Unlocking the Role of sMyBP-C: A Key Player in Skeletal Muscle Development and Growth.

Skeletal muscle is the largest organ in the body, responsible for gross movement and metabolic regulation. Recently, variants in the MYBPC1 gene have been implicated in a variety of developmental muscle diseases, such as distal arthrogryposis. How MYBPC1 variants cause disease is not well understood. Here, through a collection of novel gene-edited mouse models, we define a critical role for slow myosin binding protein-C (sMyBP-C), encoded by MYBPC1, across muscle development, growth, and maintenance during prenatal, perinatal, postnatal and adult stages. Specifically, Mybpc1 knockout mice exhibited early postnatal lethality and impaired skeletal muscle formation and structure, skeletal deformity, and respiratory failure. Moreover, a conditional knockout of Mybpc1 in perinatal, postnatal and adult stages demonstrates impaired postnatal muscle growth and function secondary to disrupted actomyosin interaction and sarcomere structural integrity. These findings confirm the essential role of sMyBP-C in skeletal muscle and reveal specific functions in both prenatal embryonic musculoskeletal development and postnatal muscle growth and function.

Leptospiral imelysin (LIC_10713) is secretory, immunogenic and binds to laminin, fibronectin, and collagen IV.

Leptospirosis is a widespread zoonotic disease caused by pathogenic Leptospira. Early and accurate diagnosis is the prime step in managing the disease. Secretory proteins of Leptospira remain distinguished for diagnosis due to their availability as soluble proteins in the serum and their interaction with the host immune response due to their extracellular presence. This study presents the cloning, expression, purification, and characterization of imelysin or LruB (LIC_10713), a putative leptospiral protein. We report that the localization of imelysin showed its presence in the inner membrane and in the culture supernatant. The imelysin was upregulated under in vitro physiological conditions of infection. The LIC_10713 interacted significantly with laminin, fibronectin, collagen type I, and collagen type IV in a dose-dependent manner. Phylogenetic analysis showed that LIC_10713 is predominately found in the pathogenic species of Leptospira, and the GxHxxE motif of imelysin-like proteins is represented as the amino acid sequence GWHAIE. Also, immunoglobulins in leptospirosis-infected patients recognize recombinant-LIC_10713 with 100% specificity and 90.9% sensitivity. The secretion nature, abundance, upregulation, binding to ECM components, and immunogenicity determine LIC_10713 as an important molecule that can be used as an anti-leptospirosis measure. KEY POINTS: • The imelysin-like protein (LIC_10713) of Leptospira is a secretory protein • The protein LIC_10713 can bind ECM molecules • The LIC_10713 is mainly found in pathogenic leptospires • The anti-LIC_10713 antibody from human serum can detect the r-LIC_10713.

Deep learning for detection of iso-dense, obscure masses in mammographically dense breasts.

OBJECTIVES: To analyze the performance of deep learning in isodense/obscure masses in dense breasts. To build and validate a deep learning (DL) model using core radiology principles and analyze its performance in isodense/obscure masses. To show performance on screening mammography as well as diagnostic mammography distribution. METHODS: This was a retrospective, single-institution, multi-centre study with external validation. For model building, we took a 3-pronged approach. First, we explicitly taught the network to learn features other than density differences: such as spiculations and architectural distortion. Second, we used the opposite breast to enable the detection of asymmetries. Third, we systematically enhanced each image by piece-wise-linear transformation. We tested the network on a diagnostic mammography dataset (2569 images with 243 cancers, January to June 2018) and a screening mammography dataset (2146 images with 59 cancers, patient recruitment from January to April 2021) from a different centre (external validation). RESULTS: When trained with our proposed technique (and compared with baseline network), sensitivity for malignancy increased from 82.7 to 84.7% at 0.2 False positives per image (FPI) in the diagnostic mammography dataset, 67.9 to 73.8% in the subset of patients with dense breasts, 74.6 to 85.3 in the subset of patients with isodense/obscure cancers and 84.9 to 88.7 in an external validation test set with a screening mammography distribution. We showed that our sensitivity exceeded currently reported values (0.90 at 0.2 FPI) on a public benchmark dataset (INBreast). CONCLUSION: Modelling traditional mammographic teaching into a DL framework can help improve cancer detection accuracy in dense breasts. CLINICAL RELEVANCE STATEMENT: Incorporating medical knowledge into neural network design can help us overcome some limitations associated with specific modalities. In this paper, we show how one such deep neural network can help improve performance on mammographically dense breasts. KEY POINTS: • Although state-of-the-art deep learning networks achieve good results in cancer detection in mammography in general, isodense, obscure masses and mammographically dense breasts posed a challenge to deep learning networks. • Collaborative network design and incorporation of traditional radiology teaching into the deep learning approach helped mitigate the problem. • The accuracy of deep learning networks may be translatable to different patient distributions. We showed the results of our network on screening as well as diagnostic mammography datasets.

Cost-Effective Transcriptome-Wide Profiling of Circular RNAs by the Improved-tdMDA-NGS Method.

Covalently closed circular RNAs are neoteric to the eukaryotic family of long non-coding RNAs emerging as a result of 5'-3' backsplicing from exonic, intronic, or intergenic regions spanning the parental gene. Owing to their unique structure and stability, circular RNAs have a multitude of functional properties such as micro-RNA and protein sponges, direct and indirect modulators of gene expression, protein translation, and many unproven activities apart from being potential biomarkers. However, due to their low abundance, most of the global circular RNA identification is carried out by high-throughput NGS-based approaches requiring millions of sequencing reads. This lag in methodological advancements demands for newer, more refined, and efficient identification techniques. Here, we aim to show an improved version of our previously reported template-dependent multiple displacement amplification (tdMDA)-NGS method by superimposing the ribosomal depletion step and use of H minus reverse transcriptase and RNase H. Implication of tdMDA using highly replicative Phi29 DNA polymerase after minimizing the linear and ribosomal RNA content further intensifies its detection limit toward even the abysmally expressing circular RNA at a low NGS depth, thereby decreasing the cost of identifying a single circular RNA. A >11-fold and >6-fold increase in total circular RNA was identified from the improved-tdMDA-NGS method over the traditional method of circRNA sequencing using DCC and CIRI2 pipelines, respectively, from Oryza sativa subsp. Indica. Furthermore, the reliability of the improved-tdMDA-NGS method was also asserted in HeLa cell lines, showing a significant fold difference in comparison with the existing traditional method of circRNA sequencing. Among the identified circular RNAs, a significant percentage from both rice (∼58%) and HeLa cell lines (∼84%) is found to be matched with the previously reported circular RNAs, suggesting that the improved-tdMDA-NGS method can be adapted to detect and characterize the circular RNAs from different biological systems.

Imaging Features of Breast Cancer Subtypes on Mammography and Ultrasonography: an Analysis of 479 Patients.

To compare features of clinically defined subtypes of breast cancer on mammography (MG) and ultrasonography (USG). After obtaining approval from the institute ethics committee, a retrospective observational study was performed on biopsy-proven breast cancer patients who underwent baseline MG from 2016 to 2020. MG and USG features were evaluated and the patients were classified based on immunohistochemistry profile into luminal like (LL)-oestrogen receptor (ER)/progesterone receptor (PR) + , Her2neu-; basal like (BL)-ER/PR-, Her2neu-; Her2 like (HL)-Her2neu + . A total of 479 patients (mean age, 51.4 ± 11.7 years; all females) were included: LL-198 (41.3%), BL-121 (25.2%) and HL-160 (33.3%). On MG, round shape (21/115, 18.3%, p < 0.001); circumscribed (16/115, 13.9%, p < 0.001) and microlobulated margins (28/115, 24.4%) were associated with BL tumours. Associated suspicious calcifications (96/160, 60%, p < 0.001) and skin thickening or retraction (75/149, 50.3%, p < 0.001) were more common in HL. On USG, round shape (12/95, 12.8%, p = 0.005); circumscribed (8/94, 8.5%) and microlobulated margins (44/94, 46.8%) and posterior acoustic enhancement (7/95, 7.5%, p = 0.012) were associated with BL. The logistic regression analysis revealed that spiculated margins on MG favoured LL (OR: 8.5, p = 0.001); round shape (OR: 6.8), circumscribed (OR: 10.8) or microlobulated margins (OR: 3.5) (p < 0.001 for each) favoured BL; whereas associated features of calcifications (OR: 3.3) (p = 0.019) and skin retraction or thickening (OR: 1.8) (p < 0.001) favoured HL. On USG, circumscribed (OR: 5.9, p = 0.005) or microlobulated margins (OR: 3, p < 0.001) and posterior acoustic enhancement (OR: 9.5, p = 0.006) favoured BL. Clinically defined subtypes of breast cancer show significant differences in the imaging appearances on mammography and USG. BL tumours may not show the typical imaging features of malignancy, necessitating clinicopathological correlation for accurate diagnosis.

Radiological evaluation of metastatic lymph nodes in carcinoma cervix with emphasis on their infiltrative pattern.

Background & objectives: Imaging has been added to the International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system of cervical carcinoma. This study was performed to assess the impact of imaging in staging and to ascertain the prevalence and pattern of nodal metastasis on contrast-enhanced computed tomography (CECT) in patients with cervical carcinoma who were treated based on FIGO 2009 staging system. Methods: This retrospective study was conducted to evaluate all patients with biopsy-proven cervical carcinoma who underwent CECT of abdomen at a tertiary cancer centre in north India from April 2017 to April 2019 and for whom either baseline or follow up scans were available. In patients with enlarged or necrotic lymph nodes, the location, size and pattern of infiltration of adjacent organs were recorded. Results: A total of 602 patients of cervical carcinoma had undergone CT during the study period, of whom 138 (22.9%) underwent CT at baseline and 464 (77.1%) patients during follow up. The FIGO (2009) stage distribution at the time of presentation was stage IB: 109 (18.1%); stage IIA: 14 (2.3%), stage IIB: 118 (19.6%), stage IIIA: 12 (2%), stage IIIB: 277 (46%), stage IVA: 20 (3.3%) and stage IVB: 52 (8.6%). Ninety of the 138 (65.22%) patients underwent a stage shift according to the FIGO 2018 because of the presence of enlarged lymph nodes at baseline scan. Sixteen (2.7%) patients had infiltrative nodal masses most commonly involving the blood vessels (n=14) followed by ureter (n=8), bones (n=5), muscle and bowel (n=3, each). The majority (14/16) of these patients presented with vague abdominal pain, discomfort and vomiting, while two had bone pain. Interpretation & conclusions: CECT at baseline helps in accurately assessing the stage in cervical carcinoma. It helps in the identification of lymph node metastasis in cervical carcinoma, which is crucial for guiding accurate management.

CT-guided percutaneous nephrostomy in an obstructed pelvic pancake kidney: a report of a novel transiliopsoas approach.

Pancake kidney is a rare renal fusion anomaly with increased risk of complications, such as stone disease and infections, due to altered urodynamics. Image-guided (ultrasonography and fluoroscopy) percutaneous nephrostomy (PCN) is performed to decompress an obstructed pancake kidney. However, routine image guidance may be unable to provide a suitable access in complex clinical scenarios. The approach for PCN in a low-lying fused kidney is difficult due to a limited safe posterior retroperitoneal paraspinal route, and anterior transperitoneal approach poses risks of urine leak and peritonitis. We report a case of an obstructed pancake kidney managed by CT-guided PCN through a transiliopsoas approach.