Metal-Organic Frameworks Possessing Suitable Pores for Xe/Kr Separation.

Adsorption separation of the Xe/Kr mixture remains a tough issue since Xe and Kr have an inert nature and similar sizes. Here we present a chlorinated metal-organic framework (MOF) [JXNU-19(Cl)] and its nonchlorinated analogue (JXNU-19) for Xe/Kr separation. The two isostructural MOFs constructed from the heptanuclear cobalt-hydroxyl clusters bridged by organic ligands are three-dimensional structures. Detailed contrast of the Xe/Kr adsorption separation properties of the MOF shows that significantly enhanced Xe uptakes and Xe/Kr adsorption selectivity (17.1) are observed for JXNU-19 as compared to JXNU-19(Cl). The main binding sites for Xe in the MOF revealed by computational simulations are far away from the chlorine sites, suggesting that the introduction of the chlorine groups results in the unfavorable Xe adsorption for JXNU-19(Cl). The optimal pores, high surface area, and multiple strong Xe-framework interactions facilitate the effective Xe/Kr separation for JXNU-19.

Fluoride exposure-induced gut microbiota alteration mediates colonic ferroptosis through N6-methyladenosine (m6A) mediated silencing of SLC7A11.

Fluoride exposure is widespread worldwide and poses a significant threat to organisms, particularly to their gastrointestinal tracts. However, due to limited knowledge of the mechanism of fluoride induced intestinal injury, it has been challenging to develop an effective treatment. To address this issue, we used a series of molecular biology in vitro and in vivo experiments. NaF triggered m6A mediated ferroptosis to cause intestinal damage. Mechanistically, NaF exposure increased the m6A level of SLC7A11 mRNA, promoted YTHDF2 binding to m6A-modified SLC7A11 mRNA, drove the degradation of SLC7A11 mRNA, and led to a decrease in its protein expression, which eventually triggers ferroptosis. Moreover, NaF aggravated ferroptosis of the colon after antibiotics destroyed the composition of gut microbiota. 16 S rRNA sequencing and SPEC-OCCU plots, Zi-Pi relationships, and Spearman correlation coefficients verified that Lactobacillus murinus (ASV54, ASV58, and ASV82) plays a key role in the response to NaF-induced ferroptosis. Collectively, NaF-induced gut microbiota alteration mediates severe intestinal cell injury by inducing m6A modification-mediated ferroptosis. Our results highlight a key mechanism of the gut in response to NaF exposure and suggest a valuable theoretical basis for its prevention and treatment.

Cross-linked Sodium Hyaluronate Gel with PLLA-b-PEG Microsphere for Facial Contouring in Chinese: A Retrospective Study.

BACKGROUND: In Asia, the demand for cosmetic facial treatments has surged due to technological advancements, increased social acceptability, and affordability. Poly-L-lactic acid (PLLA) fillers, known for their biocompatibility and biodegradability, have emerged as a popular choice for facial contouring, yet studies specifically addressing their use in Asian populations are scarce. METHODS: This retrospective study examined 30 Chinese patients who underwent facial contouring with PLLA fillers, focusing on product composition, injection techniques, and safety measures. A comprehensive clinical evaluation was performed, including the Global Aesthetic Improvement Scale (GAIS) and Global Impression of Change Scale (GICS) for effectiveness and patient satisfaction, respectively. RESULTS: No significant difference in GAIS scores was observed between injectors and blinded evaluators over a 12-month period, indicating consistent effectiveness. Patient satisfaction remained high, with GICS scores reflecting positive outcomes. The safety profile was favorable, with no serious adverse events reported. The study highlighted the importance of anatomical knowledge to avoid complications, particularly in areas prone to blindness. CONCLUSIONS: PLLA fillers offer a safe, effective option for facial contour correction in the Asian population, achieving high patient satisfaction and maintaining results over time. The study underscores the need for tailored approaches in cosmetic procedures for Asians, considering their unique facial structures and aesthetic goals. Further research with larger, multicenter cohorts is recommended to validate these findings and explore long-term effects. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Highly Efficient Multicolor-Emitting Tetraphenylethylene-Based Organic Salts with Commercialization Prospects.

Since the discovery of aggregation-induced emission from tetraphenylethylene derivatives, various methods have been explored to prepare highly efficient multicolored luminescent materials. Herein, we report a simple and efficient strategy for constructing luminescent organic salts of the tetracationic luminogen, tetrapyridinium-tetraphenylethylene (T4Py-TPE4+), combined with seven di- and tetra-anionic aromatic sulfonate ligands. When aqueous solutions of the cationic luminogen and the anionic ligands were mixed, they rapidly aggregated into organic salts within seconds to minutes, giving yields of up to >90%. This was accompanied by an increase in the emission efficiency from ∼58% to almost 100%, and the ability to tune the emission color between 511 and 586 nm. These improvements were mainly attributed to the strong electrostatic attractions between the cation and anions, which resulted in the formation of a rigid hydrophobic network of the T4Py-TPE4+ luminogen with various π-conjugation lengths. Because these compounds are commercially available, this method opens the possibility of fabricating novel light-emitting materials for device fabrication and research.

Semi-supervised iterative adaptive network for low-dose CT sinogram recovery.

Background.Concern has been expressed regarding the risk of carcinogenesis from medical computed tomography (CT) radiation. Lowering radiation in CT without appropriate modifications often leads to severe noise-induced artifacts in the images. The utilization of deep learning (DL) techniques has achieved promising reconstruction performance in low-dose CT (LDCT) imaging. However, most DL-based algorithms require the pre-collection of a large set of image pairs (low-dose/standard-dose) and the training of networks in an end-to-end supervised manner. Meanwhile, securing such a large volume of paired, well-registered training data in clinical practice is challenging. Moreover, these algorithms often overlook the potential to utilize the abundant information in a large collection of LDCT-only images/sinograms.Methods.In this paper, we introduce a semi-supervised iterative adaptive network (SIA-Net) for LDCT imaging, utilizing both labeled and unlabeled sinograms in a cohesive network framework, integrating supervised and unsupervised learning processes. Specifically, the supervised process captures critical features (i.e. noise distribution and tissue characteristics) latent in the paired sinograms, while the unsupervised process effectively learns these features in the unlabeled low-dose sinograms, employing a conventional weighted least-squares model with a regularization term. Furthermore, the SIA-Net method is designed to adaptively transfer the learned feature distribution from the supervised to the unsupervised process, thereby obtaining a high-fidelity sinogram through iterative adaptive learning. Finally, high-quality CT images can be reconstructed from the refined sinogram using the filtered back-projection algorithm.Results.Experimental results on two clinical datasets indicate that the proposed SIA-Net method achieves competitive performance in terms of noise reduction and structure preservation in LDCT imaging, when compared to traditional supervised learning methods.

Effects of polyethylene microplastics occurrence on estrogens degradation in soil.

Growing focus has been drawn to the continuous detection of high estrogens levels in the soil environment. Additionally, microplastics (MPs) are also of growing concern worldwide, which may affect the environmental behavior of estrogens. However, little is known about effects of MPs occurrence on estrogens degradation in soil. In this study, polyethylene microplastics (PE-MPs) were chosen to examine the influence on six common estrogens (estrone (E1), 17α-estradiol (17α-E2), 17ß-estradiol (17ß-E2), estriol (E3), diethylstilbestrol (DES), and 17α-ethinylestradiol (17α-EE2)) degradation. The results indicated that PE-MPs had little effect on the degradation of E3 and DES, and slightly affected the degradation of 17α-E2, however, significantly inhibited the degradation of E1, 17α-EE2, and 17ß-E2. It was explained that (i) obvious oxidation reaction occurred on the surface of PE-MPs, indicating that PE-MPs might compete with estrogens for oxidation sites, such as redox and biological oxidation; (ii) PE-MPs significantly changed the bacterial community in soil, resulting in a decline in the abundance of some bacterial communities that biodegraded estrogens. Moreover, the rough surface of PE-MPs facilitated the estrogen-degrading bacterial species (especially for E1, E2, and EE2) to adhere, which decreased their reaction to estrogens. These findings are expected to deepen the understanding of the environmental behavior of typical estrogens in the coexisting system of MPs.

Study on the Aging Characteristics of a ±500 kV Composite Dead-End Insulator in Longtime Service.

Composite insulators have been widely used in power grids due to their excellent electrical-external-insulation performance. Long-term operation at high voltage levels accelerates the aging of composite insulators; however, there is a scarcity of research on aged composite insulators operating at 500 kV for over ten years. In this paper, the mechanical, electrical, and microscopic properties were tested on different sheds along a 500 kV composite insulator that had been running for 18 years. Additionally, the results were compared with a new insulator and the standards for live insulator operation. The results showed that the aging of the high-voltage end of composite insulators was the most serious. The results of the physical properties test indicated that the insulator's hardness was compliant but its tensile strength and break elongation did not meet standards. Under wet conditions, the pollution flashover voltage decreases by about 50% compared to the new insulator. Combined with the microscopic test results, the shed skeleton structure could be damaged and the filler might be lost during the aging process of polydimethylsiloxane (PDMS). The hardness of the insulator would increase by the precipitation of inorganic silicon; however, inorganic silicon might destroy the hydrophobicity and other properties of insulator sheds. These results can provide theoretical references for insulator life prediction and operation protection.

CircInpp5b Ameliorates Renal Interstitial Fibrosis by Promoting the Lysosomal Degradation of DDX1.

Renal interstitial fibrosis (RIF) is a classic pathophysiological process of chronic kidney disease (CKD). However, the mechanisms underlying RIF remain unclear. The present study found that a novel circular RNA, cirInpp5b, might be involved in RIF by high-throughput sequencing. Subsequent experiments revealed that circInpp5b was reduced in UUO mouse kidney tissues and TGF-ß1-treated proximal tubular cells. The overexpression of circInpp5b inhibited RIF in UUO mice and prevented extracellular matrix (ECM) deposition in TGF-ß1-treated proximal tubular cells. Furthermore, overexpression of circInpp5b down-regulated the protein level of DDX1. Mechanistically, circInpp5b bound to the DDX1 protein and promoted its lysosomal degradation. Collectively, the findings of our study demonstrate that circInpp5b ameliorates RIF by binding to the DDX1 protein and promoting its lysosomal degradation.

Construction of intelligent response gene vector based on MOF/Fe3O4/AuNRs for tumor-targeted gene delivery.

Metal-organic frameworks (MOFs) have the potential to efficiently carry cargo due to their excellent porosity and high surface area. Nevertheless, conventional MOFs and their derivatives exhibit low efficiency in transporting nucleic acids and other small molecules, as well as having poor colloidal stability. In this study, a ZIF-90 loaded with iron oxide nanoparticles and Au nanorods was prepared, and then surface-functionalized with polyethyleneimine (PEI) to create a multifunctional nanocomposite (AFZP25k) with pH, photothermal, and magnetic responsiveness. AFZP25k can condense plasmid DNA to form AFZP25k/DNA complexes, with a maximum binding efficiency of 92.85 %. DNA release assay showed significant light and pH responsiveness, with over 80 % cumulative release after 6 h of incubation. When an external magnetic field is applied, the cellular uptake efficiency in HeLa cells reached 81.51 %, with low cytotoxicity and specific distribution. In vitro transfection experiments demonstrated a gene transfection efficiency of 44.77 % in HeLa cells. Following near-infrared irradiation, the uptake efficiency and transfection efficiency of AFZP25k in HeLa cells increased by 21.3 % and 13.59 % respectively. The findings indicate the potential of AFZP25k as an efficient and targeted gene delivery vector in cancer gene therapy.

b-MAR: bidirectional artifact representations learning framework for metal artifact reduction in dental CBCT.

Objective.Metal artifacts in computed tomography (CT) images hinder diagnosis and treatment significantly. Specifically, dental cone-beam computed tomography (Dental CBCT) images are seriously contaminated by metal artifacts due to the widespread use of low tube voltages and the presence of various high-attenuation materials in dental structures. Existing supervised metal artifact reduction (MAR) methods mainly learn the mapping of artifact-affected images to clean images, while ignoring the modeling of the metal artifact generation process. Therefore, we propose the bidirectional artifact representations learning framework to adaptively encode metal artifacts caused by various dental implants and model the generation and elimination of metal artifacts, thereby improving MAR performance.Approach.Specifically, we introduce an efficient artifact encoder to extract multi-scale representations of metal artifacts from artifact-affected images. These extracted metal artifact representations are then bidirectionally embedded into both the metal artifact generator and the metal artifact eliminator, which can simultaneously improve the performance of artifact removal and artifact generation. The artifact eliminator learns artifact removal in a supervised manner, while the artifact generator learns artifact generation in an adversarial manner. To further improve the performance of the bidirectional task networks, we propose artifact consistency loss to align the consistency of images generated by the eliminator and the generator with or without embedding artifact representations.Main results.To validate the effectiveness of our algorithm, experiments are conducted on simulated and clinical datasets containing various dental metal morphologies. Quantitative metrics are calculated to evaluate the results of the simulation tests, which demonstrate b-MAR improvements of >1.4131 dB in PSNR, >0.3473 HU decrements in RMSE, and >0.0025 promotion in structural similarity index measurement over the current state-of-the-art MAR methods. All results indicate that the proposed b-MAR method can remove artifacts caused by various metal morphologies and restore the structural integrity of dental tissues effectively.Significance.The proposed b-MAR method strengthens the joint learning of the artifact removal process and the artifact generation process by bidirectionally embedding artifact representations, thereby improving the model's artifact removal performance. Compared with other comparison methods, b-MAR can robustly and effectively correct metal artifacts in dental CBCT images caused by different dental metals.

DDT-Net: Dose-Agnostic Dual-Task Transfer Network for Simultaneous Low-Dose CT Denoising and Simulation.

Deep learning (DL) algorithms have achieved unprecedented success in low-dose CT (LDCT) imaging and are expected to be a new generation of CT reconstruction technology. However, most DL-based denoising models often lack the ability to generalize to unseen dose data. Moreover, most simulation tools for LDCT typically operate on proprietary projection data, which is generally not accessible without an established collaboration with CT manufacturers. To alleviate these issues, in this work, we propose a dose-agnostic dual-task transfer network, termed DDT-Net, for simultaneous LDCT denoising and simulation. Concretely, the dual-task learning module is constructed to integrate the LDCT denoising and simulation tasks into a unified optimization framework by learning the joint distribution of LDCT and NDCT data. We approximate the joint distribution of continuous dose level data by training DDT-Net with discrete dose data, which can be generalized to denoising and simulation of unseen dose data. In particular, the mixed-dose training strategy adopted by DDT-Net can promote the denoising performance of lower-dose data. The paired dataset simulated by DDT-Net can be used for data augmentation to further restore the tissue texture of LDCT images. Experimental results on synthetic data and clinical data show that the proposed DDT-Net outperforms competing methods in terms of denoising and generalization performance at unseen dose data, and it also provides a simulation tool that can quickly simulate realistic LDCT images at arbitrary dose levels.

Targeted Screening of Fiber Degrading Bacteria with Probiotic Function in Herbivore Feces.

Cellulolytic bacteria with probiotic functions play a crucial role in promoting the intestinal health in herbivores. In this study, we aimed to correlate the 16S rRNA gene amplicon sequencing and fiber-degrading enzyme activity data from six different herbivore feces samples. By utilizing the separation and screening steps of probiotics, we targeted and screened high-efficiency fiber-degrading bacteria with probiotic functions. The animals included Maiwa Yak (MY), Holstein cow (CC), Tibetan sheep (TS), Southern Sichuan black goat (SG), Sichuan white rex rabbit (CR), and New Zealand white rabbit (ZR). The results showed that the enzymes associated with fiber degradation were higher in goat and sheep feces compared to cattle and rabbit's feces. Correlation analysis revealed that Bacillus and Fibrobacter were positively correlated with five types of fiber-degrading related enzymes. Notably, the relative abundance of Bacillus in the feces of Tibetan sheep was significantly higher than that of other five herbivores. A strain TS5 with good cellulose decomposition ability from the feces of Tibetan sheep by Congored staining, filter paper decomposition test, and enzyme activity determination was isolated. The strain was identified as Bacillus velezensis by biological characteristics, biochemical analysis, and 16S rRNA gene sequencing. To test the probiotic properties of Bacillus velezensis TS5, we evaluated its tolerance to acid and bile salt, production of digestive enzymes, antioxidants, antibacterial activity, and adhesion ability. The results showed that the strain had good tolerance to pH 2.0 and 0.3% bile salts, as well as good potential to produce cellulase, protease, amylase, and lipase. This strain also had good antioxidant capacity and the ability to antagonistic Staphylococcus aureus BJ216, Salmonella SC06, Enterotoxigenic Escherichia coli CVCC196, and Escherichia coli ATCC25922. More importantly, the strain had good self-aggregation and Caco-2 cell adhesion rate. In addition, we tested the safety of Bacillus velezensis TS5 by hemolysis test, antimicrobial susceptibility test, and acute toxicity test in mice. The results showed that the strain had no hemolytic phenotype, did not develop resistance to 19 commonly used antibiotics, had no cytotoxicity to Caco-2, and did not have acute toxic harm to mice. In summary, this study targeted isolated and screened a strain of Bacillus velezensis TS5 with high fiber-degrading ability and probiotic potency. This strain can be used as a potential probiotic for feeding microbial preparations for ruminants.

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. AIM: To construct and evaluate a preoperative diagnostic method to predict OCLNM in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. METHODS: A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA), and survival analysis. RESULTS: Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927), and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1, and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. CONCLUSION: The proposed MRI-based Resnet50 DL model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

Complete genome analysis of Bacillus velezensis TS5 and its potential as a probiotic strain in mice.

Introduction: In recent years, a large number of studies have shown that Bacillus velezensis has the potential as an animal feed additive, and its potential probiotic properties have been gradually explored. Methods: In this study, Illumina NovaSeq PE150 and Oxford Nanopore ONT sequencing platforms were used to sequence the genome of Bacillus velezensis TS5, a fiber-degrading strain isolated from Tibetan sheep. To further investigate the potential of B. velezensis TS5 as a probiotic strain, in vivo experiments were conducted using 40 five-week-old male specific pathogen-free C57BL/6J mice. The mice were randomly divided into four groups: high fiber diet control group (H group), high fiber diet probiotics group (HT group), low fiber diet control group (L group), and low fiber diet probiotics group (LT group). The H and HT groups were fed high-fiber diet (30%), while the L and LT groups were fed low-fiber diet (5%). The total bacteria amount in the vegetative forms of B. velezensis TS5 per mouse in the HT and LT groups was 1 × 109 CFU per day, mice in the H and L groups were given the same volume of sterile physiological saline daily by gavage, and the experiment period lasted for 8 weeks. Results: The complete genome sequencing results of B. velezensis TS5 showed that it contained 3,929,788 nucleotides with a GC content of 46.50%. The strain encoded 3,873 genes that partially related to stress resistance, adhesion, and antioxidants, as well as the production of secondary metabolites, digestive enzymes, and other beneficial nutrients. The genes of this bacterium were mainly involved in carbohydrate metabolism, amino acid metabolism, vitamin and cofactor metabolism, biological process, and molecular function, as revealed by KEGG and GO databases. The results of mouse tests showed that B. velezensis TS5 could improve intestinal digestive enzyme activity, liver antioxidant capacity, small intestine morphology, and cecum microbiota structure in mice. Conclusion: These findings confirmed the probiotic effects of B. velezensis TS5 isolated from Tibetan sheep feces and provided the theoretical basis for the clinical application and development of new feed additives.