Recent Advances in Self-Powered Tactile Sensing for Wearable Electronics.

With the arrival of the Internet of Things era, the demand for tactile sensors continues to grow. However, traditional sensors mostly require an external power supply to meet real-time monitoring, which brings many drawbacks such as short service life, environmental pollution, and difficulty in replacement, which greatly limits their practical applications. Therefore, the development of a passive self-power supply of tactile sensors has become a research hotspot in academia and the industry. In this review, the development of self-powered tactile sensors in the past several years is introduced and discussed. First, the sensing principle of self-powered tactile sensors is introduced. After that, the main performance parameters of the tactile sensors are briefly discussed. Finally, the potential application prospects of the tactile sensors are discussed in detail.

Correlation Analysis of Multi-Scale Ictal EEG Signals in Juvenile Myoclonic Epilepsy.

BACKGROUND: To explore the time-frequency structure and cross-scale coupling of electroencephalography (EEG) signals during seizure in juvenile myoclonic epilepsy (JME), correlations between different leads, as well as dynamic evolution in epileptic discharge, progression and end of seizure were examined. METHODS: EEG data were obtained for 10 subjects with JME and 10 normal controls and were decomposed using gauss continuous wavelet transform (CWT). The phase amplitude coupling (PAC) relationship between the 11th (4.57 Hz) and 17th (0.4 Hz) scale was investigated. Correlations were examined between the 11th and 17th scale EEG signals in different leads during seizure, using multi-scale cross correlation analysis. RESULTS: The time-frequency structure of JME subjects showed strong rhythmic activity in the 11th and 17th scales and a close PAC was identified. Correlation analysis revealed that the ictal JME correlation first increased in the anterior head early in seizure and gradually expanded to the posterior head. CONCLUSION: PAC was exhibited between the 11th and 17th scales during JME seizure. The results revealed that the correlation in the anterior leads was higher than the posterior leads. In the perictal period, the 17th scale EEG signal preceded the 11th scale signal and remained for some time after a seizure. This suggests that the 17th scale signal may play an important role in JME seizure.

Sleep deprivation reduces the baroreflex sensitivity through elevated angiotensin (Ang) II subtype 1 receptor expression in the nucleus tractus solitarii.

Introduction: Sleep insufficiency has been linked to an increased risk of high blood pressure and cardiovascular diseases. Emerging studies have demonstrated that impaired baroreflex sensitivity (BRS) is involved in the adverse cardiovascular effects caused by sleep deprivation, however, the underlying mechanisms remain unknown. Therefore, the present study aims to clarify the role of abnormal renin-angiotensin system in the nucleus tractus solitarii (NTS) in impaired BRS induced by sleep deprivation. Methods: Rats were randomly divided into two groups: normal sleep (Ctrl) and chronic sleep deprivation (CSD) group. Rats were sleep deprived by an automated sleep deprivation system. The blood pressure, heart rate, BRS, the number of c-Fos positive cells and the expression of angiotensin (Ang) II subtype 1 receptors (AT1R) in the NTS of rats were assessed. Results: Compared to Ctrl group, CSD group exhibited a higher blood pressure, heart rate, and reduced BRS. Moreover, the number of c-Fos positive cells and local field potential in the NTS in CSD group were increased compared with the Ctrl group. It was shown that the expression of the AT1R and the content of Ang II and the ratio of Ang II to Ang-(1-7) were increased in the NTS of rats in CSD group compared to Ctrl group. In addition, microinjection of losartan into the NTS significantly improved the impaired BRS caused by sleep deprivation. Discussion: In conclusion, these data suggest that the elevated AT1R expression in the NTS mediates the reduced BRS induced by chronic sleep deprivation.

Wavelet Entropy Analysis of Electroencephalogram Signals During Wake and Different Sleep Stages in Patients with Insomnia Disorder.

Objective: To investigate the changes in the wavelet entropy during wake and different sleep stages in patients with insomnia disorder. Methods: Sixteen patients with insomnia disorder and sixteen normal controls were enrolled. They underwent scale assessment and two consecutive nights of polysomnography (PSG). Wavelet entropy analysis of electroencephalogram (EEG) signals recorded from all participants in the two groups was performed. The changes in the integral wavelet entropy (En) and individual-scale wavelet entropy (En(a)) during wake and different sleep stages in the two groups were observed, and the differences between the two groups were compared. Results: The insomnia disorder group exhibited lower En during the wake stage, and higher En during the N3 stage compared with the normal control group (all P < 0.001). In terms of En(a), patients with insomnia disorder exhibited lower En(a) in the ß and α frequency bands during the wake stage compared with normal controls (ß band, P < 0.01; α band, P < 0.001), whereas they showed higher En(a) in the ß and α frequency bands during the N3 stage than normal controls (ß band, P < 0.001; α band, P < 0.001). Conclusion: Wavelet entropy can reflect the changes in the complexity of EEG signals during wake and different sleep stages in patients with insomnia disorder, which provides a new method and insights about understanding of pathophysiological mechanisms of insomnia disorder. Wavelet entropy provides an objective indicator for assessing sleep quality.

High-throughput imaging through dynamic scattering media based on speckle de-blurring.

Effectively imaging through dynamic scattering media is of great importance and challenge. Some imaging methods based on physical or learning models have been designed for object reconstruction. However, with an increase in exposure time or more drastic changes in the scattering medium, the speckle pattern superimposed during camera integration time undergoes more significant changes, resulting in a modification of the collected speckle structure and increased blurring, which brings significant challenges to the reconstruction. Here, the clearer structural information of blurred speckles is unearthed with a presented speckle de-blurring algorithm, and a high-throughput imaging method through rapidly changing scattering media is proposed for reconstruction under long exposure. For the problem of varying blur degrees in different regions of the speckle, a block-based method is proposed to divide the speckle into distinct sub-speckles, which can realize the reconstruction of hidden objects. The imaging of hidden objects with different complexity through dynamic scattering media is demonstrated, and the reconstruction results are improved significantly for speckles with different blur degrees, which verifies the effectiveness of the method. This method is a high-throughput approach that enables non-invasive imaging solely through the collection of a single speckle. It directly operates on blurred speckles, making it suitable for traditional speckle-correlation methods and deep learning (DL) methods. This provides a new way of thinking about solving practical scattering imaging challenges.

The suppression of cervical cancer ferroptosis by macrophages: The attenuation of ALOX15 in cancer cells by macrophages-derived exosomes.

Induction of cancer cell ferroptosis has been proposed as a potential treatment in several cancer types. Tumor-associated macrophages (TAMs) play a key role in promoting tumor malignant progression and therapy resistance. However, the roles and mechanisms of TAMs in regulating tumor ferroptosis is still unexplored and remains enigmatic. This study shows ferroptosis inducers has shown therapeutic outcomes in cervical cancer in vitro and in vivo. TAMs have been found to suppress cervical cancer cells ferroptosis. Mechanistically, macrophage-derived miRNA-660-5p packaged into exosomes are transported into cancer cells. In cancer cells, miRNA-660-5p attenuates ALOX15 expression to inhibit ferroptosis. Moreover, the upregulation of miRNA-660-5p in macrophages depends on autocrine IL4/IL13-activated STAT6 pathway. Importantly, in clinical cervical cancer cases, ALOX15 is negatively associated with macrophages infiltration, which also raises the possibility that macrophages reduce ALOX15 levels in cervical cancer. Moreover, both univariate and multivariate Cox analyses show ALOX15 expression is independent prognostic factor and positively associated with good prognosis in cervical cancer. Altogether, this study reveals the potential utility of targeting TAMs in ferroptosis-based treatment and ALOX15 as prognosis indicators for cervical cancer.

Valproic acid increases CAR T cell cytotoxicity against acute myeloid leukemia.

The treatment of B cell malignancies has dramatically changed with the introduction of immunotherapy, especially chimeric antigen receptor T (CAR-T) cell therapy. However, only limited efficacy is observed in acute myeloid leukaemia (AML). In the study, We detected CD123 and CLL-1 expression on leukaemia cells from Relapsed/Refractory AML (R/R AML) patients. Then, we constructed anti-CD123 CAR and CLL-1 CAR with different co-stimulation domains (CD28 or 4-1BB) and detected their anti-AML effects. To increase the efficacy of CAR-T cell therapy, we tested different strategies, including application of combined checkpoint inhibitors and histone deacetylase inhibitors (HDACi) in vivo and in vitro We found CD123 and CLL-1 were highly expressed on AML cells. The proportions of T cell subsets and NK cells involved in anti-tumour or anti-inflammation processes in AML patients significantly decreased when compared with healthy donors. Both CD123 CAR and CLL-1 CAR displayed specific anti-AML effects in vitro To improve the lysis effects of CAR-T cells, we combined CAR-T cell therapy with different agents. PD-1/PD-L1 antibodies only slightly improved the potency of CAR-T cell therapy (CD123 CAR-T 60.92% ± 2.9087% vs. 65.43% ± 2.1893%, 60.92% ± 2.9087% vs. 67.43% ± 3.4973%; 37.37% ± 3.908% vs. 41.89% ± 5.1568%, 37.37% ± 3.908% vs. 42.84% ± 4.2635%). However, one HDACi (valproic acid [VPA]) significantly improved CAR-T cell potency against AML cells (CLL-1 CAR-T 34.97% ± 0.3051% vs. 88.167% ± 1.5327%, p < 0.0001; CD123 CAR-T 26.87% ± 2.7010% vs. 82.56% ± 3.086%, p < 0.0001 in MV411; CLL-1 CAR-T 78.77% ± 1.2061% vs. 93.743% ± 1.2333%, p < 0.0001; CD123 CAR-T 64.10% ± 1.5130% vs. 94.427% ± 0.142%, p = 0.0001 in THP-1). Combination therapy prolonged the overall survival of mice when compared with single CD123 CAR-T cell therapy (median survival: 180 days vs. unfollowed). A possible mechanism is that activated CD8+T cells upregulate natural-killer group 2 member D (NKG2D), and VPA upregulates NKG2D ligand expression in AML cells, contributing to NKG2D-mediated cytotoxicity of CAR-T cells against tumour cells. In conclusion, CD123 and CLL-1 are promising targets for AML CAR-T cell therapy. A combination of VPA pre-treatment and CAR-T against AML exhibits synergic effects.

Alpha Rhythm Wavelength of Electroencephalography Signals as a Diagnostic Biomarker for Alzheimer's Disease.

OBJECTIVE: To explore changes in the alpha rhythm wavelength of background electroencephalography in Alzheimer's disease patients with different degrees of dementia in a resting state; examine their correlation with the degree of cognitive impairment; determine whether the alpha rhythm wavelength can distinguish mild Alzheimer's disease patients, moderately severe Alzheimer's disease patients, and healthy controls at the individual level; and identify a cut-off value to differentiate Alzheimer's disease patients from healthy controls. METHODS: Quantitative electroencephalography signals of 42 patients with mild Alzheimer's disease, 42 patients with moderately severe Alzheimer's disease, and 40 healthy controls during rest state with eyes closed were analyzed using wavelet transform. Electroencephalography signals were decomposed into different scales, and their segments were superimposed according to the same length (wavelength and amplitude) and phase alignment. Phase averaging was performed to obtain average phase waveforms of the desired scales of each lead. The alpha-band wavelengths corresponding to the ninth scale of the background rhythm of different leads were compared between groups. RESULTS: The average wavelength of the alpha rhythm phase of the whole-brain electroencephalography signals in Alzheimer's disease patients was prolonged and positively correlated with the severity of cognitive dysfunction (P < 0.01). The ninth-scale phase average wavelength of each lead had high diagnostic efficacy for Alzheimer's disease, and the diagnostic efficacy of lead P3 (area under the receiver operating characteristic curve = 0.873) was the highest. CONCLUSION: The average wavelength of the electroencephalography alpha rhythm phase may be used as a quantitative feature for the diagnosis of Alzheimer's disease, and the slowing of the alpha rhythm may be an important neuro-electrophysiological index for disease evaluation.

Construction of high-dimensional cyclic symmetric chaotic map with one-dimensional chaotic map and its security application.

Classical one-dimensional chaotic map has many ideal characteristics which is quite suitable for many different kinds of scientific fields, especially cryptography. In this paper, we propose an idea of constructing high-dimensional (HD) cyclic symmetric chaotic maps by using one-dimensional (1D) chaotic map. Two constructed 3D cyclic symmetric chaotic maps are taken as the examples, named three-dimensional cyclic symmetric logistic map (3D-CSLM) and three-dimensional cyclic symmetric Chebyshev map (3D-CSCM), respectively. Numerical experiments show that the new maps possesses better dynamical performances, and their parameters have a wider range, compared with the original map. Furthermore, to verify its effect in image encryption, a novel image encryption algorithm based on 3D-CSLM and DNA coding is proposed. DNA method for image encryption can improve the efficiency of permutation and diffusion. Firstly, the algorithm uses 3D-CSLM to generate chaotic sequences for DNA operation rule selection and pixel permutation. Then through the DNA XOR operation to achieve diffusion, and finally form an encrypted image. Several simulation tests results indicate that the proposal has a promising security performance and strong anti-attack ability.

Identification of ferroptosis-related signature with potential implications in prognosis and immunotherapy of renal cell carcinoma.

Developing individualized therapies for different renal cell carcinoma patients is pivotal for improving the efficacy of immunotherapy. It has been reported that ferroptosis is involved in T cell-mediated anti-tumor immunity, and that therapeutic approaches targeting tumor ferroptosis pathway in combination with immune checkpoint blockade drugs improve the efficacy of cancer immunotherapy. This study focused specifically on ferroptosis genes to identify novel biomarkers that reflect prognosis in different renal cell carcinoma subtypes. LASSO algorithm and multivariate Cox regression were initiated for identifying ferroptosis-related multigene risk signature (FRGsig) and established a FRGsig score model. We used multiple tumor microenvironment gene signatures and methods to infer tumor microenvironment status and immune cell invasion levels. Our study found that high FRGsig score was associated with poor prognosis in patients with predominant histologic subtypes of renal cell carcinoma. And high FRGsig score samples had higher levels of anti-tumor immunity cells infiltration, and there was a feedback mechanism whereby anti-tumor inflammation promoted the recruitment or differentiation of immunosuppressive cells. FRGsig was a potential biomarker for predicting the response to immune checkpoint blockade therapy in kidney clear cell carcinoma and kidney papillary cell carcinoma, and the kidney papillary cell carcinoma patients with high FRGsig was associated with better response to anti-VEGF therapy. Our findings provided further insights into assessing immunotherapy sensitivity of predominant histologic subtypes of renal cell carcinoma. FRGsig might be a potential biomarker for predicting the efficacy of angiogenic blocking drugs or immune checkpoint inhibitors in different renal cell carcinoma subtypes, enabling more precise patient selection.

A novel HNRNPH1::ERG rearrangement in aggressive acute myeloid leukemia.

FUS::ERG rearrangement is a recurrent abnormality seen in a subgroup of acute myeloid leukemia (AML) with a poor prognosis. We described here a novel HNRNPH1::ERG rearrangement in a de novo AML. The patient was unresponsive to routine chemotherapy and succumbed to the disease just 3 months after diagnosis. Two additional cases of AML with HNRNPH1::ERG rearrangement were discovered by searching a publicly available sequencing database. The three patients share several clinical phenotypes with the FUS::ERG rearranged AML, including high blast count at diagnosis, pediatric or young adult-onset, and poor overall survival. In addition, hnRNPH1 and FUS are both hnRNP family members, a group of RNA-binding proteins functioning in RNA metabolism and transport. Therefore, we suggest that patients with HNRNPH1::ERG or FUS::ERG rearrangement belong to the same distinct clinicopathologic subtype of AML, that is, AML with ERG rearrangement. Based on a previous study showing that FUS::ERG binds to the retinoic acid-responsive elements and that all-trans retinoic acid-induced cell differentiation of AML cells, we support the clinical evaluation of an APL-like therapeutic regimen for AML with ERG rearrangement.

Effect of PD-1 Inhibitor Combined with X-Ray Irradiation on the Inflammatory Microenvironment and Lung Tissue Injury in Mice.

PURPOSE: This study was designed to evaluate the effects of PD-1 inhibitor on lung tissue morphology and the immune system in a mouse model of radiation-induced lung injury (RILI) and to assess interactions between radiation therapy and PD-1 inhibition. METHODS: Twenty C57BL/6 mice were divided randomly into four groups of five mice each. Mice were treated with an anti-mouse PD-1 monoclonal antibody, whole thorax irradiation, both or neither. Lung tissue morphology and pathological changes were assessed by hematoxylin-eosin staining; lung fibrosis was assessed by Masson staining and analysis of hydroxyproline; CD3+, CD4+, and CD8+ T lymphocytes in lung tissues were detected immunohistochemically; and the concentrations of transforming growth factor-ß1 (TGF-ß1) and interleukin-6 (IL-6) in lung tissue were evaluated by cytokine multiplex analysis. RESULTS: Lung injury scores and indicators of pulmonary fibrosis were higher in mice administration whole thorax irradiation than in control mice. Inflammatory infiltrate scores, alveoli deformation scores, collagen volume fractions and hydroxyproline contents in lung tissues were all significantly higher in mice administered PD-1 inhibitor plus irradiation than in the other three groups. Similarly, the percentages of CD3+ and CD8+T cells and the concentrations of IL-6 and TGF-ß1 in lung tissue were significantly higher in mice treated with radiation and PD-1 inhibitor than in the other groups. However, PD-1 inhibitor and irradiation interacted significantly only in the elevation of TGF-ß1 level. CONCLUSION: Whole thorax X-ray irradiation in mice can cause pulmonary injury and fibrosis, which could be exacerbated by PD-1 inhibitors. Radiotherapy combined with PD-1 inhibitors may aggravate RILI by synergistically upregulating TGF-ß1 expression, thereby affecting the immune-inflammatory microenvironment in the lungs.

Joint Constraints Based Dynamic Calibration of IMU Position on Lower Limbs in IMU-MoCap.

The position calibration of inertial measurement units (IMUs) is an important part of human motion capture, especially in wearable systems. In realistic applications, static calibration is quickly invalid during the motions for IMUs loosely mounted on the body. In this paper, we propose a dynamic position calibration algorithm for IMUs mounted on the waist, upper leg, lower leg, and foot based on joint constraints. To solve the problem of IMUs' position displacement, we introduce the Gauss-Newton (GN) method based on the Jacobian matrix, the dynamic weight particle swarm optimization (DWPSO), and the grey wolf optimizer (GWO) to realize IMUs' position calibration. Furthermore, we establish the coordinate system of human lower limbs to estimate each joint angle and use the fusion algorithm in the field of quaternions to improve the attitude calibration performance of a single IMU. The performances of these three algorithms are analyzed and evaluated by gait tests on the human body and comparisons with a high-precision IMU-Mocap reference device. The simulation results show that the three algorithms can effectively calibrate the IMU's position for human lower limbs. Additionally, when the degree of freedom (DOF) of a certain dimension is limited, the performances of the DWPSO and GWO may be better than GN, when the joint changes sufficiently, the performances of the three are close. The results confirm that the dynamic calibration algorithm based on joint constraints can effectively reduce the position offset errors of IMUs on upper or lower limbs in practical applications.

A Bit Shift Image Encryption Algorithm Based on Double Chaotic Systems.

A chaotic system refers to a deterministic system with seemingly random irregular motion, and its behavior is uncertain, unrepeatable, and unpredictable. In recent years, researchers have proposed various image encryption schemes based on a single low-dimensional or high-dimensional chaotic system, but many algorithms have problems such as low security. Therefore, designing a good chaotic system and encryption scheme is very important for encryption algorithms. This paper constructs a new double chaotic system based on tent mapping and logistic mapping. In order to verify the practicability and feasibility of the new chaotic system, a displacement image encryption algorithm based on the new chaotic system was subsequently proposed. This paper proposes a displacement image encryption algorithm based on the new chaotic system. The algorithm uses an improved new nonlinear feedback function to generate two random sequences, one of which is used to generate the index sequence, the other is used to generate the encryption matrix, and the index sequence is used to control the generation of the encryption matrix required for encryption. Then, the encryption matrix and the scrambling matrix are XORed to obtain the first encryption image. Finally, a bit-shift encryption method is adopted to prevent the harm caused by key leakage and to improve the security of the algorithm. Numerical experiments show that the key space of the algorithm is not only large, but also the key sensitivity is relatively high, and it has good resistance to various attacks. The analysis shows that this algorithm has certain competitive advantages compared with other encryption algorithms.

ARMA-Based Segmentation of Human Limb Motion Sequences.

With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap data collection in different scenarios and applications, effective segmentation of MoCap data is becoming a crucial issue for further human motion posture and behavior analysis, which requires both robustness and computation efficiency in the algorithm design. In this paper, we propose an unsupervised segmentation algorithm based on limb-bone partition angle body structural representation and autoregressive moving average (ARMA) model fitting. The collected MoCap data were converted into the angle sequence formed by the human limb-bone partition segment and the central spine segment. The limb angle sequences are matched by the ARMA model, and the segmentation points of the limb angle sequences are distinguished by analyzing the good of fitness of the ARMA model. A medial filtering algorithm is proposed to ensemble the segmentation results from individual limb motion sequences. A set of MoCap measurements were also conducted to evaluate the algorithm including typical body motions collected from subjects of different heights, and were labeled by manual segmentation. The proposed algorithm is compared with the principle component analysis (PCA), K-means clustering algorithm (K-means), and back propagation (BP) neural-network-based segmentation algorithms, which shows higher segmentation accuracy due to a more semantic description of human motions by limb-bone partition angles. The results highlight the efficiency and performance of the proposed algorithm, and reveals the potentials of this segmentation model on analyzing inter- and intra-motion sequence distinguishing.

Photobiomodulation therapy for hair regeneration: A synergetic activation of ß-CATENIN in hair follicle stem cells by ROS and paracrine WNTs.

Photobiomodulation therapy (PBMT) has shown encouraging results in the treatment of hair loss. However, the mechanism by which PBMT controls cell behavior to coordinate hair cycle is unclear. Here, PBMT is found to drive quiescent hair follicle stem cell (HFSC) activation and alleviate hair follicle atrophy. Mechanistically, PBMT triggers a new hair cycle by upregulating ß-CATENIN expression in HFSCs. Loss of ß-Catenin (Ctnnb1) in HFSCs blocked PBMT-induced hair regeneration. Additionally, we show PBMT-induced reactive oxygen species (ROS) activate the PI3K/AKT/GSK-3ß signaling pathway to inhibit proteasome degradation of ß-CATENIN in HFSCs. Furthermore, PBMT promotes the expression and secretion of WNTs in skin-derived precursors (SKPs) to further activate the ß-CATENIN signal in HFSCs. By contrast, eliminating ROS or inhibiting WNT secretion attenuates the activation of HFSCs triggered by PBMT. Collectively, our work suggests that PBMT promotes hair regeneration through synergetic activation of ß-CATENIN in HFSCs by ROS and paracrine WNTs by SKPs.

Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis.

BACKGROUND: The purpose of present study was to identify the differentially expressed genes (DEGs) associated with BMP-9-induced osteogenic differentiation of mesenchymal stem cells (MSCs) by using bioinformatics methods. METHODS: Gene expression profiles of BMP-9-induced MSCs were compared between with GFP-induced MSCs and BMP-9-induced MSCs. GSE48882 containing two groups of gene expression profiles, 3 GFP-induced MSC samples and 3 from BMP-9-induced MSCs, was downloaded from the Gene Expression Omnibus (GEO) database. Then, DEGs were clustered based on functions and signaling pathways with significant enrichment analysis. Pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that the identified DEGs were potentially involved in cytoplasm, nucleus, and extracellular exosome signaling pathway. RESULTS: A total of 1967 DEGs (1029 upregulated and 938 downregulated) were identified from GSE48882 datasets. R/Bioconductor package limma was used to identify the DEGs. Further analysis revealed that there were 35 common DEGs observed between the samples. GO function and KEGG pathway enrichment analysis, among which endoplasmic reticulum, protein export, RNA transport, and apoptosis was the most significant dysregulated pathway. The result of protein-protein interaction (PPI) network modules demonstrated that the Hspa5, P4hb, Sec61a1, Smarca2, Pdia3, Dnajc3, Hyou1, Smad7, Derl1, and Surf4 were the high-degree hub nodes. CONCLUSION: Taken above, using integrated bioinformatical analysis, we have identified DEGs candidate genes and pathways in BMP-9 induced MSCs, which could improve our understanding of the key genes and pathways for BMP-9-induced osteogenic of MSCs.

Prognostic Model to Predict Overall Survival for Metastatic Non-Small Cell Lung Cancer Patients Treated With Chemotherapy Combined With Concurrent Radiation Therapy to the Primary Tumor: Analysis From Two Prospective Studies.

PURPOSE: The role of radiotherapy, in addition to chemotherapy, has not been thoroughly determined in metastatic non-small cell lung cancer (NSCLC). The purpose of the study was to investigate the prognostic factors and to establish a model for the prediction of overall survival (OS) in metastatic NSCLC patients who received chemotherapy combined with the radiation therapy to the primary tumor. METHODS: The study retrospectively reviewed 243 patients with metastatic NSCLC in two prospective studies. A prognostic model was established based on the results of the Cox regression analysis. RESULTS: Multivariate analysis showed that being male, Karnofsky Performance Status score < 80, the number of chemotherapy cycles <4, hemoglobin level ≤120 g/L, the count of neutrophils greater than 5.8 ×109/L, and the count of platelets greater than 220 ×109/L independently predicted worse OS. According to the number of risk factors, patients were further divided into one of three risk groups: those having ≤ 2 risk factors were scored as the low-risk group, those having 3 risk factors were scored as the moderate-risk group, and those having ≥ 4 risk factors were scored as the high-risk group. In the low-risk group, 1-year OS is 67.7%, 2-year OS is 32.1%, and 3-year OS is 19.3%; in the moderate-risk group, 1-year OS is 59.6%, 2-year OS is 18.0%, and 3-year OS is 7.9%; the corresponding OS rates for the high-risk group were 26.2%, 7.9%, and 0% (P<0.001) respectively. CONCLUSION: Metastatic NSCLC patients treated with chemotherapy in combination with thoracic radiation may be classified as low-risk, moderate-risk, or high-risk group using six independent prognostic factors. This prognostic model may help design the study and develop the plans of individualized treatment.

Cisplatin-induced ototoxicity: Updates on molecular mechanisms and otoprotective strategies.

Cisplatin is a highly effective antitumor drug generally used in the treatment of solid malignant tumors. However, cisplatin causes severe side effects such as bone marrow depression, nephrotoxicity, and ototoxicity, thus limiting its clinical application. The incidence of ototoxicity induced by cisplatin ranges from 20% to 70%, and it usually manifests as a progressive, bilateral and irreversible hearing loss. Although the etiology of cisplatin-induced ototoxicity remains unclear, an increasing body of evidence suggests that the ototoxicity of cisplatin is mainly related to the production of reactive oxygen species and activation of apoptotic pathway in cochlear tissues. Many drugs have been well proved to protect cisplatin-induced hearing loss in vitro and in vivo. However, the anti-tumor effect of cisplatin is also weakened by systemic administration of those drugs for hearing protection, especially antioxidants. Therefore, establishing a local administration strategy contributes to the otoprotection without affecting the effect of cisplatin. This review introduces the pathology of ototoxicity caused by cisplatin, and focuses on recent developments in the mechanisms and protective strategies of cisplatin-induced ototoxicity.