Lamin proteins are a type of intermediate filament primarily located in the nucleus. They are classified into two categories: A-type and B-type lamins. Lamin A and lamin C belong to the A-type category and are commonly grouped as Lamin A/C. Diseases related to this protein are generally called laminopathies which have different presentations. Lamin A/C is also involved in cancers specifically breast cancer. Research has shown that changes in lamin A/C expression, particularly its decrease in breast cancer, are associated with various cancer-related features, including altered nuclear shape, mitotic abnormalities, shifts in gene expression, cancer cell migration, and metastasis. This review delivers a complete overview of the findings regarding the association and roles of lamin A/C in breast tumor cells. It highlights the importance and potential clinical applications of this promising biomarker, offering the possibility of using this protein for breast cancer diagnosis and as a prognostic marker for patients with breast cancer.

A new study shows that receiving an updated COVID vaccine reduced people’s risk of severe disease and death in all age groups, regardless of immunity from prior infection or vaccination

Lamin proteins are a type of intermediate filament primarily located in the nucleus. They are classified into two categories: A-type and B-type lamins. Lamin A and lamin C belong to the A-type category and are commonly grouped as Lamin A/C. Diseases related to this protein are generally called laminopathies which have different presentations. Lamin A/C is also involved in cancers specifically breast cancer. Research has shown that changes in lamin A/C expression, particularly its decrease in breast cancer, are associated with various cancer-related features, including altered nuclear shape, mitotic abnormalities, shifts in gene expression, cancer cell migration, and metastasis. This review delivers a complete overview of the findings regarding the association and roles of lamin A/C in breast tumor cells. It highlights the importance and potential clinical applications of this promising biomarker, offering the possibility of using this protein for breast cancer diagnosis and as a prognostic marker for patients with breast cancer.

What you need to know about COVID-19 vaccines if you are pregnant or breastfeeding.

Quantitative Biology: Papers and Perspectives · Episode

Purpose Carcinoembryonic antigen (CEA) is an important prognostic factor for rectal cancer. This study aims to introduce a novel cutoff point for CEA within the normal range to improve prognosis prediction and enhance patient stratification in rectal cancer patients. Methods A total of 316 patients with stages I to III rectal cancer who underwent surgical tumor resection were enrolled. The Cox proportional hazards regression model was used to evaluate the impact of preoperative CEA level and other co-variates on overall survival (OS). The Youden Index method was used for CEA optimal cutoff estimation. Results The mean follow-up period was 46.47 months. In risk-adjusted Cox proportional analysis, higher preoperative CEA levels (HR 1.17, CI 1.131.21; P < 0.001), and T-stage were associated with poor OS. The mean preoperative CEA level was significantly higher in patients with positive lymphovascular invasion (LVI) and perineural invasion (PNI) (CI: 1.06–2.45 and 0.75–2.33, respectively, P < 0.001, t test). Pathologic complete response (pCR) occurred in 71 (22.4%) cases. Patients with pCR had lower levels of preoperative CEA than non-pCR group (P = 0.002, CEApCR-CEAnonpCR =  − 1.3; t test). Using Youden Index, the estimated optimal CEA cutoff value for predicting OS was 2.8 ng/mL (sensitivity 90%; specificity 78.5%). Lower preoperative CEA levels predict higher pCR rates, aiding patient stratification and planning. Conclusion Preoperative CEA may play a role in the prediction of pCR in rectal cancer. Considering the CEA level of 2.8 ng/ml, as a newly defined cutoff point, patients with a worse prognosis can be identified prior to operation. PNI, along with LVI as independent predictors, may be contemplated as prognostic indicators to improve treatment strategies.

Purpose Fluorescence imaging is critical for intraoperative intestinal perfusion assessment in colorectal surgery, yet its clinical adoption remains limited by subjective interpretation and lack of quantitative standards. This study introduces an integrated approach combining fluorescence curve analysis, biophysical modeling, and machine learning to improve intraoperative perfusion assessment. Methods Laparoscopic fluorescence videos from 68 low rectal cancer patients were analyzed, with 1,263 measurement points (15–20 per case) selected along colonic bands. Fluorescence intensity dynamics were extracted via color space transformation, video stabilization and image registration, then modeled using the Random Sample Consensus (RANSAC) algorithm and nonlinear least squares fitting to derive biophysical parameters. Three clinicians independently scored perfusion quality (0–100 scale) using morphological features and biophysical metrics. An XGBoost model was trained on these parameters to automate scoring. Results The model achieved superior test performance, with a root mean square error (RMSE) of 2.47, a mean absolute error (MAE) of 1.99, and an R2 of 97.2%, outperforming conventional time-factor analyses. It demonstrated robust generalizability, showing no statistically significant prediction differences across age, diabetes, or smoking subgroups (P > 0.05). Clinically, low perfusion scores in distal anastomotic regions were significantly associated with postoperative complications (P < 0.001), validating the scoring system’s clinical relevance and discriminative capacity. The automated software we developed completed analyses within 2 min, enabling rapid intraoperative assessment. Conclusion This framework synergistically enhances surgical evaluation through three innovations: (1) Biophysical modeling quantifies perfusion dynamics beyond time-based parameters; (2) Machine learning integrates multimodal data for surgeon-level accuracy; (3) Automated workflow enables practical clinical translation. By addressing limitations of visual assessment through quantitative, rapid, and generalizable analysis, this method advances intraoperative perfusion monitoring and decision-making in colorectal surgery.

In this Tools of the Trade article, Christopher Lowden describes the development and use of CRISPR-StAR, which leverages internal controls to overcome experimental noise for improved in vivo functional genomic screens.

Construction of the FBN-125 template enhances neonatal brain MRI processing by providing a high-resolution, multi-contrast atlas for accurate segmentation and spatial normalization, improving consiste...

Background and purpose The glymphatic system, a waste clearance pathway, has been implicated in several neurological conditions associated with neuroinflammation. COVID-19 associated neurocognitive im...

Weight loss drugs have surged in popularity. But Gov. Ned Lamont wants CT’s Medicaid program to discontinue covering them for obesity.

Background Patients with pancreatic ductal adenocarcinoma (PDAC) commonly have occult metastatic dissemination and current standard staging methods have significant limitations in identifying these patients. A clinically available assay allows for the identification of mutant KRAS (mKRAS) circulating tumor DNA (ctDNA) from patient plasma and peritoneal fluid that may identify these patients and impact treatment decision making. We investigated the patterns of diagnostic and prognostic capabilities of mKRAS ctDNA in patients with localized PDAC. Methods Patients with non-metastatic PDAC were identified and underwent a full staging work-up during their first visit at our institution. Development of metastatic disease and long-term survival outcomes were assessed to compare between the mKRAS testing groups. Results Between 2018 and 2022, 785 patients were evaluated. Among the 785 patients who underwent plasma mKRAS testing, 104 were mKRAS positive. Plasma mKRAS-positive patients were more likely to develop metastatic disease and had worse overall survival. In the 419 patients who underwent peritoneal mKRAS, 123 were mKRAS-positive and were more likely to harbor occult metastases or develop peritoneal rather than hematogenous metastases. For patients who underwent both baseline plasma and peritoneal mKRAS testing, any positive mKRAS test regardless of compartment was associated with worse outcomes. Conclusions Detection of mKRAS ctDNA in plasma and peritoneal fluid of patients with localized PDAC is not only feasible but also identifies those at high risk of metastatic progression and worse survival outcomes. It allows for better prognostication and can significantly impact subsequent treatment decisions, particularly in patients where an aggressive surgical approach is being considered.

Weight loss, weight gain, and appetite changes are common during cancer treatment. In some people with cancer, these changes can lead to malnutrition.

Mandimycin, a polyene macrolide, exhibits strong antifungal activity and possesses a mode of action that is distinct from other compounds of this class.