An Online Model for Central Lymph Node Metastases in Papillary Thyroid Carcinoma With BRAF V600E Mutation.

BACKGROUND: To construct a predictive model to direct the dissection of the central lymph nodes in papillary thyroid cancer (PTC) with BRAF V600E mutation by identifying the risk variables for central lymph node metastases (CLNM). METHODS: Data from 466 PTC patients with BRAF V600E mutations underwent thyroid surgery was collected and analyzed retrospectively. For these patients, we conducted univariate and multivariate logistic regression analysis to find risk variables for CLNM. To construct a nomogram, the independent predictors were chosen. The calibration, discrimination, and clinical utility of the predictive model were assessed by training and validation data. RESULTS: CLNM was present in 323/466 PTC patients with BRAF V600E mutations. By using univariate and multivariate logistic regression, we discovered that gender, age, tumor size, multifocality, and pathological subtype were all independent predictors of CLNM in PTC patients with BRAF V600E mutations. A predictive nomogram was created by combining these variables. In both training and validation groups, the nomogram demonstrated great calibration capacities. The training and validation groups' areas under the curve (AUC) were 0.772 (specificity 0.694, sensitivity 0.728, 95% CI: 0.7195-0.8247) and 0.731 (specificity 0.778, sensitivity 0.653, 95% CI: 0.6386-0.8232) respectively. According to the nomogram's decision curve analysis (DCA), the nomogram might be beneficial. As well, an online dynamic calculator was developed to make the application of this nomogram easier in the clinic. CONCLUSION: An online nomogram model based on the 5 predictors included gender, age, pathological subtype, multifocality, and tumor size was confirmed to predict CLNM and guide the central lymph nodes dissection in PTC patients with BRAF V600E mutations.

A Web-based Prediction Model for Early Death in Patients With Metastatic Triple-negative Breast Cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2. This subtype of breast cancer is known for its high aggressiveness, high metastatic potential, tendency for recurrence, and poor prognosis. Patients with metastatic TNBC (mTNBC) have a poorer prognosis and a higher likelihood of early death (survival time ≤3 months). Therefore, the development of effective individualized survival prediction tools, such as prediction nomograms and web-based survival calculators, is of great importance for predicting the probability of early death in patients with metastatic TNBC. METHODS: Patients diagnosed with mTNBC in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were included in the model construction. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with early death in patients with mTNBC and predictive prognostic nomograms were constructed. The accuracy of the nomograms was verified using receiver operating characteristic curves, and GiViTi Calibration belt plots were used to evaluate the model consistency. The clinical applicability of the nomograms was evaluated using decision curve analysis. On the basis of the predictive prognostic nomograms, a network survival rate calculator was developed for individualized survival prediction in patients with mTNBC. RESULTS: A total of 2230 patients diagnosed with mTNBC were included in the Surveillance, Epidemiology, and End Results database for this study. After strict exclusion criteria, 1428 patients were found to be eligible for the study. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. Independent risk factors for mTNBC, including age, tumor size, brain metastasis, liver metastasis, surgery, and chemotherapy, were identified and integrated to construct the prediction nomogram and survival calculator. Results of receiver operating characteristic curves, calibration curves, and decision curve analysis curves from the training and validation cohort confirmed that the developed nomogram and web-based survival calculator in this study could accurately predict the probability of early death in patients with mTNBC. CONCLUSIONS: In this study, we developed a reliable prediction nomogram and web-based survival calculator for predicting the probability of early death in patients with mTNBC. These tools can assist clinical physicians in identifying high-risk patients and developing personalized treatment plans as early as possible.

The visual stimulation in disorders of consciousness.

Severe brain damage usually leads to disorders of consciousness (DOC), which include coma, unresponsive wakefulness syndrome (UWS) and a minimally conscious state (MCS). Visual stimulation is widely used, especially in the diagnosis and treatment and treatment of DOC. Researchers have indicated that tests based on visual stimulation including visual pursuit, when used in conjunction with the Coma Recovery Scale-Revised, are able to differentiate between UWS from an MCS. Recently, targeting patients' circadian rhythms has been proposed to be a possible treatment target for DOC. Indeed, light therapy has been applied in some other fields, including treating seasonal affective disorder, sleep problems, and Parkinson's disease. However, at present, although visual stimulation and light therapy are frequently used in DOC, there is still no international unified standard. Therefore, we recommend the development of an international consensus in regard to the definitions, operational criteria and assessment procedures of visual stimulation and light therapy. This review combines visual stimulation, circadian rhythm recovery, and light therapy in DOC patients and presents the mechanisms and current advances in applications related to light therapy and visual stimulation in an attempt to provide additional ideas for future research and treatment of DOC.

Metabolic Intervention Liposome Boosted Lung Cancer Radio-Immunotherapy via Hypoxia Amelioration and PD-L1 Restraint.

At present, radiotherapy (RT) still acquires limited success in clinical due to the lessened DNA damage under hypoxia and acquired immune tolerance owing to the amplified programmed death ligand-1 (PD-L1) expression. Incredibly, intracellular PD-L1 expression depression is proven to better sensitize RT by inhibiting DNA damage repair. However, the disability of the clinically used antibodies in disrupting the extracellular PD-L1function still limits the effectiveness of radio-immunotherapy. Therefore, better PD-L1 regulation strategies are still urgently needed to better sensitize radio-immunotherapy. Hence, for this purpose, TPP-LND is synthesized by linking mitochondrial-targeted triphenylphosphine cations (TPP+ ) to the antineoplastic agent lonidamine (LND), which significantly reduces the dose needed for LND to induce effective oxidative phosphorylation inhibition (2 vs 300 µM). Then, TPP-LND is wrapped with liposomes to form TPP-LND@Lip nanoparticles. By doing this, TPP-LND@Lip nanoparticles can sensitize RT by reversing the hypoxic microenvironment of tumors to generate more DNA damage and reducing the expression of PD-L1 via enhancing the adenosine 5'-monophosphate-activated protein kinase activation. As expected, these well-designed economical TPP-LND@Lip nanoparticles are more effective than conventional anti-PD-L1 antibodies to some extent.

G2-LIKE CAROTENOID REGULATOR (SlGCR) is a positive regulator of lutein biosynthesis in tomato.

Lutein is an oxygen-containing carotenoid synthesized in plant chloroplasts and chromoplasts. It plays an indispensable role in promoting plant growth and maintaining eye health in humans. The rate-limiting step of lutein biosynthesis is catalyzed by the lycopene ε-cyclase enzyme (LCYE). Although great progress has been made in the identification of transcription factors involved in the lutein biosynthetic pathway, many systematic molecular mechanisms remain to be elucidated. Here, using co-expression analysis, we identified a gene, G2-LIKE CAROTENOID REGULATOR (SlGCR), encoding a GARP G2-like transcription factor, as the potential regulator of SlLCYE in tomato. Silencing of SlGCR reduced the expression of carotenoid biosynthetic genes and the accumulation of carotenoids in tomato leaves. By contrast, overexpression of SlGCR in tomato fruit significantly increased the expression of relevant genes and enhanced the accumulation of carotenoids. SlGCR can directly bind to the SlLCYE promoter and activate its expression. In addition, we also discovered that expression of SlGCR was negatively regulated by the master regulator SlRIN, thereby inhibiting lutein synthesis during tomato fruit ripening. Taken together, we identified SlGCR as a novel regulator involved in tomato lutein biosynthesis, elucidated the regulatory mechanism, and provided a potential tool for tomato lutein metabolic engineering. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-022-00088-z.

Enrichment of health-promoting lutein and zeaxanthin in tomato fruit through metabolic engineering.

Carotenoids constitute a large group of natural pigments widely distributed in nature. These compounds not only provide fruits and flowers with distinctive colors, but also have significant health benefits for humans. Lutein and zeaxanthin, both oxygen-containing carotenoids, are considered to play vital roles in promoting ocular development and maintaining eye health. However, humans and mammals cannot synthesize these carotenoid derivatives, which can only be taken from certain fruits or vegetables. Here, by introducing four endogenous synthetic genes, SlLCYE, SlLCYB, SlHYDB, and SlHYDE under fruit-specific promoters, we report the metabolic engineering of lutein/zeaxanthin biosynthesis in tomato fruit. Transgenic lines overexpression of one (SlLCYE), two (SlLCYE and SlLCYB; SlLCYB and SlHYDB), and all these four synthetic genes re-established the lutein/zeaxanthin biosynthetic pathways in the ripe tomato fruit and thus resulted in various types of carotenoid riched lines. Metabolic analyses of these engineered tomato fruits showed the strategy involved expression of SlLCYE tends to produce α-carotene and lutein, as well as a higher content of ß-carotene and zeaxanthin was detected in lines overexpressing SlLCYB. In addition, the different combinations of engineered tomatoes with riched carotenoids showed higher antioxidant capacity and were associated with a significantly extended shelf life during postharvest storage. This work provides a successful example of accurate metabolic engineering in tomato fruit, suggesting the potential utility for synthetic biology to improve agronomic traits in crops. These biofortified tomato fruits could be also exploited as new research subjects for studying the health benefits of carotenoid derivatives.

SlWRKY35 positively regulates carotenoid biosynthesis by activating the MEP pathway in tomato fruit.

Carotenoids are vital phytonutrients widely recognised for their health benefits. Therefore, it is vital to thoroughly investigate the metabolic regulatory network underlying carotenoid biosynthesis and accumulation to open new leads towards improving their contents in vegetables and crops. The outcome of our study defines SlWRKY35 as a positive regulator of carotenoid biosynthesis in tomato. SlWRKY35 can directly activate the expression of the 1-deoxy-d-xylulose 5-phosphate synthase (SlDXS1) gene to reprogramme metabolism towards the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway, leading to enhanced carotenoid accumulation. We also show that the master regulator SlRIN directly regulates the expression of SlWRKY35 during tomato fruit ripening. Compared with the SlLCYE overexpression lines, coexpression of SlWRKY35 and SlLCYE can further enhance lutein production in transgenic tomato fruit, indicating that SlWRKY35 represents a potential target towards designing innovative metabolic engineering strategies for carotenoid derivatives. In addition to providing new insights into the metabolic regulatory network associated with tomato fruit ripening, our data define a new tool for improving fruit content in specific carotenoid compounds.

Development and validation of an interpretable radiomic nomogram for severe radiation proctitis prediction in postoperative cervical cancer patients.

Background: Radiation proctitis is a common complication after radiotherapy for cervical cancer. Unlike simple radiation damage to other organs, radiation proctitis is a complex disease closely related to the microbiota. However, analysis of the gut microbiota is time-consuming and expensive. This study aims to mine rectal information using radiomics and incorporate it into a nomogram model for cheap and fast prediction of severe radiation proctitis prediction in postoperative cervical cancer patients. Methods: The severity of the patient's radiation proctitis was graded according to the RTOG/EORTC criteria. The toxicity grade of radiation proctitis over or equal to grade 2 was set as the model's target. A total of 178 patients with cervical cancer were divided into a training set (n = 124) and a validation set (n = 54). Multivariate logistic regression was used to build the radiomic and non-raidomic models. Results: The radiomics model [AUC=0.6855(0.5174-0.8535)] showed better performance and more net benefit in the validation set than the non-radiomic model [AUC=0.6641(0.4904-0.8378)]. In particular, we applied SHapley Additive exPlanation (SHAP) method for the first time to a radiomics-based logistic regression model to further interpret the radiomic features from case-based and feature-based perspectives. The integrated radiomic model enables the first accurate quantitative assessment of the probability of radiation proctitis in postoperative cervical cancer patients, addressing the limitations of the current qualitative assessment of the plan through dose-volume parameters only. Conclusion: We successfully developed and validated an integrated radiomic model containing rectal information. SHAP analysis of the model suggests that radiomic features have a supporting role in the quantitative assessment of the probability of radiation proctitis in postoperative cervical cancer patients.

Insight into the structural stability of wild type and mutants of the tobacco etch virus protease with molecular dynamics simulations.

The efficiency and high specificity of tobacco etch virus protease (TEVp) has made it widely used for cleavage of recombinant fusion proteins. However, TEVp suffers from a few intrinsic defects such as self-cleavage, poorly expressed in E. coli and less soluble. So some mutants were designed to improve it, such as S219V, T17S/N68D/I77V and L56V/S135G etc. MD simulations for the WT TEVp and its mutants were performed to explore the underlying dynamic effects of mutations on TEVp. Although the globular domains are fairly conserved, the three mutations have diverse effects on the dynamics properties of TEVp, including the elongation of ß-sheet, conversion of loop to helix and the flexibility of active core. Our present study indicates that the three mutants for TEVp can change their secondary structure and tend to form more helixes and sheets to improve stability. The study also helps us to understand the effects of some mutations on TEVp, provides us insights into the change of them at the atomic level and gives a potential rational method to design an improved protein.