A basally active cGAS-STING pathway limits SARS-CoV-2 replication in a subset of ACE2 positive airway cell models.

Host factors that define the cellular tropism of SARS-CoV-2 beyond the cognate ACE2 receptor are poorly defined. Here we report that SARS-CoV-2 replication is restricted at a post-entry step in a number of ACE2-positive airway-derived cell lines due to tonic activation of the cGAS-STING pathway mediated by mitochondrial DNA leakage and naturally occurring cGAS and STING variants. Genetic and pharmacological inhibition of the cGAS-STING and type I/III IFN pathways as well as ACE2 overexpression overcome these blocks. SARS-CoV-2 replication in STING knockout cell lines and primary airway cultures induces ISG expression but only in uninfected bystander cells, demonstrating efficient antagonism of the type I/III IFN-pathway in productively infected cells. Pharmacological inhibition of STING in primary airway cells enhances SARS-CoV-2 replication and reduces virus-induced innate immune activation. Together, our study highlights that tonic activation of the cGAS-STING and IFN pathways can impact SARS-CoV-2 cellular tropism in a manner dependent on ACE2 expression levels.

Advanced alginate-based nanofiber aerogels: A synthetic matrix for high-efficiency lysozyme adsorption and controlled release.

The development of materials with high lysozyme adsorption is critical for drug delivery and skin wound applications, as it enhances antibacterial properties, stability, and controlled release of therapeutic agents, thereby improving treatment efficacy and safety. Alginate-based nanofiber scaffolds, featuring high surface area and multiple adsorption sites, can efficiently absorb lysozyme and regulate its release through tunable pore channels, offering a promising approach to chronic wound management. In this study, we fabricated poly (vinyl alcohol-co-ethylene) (EVOH) nanofiber-based sodium alginate (ENSA) aerogels using a simple two-step crosslinking procedure. The resulting aerogels, with controllable porosity formed via high-pressure spraying techniques (aerogel film) and molding (aerogel sponge), were evaluated for their high-loading capacity and controllable release of lysozyme. The aerogel film exhibited a remarkable lysozyme adsorption capacity of 1965 ±â€¯36 mg/g, while the aerogel sponge sustained lysozyme release over 14 days. Analysis of the drug-release mechanism through four kinetic models revealed two distinct processes: cation exchange and matrix diffusion. The aerogel's pore structure influenced the diffusion processes, enabling tailored drug release profiles. Additionally, the ENSA aerogels demonstrated good mechanical properties, non-cytotoxicity, and potent antibacterial activity, positioning them as promising materials for skin wound dressings.

Multi-task Learning for Audio-based Infant Cry Detection and Reasoning.

Infant cry is a crucial indicator that offers valuable insights into their physical and mental conditions, such as hunger and pain. However, the scarcity of infant cry datasets hinders the model's generalization in real-life scenarios. The varying voiceprint characteristics among infants further exacerbate this challenge, deteriorating the model's performance on unseen infants. To this end, we propose a multi-task model for Infant Cry Detection and Reasoning (ICDR). It leverages datasets from two tasks to enrich data diversity and introduces an efficient attention module to achieve inter-task feature supplementarity. To mitigate the impact of subject differences, ICDR introduces an intra-task contrastive mixture of experts (CMoE) module that adaptively allocates experts to reduce subject variance and applies contrastive learning to enhance the representation consistency of samples from different infants in the same state. Extensive cross-subject experiments show that ICDR outperforms the state-of-the-art models in infant cry detection and reasoning, with an improvement of 2-9% in the F1-score. This demonstrates that multi-task learning effectively enhances the model's generalization ability by inter-task attention and intra-task CMoE.

RNA-binding protein LSM7 facilitates breast cancer metastasis through mediating alternative splicing of CD44.

AIMS: The RNA-binding protein LSM7 is essential for RNA splicing, acting as a key component of the spliceosome complex; however, its specific role in breast cancer (BC) has not been extensively investigated. MATERIALS AND METHODS: LSM7 expression in BC samples was evaluated through bioinformatics analysis and immunohistochemistry. The impact of LSM7 on promoting metastatic tumor characteristics was examined using transwell and wound healing assays, as well as an orthotopic xenograft model. Additionally, the involvement of LSM7 in alternative splicing of CD44 was explored via RNA immunoprecipitation and third-generation sequencing. The regulatory role of TCF3 in modulating LSM7 gene expression was further elucidated using luciferase reporter assays and chromatin immunoprecipitation. KEY FINDINGS: Our findings demonstrate that LSM7 was significantly overexpressed in metastatic BC tissues and was associated with poor prognostic outcomes in patients with BC. LSM7 overexpression markedly increased the migratory and invasive capabilities of BC cells in vitro and significantly promoted spontaneous lung metastasis in vivo. Furthermore, RIP-seq analysis revealed that LSM7 binded to CD44 RNA, enhancing the expression of its alternatively spliced isoform CD44s, thereby driving BC metastasis and invasion. Additionally, the transcription factor TCF3 was found to activate LSM7 transcription by directly binding to its promoter. SIGNIFICANCE: In summary, this study highlights the pivotal role of LSM7 in the production of the CD44s isoform and the promotion of breast cancer metastasis. Targeting the TCF3/LSM7/CD44s axis may offer a promising therapeutic strategy for breast cancer treatment.

Dual-branch Transformer for semi-supervised medical image segmentation.

PURPOSE: In recent years, the use of deep learning for medical image segmentation has become a popular trend, but its development also faces some challenges. Firstly, due to the specialized nature of medical data, precise annotation is time-consuming and labor-intensive. Training neural networks effectively with limited labeled data is a significant challenge in medical image analysis. Secondly, convolutional neural networks commonly used for medical image segmentation research often focus on local features in images. However, the recognition of complex anatomical structures or irregular lesions often requires the assistance of both local and global information, which has led to a bottleneck in its development. Addressing these two issues, in this paper, we propose a novel network architecture. METHODS: We integrate a shift window mechanism to learn more comprehensive semantic information and employ a semi-supervised learning strategy by incorporating a flexible amount of unlabeled data. Specifically, a typical U-shaped encoder-decoder structure is applied to obtain rich feature maps. Each encoder is designed as a dual-branch structure, containing Swin modules equipped with windows of different size to capture features of multiple scales. To effectively utilize unlabeled data, a level set function is introduced to establish consistency between the function regression and pixel classification. RESULTS: We conducted experiments on the COVID-19 CT dataset and DRIVE dataset and compared our approach with various semi-supervised and fully supervised learning models. On the COVID-19 CT dataset, we achieved a segmentation accuracy of up to 74.56%. Our segmentation accuracy on the DRIVE dataset was 79.79%. CONCLUSIONS: The results demonstrate the outstanding performance of our method on several commonly used evaluation metrics. The high segmentation accuracy of our model demonstrates that utilizing Swin modules with different window sizes can enhance the feature extraction capability of the model, and the level set function can enable semi-supervised models to more effectively utilize unlabeled data. This provides meaningful insights for the application of deep learning in medical image segmentation. Our code will be released once the manuscript is accepted for publication.

A Pseudovirus Nanoparticle Displaying the Vaccinia Virus L1 Protein Elicited High Neutralizing Antibody Titers and Provided Complete Protection to Mice against Mortality Caused by a Vaccinia Virus Challenge.

The recent worldwide incidence of mpox infection and concerns about future emerging variants of mpox viruses highlight the need for the development of a new generation of mpox vaccines. To achieve this goal, we utilized our norovirus S nanoparticle vaccine platform to produce and evaluate two pseudovirus nanoparticles (PVNPs), S-L1 and S-J1. These PVNPs displayed the L1 neutralizing antigen target of the vaccinia virus and a yet-untested J1 antigen of the mpox virus, respectively, with the aim of creating an effective nanoparticle-based mpox vaccine. Each self-assembled PVNP consists of an inner shell resembling the interior layer of the norovirus capsid and multiple L1 or J1 antigens on the surface. The PVNPs improved the antibody responses toward the displayed L1 or J1 antigens in mice, resulting in significantly greater L1/J1-specific IgG and IgA titers than those elicited by the corresponding free L1 or J1 antigens. After immunization with the S-L1 PVNPs, the mouse sera exhibited high neutralizing antibody titers against the vaccinia virus, and the S-L1 PVNPs provided mice with 100% protection against mortality caused by vaccinia virus challenge. In contrast, the S-J1 PVNPs induced low neutralizing antibody titers and conferred mice weak protective immunity. These data confirm that the L1 protein is an excellent vaccine target and that the readily available S-L1 PVNPs are a promising mpox vaccine candidate worthy of further development.

Gallbladder cancer masquerading as xanthogranulomatous cholecystitis: a case report and literature review.

Xanthogranulomatous cholecystitis (XGC) is a rare type of cholecystitis that, despite being benign poses diagnostic challenges due to its low prevalence and need for consensus on diagnostic criteria. Consequently, distinguishing XGC from gallbladder cancer (GBC) is challenging, leading to clinical misdiagnoses. This article presents a case where a patient initially diagnosed with GBC was later found to have XGC.

Structural Color Colloidal Photonic Crystals for Biomedical Applications.

Photonic crystals are a new class of optical microstructure materials characterized by a dielectric constant that varies periodically with space and features a photonic bandgap. Inspired by natural photonic crystals such as butterfly scales, a series of artificial photonic crystals are developed for use in integrated photonic platforms, biosensing, communication, and other fields. Among them, colloidal photonic crystals (CPCs) have gained widespread attention due to their excellent optical properties and advantages, such as ease of preparation and functionalization. This work reviews the classification and self-assembly principles of CPCs, details some of the latest biomedical applications of large-area, high-quality CPCs prepared using advanced self-assembly methods, summarizes the existing challenges in CPC construction and application, and anticipates future development directions and optimization strategy. With further advancements, CPCs are expected to play a more critical role in biosensors, drug delivery, cell research, and other fields, bringing significant benefits to biomedical research and clinical practice.

[Progress in Surgical Treatment of Upper Urinary Tract Stones in Children].

The incidence of urinary calculi in children has been increasing annually,and most of the cases are upper urinary tract stones.At present,surgery is the main way to treat upper urinary tract stones in children.With the gradual development of minimally invasive techniques in surgery,percutaneous nephrolithotomy,retrograde intrarenal surgery,and extracorporeal shock wave lithotripsy have become the main methods for treating upper urinary tract stones in children.We reviewed the current progress in surgical treatment of upper urinary tract stones in children and provided prospects for future treatment options.

Sandwiched-structure fabric-based high-performance moisture-enabled electricity generators for the power supply of small electronics.

In response to the energy crisis caused by the exhaustion of fossil energy sources, as well as to combat global warming and achieve carbon neutrality, a sandwiched-structure fabric-based moisture-enabled electricity generator (SMEG) has been developed. Cotton fabric coated with MWCNT and PEDOT: PSS solution is used as the upper and bottom electrodes, while the acid-treated cotton fabric with coating PVA and HCl hydrogel electrolyte serves as the middle layer. A single SMEG can generate a maximum open-circuit voltage (Voc) of 0.44 V and a maximum short-circuit current (Isc) of 30 µA. When a drop of LiCl is dripped on one side of SMEGs, the maximum Voc and Isc increases to 0.57 V and 66 µA, respectively. The decline in output performance slows down when LiCl is applied. The Voc increases almost linearly in series and reaches 3.55 V when six SMEGs are connected, while the Isc increases linearly in parallel and reaches 204 µA when six SMEGs are connected. The maximum power density of a single SMEG yields 0.29 µW/cm2 with an external resistance of 1 kΩ. The series connection of six SMEGs successfully lit an LED and a calculator under ambient humidity conditions, demonstrating their potential application in small electronics.

Evaluation of accurate measurement methods for radon exhalation rate with advection effect and application in field.

In decommissioning of a uranium tailings pond, radon exhalation rates on a beach surface should meet regulatory standards. Accurate measurements of the radon exhalation rate are demanded. However, current studies fail to consider the impact of advection under temperature variations or pressure gradients caused by gas movement on measurements using an accumulation chamber. Two proposed methods were therefore evaluated to accurately measure radon exhalation rates on the loose medium surface under advective conditions. Repeated experiments were conducted on a laboratory experimental platform filled with uranium tailings sand under advective flow rates of 0.03 and 0.3 L/min to validate the stability and reliability. Deviations between measured and true values were 0.1-6.1 % and 6.3-29.2 % for the two methods, respectively. Subsequently, numerical simulation was used to analyze defects of traditional methods and mechanisms of the new methods. In a field study, all methods were compared, and a predictive map of radon exhalation rates was created using interpolated data from 20 random sites using the new method. Results from the proposed methods, compared with traditional ones, were closer to true values under advective conditions, and accurate assessment of beach surface treatment was expected.

Preparation and application of alkali-activated cementitious materials in solidification/stabilization of chromite ore processing residue.

Chromite ore processing residue (COPR) is a typical hazardous waste, which contains Cr(vi) and poses a great threat to the ecological environment and human health. In this study, solidification/stabilization (S/S) of COPR was carried out by using blast furnace slag (BFS) and fly ash (FA) to prepare alkali-activated cementitious materials (AACM). The influence of different factors (water glass modulus, liquid-solid ratio, alkali-solid content and curing temperature) on compressive strength was investigated by single-factor experiment. Additionally, solidification effect of AACM was determined according to the compressive strength and the leaching concentration of chromium (Cr(vi) and total Cr). According to the optimal conditions of the single-factor experiment, the highest compressive strength of 147.6 MPa was obtained after using the water glass modulus 1.0, liquid-solid ratio 0.28, alkali-solid content 8%, curing temperature 45 °C. The COPR was solidified in the AACM sample having highest compressive strength. The solidified body still has a good mechanical property (38.2 MPa) with 60% addition COPR. According to leaching tests, the leaching of Cr(vi) and total Cr of solidified body with 50% COPR was far lower than the limit value, which met the purpose of construction and landfill disposal. X-ray diffraction (XRD) analysis, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) analysis proved that heavy metal chromium was solidified in AACM by physical and chemical means.

RANKL/RANK signaling recruits Tregs via the CCL20-CCR6 pathway and promotes stemness and metastasis in colorectal cancer.

TNF receptor superfamily member 11a (TNFRSF11a, RANK) and its ligand TNF superfamily member 11 (TNFRSF11, RANKL) are overexpressed in many malignancies. However, the clinical importance of RANKL/RANK in colorectal cancer (CRC) is mainly unknown. We examined CRC samples and found that RANKL/RANK was elevated in CRC tissues compared with nearby normal tissues. A higher RANKL/RANK expression was associated with a worse survival rate. Furthermore, RANKL was mostly produced by regulatory T cells (Tregs), which were able to promote CRC advancement. Overexpression of RANK or addition of RANKL significantly increased the stemness and migration of CRC cells. Furthermore, RANKL/RANK signaling stimulated C-C motif chemokine ligand 20 (CCL20) production by CRC cells, leading to Treg recruitment and boosting tumor stemness and malignant progression. This recruitment process was accomplished by CCL20-CCR6 interaction, demonstrating a connection between CRC cells and immune cells. These findings suggest an important role of RANKL/RANK in CRC progression, offering a potential target for CRC prevention and therapy.

A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.

BACKGROUND: With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11. METHODS: Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members. RESULTS: A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p = 0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%). CONCLUSIONS: This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.

Automatic detection of obstructive sleep apnea based on speech or snoring sounds: a narrative review.

Background and Objective: Obstructive sleep apnea (OSA) is a common chronic disorder characterized by repeated breathing pauses during sleep caused by upper airway narrowing or collapse. The gold standard for OSA diagnosis is the polysomnography test, which is time consuming, expensive, and invasive. In recent years, more cost-effective approaches for OSA detection based in predictive value of speech and snoring has emerged. In this paper, we offer a comprehensive summary of current research progress on the applications of speech or snoring sounds for the automatic detection of OSA and discuss the key challenges that need to be overcome for future research into this novel approach. Methods: PubMed, IEEE Xplore, and Web of Science databases were searched with related keywords. Literature published between 1989 and 2022 examining the potential of using speech or snoring sounds for automated OSA detection was reviewed. Key Content and Findings: Speech and snoring sounds contain a large amount of information about OSA, and they have been extensively studied in the automatic screening of OSA. By importing features extracted from speech and snoring sounds into artificial intelligence models, clinicians can automatically screen for OSA. Features such as formant, linear prediction cepstral coefficients, mel-frequency cepstral coefficients, and artificial intelligence algorithms including support vector machines, Gaussian mixture model, and hidden Markov models have been extensively studied for the detection of OSA. Conclusions: Due to the significant advantages of noninvasive, low-cost, and contactless data collection, an automatic approach based on speech or snoring sounds seems to be a promising tool for the detection of OSA.

Glutamatergic neurons in the paraventricular nucleus of the hypothalamus participate in the regulation of visceral pain induced by pancreatic cancer in mice.

Background: Visceral pain induced by pancreatic cancer seriously affects patients' quality of life, and there is no effective treatment, because the mechanism of its neural circuit is unknown. Therefore, the aim of this study is to explore the main neural circuit mechanism regulating visceral pain induced by pancreatic cancer in mice. Methods: The mouse model of pancreatic cancer visceral pain was established on C57BL/6N mice by pancreatic injection of mPAKPC-luc cells. Abdominal mechanical hyperalgesia and hunch score were performed to assess visceral pain; the pseudorabies virus (PRV) was used to identify the brain regions innervating the pancreas; the c-fos co-labeling method was used to ascertain the types of activated neurons; in vitro electrophysiological patch-clamp technique was used to record the electrophysiological activity of specific neurons; the calcium imaging technique was used to determine the calcium activity of specific neurons; specific neuron destruction and chemogenetics methods were used to explore whether specific neurons were involved in visceral pain induced by pancreatic cancer. Results: The PRV injected into the pancreas was detected in the paraventricular nucleus of the hypothalamus (PVN). Immunofluorescence staining showed that the majority of c-fos were co-labeled with glutamatergic neurons in the PVN. In vitro electrophysiological results showed that the firing frequency of glutamatergic neurons in the PVN was increased. The calcium imaging results showed that the calcium activity of glutamatergic neurons in the PVN was enhanced. Both specific destruction of glutamatergic neurons and chemogenetics inhibition of glutamatergic neurons in the PVN alleviated visceral pain induced by pancreatic cancer. Conclusions: Glutamatergic neurons in the PVN participate in the regulation of visceral pain induced by pancreatic cancer in mice, providing new insights for the discovery of effective targets for the treatment of pancreatic cancer visceral pain.

Vertical habitat preferences shape the fish gut microbiota in a shallow lake.

Understanding the interactions between fish gut microbiota and the aquatic environment is a key issue for understanding aquatic microorganisms. Environmental microorganisms enter fish intestines through feeding, and the amount of invasion varies due to different feeding habits. Traditional fish feeding habitat preferences are determined by fish morphology or behavior. However, little is known about how the feeding behavior of fish relative to the vertical structure in a shallow lake influences gut microbiota. In our study, we used nitrogen isotopes to measure the trophic levels of fish. Then high-throughput sequencing was used to describe the composition of environmental microbiota and fish gut microbiota, and FEAST (fast expectation-maximization for microbial source tracking) method was used to trace the source of fish gut microbiota. We investigated the microbial diversity of fish guts and their habitats in Lake Sanjiao and verified that the sediments indeed played an important role in the assembly of fish gut microbiota. Then, the FEAST analysis indicated that microbiota in water and sediments acted as the primary sources in half of the fish gut microbiota respectively. Furthermore, we classified the vertical habitat preferences using microbial data and significant differences in both composition and function of fish gut microbiota were observed between groups with distinct habitat preferences. The performance of supervised and unsupervised machine learning in classifying fish gut microbiota by habitat preferences actually exceeded classification by fish species taxonomy and fish trophic level. Finally, we described the stability of fish co-occurrence networks with different habitat preferences. Interestingly, the co-occurrence network seemed more stable in pelagic fish than in benthic fish. Our results show that the preferences of fish in the vertical structure of habitat was the main factor affecting their gut microbiota. We advocated the use of microbial interactions between fish gut and their surrounding environment to reflect fish preferences in vertical habitat structure. This approach not only offers a novel perspective for understanding the interactions between fish gut microbiota and environmental factors, but also provides new methods and ideas for studying fish habitat selection in aquatic ecosystems.

Biomimetic Design of 3D Fe3O4/V-EVOH Fiber-Based Self-Floating Composite Aerogel to Enhance Solar Steam Generation Performance.

An interfacial solar steam generation evaporator for seawater desalination has attracted extensive interest in recent years. Nevertheless, challenges still remain in relatively low evaporation rate, unsatisfactory energy conversion efficiency, and salt accumulation. Herein, we have demonstrated a biomimetic bilayer composite aerogel consisting of bottom hydrophilic and vertically aligned EVOH channels and an upper hydrophobic conical Fe3O4 array. Thanks to the design merits, the 3D Fe3O4/V-EVOH evaporator exhibits a high evaporation rate of ∼2.446 kg m-2 h-1 and an impressive solar energy conversion efficiency of ∼165.5% under 1 sun illumination, which is superior to those of state-of-the-art evaporators reported so far. Moreover, the asymmetrical wettability not only allows the evaporator to self-float on the water but also facilitates the salt ion diffusion in the channels; thus, the evaporator shows no salt crystals on its surface and only a 6% decrease in evaporation performance even after the salt concentration increases from 0 to 10.0 wt %.