Predictive value of MRI-based deep learning model for lymphovascular invasion status in node-negative invasive breast cancer.

To retrospectively assess the effectiveness of deep learning (DL) model, based on breast magnetic resonance imaging (MRI), in predicting preoperative lymphovascular invasion (LVI) status in patients diagnosed with invasive breast cancer who have negative axillary lymph nodes (LNs). Data was gathered from 280 patients, including 148 with LVI-positive and 141 with LVI-negative lesions. These patients had undergone preoperative breast MRI and were histopathologically confirmed to have invasive breast cancer without axillary LN metastasis. The cohort was randomly split into training and validation groups in a 7:3 ratio. Radiomics features for each lesion were extracted from the first post-contrast dynamic contrast-enhanced (DCE)-MRI. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method and logistic regression analyses were employed to identify significant radiomic features and clinicoradiological variables. These models were established using four machine learning (ML) algorithms and one DL algorithm. The predictive performance of the models (radiomics, clinicoradiological, and combination) was assessed through discrimination and compared using the DeLong test. Four clinicoradiological parameters and 10 radiomic features were selected by LASSO for model development. The Multilayer Perceptron (MLP) model, constructed using both radiomic and clinicoradiological features, demonstrated excellent performance in predicting LVI, achieving a high area under the curve (AUC) of 0.835 for validation. The DL model (MLP-radiomic) achieved the highest accuracy (AUC = 0.896), followed by DL model (MLP-combination) with an AUC of 0.835. Both DL models were significantly superior to the ML model (RF-clinical) with an AUC of 0.720. The DL model (MLP), which integrates radiomic features with clinicoradiological information, effectively aids in the preoperative determination of LVI status in patients with invasive breast cancer and negative axillary LNs. This is beneficial for making informed clinical decisions.

TMC6 functions as a GPCR-like receptor to sense noxious heat via Gαq signaling.

Thermosensation is vital for the survival, propagation, and adaption of all organisms, but its mechanism is not fully understood yet. Here, we find that TMC6, a membrane protein of unknown function, is highly expressed in dorsal root ganglion (DRG) neurons and functions as a Gαq-coupled G protein-coupled receptor (GPCR)-like receptor to sense noxious heat. TMC6-deficient mice display a substantial impairment in noxious heat sensation while maintaining normal perception of cold, warmth, touch, and mechanical pain. Further studies show that TMC6 interacts with Gαq via its intracellular C-terminal region spanning Ser780 to Pro810. Specifically disrupting such interaction using polypeptide in DRG neurons, genetically ablating Gαq, or pharmacologically blocking Gαq-coupled GPCR signaling can replicate the phenotype of TMC6 deficient mice regarding noxious heat sensation. Noxious heat stimulation triggers intracellular calcium release from the endoplasmic reticulum (ER) of TMC6- but not control vector-transfected HEK293T cell, which can be significantly inhibited by blocking PLC or IP3R. Consistently, noxious heat-induced intracellular Ca2+ release from ER and action potentials of DRG neurons largely reduced when ablating TMC6 or blocking Gαq/PLC/IP3R signaling pathway as well. In summary, our findings indicate that TMC6 can directly function as a Gαq-coupled GPCR-like receptor sensing noxious heat.

Regulation of Erythroid Differentiation via the HIF1α-NFIL3-PIM1 Signaling Axis Under Hypoxia.

Aims: Erythropoiesis is controlled by several factors, including oxygen level under different circumstances. However, the role of hypoxia in erythroid differentiation and the underlying mechanisms are poorly understood. We studied the effect and mechanism of hypoxia on erythroid differentiation of K562 cells and observed the effect of hypoxia on early erythropoiesis of zebrafish. Results: Compared with normal oxygen culture, both hemin-induced erythroid differentiation of K562 cells and the early erythropoiesis of zebrafish were inhibited under hypoxic treatment conditions. Hypoxia-inducible factor 1 alpha (HIF1α) plays a major role in the response to hypoxia. Here, we obtained a stable HIF1α knockout K562 cell line using the CRISPR-Cas9 technology and further demonstrated that HIF1α knockout promoted hemin-induced erythroid differentiation of K562 cells under hypoxia. We demonstrated an HIF1-mediated induction of the nuclear factor interleukin-3 (NFIL3) regulated in K562 cells under hypoxia. Interestingly, a gradual decrease in NFIL3 expression was detected during erythroid differentiation of erythropoietin-induced CD34+ hematopoietic stem/progenitor cells (HSPCs) and hemin-induced K562 cells. Notably, erythroid differentiation was inhibited by enforced expression of NFIL3 under normoxia and was promoted by the knockdown of NFIL3 under hypoxia in hemin-treated K562 cells. In addition, a target of NFIL3, pim-1 proto-oncogene, serine/threonine kinase (PIM1), was obtained by RNA microarray after NFIL3 knockdown. PIM1 can rescue the inhibitory effect of NFIL3 on hemin-induced erythroid differentiation of K562 cells. Innovation and Conclusion: Our findings demonstrate that the HIF1α-NFIL3-PIM1 signaling axis plays an important role in erythroid differentiation under hypoxia. These results will provide useful clues for preventing the damage of acute hypoxia to erythropoiesis.