Exploring pathogenesis and biomarkers through establishment of a rat model of male infertility with liver depression and kidney deficiency.

OBJECTIVES: To establish a rat model that accurately replicates the clinical characteristics of male infertility (MI) with Liver Depression and Kidney Deficiency (LD & KD) and investigate the pathogenesis. METHODS: After subjecting the rats to chronic restraint stress (CRS) and adenine treatment, a series of tests were conducted, including ethological assessments, evaluations of reproductive characteristics, measurements of biochemical parameters, histopathological examinations, and analyses of urinary metabolites. Additionally, bioinformatics predictions were performed for comprehensive analysis. RESULTS: Compared to the control, the model exhibited significant manifestations of MI with LD & KD, including reduced responsiveness, diminished frequency of capturing estrous female rats, and absence of mounting behavior. Additionally, the kidney coefficient increased markedly, while the coefficients of the testis and epididymis decreased significantly. Sperm counts and viabilities decreased notably, accompanied by an increase in sperm abnormalities. Dysregulation of reproductive hormone levels in the serum was observed, accompanied by an upregulation of proinflammatory cytokines expressions in the liver and kidney, as well as exacerbated oxidative stress in the penile corpus cavernosum and testis. The seminiferous tubules in the testis exhibited a loose arrangement, loss of germ cells, and infiltration of inflammatory cells. Furthermore, utilizing urinary metabolomics and bioinformatics analysis, 5 key biomarkers and 2 crucial targets most closely linked to MI were revealed. CONCLUSION: The study successfully established a clinically relevant animal model of MI with LD & KD. It elucidates the pathogenesis of the condition, identifies key biomarkers and targets, and provides a robust scientific foundation for the prediction, diagnosis, and treatment of MI with LD & KD.

Engineering a Carotenoid Cleavage Oxygenase for Coenzyme-Free Synthesis of Vanillin from Ferulic Acid.

One-pot biosynthesis of vanillin from ferulic acid without providing energy and cofactors adds significant value to lignin waste streams. However, naturally evolved carotenoid cleavage oxygenase (CCO) with extreme catalytic conditions greatly limited the above pathway for vanillin bioproduction. Herein, CCO from Thermothelomyces thermophilus (TtCCO) was rationally engineered for achieving high catalytic activity under neutral pH conditions and was further utilized for constructing a one-pot synthesis system of vanillin with Bacillus pumilus ferulic acid decarboxylase. TtCCO with the K192N-V310G-A311T-R404N-D407F-N556A mutation (TtCCOM3) was gradually obtained using substrate access channel engineering, catalytic pocket engineering, and pocket charge engineering. Molecular dynamics simulations revealed that reducing the site-blocking effect in the substrate access channel, enhancing affinity for substrates in the catalytic pocket, and eliminating the pocket's alkaline charge contributed to the high catalytic activity of TtCCOM3 under neutral pH conditions. Finally, the one-pot synthesis of vanillin in our study could achieve a maximum rate of up to 6.89 ± 0.3 mM h-1. Therefore, our study paves the way for a one-pot biosynthetic process of transforming renewable lignin-related aromatics into valuable chemicals.

Testicular metastasis from urothelial carcinoma: case report and literature review.

Urothelial carcinoma (UC) with testicular metastasis is extremely rare, and its modes of metastasis, prognosis, and treatment are unclear. In this report, we present an extraordinarily rare case of testicular metastasis arising from UC 8 years after surgery. The patient underwent left orchiepididymectomy and received immunotherapy postoperatively. After a 6-month follow-up, there were no signs of recurrence. Moreover, the clinical characteristics, metastasis pattern, and treatment plan were also summarized based on 14 earlier reported cases of UC with testicular metastasis.

METTL3 attenuates ferroptosis sensitivity in lung cancer via modulating TFRC.

Overexpression of methyltransferase-like 3 (METTL3) is significantly correlated with the malignancy of lung cancer (LC). In the present study, we demonstrated that METTL3 had higher levels in LC tissues relative to normal tissues. METTL3 showed superior sensitivity and specificity for diagnosis and identification of LC functions. In addition, silencing METTL3 resulted in enhanced ferroptosis sensitivity, whereas overexpression of METTL3 exhibited the opposite effect. Inhibition of METTL3 impeded LC growth in cell-derived xenografts. Further exploratory studies found that METTL3 stimulated the low expression of transferrin receptor (TFRC), which was critical for ferroptosis sensitization in LC cells induced by silenced METTL3, as silencing of TFRC caused a decrease in negative regulators of ferroptosis (FTH1 and FTL) in METTL3 knockdown A549 and PC9 cells. Finally, we confirmed that METTL3 attenuation effectively maintained the stability of TFRC mRNA. In conclusion, we reported a novel mechanism of METTL3 desensitization to ferroptosis via regulating TFRC, and an appropriate reduction of METTL3 might sensitize cancer cells to ferroptosis-based therapy.

Green synthesis of epigallocatechin gallate-ferric complex nanoparticles for photothermal enhanced antibacterial and wound healing.

Bacterial infections are a significant global health concern, particularly in the context of skin infections and chronic wounds, which was further exacerbated by the emerging of antibiotic resistance. Therefore, there are urgent needs to develop alternative antibacterial strategies without inducing significant resistance. Photothermal therapy (PTT) is a promising alternative approach but usually faces limitations such as the need for stable and environmental-friendly PTT agents and ensuring biocompatibility with living tissues, necessitating ongoing research for its clinical advancement. Herein, in this study, with the aim to develop a green synthesized PTT agent for photothermal enhanced antibacterial and wound healing, we proposed a facile one-pot method to prepare epigallocatechin gallate-ferric (EGCG-Fe) complex nanoparticles. The obtained nanoparticles showed improved good size distribution and stability with high reproducibility. More importantly, EGCG-Fe complex nanoparticles have additional photothermal conversion ability which can give photothermal enhanced antibacterial effect on various pathogens, including Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli) strains. EGCG-Fe complex nanoparticles also showed powerful biofilm prevention and destruction effects with promoted antibacterial and wound healing on mice model. In conclusion, EGCG-Fe complex nanoparticles can be a robust green material with effective and novel light controllable antibacterial properties for photothermal enhanced antibacterial and wound healing applications.

Study on the simultaneous release of microfiber and indigo dye in denim fabric home washing.

In recent years, with the increasing global focus on environmental protection, the issue of microfiber release from denim during the washing process has gained attention. In this study, a programmable washing device simulating household drum washing was designed and developed, microfibers and indigo dyes released from denim washing were quantitatively detected, and we have also developed a novel method for estimating the release of microfibers during washing. The effects of washing time, washing temperature, and washing load on microfiber and indigo dye release from denim were explored. The results showed that the effect of washing load on microfiber and indigo dye release was greater than washing temperature and washing time. The research findings indicate that with an increase in washing time (35-95 min) and washing load (100-250 g), the shedding of microfibers and indigo dye significantly increases, reaching peak release levels of 343.6 µg/g fabric and 0.027 mg/L, respectively. However, there is a decreasing trend in the release of microfibers and indigo dye when the washing temperature exceeds 50 °C. Furthermore, our data suggests that an increase in washing load leads to a significant change in the number of microfibers (from 978 items/g fabric to 1997 items/g fabric) and their mass (from 156.87 µg/g fabric to 343.56 µg/g fabric). The influence of washing time, washing temperature, and washing load on microfiber length shows relatively small fluctuations within the range of 600-900 µm. This study provides new ideas and methods for estimating the release of microfiber and indigo dye in denim washing around the world.

Multilevel Laser-Induced Pain Measurement with Wasserstein Generative Adversarial Network - Gradient Penalty Model.

Pain is an experience of unpleasant sensations and emotions associated with actual or potential tissue damage. In the global context, billions of people are affected by pain disorders. There are particular challenges in the measurement and assessment of pain, and the commonly used pain measuring tools include traditional subjective scoring methods and biomarker-based measures. The main tools for biomarker-based analysis are electroencephalography (EEG), electrocardiography and functional magnetic resonance. The EEG-based quantitative pain measurements are of immense value in clinical pain management and can provide objective assessments of pain intensity. The assessment of pain is now primarily limited to the identification of the presence or absence of pain, with less research on multilevel pain. High power laser stimulation pain experimental paradigm and five pain level classification methods based on EEG data augmentation are presented. First, the EEG features are extracted using modified S-transform, and the time-frequency information of the features is retained. Based on the pain recognition effect, the 20-40[Formula: see text]Hz frequency band features are optimized. Afterwards the Wasserstein generative adversarial network with gradient penalty is used for feature data augmentation. It can be inferred from the good classification performance of features in the parietal region of the brain that the sensory function of the parietal lobe region is effectively activated during the occurrence of pain. By comparing the latest data augmentation methods and classification algorithms, the proposed method has significant advantages for the five-level pain dataset. This research provides new ways of thinking and research methods related to pain recognition, which is essential for the study of neural mechanisms and regulatory mechanisms of pain.

A Light Vehicle License-Plate-Recognition System Based on Hybrid Edge-Cloud Computing.

With the world moving towards low-carbon and environmentally friendly development, the rapid growth of new-energy vehicles is evident. The utilization of deep-learning-based license-plate-recognition (LPR) algorithms has become widespread. However, existing LPR systems have difficulty achieving timely, effective, and energy-saving recognition due to their inherent limitations such as high latency and energy consumption. An innovative Edge-LPR system that leverages edge computing and lightweight network models is proposed in this paper. With the help of this technology, the excessive reliance on the computational capacity and the uneven implementation of resources of cloud computing can be successfully mitigated. The system is specifically a simple LPR. Channel pruning was used to reconstruct the backbone layer, reduce the network model parameters, and effectively reduce the GPU resource consumption. By utilizing the computing resources of the Intel second-generation computing stick, the network models were deployed on edge gateways to detect license plates directly. The reliability and effectiveness of the Edge-LPR system were validated through the experimental analysis of the CCPD standard dataset and real-time monitoring dataset from charging stations. The experimental results from the CCPD common dataset demonstrated that the network's total number of parameters was only 0.606 MB, with an impressive accuracy rate of 97%.

Potential Environmental Contaminants: Exploring Hydrolyzed Dyes in Household Washing Sources and Electrochemical Degradation.

Reactive dyes are often released into the environment during the washing process due to their susceptibility to hydrolysis. The hydrolysis experiment of a pure reactive dye, red 195 (RR 195), and the washing experiment of RR 195-colored fabrics (CFSCs) were carried out successively to explore the sources of hydrolyzed dyes in the washing microenvironment. Reversed-phase high-performance liquid chromatography (RP-HPLC) was used for the analysis of hydrolysis intermediates and final products of reactive red 195. The experimental results indicated that the structure of the dye washing shed is consistent with the final hydrolysate of reactive red 195, which is the main colored contaminant in washing wastewater. To eliminate the hydrolyzed dyes from the source, an electrochemical degradation device was designed. The degradation parameters, including voltage, electrolyte concentration, and dye shedding concentration are discussed in the electrochemical degradation experiment. The electrochemical degradation device was also successfully implemented and verified in a home washing machine.

Application of f-FeNC@GOx cascade enzyme nanomaterials in the healing of infected wounds.

AIMS: Bacterial infection is a significant factor contributing to the deterioration of wounds, and the misuse of antibiotics has exacerbated bacterial resistance. Therefore, there is an urgent need to develop a novel antibacterial strategy to replace conventional therapies. This study aims to construct a self-activated cascade reaction nanozyme, f-FeNC@GOx, which triggers a cascade reaction in the presence of glucose. This cascade reaction generates highly toxic hydroxyl radicals (OH), thereby achieving the goal of eliminating bacteria and promoting wound healing. MATERIAL AND METHODS: In vitro antibacterial experiments, bacterial spread plate method, Live/Dead staining, and crystal violet staining were conducted to analyze the antibacterial ability and mechanism of f-FeNC@GOx. In vivo experiments, a mouse wound model was established, and H&E and Masson staining of wound tissues were performed to assess the antibacterial activity of the f-FeNC@GOx in vivo. KEY FINDINGS: The in vivo and in vitro experiments confirmed that f-FeNC@GOx exhibited significant antibacterial effect against both Staphylococcus aureus and Escherichia coli in the presence of glucose. Furthermore, it showed optimal wound healing performance in the wound models. SIGNIFICANCE: These findings suggested that f-FeNC@GOx was a novel and effective antibacterial nanomaterial, which provided a promising antibacterial strategy using nanoenzyme based cascade reaction.

[Simultaneous determination of eleven volatile components in Cinnamomi Oleum by GC-MS].

A gas chromatography-triple quadrupole mass spectrometry(GC-MS) method was established for the simultaneous determination of eleven volatile components in Cinnamomi Oleum and the chemical pattern recognition was utilized to evaluate the quality of essential oil obtained from Cinnamomi Fructus medicinal materials in various habitats. The Cinnamomi Fructus medicinal materials were treated by water distillation, analyzed using GC-MS, and detected by selective ion monitoring(SIM), and the internal standards were used for quantification. The content results of Cinnamomi Oleum from various batches were analyzed by hierarchical clustering analysis(HCA), principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) for the statistic analysis. Eleven components showed good linear relationships within their respective concentration ranges(R~2>0.999 7), with average recoveries of 92.41%-102.1% and RSD of 1.2%-3.2%(n=6). The samples were classified into three categories by HCA and PCA, and 2-nonanone was screened as a marker of variability between batches in combination with OPLS-DA. This method is specific, sensitive, simple, and accurate, and the screened components can be utilized as a basis for the quality control of Cinnamomi Oleum.

A Fiber-Optic Sensor-Embedded and Machine Learning Assisted Smart Helmet for Multi-Variable Blunt Force Impact Sensing in Real Time.

Early on-site diagnosis of mild traumatic brain injury (mTBI) will provide the best guidance for clinical practice. However, existing methods and sensors cannot provide sufficiently detailed physical information related to the blunt force impact. In the present work, a smart helmet with a single embedded fiber Bragg grating (FBG) sensor is developed, which can monitor complex blunt force impact events in real time under both wired and wireless modes. The transient oscillatory signal "fingerprint" can specifically reflect the impact-caused physical deformation of the local helmet structure. By combination with machine learning algorithms, the unknown transient impact can be recognized quickly and accurately in terms of impact magnitude, direction, and latitude. Optimization of the training dataset was also validated, and the boosted ML models, such as the S-SVM+ and S-IBK+, are able to predict accurately with complex databases. Thus, the ML-FBG smart helmet system developed by this work may become a crucial intervention alternative during a traumatic brain injury event.

High expression of GMNN predicts malignant progression and poor prognosis in ACC.

BACKGROUND: Adrenocortical carcinoma (ACC) is a rare endocrine neoplasm, which is characterized by poor prognosis and high recurrence rate. Novel and reliable prognostic and metastatic biomarkers are lacking for ACC patients. This study aims at screening potential prognostic biomarkers and therapeutic targets of ACC through bioinformatic methods and immunohistochemical (IHC) analysis. METHODS: In the present study, by using the Gene Expression Omnibus (GEO) database we identified differentially expressed genes (DEGs) in ACC and validated these DEGs in The Cancer Genome Atlas (TCGA) ACC cohort. A DEGs-based signature was additionally constructed and we assessed its prognosis and prescient worth for ACC by survival analysis and nomogram. Immunohistochemistry (IHC) was used to verify the relationship between hub gene-GMNN expressions and clinicopathologic outcomes in ACC patients. RESULTS: A total of 24 DEGs correlated with the prognosis of ACC were screened from the TCGA and GEO databases. Five DEGs were subsequently selected in a signature which was closely related to the survival rates of ACC patients and GMNN was identified as the core gene in this signature. Univariate and multivariate Cox regression showed that the GMNN was an independent prognostic factor for ACC patients (P < 0.05). Meanwhile, GMNN was closely related to the OS and PFI of ACC patients treated with mitotane (P < 0.001). IHC confirmed that GMNN protein was overexpressed in ACC tissues compared with normal adrenal tissues and significantly correlated with stage (P = 0.011), metastasis (P = 0.028) and Ki-67 index (P = 0.014). CONCLUSIONS: GMNN is a novel tumor marker for predicting the malignant progression, metastasis and prognosis of ACC, and may be a potential therapeutic target for ACC.

Deep Convolution Generative Adversarial Network-Based Electroencephalogram Data Augmentation for Post-Stroke Rehabilitation with Motor Imagery.

The motor imagery brain-computer interface (MI-BCI) system is currently one of the most advanced rehabilitation technologies, and it can be used to restore the motor function of stroke patients. The deep learning algorithms in the MI-BCI system require lots of training samples, but the electroencephalogram (EEG) data of stroke patients is quite scarce. Therefore, the expansion of EEG data has become an important part of stroke clinical rehabilitation research. In this paper, a deep convolution generative adversarial network (DCGAN) model is proposed to generate artificial EEG data and further expand the scale of the stroke dataset. First, multichannel one-dimensional EEG data is converted into a two-dimensional EEG spectrogram using EEG2Image based on the modified S-transform. Then, DCGAN is used to artificially generate EEG data based on MI. Finally, the validity of the generated artificial EEG data is proved. This paper preliminarily indicates that generating artificial stroke data is a promising strategy, which contributes to the further development of stroke clinical rehabilitation.

CtBP2 interacts with TGIF to promote the progression of esophageal squamous cell cancer through the Wnt/ß­catenin pathway.

C­terminal­binding protein 2 (CtBP2), a transcriptional co­repressor, plays a main role in tumorigenesis and in the development of multiple tumors. Transforming growth interacting factor (TGIF) is involved in a number of cellular signal transduction pathways and is related to tumor occurrence and development. In the present study, the proteins interacting with CtBP2 were identified and the mechanisms underlying the biological activity of CtBP2 in esophageal squamous cell carcinoma (ESCC) were investigated. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to search for known proteins interacting with CtBP2, and co­immunoprecipitation (Co­IP) assay was performed to validate the interactions. Reverse transcription­quantitative PCR (RT­qPCR), immunohistochemistry (IHC) and western blot analysis were performed to examine the expression levels of CtBP2 and TGIF in ESCC. The correlation between CtBP2 and TGIF was analyzed using Gene Expression Profiling Interactive Analysis (GEPIA) by Pearson's correlation analysis, and the co­localization of CtBP2 with TGIF in the ECA109 cells was identified using immunofluorescence staining. XAV939 treatment, CCK­8, 5­ethynyl­2'­deoxyuridine (EdU) staining, wound healing and Transwell assays were performed to investigate the signaling pathways involved in the biological activity of CtBP2 in ECA109 cells. According to the results obtained from STRING and Co­IP analysis, an interaction between CtBP2 and TGIF was indicated, and these proteins were co­localized in the nucleus. CtBP2 and TGIF mRNA and protein expression levels were robustly and simultaneously increased in both ESCC tissues and cell lines. There was a direct correlation between CtBP2 and TGIF expression levels in ESCC tissues, and both were significantly associated with metastasis and survival. The TGIF and CtBP2 expression levels were significantly increased or decreased simultaneously, in ECA109 cells transfected with LV­CtBP2 or sh­CtBP2, and vice versa. According to the results of CCK­8 assay, EdU staining and Transwell assay, CtBP2 promoted the proliferation, migration and invasion of ECA109 cells through the Wnt/ß­catenin pathway. On the whole, the present study demonstrates that CtBP2 interacts with TGIF and promotes the malignant progression of ESCC through the Wnt/ß­catenin pathway.

Exploration of sleep function connection and classification strategies based on sub-period sleep stages.

Background: As a medium for developing brain-computer interface systems, EEG signals are complex and difficult to identify due to their complexity, weakness, and differences between subjects. At present, most of the current research on sleep EEG signals are single-channel and dual-channel, ignoring the research on the relationship between different brain regions. Brain functional connectivity is considered to be closely related to brain activity and can be used to study the interaction relationship between brain areas. Methods: Phase-locked value (PLV) is used to construct a functional connection network. The connection network is used to analyze the connection mechanism and brain interaction in different sleep stages. Firstly, the entire EEG signal is divided into multiple sub-periods. Secondly, Phase-locked value is used for feature extraction on the sub-periods. Thirdly, the PLV of multiple sub-periods is used for feature fusion. Fourthly, the classification performance optimization strategy is used to discuss the impact of different frequency bands on sleep stage classification performance and to find the optimal frequency band. Finally, the brain function network is constructed by using the average value of the fusion features to analyze the interaction of brain regions in different frequency bands during sleep stages. Results: The experimental results have shown that when the number of sub-periods is 30, the α (8-13 Hz) frequency band has the best classification effect, The classification result after 10-fold cross-validation reaches 92.59%. Conclusion: The proposed algorithm has good sleep staging performance, which can effectively promote the development and application of an EEG sleep staging system.

Corrigendum to: Physicochemical insights of irradiation-enhanced hydroxyl radical generation from ZnO nanoparticles.

[This corrects the article DOI: 10.1039/c5tx00384a.].

Do reverse total shoulder replacements have better clinical and functional outcomes than hemiarthroplasty for patients undergoing proximal humeral tumor resection using devitalized autograft composite reconstruction: a case-control study.

OBJECTIVE: To compare the efficacy and prognosis of reverse total shoulder arthroplasty (rTSA) with shoulder hemiarthroplasty (SHA) using devitalized autograft or allograft composite reconstruction after proximal humeral tumor resection. METHODS: We retrospectively reviewed patients who underwent SHA (32) and rTSA (20) for tumor resections of the proximal humerus from January 2014 to July 2020. The clinical results included duration of the operation, intraoperative blood loss, bone union, visual analog scale (VAS) score, shoulder range of motion (ROM), American Shoulder and Elbow Surgeons (ASES) shoulder score, recurrence, and overall survival. RESULTS: Fifty-two patients were followed up for a mean of 30 months. Thirty-two patients were SHA with allograft-prosthetic composite (APC) reconstructions, while other 20 were rTSA with devitalized autograft-prosthetic composite reconstructions. At the end of the follow-up, 2 recurrence, 3 postoperative infections, and 4 subluxations occurred among the SHA patients. Two patients in the rTSA group had postoperative anterior dislocation and underwent revision surgery with surgical mesh, and 2 (2/20) had grade II scapular notching. The mean VAS score of the shoulder was 1.5 ± 0.8 in the rTSA group and 2.3 ± 1.2 in the SHA group (p < 0.05). The mean active forward flexion of the shoulder joint was 50.6 ± 6.0 in the SHA group and 100 ± 7.6 in the rTSA group (p < 0.05). The ASES shoulder score was 78 ± 3.0 in the rTSA group and 52 ± 5.6 in the SHA group (p < 0.05). The overall 3-year survival rate of all patients was 60.0%, and patients in the rTSA group showed better survival in terms of the mean 3-year OS than patients in the SHA group (p = 0.04). CONCLUSION: rTSA with devitalized autograft-prosthetic composite can offer a reasonable reconstruction of the shoulder joint after Malawer type I tumor resection. Compared with patients who underwent SHA, patients who underwent rTSA present good outcomes, a better range of motion, better bone union, and no increase in instability rate in the mid-term.

LncRNA ABCC6P1 promotes proliferation and migration of papillary thyroid cancer cells via Wnt/ß-catenin signaling pathway.

BACKGROUND: LncRNAs play an important regulatory function in the occurrence and progression of papillary thyroid cancer (PTC). This study aimed to investigate the role and mechanism of ATP binding cassette subfamily C member 6 pseudogene 1 (ABCC6P1) in PTC. METHODS: Cancerous and paracancer normal thyroid tissues were collected from 18 patients with PTC, who were operated at the Second Affiliated Hospital of Harbin Medical University. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to investigate the levels of ABCC6P1. Cell proliferation was evaluated using Cell Counting Kit-8 (CCK-8) and colony formation assays. Wound healing and Transwell invasion assays were performed to examine cell migratory and invasive ability. Western blotting analysis was used to detect the expression levels of EMT-related markers and Wnt/ß-catenin signaling pathway-related proteins. RESULTS: The expression of ABCC6P1 was upregulated in PTC tissues and cells. ABCC6P1 silencing could significantly suppress the proliferation, colony formation ability, migratory and invasive ability in PTC cells. Moreover, knockdown of ABCC6P1 induced cell cycle arrest at G0/G1 phase and inhibited epithelial-mesenchymal transition (EMT) process of PTC cells by increasing the E-cadherin expression, but downregulating N-cadherin and vimentin expression. In addition, knockdown of ABCC6P1 caused a significant decrease in levels of Wnt/ß-catenin signaling pathway members (including ß-catenin, c-myc, and cyclin D1) in PTC cells. CONCLUSIONS: Our study confirms that ABCC6P1 exerts an oncogenic activity in PTC which may be mediated by the Wnt/ß-catenin pathway, suggesting that ABCC6P1 may be a promising therapeutic target for PTC.

Retracted: Phillygenin Exerts In Vitro and In Vivo Antitumor Effects in Drug-Resistant Human Esophageal Cancer Cells by Inducing Mitochondrial-Mediated Apoptosis, ROS Generation, and Inhibition of the Nuclear Factor kappa B NF-κB Signalling Pathway.

An editorial decision has been made to retract this manuscript due to breach of publishing guidelines, following the identification of non-original and manipulated figures. Reference: Jiantao He, Wei Wei, Qingbo Yang, Yiling Wang: Phillygenin Exerts In Vitro and In Vivo Antitumor Effects in Drug-Resistant Human Esophageal Cancer Cells by Inducing Mitochondrial-Mediated Apoptosis, ROS Generation, and Inhibition of the Nuclear Factor kappa B NF-kappaB Signalling Pathway. Med Sci Monit 2019; 25:739-745. 10.12659/MSM.913138.