Alcohol drinking is an increasingly recognized risk factor for cardiovascular disease. However, there are few studies of the impact of harmful and hazardous drinking on biomarkers of myocardial health. We conducted a study in Russia to investigate the impact of heavy drinking on biomarkers of cardiac damage and inflammation.CI, 3.7%–17.4%), NT‐proBNP by 46.7% , and hsCRP by 69.2% . In the general population sample, NT‐proBNP was 31.5%  higher among harmful drinkers compared with nonproblem drinkers. Overall, NT‐proBNP and hsCRP increased with increasing intensity of alcohol exposure (test of trend P<0.001).The Know Your Heart study recruited a random sample of 2479 participants from the population of northwest Russia  plus 278 patients (narcology clinic subsample) with alcohol problems. The general population sample was categorized into harmful drinkers, hazardous drinkers, nonproblem drinkers, and nondrinkers, according to self‐reported level of alcohol consumption, whereas the narcology clinic sample was treated as the separate group in the analysis. Measurements were made of the following: (1) high‐sensitivity cardiac troponin T, (2) NT‐proBNP , and (3) hsCRP (high‐sensitivity C‐reactive protein). The narcology clinic subsample had the most extreme drinking pattern and the highest levels of all 3 biomarkers relative to nonproblem drinkers in the general population: high‐sensitivity cardiac troponin T was elevated by 10.3% (95% These results support the hypothesis that heavy alcohol drinking has an adverse effect on cardiac structure and function that may not be driven by atherosclerosis. In the population‐based study, we observed elevated levels of markers of heart damage, cardiac wall stretch, and general inflammation among heavy alcohol users compared with nonproblem drinkers.Heavy drinking was confirmed as an important risk factor of cardiovascular disease, with probable direct effect on cardiac structure and function.Prevention of cardiovascular diseases in the general population should include screening and intervening on harmful and hazardous alcohol use.Alcohol drinking is increasingly recognized as a risk factor for cardiovascular disease (CVD).Levels of blood‐based cardiovascular biomarkers can be used as proxy measures of cardiovascular health. High‐sensitivity cardiac troponin T (hs‐cTnT) and NT‐proBNP  were both developed for use in clinical cardiology and are now increasingly used in population‐based studies of CVD. When evaluating general population cohorts, any concentration of hs‐cTnT >3 ng/L has been associated with subclinical CVD and has adverse prognostic implications.There has been substantial interest in CRP (C‐reactive protein) as a risk predictor related to the underlying inflammatory nature of atherosclerosis,Previous research has looked at the relationship of biomarkers with classic risk factors for CVD, among them smoking, obesity indexes, blood pressure, and lipid profiles.Russia is one of the countries that has had a tradition of heavy drinking of spirits and has been characterized as having a particularly harmful drinking profile.Requests to access the data set from bona fide researchers may be sent to the International Project on Cardiovascular Disease in Russia.The Know Your Heart study recruited 2479 participants from the general population of the city of Arkhangelsk in northwest Russia from 2015 to 2018. A detailed account of the rationale and description of the methods of the study has been published previously.All procedures performed were in accordance with the ethical standards of the institutional research committee  and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. All participants included in the analysis gave signed informed consent.The general population sample from Arkhangelsk was recruited at random  using the regional health insurance fund register as the sampling frame. Trained interviewers visited the addresses selected and invited the appropriate resident at each address to take part in the study. A minimum of 3 attempts were made to get a response from each address. When successful, an interview was conducted about circumstances, health, and behaviors of the participant. The response rate was 68% of the addresses where contact with a person of the target age and sex was established, and 96% of those interviewed took part in a subsequent health check.Experiencing alcohol withdrawal symptoms or during the first week of alcohol detoxification;Behavior that suggested that an individual could pose a threat to the safety of the clinic staff or other participants during the survey;Current or past misuse of drugs other than nicotine or alcohol;Unable to give informed consent for participation in the study .In addition, a sample of heavy drinkers (narcology clinic subsample) were recruited from inpatients at the regional psychiatric hospital. The inclusion criteria were as follows: age of 35 to 69 years, resident in the city of Arkhangelsk or Arkhangelsk region, and admitted to the narcological department of the regional psychiatric hospital with a primary diagnosis related to alcohol drinking. People with ≥1 of the following characteristics were excluded:Clinicians at the hospital used their judgement to decide which participants should or should not be invited. Signed informed consent was obtained. A total of 278 patients were recruited of 322 patients invited (85.4%).We analyzed data on 2354 participants from the general population in Arkhangelsk plus 271 individuals from the narcology clinic subsample who attended the health check and for whom blood analyte concentrations were available.The baseline interview was administered by a trained interviewer using a tablet computer‐assisted personal interviewing device. For the general population sample, the interview was done in people's homes in nearly all cases. For the narcology clinic subsample, it was done at the Arkhangelsk Regional Psychiatric Hospital by the same set of trained interviewers. Information was collected on medical history and socioeconomic circumstances, education, and lifestyle.The subsequent health check comprised a physical examination  and blood sample collection. Participants were requested not to eat or drink alcohol in the 4 hours before their appointment. Participants in the narcology clinic subsample were transported to the research clinic for the health check, accompanied by a nurse. A second interview was conducted at this stage that recorded medical history, use of medications, alcohol use, and smoking.A total of 50 mL of blood was taken from each participant. Samples were centrifuged, and serum was transferred to barcoded 1.8‐mL cryovials and frozen (−80°C) within 2 hours after venipuncture. These were subsequently shipped to a laboratory in Moscow, where they were stored at −80°C and then analyzed in a single batch at the end of the fieldwork. The laboratory staff were blind to all characteristics of participants, including whether serum was from the narcology clinic subsample or the general population sample.hs‐cTnT and NT‐proBNP were measured using a high‐sensitivity electrochemiluminescence immunoassay  on a Cobas e411 analyzer. hsCRP was measured using a high‐sensitivity immunoturbidimetric test on AU 680 Chemistry System Beckman Coulter. The lower limit of detection for hs‐cTnT test was 3 ng/L, and 54 participants (2.07%) with values below the limit of detection had their values recoded to 2.9 ng/L. The limit of detection of NT‐proBNP test was 5 ng/L, and NT‐proBNP values of 19 participants (0.7%) with values below the limit of detection were recoded to 4.9 ng/L. Because we were interested in low‐grade inflammation that is not caused by acute infection, 38 participants with hsCRP values >99th percentile for the general population (30 mg/L) were excluded from the statistical analysis of hsCRP.We defined 2 categorical exposure variables. The first was binary and divided the study group into those from the narcology clinic subsample and those from the general population sample. The second exposure variable further categorized the general population sample into groups based on self‐report of various dimensions of alcohol consumption. Those who reported not drinking alcoholic beverages during the past 12 months at baseline interview and health check were classified as nondrinkers. The categories of harmful and hazardous drinkers were defined using 3 instruments: the validated Russian‐language translations of the Alcohol Use Disorders Identification Test,To validate the approach chosen for classification of the general population sample into drinking categories, we used the following: (1) information on alcohol volume consumed during the past 12 months, calculated using the standard quantity frequency approachInformation was available on classic risk factors, including those that are on the potential causal pathway between alcohol use and CVD biomarkers. We constructed directed acyclic graphs to identify the minimal sufficient adjustment set of variables for estimating the total effect of alcohol use Figures . These wOther variables used in the analysis included potential mediators. These included systolic and diastolic blood pressure (mean of second and third measurements) and use of antihypertensives, determined according to recorded medications coded to the Anatomical Therapeutic Chemical classification as C02 (antihypertensives), C03 (diuretics), C07 (β‐blocking agents), C08 , or C09 (agents operating on the renin‐angiotensin system). A small proportion of participants self‐reported use of blood pressure–lowering medication without a corresponding Anatomical Therapeutic Chemical code being found. These participants were also defined as being on antihypertensives.Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters) squared. Waist/hip ratio was the mean of 2 measurements of waist divided by the mean of 2 measurements of hip. The blood lipid profile was measured and included total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, apolipoprotein A1, and apolipoprotein B. Renal function was assessed by measuring cystatin C and estimated glomerular filtration rate using the Chronic Kidney Disease Epidemiology Collaboration cystatin C equation.Descriptive tabulations of participant characteristics were age and sex standardized to the Standard European Population 2013. hs‐cTnT, NT‐proBNP, and hsCRP had right‐skewed distributions and were ln transformed for analysis.We assessed the association between alcohol use and biomarkers of CVD  by comparing geometric mean levels of biomarkers in the narcology and general population samples. Next, we compared means of ln‐transformed biomarkers across the categories of alcohol consumption: (1) narcology clinic subsample; (2) general population sample, harmful drinking pattern; (3) general population sample, hazardous drinking pattern; (4) general population sample, nonproblem drinkers; and (5) general population sample, nondrinkers. This approach allowed a nuanced assessment of CVD biomarkers, depending on the drinking pattern, separating nonproblem drinkers as a comparison group and determining if there was an increasing trend with increased intensity of alcohol use.P<0.05. Model 1 involved adjustment for age and sex. Model 2 adjusted for potential confounders . Model 3 additionally included possible mediators . This final model provided an estimate for the direct effect of alcohol on cardiac damage, cardiac wall stretch, and low‐grade inflammation. A test for increasing linear trend in means of biomarkers across the categories of alcohol exposure was done with df=1. To make the regression coefficients more interpretable and comparable, they were back transformed and presented as percentage of difference in mean compared with the reference category (nonproblem drinkers). Statistical analysis was performed using SAS software 9.4 .The sociodemographic characteristics and CVD risk factors were compared by the categories of main exposure variable using heterogeneity tests adjusting for age and sex in generalized linear models. The associations between alcohol use and ln‐transformed biomarkers of CVD  were assessed using multivariable adjusted linear regression models. Age was included in the model as a continuous variable. Quadratic and cubic terms were added to account for nonlinearity and kept in the modelif associated with an outcome at The descriptive characteristics of the narcology clinic subsample and the general population sample (age and sex standardized) are presented in Table The face validity of our categorization of alcohol use is demonstrated in Table After adjustment for age, sex, smoking, and education, the levels of all biomarkers  were higher in the narcology clinic subsample compared with the general population sample as a whole Table . SpecifiConsistent with the previous analysis, compared with nonproblem drinkers in the general population sample, the narcology clinic subsample had much higher levels of hs‐cTnT, NT‐proBNP, and hsCRP Table .hs‐cTnT was elevated by 10.3%  in the narcology clinic subsample compared with the nonproblem drinkers in the general population, controlling for sex, age, smoking, and education. However, hs‐cTnT levels were lower in the group of harmful drinkers in the general population compared with nonproblem drinkers. Adjustment for the additional set of variables that are likely to be the mediators of the association between extremely heavy alcohol use and cardiac injury (determined via hs‐cTnT) had only a minor effect on parameter estimates  compared with nonproblem drinkers, but to lesser extent than in the narcology clinic subsample , controlling for age, sex, smoking, and education. Adjustment for potential mediators of the association between excessive alcohol use and cardiac wall stretch (measured by NT‐proBNP) resulted in some attenuation of the effect estimate  was observed in the narcology clinic subsample compared with nonproblem drinkers in the general population sample, controlled for age, sex, smoking, and education. Intermediate elevations were also seen for harmful drinkers. Further adjustment for covariates that are likely to be on the mediation pathway between alcohol use and hsCRP leads to increases in the regression coefficient  was significant for NT‐proBNP and hsCRP, with concentration of biomarkers higher with higher level of alcohol exposure Table .hs‐cTnT assays are known to show appreciable imprecision at the low values seen in the general population.Separating the category of nondrinkers into never drinkers and ex‐drinkers for regression analysis did not reveal any specific differences in biomarkers between these 2 groups; therefore, the results were presented keeping current nondrinkers as one group.In a further sensitivity analysis, we excluded those with previous myocardial infarction, operations on the heart, and grade 2 angina (N=307 [11.73%]) to see if elevated cardiac injury and cardiac wall stretch biomarkers were secondary to coronary heart disease. This had no material effect on the associations observed.In this study, we have shown that markers of cardiac injury hs‐cTnT, cardiac wall stretch NT‐proBNP, and general inflammation hsCRP are substantially elevated among those receiving treatment for alcohol problems at the narcology clinic compared with the general population. Most important, there was a significant linear increasing trend of NT‐proBNP across 4 groups of drinkers: nonproblem drinkers, hazardous drinkers, harmful drinkers, and the narcology clinic sample. Similarly, there was a linear increase in hsCRP levels over drinking groups.NT‐proBNP has been developed and primarily used in the clinical contexts of diagnosis and prognosis of heart failure.After the adjustment for the possible mediators of the association between alcohol use and NT‐proBNP , the regression coefficients were partly attenuated. This could be explained by an effect of alcohol on kidney function because it was shown that risk of chronic kidney disease is higher in people with alcohol use disorder.The direct toxic effect of alcohol on the heart as a result of persistent heavy drinking is an established mechanism of alcoholic cardiomyopathy.Cardiac troponin T elevation is a biomarker used for the diagnosis of acute myocardial infarction. Development of the testing technology and introduction of hs‐cTnT tests led to recognition that low‐grade elevations of hs‐cTnT are predictive of future cardiovascular events and death in general population.A U‐shaped relation between alcohol intake and CRP was previously observed, with heavy drinkers showing higher CRP than moderate drinkers.Our study has several strengths that make it a significant contribution to the body of evidence on detrimental effects of alcohol on cardiovascular health by relating harmful and hazardous alcohol use to the markers of cardiac damage, cardiac wall stretch, and low‐grade inflammation. We were able to recruit a substantial number of participants with substantial variation in the level and intensity of alcohol drinking. In addition, this study has addressed a gap in the research literature about the impact of high levels of exposure on cardiac injuryPrevious studies of association between alcohol consumption and CVD biomarkers are few and done in populations with relatively moderate quantities of consumed alcohol, whereas this study was able to differentiate between different patterns of heavy alcohol use, including extreme drinking patterns commonly observed in patients treated in Russian state‐run narcology services. Although patients there may experience multiple comorbidities, they are most likely the consequence of an extremely heavy pattern of alcohol use. Their admission to the narcology clinic was because of the need for detoxification rather than organic comorbidities. Therefore, it is a good setting to study the mechanisms of cardiac injury caused by heavy alcohol use; and the results are likely to be generalizable to all countries and populations.A particular strength of our study is that the collection of detailed questionnaire information on patterns and quantities of alcohol consumption during the past year has allowed us to construct a plausible grouping of general population participants according to degree of harmfulness of their alcohol consumption with strong face validity. Moreover, our ability to separate nondrinkers from nonproblem drinkers and the availability of data on confounders beyond age and sex have minimized the bias common to many other studies on alcohol drinking and CVD.The elevated levels of both NT‐proBNP and hs‐cTnT in the group of extremely heavy drinkers from the narcology subsample are consistent with heavy alcohol drinking leading to nonischemic damage of the heart. Elevated NT‐proBNP in harmful drinkers from the general population provides further evidence for this. Furthermore, exclusion of individuals who had a previous diagnosis of coronary heart disease did not have an impact on the substantive results. However, this study cannot definitively exclude that heavy drinking may also contribute to increased CVD risk through ischemic pathways, as could be indicated by elevated hsCRP. The significance of findings in this study and the relative importance of different pathophysiological processes in harmful and hazardous drinkers should be further investigated using heart imaging methods. Echocardiography and cardiac magnetic resonance imaging can give more information about significance of cardiomyopathy‐related indexes in excessive drinkers. Computerized tomography coronary angiogram or carotid ultrasound will allow direct measurement of the extent of atherosclerosis and will answer the question about significance of elevated hsCRP levels in harmful and hazardous drinkers.The results of this study help to explain why heavy alcohol drinking has been related to excess mortality in Russia if considered in the context of previous studies exploring causes of high cardiovascular mortality in Russia.The Know Your Heart study is a component of the International Project on Cardiovascular Disease in Russia (IPCDR). IPCDR was funded by a Wellcome Trust Strategic Award (100217), supported by funds from the University in Tromsø The Arctic University of Norway; Norwegian Institute of Public Health; and the Norwegian Ministry of Health and Social Affairs. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.None.Table S1. Association of High Values of hs‐cTrT (Above 9.34 ng/L) With Levels of Alcohol Use Figure S1. The directed acyclic graph (DAG) depicting the suggested causal relationship between heavy alcohol use and heart damage (hs‐cTrT serving as a biomarker).Figure S2. The directed acyclic graph (DAG) depicting the suggested causal relationship between heavy alcohol use and cardiac wall stretch (NT‐proBNP serving as a biomarker).Figure S3. The directed acyclic graph (DAG) depicting the suggested causal relationship between heavy alcohol use and systemic inflammation (hsCRP serving as a biomarker).Click here for additional data file.


Various cardiac arrhythmias and conduction defects have been described in patients with mitral valve prolapse. We describe a case of a young woman affected by a mitral valve prolapse, involving the posterior mitral leaflet, with mild mitral regurgitation and an episode of syncope due to asystolia. It is hoped that this short communication will once again focus attention on the as yet unexplained association between mitral valve prolapse and various cardiac conduction disorders. Various cardiac arrhythmias and conduction defects have been described in patients with mitral valve prolapse (MVP). 10This is a case report of a 23–year–old woman who presented to our Department of Cardiology with an episode of syncope. Clinical examination revealed a grade II systolic murmur and the electrocardiogram showed a first–degree atrio–ventricular block . EchocarFurther diagnostic tests, including a chest X–ray, thyroid function tests and coronary angiography were all within normal limits. Telemetric electrocardiography revealed multiple episodes of asystole, the longest of which lasted for four seconds . FollowiTachyarrhythmias have been shown to represent the most frequent and potentially dangerous clinical manifestation of MVP and there is an association between mitral valve prolapse and sudden cardiac death.13Atrio–ventricular conduction disturbances occur in mitral valve prolapse but the true mechanism(s) of arrhythmia is still unclear. In some patients with mitral valve prolapse, electro– physiological studies have demonstrated prolonged atrio–hisian intervals and/or abnormal responses to atrial pacing. In addition, a significant proportion of these patients had abnormalities of both sinus and atrio–ventricular node function, as well as distal His–Purkinje conduction abnormalities.Atrio–ventricular block of all three degrees are well documented in mitral valve prolapse,16The prevalence of AV conduction disturbances among patients with mitral valve prolapse is probably higher than expected. It is hoped that this short communication will focus attention on the as yet unexplained association between mitral valve prolapse and various cardiac conduction disorders.


Pulmonary mucormycosis is a life‐threatening invasive fungal infection usually seen in the background of immunosuppression, haematological malignancies, or uncontrolled diabetes. Immunocompetent hosts can also be affected. Isolated endobronchial mucormycosis is rare with only a few cases reported in the literature. Here, we present a case of an endobronchial mass masquerading as a tumour that was later diagnosed as invasive mucormycosis by histopathological examination. Pulmonary mucormycosis is a serious opportunistic fungal infection that occurs most commonly in immunocompromised but also reported in an immunocompetent host 2) of 64.7 mm Hg and saturation of 94% in room air. Her chest X‐ray revealed a complete homogenous opacity on the left side  and grade 4 chronic kidney disease (creatinine of 3.2 mg/dL) presented to the clinic with a history of productive cough and dyspnoea of grade 4 Modified Medical Research Council scale for a period of one week. She had a history of high‐grade squamous intraepithelial lesion on her pap smear a year back for which she has not consulted further. Her physical examination revealed tachypnoea and grossly reduced breath sounds on the left side. Her blood gas analysis on admission showed respiratory alkalosis with partial pressure of Oxygen  Mucormycosis can present as five predominant forms: rhino‐cerebral, pulmonary, cutaneous, gastrointestinal, or disseminated Pulmonary mucormycosis presenting as an endobronchial lesion is rare. A recent analysis revealed that only 60 cases of mucormycosis involving larger airways have been reported in the literature so far Our patient had both uncontrolled diabetes and renal failure as comorbidities. She presented with an endobronchial mass that was radiologically evident with collapse consolidation of the left lung. Bronchoscopy showed a fleshy vascular growth mimicking a bronchial adenoma or bronchogenic carcinoma. Biopsy confirmed the diagnosis. A high index of suspicion is required for diagnosis.Appropriate written informed consent was obtained for publication of this case report and accompanying images.


Recent reports demonstrate that applications of the biopolymer lignin can be helped by the use of a fraction of the lignin which has an optimal molecular weight range. Unfortunately, the current methods used to determine lignin's molecular weight are inconsistent or not widely accessible. Here, an approach that relies on 2D DOSY NMR analysis is described that provides a measure of lignin's molecular weight. Consistent results were obtained using this well‐established NMR technique across a range of lignins. Evening the playing field: Using DOSY NMR and the Mark Houwink Sakurada relationship to streamline access to reproducible lignin molecular weight estimations. One option is to use MALDI‐TOF MS however, it is challenging to both ionize lignin and ensure uniform ionization across its polydisperse MWD.w) and number average (Mn) molecular weights. Although there is wide spread use of this technique, it has been shown that repeat analyses performed on different GPC setups are inconsistent, inhibiting fair comparisons of data across different labs.The most popular method used to analyse lignin MW is gel permeation chromatography (GPC).We have previously shown that diffusion ordered spectroscopy (DOSY‐NMR) has potential for use in monitoring lignin MW.1H NMR and 1H,13C‐HSQC). To build upon our earlier study, 151 lignin fractions, generated in 13 different fractionations of several types of lignins were analysed. MHS analysis revealed a linear correlation with a reasonable r2 value (∼0.9). All DOSY measurements were performed using NMR samples of fixed lignin concentration (86 mg mL−1) and temperature 295 K. Several types of lignins were then used to test the concept and showed good agreement between the DOSY derived MW and that measured directly using GPC.The linear scaling of lignin diffusion coefficients found in our and more recently, other2w and Mn molecular weights, polydispersity, and linkage content (Table S1).The study was carried out using three diverse types of lignin (Table S1). An industrial Kraft lignin , was fractionated twice. Until very recently, it has been difficult to achieve this type of fractionation for unmodified Kraft lignin using volatile organic solvents only.2.1In order to generate fractions of lignin of variable MW, a solvent fractionation was used to divide the bulk material into narrower MW bands. Whilst our previous acetylation followed by selective dissolution approach enabled the use of volatile organic solvents only, new challenges arose in the further processing of these modified lignins.2.23,2) solution . In order to collate more independent data points for subsequent studies, DFSD and BHD lignin samples were also fractionated in an analogous way using 9 : 1 and 4 : 1 AM solutions, respectively (Tables S6 and S7). The success of the fractionation protocol was confirmed by GPC analysis showing, with only a few exceptions, that Mw values increased gradually with fraction number w) correlations with reasonably high r2 values for all fractionation experiments . Surprisingly, there was only very small variations in the calculated values of α and log K as a function of the lignin (Table S16). Of note was the similarity of MHS parameters when comparing fractions from unmodified Douglas Fir Softwood lignin with the fractions after they had been acetylated and reanalysed . From this comparison, it seems evident that acetylation has only a marginal effect on the structure adopted by lignin chains in a DMSO solution (i. e. modified vs native lignins).DOSY analysis was carried out on selected fractions from 10 different fractionations . Importantly, a standard protocol was used for each analysis (see Supplementary Information). The resulting diffusivity values were used in conjunction with the GPC‐determined M2 s−1±0.06 when a solution of lignin at 86 mg mL−1 in d6‐DMSO is analysed at 295 K  was found to be ±962 g mol−1 and the mean absolute percentage error (MAPE) was calculated as 19 % . The size of error was MW dependent with the greatest uncertainty found towards the heaviest fractions . This could be the result of poor signal to noise in the DOSY experiment or a result of greater degrees of freedom of possible conformations of the larger polymer chains in these fractions. The latter would not be detected by GPC leading to underestimations and possible outliers. Further error analysis was performed to investigate this by removing outliers from the dataset however this did not lead to a significant difference in the α and log K scaling factors, (see Table S16 & Supporting Information Section 10).Despite the convincing correlations observed, it was decided to explore in more detail potential limitations. Considering the DOSY NMR component of the analysis, we have previously reported that the heavy fractions, with log D values below −10.6 mw data were considered. GPC elution profiles are usually calibrated by well‐defined standards (in our case polystyrene), that are likely structurally different to lignin. For instance, it has been reported that an acetylated hardwood Kraft lignin is more compact than polystyrene in organic solvents (THF and DMSO) and could be approximately 6 times larger than estimated by GPC.w against Mw derived from DOSY for all 151 data points clearly shows that the largest residuals from the identity line occur at high Mw . In this region of the Mw distribution, there is likely a wider range of possible conformations/shapes of the lignin. Consequently, lignin is more likely to deviate from the structure of polystyrene in THF leading to inaccurate MW measurements. This hypothesis would be supported by the biasing of residuals seen in Figure S8, however, biasing of the MHS scaling factors by branching of larger lignin polymers cannot be excluded as well. We believe this further demonstrates the limitations of the Mw determination of lignin using GPC as suggested in the recent literature.Next, potential pitfalls in the GPC determination of the Mw were then calculated using the observed diffusivities and our generic MHS scaling parameters. These Mw values were then compared with the Mw values measured by GPC. Bulk samples of Lig A, Lig B, and Lig C are lignins that are represented in the calibration chart  of lignin samples from diffusivity values measured by DOSY NMR. This approach is potentially a widely accessible method to compare the Mw of lignins without GPC analysis that could be utilized by the community of synthetic chemists in addition to the qualitative monitoring of the polymer through processing strategies, in this case fractionation. A potential user only needs to do two things: (i) analyse their lignin sample by DOSY NMR under the conditions we describe and (ii) use our equation to convert the DOSY‐determined diffusivity into an estimate of the molecular weight. Although the proposed method streamlines access to Mw of lignin samples, the accuracy of these estimates is likely limited by the reliance on the use of the GPC during the calibration phase and we cannot exclude that there might be occasions when the proposed approach cannot be used. In the future, this may be improved by using more accurate methods to determine the lignin Mw for MHS calibration, providing access for the wider community.In summary, a wide range of lignins were fractionated using a selective dissolution solvent fractionation protocol. A MHS plot containing 151 data points from 13 separate fractionations showed a general trend in lignin diffusivity with increasing MW with an rFull Experimental details of this study can be found in the Supporting Information.The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


Post‐operative peripheral bronchopleural fistulas (BPF) are sometimes caused by post‐operative pneumonia and empyema. Conservative treatment options such as administration of antibiotics and chest tube drainage can have limited outcomes in certain cases. Bronchial occlusion is an effective treatment option if the target bronchi for BPF are identified. This case study describes a successful bronchial occlusion for peripheral BPF with endobronchial Watanabe spigots (EWSs) and a digital drainage system. This case involved a 70‐year‐old man who developed a post‐operative peripheral BPF after a left upper lobectomy. Bronchial occlusion with EWS was performed because the target bronchi responsible for BPF were clearly detected by a chest computerized tomography scan. The effectiveness of the occlusion was confirmed with the use of a digital drainage system immediately after the procedure was completed. The chest tube was removed one week following the bronchial occlusion procedure. A 70‐year‐old man who developed a post‐operative peripheral bronchopleural fistulas (BPF) after a left upper lobectomy. Bronchial occlusion with endobronchial Watanabe spigots (EWS) was performed because the target bronchi responsible for BPF were clearly detected by a chest computerized tomography scan. The effectiveness of the occlusion was confirmed with the use of a digital drainage system immediately after the procedure was completed. Post‐operative bronchopleural fistula (BPF) can occur as a serious complications of lung resection. This may result in increased morbidity and mortality for the patient. In the case of post‐operative peripheral BPF, bronchial occlusion can be an effective treatment if the target bronchi causing the BPF are identifiable. In this case report, we discuss a successful bronchial occlusion for post‐operative peripheral BPF with endobronchial Watanabe spigots (EWSs) and a digital drainage system.A 70‐year‐old man with bladder cancer underwent an endoscopic bladder tumour resection. Prior to him undergoing this surgery, a full body scan was performed, in which a lung tumour in his left upper lobe was identified. He was diagnosed with metastatic lung cancer and was admitted to our institution for the resection. Video‐assisted thoracoscopic surgery was undertaken to perform the left upper lobectomy. The patient's chest tube was removed on post‐operative day 3 without any complications. On post‐operative day 6, the patient developed dyspnoea, and a chest X‐ray image showed his left lung had collapsed because of post‐operative pneumothorax. Chest tube drainage was commenced, and by post‐operative day 19, he developed left empyema due to pneumonia in the residual left lung. With antibiotic therapy, the patient's inflammatory markers improved. However, on post‐operative day 42, massive air leakage was identified. The chest computed tomography (CT) scan showed damage to the lung tissue in the superior segment of the left lower lobe and several bronchi leading to the intrathoracic cavity (Fig. Post‐operative BPF can be a serious complication of lung resection and is associated with significant morbidity and mortality rates. It can be categorized as either central BPF or peripheral BPF. The common causes of peripheral BPF are necrotizing infections such as pulmonary tuberculosis, pneumonia, and empyema Commonly used surgical treatments, such as fenestration and thoracoplasty, can impair post‐operative quality of life, especially in patients with poor physical condition. It has been reported that bronchoscopic occlusion is effective for BPF and is less invasive than surgery In this case, we identified target bronchi through the use of a three‐dimensional CT scan and were able to achieve a good patient outcome by performing bronchial occlusion. Bronchial occlusion should be considered as the first treatment option when post‐operative BPF is detected and target bronchi are clearly identifiable.EWS is widely used as an occlusion material, especially for treating peripheral BPF A digital drainage system, such as the Thopaz, which was used in this case, provides objective real‐time data of the air leakage In conclusion, bronchial occlusion for peripheral BPF with EWS and a digital drainage system such as the Thopaz was an appropriate choice in this case. An important factor in the success of this procedure was identifying the target bronchi via CT scan and that the procedure was performed using appropriate instruments. Bronchial occlusion with EWS should be considered as the first treatment option when post‐operative BPF is detected and target bronchi are clearly identifiable.Appropriate written informed consent was obtained for publication of this case report and accompanying images.This study was conducted with the financial support of our department.


Cynomys spp.) display different degrees of susceptibility to experimental challenge with fully virulent Yersinia pestis, the causative agent of plague. We evaluated patterns in prairie dog susceptibility to plague to determine whether the historical occurrence of plague at location of capture was related to survival times of prairie dogs challenged with Y. pestis. We found that black‐tailed prairie dogs (Cynomys ludovicianus) from South Dakota (captured prior to the detection of plague in the state), Gunnison's prairie dogs (Cynomys gunnisoni) from Colorado, and Utah prairie dogs (Cynomys parvidens) from Utah were most susceptible to plague. Though the susceptibility of black‐tailed prairie dogs in South Dakota compared with western locations supports our hypothesis regarding historical exposure, both Colorado and Utah prairie dogs have a long history of exposure to plague. It is possible that for these populations, genetic isolation/bottle necks have made them more susceptible to plague outbreaks.Laboratory trials conducted over the past decade at U.S. Geological Survey National Wildlife Health Center indicate that wild populations of prairie dogs ( Cynomys spp.) from different populations across the western United States to plague challenge. We hypothesized that historical exposure to plague would affect the susceptibility of prairie dog populations to plague. We conclude that though historical exposure may play a role that connectivity of populations is also likely to affect a population's response to plague.We conduct meta‐analyses of the responses of prairie dogs ( Prairie dogs (Cynomys spp.) and ground squirrels (Spermophilus spp.) are highly susceptible to plague, with outbreaks often causing >90% mortality in affected colonies. Some studies have suggested that plague may also occur in prairie dog colonies at enzootic levels  arriving on ships from China, where the last worldwide pandemic of plague originated at the end of the 19th century , with animals from Texas and Colorado surviving at higher rates compared with animals from South Dakota where plague had not occurred previously. Pauli, Buskirk, Williams, and Edwards  versus a low altitude plague‐free area . For prairie dogs, elevation may provide a barrier that influences the level of connectedness in populations  to support the development of a bait‐delivered sylvatic plague vaccine (SPV) for prairie dogs  to assess the ability of SPV to protect prairie dogs  and with the same personnel responsible for inoculum preparation and injections of Y. pestis. These data included a total of 305 prairie dogs that were challenged but not vaccinated (positive controls) or received placebo vaccine baits. One hundred Gunnison's prairie dogs , from two states, and 143 adult black‐tailed prairie dogs from three states, were included from previous publications, as well as data from two unpublished studies, including 21 adult Utah prairie dogs (Cynomys parvidens) and 15 adult white‐tailed prairie dogs (Cynomys leucurus) from Colorado , stored frozen in glycerol at −20°C, were thawed and diluted in 1× phosphate‐buffered saline (PBS) to achieve the desired dosage of challenge inoculum (in MLD50). Prairie dogs were restrained by hand and injected subcutaneously with 0.2 ml of the inoculum. For the larger dose , the inoculum was divided and injected subcutaneously at six different injection sites, to simulate multiple flea bites. In every experiment, the challenge inoculum was also injected simultaneously in laboratory mice to confirm the intended dosage, and in every challenge, this dosage was achieved.Challenge inocula of fully virulent Ss|r=exp-∑i=rsexpγ+β1:k∗Xk; where S is the rate of survival to time point s given survival to time point r, γ is the intercept value, X is a matrix of k covariates, and β is a vector of the k estimated coefficients. The unit cumulative hazard (the hazard from r to s) is Λ=expγ+β1:k∗Xk, and we estimated the coefficients γ and β using rjags . Results of a Cox‐proportional hazard model indicate that Utah prairie dogs were less likely to survive challenge than all other populations of prairie dogs  upon plague challenge at 3,500 MLD50 and the greatest number of mean days until death, 22.1  compared with animals that received multiple injections with a 10× higher dosage , it is likely that changes in host genetics are the mechanism by which these differences occur  among closely neighboring colonies, as animals in varying stages of infection disperse from outbreak locations due to social upheaval  diet, and efforts to reintroduce black‐footed ferrets have been hampered by the decimation of prairie dog populations by plague. Prairie dog populations regularly exposed to plague may develop some level of resistance to the disease over time, and less susceptible prairie dogs may play a role in spreading plague or maintaining the bacterium between outbreaks. One potential outcome of lowered susceptibility is increased incubation time (Atkins, Townsend, Medlock, & Galvani, Prairie dogs form the basis of the endangered black‐footed ferret (None declared.Dr. Tonie Rocke conceived and designed the overall study, Mr. Daniel Tripp contributed to the Colorado portion of the study. Dr. Robin Russell conducted the statistical analyses and wrote the manuscript. All three authors contributed substantially to revisions of the paper.


Gastroenterological (GE) cancer is the leading cause of cancer‐related death, with the highest mortality rate worldwide. Although the recent development of multidisciplinary treatments has improved the prognosis of GE cancer, surgical treatment remains the mainstay of therapy. However, the clinical significance of extended surgery for advanced GE cancer has been contradicted by large‐scale clinical trials. It is well known that invasive surgical procedures or postoperative complications can lead to adverse effects not only on short‐term but also on long‐term outcomes for GE cancer. Many hospitals and surgeons have trouble tracking surgical complications and may lack the data necessary to analyze and take appropriate steps to correct problems. We cannot improve our surgical quality if we do not properly measure it, and so it is essential to establish a nationally validated, risk‐adjusted, outcomes‐based system to measure and improve the quality of surgical care.In Japan, the National Clinical Database (NCD) was founded in 2010 as the parent body of the database system linked to the board certification system.Annals of Gastroenterological Surgery. Hata et al show real‐world data in Japan regarding the frequency of and risk factors for venous thromboembolism (VTE) after GE surgery in 516 217 patients. Deep vein thrombosis was observed in 0.3% and pulmonary embolism in 0.2% of these patients. Esophagectomy, pancreatoduodenectomy and hepatectomy were identified as risk factors for VTE. Based on this finding, we should reconsider the use of prophylaxis anticoagulant medication for these procedures. Haga et al constructed a prediction model to estimate grade‐specific postoperative morbidity in gastrectomy using NCD data. This model can predict more precisely severe‐grade complications, such as grade ≥4 or grade 5, with good discriminative and calibration power. We believe that these data provide valuable information for assessing average risk in GE surgery, contributing to informing patients and their families of the risks associated with each GE surgical procedure.Two reports regarding GE surgery using NCD data appear in the present issue of In addition to the above clinical utility of the NCD, it is likely that the NCD system will have several promising applications in clinical practice. First, although information on long‐term outcomes, such as recurrence‐free survival and overall survival, has not been registered in the NCD, we have been able to register prognostic data for gastric cancer through the NCD system since September 2018. We hope that the linkage between short‐ and long‐term information can result in further establishment of clinical evidence from Japan. Second, Konno et al investigated the association between board‐certified surgeons in GE surgery and the surgical outcomes of GE surgery using NCD data.Conflicts of Interest: Author declares no conflicts of interest for this article.


For over seven decades, bacteria served as a valuable source of bioactive natural products some of which were eventually developed into drugs to treat infections, cancer and immune system‐related diseases. Traditionally, novel compounds produced by bacteria were discovered via conventional bioprospecting based on isolation of potential producers and screening their extracts in a variety of bioassays. Over time, most of the natural products identifiable by this approach were discovered, and the pipeline for new drugs based on bacterially produced metabolites started to run dry. This mini‐review highlights recent developments in bacterial bioprospecting for novel compounds that are based on several out‐of‐the‐box approaches, including the following: (i) targeting bacterial species previously unknown to produce any bioactive natural products, (ii) exploring non‐traditional environmental niches and methods for isolation of bacteria and (iii) various types of ‘genome mining’ aimed at unravelling genetic potential of bacteria to produce secondary metabolites. All these approaches have already yielded a number of novel bioactive compounds and, if used wisely, will soon revitalize drug discovery pipeline based on bacterial natural products. Over 50% of all pharmaceutical drugs currently on the market are directly derived from or inspired by natural products , streptomycin, was discovered from a soil‐dwelling Streptomyces griseus  that were unique for isolates tagged to particular locations. This finding implies that actinomycetes are able to acquire new BGCs from other bacteria dwelling in the same environment, thereby probably enhancing their adaptive capabilities for a particular environmental niche. Other recent studies have also showed the same trend for Strepomyces spp., which were lately considered by many as being of no more interest in search for novel compounds. For example, the genome of Streptomyces albus isolated from a marine sponge was found to harbour many BGCs not found in its counterpart isolated from a terrestrial source  was the first one to isolate a true marine actinomycete Staphylococcus aureus, was isolated from Staphylococcus lugdunensis, a common nasal commensal bacterium  that offer new opportunities for discovering habitats of rare bacteria that may become sources of new drug leads. One of the NGS‐based approaches targeted at environmental samples encompasses metagenome sequencing, allowing direct access to the genomes of the majority of bacteria dwelling in this habitat. Whether or not these bacteria can be cultivated is of no importance, as long as the genes for secondary metabolite biosynthesis discovered in metagenomes can be amplified or synthesized and heterologously expressed in an appropriate well‐characterized bacterial host (see next section). However, considering relatively low success rate for heterologous expression of metagenomic DNA, it is still preferable to be able to isolate and cultivate an actual host harbouring secondary metabolite biosynthesis genes and thus most likely possessing all the machinery required for the biosynthesis of cognate compounds. In this, metagenomics may also be of great help, since it can provide important insights into the metabolic/nutritional requirements of particular bacteria, especially if their genomes can be at least partially assembled from the metagenomics data. If such bacterium carries biosynthetic genes that are presumed to specify biosynthesis of a new secondary metabolite, such information can be used to design growth media and specific conditions allowing isolation and propagation of this bacterium.et al., Actinoalloteichus fjordicus that shares 99.9% 16S rRNA gene sequence identity with that of Actinoalloteichus hyamenocidonis isolated from a different sponge showed drastically different capacities of these bacteria to produce secondary metabolites , to name the most common types. The genes encoding biosynthetic machinery for secondary metabolites are organized in biosynthetic gene clusters (BGC), analyses of which can provide important information regarding chemical class of the compounds they specify. This predictive correlation between BGCs and cognate compounds can now be achieved using a wide range of bioinformatics tools [e.g. antiSMASH  . The strain Del14 showed enhanced production of secondary metabolites compared to S. albus J1074 and S. coelicolor M1152 and M1154. Additional changes in the genome of Del14 have been made by introduction of phage phiC31 attB attachment sites, yielding strains B2P1 and B4. This step allowed the integration of multiple copies of heterologous BGCs into the chromosome and resulted in improved yields of six out of eight exogenous compounds tested.Recently, a new host based on genome‐reduced et al., et al., et al., et al., et al., E. coli and yeast, and integrating into the genome of the host chosen for heterologous expression. Details on various modern methods currently employed for this purpose can be found in recent reviews   saturated and cyclopropane FAs (C7–C30). Two of these, i‐17:0cy9‐10 and a‐18:0cy9‐10, represent new natural products . Apparently, this protein acted as a repressor, since its deletion led to cpk cluster activation and production of an antibacterial compound later identified as coelimycin P1  to treat systemic infections caused by Gram‐positive bacteria. Daptomycin is synthesized by the modular NRPS, making its biosynthetic pathway amenable to genetic modifications by swapping the domains, modules and subunits in an approach called ‘combinatorial biosynthesis’ [for review, see  into fluorescent or colorimetric signal, which makes the screening fast and convenient  will help to identify compounds that were previously not detected simply because there were no corresponding assays. Genome mining will definitely expand to more bacterial species and BGCs, providing new bioactive compounds via a combination of different methods, including those inspired by synthetic biology. Once discovered, the new compounds will have to be produced at a scale allowing biological testing for pharmacological properties. Therefore, the supply issue will have to be addressed by both refactoring of the BGCs and streamlining metabolism of the host through metabolic engineering, focusing on metabolic flux through target pathway, robustness of the producer and balancing precursor supply. Considering all the advances made in bacterial biology over the last two decades, the future for the discovery of novel drug candidates from bacteria looks bright.Authors declare that they do not have conflict of interest.


HIV found in these cross‐border areas in each stage of the HIV care and treatment cascade, including the proportion who knows their status, the proportion on treatment and the proportion virally suppressed.HIV care and treatment in cross‐border areas in East Africa face challenges perhaps not seen to the same extent in other geographic areas, particularly for mobile and migrant populations. Here, we estimate the proportion of people with AIDS Control Efforts method and administered a behavioural survey and rapid HIV test. This approach was designed to recruit a stratified random sample of people found in public spaces or venues in each cross border area. For participants testing positive for HIV, viral load was measured from dried blood spots. The proportion in each step of the cascade was estimated using inverse probability weights to account for the sampling design and informative HIV test refusals. Estimates are reported separately for residents of the cross border areas and non‐residents found in those areas.Participants  working or socializing in public places in selected East Africa cross border areas were recruited between June 2016 and February 2017 using the Priorities for Local HIV found in cross‐border areas knew their status, 87% of those participants were on antiretroviral therapy (ART), and 80% of participants on ART were virally suppressed. About 20% of people with HIV found in cross border areas were sampled outside their subdistrict or subcounty of residence. While both resident and non‐resident individuals who knew their status were likely to be on ART (85% and 96% respectively), people on ART recruited outside their area of residence were less likely to be suppressed  compared to residents .Overall, 43% of participants with HIV status. Moreover, while non‐residents were more likely to be on treatment than residents, they were less likely to be suppressed, suggesting gaps in continuity of care for people in East Africa travelling outside their area of residence despite timely initiation of treatment.People living in or travelling through cross‐border areas may face barriers in learning their  The East Africa Cross Border Integrated Health Study (CBIHS) offers a rare opportunity to assess outcomes along the HIV care continuum for people living, working and socializing in cross‐border areas, including highly mobile cross‐border priority populations who are typically excluded from traditional epidemiologic studies implemented using household‐based surveys. Because such groups likely access services differently and face distinct sets of health risk factors 22.1The CBIHS is a population‐based cross‐sectional study of a wide array of health outcomes in 14 survey sites in cross‐border areas in Kenya, Uganda, Tanzania and Rwanda  method Step 1: Enumeration of all venues in each cross border site: Approximately 200 community informants in each cross‐border area were interviewed and each asked to provide the names and locations of up to 10 venues where people (including residents and non‐residents) socialize and meet new sexual partners. Additional community informants were interviewed until the list of venues reached saturation or no new venues were named.Step 2: Verification of a sample of venues: The team verified characteristics of a sample of up to 100 venues in each cross‐border area to ensure that venues named in step 1 existed, were unique and were operational. In areas with fewer than 100 venues, all venues were included. In areas with more than 100 venues, a stratified random sample of venues was selected for verification.Step 3: Bio‐behavioural survey: The team conducted a bio‐behavioural survey among individuals socializing at a stratified random sample of 40 venues per area. At sampled venues, a stratified sample of workers and male and female patrons was approached, with interview targets proportional to the total number of people at the venue. The appendix contains additional details on the sampling of venues and individuals.Sampled individuals were offered counselling and rapid HIV testing according to the algorithm approved by each country. In addition, respondents were asked to participate in an interview to gather sociodemographic information, health history, family information, sexual behaviour, health‐seeking behaviour, and exposure to HIV prevention, care and treatment programmes, including ART. Participants who refused the HIV test were offered the option of participating in the interview. After the interview, participants who agreed to be tested received their result and post‐test counselling. Those with positive results were asked to provide dried blood spots for HIV‐1 RNA viral load testing, which was conducted according to national guidelines in each country. People newly testing positive for HIV were linked to care at a local health facility. Viral load measurements were communicated back to the facility with which the local staff who provided the HIV counselling and testing were associated. Respondents were given a card with an identification code and facility name so that they could obtain their viral load results. Participants who refused the HIV test were not invited to provide dried blood spots for viral load quantification.To evaluate disparities in achieving the 90‐90‐90 goals between resident and non‐resident populations, we estimated the proportion in each stage separately for each group. We defined the “non‐resident” population as individuals who reported residing in a subnational administrative area  outside the cross border area where they were recruited. In contrast, the resident population consisted of individuals who reported that they reside within the subnational unit of the cross‐border area.Study protocols were reviewed and approved by the University of North Carolina at Chapel Hill Institutional Review Board; Makerere University Higher Degrees, Research, and Ethics Committee in Uganda; the Kenya Medical Research Institute Ethics Review Committee; the National Institute for Medical Research in Tanzania; and the Rwanda National Ethics Committee. All participants in the biobehavioural survey provided written informed consent.2.2The proportion of people living with HIV who know their status (the first 90)The proportion of people who know that they are living with HIV who are on ART (the second 90)The proportion of people on ART who have a suppressed viral load, defined as a viral load under 1000 copies/mL (the third 90); andThe overall proportion of people living with HIV who had a detectable viral load.The purpose of this analysis was to estimate indicators related to the 90‐90‐90 targets in cross‐border areas, including:The questions used to ascertain whether an individual met the inclusion criteria for each step of the care continuum are provided in Table All participants who tested positive for HIV or who reported a previous positive HIV test were included. All analyses accounted for the survey design, including clustering by recruitment venue and stratified random sampling. Survey sampling weights were used to reweight the study sample to represent all people with HIV who socialize in public venues in the selected cross‐border areas, and we accounted for missing data due to informative refusals of the HIV test and viral load testing using inverse probability weights Each parameter (i.e. each 90‐90‐90 indicator) was estimated for the entire population and separately for resident and non‐resident populations. We also examined associations between achieving each stage of the HIV care continuum and other individual‐ and venue‐level characteristics using weighted bivariate (unadjusted) prevalence ratios (PRs). Corresponding 95% confidence intervals [CIs] were based on standard errors estimated using Taylor series linearization to account for the sampling design 33.1Of the 1,769 venues identified by community informants in the 14 cross‐border areas, 1,161 (66%) were sampled for verification. Of these sampled venues, 883 (76%) were successfully located, operational and contained a venue informant who consented to participate. A total of 452 of these venues were sampled for the bio‐behavioural survey, from which 11,567 individuals were sampled and asked to participate in the study. Of those, 11,410 (98.6%) agreed to participate in the interview and 10,549 (91.2%) agreed to be tested for HIV. Overall, 8656 (76%) of those completing the interview reported a place of residence within the cross border area and 2754 (24%) reported a place of residence outside the cross border area. Of those completing the interview, 576 individuals (5.0%) tested HIV positive or declined the HIV test and reported that they were HIV positive (460 residents and 116 non‐residents).Of the 576 people living with HIV, 58% were female (n = 347), 68% were between the ages of 20 and 40 (n = 408), 69% had completed primary school or higher education (n = 411), and 16% reported receiving cash for sex in the past 12 months (n = 98)  and 234 knew their status and were receiving ART . Of those living with HIV, 29.5% knew their status, were receiving ART, and were virally suppressed . These weighted percentages and 95% confidence intervals are compared visually to the 90‐90‐90 targets in Figure Table 3.3Overall, the strongest risk factors for having a detectable viral load were being a non‐resident of the cross border area (compared with residents of the area), being a young woman between the ages of 18 and 24 (compared with being an older woman), and being recruited at a commercial venue , outdoor venue , or other type of venue , compared with being recruited at a bar, pub or restaurant , with the goal of recruiting a cross‐section of people who could be found in a cross‐border area at a given point in time. In contrast, other studies often employ household surveys to recruit residents of the selected communities. Because cross‐border sites are both home to and frequented by mobile populations, sampling both resident and non‐resident populations from public places using the PLACE sampling methodology was an important strength of this study. Cross‐border areas are important mixing grounds between resident populations and non‐resident populations travelling through the site or visiting the site for work, commerce or socializing. Such mixing between population subgroups provides important opportunities for HIV transmission Furthermore, cross‐border areas are places where behavioural determinants of transmission such as new sexual partnership rates and sexual mixing may be higher than in other areas. Many public places in cross‐border areas (48% of those sampled for verification) offer opportunities for sex on site and, therefore, direct opportunities for HIV transmission This study has several limitations. The non‐resident population described here is likely a heterogeneous group of individuals that included long‐term visitors to the site, daily commuters to the site for work or commerce or residents of neighbouring communities. The specific composition of this group in each cross border area may have an impact on the effectiveness of any intervention aimed at improving viral suppression. Moreover, the concept of “residence” itself is vague and may have implied different definitions to different respondents. In addition, some individuals refused the HIV test. We accounted for informative refusals of the HIV test among those who participated in the survey by up‐weighting those who agreed to be tested to represent all participants who responded to the survey, conditional on covariates. However, these weights did not account for any systematic bias that may have occurred if HIV‐positive individuals who were sampled simply refused to participate in the survey altogether.5Despite these limitations, this study represents the most complete information available on the HIV care and treatment cascade in strategically important cross‐border areas in East Africa. Findings suggest that people with HIV who can be found in cross‐border areas are unlikely to know their status. Moreover, people travelling outside their area of residence may face serious barriers to maintaining viral suppression even after starting treatment. These barriers could include lack of knowledge about where to get ART while away from home, cost of obtaining ART when travelling outside one's country of residence, or suboptimal outcomes due to switching regimens when obtaining ART in different countries Halting the HIV epidemic in East Africa requires preventing transmission of HIV from people infected with HIV to their uninfected partners. Improving viral suppression among populations as they travel away from home may be an efficient means to reduce HIV transmission in cross‐border areas and beyond.The other authors declare no conflicts of interest.JKE designed the study, oversaw data collection, performed the analysis and wrote the manuscript. PA, EAB and JTO were involved in designing and conducting the study and revised the manuscript. FS, GM and MM were involved in study design, overseeing data collection, analysis and revision of the manuscript. AV participated in data analysis and revised the manuscript. SS was involved in study design and revised the manuscript.Appendix S1. Sampling details.Click here for additional data file.


Sufficiency and stability of the evidence was assessed through application of pre‐published indicators. Meta‐analyses suggest overall positive intervention effects on physical activity. The evidence base for effectiveness immediately post‐intervention reached levels of sufficiency and stability in 2007; and for long‐term follow‐up in 2011. In the time since, intervention effectiveness has not substantially changed, and further trials are unlikely to change the direction and magnitude of effect. Substantial evidence exists demonstrating that physical activity interventions can modify individual behaviour in controlled settings. Researchers are urged to shift focus towards investigating the optimization, implementation, sustainability and cost‐effectiveness of interventions.Despite a large and increasing evidence base on physical activity interventions, the high rates of physical inactivity and associated chronic diseases are continuing to increase globally. The purpose of this cumulative meta‐analysis was to investigate the evolution of randomized controlled trial evidence of individual‐level physical activity interventions to asses if new trials are contributing novel evidence to the field. Through a two‐staged search process, primary studies examining the effects of interventions targeted at increasing physical activity within healthy adult populations were pooled and selected from eligible systematic reviews. Cumulative meta‐analyses were performed on effect sizes immediately post‐intervention ( Physical inactivity is the fourth leading risk factor for global mortality Ideally, the results of early intervention evaluations inform the development and design of future interventions and through the accumulation of evidence, knowledge and innovation lead to the production of more effective interventions. However, successful promotion of physical activity across populations has lagged relative to available evidence As new interventions are developed, evaluated and published, evidence evolves over time, with new knowledge strengthening and updating, or altering and invalidating the results documented in earlier trials A two‐staged selection strategy was used to gather evidence. First, relevant systematic reviews were identified through a systematic search. Secondly, primary studies were pooled from selected systematic reviews, screened against the inclusion criteria and relevant trials selected. Physical activity data from included trials was then cumulatively meta‐analysed. Screening, data extraction and risk of bias assessments were completed by the primary author, with quality checks performed by a second author. The review was directed by the preferred reporting items for systematic reviews and meta‐analyses guidelines (PRISMA).In stage one, six electronic databases  were searched for relevant systematic reviews. Searches were conducted in May 2015 with pre‐piloted search strategies (Data S1). Systematic reviews that examined the effects of interventions targeted at healthy adults to promote physical activity and included RCTs, were considered for inclusion. Reviews that did not utilize a systematic process for identifying studies were excluded. In stage two, primary studies were extracted from the included systematic reviews, and all RCTs in healthy adults, comparing the effect of a physical activity promotion intervention to a control condition, considered for inclusion. Included trials were restricted to those reporting a continuous measure of physical activity, and reporting N (sample size), mean and standard deviation (SD) for the intervention and control group at follow‐up. As a result of potential problems with cross‐over and wait‐list trials, including spillover effects from the waiting period to intervention phase, and loss of a viable control group making comparisons impossible, only data up to the point of cross‐over was extracted and included in the analysis. Resulting from the heterogeneous characteristics of interventions targeted at obese populations and individuals with pre‐existing medical conditions, inclusion was restricted to interventions aimed at increasing physical activity within a generally healthy adult population. Inclusion was further limited to interventions with a continuous measure of individual duration of physical activity measured either objectively or subjectively (e.g. via accelerometer and questionnaire) at baseline and follow‐up. In order to develop a homogeneous set of data for analysis, trials with alternative indicators of activity (e.g. motivation to exercise) or sedentary behaviour were not included. A detailed overview of the inclusion and exclusion criteria for both stages is outlined in Table Intervention characteristics were extracted for each primary study meeting the inclusion criteria. Effect size data was extracted at the first follow‐up post intervention, and (where available) for long‐term behaviour change (defined as at least 12‐month post‐baseline). Post‐baseline, as opposed to post‐intervention, time‐points were included to assess the effect on long‐term behaviour change, irrespective of intervention length. If multiple long‐term follow‐up measures were reported, these were collapsed into a single intervention effect. When adequate data was not reported in primary studies, where available, we extracted this from published reviews that had utilized author data requests to clarify outcome values g and its 95% confidence intervals (95% CI) g was selected as the index of mean difference as it is the preferred approach when the majority of included studies have small sample sizes with comparably greater standard errors Intervention effects for outcome measures were calculated and expressed as standardized mean differences (SMDs), based on Hedges's adjusted metacum user written command in STATA version 14.0.To assess differences in the accumulation of evidence for behaviour change immediately following an intervention trial and long‐term behaviour change, two separate cumulative meta‐analyses were conducted. The first, intervention effect at the follow‐up time point closest to intervention end, included all trials in the review. The second included only those trials reporting assessments at least 12‐month post‐baseline. The cumulative meta‐analysis provides cumulative pooled estimates and 95% CIs. As studies are successively added, the overall SMD and 95% CIs are recalculated providing evidence of the evolution of intervention effects over time. To assess the sequential contributions of trials and evaluate changes in effectiveness over time, studies were added alphabetically by year of publication to a random‐effects models using the Random effects models, based on the method of moments, were used under the assumption that the true effect sizes estimated by individual studies were drawn from a distribution of true effects rather than a single value, and an expectation of substantial heterogeneity given the differences in interventions eligible for inclusion To address the question of whether and when sufficient evidence had been accumulated that the addition of further trials would not change established conclusions, Muellerleile's indicators of sufficiency and stability were applied to both cumulative meta‐analyses Figure A summary of intervention characteristics is outlined Table n = 62). Early trials conducted throughout the 1980s and 1990s demonstrated a high degree of heterogeneity, with the first published results revealing statistically significant, positive effects. However, the conduct of additional trials weakened the initial evidence of effectiveness, with the overall effect no longer being significant by the ninth trial. Two trials in 1997 and 1999 reporting harmful, negative intervention effects contributed to this decrease in effect size. The overall effect regains statistical significance following the addition of the 33rd trial in 2007. According to the pre‐established thresholds (Data S4), a sufficient and stable body of evidence with the potential to change the physical activity behaviour of participants immediately following intervention implementation, was achieved in 2007 with the addition of the 39th trial. Since then, we identified 23 further RCTs were reported up untill to 2013.Figure n = 27), the thresholds of sufficiency and stability were not met until later. As displayed in Figure When the analysis was restricted to interventions with physical activity measurements at least 12‐month post‐baseline Figure 2. Application of indicator of stability (Cumulative Slope)Figure 3. Application of indicator of sufficiency (Failsafe Ratio)Figure 4. Application of indicator of stability (Cumulative Slope)Click here for additional data file.


Granular acute lymphoblastic leukemia (ALL) is a rare variant of the disease that is associated with a lower remission rate to standard induction chemotherapy. Flow immunophenotyping, cytogenetics, and molecular diagnostics should be utilized to confirm the diagnosis of ALL versus acute myeloid leukemia (AML) in order to provide appropriate management. Granular ALL is extremely rare in adults, and the natural history of this condition in adults is not well described. We describe a case of granular ALL in a 54‐year‐old woman and review its clinical significance in adults reported in the literature.The presence of azurophilic granules in the cytoplasm is one of the key distinguishing features of acute myeloid leukemia (AML) which differentiates it from acute lymphoblastic leukemia (ALL). However, on rare occasions, these intracytoplasmic inclusions may be found in ALL blasts, termed granular ALL, that defy conventional teaching and diagnostic pathways.2A 54‐year‐old woman presented with light chain multiple myeloma three years prior and was treated with VAD  followed by an autologous stem cell transplant resulting in a complete response. This was followed by thalidomide maintenance therapy complicated by mild peripheral neuropathy.The patient subsequently developed progressive neutropenia over the course of three years. Work‐up demonstrated abnormal appearing blasts and nucleated red cells on her peripheral blood white cell differential and smears. 33% of peripheral leukocytes were described as blasts. She was admitted to hospital for further work‐up and management. A bone marrow aspirate was performed. Morphologic assessment revealed approximately 15% of the marrow blasts had numerous cytoplasmic granules suggestive of an underlying acute myeloid leukemia  from acute lymphoblastic leukemia (ALL). These granules in AML are fused lysosomes and contain lysosomal enzymes and crystalline inclusions, but are rarely present in adult ALL cells.9 cells/L, and 99.1 × 109 cells/L, respectively. The mean percentage of blast cells with granules was 39% (range 15‐98). All patients were MPO negative where data were available. Most patients were also CD10 positive, with two exceptions, one of which is our case. All patients where data were available were FAB group L2, which is consistent with the pediatric finding of increased granular ALL rates in that group. Most cases of granular ALL were of B‐cell lineage origin and most cases were primary leukemias. A variety of chemotherapeutic regimens were applied. The complete remission rate to induction chemotherapy was 53% which is lower than the rates reported in the literature for non‐granular adult ALL (80%‐90%).However, it is currently unknown whether granular ALL presents a different clinical outcome in adult patients. We performed an exhaustive literature search of all cases of adult granular acute lymphoblastic leukemia and found 18 cases in addition to our case (Table % range 1‐98. All The heterogeneity in presentation of these cases imparts difficulty in the analysis and categorization of adult granular acute lymphoblastic leukemia. Limitations of our review of the literature include missing data in the described cases as well as the diversity in patient, disease characteristics, and treatment modalities described. The rarity of granular ALL also limits statistical analysis, further generalization, and adequate assessment of subgroups of ALL.4An accurate diagnosis is critically important for treatment implementation and prognosis in acute leukemia. Diagnostic confusion may arise in acute lymphoblastic leukemia with cytoplasmic granular inclusions resembling that of acute myeloid leukemia. It is important to confirm the type of acute leukemia with flow cytometric immunophenotyping in all cases. In this review of the literature, granular ALL in adults results in a worse prognosis compared to non‐granular adult ALL patients which is consistent with the finding in pediatric granular ALL patients.None declared.SJ and JJ: wrote the initial manuscript. CCH: provided case and revised the manuscript.


Xenopus embryos). In these earliest developmental stages, morphogen concentration gradients are not relevant for setting up this axis. It emerges that at these stages, the core patterning mechanism is timing: BMP‐anti BMP mediated time space translation that regulates Hox temporal and spatial collinearities and Hox‐Hox auto‐ and cross‐ regulation. The known anterior–posterior morphogens and signaling pathways––retinoids, FGF's, Cdx, Wnts, Gdf11 and others––interact with this core mechanism at and after space–time defined “decision points,” leading to the separation of distinct axial domains. There are also other roles for signaling pathways. Besides the Hox regulated hindbrain/trunk part of the axis, there is a rostral part (including the anterior part of the head and the extreme anterior domain [EAD]) that appears to be regulated by additional mechanisms. Key aspects of anterior–posterior axial patterning, including: the nature of different phases in early patterning and in the whole process; the specificities of Hox action and of intercellular signaling; and the mechanisms of Hox temporal and spatial collinearities, are discussed in relation to the facts and hypotheses proposed above.This article is concerned with the roles of retinoids and other known anterior–posterior morphogens in setting up the embryonic vertebrate anterior–posterior axis. The discussion is restricted to the very earliest events in setting up the anterior–posterior axis (from blastula to tailbud stages in  Recent developments  validate this line of reasoning and give confidence that it is correct.This review represents the conclusion of and harvest from (necessitated by old age) 20 years of intensively and obsessively pursuing a line of reasoning/scientific insight into the nature and ontogenesis of the vertebrate anterior–posterior (A–P) axial pattern. This main effort was preceded by other necessary and substantial phases devoted to learning vertebrate embryology and figuring out the way in to approach investigating and understanding vertebrate axial patterning and to learning how to approach developmental problems by using the elegant 2Hox genes  out of many tested in different organisms for regulation by the three best known A–P morphogen pathways  have actually been shown to be direct morphogen targets during early A–P patterning. Some clearly are not, but are however regulated indirectly, sometimes via Hox‐Hox interactions or other regulatory interactions  and a few of the others are probably direct early A–P morphogen targets in the first phase of A–P axial patterning. Below, I puzzle out what the early role of morphogens actually is. Is a morphogen gradient the only mechanism involved in the first phase of axial patterning? Evidence is presented below that an entirely different mechanism: a timing mechanism ? Many previous models propose that retinoids and other morphogen signaling pathways have a role in patterning the vertebrate anterior–posterior (A–P) axis. A frequently used model has been that different threshold values on a morphogen concentration gradient specify different A–P axial positions , forms via ventral‐ward bending of the anterior end of the dorsal A–P axis so it faces backward ventrally like the handle of a walking stick  dependent timer  in the nonorganizer (NO) mesoderm of the early embryo. Another embryonic region, Spemann's organizer (SO) emits anti‐BMP signals. Timed application of either an intact organizer or the organizer anti‐BMP signal noggin to the embryo at sequential stages blocked the timer at sequential A–P Hox values, and thereby fixed timed cell states sequentially. Either the treatment generated an anteriorly truncated axis with the truncation at sequentially more posterior positions for sequentially later treatments (implanted organizer: continuous anti‐BMP source) or it generated one or more A–P/Hox zones; sequentially later treatments gave sequentially more posterior zones  in later development  embryos show temporal but not spatial 3.3Hox genes themselves is clearly a part of the timing and TST mechanism. The timing mechanism operates and the spatial Hox pattern is generated at least partly via autoregulation and cross‐regulation among the Hox genes, leading to a sequence of collinear interactions among them. This is thus a Hox cascade mechanism. The fact that Hox cascades are involved in specifying the axis is clearly demonstrated by the cascade of phenotypes generated by Hox gain and loss of function experiments in Xenopus and other systems  are not. PI is evident from the first expression of Hox genes in NO mesoderm during mid‐gastrulation  is likely to be the basis of temporal collinearity , which starts from this stage. It is blocked by BMP.The suppression of expression or function of anterior Hox‐Hox interactions mediate Hox collinearities and TST comes principally from gain and loss of function experiments, especially from the cascade phenotypes  have been reported previously  and proceeds next with the presumptive telencephalon/anterior diencephalon, marked by expression of Six3 (late marker), then goes on next to the presumptive diencephalon/mesencephalon, marked by Otx2 (early marker) and to the presumptive anterior rhombencephalon , marked by expression of Gbx2 , and next to presumptive mid‐rhombencephalon, marked by Hoxd1 (early marker). These anterior zones are sequentially induced very early in development by timed anti‐BMP signals during mid‐blastula to mid‐gastrula stages, before and as the A–P Hox gene sequence starts to be expressed  are collaborators (noncooperatively binding coactivators) for a Drosophila Hox gene: Ubx.  patterning  to the occipital and cervical regions of paraxial mesoderm. The post‐hindbrain CNS  has a collinear sequence of Hox anterior expression boundaries similar to the paraxial mesoderm, but is not obviously divided into domains. Some domains are also subdivided into what are presumably tissue specific subdomains, for example, the division of presumptive abdominal paraxial mesoderm into presumptive lumbar and sacral regions. Mesodermal domains can also be segmented metamerically from the cephalic region back to the tail into somites and neural domains in the rhombencephalon and perhaps more anterior regions into neuroectodermal rhombomeres and prosomeres  and then in sequentially later steps is progressively posteriorised  knockdown phenotype  MO translation knockdowns, are influenced by genetic compensation  signaling. Wnt signals are mesodermal in origin, arising in Xenopus from the NO mesoderm or from the mouse equivalent, the primitive streak  together with Cdx signaling  but not necessarily more posterior Hox genes  but not Hox1‐5  gives a phenotype that is closely similar to that for MO‐induced loss of function for Amphi‐Hox1. It posteriorises expression of Amphi‐Hox1‐6. On the other hand, retinoid gain of function anteriorises expression of Amphi‐Hox1‐6 , but it is not known when, where or even if these are active  cells (an embryo‐like system) that retinoids induce temporally collinear (TC) expression of 4.4.2Wnt action has been studied in Xenopus, where Wnt8 loss of function and ectopic expression were used to examine Wnt regulation of Hox genes. Wnt 8 induces Hox genes . The others were induced indirectly, probably via Hox1. The sample of Hox genes examined here was small but it is possible that, unlike the situation with retinoids, Wnt only directly induces Hox1 genes, not multiple genes in the posterior head and neck domains.4.4.3Xenopus, chicken, and mouse. FGF‐Cdx induces neuroectodermal expression of all thoracic Hox genes but none of the neck or posterior head Hox genes studied in Xenopus and chicken. Hoxb6, Hoxc6, Hoxa7, Hoxb7, Hoxb8, Hoxb9, but not Hoxb1, Hoxb3, Hoxb4 or Hoxb5, were induced by FGF  generally? And, why does anti‐BMP not permit it, but instead fosters spatial collinearity (SC) and vertical signaling autoregulation (Au)? TC is putatively mediated by PI, a noncell autonomous Hox–Hox interaction. There are in principle at least two ways in which signaling pathways could interact with PI and temporal collinearity specifically and with the Hox‐macro‐collinearity mechanism , thus breaking the TC cascade and stabilizing Hox expression . TC is sequential by direct induction of expression going from one Hox paralogue group (PG) primarily to other Hox genes close to it, for example, to its immediate 5′ neighboring PG. It can be assumed, therefore, that PI does the same. In the one case that has been tested, it does: Hoxb4 induces Hoxb5 directly but Hoxb7 and Hoxb9 indirectly  are generated by interaction of a temporal oscillation (somitogenesis clock) in presomitic mesoderm with an anterior to posterior traveling wave front that fixes oscillation phase and generates spatially periodic somites in a sequence from anterior to posterior  stage of TST. It is therefore interesting to examine the timing of the actions of signaling pathways on axial patterning. Anterior head/posterior head onset of Wnt action occurs in the early gastrula NO mesoderm during TC in Xenopus  anterior head determinant in NO mesoderm . In addition, several more specificities are required for PI if it functions in Hox‐independent determination of the anterior head and EAD. These specificities are determined intracellularly by homeobox proteins, and possibly other transcription factors, acting in the nucleus. The corresponding complexity of intercellular signaling during noncell autonomous Hox–Hox interactions could depend on the many different Hox genes being activated differently by specific action of different conventional signaling pathways or combinations of pathways such that a Hox induced ligand–receptor interaction induces a Hox gene via a signal transduction pathway and the induced Hox gene induces a second (sometimes different) ligand–receptor interaction and a second (sometimes different) signal transduction cascade (see below). This is possible, but seems to invite chaos. It is unlikely, but possible, that several different Hox genes could signal in the same cell without mutual interference by activating different variants of similar signaling pathways. A solution for signaling that should not be ruled out at this point is that specificity lies entirely in the specificity of intracellular Hox–Hox interactions in the nucleus and that noncell autonomy/signaling is regulated relatively nonspecifically via intercellular homeoprotein transport  and possibly as many as 39 ––in a diploid vertebrate is perhaps determined very little by the specificity of cell interactions because Hox proteins possibly travel relatively nonspecifically from cell to cell but almost entirely by the specificity of events in the nucleus. Presumably, at least in some cases, this occurs by binding of the Hox transcription factors to specific enhancers, resulting in either repression or activation of transcription. What are these events?From the sections above, it is evident that we suspect that transcriptional control of Hox proteins bind to rather similar DNA sequences. This has generated a dilemma: how is the precise developmental specificity of Hox gene action, which evidently exists, generated? Is it by binding of different Hox proteins to their own specific enhancers? There is no clear evidence that this is the case . However, there is evidence that the specificity of Hox binding to enhancers can be modified and enhanced by the Hox protein binding to members of one or both of two specific families of DNA binding homeobox containing cofactors: the extradenticle‐Pbx family and the homothorax‐Meis family. Most Hox proteins heterodimerise with Pbx proteins and it is known that binding of Pbx‐Hox heterodimers to their cognate response elements occurs with higher affinity and thus presumably higher specificity than binding of Hox monomers. The vertebrate orthologues of Drosophila Abd B, Hox10–13, on the other hand, less often use Pbx and can use Meis as a cofactor. In addition, Homothorax‐Meis has additional functions: it binds to Hox‐Pbx dimers in a tripartite complex and facilitates their entry into the nucleus as well as binding with them to enhancers  or the strength of the action. The direction of modification is presently not clearly predictable. Co‐operators are typically transcription factors mediating action of signaling pathways . A last aspect to specificity is that this would be affected by nano‐collinearity  due to being in a trithorax compartment and which are inaccessible, due to being in a polycomb compartment . According to our findings above, it is likely that Hox cluster opening is regulated progressively by Hox‐Hox interactions. This fits with previous evidence for local as well as global interactions mediating chromatin opening  for initial A–P patterning. The timing mechanism depends on The timing mechanism interacts with a higher level of control that distinguishes domains on the A–P axis.Hox–Hox interactions.The domains are distinguished by the action of different A–P signaling pathways, interacting via “decision points” at and after which they collaborate with the collinear Hox–Hox interactions.Signaling pathways can also act in other ways, for example as collaborators that co‐mediate noncell autonomous Hox TST.The existence of a second early TST mechanism coupled to early A–P patterning (somitogenesis) poses an interesting problem yet to be resolved. Somitogenesis interacts with Hox specificity is regulated poses another interesting problem for future investigation.The question of how The A–P patterning process is complex and time dependent. I deal here only with the initial phase. There are other important phases, which presumably have their own specific mechanisms.This review provides some novel clues as to how the vertebrate A–P pattern is set up. There is still a lot to be done.The sections above discuss the nature of early vertebrate A–P patterning and its connections with retinoids and other known A–P morphogens. We conclude from the evidence presented: