beta-Lactam antibiotics can induce severe neutropenia by a hitherto unknown mechanism. Fifty cases of beta-lactam antibiotic-induced neutropenia (less than 1,000 neutrophils/mm3) from 17 hospitals were analyzed and compared with 140 literature cases. The incidence of neutropenia was 5%-greater than 15% in patients treated for greater than or equal to 10 days with large doses of any beta-lactam antibiotic but less than 0.1% with shorter duration of therapy. In greater than 95% of cases recovery occurred between one to seven days after withdrawal of beta-lactam antibiotics. Bone marrow aspirates were characterized by a lack of well-differentiated myeloid elements in the presence of numerous immature granulocyte precursors. Nine penicillins and eight cephalosporins inhibited in vitro granulopoiesis in a dose-dependent manner. There was a good correlation between the inhibitory capacity of beta-lactam antibiotics in vitro and the doses inducing neutropenia in vivo. These observations may be relevant for therapy in the granulocytopenic patient.

The glucocorticoid methylprednisolone has clinically important anti;inflammatory effects at high concentrations through unknown mechanisms. Methylprednisolone at 0.2 mg/107 cells inhibits respiration in Concanavalin-A(ConA)-stimulated thymocytes from rats by about 20%. We have used topdown elasticity analysis to identify the blocks of reactions within oxidative phosphorylation in thymocytes whose kinetics are significantly affected by treatment with methylprednisolone. At this concentration methylprednisolone greatly inhibited the reactions of substrate oxidation and increased mitochondrial proton leak but did not significantly affect the synthesis and turnover of ATP by the phosphorylating system. Metabolic control analysis showed that oxygen consumption by ConAtreated thymocytes was controlled largely (0.51) by the phosphorylating system but also by proton leak (0.32) and substrate oxidation (0.17); this is similar to the distribution of control in hepatocytes, suggesting that this pattern may be general in cells. Methylprednisolone lowered control by the phosphorylating system to 0.26 and raised control by substrate oxidation to 0.37. From these results we conclude that the inhibition of respiration in ConA-stimulated thymocytes by methylprednisolone at this concentration results from an inhibition of substrate oxidation and a smaller stimulation of mitochondrial proton leak, with only a minor contribution of any effects within the phosphorylating system.The therapeutic effects of glucocorticoids are mostly receptor-mediated. However, clinical observations and experimental findings suggest that there are also rapid direct effects that are not mediated by induction or repression of specific genes. It is well known that the application of methylprednisolone in megadoses is an effective treatment in acute situations of autoimmune diseases (see e.g. Barile and La- Abbreviations. ConA, concanavalin A ; C, overall flux control coefficient; E , overall elasticity coefficient, J,,, or J,, total rate of oxygen consumption; J , rate of oxygen consumption required to pump protons out at a rate equal to their rate of return through the phosphorylating system ; JL, rate of oxygen consumption required to pump protons out at a rate equal to their rate of return through the proton leak; A tym, mitochondrial membrane potential; FCCP, carbonyl cyanide p-trifluoromethoxyphenylhydrazone; Ph,MeP+, triphenylmethylphosphonium cation ; Ph,MePBr, triphenylmethylphosphonium bromide ; P/O ratio, ATP molecules synthesized0 atom consumed; ADP/O ratio, ADP molecules consumed/O atom consumed. The superscripts and subscripts S, L and P refer to the three blocks of reactions that produce or consume dtyy,: substrate oxidation (cytosolic catabolic reactions, citric acid cycle, electron transport chain), proton leak (leak of protons and any proton-transporting cation cycles across the mitochondrial inner membrane) and the phosphorylation system (ATP synthesis and transport, all cellular ATP-consuming reactions) respectively. valle, 1992; de Gla...

In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and increasingly potent hardware and software that enables us to work with these new big data streams. At the same time, many challenging problems have been identified. First, there is often a mismatch between how rapidly online data can change, and how rapidly algorithms are updated, which means that there is limited reusability for algorithms trained on past data as their performance decreases over time. Second, much of the work is focusing on specific issues during a specific past period in time, even though public health institutions would need flexible tools to assess multiple evolving situations in real time. Third, most tools providing such capabilities are proprietary systems with little algorithmic or data transparency, and thus little buy-in from the global public health and research community. Here, we introduce Crowdbreaks, an open platform which allows tracking of health trends by making use of continuous crowdsourced labeling of public social media content. The system is built in a way which automatizes the typical workflow from data collection, filtering, labeling and training of machine learning classifiers and therefore can greatly accelerate the research process in the public health domain. This work describes the technical aspects of the platform, thereby covering the functionalities at its current state and exploring its future use cases and extensions.

IntroductionThis study presents COVID-Twitter-BERT (CT-BERT), a transformer-based model that is pre-trained on a large corpus of COVID-19 related Twitter messages. CT-BERT is specifically designed to be used on COVID-19 content, particularly from social media, and can be utilized for various natural language processing tasks such as classification, question-answering, and chatbots. This paper aims to evaluate the performance of CT-BERT on different classification datasets and compare it with BERT-LARGE, its base model.MethodsThe study utilizes CT-BERT, which is pre-trained on a large corpus of COVID-19 related Twitter messages. The authors evaluated the performance of CT-BERT on five different classification datasets, including one in the target domain. The model's performance is compared to its base model, BERT-LARGE, to measure the marginal improvement. The authors also provide detailed information on the training process and the technical specifications of the model.ResultsThe results indicate that CT-BERT outperforms BERT-LARGE with a marginal improvement of 10-30% on all five classification datasets. The largest improvements are observed in the target domain. The authors provide detailed performance metrics and discuss the significance of these results.DiscussionThe study demonstrates the potential of pre-trained transformer models, such as CT-BERT, for COVID-19 related natural language processing tasks. The results indicate that CT-BERT can improve the classification performance on COVID-19 related content, especially on social media. These findings have important implications for various applications, such as monitoring public sentiment and developing chatbots to provide COVID-19 related information. The study also highlights the importance of using domain-specific pre-trained models for specific natural language processing tasks. Overall, this work provides a valuable contribution to the development of COVID-19 related NLP models.

Mitochondrial inclusion bodies are often described in skeletal muscle of patients suffering diseases termed mitochondrial myopathies. A major component of these structures was discovered as being mitochondrial creatine kinase. Similar creatine kinase enriched inclusion bodies in the mitochondria of creatine depleted adult rat cardiomyocytes have been demonstrated. Structurally similar inclusion bodies are observed in mitochondria of ischemic and creatine depleted rat skeletal muscle. This paper describes the various methods for inducing mitochondrial inclusion bodies in rodent skeletal muscle, and compares their effects on muscle metabolism to the metabolic defects of mitochondrial myopathy muscle. We fed rats with a creatine analogue guanidino propionic acid and checked their solei for mitochondrial inclusion bodies, with the electron microscope. The activity of creatine kinase was analysed by measuring creatine stimulated oxidative phosphorylation in soleus skinned fibres using an oxygen electrode. The guanidino propionic acid-rat soleus mitochondria displayed no creatine stimulation, whereas control soleus did, even though the GPA solei had a five fold increase in creatine kinase protein per mitochondrial protein. The significance of these results in light of their relevance to human mitochondrial myopathies and the importance of altered cell energetics and metabolism in the formation of these crystalline structures are discussed.

ATP production of Ehrlich ascites tumour cells was estimated on the basis of their coupled respiration and lactate formation. ATPconsuming processes were assessed from the effects of selective inhibitors of RNA synthesis, protein synthesis and proteolysis, Na+/K+-ATPase and CaZ+-ATPase on respiration. The extent of protein synthesis and proteolysis were also determined directly. From these values and those of the inhibition of respiration by selective inhibitors, a P/O ratio of 2.2 was calculated. About 75% of the total ATP consumption could be assigned to specific processes. The major ATP-consuming processes of tumour cells in an amino-acidenriched medium, in which they are in an approximate steady state, are protein synthesis with about 30% of total ATP consumption, and Na+/K+-ATPase with about 20%, while RNA synthesis, ATP-dependent proteolysis and Ca2+-ATPase contribute about 10% each. In an amino-acid-free glucose medium, protein synthesis is reduced to a third, with a corresponding decrease of respiration, whereas the rate of the other ATP-consuming processes is unchanged.Meyerhof was perhaps the first to demonstrate that consumption of ATP is a necessary requirement for continuous ATP production and a steady state of metabolism without accumulation of intermediary products in glycolysis [l]. The first accounting and balancing of ATP production and consumption on a respiring cell was made on the relatively simple metabolic system of rabbit reticulocytes [2], which lack DNA and RNA synthesis. It was found that about 70% of ATP consumption was accounted for by protein synthesis, Na+/ K + -ATPase and ATP-and ubiquitin-depending proteolysis. Therefore we proceeded to study a more complex cell, the Ehrlich ascites tumour cell, which is the object of the present report. Previously Racker et al. had performed a partial balance of ATP production and consumption on such cells [3]. They demonstrated that 50% of the ATP produced by phosphate-stimulated glycolysis may be consumed by Na+/ K+-ATPase. Since, however, even in tumour cells ATP is formed predominantly by oxidative phosphorylation, it appears necessary to estimate its contribution and also to take account of other ATP-consuming processes. We estimated ATP production from the coupled respiration and lactate formation. The extent of various ATP-consuming processes, i. e. protein synthesis, ATP-dependent proteolysis, RNA synthesis, Na+/K+-ATPase and CaZ +-ATPase, was assessed from the effect of selective inhibitors on coupled respiration. Protein synthesis and consumption were determined directly, thus permitting an estimate of the P/O ratio. MATERIAL AND METHODSThe Ehrlich tumour was propagated in female mice of the ICR strain by intraperitoneal transplantation. Tumour cells were obtained by peritoneal puncture 6-13 days after inCorrespondence to s.

The ATP-dependent breakdown of mitochondria-containing stroma proceeds via the ubiquitin-requiring pathway. The proteolysis is linked to a large ATP-cleaved consumption amounting to 1 ATP per peptide bond or more. Proteins of mitochondria-containing stroma are much better substrates of ATP-ubiquitindependent proteolysis than heat-denatured ones. Hemin suppresses both proteolysis and ATP hydrolysis.

Background The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available. Objective We aim to characterize and compare the start, peak, and doubling time of COVID-19 misinformation topics across 8 countries using an exponential growth model usually employed to study infectious disease epidemics. Methods COVID-19 misinformation topics were selected from the World Health Organization Mythbusters website. Data representing exposure was obtained from the Google Trends application programming interface for 8 English-speaking countries. Exponential growth models were used in modeling trends for each country. Results Searches for “coronavirus AND 5G” started at different times but peaked in the same week for 6 countries. Searches for 5G also had the shortest doubling time across all misinformation topics, with the shortest time in Nigeria and South Africa (approximately 4-5 days). Searches for “coronavirus AND ginger” started at the same time (the week of January 19, 2020) for several countries, but peaks were incongruent, and searches did not always grow exponentially after the initial week. Searches for “coronavirus AND sun” had different start times across countries but peaked at the same time for multiple countries. Conclusions Patterns in the start, peak, and doubling time for “coronavirus AND 5G” were different from the other misinformation topics and were mostly consistent across countries assessed, which might be attributable to a lack of public understanding of 5G technology. Understanding the spread of misinformation, similarities and differences across different contexts can help in the development of appropriate interventions for limiting its impact similar to how we address infectious disease epidemics. Furthermore, the rapid proliferation of misinformation that discourages adherence to public health interventions could be predictive of future increases in disease cases.