such as ionophores. Here, a novel biodegradable fiber calcium ion sensor is introduced, wherein ionophores are covalently bonded with bioinert nanoparticles to replace the classical ion-selective membrane. The fiber sensor demonstrates comparable sensing performance to classical ion sensors and good flexibility. It can monitor the fluctuations of Ca2+ in a 4-day lifespan in vivo and biodegrade in 4 weeks. Benefiting from the stable bonding between ionophores and nanoparticles, the biodegradable sensor exhibits a good biocompatibility after degradation. Moreover, this approach of bonding active molecules on bioinert nanoparticles can serve as an effective methodology for minimizing health concerns about biodegradable chemical sensors.

A harmonized global gridded transpiration product based on collocation analysis.

Transpiration (T) is pivotal in the global water cycle, responding to soil moisture, atmospheric stress, climate changes, and human impacts. Therefore, establishing a reliable global transpiration dataset is essential. Collocation analysis methods have been proven effective for assessing the errors in these products, which can subsequently be used for multisource fusion. However, previous results did not consider error cross-correlation, rendering the results less reliable. In this study, we employ collocation analysis, taking error cross-correlation into account, to effectively analyze the errors in multiple transpiration products and merge them to obtain a more reliable dataset. The results demonstrate its superior reliability. The outcome is a long-term daily global transpiration dataset at 0.1°from 2000 to 2020. Using the transpiration after partitioning at FLUXNET sites as a reference, we compare the performance of the merged product with inputs. The merged dataset performs well across various vegetation types and is validated against in-situ observations. Incorporating non-zero ECC considerations represents a significant theoretical and proven enhancement over previous methodologies that neglected such conditions, highlighting its reliability in enhancing our understanding of transpiration dynamics in a changing world.

High expression levels of centromere protein O participates in cell proliferation of human ovarian cancer.

Ovarian cancer is a common malignant tumor in women, with a high mortality rate ranking first among gynecological tumors. Currently, there is insufficient understanding of the causes, pathogenesis, recurrence and metastasis of ovarian cancer, and early diagnosis and treatment still face great challenges. The sensitivity and specificity of existing ovarian cancer screening methods are still unsatisfactory. Centromere protein O (CENP-O) is a recently discovered structural centromere protein that is involved in cell death and is essential for spindle assembly, chromosome separation, and checkpoint signaling during mitosis. The abnormal high expression of CENP-O was detected in various tumors such as bladder cancer and gastric cancer, and it participates in the regulation of tumor cell proliferation. In this study, we detect the expression abundance of CENP-O mRNA in different ovarian cancer cells ( ES-2, A2780, Caov-3, OVCAR-3 and SK-OV-3). The biological function changes of cell proliferation and apoptosis were detected and the role of CENP-O in ovarian cancer cell proliferation and apoptosis was explored by knocking down the expression of CENP-O gene. The results showed that CENP-O gene was significantly expressed in 5 types of ovarian cancer cell lines. After knocking down the CENP-O gene, the proliferation and cloning ability of ovarian cancer cells decreased, and the apoptosis increased. This study indicates that CENP-O has the potential to be a molecular therapeutic target, and downregulating the expression of CENP-O gene can break the unlimited proliferation ability of cancer cells and promote their apoptosis, providing a foundation and new ideas for subsequent molecular mechanism research and targeted therapy.

Burnout among Chinese live streamers: Prevalence and correlates.

BACKGROUND: The prevalence of burnout among live streamers remains largely unknown. This study aims to investigate the prevalence and factors associated with burnout among Chinese live streamers. METHODS: A cross-sectional study recruited 343 full-time live streamers from 3 companies in Changsha city. Socio-demographic and occupational characteristics were collected using self-designed items. Job stress was assessed using the Job Content Questionnaire (JCQ-22), while supervisor and coworker support were evaluated using the last 8 items of the JCQ-22. Burnout was assessed using the 17-item Chinese version of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). RESULTS: Our findings revealed that 30.6% of live streamers experienced burnout. Lower levels of education (OR = 2.65 and 3.37, p = 0,005 and 0.003), higher monthly income (OR = 10.56 and 11.25, both p = 0.003), being an entertainment-oriented streamer (OR = 2.13, p = 0.028), continuous walking during live streams (OR = 2.81, p = 0.006), significant drop in follower count (OR = 2.65, P = 0.006), live streaming during the daytime (OR = 3.75, p = 0.001), and higher support from supervisors and coworkers (OR = 3.66, p = 0.001) were positively associated with burnout. However, the effects of education and drop in followers on burnout were not significant in the multivariate logistic models (p = 0.321 and 0.988). CONCLUSIONS: Burnout among Chinese live streamers is associated with income, being an entertainment streamer, engaging in continuous walking during live streams, conducting live streams during the daytime, and experiencing excessive support from supervisors and coworkers.

EV71 5'UTR interacts with 3D protein affecting replication through the AKT-mTOR pathway.

BACKGROUND: EV71 is one of the important pathogens of Hand-foot-and-mouth disease (HFMD), which causes serious neurological symptoms. Several studies have speculated that there will be interaction between 5'UTR and 3D protein. However, whether 5'UTR interacts with the 3D protein in regulating virus replication has not been clarified. METHODS: Four 5'UTR mutation sites (nt88C/T, nt90-102-3C, nt157G/A and nt574T/A) and two 3D protein mutation sites (S37N and R142K) were mutated or co-mutated using virulent strains as templates. The replication of these mutant viruses and their effect on autophagy were determined. RESULTS: 5'UTR single-point mutant strains, except for EGFP-EV71(nt90-102-3C), triggered replication attenuation. The replication ability of them was weaker than that of the parent strain the virulent strain SDLY107 which is the fatal strain that can cause severe neurological complications. While the replication level of the co-mutant strains showed different characteristics. 5 co-mutant strains with interaction were screened: EGFP-EV71(S37N-nt88C/T), EGFP-EV71(S37N-nt574T/A), EGFP-EV71(R142K-nt574T/A), EGFP-EV71(R142K-nt88C/T), and EGFP-EV71(R142K-nt157G/A). The results showed that the high replicative strains significantly promoted the accumulation of autophagosomes in host cells and hindered the degradation of autolysosomes. The low replicative strains had a low ability to regulate the autophagy of host cells. In addition, the high replicative strains also significantly inhibited the phosphorylation of AKT and mTOR. CONCLUSIONS: EV71 5'UTR interacted with the 3D protein during virus replication. The co-mutation of S37N and nt88C/T, S37N and nt574T/ A, R142K and nt574T/A induced incomplete autophagy of host cells and promoted virus replication by inhibiting the autophagy pathway AKT-mTOR. The co-mutation of R142K and nt88C/T, and R142K and nt157G/A significantly reduced the inhibitory effect of EV71 on the AKT-mTOR pathway and reduced the replication ability of the virus.

Streamflow seasonality in a snow-dwindling world.

Climate warming induces shifts from snow to rain in cold regions1, altering snowpack dynamics with consequent impacts on streamflow that raise challenges to many aspects of ecosystem services2-4. A straightforward conceptual model states that as the fraction of precipitation falling as snow (snowfall fraction) declines, less solid water is stored over the winter and both snowmelt and streamflow shift earlier in season. Yet the responses of streamflow patterns to shifts in snowfall fraction remain uncertain5-9. Here we show that as snowfall fraction declines, the timing of the centre of streamflow mass may be advanced or delayed. Our results, based on analysis of 1950-2020 streamflow measurements across 3,049 snow-affected catchments over the Northern Hemisphere, show that mean snowfall fraction modulates the seasonal response to reductions in snowfall fraction. Specifically, temporal changes in streamflow timing with declining snowfall fraction reveal a gradient from earlier streamflow in snow-rich catchments to delayed streamflow in less snowy catchments. Furthermore, interannual variability of streamflow timing and seasonal variation increase as snowfall fraction decreases across both space and time. Our findings revise the 'less snow equals earlier streamflow' heuristic and instead point towards a complex evolution of seasonal streamflow regimes in a snow-dwindling world.

Unleashing the potential: integrating nano-delivery systems with traditional Chinese medicine.

This review explores the potential of integrating nano-delivery systems with traditional Chinese herbal medicine, acupuncture, and Chinese medical theory. It highlights the intersections and potential of nano-delivery systems in enhancing the effectiveness of traditional herbal medicine and acupuncture treatments. In addition, it discusses how the integration of nano-delivery systems with Chinese medical theory can modernize herbal medicine and make it more readily accessible on a global scale. Finally, it analyzes the challenges and future directions in this field.

PERF: Panoramic Neural Radiance Field from a Single Panorama.

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single image with 3D priors. They mainly focus on a limited field of view with a few occlusions, which greatly limits their scalability to real-world 360-degree panoramic scenarios with large-size occlusions. In this paper, we present PERF, a 360-degree novel view synthesis framework that trains a panoramic neural radiance field from a single panorama. Notably, PERF allows 3D roaming in a complex scene without expensive and tedious image collection. To achieve this goal, we propose a novel collaborative RGBD inpainting method and a progressive inpainting-and-erasing method to lift up a 360-degree 2D scene to a 3D scene. Specifically, we first predict a panoramic depth map as initialization given a single panorama and reconstruct visible 3D regions with volume rendering. Then we introduce a collaborative RGBD inpainting approach into a NeRF for completing RGB images and depth maps from random views, which is derived from an RGB Stable Diffusion model and a monocular depth estimator. Finally, we introduce an inpainting-and-erasing strategy to avoid inconsistent geometry between a newly-sampled view and reference views. The two components are integrated into the learning of NeRFs in a unified optimization framework and achieve promising results. Extensive experiments on Replica and a new dataset PERF-in-the-wild demonstrate the superiority of our PERF over state-of-the-art methods. Our PERF can be widely used for real-world applications, such as panorama-to-3D, text-to-3D, and 3D scene stylization applications. Project page and code are available at https://github.com/perf-project/PeRF.

Impact of Long COVID on Health-Related Quality of Life Among Patients After Acute COVID-19 Infection: A Cross-Sectional Study.

Concerns have been raised globally regarding the long-term effects of the novel coronavirus disease 2019 (COVID-19). This study aimed to investigate the impact of long COVID on the health of patients recovering from acute COVID-19 in China. We conducted a cross-sectional questionnaire survey from 1 February to 9 March 2023. Propensity score matching (PSM) was used to understand the differences in health utility values between individuals with and without long COVID. Factors associated with health-related quality of life (HRQoL) were determined using a multiple linear regression model. A chi-square test was used to compare differences between the 2 groups for each dimension of the EuroQoL-5 Dimension-5 Level (EQ-5D-5L) scale. In total, 307 participants were included in the analysis, of which 40.39% exhibited at least 1 persistent symptom. The common symptoms of long COVID were fatigue/weakness, coughing, memory decline, poor concentration, and phlegm in the throat. Most patients with long COVID reported mild effects from their symptoms. After propensity score matching, the long-COVID group had lower health utility scores than the non-long-COVID group (0.94 vs 0.97). In the multivariable linear regression analysis, persistent symptoms and low annual household income were associated with lower health utility values (P < .05). Anxiety/depression and pain/discomfort were the major problems experienced by the participants with long COVID. Long-COVID symptoms following acute COVID-19 infection have a serious impact on health-related quality of life. Therefore, it is necessary to implement interventions to improve patient health after the recovery from acute COVID-19.

Through-polymer, via technology-enabled, flexible, lightweight, and integrated devices for implantable neural probes.

In implantable electrophysiological recording systems, the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal processing. While advancements in MEMS and CMOS technology have significantly improved these components, their interconnection still relies on conventional printed circuit boards and sophisticated adapters. This conventional approach adds considerable weight and volume to the package, especially for high channel count systems. To address this issue, we developed a through-polymer via (TPV) method inspired by the through-silicon via (TSV) technique in advanced three-dimensional packaging. This innovation enables the vertical integration of flexible probes, amplifier chips, and PCBs, realizing a flexible, lightweight, and integrated device (FLID). The total weight of the FLIDis only 25% that of its conventional counterparts relying on adapters, which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without implants. Furthermore, by incorporating a platinum-iridium alloy as the top layer material for electrical contact, the FLID realizes exceptional electrical performance, enabling in vivo measurements of both local field potentials and individual neuron action potentials. These findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

Can We Differentiate Between Primary Sjögren Syndrome and Idiopathic Multicentric Castleman Disease Based on the Characteristics of Pulmonary Cysts?

PURPOSE: To identify radiological characteristics that could help differentiate cystic lung diseases between primary Sjögren syndrome (pSS) and idiopathic multicentric Castleman disease (iMCD). PATIENTS AND METHODS: Patients with pSS or iMCD who had cysts were enrolled. Cyst characteristics (number, size, morphology, and distribution) and other accompanying manifestations (nodules, ground-glass opacities, calcification, and thickening of the bronchovascular bundles and interlobular septa) were compared between them. RESULTS: Eleven patients with pSS and 25 patients with iMCD were eligible for our study. Eleven patients with pSS (100.0%) and 23 patients with iMCD (92.0%) had round or oval cysts. None of the patients with pSS had irregular cysts, but 21 (84.0%) patients with iMCD had irregular cysts (P = 0.005). Smooth-walled cysts were present in 11 patients with pSS (100.0%) and 18 patients with iMCD (72.0%). Only 1 patient with pSS (9.1%) exhibited non-smooth-walled cysts, whereas 23 patients with iMCD (92.0%) had non-smooth-walled cysts (P = 0.003). The presence of nodules was common in both groups (P = 1.000). However, the nodules were more likely to be larger and more numerous in patients with iMCD (P < 0.001). Cysts with mural nodules (52.2%) and central nodules (47.8%) were only observed in iMCD (P = 0.007). CONCLUSION: Although regular and smooth-walled cysts were common in the 2 diseases, irregular and non-smooth-walled cysts were more often associated with iMCD than pSS. Nodules in iMCD tended to be larger and more numerous, and a close positional relationship between nodules and cysts was only observed in iMCD.