Hepatotoxicity of oral exposure to 2-methyl-4-nitroaniline: toxicity prediction and in vivo evaluation.

2-Methyl-4-nitroaniline (MNA), an intermediate in the synthesis of azo dyes, is widely distributed in various environmental media and organisms. Although there is speculation regarding MNA's potential to be hepatotoxic, the underlying mechanisms of its hepatotoxicity and its definitive diagnostic process remain largely unexplored. In this research. In the present study, we initially predicted the toxicity and possible toxic effect pathways of MNA using ProTox-II, and found that MNA binds to the PPARγ receptor (binding energy －6.118kcal/mol) with a potential PPARγ agonist effect. Subsequently, in vivo exposure evaluation was conducted on Wistar rats to assess the impact of MNA after a 90-day exposure period, by detecting serum biochemical indexes, hematological indexes, urinary indexes, inflammatory factors, liver histopathological observations and liver tissue PPARγ mRNA expression. The results showed that MNA causes liver function abnormalities, liver histopathological changes and inflammatory response, along with a pronounced increase in PPARγ mRNA levels. This study suggests that the hepatotoxic mechanism of MNA may be related to its possible upregulation of PPARγ expression, increased liver dysfunction and inflammatory responses. Based on these results, the benchmark dose lower limit (BMDL) of 1.503mg/kg for male Wistar rats was also established, providing a vital benchmark for determining the safety threshold of MNA. Our data highlight the hepatotoxic mechanism of MNA and contribute to a better understanding of its potential etiological diagnosis.

Low-Voltage Solution-Processed Zinc-Doped CuI Thin Film Transistors with NOR Logic and Artificial Synaptic Function.

Low-voltage Zn-doped CuI thin film transistors (TFTs) gated by chitosan dielectric were fabricated at a low temperature. The Zn-doped CuI TFT exhibited a more superior on/off current ratio than CuI TFT due to the substitution or supplementation of copper vacancies by Zn ions. The Zn-doped CuI films were characterized by scanning electron microscope, X-ray diffraction, and X-ray photoelectron spectroscopy. The Zn-doped CuI TFTs exhibited an on/off current ratio of 1.58 × 104, a subthreshold swing of 70 mV/decade, and a field effect mobility of 0.40 cm2V-1s-1, demonstrating good operational stability. Due to the electric-double-layer (EDL) effect and high specific capacitance (17.3 µF/cm2) of chitosan gate dielectric, Zn-doped CuI TFT operates at a voltage below -2 V. The threshold voltage is -0.2 V. In particular, we have prepared Zn-doped CuI TFTs with two in-plane gates and NOR logic operation is implemented on such TFTs. In addition, using the ion relaxation effect and EDL effect of chitosan film, a simple pain neuron simulation is realized on such a p-type TFTs for the first time through the bottom gate to regulate the carrier transport of the channel. This p-type device has promising applications in low-cost electronic devices, complementary electronic circuit, and biosensors.

Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy.

Purpose: To introduce a model for automatic segmentation of thoracic organs at risk (OARs), especially the esophagus, in non-small cell lung cancer radiotherapy, using a novel two-step deep learning network. Materials and methods: A total of 59 lung cancer patients' CT images were enrolled, of which 39 patients were randomly selected as the training set, 8 patients as the validation set, and 12 patients as the testing set. The automatic segmentations of the six OARs including the esophagus were carried out. In addition, two sets of treatment plans were made on the basis of the manually delineated tumor and OARs (Plan1) as well as the manually delineated tumor and the automatically delineated OARs (Plan2). The Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) of the proposed model were compared with those of U-Net as a benchmark. Next, two groups of plans were also compared according to the dose-volume histogram parameters. Results: The DSC, HD95, and ASD of the proposed model were better than those of U-Net, while the two groups of plans were almost the same. The highest mean DSC of the proposed method was 0.94 for the left lung, and the lowest HD95 and ASD were 3.78 and 1.16 mm for the trachea, respectively. Moreover, the DSC reached 0.73 for the esophagus. Conclusions: The two-step segmentation method can accurately segment the OARs of lung cancer. The mean DSC of the esophagus realized preliminary clinical significance (>0.70). Choosing different deep learning networks based on different characteristics of organs offers a new option for automatic segmentation in radiotherapy.

Automatic segmentation of the tumor in nonsmall-cell lung cancer by combining coarse and fine segmentation.

OBJECTIVES: Radiotherapy plays an important role in the treatment of nonsmall-cell lung cancer (NSCLC). Accurate delineation of tumor is the key to successful radiotherapy. Compared with the commonly used manual delineation ways, which are time-consuming and laborious, the automatic segmentation methods based on deep learning can greatly improve the treatment efficiency. METHODS: In this paper, we introduce an automatic segmentation method by combining coarse and fine segmentations for NSCLC. Coarse segmentation network is the first level, identifing the rough region of the tumor. In this network, according to the tissue structure distribution of the thoracic cavity where tumor is located, we designed a competition method between tumors and organs at risk (OARs), which can increase the proportion of the identified tumor covering the ground truth and reduce false identification. Fine segmentation network is the second level, carrying out precise segmentation on the results of the coarse level. These two networks are independent of each other during training. When they are used, morphological processing of small scale corrosion and large scale expansion is used for the coarse segmentation results, and the outcomes are sent to the fine segmentation part as input, so as to achieve the complementary advantages of the two networks. RESULTS: In the experiment, CT images of 200 patients with NSCLC are used to train the network, and CT images of 60 patients are used to test. Finally, our method produced the Dice similarity coefficient of 0.78 ± 0.10. CONCLUSIONS: The experimental results show that the proposed method can accurately segment the tumor with NSCLC, and can also provide support for clinical diagnosis and treatment.

Clinical Efficacy, Antibiotic Resistance Genes, Virulence Factors and Outcome of Hospital-Acquired Pneumonia Induced by Klebsiella pneumoniae Carbapenemase 2-Producing with Tigecycline Treatment in the ICU.

Purpose: Tigecycline is an agent for carbapenemase-producing Klebsiella pneumonia (KPC-KP), given its penetration into lung tissues. Our study focused on the molecular and clinical efficacy of tigecycline for hospital-acquired pneumonia (HAP) in the ICU. Patients and Methods: A retrospective cohort study of 52 adult KPC-KP HAP patients by searching hospital medical records from January 2018 to December 2020 was established to investigate the epidemiology of KPC-KP infections for tigecycline treatment and the associated clinical efficacy of tigecycline. The KPC-KP isolates underwent multilocus sequence typing. Molecular typing, antimicrobial resistance, and virulence profiling were also analyzed by whole-genome sequencing of KPC-KP. Results: Among 52 patients with KPC-KP, the ICU mortality rate was 14/52 (27%), and there was no significant statistical difference in mortality between the effective group and failure group (p = 0.754). However, the duration of tigecycline was statistically different between the two groups of patients (14.4 vs 10 days, p=0.046). The total bacterial clearance rate was 6/52 (11.5%). There was no significant statistical difference in both groups (p=0.416). Antibiotic resistance genes (aac3iia) and virulence gene (AREO-iutA, Capsule-wzc) were negatively correlated with clinical efficacy (p = 0.011, OR = 1.237). Conclusions: Blakpc was the main carbapenemase in all K. pneumoniae strains. ST11-KL64 KPC-KP was the most common virulence factors in KPC-KP isolates. This study suggested that antibiotic resistance genes (aac3iia) and virulence gene (AREO-iutA, Capsule-wzc) were independent mortality risk factors for patients with Klebsiella pneumoniae carbapenemase-2 producing K. pneumoniae infections, when during the tigecycline treatment. Molecular analysis of K. pneumoniae may provide an option when choosing the antimicrobial treatment.

Geometric and Dosimetric Evaluation of the Automatic Delineation of Organs at Risk (OARs) in Non-Small-Cell Lung Cancer Radiotherapy Based on a Modified DenseNet Deep Learning Network.

Purpose: To introduce an end-to-end automatic segmentation model for organs at risk (OARs) in thoracic CT images based on modified DenseNet, and reduce the workload of radiation oncologists. Materials and Methods: The computed tomography (CT) images of 36 lung cancer patients were included in this study, of which 27 patients' images were randomly selected as the training set, 9 patients' as the testing set. The validation set was generated by cross validation and 6 patients' images were randomly selected from the training set during each epoch as the validation set. The autosegmentation task of the left and right lungs, spinal cord, heart, trachea and esophagus was implemented, and the whole training time was approximately 5 hours. Geometric evaluation metrics including the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and average surface distance (ASD), were used to assess the autosegmentation performance of OARs based on the proposed model and were compared with those based on U-Net as benchmarks. Then, two sets of treatment plans were optimized based on the manually contoured targets and OARs (Plan1), as well as the manually contours targets and the automatically contoured OARs (Plan2). Dosimetric parameters, including Dmax, Dmean and Vx, of OARs were obtained and compared. Results: The DSC, HD95 and ASD of the proposed model were better than those of U-Net. The differences in the DSC of the spinal cord and esophagus, differences in the HD95 of the spinal cord, heart, trachea and esophagus, as well as differences in the ASD of the spinal cord were statistically significant between the two models (P<0.05). The differences in the dose-volume parameters of the two sets of plans were not statistically significant (P>0.05). Moreover, compared with manual segmentation, autosegmentation significantly reduced the contouring time by nearly 40.7% (P<0.05). Conclusions: The bilateral lungs, spinal cord, heart and trachea could be accurately delineated using the proposed model in this study; however, the automatic segmentation effect of the esophagus must still be further improved. The concept of feature map reuse provides a new idea for automatic medical image segmentation.

Dosimetric evaluation of helical tomotherapy and volumetric-modulated arc therapy for malignant pleural mesothelioma: a planning study for dose escalation.

BACKGROUND: To compare the dosimetric differences between helical tomotherapy (HT) and volumetric-modulated arc therapy (VMAT) treatment plans for inoperable malignant pleural mesothelioma (MPM). METHODS: Ten patients with inoperable MPM were retrospectively planned with the HT and VMAT techniques, and the dose-volume histogram (DVH)-based parameters of the planning target volume (PTV) and organs at risk (OARs) were compared. RESULTS: Compared with the VMAT plans, the target homogeneity index (HI) and conformity index (CI) of the HT plans were significantly better (HI: 1.04±0.01 vs. 1.11±0.03, CI: 0.80±0.07 vs. 0.71±0.12, respectively) (P<0.001, P=0.013, respectively). Regarding the OARs, including the ipsilateral lung, contralateral lung, heart, and spinal cord, the differences among the V30 (Vx: fraction of volume receiving >5, 10, 20, and 30 Gy, respectively) of the ipsilateral lung and V5, V10, and V20 of the contralateral lung were statistically significant (P=0.031, P=0.030, P=0.021, P=0.003, respectively). However, there was no significant differences between HT plans and VMAT plans, regarding the V5, V10 and V20 of the ipsilateral lung, V3 of the contralateral lung, V5 and Dmean of the heart, and Dmax of the cord. The treatment delivery time of the VMAT was significantly shorter than that of the HT (mean delivery time: 3.27±1.65 vs. 11.11±3.75 min, respectively) (P<0.001). CONCLUSIONS: Compared to the VMAT plans, the HT plans not only demonstrated more optimal target coverage and conformity but also considerably reduced the dose-volume parameters of the OARs in both low-dose areas in contralateral lung and high-dose areas in ipsilateral lung and contralateral lung, which is correlated to radiation injury. However, the treatment delivery time of the HT plans was longer.

MiR-218-5p Suppresses the Killing Effect of Natural Killer Cell to Lung Adenocarcinoma by Targeting SHMT1.

PURPOSE: Lung adenocarcinoma (LA) is one of the major types of lung cancer. MicroRNAs (miRNAs) play an essential role in regulating responses of natural killer (NK) cells to cancer malignancy. However, the mechanism of miR-218-5p involved in the killing effect of NK cells to LA cells remains poorly understood. MATERIALS AND METHODS: The expression of miR-218-5p was examined by quantitative real-time polymerase chain reaction (qRT-PCR). Serine hydroxymethyl transferase 1 (SHMT1) level was detected by qRT-PCR or western blots. Cytokines production of interferon-γ (IFN-γ) and tumor necrosis factor-α (TNF-α) were detected by ELISA. The killing effect of NK cells to LA cells was investigated using lactate dehydrogenase cytotoxicity assay kit. The interaction of miR-218-5p and SHMT1 was probed by luciferase activity assay. Xenograft model was established to investigate the killing effect of NK cells in vivo. RESULTS: miR-218-5p was enhanced and SHMT1 was inhibited in NK cells of LA patients, whereas stimulation of interleukin-2 (IL-2) reversed their abundances. Addition of miR-218-5p reduced IL-2-induced cytokines expression and cytotoxicity in NK-92 against LA cells. Moreover, SHMT1 was negatively regulated by miR-218-5p and attenuated miR-218-5p-mediated effect on cytotoxicity, IFN-γ and TNF-α secretion in IL-2-activated NK cells. In addition, miR-218-5p exhaustion inhibited tumor growth by promoting killing effect of NK cells. CONCLUSION: miR-218-5p suppresses the killing effect of NK cells to LA cells by targeting SHMT1, providing a potential target for LA treatment by ameliorating NK cells function.

Mechanism for Amplitude Alternans in Electrocardiograms and the Initiation of Spatiotemporal Chaos.

It is widely believed that one major life-threatening transition to chaotic fibrillation occurs via spiral-wave breakup that is preceded by spatiotemporal dispersion of refractoriness due to alternations in the duration of the cardiac action potential (AP). However, recent clinical and experimental evidence suggests that other characteristics of the AP may contribute to, and perhaps drive, this dangerous dynamical instability. To identify the relative roles of AP characteristics, we performed experiments in rabbit hearts under conditions to minimize AP duration dynamics which unmasked pronounced AP amplitude alternans just before the onset of fibrillation. We used a simplified ionic cell model to derive a return map and a stability condition that elucidates a novel underlying mechanism for AP alternans and spiral breakup. We found that inactivation of the sodium current is key to developing amplitude alternans and is directly connected to conduction block and initiation of arrhythmias. Simulations in 2D where AP amplitude alternation led to turbulence confirm our hypothesis.

Germanicol induces selective growth inhibitory effects in human colon HCT-116 and HT29 cancer cells through induction of apoptosis, cell cycle arrest and inhibition of cell migration.

PURPOSE: The main aim of this research was to evaluate the anticancer and apoptotic effects of germanicol - a natural triterpene - in HCT-116 and HT29 human colon cancer cells and deciphering its mode of action by studying its effect on the cell cycle and cell migration. METHODS: Cell cytotoxicity was evaluated by MTT assay, while cell death was assessed by LDH assay. Fluorescence microscopy, using DAPI and acridine orange/ethidium bromide (AO-ETBR), was carried out to evaluate the effect of germanicol on cellular morphology and apoptosis induction. Apoptosis quantification was performed by Annexin V-FITC assay, while cell cycle analysis was performed by flow cytometry using propidium iodide (PI). RESULTS: The results revealed that germanicol showed selective, potent and dose-dependent cytotoxicity in HCT-116 and HT29 human colon cancer cells, while it showed lower cytotoxicity in normal colon cells (human colon fibroblast, CCD-18Co). LDH assay also showed that germanicol induced dose-dependent cell death in HCT-116 and HT29 cells. Fluorescence microscopy revealed that germanicol induced apoptosis via chromatin condensation and DNA damage in HCT-116 colon cancer cells. It also revealed that the percentage of cells with orange and red fluorescence increased when adding a germanicol dose, indicating apoptosis. Germanicol also inhibited cancer cell migration. CONCLUSION: The current findings reveal that germanicol exhibits selective antiproliferative activity against two human colon cancer cells. The normal cell line was less affected by the drug, as compared to the two cancer cell lines, indicating that germanicol will not target normal living cells. The antiproliferative effect was shown to be mediated through the induction of apoptosis and suppression of cell migration.

Association between genetic polymorphisms of inflammatory response genes and the risk of ovarian cancer.

BACKGROUND/PURPOSE: Inflammation plays an important role in promoting ovarian tumorigenesis and cancer progression. However, the relationship between polymorphisms in inflammatory response genes and risk of ovarian cancer remains poorly understood. In this study, we investigated the association of PPARG Pro12Ala, IL6-174G/C, E-selectin S128R, NFKB1-94 ins/del, NFKBIA-826C/T, and ICAM-1 K469E polymorphisms with ovarian cancer risk in a Chinese population. METHODS: Genotyping of the polymorphisms was performed on 687 cases and 687 controls employing the PCR-RFLP technique, and the logistic regression model was used to measure the risk association. RESULTS: A significantly increased risk association was observed for the heterozygous genotypes of PPARG [odds ratio (OR) = 1.52, 95% confidence interval (CI) = 1.01-2.29] and E-selectin (OR = 1.77, 95% CI = 1.07-2.93) polymorphisms, as well as the homozygous ins/ins genotype of NFKB1 polymorphism (OR = 1.39, 95% CI = 1.00-1.92). By contrast, ICAM-1 KE genotype was associated with a decreased ovarian cancer risk (OR = 0.77, 95% CI = 0.60-0.98). In addition, the NFKB1 del/del + NFKBIA TT combination was also found to be associated with a decreased ovarian cancer risk, with OR = 0.12 (95% CI = 0.01-0.95). The associations of the NFKB1 and ICAM-1 polymorphisms replicated the findings of previous reports, assuring the reliability of the results obtained. CONCLUSION: NFKB1 and ICAM-1 polymorphisms could serve as useful ovarian cancer risk prediction biomarkers for the Chinese population, while the utility of PPARG and E-selectin polymorphisms as biomarkers requires further confirmation in independent ovarian cancer cohorts.

[miR-29b Reduces Cisplatin Resistance of Gastric Cancer Cell by Targeting PI3K/Akt Pathway].

OBJECTIVE: To investigate the regulatory effect of miR-29b on gastric cells' resistance to cisplatin. METHODS: The expression of miR-29b in gastric cancer cell line treated with cisplatin concentration gradient was detected using quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. CCK8 was used to measure the cell viability after cisplatin treatment in condition of miR-29b knock-down and overexpression. RESULTS: The expression of miR-29b was significantly upregualted by cisplatin treatment,while its target gene AKT2 was downregulated. The up-regulation of miR-29b enhanced the sensitivity of gastric cancer cells to cisplatin,while the knock-down of miR-29b enhanced the cisplatin resistance. Rescue experiments demonstrated that the miR-29b might regulate cisplatin resistance of gastric cancer cell by targeting PI3K/Akt pathway. The expressions of the other two members of miR-29 family, miR-29a/c, were promoted by cisplatin treatment,but they had no significant effect on gastric cancer cell's resistance to cisplatin. CONCLUSION: miR-29b can enhance the sensitivity of S gastric cancer cell by directly targeting PI3K/Akt pathway.

A human ECG identification system based on ensemble empirical mode decomposition.

In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness.