SGNet: Folding Symmetrical Protein Complex with Deep Learning

Deep learning has made significant progress in protein structure prediction, advancing the development of computational biology. However, despite the high accuracy achieved in predicting single-chain structures, a significant number of large homo-oligomeric assemblies exhibit internal symmetry, posing a major challenge in structure determination. The performances of existing deep learning methods are limited since the symmetrical protein assembly usually has a long sequence, making structural computation infeasible. In addition, multiple identical subunits in symmetrical protein complex cause the issue of supervision ambiguity in label assignment, requiring a consistent structure modeling for the training. To tackle these problems, we propose a protein folding framework called SGNet to model protein-protein interactions in symmetrical assemblies. SGNet conducts feature extraction on a single subunit and generates the whole assembly using our proposed symmetry module, which largely mitigates computational problems caused by sequence length. Thanks to the elaborate design of modeling symmetry consistently, we can model all global symmetry types in quaternary protein structure prediction. Extensive experimental results on a benchmark of symmetrical protein complexes further demonstrate the effectiveness of our method

Experimental estimation of the quantum Fisher information from randomized measurements

The quantum Fisher information (QFI) represents a fundamental concept in quantum physics. On the one hand, it quantifies the metrological potential of quantum states in quantum-parameter-estimation measurements. On the other hand, it is intrinsically related to the quantum geometry and multipartite entanglement of many-body systems. Here, we explore how the QFI can be estimated via randomized measurements, an approach which has the advantage of being applicable to both pure and mixed quantum states. In the latter case, our method gives access to the sub-quantum Fisher information, which sets a lower bound on the QFI. We experimentally validate this approach using two platforms: a nitrogen-vacancy center spin in diamond and a 4-qubit state provided by a superconducting quantum computer. We further perform a numerical study on a many-body spin system to illustrate the advantage of our randomized-measurement approach in estimating multipartite entanglement, as compared to quantum state tomography. Our results highlight the general applicability of our method to general quantum platforms, including solid-state spin systems, superconducting quantum computers and trapped ions, hence providing a versatile tool to explore the essential role of the QFI in quantum physics.Comment: 11 pages, 6 figures, comments are welcom

Explainable Artificial Intelligence and Domain Adaptation for Predicting HIV Infection With Graph Neural Networks

OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets. METHODS: Network data from two cohorts of younger sexual minority men (SMM) from two U.S. cities (Chicago, IL, and Houston, TX) were collected between 2014 and 2016. Feature importance from graph attention network (GAT) models were determined using GNNExplainer. Domain adaptation was performed to examine model transferability from one city dataset to the other dataset, training with 100% of the source dataset with 30% of the target dataset and prediction on the remaining 70% from the target dataset. RESULTS: Domain adaptation showed the ability of GAT to improve prediction over training with single city datasets. Feature importance analysis with GAT models in single city training indicated similar features across different cities, reinforcing potential application of GAT models in predicting HIV infections through domain adaptation. CONCLUSION: GAT models can be used to address the data sparsity issue in HIV study populations. They are powerful tools for predicting individual risk of HIV that can be further explored for better understanding of HIV transmission

Podocyte specific knock out of selenoproteins does not enhance nephropathy in streptozotocin diabetic C57BL/6 mice

Abstract Background Selenoproteins contain selenocysteine (Sec), commonly considered the 21st genetically encoded amino acid. Many selenoproteins, such as the glutathione peroxidases and thioredoxin reductases, protect cells against oxidative stress by functioning as antioxidants and/or through their roles in the maintenance of intracellular redox balance. Since oxidative stress has been implicated in the pathogenesis of diabetic nephropathy, we hypothesized that selenoproteins protect against this complication of diabetes. Methods C57BL/6 mice that have a podocyte-specific inability to incorporate Sec into proteins (denoted in this paper as PodoTrsp-/-) and control mice were made diabetic by intraperitoneal injection of streptozotocin, or were injected with vehicle. Blood glucose, body weight, microalbuminuria, glomerular mesangial matrix expansion, and immunohistochemical markers of oxidative stress were assessed. Results After 3 and 6 months of diabetes, control and PodoTrsp-/- mice had similar levels of blood glucose. There were no differences in urinary albumin/creatinine ratios. Periodic acid-Schiff staining to examine mesangial matrix expansion also demonstrated no difference between control and PodoTrsp-/- mice after 6 months of diabetes, and there were no differences in immunohistochemical stainings for nitrotyrosine or NAD(P)H dehydrogenase, quinone 1. Conclusion Loss of podocyte selenoproteins in streptozotocin diabetic C57BL/6 mice does not lead to increased oxidative stress as assessed by nitrotyrosine and NAD(P)H dehydrogenase, quinone 1 immunostaining, nor does it lead to worsening nephropathy.http://deepblue.lib.umich.edu/bitstream/2027.42/112674/1/12882_2008_Article_98.pd

The effect of suramin on inhibiting fibroblast proliferation and preventing epidural fibrosis after laminectomy in rats

BACKGROUND: Epidural fibrosis often causes serious complications in patients after lumbar laminectomy and discectomy and is associated with the proliferation of fibroblasts. Suramin is known to have an obvious inhibitory effect on the coactions of many growth factors and their receptors, but little was previously known about the effect of suramin on fibroblast proliferation and the progress of epidural fibrosis. METHODS: We illustrated the effect of suramin on cultured fibroblasts of rats with different concentrations (0, 200, 400, 600 mg/l). The proliferation of suramin-treated fibroblasts was evaluated by CCK-8 and western blot analysis. Additionally, in a rat model of laminectomy, different concentrations of suramin (100, 200, and 300 mg/ml) and saline were applied to the laminectomy sites locally. The effect of suramin on preventing epidural fibrosis was detected by the Rydell classification, hydroxyproline content, histological analysis, and collagen density analyses. RESULTS: The results of CCK-8 shown that suramin could significantly inhibit fibroblasts proliferation in a dose-dependent manner. The western blotting shown that the expression levels of the cell proliferation markers such as cyclin D1, cyclin E, and PCNA were down-regulated. Moreover, in a rat model, we found that suramin could reduce epidural fibrosis as well as inhibit fibroblast proliferation, and 300 mg/ml suramin had better effect. CONCLUSIONS: Topical application of suramin could reduce epidural fibrosis after laminectomy, and the application of suramin could inhibit the proliferation of fibroblasts in rats. This study indicates that suramin is a potent antifibrotic agent that may have therapeutic potential for patients with epidural fibrosis

Systematic Design and Data-Driven Evaluation of Social Determinants of Health Ontology (SDoHO)

Objective: Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a sick care system into a health-promoting system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way. Material and methods: Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and constraints based on multiple SDoH-related resources. Expert review and coverage evaluation, using a bottom-up approach employing clinical notes data and a national survey, were performed. Results: We constructed the SDoHO with 708 classes, 106 object properties, and 20 data properties, with 1,561 logical axioms and 976 declaration axioms in the current version. Three experts achieved 0.967 agreement in the semantic evaluation of the ontology. A comparison between the coverage of the ontology and SDOH concepts in 2 sets of clinical notes and a national survey instrument also showed satisfactory results. Discussion: SDoHO could potentially play an essential role in providing a foundation for a comprehensive understanding of the associations between SDoH and health outcomes and paving the way for health equity across populations. Conclusion: SDoHO has well-designed hierarchies, practical objective properties, and versatile functionalities, and the comprehensive semantic and coverage evaluation achieved promising performance compared to the existing ontologies relevant to SDoH

Sacral terminal filar cyst: a distinct variant of spinal meningeal cyst and midterm clinical outcome following combination resection surgery

ObjectiveSpinal meningeal cysts (SMCs) are currently classified into three types: extradural cysts without nerve root fibers (Type I), extradural cysts with nerve root fibers (Type II), and intradural cysts (Type III). However, the sacral terminal filar cyst is a distinct subtype with the filum terminale rather than nerve roots within the cyst. This study aimed to investigate the clinicoradiological characteristics and surgical outcomes of sacral terminal filar cysts.MethodsA total of 32 patients with sacral terminal filar cysts were enrolled. Clinical and radiological profiles were collected. All patients were surgically treated, and preoperative and follow-up neurological functions were evaluated.ResultsChronic lumbosacral pain and sphincter dysfunctions were the most common symptoms. On MRI, the filum terminale could be identified within the cyst in all cases, and low-lying conus medullaris was found in 23 (71.9%) cases. The filum terminale was dissociated and cut off in all cases, and the cyst wall was completely resected in 23 (71.9%) cases. After a median follow-up period of 26.5 ± 15.5 months, the pain and sphincter dysfunctions were significantly improved (both P < 0.0001). The cyst recurrence was noted in only 1 (3.1%) case.ConclusionsSacral terminal filar cysts are rare, representing a distinct variant of SMCs. Typical MRI features, including filum terminale within the cyst and low-lying conus medullaris, may suggest the diagnosis. Although the optimal surgical strategy remains unclear, we recommend a combination of resection of the cyst wall and dissociation of the filum terminale. The clinical outcomes can be favorable

Podocyte specific knock out of selenoproteins does not enhance nephropathy in streptozotocin diabetic C57BL/6 mice

<p>Abstract</p> <p>Background</p> <p>Selenoproteins contain selenocysteine (Sec), commonly considered the 21^stgenetically encoded amino acid. Many selenoproteins, such as the glutathione peroxidases and thioredoxin reductases, protect cells against oxidative stress by functioning as antioxidants and/or through their roles in the maintenance of intracellular redox balance. Since oxidative stress has been implicated in the pathogenesis of diabetic nephropathy, we hypothesized that selenoproteins protect against this complication of diabetes.</p> <p>Methods</p> <p>C57BL/6 mice that have a podocyte-specific inability to incorporate Sec into proteins (denoted in this paper as PodoTrsp^-/-) and control mice were made diabetic by intraperitoneal injection of streptozotocin, or were injected with vehicle. Blood glucose, body weight, microalbuminuria, glomerular mesangial matrix expansion, and immunohistochemical markers of oxidative stress were assessed.</p> <p>Results</p> <p>After 3 and 6 months of diabetes, control and PodoTrsp^-/-mice had similar levels of blood glucose. There were no differences in urinary albumin/creatinine ratios. Periodic acid-Schiff staining to examine mesangial matrix expansion also demonstrated no difference between control and PodoTrsp^-/-mice after 6 months of diabetes, and there were no differences in immunohistochemical stainings for nitrotyrosine or NAD(P)H dehydrogenase, quinone 1.</p> <p>Conclusion</p> <p>Loss of podocyte selenoproteins in streptozotocin diabetic C57BL/6 mice does not lead to increased oxidative stress as assessed by nitrotyrosine and NAD(P)H dehydrogenase, quinone 1 immunostaining, nor does it lead to worsening nephropathy.</p