Enhancing H2O2 Electrosynthesis at Industrial-Relevant Current in Acidic Media on Diatomic Cobalt Sites.

Electrocatalytic synthesis of hydrogen peroxide (H2O2) in acidic media is an efficient and eco-friendly approach to produce inherently stable H2O2, but limited by the lack of selective and stable catalysts under industrial-relevant current densities. Herein, we report a diatomic cobalt catalyst for two-electron oxygen reduction to efficiently produce H2O2 at 50-400 mA cm-2 in acid. Electrode kinetics study shows a >95% selectivity for two-electron oxygen reduction on the diatomic cobalt sites. In a flow cell device, a record-high production rate of 11.72 mol gcat-1 h-1 and exceptional long-term stability (100 h) are realized under high current densities. In situ spectroscopic studies and theoretical calculations reveal that introducing a second metal into the coordination sphere of the cobalt site can optimize the binding strength of key H2O2 intermediates due to the downshifted d-band center of cobalt. We also demonstrate the feasibility of processing municipal plastic wastes through decentralized H2O2 production.

Baicalin induces ferroptosis in oral squamous cell carcinoma by suppressing the activity of FTH1.

BACKGROUND: This study investigated the role of the ferroptosis-related gene FTH1 in oral squamous cell carcinoma (OSCC) and evaluated the therapeutic potential of baicalin in OSCC cell treatment. METHODS: A prognostic model was established by bioinformatic analysis, consisting of 12 ferroptosis related genes (FRGs), and FTH1 was selected as the most significantly up-regulated FRGs. The clinical correlation of FTH1 in OSCC samples was evaluated by both immunohistochemical and bioinformatic characterizations. The effects of FTH1 on migration, invasion, epithelial-mesenchymal transition (EMT) and proliferation were determined by wound healing assays, transwell assays, western blotting and 5'-ethynl 2'-deoxyuridine proliferation assays, respectively. The effects of FTH1 on ferroptosis were tested via ferroptosis markers and Mito Tracker staining. In addition, the therapeutic effects of baicalin on OSCC cells were confirmed using EMT, migration, invasion, proliferation and ferroptosis assays. RESULTS: The 12 FRGs were predictive of the prognosis for OSCC patients, and FTH1 expression was identified as significantly up-regulated in OSCC samples, which was highly associated with survival, immune cell infiltration and drug sensitivity. Moreover, knocking down FTH1 inhibited cell proliferation, EMT and invasive phenotypes, but induced ferroptosis in OSCC cells (Cal27 and SCC25). Furthermore, baicalin directly suppressed expression of FTH1 in OSCC cells, and effectively promoted ferroptosis and inhibited the proliferation as well as EMT by directly targeting FTH1. CONCLUSIONS: This study has demonstrated that FTH1 is a therapeutic target for OSCC treatment, and has provided evidence that baicalin offers a promising alternative for OSCC treatment.

Associations of perfluoroalkyl substances with metabolic-associated fatty liver disease and non-alcoholic fatty liver disease: NHANES 2017-2018.

OBJECTIVES: This study investigated the potential effects of perfluoroalkyl substance (PFAS) in serum on MAFLD, NAFLD, and liver fibrosis. METHODS: Our sample included 696 participants (≥ 18 years) from the 2017-2018 NHANES study with available serum PFASs, covariates, and outcomes. Using the first quartile of PFAS as the reference group, we used weighted binary logistic regression and multiple ordered logistic regression used to analyze the relationship between PFAS and MAFLD, NAFLD, and liver fibrosis and multiple ordinal logistic regression to investigate the relationship between PFAS and MAFLD, NAFLD, and liver fibrosis and calculated the odds ratio (OR) and 95% confidence interval for each chemical. Finally, stratified analysis and sensitivity analysis were performed according to gender, age, BMI, and serum cotinine concentration. RESULTS: A total of 696 study subjects were included, including 212 NAFLD patients (weighted 27.03%) and 253 MAFLD patients (weighted 32.65%). The quartile 2 of serum PFOA was positively correlated with MAFLD and NAFLD (MAFLD, OR 2.29, 95% CI 1.05-4.98; NAFLD, OR 2.37, 95% CI 1.03-5.47). PFAS were not significantly associated with liver fibrosis after adjusting for potential confounders in MAFLD and NAFLD. Stratified analysis showed that PFOA was strongly associated with MAFLD, NAFLD, and liver fibrosis in males and obese subjects. In women over 60 years old, PFHxS was also correlated with MAFLD, NAFLD, and liver fibrosis. CONCLUSION: The serum PFOA was positively associated with MAFLD and NAFLD in US adults. After stratified analysis, the serum PFHxS was correlated with MFALD, NAFLD, and liver fibrosis.

Protopanaxadiols Eliminate Behavioral Impairments and Mitochondrial Dysfunction in Parkinson's Disease Mice Model.

Currently, there are no effective therapies to cure Parkinson's disease (PD), which is the second most common neurodegenerative disease primarily characterized by motor dysfunction and degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc). Protopanaxadiols (PPDs), including 20 (R)- protopanaxadiol (R-PPD) and 20 (S)- protopanaxadiol (S-PPD), are main metabolites of ginsenosides. The role of ginsenosides in neurodegenerative diseases has been thoroughly studied, however, it is unknown whether PPDs can attenuate behavioral deficits and dopaminergic neuron injury in PD model mice to date. Here, we administered PPDs to MPTP-induced PD model mice and monitored the effects on behavior and dopaminergic neurons to investigate the effects of R-PPD and S-PPD against PD. Our results showed that R-PPD and S-PPD (at a dose of 20 mg/kg, i.g.) treatment alleviated MPTP (30 mg/kg, i.p.) induced behavioral deficits. Besides, R-PPD and S-PPD protected MPP+-induced neuron injury and mitochondrial dysfunction, and reduced the abnormal expression of Cyt C, Bax, caspase-3 and Bcl-2. These findings demonstrate that R-PPD and S-PPD were potentially useful to ameliorate PD.

R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut.

Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such as GPT4. This paper presents a novel method to enhance the explainability of transformer-based image classification models. Our method aims to improve trust in classification results and empower users to gain a deeper understanding of the model for downstream tasks by providing visualizations of class-specific maps. We introduce two modules: the "Relationship Weighted Out" and the "Cut" modules. The "Relationship Weighted Out" module focuses on extracting class-specific information from intermediate layers, enabling us to highlight relevant features. Additionally, the "Cut" module performs fine-grained feature decomposition, taking into account factors such as position, texture, and color. By integrating these modules, we generate dense class-specific visual explainability maps. We validate our method with extensive qualitative and quantitative experiments on the ImageNet dataset. Furthermore, we conduct a large number of experiments on the LRN dataset, which is specifically designed for automatic driving danger alerts, to evaluate the explainability of our method in scenarios with complex backgrounds. The results demonstrate a significant improvement over previous methods. Moreover, we conduct ablation experiments to validate the effectiveness of each module. Through these experiments, we are able to confirm the respective contributions of each module, thus solidifying the overall effectiveness of our proposed approach.

Accurate and Convenient Lung Cancer Diagnosis through Detection of Extracellular Vesicle Membrane Proteins via Förster Resonance Energy Transfer.

Tumor-derived extracellular vesicles (EVs) are promising to monitor early stage cancer. Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For this, we devised an EV membrane proteins detection system (EV-MPDS) based on Förster resonance energy transfer (FRET) signals between aptamer quantum dots and AIEgen dye, which eliminated the EV extraction and purification to conveniently diagnose lung cancer. In a cohort of 80 clinical samples, this system showed enhanced accuracy (100% versus 65%) and sensitivity (100% versus 55%) in cancer diagnosis as compared to the ELISA detection method. Improved accuracy of early screening (from 96.4% to 100%) was achieved by comprehensively profiling five biomarkers using a machine learning analysis system. FRET-based tumor EV-MPDS is thus an isolation-free, low-volume (1 µL), and highly accurate approach, providing the potential to aid lung cancer diagnosis and early screening.

Proanthocyanidins Ameliorate LPS-Inhibited Osteogenesis of PDLSCs by Restoring Lysine Lactylation.

Periodontitis is a bacteria-induced inflammatory disease characterized by the progressive destruction of periodontal supporting tissues. Periodontal ligament stem cells (PDLSCs) are capable of differentiating into osteoblasts, which is an important stem cell source for endogenous periodontal tissue regeneration. Lysine lactylation (Kla) is a novel post-translational modification of proteins that is recently thought to be associated with osteogenic differentiation. Here, we found that lactylation levels are reduced both in the periodontal tissue of rats with periodontitis and lipopolysaccharide (LPS)-stimulated human PDLSCs. Proanthocyanidins were able to promote the osteogenesis of inflamed PDLSCs by restoring lactylation levels. Mechanistically, proanthocyanidins increased lactate production and restored the lactylation levels of PDLSCs, which recovered osteogenesis of inflamed PDLSCs via the Wnt/ß-catenin pathway. These results provide evidence on how epigenetic regulation by pharmacological agents influence the osteogenic phenotype of stem cells and the process of periodontal tissue repair. Our current study highlights the valuable potential of natural product proanthocyanidins in the regenerative engineering of periodontal tissues.

Piezofluorochromism in Hierarchical Porous π-stacked Supermolecular Spring Frameworks from Aromatic Chiral Cages.

Piezochromic materials that exhibit pressure-dependent luminescence variations are attracting interest with wide potential applications in mechanical sensors, anticounterfeiting and storage devices. Crystalline porous materials (CPMs) have been widely studied in piezochromism for highly tunable luminescence. Nevertheless, reversible and high-contrast emission response with a wide pressure range is still challenging. Herein, the first example of hierarchical porous cage-based πOF (Cage-πOF-1) with spring structure was synthesized by using aromatic chiral cages as building blocks. Its elastic properties evaluated based on the bulk modulus (9.5 GPa) is softer than most reported CPMs and the collapse point (20.0 GPa) significantly exceeds ever reported CPMs. As smart materials, Cage-πOF-1 displays linear pressure-dependent emission and achieves a high-contrast emission difference up to 154 nm. Pressure-responsive limit is up to 16 GPa, outperforming the CPMs reported so far. Dedicated experiments and density functional theory (DFT) calculations illustrate that π-π interactions-dominated controllable structural shrinkage and porous-spring-structure-mediated elasticity is responsible for the outstanding piezofluorochromism.

Tailoring d-p Orbital Hybridization to Decipher the Essential Effects of Heteroatom Substitution on Redox Kinetics.

The heteroatom substitution is considered as a promising strategy for boosting the redox kinetics of transition metal compounds in hybrid supercapacitors (HSCs) although the dissimilar metal identification and essential mechanism that dominate the kinetics remain unclear. It is presented that d-p orbital hybridization between the metal and electrolyte ions can be utilized as a descriptor for understanding the redox kinetics. Herein, a series of Co, Fe and Cu heteroatoms are respectively introduced into Ni3Se4 cathodes, among them, only the moderate Co-substituted Ni3Se4 can hold the optimal d-p orbital hybridization resulted from the formed more unoccupied antibonding states π*. It inevitably enhances the interfacial charge transfer and ensures the balanced OH- adsorption-desorption to accelerate the redox kinetics validated by the lowest reaction barrier (0.59 eV, matching well with the theoretical calculations. Coupling with the lower OH- diffusion energy barrier, the prepared cathode delivers ultrahigh rate capability (~68.7% capacity retention even the current density increases by 200 times), and an assembled HSC also presents high energy/power density. This work establishes the principles for determining heteroatoms and deciphers the underlying effects of the heteroatom substitution on improving redox kinetics and the rate performance of battery-type electrodes from a novel perspective of orbital-scale manipulation.

General Synthesis of a Diatomic Catalyst Library via a Macrocyclic Precursor-Mediated Approach.

Heterogeneous catalysts containing diatomic sites are often hypothesized to have distinctive reactivity due to synergistic effects, but there are limited approaches that enable the convenient production of diatomic catalysts (DACs) with diverse metal combinations. Here, we present a general synthetic strategy for constructing a DAC library across a wide spectrum of homonuclear (Fe2, Co2, Ni2, Cu2, Mn2, and Pd2) and heteronuclear (Fe-Cu, Fe-Ni, Cu-Mn, and Cu-Co) bimetal centers. This strategy is based on an encapsulation-pyrolysis approach, wherein a porous material-encapsulated macrocyclic complex mediates the structure of DACs by preserving the main body of the molecular framework during pyrolysis. We take the oxygen reduction reaction (ORR) as an example to show that this DAC library can provide great opportunities for electrocatalyst development by unlocking an unconventional reaction pathway. Among all investigated sites, Fe-Cu diatomic sites possess exceptional high durability for ORR because the Fe-Cu pairs can steer elementary steps in the catalytic cycle and suppress the troublesome Fenton-like reactions.

MicroRNA-19b-3p dysfunction of mesenchymal stem cell-derived exosomes from patients with abdominal aortic aneurysm impairs therapeutic efficacy.

Senescence of vascular smooth muscle cells (VSMCs) contributes to the formation of abdominal aortic aneurysm (AAA). Although mesenchymal stem cell exosomes (MSC-EXO) have been confirmed to restrict the development of AAA, their biological activity depends largely on the physiological state of the MSCs. This study aimed to compare the effects of adipose-derived MSC-EXO from healthy donors (HMEXO) and AAA patients (AMEXO) on senescence of VSMCs in AAA and explore the underlying mechanisms. An ApoE-/- mouse model of AAA was used to investigate the therapeutic effects of HMEXO, AMEXO or miR-19b-3p-AMEXO on AAA development. This in vitro model of AAA was established by treating VSMCs with Ang II (Angiotensin II). The senescence of VSMCs was determined by senescence-associated ß-galactosidase (SA-ß-gal) staining. The morphology of mitochondria in VSMCs was examined by MitoTracker staining. HMEXO exhibited superior capacity compared with AMEXO to inhibit VSMC senescence and attenuate AAA formation in Ang II-treated ApoE-/- mice. In vitro, both AMEXO and HMEXO inhibited Ang II-induced VSMC senescence via downregulation of mitochondrial fission. Notably, compared with HMEXO, the ability of AMEXO to inhibit VSMC senescence was significantly decreased. miRNA sequencing and the expression of miR-19b-3p was significantly decreased in AMEXO compared with HMEXO. Luciferase assay suggested that MST4 (Mammalian sterile-20-like kinase 4) is a potential target of miR-19b-3p. Mechanistically, miR-19b-3p in HMEXO ameliorated VSMC senescence by inhibiting mitochondrial fission via regulation of the MST4/ERK/Drp1 signaling pathway. Overexpression of miR-19b-3p in AMEXO improved their beneficial effect on AAA formation. Our study reveals that MSC-exosomal miR-19b-3p exerts protective effects against Ang II-induced AAA and VSMC senescence via regulation of the MST4/ERK/Drp1 pathway. The pathological state of AAA patients alters the miRNA components of AMEXO and impairs their therapeutic benefits.

Framework for Generation and Removal of Multiple Types of Adverse Weather from Driving Scene Images.

Weather variation in the distribution of image data can cause a decline in the performance of existing visual algorithms during evaluation. Adding additional samples of target domain to training data or using pre-trained image restoration methods such as de-hazing, de-raining, and de-snowing, to improve the quality of input images are two promising solutions. In this work, we propose Multiple Weather Translation GAN (MWTG), a CycleGAN-based, dual-purpose framework that simultaneously learns weather generation and its removal from image data. MWTG consists of four GANs constrained using cycle consistency that carry out domain translation tasks between hazy, rainy, snowy, and clear weather, using an asymmetric approach. To increase network capacity, we employ a spatial feature transform (SFT) layer to fuse the features extracted from the weather layer, which contains high-level domain information from the previous generators. Further, we collect an unpaired, real-world driving dataset recorded under various weather conditions called Realistic Driving Scenes under Bad Weather (RDSBW). We qualitatively and quantitatively evaluate MWTG using the RDSBW and the variation of Cityscapes that synthesize weather effects, eg., FoggyCityscape. Our experimental results suggest that MWTG can generate realistic weather in clear images and also accurately remove noise from weather images. Furthermore, the SOTA pedestrian detector ASCP is shown to achieve an impressive gain in detection precision after image restoration using the proposed MWTG method.

Controllable Unsupervised Snow Synthesis by Latent Style Space Manipulation.

In the field of intelligent vehicle technology, there is a high dependence on images captured under challenging conditions to develop robust perception algorithms. However, acquiring these images can be both time-consuming and dangerous. To address this issue, unpaired image-to-image translation models offer a solution by synthesizing samples of the desired domain, thus eliminating the reliance on ground truth supervision. However, the current methods predominantly focus on single projections rather than multiple solutions, not to mention controlling the direction of generation, which creates a scope for enhancement. In this study, we propose a generative adversarial network (GAN)-based model, which incorporates both a style encoder and a content encoder, specifically designed to extract relevant information from an image. Further, we employ a decoder to reconstruct an image using these encoded features, while ensuring that the generated output remains within a permissible range by applying a self-regression module to constrain the style latent space. By modifying the hyperparameters, we can generate controllable outputs with specific style codes. We evaluate the performance of our model by generating snow scenes on the Cityscapes and the EuroCity Persons datasets. The results reveal the effectiveness of our proposed methodology, thereby reinforcing the benefits of our approach in the ongoing evolution of intelligent vehicle technology.

L-DIG: A GAN-Based Method for LiDAR Point Cloud Processing under Snow Driving Conditions.

LiDAR point clouds are significantly impacted by snow in driving scenarios, introducing scattered noise points and phantom objects, thereby compromising the perception capabilities of autonomous driving systems. Current effective methods for removing snow from point clouds largely rely on outlier filters, which mechanically eliminate isolated points. This research proposes a novel translation model for LiDAR point clouds, the 'L-DIG' (LiDAR depth images GAN), built upon refined generative adversarial networks (GANs). This model not only has the capacity to reduce snow noise from point clouds, but it also can artificially synthesize snow points onto clear data. The model is trained using depth image representations of point clouds derived from unpaired datasets, complemented by customized loss functions for depth images to ensure scale and structure consistencies. To amplify the efficacy of snow capture, particularly in the region surrounding the ego vehicle, we have developed a pixel-attention discriminator that operates without downsampling convolutional layers. Concurrently, the other discriminator equipped with two-step downsampling convolutional layers has been engineered to effectively handle snow clusters. This dual-discriminator approach ensures robust and comprehensive performance in tackling diverse snow conditions. The proposed model displays a superior ability to capture snow and object features within LiDAR point clouds. A 3D clustering algorithm is employed to adaptively evaluate different levels of snow conditions, including scattered snowfall and snow swirls. Experimental findings demonstrate an evident de-snowing effect, and the ability to synthesize snow effects.

THBS1-Mediated Degradation of Collagen via the PI3K/AKT Pathway Facilitates the Metastasis and Poor Prognosis of OSCC.

Oral squamous cell carcinoma (OSCC) is a prevalent form of malignant tumor, characterized by a persistently high incidence and mortality rate. The extracellular matrix (ECM) plays a crucial role in the initiation, progression, and diverse biological behaviors of OSCC, facilitated by mechanisms such as providing structural support, promoting cell migration and invasion, regulating cell morphology, and modulating signal transduction. This study investigated the involvement of ECM-related genes, particularly THBS1, in the prognosis and cellular behavior of OSCC. The analysis of ECM-related gene data from OSCC samples identified 165 differentially expressed genes forming two clusters with distinct prognostic outcomes. Seventeen ECM-related genes showed a significant correlation with survival. Experimental methods were employed to demonstrate the impact of THBS1 on proliferation, migration, invasion, and ECM degradation in OSCC cells. A risk-prediction model utilizing four differentially prognostic genes demonstrated significant predictive value in overall survival. THBS1 exhibited enrichment of the PI3K/AKT pathway, indicating its potential role in modulating OSCC. In conclusion, this study observed and verified that ECM-related genes, particularly THBS1, have the potential to influence the prognosis, biological behavior, and immunotherapy of OSCC. These findings hold significant implications for enhancing survival outcomes and providing guidance for precise treatment of OSCC.

Measurement of 7-dehydrocholesterol and cholesterol in hair can be used in the diagnosis of Smith-Lemli-Opitz syndrome.

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50-4000 ng/mg and 30-6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.

Suncheonosides E-M and Benzothioate Derivatives from the Marine-Derived Streptomyces sp. ZSN77.

Thirteen new compounds, including suncheonosides E-M (1-9), four benzothioate derivatives (10-13), and one known compound (14), were identified from the marine-derived Streptomyces sp. ZSN77. Suncheonosides E-M incorporate ß-d-glucose, while the reported suncheonosides (A-D) incorporate only l-rhamnose. All of the structures were determined by extensive analysis of NMR spectroscopic and HRESIMS data. Bioactivity evaluation of these compounds showed that 6 had significant activity against PC3 cells with an IC50 value of 4.1 ± 0.1 µM, while compounds 12 and 14 exhibited cytotoxicity against HCT116 cells with IC50 values of 7.3 ± 0.4 and 3.9 ± 0.3 µM, respectively. In addition, compounds 1, 2, 6, 10, and 14 displayed potent in vivo anti-inflammatory efficacy with inhibition of NO production in a dose-dependent manner.

A reliable tool for detecting 7-dehydrocholesterol and cholesterol in human plasma and its use in diagnosis of Smith-Lemli-Opitz syndrome.

BACKGROUND: Smith-Lemli-Opitz syndrome is a birth defect caused by the deficiency of 7-dehydrocholesterol reductase in cholesterol biosynthesis pathway, which leads to accumulation of 7-dehydrocholesterol and reduction of cholesterol in body fluids. To effectively diagnose Smith-Lemli-Opitz syndrome and monitor therapy, a reliable method for simultaneous detection of 7-dehydrocholesterol and cholesterol is needed. METHODS: In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), 50 µL of human plasma were hydrolyzed at 70℃ for 40 min with 1 M potassium hydroxide in 90% ethanol, and then 7-dehydrocholesterol and cholesterol were extracted by 600 µL of n-hexane for three times. After microwave-assisted derivatization with 70 µL of N,O-bis(trimethylsilyl)trifluoroacetamide at 460 W for 3 min, the analytes were measured by gas chromatography-mass spectrometry. RESULTS: The limits of detection were 100 ng/mL for 7-dehydrocholesterol and 300 ng/mL for cholesterol. Good linearity was obtained in the range of 1-600 µg/mL for 7-dehydrocholesterol and 10-600 µg/mL for cholesterol, which completely covered the biochemical levels of Smith-Lemli-Opitz syndrome patients that have been reported. CONCLUSION: A time-saving and accurate gas chromatography with mass spectrometry based method was developed for the determination of 7-dehydrocholesterol and cholesterol in human plasma, which also serves as a useful tool for Smith-Lemli-Opitz syndrome diagnosis, treatment, and research.

Anterolateral thigh flaps in closing large abdominal wall defect after the resection of mucinous adenocarcinoma: a case report.

BACKGROUND: It is a big challenge to repair a large abdominal wall defect after tumor resection, and en bloc resection with vascularized tissue reconstruction might be an alternative to achieve an improved survival for abdominal wall tumors. CASE PRESENTATION: A 45-year-old woman presented with a 1-year history of persistent abdominal pain of the right lower quadrant and a mass with dermal ulceration. An enhanced computed tomography scan and biopsy of the mass were performed to achieve the definite diagnosis of abdominal mucinous adenocarcinoma. After four courses of "FOLFOX" chemotherapy, the tumor grew to 6 × 5 cm during preoperative examination. Thereafter, we removed the tumor and involved tissues and organs and repaired the sizeable abdominal wall defect used by biological meshes and vascularized anterolateral thigh flaps. The patient suffered green drainage of 450 ml in the abdominal cavity and intestinal anastomotic fistula, for which she readmitted and recovered afterward. CONCLUSIONS: Biological mesh combined with vascularized anterolateral thigh flaps could effectively repair the large abdominal wall defect and restore the biological function of the abdominal wall.

[Sleep patterns of infants and young children and their association with breastfeeding: a study based on K-means clustering]. / 基于K-meansèšç±»åˆ†æžçš„å©´å¹¼å„¿ç¡çœ æ¨¡å¼åŠä¸Žæ¯ä¹³å–‚å »å ³ç³»çš„ç ”ç©¶.

OBJECTIVES: To investigate the sleep patterns and characteristics of infants and young children and the association between sleep patterns and breastfeeding. METHODS: A general information questionnaire, Brief Infant Sleep Questionnaire (BISQ), and a questionnaire on feeding were used to investigate the sleep quality and feeding patterns of 1 148 infants and young children aged 7-35 months. The K-means clustering method was used to identify sleep patterns and characteristics. A multivariate logistic regression analysis was used to investigate the association between sleep patterns and breastfeeding. RESULTS: Three typical sleep patterns were identified for the 1 148 infants and young children aged 7-35 months: early bedtime and long sleep time; short sleep latency and moderate sleep time; late bedtime, prolonged sleep latency, and insufficient sleep time. The third pattern showed sleep disorders. The multivariate logistic regression analysis showed that compared with formula feeding, exclusive breastfeeding within 6 months after birth reduced the risk of sleep disorder patterns by 69% (OR=0.31, 95%CI: 0.11-0.81). The risk of sleep disorder patterns was reduced by 40% (OR=0.60, 95%CI: 0.38-0.96) in the infants receiving breastfeeding for 4-6 months compared with those receiving breastfeeding for 1-3 months. CONCLUSIONS: There are different sleep patterns in infants and young children, and breastfeeding can reduce the development of sleep disorder patterns.