Search

Summary:. We report the case of a 43-year-old woman who presented with combined radial, median, and ulnar nerve palsies and a spiral humeral shaft fracture after falling down stairs. Postinjury, the patient did not recover full median, ulnar, and radial nerve function despite aggressive hand therapy. Electrodiagnostic studies and imaging findings were concerning for traction neuropraxia or transection, radial nerve neuroma, and scar encasement of the radial, median, and ulnar nerves. The patient underwent radial, median, ulnar, and musculocutaneous nerve neuroplasty, nerve wrap application, nerve stimulation and laser angiography. Surgical exploration revealed no transection injuries to the median, ulnar, or musculocutaneous nerves. The radial nerve was tethered to the fracture site and enlarged, but no neuroma was observed. Laser angiography demonstrated intact perfusion to all nerves. The patient went on to recover full nerve function. Although isolated radial nerve palsies associated with closed humeral shaft fractures are typically observed initially, management of combined nerve palsies is controversial. This case serves to caution surgeons to perform a thorough neurovascular examination on patients with humeral shaft fractures to identify combined nerve palsies.

Abstract Patients affected by neurofibromatosis type 1 (NF1) frequently show muscle weakness with unknown etiology. Here we show that, in mice, Neurofibromin 1 (Nf1) is not required in muscle fibers, but specifically in early postnatal myogenic progenitors (MPs), where Nf1 loss led to cell cycle exit and differentiation blockade, depleting the MP pool resulting in reduced myonuclear accretion as well as reduced muscle stem cell numbers. This was caused by precocious induction of stem cell quiescence coupled to metabolic reprogramming of MPs impinging on glycolytic shutdown, which was conserved in muscle fibers. We show that a Mek/Erk/NOS pathway hypersensitizes Nf1-deficient MPs to Notch signaling, consequently, early postnatal Notch pathway inhibition ameliorated premature quiescence, metabolic reprogramming and muscle growth. This reveals an unexpected role of Ras/Mek/Erk signaling supporting postnatal MP quiescence in concert with Notch signaling, which is controlled by Nf1 safeguarding coordinated muscle growth and muscle stem cell pool establishment. Furthermore, our data suggest transmission of metabolic reprogramming across cellular differentiation, affecting fiber metabolism and function in NF1.

Abstract Autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy is an inflammatory disease of the central nervous system (CNS), which affects various regions in the CNS, presenting by variable clinical manifestations. Meningoencephalitis is the most common clinical presentation and association with autoimmune disorders has been reported in about 20% of these patients. Diagnosis is confirmed by the presence of CSF or serum immunoglobulin‐G (IgG) against GFAP. The reported case is a 53‐year‐old woman with the history of long‐standing rheumatoid arthritis who first presented with acute‐onset dizziness and gait disturbance, periventricular linear and radial enhancement pattern on MRI, and normal CSF analysis, successfully treated with an increase in the dose of oral steroids. After a year she had a subacute‐onset, moderate to severe holocephalic headache, normal neurologic examination and CSF analysis, and bilateral diffuse, pachymeningeal, and leptomeningeal enhancement on MRI. According to her Brain MRI imaging with relapsing remitting course steroid responsive ataxia and aseptic meningitis, her serum was tested for GFAP IgG antibodies which was positive. The reported patient is the first in the literature reported pachymeningitis in GFAP astrocytopathy. This case highlights the co‐occurrence of rheumatoid arthritis with GFAP‐associated astrocytopathy, and expands on the previously reported cases with similar association. This might also suggest a common immune pathogenesis.

HIV prevalence in Alameda County (including Oakland) is among the highest in California, yet the case registry may under-appreciate the full burden of disease. Using lists from health care facilities serving socioeconomically diverse populations and the HIV surveillance list, we applied capture-recapture methods to evaluate the completeness of the surveillance system by estimating the number of diagnosed people living with HIV and seeking care in Alameda County in 2013. Of the 5376 unique individuals reported from the lists, 397 were missing from the surveillance list. Models projected the total population size to be 5720 (95% CI 5587-6190), estimating the surveillance system as 87% complete. Subgroup analyses identified groups facing a disproportionate burden of HIV as more likely to be detected by the surveillance list. The Alameda County HIV surveillance system reports a high proportion of persons diagnosed with HIV within the jurisdiction. Capture-recapture analysis can help track progress towards maximizing engagement in HIV care.

Blockchain and Artificial Intelligence (AI) are two ground-breaking technologies that are transforming industries all over the world. While blockchain is a decentralized digital ledger that guarantees transparency, security, and tamper-proof records across many systems, AI is the emulation of human intellect in machines that can duplicate human decision-making and behavior. There is enormous potential for integrating AI into blockchain systems to enable safer, more intelligent, and more effective procedures. Blockchain and AI integration is changing the corporate environment by providing innovative answers to important problems like trust, efficiency, security, and transparency. AI gives companies strong capabilities for automation, predictive analytics, and data-driven decision-making. Blockchain guarantees a decentralized, impenetrable method of managing, storing, and confirming data. Such revolutionary use cases as AI-enhanced smart contracts, decentralized identity management, predictive supply chain optimization, and sophisticated fraud detection systems are made possible by the convergence of these two technologies. Businesses may improve supply chain logistics, expedite financial transactions, and optimize operations thanks to this synthesis. It becomes evident when we examine the advantages, applications, and difficulties of integrating blockchain technology with artificial intelligence that this combination has the potential to fundamentally alter how various businesses operate in the digital era. This study explores how AI and blockchain might work together in a variety of sectors, including as real estate, supply chain, healthcare, and finance. Using a literature review approach, this study also seeks to describe the uses and advantages of integrated AI and blockchain platforms across several business verticals. Businesses may reach a new degree of trust, efficiency, and creativity by fusing the advantages of blockchain and artificial intelligence (AI), propelling future growth in an increasingly digitized and networked market. [ABSTRACT FROM AUTHOR]

Background: Bone marrow examination is a useful investigative tool to diagnose several hematological and nonhematological disorders. While the aspiration provides excellent cytological detail, the biopsy provides information regarding the spatial relationships of cells, marrow architecture, and valuable information when aspirate is nondiagnostic. We conducted this study to compare the diagnostic usefulness and comparison between aspirate and trephine biopsies in the evaluation of hematological disorders. Aim: The aim was to assess the relative efficacy of bone marrow aspiration and trephine biopsy and the overall diagnostic utility of this procedure in the diagnosis of hematological and nonhematological disorders. Materials and Methods: This is a retrospective study of 6-month duration at a tertiary care hospital in Himachal Pradesh. Patients were aged from 1 to 85 years. A total of 169 cases were studied, in whom bone marrow aspiration and trephine biopsy were performed, with special stains used where required. Results: A specific pathology was found in 89 cases(52.66%), rest being a normal or unsatisfactory study. Trephine biopsy was fundamental in the diagnosis in 69 cases(48.93%). Nearly 21.05% of the aspirates indicating a normal study further revealed a specific pathology on trephine biopsy and 38.88% of the unsatisfactory aspirates revealed definite pathology on biopsy. We noted that 8.87% of cases were diagnosed by trephine biopsy alone, with 89.94% concordance between trephine biopsy and aspiration. Conclusion: Bone marrow aspirate cytology and trephine biopsy are useful adjuncts to each other and should be used to supplement each other in arriving at a definite diagnosis, and they remain as a key diagnostic tool in hematological disorders.

Modeling joint probability distributions is an important task in a wide variety of fields. One popular technique for this employs a family of multivariate distributions with uniform marginals called copulas. While the theory of modeling joint distributions via copulas is well understood, it gets practically challenging to accurately model real data with many variables. In this paper, we show that any copula can be naturally mapped to a multipartite maximally entangled state. Thus, the task of learning joint probability distributions becomes the task of learning maximally entangled states. We prove that a variational ansatz we christen as a “qopula” based on this insight leads to an exponential advantage over classical methods of learning some joint distributions. As an application, we train a quantum generative adversarial network (QGAN) and a quantum circuit Born machine (QCBM) using this variational ansatz to generate samples from joint distributions of two variables in historical data from the stock market. We demonstrate our generative learning algorithms on trapped ion quantum computers from IonQ for up to eight qubits. Our experimental results show interesting findings such as the resilience against noise, outperformance against equivalent classical models and 20–1000 times less iterations required to converge as compared to equivalent classical models.

Novel synthetic mimics of antimicrobial peptides have been developed to exhibit structural properties and antimicrobial activity similar to those of natural antimicrobial peptides (AMPs) of the innate immune system. These molecules have a number of potential advantages over conventional antibiotics, including reduced bacterial resistance, cost-effective preparation, and customizable designs. In this study, we investigate a family of nylon-3 polymer-based antimicrobials. By combining vesicle dye leakage, bacterial permeation, and bactericidal assays with small-angle X-ray scattering (SAXS), we find that these polymers are capable of two interdependent mechanisms of action: permeation of bacterial membranes and binding to intracellular targets such as DNA, with the latter necessarily dependent on the former. We systemically examine polymer-induced membrane deformation modes across a range of lipid compositions that mimic both bacteria and mammalian cell membranes. The results show that the polymers' ability to generate negative Gaussian curvature (NGC), a topological requirement for membrane permeation and cellular entry, in model Escherichia coli membranes correlates with their ability to permeate membranes without complete membrane disruption and kill E. coli cells. Our findings suggest that these polymers operate with a concentration-dependent mechanism of action: at low concentrations permeation and DNA binding occur without membrane disruption, while at high concentrations complete disruption of the membrane occurs. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova.