Resolving Ultraviolet-Visible Spectra for Complex Dissolved Mixtures of Multitudinous Organic Matters in Aerosols.

Light-absorbing organic aerosols, referred to as brown carbon (BrC), play a vital role in the global climate and air quality. Due to the complexity of BrC chromophores, the identified absorbing substances in the ambient atmosphere are very limited. However, without comprehensive knowledge of the complex absorbing compounds in BrC, our understanding of its sources, formation, and evolution mechanisms remains superficial, leading to great uncertainty in climatic and atmospheric models. To address this gap, we developed a constrained non-negative matrix factorization (NMF) model to resolve the individual ultraviolet-visible spectrum for each substance in dissolved organic aerosols, with the power of ultrahigh-performance liquid chromatography-diode array detector-ultrahigh-resolution mass spectrometry (UHPLC-DAD-UHRMS). The resolved spectra were validated by selected standard substances and validation samples. Approximately 40,000 light-absorbing substances were recognized at the MS1 level. It turns out that BrC is composed of a vast number of substances rather than a few prominent chromophores in the urban atmosphere. Previous understanding of the absorbing feature of BrC based on a few identified compounds could be biased. Weak-absorbing substances missed previously play an important role in BrC absorption when they are integrated due to their overwhelming number. This model brings the property exploration of complex dissolved organic mixtures to a molecular level, laying a foundation for identifying potentially significant compositions and obtaining a comprehensive chemical picture.

Utilization of Polycyclic Aromatic Solid Additives for Morphology and Thermal Stability Enhancement in Photoactive Layers of Organic Solar Cells.

Volatile solid additives have emerged as a promising strategy for enhancing film morphology and promoting the power conversion efficiency (PCE) of organic solar cells (OSCs). Herein, a series of novel polycyclic aromatic additives with analogous chemical structures, including fluorene (FL), dibenzothiophene (DBT), and dibenzofuran (DBF) derived from crude oils, are presented and incorporated into OSCs. All these additives exhibit strong interactions with the electron-deficient terminal groups of L8-BO within the bulk-heterojunction OSCs. Moreover, they demonstrate significant sublimation during thermal annealing, leading to increase free volumes for the rearrangement and recrystallization of L8-BO. This phenomenon leads to an improved film morphology and an elevated glass-transition temperature of the photoactive layers. Consequently, the PCE of the PM6:L8-BO blend has been boosted from 16.60% to 18.60% with 40 wt% DBF additives, with a champion PCE of 19.11% achieved for ternary PM6:L8-BO:BTP-eC9 OSCs. Furthermore, the prolonged shelf and thermal stability have been observed in OSCs with these additives. This study emphasizes the synergic effect of volatile solid additives on the performance and thermal stability of OSCs, highlighting their potential for advancing the field of photovoltaics.

Unraveling the Significance of MET Focal Amplification in Lung Cancer: Integrative NGS, FISH, and IHC Investigation.

MET amplification (METamp) represents a promising therapeutic target in non-small cell lung cancer, but no consensus has been established to identify METamp-dependent tumors that could potentially benefit from MET inhibitors. In this study, an analysis of MET amplification/overexpression status was performed in a retrospectively recruited cohort comprising 231 patients with non-small cell lung cancer from Shanghai Chest Hospital (SCH cohort) using 3 methods: fluorescence in situ hybridization (FISH), hybrid capture-based next-generation sequencing, and immunohistochemistry for c-MET and phospho-MET. The SCH cohort included 130 cases known to be METamp positive by FISH and 101 negative controls. The clinical relevance of these approaches in predicting the efficacy of MET inhibitors was evaluated. Additionally, next-generation sequencing data from another 2 cohorts including 22,010 lung cancer cases were utilized to examine the biological characteristics of different METamp subtypes. Of the 231 cases, 145 showed MET amplification/overexpression using at least 1 method, whereas only half of them could be identified by all 3 methods. METamp can occur as focal amplification or polysomy. Our study revealed that the inconsistency between next-generation sequencing and FISH primarily occurred in the polysomy subtype. Further investigations indicated that compared with polysomy, focal amplification correlated with fewer co-occurring driver mutations, higher protein expressions of c-MET and phospho-MET, and higher incidence in acquired resistance than in de novo setting. Moreover, patients with focal amplification presented a more robust response to MET inhibitors compared with those with polysomy. Notably, a strong correlation was observed between focal amplification and programmed cell death ligand-1 expression, indicating potential therapeutic implications with combined MET inhibitor and immunotherapy for patients with both alterations. Our findings provide insights into the molecular complexity and clinical relevance of METamp in lung cancer, highlighting the role of MET focal amplification as an oncogenic driver and its feasibility as a primary biomarker to further investigate the clinical activity of MET inhibitors in future studies.

Altered Dynamics of Brain Spontaneous Activity and Functional Networks Associated With Cognitive Impairment in Patients With Type 2 Diabetes.

BACKGROUND: Cognitive impairment is increasingly recognized as an important comorbidity and complication of type 2 diabetes (T2D), affecting patients' quality of life and diabetes management. Dynamic brain activity indicators can reflect changes in key neural activity patterns of cognition and behavior. PURPOSE: To investigate dynamic functional connectivity (DFC) changes and spontaneous brain activity based on resting-state functional magnetic resonance imaging (rs-fMRI) in patients with T2D, exploring their correlations with clinical features. STUDY TYPE: Retrospective. SUBJECTS: Forty-five healthy controls (HCs) (22 males and 23 females) and 102 patients with T2D (57 males and 45 females). FIELD STRENGTH/SEQUENCE: 3.0 T/T1-weighted imaging and rs-fMRI with gradient-echo planar imaging sequence. ASSESSMENT: Functional networks were created using independent component analysis. DFC states were determined using sliding window approach and k-means clustering. Spontaneous brain activity was assessed using dynamic regional homogeneity (dReHo) variability. STATISTICAL TESTS: One-way analysis of variance and post hoc analysis were used to compare the essential information including demographics, clinical data, and features of DFC and dReHo among groups. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve. P-values <0.05 were taken to indicate statistical significance. RESULTS: T2D group had significantly decreased mean dwell time and fractional windows in state 4 compared to HC. T2D with mild cognitive impairment showed significantly increased dReHo variability in left superior occipital gyrus compared to T2D with normal cognition. Mean dwell time and number of fractional windows of state 4 both showed significant positive correlations with the Montreal cognitive assessment scores (r = 0.309; r = 0.308, respectively) and the coefficient of variation of dReHo was significantly positively correlated with high-density lipoprotein cholesterol (r = 0.266). The integrated index had an area under the curve of 0.693 (95% confidence interval = 0.592-0.794). DATA CONCLUSION: Differences in DFC and dynamic characteristic of spontaneous brain activity associated with T2D-related functional impairment may serve as indicators for predicting symptom progression and assessing cognitive dysfunction. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer.

OBJECTIVE: The genome-wide profiling of 5-hydroxymethylcytosines (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for various diseases. The purpose of this study was to investigate 5hmC signals in serum cfDNA and identify novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5hmC profiles in cfDNA reflect the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. Moreover, we sought to identify predictors that would better stratify outcomes for women with intermediate-sensitive HGSOC. METHODS: Women diagnosed with HGSOC and known platinum sensitivity status were selected for this study. Nano-hmC-Seal was performed on cfDNA isolated from archived serum samples, and differential 5hmC features were identified using DESeq2 to establish a model predictive of chemoresistance. RESULTS: A multivariate model consisting of three features (preoperative CA-125, largest residual implant after surgery, 5hmC level of OSGEPL), stratified samples from intermediate sensitive, chemo-naive women diagnosed with HGSOC into chemotherapy-resistant- and sensitive-like strata with a significant difference in overall survival (OS). Independent analysis of The Cancer Genome Atlas data further confirmed that high OSGEPL1 expression is a favorable prognostic factor for HGSOC. CONCLUSIONS: We have developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC modified gene, OSGEPL1, that predicted response to platinum-based chemotherapy in intermediate-sensitive HGSOC. Our multivariate model applies to chemo-naïve samples regardless if the patint was treated with adjuvant or neoadjuvant chemotherapy. These results merit further investigation of the predictive capability of our model in larger cohorts.

Whole-genome sequences restore the original classification of dabbling ducks (genus Anas).

Anas, is a genus of dabbling ducks and encompasses a considerable number of species, among which some are the progenitors of domestic ducks. However, the taxonomic position of the Anas genus remains uncertain because several of its species, initially categorized as Anas based on morphological characteristics, were subsequently reclassified and grouped with the South American genus Tachyeres, primarily based on analysis of their mitochondrial gene sequences. Here, we constructed a phylogenetic tree using nine of our recently assembled Anas genomes, two Tachyeres genomes, and one Cairina genome that are publicly available. The results showed that the Northern shoveler (Anas clypeata) and Baikal teal (Anas formosa) clustered with the other Anas species at the whole-genome level rather than with the Steamer ducks (genus Tachyeres). Therefore, we propose to restore the original classification of the Anas genus, which includes the Northern shoveler and Baikal teal species, 47 species in total. Moreover, our study unveiled extensive incomplete lineage sorting and an ancient introgression event from Tachyeres to Anas, which has led to notable phylogenetic incongruence within the Anas genome. This ancient introgression event not only supports the theory that Anas originated in South America but also that it played a significant role in shaping the evolutionary trajectory of Anas, including the domestic duck.

Bioremediation of 2,4,6-trichlorophenol by extracellular enzymes of white rot fungi immobilized with sodium alginate/hydroxyapatite/chitosan microspheres.

Hydroxyapatite, a calcium phosphate biomass material known for its excellent biocompatibility, holds promising applications in water, soil, and air treatment. Sodium alginate/hydroxyapatite/chitosan (SA-HA-CS) microspheres were synthesized by cross-linking sodium alginate with calcium chloride. These microspheres were carriers for immobilizing extracellular crude enzymes from white rot fungi through adsorption, facilitating the degradation of 2,4,6-trichlorophenol (2,4,6-TCP) in water and soil. At 50 °C, the immobilized enzyme retained 87.2% of its maximum activity, while the free enzyme activity dropped to 68.86%. Furthermore, the immobilized enzyme maintained 68.09% of its maximum activity at pH 7, surpassing the 51.16% observed for the free enzyme. Under optimal conditions (pH 5, 24 h), the immobilized enzymes demonstrated a remarkable 94.7% removal rate for 160 mg/L 2,4,6-TCP, outperforming the 62.1% achieved by free crude enzymes. The degradation of 2,4,6-TCP by immobilized and free enzymes adhered to quasi-first-order degradation kinetics. Based on LC-MS, the plausible biodegradation mechanism and reaction pathway of 2,4,6-TCP were proposed, with the primary degradation product identified as 1,2,4-trihydroxybenzene. The immobilized enzyme effectively removed 72.9% of 2,4,6-TCP from the soil within 24 h. The degradation efficiency of the immobilized enzyme varied among different soil types, exhibiting a negative correlation with soil organic matter content. These findings offer valuable insights for advancing the application of immobilized extracellular crude enzymes in 2,4,6-TCP remediation.

Bioremediation of PAHs-contaminated site in a full-scale biopiling system with immobilized enzymes: Removal efficiency and microbial communities.

Bioremediation of PAHs-contaminated soil by immobilized enzymes is a promising technology. Nevertheless, the practical implementation of highly efficient enzymatic remediation remains confined to laboratory settings, with limited experience in full-scale applications. In this study, the extracellular enzymes from white rot fungi are fully applied to treat sites contaminated with PAHs by combining a new hydrogel microenvironment and a biopiling system. The full-scale project was conducted on silty loam soil contaminated with PAHs. In line with China's guidelines for construction land, 7 out of the 12 PAHs identified are considered to be a threat to the soil quality of construction sites, with benzo[a]pyrene levels reaching 1.50 mg kg-1, surpassing the acceptable limit of 0.55 mg kg-1 for the first type of land. After 7 days of remediation, the benzo[a]pyrene level decreased from 1.50 mg kg-1 to 0.51 mg kg-1, reaching the remediation standard of Class I screening values, with a removal rate of 66%. Microbiomes were utilized to assess the microbial biodiversity and structure analyses for PAHs biodegradation. The remediation enhanced the abundance of dominant bacterium (Marinobacter, Pseudomonas, and Truepera) and fugin (Thielavia, Neocosmospora, and Scedosporium). The research offers further insights into the exploration of soil remediation on the full-scale of the immobilized enzyme and biopiling technology.

Safeguarding healthcare professionals from sexual harassment in the workplace: urgent need for effective training and education.

Sexual harassment (SH) is a particularly harmful type of harassment that can inflict lasting psychological harm on victims. Within the healthcare sector, it negatively impacts teamwork, communication, and potentially compromises patient care. While concerns about workplace SH, including in healthcare, are long-standing, the #MeToo movement has brought renewed scrutiny to this issue since late 2017. Despite increased awareness, evidence suggests that SH remains prevalent in healthcare settings and shows no signs of decline over time. Therefore, there is an urgent need for effective training and intervention measures to enhance the identification of potential sexually offensive behaviors, thus fostering a work environment characterized by respect and inclusivity.

Fertility preservation in males with cancer of trends, region development, and efficacy in mainland China from 16 regions Chinese sperm banks.

PURPOSE: Male cancer survivors experience confusion about fertility following cancer treatment. The aims of this study were to evaluate survivors' semen quality in different tumor type groups in China and to analyze the current situation and challenges of male cancer patients with sperm cryopreservation. METHODS: This was a multicenter retrospective study of male patients with cancer who underwent sperm cryopreservation in 16 regions of the national sperm banks over an 11-year period from 2010 to 2020. RESULTS: The number of male cancer patients with sperm cryopreservation showed an overall upward trend. The development of male cancer fertility preservation (FP) in the eastern, central, and western regions of Chinese displayed imbalance. There are seven tumor types for sperm preservation in the top incidence ten tumor types, including lymphoma, leukemia, nasopharyngeal carcinoma, sarcoma, thyroid cancer, and brain tumor. Moreover, nasopharyngeal carcinoma is a high incidence rate in China, which is related to high sperm preservation rate, different from other countries. The most percentage of males receiving sperm cryopreservation in the testicular cancers (15-39 years old) of China in 2020 was 5.55%, 1.29% in the lymphoma, and 0.39% in the leukemia. According to the type of cancer, a statistically significant lower pre-sperm density, total sperm output, and post-sperm density was observed in testicular cancers. It is worth noting that the prevalence of azoospermia 22.2% in leukemia patients attribute to urgent treatment before sperm cryopreservation. Disposition of cryopreserved sperm categories included continued storage (47.2%), discarded (9%), death (0.9%), and use (3.7%). CONCLUSION: This study provides the first comprehensive national statistical census and review of fertility preservation in male cancer patients with respect to trends, prevalence, and cancer types. The development of male cancer fertility preservation in China is imbalanced and percentage of males receiving sperm cryopreservation in the adolescent and young adult cancers was low. Sixteen human sperm banks from China analyze current problems and challenges, and then prioritize steps toward the achievement of the FP strategy framework for Healthy China 2030.

Real-Time Ferrogram Segmentation of Wear Debris Using Multi-Level Feature Reused Unet.

The real-time monitoring and fault diagnosis of modern machinery and equipment impose higher demands on equipment maintenance, with the extraction of morphological characteristics of wear debris in lubricating oil emerging as a critical approach for real-time monitoring of wear, holding significant importance in the field. The online visual ferrograph (OLVF) technique serves as a representative method in this study. Various semantic segmentation approaches, such as DeepLabV3+, PSPNet, Segformer, Unet, and other models, are employed to process the oil wear particle image for conducting comparative experiments. In order to accurately segment the minute wear debris in oil abrasive images and mitigate the influence of reflection and bubbles, we propose a multi-level feature reused Unet (MFR Unet) that enhances the residual link strategy of Unet for improved identification of tiny wear debris in ferrograms, leading to superior segmentation results.

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction.

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R2) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

In-situ methane enrichment in anaerobic digestion of food waste slurry by nano zero-valent iron: Long-term performance and microbial community succession.

In this work, nano zero-valent iron (nZVI) was added to a lab-scale continuous stirring tank reactor (CSTR) for food waste slurry treatment, and the effect of dosing rate and dosage of nZVI were attempted to be changed. The results showed that anaerobic digestion (AD) efficiency and biomethanation stability were optimum under the daily dosing and dosage of 0.48 g/gTCOD. The average daily methane (CH4) yield reached 495.38 mL/gTCOD, which was 43.65% higher than that at control stage, and the maximum CH4 content reached 95%. However, under single dosing rate conditions, high nZVI concentrations caused microbial cell rupture and loosely bound extracellular polymeric substances (LB-EPS) precipitation degradation. The daily dosing rate promoted the hydrogenotrophic methanogenesis pathway, and the activity of coenzyme F420 increased by 400.29%. The microbial analysis indicated that daily addition of nZVI could promote the growth of acid-producing bacteria (Firmicutes and Bacteroidetes) and methanogens (Methanothrix).

Enrichment of Total Flavonoids and Licochalcone A from Glycyrrhiza inflata Bat. Residue Based on a Combined Membrane-Macroporous Resin Process and a Quality-Control Study.

Glycyrrhiza inflata Bat. produces a lot of licorice waste after water extraction, which also retains abundant total flavonoids (TFs) and licochalcone A. However, licorice residue is often wasted due to the lack of good utilization of resources in practical applications. This study first screened the optimal membrane pore size and resin type and then explored the mechanism and conditions of the adsorption of TFs on the resin. Then, different combinations and sequences of membrane and macroporous resin (MR) methods were investigated. It was found that using the membrane method for initial purification, followed by the MR method for further purification, yielded the best purification results. Next, response surface methodology was utilized to investigate the resin's dynamic desorption conditions for TFs. Finally, the TF purity increased from 32.9% to 78.2% (2.38-fold) after purification by a combined membrane-MR process; the purity of licochalcone A increased from 11.63 mg·g-1 to 22.70 mg·g-1 (1.95-fold). This study verified the feasibility of enriching TFs and licochalcone A from licorice residue using a membrane-MR coupling method. In addition, a quality-control method was established using a fingerprinting method on the basis of ultrahigh-performance liquid chromatography (UPLC) to ensure the stability of the enrichment process.

Enhanced biodegradation of benzo[a]pyrene with Trametes versicolor stimulated by citric acid.

Polycyclic aromatic hydrocarbons (PAHs) are a class of persistent organic pollutants with carcinogenic, mutagenic and teratogenic effects. The white-rot fungi in the fungal group have significant degradation ability for high molecular weight organic pollutants. However, exogenous fungi are easily antagonized by indigenous microorganisms. Low molecular weight organic acids, a small molecular organic matter secreted by plants, can provide carbon sources for soil microorganisms. Combining organic acids with white rot fungi may improve the nutritional environment of fungi. In this study, immobilized Trametes versicolor was used to degrade benzo[a]pyrene in soil, and its effect on removing benzo[a]pyrene in soil mediated by different low molecular weight organic acids was investigated. The results showed that when the degradation was 35 days, the removal effect of the experimental group with citric acid was the best, reaching 43.7%. The degradation effect of Trametes versicolor on benzo[a]pyrene was further investigated in the liquid medium when citric acid was added, and the effects of citric acid on the biomass, extracellular protein concentration and laccase activity of Trametes versicolor were investigated by controlling different concentrations of citric acid. In general, citric acid can act as a carbon source for Trametes versicolor and promote its extracellular protein secretion and laccase activity, thereby accelerating the mineralization of benzo[a]pyrene by Trametes versicolor. Therefore, citric acid can be used as a biostimulant in the remediation of PAHs contaminated soil with Trametes versicolor.

Ethylenedioxythiophene-Based Small Molecular Donor with Multiple Conformation Locks for Organic Solar Cells with Efficiency of 19.3 .

Ternary organic solar cells (T-OSCs) represent an efficient strategy for enhancing the performance of OSCs. Presently, the majority of high-performance T-OSCs incorporates well-established Y-acceptors or donor polymers as the third component. In this study, a novel class of conjugated small molecules has been introduced as the third component, demonstrating exceptional photovoltaic performance in T-OSCs. This innovative molecule comprises ethylenedioxythiophene (EDOT) bridge and 3-ethylrhodanine as the end group, with the EDOT unit facilitating the creation of multiple conformation locks. Consequently, the EDOT-based molecule exhibits two-dimensional charge transport, distinguishing it from the thiophene-bridged small molecule, which displays fewer conformation locks and provides one-dimensional charge transport. Furthermore, the robust electron-donating nature of EDOT imparts the small molecule with cascade energy levels relative to the electron donor and acceptor. As a result, OSCs incorporating the EDOT-based small molecule as the third component demonstrate enhanced mobilities, yielding a remarkable efficiency of 19.3 %, surpassing the efficiency of 18.7 % observed for OSCs incorporating thiophene-based small molecule as the third component. The investigations in this study underscore the excellence of EDOT as a building block for constructing conjugated materials with multiple conformation locks and high charge carrier mobilities, thereby contributing to elevated photovoltaic performance in OSCs.

DOT1L promotes expression of CD44 through the Wnt/ß-catenin signaling pathway in early gastric carcinoma.

To assess telomere silencing 1-like (DOTIL) gene expression within gastric cancer (GC) tissues as well as its function of promoting cancer stem cell (CSC)-mediated epithelial-mesenchymal switching, tissue samples from 8 patients each in 3 stages (normal, low-grade intraepithelial neoplasia (LGIN), as well as early gastric carcinoma (EGC)) were collected for whole-exome sequencing, which revealed differentially expressed genes (DEGs). The DEGs and their prognostic value were verified through TCGA and GTEx analyses. We also verified the role of DOT1L in EGC development. We collected samples from three patients each with LGIN and EGC for single-cell sequencing. We conducted single-cell transcriptomic analysis, DEG analysis, cell‒cell interaction analysis, and pseudotime analysis using R language. Sites and levels of DOT1L, CD44 and DOT1L expression were verified by IF. We found 703 deleterious mutation sites in the LGIN group and 389 deleterious mutation sites in the EGC group. The LGIN as well as EGC categories exhibited increased levels of DOT1L expression compared to the standard category (P<0.05) in TCGA and GTEx. DOT1L also correlated significantly with TMB (P=8.45E-06), MSI (P=0.001), and tumor proliferation index (P=7.17E-09) in the TCGA and GTEx datasets. In single cells, we found that DOT1L promotes CD44 expression via the Wnt/ß-catenin signaling pathway and the development for stemness properties within GC. In addition, we found that DOT1L, CD44 and CTNNB1 colocalize and correlate positively. In conclusion, one important CSC regulator in GC, DOT1L may be crucial in coordinating the expression of genes specific to a certain lineage during MSC development.

DDK: Dynamic structure pruning based on differentiable search and recursive knowledge distillation for BERT.

Large-scale pre-trained models, such as BERT, have demonstrated outstanding performance in Natural Language Processing (NLP). Nevertheless, the high number of parameters in these models has increased the demand for hardware storage and computational resources while posing a challenge for their practical deployment. In this article, we propose a combined method of model pruning and knowledge distillation to compress and accelerate large-scale pre-trained language models. Specifically, we introduce a dynamic structure pruning method based on differentiable search and recursive knowledge distillation to automatically prune the BERT model, named DDK. We define the search space for network pruning as all feed-forward layer channels and self-attention heads at each layer of the network, and utilize differentiable methods to determine their optimal number. Additionally, we design a recursive knowledge distillation method that employs adaptive weighting to extract the most important features from multiple intermediate layers of the teacher model and fuse them to supervise the student network learning. Our experimental results on the GLUE benchmark dataset and ablation analysis demonstrate that our proposed method outperforms other advanced methods in terms of average performance.

Expression and clinical role of PRDX6 in lung adenocarcinoma.

OBJECTIVE: To explore the levels of expression and clinical role of peroxiredoxin 6 (PRDX6) in lung adenocarcinoma. METHODS: This retrospective study used a series of bioinformatics methods to detect the levels of expression of and mutations in the PRDX6 gene in a range of cancers and lung adenocarcinoma. Immunohistochemistry was used to verify the levels of expression of PRDX6 protein in samples of lung adenocarcinoma compared with normal adjacent tissue. The effect of PRDX6 gene knockdown on the in vitro proliferation of a lung adenocarcinoma cell line was measured. Bioinformatics methods were used to determine the diagnostic value and impact on survival of the PRDX6 gene in patients with lung adenocarcinoma. RESULTS: The results showed that the PRDX6 gene was highly expressed in lung adenocarcinoma and there were five mutations at different sites on the gene. PRDX6 promoted the proliferation of the lung adenocarcinoma cell line. The survival duration of lung adenocarcinoma patients with high levels of PRDX6 gene expression was significantly shorter than that of patients with low PRDX6 gene expression. CONCLUSION: PRDX6 is highly expressed in lung adenocarcinoma and higher levels of expression of the PRDX6 gene were associated with a poorer prognosis.