Reproducibility study of intravoxel incoherent motion and apparent diffusion coefficient parameters in normal pancreas.

BACKGROUND: The consistency of pancreatic apparent diffusion coefficient (ADC) values and intravoxel incoherent motion (IVIM) parameter values across different magnetic resonance imaging (MRI) devices significantly impacts the patient's diagnosis and treatment. AIM: To explore consistency in image quality, ADC values, and IVIM parameter values among different MRI devices in pancreatic examinations. METHODS: This retrospective study was approved by the local ethics committee, and informed consent was obtained from all participants. In total, 22 healthy volunteers (10 males and 12 females) aged 24-61 years (mean, 28.9 ± 2.3 years) underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors. Two independent observers subjectively scored image quality and measured the pancreas's overall ADC values and signal-to-noise ratios (SNRs). Subsequently, regions of interest (ROIs) were delineated for the IVIM parameters (true diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction) using post-processing software. These ROIs were on the head, body, and tail of the pancrease. The subjective image ratings were assessed using the kappa consistency test. Intraclass correlation coefficients (ICCs) and mixed linear models were used to evaluate each device's quantitative parameter values. Finally, a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots. RESULTS: The Kappa value for the subjective ratings of the different observers was 0.776 (P < 0.05). The ICC values for inter-observer and intra-observer agreements for the quantitative parameters were 0.803 [95% confidence interval (CI): 0.684-0.880] and 0.883 (95%CI: 0.760-0.945), respectively (P < 0.05). The ICCs for the SNR between different devices was comparable (P > 0.05), and the ICCs for the ADC values from different devices were 0.870, 0.707, and 0.808, respectively (P < 0.05). Notably, only a few statistically significant inter-device agreements were observed for different IVIM parameters, and among those, the ICC values were generally low. The mixed linear model results indicated differences (P < 0.05) in the f-value for the pancreas head, D-value for the pancreas body, and D-value for the pancreas tail obtained using different MRI machines. The Bland-Altman plots showed significant variability at some data points. CONCLUSION: ADC values are consistent among different devices, but the IVIM parameters' repeatability is moderate. Therefore, the variability in the IVIM parameter values may be associated with using different MRI machines. Thus, caution should be exercised when using IVIM parameter values to assess the pancreas.

Know your orientation: A viewpoint-aware framework for polyp segmentation.

Automatic polyp segmentation in endoscopic images is critical for the early diagnosis of colorectal cancer. Despite the availability of powerful segmentation models, two challenges still impede the accuracy of polyp segmentation algorithms. Firstly, during a colonoscopy, physicians frequently adjust the orientation of the colonoscope tip to capture underlying lesions, resulting in viewpoint changes in the colonoscopy images. These variations increase the diversity of polyp visual appearance, posing a challenge for learning robust polyp features. Secondly, polyps often exhibit properties similar to the surrounding tissues, leading to indistinct polyp boundaries. To address these problems, we propose a viewpoint-aware framework named VANet for precise polyp segmentation. In VANet, polyps are emphasized as a discriminative feature and thus can be localized by class activation maps in a viewpoint classification process. With these polyp locations, we design a viewpoint-aware Transformer (VAFormer) to alleviate the erosion of attention by the surrounding tissues, thereby inducing better polyp representations. Additionally, to enhance the polyp boundary perception of the network, we develop a boundary-aware Transformer (BAFormer) to encourage self-attention towards uncertain regions. As a consequence, the combination of the two modules is capable of calibrating predictions and significantly improving polyp segmentation performance. Extensive experiments on seven public datasets across six metrics demonstrate the state-of-the-art results of our method, and VANet can handle colonoscopy images in real-world scenarios effectively. The source code is available at https://github.com/1024803482/Viewpoint-Aware-Network.

Nomogram for Predicting Efficacy and Prognosis After Chemotherapy for Advanced NSCLC.

PURPOSE: One major issue is the therapeutic effect following chemotherapy for non-small cell lung cancer (NSCLC). Although numerous risk factors have been identified and novel therapies have been developed, improving patient overall survival (OS) remains a crucial postoperative issue. This study aimed to develop a nomogram for accurately predicting the OS of patients with Stage III-IV NSCLC treated with chemotherapy. METHODS: The Department of Respiration at Tangdu Hospital, Air Force Medical University, prospectively collected data on 321 patients between January 2018 and December 2023. A week before treatment, the platelet-to-lymphocyte ratio (PLR), the neutrophil-to-lymphocyte ratio (NLR), and seven autoantibodies were measured using Youden's index, which was obtained using the ROC curve. The formula was used to compute the values of PLR and NLR. After using multifactor Cox regression analysis to identify risk factors, a nomogram was produced regarding the therapeutic effect following chemotherapy. The performance of the nomogram was assessed using a bootstrapped-concordance index and calibration plots. RESULT: It was determined that NLR, sex-determining region Y-box 2 (SOX2), adenosine triphosphate binding RNA deconjugase 4-5 (GBU4-5), and MAGE family member A1 (MAGEA1) were significantly associated factors that could be combined to accurately predict the therapeutic effect following chemotherapy. Utilizing these risk indicators, we were able to develop a nomogram that predicted the patients' survival at 1, 3, and 5 years. At 3 years, the area under the curve representing the expected survival probability was 0.762 (95% confidence interval 0.66-0.87). With a bootstrapped-concordance index of 0.762, the nomogram demonstrated good calibration. CONCLUSIONS: Our nomogram proved to be a valuable instrument in accurately predicting the overall survival of patients.

Hydrogen-Bonded Organic Frameworks-based Electrolytes with Controllable Hydrogen Bonding Networks for Solid-State Lithium Batteries.

The lack of stable solid-state electrolytes (SSEs) with high-ionic conductivity and rational design of electrode/electrolyte interfaces remains challenging for solid-state lithium batteries. Here, for the first time, a high-performance solid-state lithium-oxygen battery is developed based on the Li-ion-conducted hydrogen-bonded organic framework (LHOF) electrolyte and the core-shell HOF-DAT@CNT cathode with a few layers of HOF-DAT on surface of carbon nanotubes. Benefiting from the abundant dynamic hydrogen bonding network in LHOF-DAT SSEs, fast Li+ ion transport (2.2 × 10-4 S cm-1), a high Li+ transfer number (0.88), and a wide electrochemical window of 5.05 V are achieved. Symmetric batteries constructed with LHOF-DAT SSEs exhibit a stably cycled duration of over 1400 h, which mainly stems from the jumping sites that promote a uniformly high rate of Li+ flux and the hydrogen-bonding network structure that can relieve the structural changes during Li+ transport. LHOF-DAT SSEs-based Li-O2 batteries exhibit high specific capacity (10335 mAh g-1), and stable cycling life up to 150 cycles. Moreover, the solid-state lithium metal battery with LHOF-DAT SSEs endow good rate capability (128.8 mAh g-1 at 1 C), long-term discharge/charge stability (210 cycles). The design of LHOF-DAT SSEs opens an avenue for the development of novel SSEs-based solid-state lithium batteries.

Photo-assisted chemical self-rechargeable zinc ion batteries with high charging and discharging efficiency.

Chemically self-recharging zinc ion batteries (ZIBs), which are capable of auto-recharging in ambient air, are promising in self-powered battery systems. Nevertheless, the exclusive reliance on chemical energy from oxygen for ZIBs charging often would bring some obstacles in charging efficiency. Herein, we develop photo-assisted chemically self-recharging aqueous ZIBs with a heterojunction of MoS2/SnO2 cathode, which are favorable to enhancing both the charging and discharging efficiency as well as the chemical self-charging capabilities under illumination. The photo-assisted process promotes the electron transfer from MoS2/SnO2 to oxygen, accelerating the occurrence of the oxidation reaction during chemical self-charging. Furthermore, the electrons within the MoS2/SnO2 cathode exhibit a low transfer impedance under illumination, which is beneficial to reducing the migration barrier of Zn2+ within the cathode and thereby facilitating the uniform inserting of Zn2+ into MoS2/SnO2 cathode during discharging. This photo-assisted chemical self-recharging mechanism enables ZIBs to attain a maximum self-charging potential of 0.95 V within 3 hours, a considerable self-charging capacity of 202.5 mAh g-1 and excellent cycling performance in a self-charging mode. This work not only provides a route for optimizing chemical self-charging energy storage, but also broadens the potential application of aqueous ZIBs.

Optimal Oxophilicity at the Fe-Nx Interface Enhances the Generation of Singlet Oxygen for Efficient Fenton-Like Catalysis.

In the pursuit of efficient singlet oxygen generation in Fenton-like catalysis, the utilization of single-atom catalysts (SACs) emerges as a highly desired strategy. Here, a discovery is reported that the single-atom Fe coordinated with five N-atoms on N-doped porous carbon, denoted as Fe-N5/NC, outperform its counterparts, those coordinated with four (Fe-N4/NC) or six N-atoms (Fe-N6/NC), as well as state-of-the-art SACs comprising other transition metals. Thus, Fe-N5/NC exhibits exceptional efficacy in activating peroxymonosulfate for the degradation of organic pollutants. The coordination number of N-atoms can be readily adjusted by pyrolysis of pre-assembly structures consisting of Fe3+ and various isomers of phenylenediamine. Fe-N5/NC displayed outstanding tolerance to environmental disturbances and minimal iron leaching when incorporated into a membrane reactor. A mechanistic study reveals that the axial ligand N reduces the contribution of Fe-3d orbitals in LUMO and increases the LUMO energy of Fe-N5/NC. This, in turn, reduces the oxophilicity of the Fe center, promoting the reactivity of *OO intermediate-a pivotal step for yielding singlet oxygen and the rate-determining step. These findings unveil the significance of manipulating the oxophilicity of metal atoms in single-atom catalysis and highlight the potential to augment Fenton-like catalysis performance using Fe-SACs.

Epigenetic recording of stimulation history reveals BLIMP1-BACH2 balance in determining memory B cell fate upon recall challenge.

Memory B cells (MBCs) differentiate into plasma cells (PCs) or germinal centers (GCs) upon antigen recall. How this decision is programmed is not understood. We found that the relative strength between two antagonistic transcription factors, B lymphocyte-induced maturation protein 1 (BLIMP1) and BTB domain and CNC homolog 2 (BACH2), progressively increases in favor of BLIMP1 in antigen-responding B cells through the course of primary responses. MBC subsets that preferentially produce secondary GCs expressed comparatively higher BACH2 but lower BLIMP1 than those predisposed for PC development. Skewing the BLIMP1-BACH2 balance in otherwise fate-predisposed MBC subsets could switch their fate preferences. Underlying the changing BLIMP1-over-BACH2 balance, we observed progressively increased accessibilities at chromatin loci that are specifically opened in PCs, particularly those that contain interferon-sensitive response elements (ISREs) and are controlled by interferon regulatory factor 4 (IRF4). IRF4 is upregulated by B cell receptor, CD40 or innate receptor signaling and it induces graded levels of PC-specifying epigenetic imprints according to the strength of stimulation. By analyzing history-stamped GC B cells, we found progressively increased chromatin accessibilities at PC-specific, IRF4-controlled gene loci over time. Therefore, the cumulative stimulation history of B cells is epigenetically recorded in an IRF4-dependent manner, determines the relative strength between BLIMP1 and BACH2 in individual MBCs and dictates their probabilities to develop into GCs or PCs upon restimulation.

Diagnosis of preeclampsia using metabolomic biomarkers.

The diagnostic criteria for preeclampsia do not accurately reflect the pathophysiological characteristics of patients with preeclampsia. Conventional biomarkers and diagnostic approaches have proven insufficient to fully comprehend the intricacies of preeclampsia. This study aimed to screen differentially abundant metabolites as candidate biomarkers for preeclampsia. A propensity score matching method was used to perform a 1:1 match between preeclampsia patients (n = 70) and healthy control individuals (n = 70). Based on univariate and multivariate statistical analysis methods, the different characteristic metabolites were screened and identified. Least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently used to further screen for differentially abundant metabolites. A receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic efficacy of the metabolites. A total of 1,630 metabolites were identified and quantified in maternal serum samples. Fifty-three metabolites were significantly increased, and two were significantly decreased in preeclampsia patients. The area under the curve (AUC) of the model composed of isobutyryl-L-carnitine and acetyl-leucine was 0.878, and the sensitivity and specificity in detecting preeclampsia were 81.4% and 87.1%, respectively. There are significant differences in metabolism between preeclampsia patients and healthy pregnant women, and a range of novel biomarkers have been identified. These findings lay the foundation for the use of metabolomic biomarkers for the diagnosis of preeclampsia.

Geochemical Characteristics and Origin of Sinian-Cambrian Natural Gas in Penglai Gas Area, Sichuan Basin.

The Sichuan Basin in southern China is well-known for its large natural gas resource potential stored in Sinian-Cambrian systems. Recently, high-yield industrial gas flow has been discovered from the Dengying Formation (Sinian System) and Canglangpu Formation (Cambrian System) in the Penglai gas area, preluding the multilayer stereoscopic exploration in Sichuan Basin. However, the origin of the natural gas and its preserving mechanics is still debated, and thus, in this study the geochemical characteristics of the natural gas are systematically analyzed, based on the data from gas composition and hydrocarbon isotope of a series of local wells. On this basis, the geochemical characteristics of natural gas in different regions and layers are compared, and the reasons for these differences from the origin and influencing factors are analyzed. The results show the following: (1) The natural gas of the Penglai gas field is dry gas dominated by CH4, and the Sinian Dengying Formation gas has lower C2H6 content, larger dryness coefficient, heavier δ13C, and lighter δ2HCH4 than the Cambrian gas, which is associated with the high proportion of hydrocarbons from the high-maturity Dengying source rocks. (2) The natural gas from some wells in the lower part of the structure is characterized by high H2S content and low CH4 content, and heavy δ13C in the components, which seems to be affected by the thermochemical sulfate reduction (TSR) effect. (3) The natural gas from the Penglai gas area has a relatively low maturity, which appears to be attributed to the continuous sealing ability of the caprock, which can preserve both the early generated gas and the late thermal-cracked gas.

How does the level of enterprise digitalization affect value creation and realization? Testing of the dual path of "based on breakthrough" and "tending to compliance".

The construction of enterprise digitization serves as a "gateway" for the integration of the digital and real economies. As enterprises undergo robust digital transformations, it becomes crucial to delineate the pathway from enterprise digitization level to value creation and realization in order to maximize enterprise value. We select sample data from Chinese A-share listed companies from 2015 to 2021 as the research subject. Based on the fixed-effects model, we empirically test the impact of enterprise digitization level on both value creation and realization, as well as the mediating mechanism of entrepreneurship and internal control within it. The results indicate that the enterprise digitization level significantly enhances both value creation and realization. However, significant differences exist in the impact of the digitization level on value creation and realization among enterprises with different technological attributes and at different stages of the lifecycle. Further mechanism tests demonstrate that the "breakthrough-based" entrepreneurship and "compliance-based" internal control quality play effective mediating roles between enterprise digitization level and enterprise value. This study provides a new perspective for understanding the value creation and realization process in the digital context, and offers relevant insights for further stimulating and guiding enterprises of different types and stages to drive value enhancement with digital capabilities, thereby facilitating the deep integration of the digital with the real economy.

High recallability of memory B cells requires ZFP318-dependent transcriptional regulation of mitochondrial function.

Expression of the transcriptional regulator ZFP318 is induced in germinal center (GC)-exiting memory B cell precursors and memory B cells (MBCs). Using a conditional ZFP318 fluorescence reporter that also enables ablation of ZFP318-expressing cells, we found that ZFP318-expressing MBCs were highly enriched with GC-derived cells. Although ZFP318-expressing MBCs constituted only a minority of the antigen-specific MBC compartment, their ablation severely impaired recall responses. Deletion of Zfp318 did not alter the magnitude of primary responses but markedly reduced MBC participation in recall. CD40 ligation promoted Zfp318 expression, whereas B cell receptor (BCR) signaling was inhibitory. Enforced ZFP318 expression enhanced recall performance of MBCs that otherwise responded poorly. ZFP318-deficient MBCs expressed less mitochondrial genes, had structurally compromised mitochondria, and were susceptible to reactivation-induced cell death. The abundance of ZFP318-expressing MBCs, instead of the number of antigen-specific MBCs, correlated with the potency of prime-boost vaccination. Therefore, ZFP318 controls the MBC recallability and represents a quality checkpoint of humoral immune memory.

Advances in the understanding of the production, modification and applications of xylanases in the food industry.

Xylanases have broad applications in the food industry to decompose the complex carbohydrate xylan. This is applicable to enhance juice clarity, improve dough softness, or reduce beer turbidity. It can also be used to produce prebiotics and increase the nutritional value in foodstuff. However, the low yield and poor stability of most natural xylanases hinders their further applications. Therefore, it is imperative to explore higher-quality xylanases to address the potential challenges that appear in the food industry and to comprehensively improve the production, modification, and utilization of xylanases. Xylanases, due to their various sources, exhibit diverse characteristics that affect production and activity. Most fungi are suitable for solid-state fermentation to produce xylanases, but in liquid fermentation, microbial metabolism is more vigorous, resulting in higher yield. Fungi produce higher xylanase activity, but bacterial xylanases perform better than fungal ones under certain extreme conditions (high temperature, extreme pH). Gene and protein engineering technology helps to improve the production efficiency of xylanases and enhances their thermal stability and catalytic properties.

Gut-derived metabolite 3-methylxanthine enhances cisplatin-induced apoptosis via dopamine receptor D1 in a mouse model of ovarian cancer.

Platinum-based chemotherapy failure represents a significant challenge in the management of ovarian cancer (OC) and contributes to disease recurrence and poor prognosis. Recent studies have shed light on the involvement of the gut microbiota in modulating anticancer treatments. However, the precise underlying mechanisms, by which gut microbiota regulates the response to platinum-based therapy, remain unclear. Here, we investigated the role of gut microbiota on the anticancer response of cisplatin and its underlying mechanisms. Our results demonstrate a substantial improvement in the anticancer efficacy of cisplatin following antibiotic-induced perturbation of the gut microbiota in OC-bearing mice. 16S rRNA sequencing showed a pronounced alteration in the composition of the gut microbiome in the cecum contents following exposure to cisplatin. Through metabolomic analysis, we identified distinct metabolic profiles in the antibiotic-treated group, with a notable enrichment of the gut-derived metabolite 3-methylxanthine in antibiotic-treated mice. Next, we employed a strategy combining transcriptome analysis and chemical-protein interaction network databases. We identified metabolites that shared structural similarity with 3-methylxanthine, which interacted with genes enriched in cancer-related pathways. It is identified that 3-methylxanthinesignificantly enhances the effectiveness of cisplatin by promoting apoptosis both in vivo and in vitro. Importantly, through integrative multiomics analyses, we elucidated the mechanistic basis of this enhanced apoptosis, revealing a dopamine receptor D1-dependent pathway mediated by 3-methylxanthine. This study elucidated the mechanism by which gut-derived metabolite 3-methylxanthine mediated cisplatin-induced apoptosis. Our findings highlight the potential translational significance of 3-methylxanthine as a promising adjuvant in conjunction with cisplatin, aiming to improve treatment outcomes for OC patients.IMPORTANCEThe precise correlation between the gut microbiota and the anticancer effect of cisplatin in OC remains inadequately understood. Our investigation has revealed that manipulation of the gut microbiota via the administration of antibiotics amplifies the efficacy of cisplatin through the facilitation of apoptosis in OC-bearing mice. Metabolomic analysis has demonstrated that the cecum content from antibiotic-treated mice exhibits an increase in the levels of 3-methylxanthine, which has been shown to potentially enhance the therapeutic effectiveness of cisplatin by an integrated multiomic analysis. This enhancement appears to be attributable to the promotion of cisplatin-induced apoptosis, with 3-methylxanthine potentially exerting its influence via the dopamine receptor D1-dependent pathway. These findings significantly contribute to our comprehension of the impact of the gut microbiota on the anticancer therapy in OC. Notably, the involvement of 3-methylxanthine suggests its prospective utility as a supplementary component for augmenting treatment outcomes in patients afflicted with ovarian cancer.

Circulating tumor DNA- and cancer tissue-based next-generation sequencing reveals comparable consistency in targeted gene mutations for advanced or metastatic non-small cell lung cancer.

BACKGROUND: Molecular subtyping is an essential complementarity after pathological analyses for targeted therapy. This study aimed to investigate the consistency of next-generation sequencing (NGS) results between circulating tumor DNA (ctDNA)-based and tissue-based in non-small cell lung cancer (NSCLC) and identify the patient characteristics that favor ctDNA testing. METHODS: Patients who diagnosed with NSCLC and received both ctDNA- and cancer tissue-based NGS before surgery or systemic treatment in Lung Cancer Center, Sichuan University West China Hospital between December 2017 and August 2022 were enrolled. A 425-cancer panel with a HiSeq 4000 NGS platform was used for NGS. The unweighted Cohen's kappa coefficient was employed to discriminate the high-concordance group from the low-concordance group with a cutoff value of 0.6. Six machine learning models were used to identify patient characteristics that relate to high concordance between ctDNA-based and tissue-based NGS. RESULTS: A total of 85 patients were enrolled, of which 22.4% (19/85) had stage III disease and 56.5% had stage IV disease. Forty-four patients (51.8%) showed consistent gene mutation types between ctDNA-based and tissue-based NGS, while one patient (1.2%) tested negative in both approaches. Advanced diseases and metastases to other organs would be fit for the ctDNA-based NGS, and the generalized linear model showed that T stage, M stage, and tumor mutation burden were the critical discriminators to predict the consistency of results between ctDNA-based and tissue-based NGS. CONCLUSION: ctDNA-based NGS showed comparable detection performance in the targeted gene mutations compared with tissue-based NGS, and it could be considered in advanced or metastatic NSCLC.

Residual learning-based robotic image analysis model for low-voltage distributed photovoltaic fault identification and positioning.

With the fast development of large-scale Photovoltaic (PV) plants, the automatic PV fault identification and positioning have become an important task for the PV intelligent systems, aiming to guarantee the safety, reliability, and productivity of large-scale PV plants. In this paper, we propose a residual learning-based robotic (UAV) image analysis model for low-voltage distributed PV fault identification and positioning. In our target scenario, the unmanned aerial vehicles (UAVs) are deployed to acquire moving images of low-voltage distributed PV power plants. To get desired robustness and accuracy of PV image detection, we integrate residual learning with attention mechanism into the UAV image analysis model based on you only look once v4 (YOLOv4) network. Then, we design the sophisticated multi-scale spatial pyramid fusion and use it to optimize the YOLOv4 network for the nuanced task of fault localization within PV arrays, where the Complete-IOU loss is incorporated in the predictive modeling phase, significantly enhancing the accuracy and efficiency of fault detection. A series of experimental comparisons in terms of the accuracy of fault positioning are conducted, and the experimental results verify the feasibility and effectiveness of the proposed model in dealing with the safety and reliability maintenance of low-voltage distributed PV systems.

Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation.

Background: Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI. Methods: Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling. Results: The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model. Conclusions: The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.

Cervical extracellular matrix hydrogel optimizes tumor heterogeneity of cervical squamous cell carcinoma organoids.

Cervical cancer, primarily squamous cell carcinoma, is the most prevalent gynecologic malignancy. Organoids can mimic tumor development in vitro, but current Matrigel inaccurately replicates the tissue-specific microenvironment. This limitation compromises the accurate representation of tumor heterogeneity. We collected para-cancerous cervical tissues from patients diagnosed with cervical squamous cell carcinoma (CSCC) and prepared uterine cervix extracellular matrix (UCEM) hydrogels. Proteomic analysis of UCEM identified several tissue-specific signaling pathways including human papillomavirus, phosphatidylinositol 3-kinase-AKT, and extracellular matrix receptor. Secreted proteins like FLNA, MYH9, HSPA8, and EEF1A1 were present, indicating UCEM successfully maintained cervical proteins. UCEM provided a tailored microenvironment for CSCC organoids, enabling formation and growth while preserving tumorigenic potential. RNA sequencing showed UCEM-organoids exhibited greater similarity to native CSCC and reflected tumor heterogeneity by exhibiting CSCC-associated signaling pathways including virus protein-cytokine, nuclear factor κB, tumor necrosis factor, and oncogenes EGR1, FPR1, and IFI6. Moreover, UCEM-organoids developed chemotherapy resistance. Our research provides insights into advanced organoid technology through native matrix hydrogels.

Gut microbial genomes with paired isolates from China illustrate probiotic and cardiometabolic effects.

The gut microbiome displays genetic differences among populations, and characterization of the genomic landscape of the gut microbiome in China remains limited. Here, we present the Chinese Gut Microbial Reference (CGMR) set, comprising 101,060 high-quality metagenomic assembled genomes (MAGs) of 3,707 nonredundant species from 3,234 fecal samples across primarily rural Chinese locations, 1,376 live isolates mainly from lactic acid bacteria, and 987 novel species relative to worldwide databases. We observed region-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. Preliminary mouse experiments suggest a probiotic effect of two Faecalibacillus intestinalis isolates in alleviating constipation, cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and isolates from the genera Parabacteroides and Lactobacillus in host lipid metabolism. Our study expands the current microbial genomes with paired isolates and demonstrates potential host effects, contributing to the mechanistic understanding of host-microbe interactions.

Bouncing Dynamics of Drops' Successive Off-Center Impact.

Bouncing dynamics of a trailing drop off-center impacting a leading drop with varying time intervals and Weber numbers are investigated experimentally. Whether the trailing drop impacts during the spreading or receding process of the leading drop is determined by the time interval. For a short time interval of 0.15 ≤ Δt* ≤ 0.66, the trailing drop impacts during the spreading of the leading drop, and the drops completely coalesce and rebound; for a large time interval of 0.66 < Δt* ≤ 2.21, the trailing drop impacts during the receding process, and the drops partially coalesce and rebound. Whether the trailing drop directly impacts the surface or the liquid film of the leading drop is determined by the Weber number. The trailing drop impacts the surface directly at moderate Weber numbers of 16.22 ≤ We ≤ 45.42, while it impacts the liquid film at large Weber numbers of 45.42 < We ≤ 64.88. Intriguingly, when the trailing drop impacts the surface directly or the receding liquid film, the contact time increases linearly with the time interval but independent of the Weber number; when the trailing drop impacts the spreading liquid film, the contact time suddenly increases, showing that the force of the liquid film of the leading drop inhibits the receding of the trailing drop. Finally, a theoretical model of the contact time for the drops is established, which is suitable for different impact scenarios of the successive off-center impact. This study provides a quantitative relationship to calculate the contact time of drops successively impacting a superhydrophobic surface, facilitating the design of anti-icing surfaces.