Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients.

BACKGROUND: Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present. METHODS: The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance. RESULTS: A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses. CONCLUSION: We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.

Bipolar Radiofrequency-Assisted Liposuction for Cervical Contouring in Eastern Asians.

Background: East Asian beauty standards uphold a V-shaped face and a long slender neck. Some patients are dissatisfied with the concurrent nonsurgical treatment and prefer limited downtime with minimally invasive procedures to achieve a natural skin-tightening outcome. The authors performed bipolar radiofrequency-assisted liposuction (RFAL) to achieve cervical rejuvenation. Objectives: To evaluate the efficacy and safety of RFAL for the treatment of cervical skin and soft-tissue laxity in Eastern Asians. Methods: In total, 66 patients with neck skin and soft-tissue laxity were treated with bipolar RFAL under tumescent local anesthesia. Further, the surgical outcomes were evaluated based on patient satisfaction score and the Global Aesthetic Improvement Scale (GAIS) score at 6 months postoperatively. Moreover, the incidence of postoperative complications was determined. Results: All patients were followed up for at least 6 months. After RFAL technologies treatment, significant improvement in the neck contour was observed. The average GAIS score was 3.03 (4, very much improved; 3, much improved; 2, improved; 1, no change; and 0, worsened). Approximately 93% of patients were satisfied with the RFAL neck contouring outcome. Notably, no serious complications requiring further intervention were encountered in this series. Conclusions: The described RFAL treatment significantly improved the refinement of neck contouring in Eastern Asian subjects. The simple, minimally invasive cervical procedure under local anesthesia improve the cervical-mental angle definition, tissue-tightening effect, face slimming, and the mandibular line. No serious adverse events except mild complications were reported. This treatment could achieve extraordinary results with a high safety profile.

An efficient approach for pixel decomposition to increase the spatial resolution of land surface temperature images from MODIS thermal infrared band data.

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world.