Vitamin B12 Supplementation in Diabetic Neuropathy: A 1-Year,Randomized, Double-Blind,Placebo-Controlled Trial

Aim: To investigate the effect of normalizing vitamin B12 (B12) levels with oral B12 (methylcobalamin) 1000 μg/day for one year in patients with diabetic neuropathy (DN). Patients and methods: In this prospective, double-blind, placebo-controlled trial, 90 patients with type 2 diabetes on metformin for at least four years and both peripheral and autonomic DN were randomized to an active treatment group (n = 44) receiving B12 and a control group (n = 46) receiving a placebo. All patients had B12 levels less than 400 pmol/L. Subjects underwent measurements of sural nerve conduction velocity (SNCV), sural nerve action potential (amplitude) (SNAP), and vibration perception threshold (VPT), and they performed cardiovascular autonomic reflex tests (CARTs: mean circular resultant (MCR), Valsalva test, postural index, and orthostatic hypotension). Sudomotor function was assessed with the SUDOSCAN that measures electrochemical skin conductance in hands and feet (ESCH and ESCF, respectively). We also used the Michigan Neuropathy Screening Instrument Questionnaire and Examination (MNSIQ and MNSIE, respectively) and questionnaires to evaluate quality of life (QoL) and level of pain (pain score). Results: B12 levels increased from 232.0 ± 71.8 at baseline to 776.7 ± 242.3 pmol/L at follow-up, p < 0.0001, in the active group but not in the control group. VPT, MNSIQ, QoL, pain score, SNCV, SNAP, and ESCF significantly improved in the active group (p < 0.001, p = 0.002, p < 0.0001, p < 0.000, p < 0.0001, p < 0.0001, and p = 0.014, respectively), whereas CARTS and MNSIE improved but not significantly. MCR, MNSIQ, SNCV, SNAP, and pain score significantly deteriorated in the control group (p = 0.025, p = 0.017, p = 0.045, p < 0.0001, and p < 0.0001, respectively). Conclusions: The treatment of patients with DN with 1 mg of oral methylcobalamin for twelve months increased plasma B12 levels and improved all neurophysiological parameters, sudomotor function, pain score, and QoL, but it did not improve CARTS and MNSIE.     

Universal HIV testing and treatment and HIV stigma reduction: a comparative thematic analysis of qualitative data from the HPTN 071 (PopART) trial in South Africa and Zambia

Despite continued development of effective HIV treatment, expanded access to care and advances in prevention modalities, HIV‐related stigma persists. We examine how, in the context of a universal HIV‐testing and treatment trial in South Africa and Zambia, increased availability of HIV services influenced conceptualisations of HIV. Using qualitative data, we explore people’s stigma‐related experiences of living in ‘intervention’ and ‘control’ study communities. We conducted exploratory data analysis from a qualitative cohort of 150 households in 13 study communities, collected between 2016 and 2018. We found that increased availability of HIV‐testing services influenced conceptualisations of HIV as normative (non‐exceptional) and the visibility of people living with HIV (PLHIV) in household and community spaces impacted opportunities for stigma. There was a shift in community narratives towards individual responsibility to take up (assumingly) widely available service – for PLHIV to take care of their own health and to prevent onward transmission. Based on empirical data, we show that, despite a growing acceptance of HIV‐related testing services, anticipated stigma persists through the mechanism of shifting responsibilisation. To mitigate the responsibilisation of PLHIV, heath implementers need to adapt anti‐stigma messaging and especially focus on anticipated stigma.     

Use of retail data in the assessment of natural experiments: the case of Reducing the Strength,an intervention to reduce alcohol availability

BackgroundRetailers routinely collect data about people's purchasing behaviours and access to consumer products associated with health and wellbeing. Here we discuss how retail data can be used in public health research and consider potential strengths and limitations to such research. To illustrate the discussion we refer to an evaluation of an intervention called Reducing the Strength, whereby off-licence shops and supermarkets voluntarily stopped selling inexpensive superstrength (≥6·5% alcohol by volume) beers and ciders.MethodsMonthly data from a large retail chain (East of England Co-operative Society) were obtained for three UK counties (141 stores). In one county the intervention started 12 months earlier than the others, allowing for a pre–post study design with a delayed implementation comparator. Difference-in-differences analysis of unit alcohol sales controlled for socioenvironmental confounders and shop-level characteristics including shop size, parking facilities, cash machines, opening hours, and other factors.FindingsThe retail data detailed shop-level characteristics and sales data such as prices, quantities, product brands, alcohol content, sales, and factors affecting sales. The wide geographical coverage, shop-level data, including data for potential confounding factors, and frequent timepoints made the retail data well-suited for a quasi-experimental evaluation capitalising on temporal and spatial variations in intervention exposure. Limitations of this study include a lack of longitudinal data for individual customers, and shops that are not covered by the data. Qualitative interviews with shop workers and customers, and triangulation using alternative data sources can help to address limitations. Alternative sources of retail data such as private sector consultants who specialise in collecting shop-level and sales data for a range of companies might also address some limitations; however, there are potential barriers of expense, accessibility, and coverage associated with the use of such consultants.InterpretationIncreasingly, researchers recognise the potential of retail data for evaluating interventions affecting social determinants of health and inequalities, such as local access to alcohol. However, shop-level data have frequently proved difficult for researchers to obtain. By obtaining such data we have been able to assess, using a quasi-experimental design, the effects of removing strong, cheap beers and ciders from shops. We have also been able to explore in more detail how to optimise the strengths and address some limitations of the data in ways that could potentially assist others planning to use this important data source in their research.FundingThe study is funded as part of the School of Public Health Research by NHS National Institute of Health Research. AJ, SA, and JW contributed as employees of Public Health Suffolk, Suffolk County Council.     

In silico dynamics of COVID-19 phenotypes for optimizing clinical management

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin−angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8⁺ T cells and sufficient control of the innate immune response. Furthermore, the best treatment—or combination of treatments—depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

COVID-19 has created unprecedented challenges for the health care system, and, until an effective vaccine is developed and made widely available, treatment options are limited. A challenge to the development of optimal treatment strategies is the extreme heterogeneity of presentation. Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in a syndrome that ranges in severity from asymptomatic to multiorgan failure and death. In addition to local complications in the lung, the virus can cause systemic inflammation and disseminated microthrombosis, which can cause stroke, myocardial infarction, or pulmonary emboli (1–4). Risk factors for poor COVID-19 outcome include advanced age, obesity, diabetes, and hypertension (5–13).Computational analyses can provide insights into the transmission, control, progression, and underlying mechanisms of infectious diseases. Indeed, epidemiological and statistical modeling has been used for COVID-19, providing powerful insights into comorbidities, transmission dynamics, and control of the disease (14–17). However, to date, these analyses have been population dynamics models of SARS-CoV-2 infection and transmission or correlative analyses of COVID-19 comorbidities and treatment response. Simple viral dynamics models have been also developed and used to predict the SARS-CoV-2 response to antiviral drugs (18, 19). These models, however, do not explicitly consider the biological or physiological mechanisms underlying disease progression or the time course of response to various therapeutic interventions, and only a few more-sophisticated models have been developed toward this direction (20, 21).Several therapies targeting various aspects of COVID-19 pathogenesis have been proposed and have either completed—or are currently being tested in—clinical trials (22). Despite strong biologic rationale, these treatments have generally produced conflicting results in the clinic. For example, trials of antiviral therapies (e.g., remdesivir) have been mixed: The original trial from China failed (23), a subsequent trial in the United States led to approval of remdesivir in the United States and other countries (24), and the recent results of the World Health Organization Solidarity trial again show no benefit (25). Other antiviral drugs alone or in combination are also showing promise (26).Other potential treatments include antiinflammatory drugs and antithrombotic agents. Because of the systemic inflammation seen in many patients, antiinflammatory drugs have been tested, including anti-IL6/IL6R therapy (e.g., tocilizumab, siltuximab) and anti-JAK1/2 drugs (e.g., barcitinib). It is not clear whether these drugs will be effective as stand-alone treatments, particularly after the recent failure of tocilizumab in a phase III trial (1, 27–29). In addition, given that a common complication of COVID-19 is the development of coagulopathies with microvascular thrombi potentially leading to the dysfunction of multiple organ systems (2, 3), antithrombotic drugs (e.g., low molecular weight heparin) are being tested. Recognizing the interactions of COVID-19 with the immune system (30), the corticosteroid dexamethasone has been tested, showing some promising results. Given the large range of patient comorbidities, disease severities, and variety of complications such as thrombosis, it is likely that patients will have heterogeneous responses to any given therapy, and such heterogeneity will continue to be a challenge for clinical trials of unselected COVID-19 patients (31).Here, we developed a systems biology-based mathematical model to address this urgent need. Our model incorporates the known mechanisms of SARS-CoV-2 pathogenesis and the potential mechanisms of action of various therapeutic interventions that have been tested in COVID-19 patients. In previous work, we have exploited angiotensin receptor blockers (ARBs) and angiotensin converting enzyme inhibitors (ACEis) for the improvement of cancer therapies and developed mathematical models of the renin−angiotensin system in the context of cancer desmoplasia (32–35). Using a similar approach, we developed a detailed model that includes lung infection by the SARS-CoV-2 virus and a pharmacokinetic/pharmacodynamic (PK/PD) model of infection and thrombosis to simulate events that take place throughout the body during COVID-19 progression (Fig. 1 and SI Appendix, Fig. S1). The model is first validated against clinical data of healthy people and COVID-19 patients and then used to simulate disease progression in patients with specific comorbidities. Subsequently, we present model predictions for various therapies currently employed for treatment of COVID-19 alone or in combination, and we identify protocols for optimal clinical management for each of the clinically observed COVID-19 phenotypes.Open in a separate windowFig. 1.Schematic of the detailed lung model. The model incorporates the virus infection of epithelial and endothelial cells, the RAS, T cells activation and immune checkpoints, the known IL6 pathways, neutrophils, and macrophages, as well as the formation of NETs, and the coagulation cascade. The lung model is coupled with a PK/PD model for the virus and thrombi dissemination through the body.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Causes, consequences, and remedies for growth-induced solid stress in murine and human tumors

The presence of growth-induced solid stresses in tumors has been suspected for some time, but these stresses were largely estimated using mathematical models. Solid stresses can deform the surrounding tissues and compress intratumoral lymphatic and blood vessels. Compression of lymphatic vessels elevates interstitial fluid pressure, whereas compression of blood vessels reduces blood flow. Reduced blood flow, in turn, leads to hypoxia, which promotes tumor progression, immunosuppression, inflammation, invasion, and metastasis and lowers the efficacy of chemo-, radio-, and immunotherapies. Thus, strategies designed to alleviate solid stress have the potential to improve cancer treatment. However, a lack of methods for measuring solid stress has hindered the development of solid stress-alleviating drugs. Here, we present a simple technique to estimate the growth-induced solid stress accumulated within animal and human tumors, and we show that this stress can be reduced by depleting cancer cells, fibroblasts, collagen, and/or hyaluronan, resulting in improved tumor perfusion. Furthermore, we show that therapeutic depletion of carcinoma-associated fibroblasts with an inhibitor of the sonic hedgehog pathway reduces solid stress, decompresses blood and lymphatic vessels, and increases perfusion. In addition to providing insights into the mechanopathology of tumors, our approach can serve as a rapid screen for stress-reducing and perfusion-enhancing drugs.     

Staphylococcus aureus interactions with the endothelium: the role of bacterial "secretable expanded repertoire adhesive molecules" (SERAM) in disturbing host defense systems

The intravascular manifestation of Staphylococcus aureus infection is often associated with a severe, and sometimes catastrophic disease. Many host factors contribute to endothelial tropism of S.aureus including subendothelial matrix proteins, endothelial cell receptors, and platelets that are engaged together with S. aureus cell wall adhesins such as the fibronectin binding proteins. Recently, the role of secreted staphylococcal factors that were initially identified by virtue of their binding function with host proteins and ligands, has been reappraised in this regard. Among these, bacterial proteins without significant homology among each other, coagulase (Coa), the extracellular fibrinogen binding protein (Efb), the extracellular matrix binding protein (Emp), or the extracellular adhesive protein (Eap), are the most prominent ones to be associated with endovascular disease. Newly discovered interactions with host components may account for profound effects on immunmodulation and wound healing which are summarized in this short review and which ascribe an important role of these molecules in acute and chronic endo- and extravascular staphylococcal disease. Further research in the complex functional role of these "secretable expanded repertoire adhesive molecules" (SERAM) may not only help to increase our understanding in the pathogenesis of S. aureus infection but can specify novel targets for preventive or therapeutic strategies.