A novel risk model based on cuproptosis-related lncRNAs predicted prognosis and indicated immune microenvironment landscape of patients with cutaneous melanoma.

Cutaneous melanoma (CM) is an aggressive form of malignancy with poor prognostic value. Cuproptosis is a novel type of cell death regulatory mechanism in tumors. However, the role of cuproptosis-related long noncoding RNAs (lncRNAs) in CM remains elusive. The cuproptosis-related lncRNAs were identified using the Pearson correlation algorithm. Through the univariate and multivariate Cox regression analysis, the prognosis of seven lncRNAs associated with cuproptosis was established and a new risk model was constructed. ESTIMATE, CIBERSORT, and single sample gene set enrichment analyses (ssGSEA) were applied to evaluate the immune microenvironment landscape. The Kaplan-Meier survival analysis revealed that the overall survival (OS) of CM patients in the high-risk group was remarkably lower than that of the low-risk group. The result of the validated cohort and the training cohort indicated that the risk model could produce an accurate prediction of the prognosis of CM. The nomogram result demonstrated that the risk score based on the seven prognostic cuproptosis-related lncRNAs was an independent prognostic indicator feature that distinguished it from other clinical features. The result of the immune microenvironment landscape indicated that the low-risk group showed better immunity than high-risk group. The immunophenoscore (IPS) and immune checkpoints results conveyed a better benefit potential for immunotherapy clinical application in the low-risk groups. The enrichment analysis and the gene set variation analysis (GSVA) were adopted to reveal the role of cuproptosis-related lncRNAs mediated by the immune-related signaling pathways in the development of CM. Altogether, the construction of the risk model based on cuproptosis-related lncRNAs can accurately predict the prognosis of CM and indicate the immune microenvironment of CM, providing a new perspective for the future clinical treatment of CM.

Molecular Mechanism of D1135E-Induced Discriminated CRISPR-Cas9 PAM Recognition.

The off-target effects of Streptococcus pyogenes Cas9 (SpCas9) pose a significant challenge to harness it as a therapeutical approach. Two major factors can result in SpCas9 off-targeting: tolerance to target DNA-guide RNA (gRNA) mismatch and less stringent recognition of protospacer adjacent motif (PAM) flanking the target DNA. Despite the abundance of engineered SpCas9-gRNA variants with improved sensitivity to target DNA-gRNA mismatch, studies focusing on enhancing SpCas9 PAM recognition stringency are quite few. A recent pioneering study identified a D1135E variant of SpCas9 that exhibits much-reduced editing activity at the noncanonical NAG/NGA PAM sites while preserving robust on-target activity at the canonical NGG-flanking sites (N is any nucleobase). Herein, we aim to clarify the molecular mechanism by which this single D1135E mutation confers on SpCas9 enhanced specificity for PAM recognition by molecular dynamics simulations. The results suggest that the variant maintains the base-specific recognition for the canonical NGG PAM via four hydrogen bonds, akin to that in the wild type (WT) SpCas9. While the noncanonical NAG PAM is engaged to the two PAM-interacting arginine residues (i.e., R1333 and R1335) in WT SpCas9 via two to three hydrogen bonds, the D1135E variant prefers to establish two hydrogen bonds with the PAM bases, accounting for its minimal editing activity on the off-target sites with an NAG PAM. The impaired NAG recognition by D1135E SpCas9 results from the PAM duplex displacement such that the hydrogen bond of R1333 to the second PAM base is disfavored. We further propose a mechanistic model to delineate how the mutation perturbs the noncanonical PAM recognition. We anticipate that the mechanistic knowledge could be leveraged for continuous optimization of SpCas9 PAM recognition specificity toward high-precision demanding applications.

Clinical Evidence and Potential Mechanisms of Complementary Treatment of Ling Gui Zhu Gan Formula for the Management of Serum Lipids and Obesity.

Objective: This study aims to evaluate the clinical effects of Ling Gui Zhu Gan formula (LGZG), a famous TCM formula, for the management of serum lipids and obesity and preliminarily elucidates the bioactive components and the potential mechanism. Methods: Cluster analysis was adopted to investigate the TCM herbs and their frequency of occurrence for treating hyperlipidemia and obesity in an academic experience database of Chinese famous TCM doctors (http://www.gjmlzy.com:83). Then, relevant randomized controlled trials (RCTs) about LGZG supplementation in improving lipid levels and obesity were retrieved and analyzed. Lastly, the integration of network pharmacology, as well as greedy algorithms, which are theoretically well founded for the set cover in computer science, was exploited to identify the bioactive components of LGZG and to reveal potential mechanisms for attenuation or reversal of hyperlipidemia and obesity. Results: Based on the cluster analysis of 104 cases in TCM academic experience database, four TCM herbs in LGZG showed high-use frequency for treating hyperlipidemia and obesity. Meta-analysis on 19 randomized controlled trials (RCTs) with 1716 participants indicated that LGZG supplementation significantly decreased the serum levels of total triglycerides, total cholesterol, low-density lipoprotein cholesterol, BMI, and body weight and increased high-density lipoprotein cholesterol, compared with clinical control groups. No serious adverse effect was detected in all studies. Twenty-one bioactive components of LGZG, mainly flavonoids (i.e., naringenin, kaempferol, and kumatakenin), saponins (i.e., hederagenin), and fatty acids (i.e., eicosenoic acid), had the potential benefits possibly by regulating multiple targets such as PTPN1, CYP19A1, and ESR2, as well as a few complex pathways including the TNF signaling pathway, PPAR signaling pathway, arachidonic acid metabolism, fat digestion, and absorption. Conclusion: The present study has proved the clinical value of LGZG as a complementary treatment for attenuation or reversal of hyperlipidemia and obesity. More high-quality clinical and experimental studies in the future are demanded to verify its effects and the precise mechanism of action.

Comparing analysis of multispectral and polarimetric imaging for mid-infrared detection blindness condition.

When detection blindness occurs due to thermal crossover for conventional broadband mid-infrared (IR) imaging, multispectral and polarimetric imaging present their advantages in solving the problem to some extent. However, neither of them is satisfactory for all application environments. In this paper, we demonstrate two types of detection blindness situations, analyze their corresponding mechanism, and identify the respective optimum application condition for multispectral and polarimetric imaging. First, a brief classification about a detection blindness situation that arises from self-radiation or reflected radiation of an object is presented. Second, based on the blindness model and detection mechanism, multispectral imaging is analyzed as superior in the emitted radiation dominant scene, while polarimetric imaging is more suitable in the field of the reflection dominant scene. Thirdly, a multispectral prototype and a polarimetric prototype for mid-IR thermal imaging are made and used to conduct a test experiment in two different environmental scenarios. The experimental results show that the multispectral and polarimetric mid-IR imaging systems can enhance the contrast of the detected images when traditional thermal imagery fails. In particular, the multispectral image has a high contrast in the scene that the emitted radiation is dominant over the ambient IR loading, such as the target and background of 295 K below a relatively less sunny sky, while the polarimetric imaging is more suitable in the scene where the reflection is dominant when the ambient IR loading is adequate, which is when the direct solar radiation is relatively strong.

Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 µm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.