CCN1 induces adipogenic differentiation of fibro/adipogenic progenitors in a chronic kidney disease model.

Previous studies have shown that sarcopenic obesity is highly prevalent in patients with chronic kidney disease (CKD). Here, the association between CKD and sarcopenic obesity were investigated. The 5/6 nephrectomy was performed to establish CKD in mice. Fluorescence-activated cell sorting (FACS), quantitative real-time PCR, ELISA kits assay, immunohistochemistry, and cell proliferation assay were carried out to investigate the condition of muscle loss and fatty infiltration were in CKD mice and the origin of adipocytes. Muscle atrophy occurred and adipogenic gene expression, Perilipin and FABP4 were markedly increased in the hind limb muscle of CKD mice. Results indicated that fibro/adipogenic progenitors (FAPs) are the precursor of adipocytes in the muscle of CKD mice. Meanwhile, the content of extracellular matrix protein CCN1 was notably increased in serum of CKD patients with sarcopenic obesity which was also found in muscle and serum of CKD mice. CCN1 induced the differentiation of FAPs into adipocytes. These results suggest that CKD mice are susceptible to sarcopenic obesity. CCN1 may be a novel activator of the differentiation of FAPs in CKD muscle.

The application value of a vendor-specific deep learning image reconstruction algorithm in "triple low" head and neck computed tomography angiography.

Background: Head and neck computed tomography angiography (CTA) technology has become the noninvasive imaging method of choice for the diagnosis and long-term follow-up of vascular lesions of the head and neck. However, issues of radiation safety and contrast nephropathy associated with CTA examinations remain concerns. In recent years, deep learning image reconstruction (DLIR) algorithms have been increasingly used in clinical studies, demonstrating their potential for dose optimization. This study aimed to investigate the value of using a DLIR algorithm to reduce radiation and contrast doses in head and neck CTA. Methods: A total of 100 patients were prospectively enrolled and randomly divided into two groups. Group A (50 patients) consisted of those who underwent 70-kVp CTA with a low contrast volume and injection rate and who were classified according to the reconstruction algorithm into subgroups A1 [DLIR at high weighting (DLIR-H)], A2 [DLIR at low weighting (DLIR-L)], and A3 [volume-based adaptive statistical iterative reconstruction with 50% weighting (ASIR-V50%)]. Meanwhile, group B (50 patients) consisted of those who underwent standard radiation and contrast doses at 100 kVp with ASIR-V50% reconstruction. The computed tomography (CT) attenuation, background noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality score (SIQS) were statistically compared for several vessels among the four groups. Results: Group A showed significant reductions in contrast dosage, injection rate, and radiation dose of 36.09%, 20.88%, and 47.80%, respectively, compared to group B (all P<0.001). The four groups differed significantly in terms of background noise (all P<0.05) with group A1 having the lowest value. Group A1 also had significantly higher SNR and CNR values compared to group B in all vessels (all P<0.05) except the M1 of the middle cerebral artery for the SNR. Group A1 also had the highest SIQS, followed by the A2, B, and A3 groups. The SIQS showed good agreement between the two reviewers in all groups, with κ values between 0.88 and 1. Conclusions: Compared to the standard-dose protocol using 100 kVp and ASIR-V50%, a protocol of 70 kVp combined with DLIR-H significantly reduces the radiation dose, contrast dose, and injection rate in head and neck CTA while still significantly improving image quality for patients with a standard body size.

A broad neutralizing nanobody against SARS-CoV-2 engineered from an approved drug.

SARS-CoV-2 infection is initiated by Spike glycoprotein binding to the human angiotensin-converting enzyme 2 (ACE2) receptor via its receptor binding domain. Blocking this interaction has been proven to be an effective approach to inhibit virus infection. Here we report the discovery of a neutralizing nanobody named VHH60, which was directly produced from an engineering nanobody library based on a commercialized nanobody within a very short period. VHH60 competes with human ACE2 to bind the receptor binding domain of the Spike protein at S351, S470-471and S493-494 as determined by structural analysis, with an affinity of 2.56 nM. It inhibits infections of both ancestral SARS-CoV-2 strain and pseudotyped viruses harboring SARS-CoV-2 wildtype, key mutations or variants at the nanomolar level. Furthermore, VHH60 suppressed SARS-CoV-2 infection and propagation 50-fold better and protected mice from death for twice as long as the control group after SARS-CoV-2 nasal infections in vivo. Therefore, VHH60 is not only a powerful nanobody with a promising profile for disease control but also provides evidence for a highly effective and rapid approach to generating therapeutic nanobodies.