To the Editor,Interstitial lung abnormalities (ILAs) are a radiological entity characterized by incidental findings in chest computed tomography (CT) scans, with specific patterns of modifications in lung density in patients with no prior history of interstitial lung disease. These radiologic changes are present in more than 5% of nondependent lung parenchyma areas. And they include reticular abnormalities or ground‐glass attenuation, lung distortion, traction bronchiectasis/bronchiolectasis, honeycombing, and nonemphysematous cysts.ILA affects about 7% of the general population. The prevalence varies with age and with smoking habits, being more prevalent in older and smoker individuals.Therefore, we designed a study to identify and characterize patients with ILA within the Enhanced Recovery After Surgery (ERAS®) program.We conducted a retrospective and descriptive study of patients referred to Pulmonary Rehabilitation in the preoperative period of major abdominal surgery, within the scope of the ERAS® program. We included patients with benign diseases and cancer, regardless of disease stage. All surgeries were programmed. The data was collected by analyzing clinical processes. We analyzed 21 months between January 2020 and October 2021.χ2 test. The significance value was taken as p < 0.05.Statistical analysis was performed using SPSS software (version 23.0). Continuous variables were presented as mean ± standard deviation or median and respective interquartile range (IQR), depending on the normality of the underlying data. Categorical variables were compared with the We considered a period until 60 days after hospital discharge to analyze mortality.n = 82; 64%), and 50.8% (n = 65) had a history of smoking (14.8% were current smokers and 35.9% ex‐smokers). Patients presented a median body mass index of 26.1 kg/m2 ± SD 5.031.We evaluated 128 patients with a median age of 71 years (IQR: 56–86), most of them were male  with curative intent, mainly of the gastrointestinal tract , and had done a chest CT scan for staging their disease.Most patients were referred to the ERAS® program for oncological disease , with a median age of 78 years (IQR: 49–107).In this study, we found seven (5.5%) patients having ILA. Most of them were male (n = 3) of ILA patients had a smoking history. Two patients had respiratory symptoms, and none of those who underwent functional assessment had alterations (n = 5). The radiologic evaluation revealed that most patients (n = 6) had reticular alterations.About 42.9% (p = 0.033). We found an association between gastroesophageal reflux disease (GERD) and the presence of ILA  .The median length of hospital stay was 9 days (IQR: 7–24) in ILA versus 7 days (IQR: 5–14) in non‐ILA patients (p = 0.005).Seven patients died, of which three had ILA. We found an association between having ILA and death  have been explained.


Due to the significant role of dyslipidemia, cardiovascular diseases (CVDs) are very common in obstructive sleep apnea (OSA). Nontraditional lipid indices are considered to be a better predictive index for cardiovascular risk. Nevertheless, the association between nontraditional lipid profiles and the severity of OSA is not clear.A retrospective study was proceeded on 635 patients. Subjects were diagnosed with OSA through polysomnography (PSG). The association between severe OSA and nontraditional lipid profiles  was examined by utilizing the restricted cubic spline and multivariate logistic regression analysis.All nontraditional lipid indices had positive relationships with the severity of OSA. By multivariable adjustment, the per SD increment of the TG/HDL‐C, TC/ HDL‐C, LDL‐C/HDL‐C, non‐HDL‐C, AI, and LCI were significantly associated with 88%, 50%, 42%, 40%, 50%, and 125% higher risk for severe OSA respectively. Compared with the lowest tertiles, the adjusted ORs (95% CI) were 2.42 (1.57–3.75), 2.39 (1.53–3.73), 2.35 (1.52–3.64), 1.86 (1.21–2.86), 2.39 (1.53–3.73), and 2.23 (1.43–3.48) for the top tertiles of TG/HDL‐C, TC/ HDL‐C, LDL‐C/HDL‐C, non‐HDL‐C, AI, and LCI respectively.All nontraditional lipid indices had positive relationship with the severity of OSA. In addition, TG/HDL‐C, TC/HDL‐C, and AI had better performance than the other nontraditional lipid indices for predicting severe OSA. These findings could help to determine the risk of cardiovascular diseases and improve the dyslipidemia management of OSA patients. This study is different from previous studies. Firstly, as a retrospective cohort study, the sample size is larger than in other studies. Secondly, previous studies only investigated 1 or 2 nontraditional lipid indexes, while our research studied 6 nontraditional lipid indexes. Last but not least, the restricted cubic spline is employed in the research to confirm the linearly positive association between nontraditional lipid profiles and the risk of severe OSA. It could lead to frequent episodes of apnea and hypopnea.For the past few years, more and more researchers have been focusing on the possible correlation between lipid metabolism disorders and OSA, especially in traditional lipids. There is a correlation between OSA and the increase in total cholesterol (TC), triglycerides (TG), and low‐density lipoprotein cholesterol (LDL‐C). In addition, the decrease in high‐density lipoprotein cholesterol (HDL‐C) is also related to OSA.Based on the following aspects, this study is different from previous studies. Firstly, as a retrospective cohort study, the sample size is larger than in other studies. 22.1A retrospective research of 2492 subjects diagnosed with OSA via polysomnography (PSG) test was carried out between January 2017 and December 2019. Data were collected from the medical record system in a retrospective manner, including sex, age, height, weight, body mass index (BMI), past history , personal history , sleep parameters, fasting plasma lipids, and patients' blood pressure (BP). The body mass index (BMI) was calculated by dividing the weight by the height squared. The patients' BP was measured in the evening before PSG and in the morning after PSG. Six hundred thirty‐five subjects remained after the following exclusion criteria: (1) individuals under the age of 18; (2) individuals with insufficient polysomnographic/clinical data; (3) individuals with history of OSA therapy; (4) individuals with corticosteroids or taking psychoactive medications; and (5) individuals with severe heart failure, liver or kidney diseases, or malignant tumor  was performed at the sleep center in the First Affiliated Hospital of Zhengzhou University. Sleep and associated events were scored according to the guidelines of the American Academy of Sleep Medicine (AASM).2.3Fasting plasma lipids included total cholesterol (TC), triglycerides (TG), high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C). After more than 12 h of overnight fasting, all venous blood samples of the study participants were collected. TC, TG, HDL‐C, and LDL‐C were measured by enzymatic methods directly. All the measurements were carried out by employing an automatic clinical chemistry analyzer . According to the separated lipid parameters, the following clinical indicators were calculated: TC/HDL‐C ratio, TG/HDL‐C ratio, LDL‐C/HDL‐C ratio, AI, LCI, and non‐HDL‐C. Non‐HDL‐C was calculated as TC minus HDL‐C; AI was calculated as non‐HDL‐C/HDL‐C; and LCI was calculated as TC*TG*LDL‐C/HDL‐C.2.42 and ≥24 kg/m2), smoking, alcohol drinking, hypertension, diabetes mellitus, coronary artery disease, and cerebral vascular disease. All the data analyses were performed by employing R version 3.6.1 (www.R‐project.org) and EmpowerStates (www. empowerstats.com). A 2‐sided p < 0.05 was considered to be statistically significant.The number (%) and the mean ± SD or the median (25th percentile and 75th percentile) were utilized to describe continuous data and categorical data respectively. By employing the one‐way analysis of variance (ANOVA) and chi‐squared test for categorical data, differences between mild, moderate, and severe OSA in data characteristics were compared. The univariate linear regression was utilized to evaluate the associations between sleep parameters and nontraditional lipid indices. By presenting the 95% confidence interval (CI) and the odds ratio (OR) with adjustment for covariates , the association between nontraditional lipid indices and OSA was assessed via logistic regression analyses. In the assessing of nontraditional lipid profiles, we established models for both continuous data per SD increment and categorical data by utilizing tertiles with the lowest tertiles (T1) as the reference group. Restricted cubic spline (smooth fitting curve) was performed to visually evaluate the association with nontraditional lipid profiles of the severity of OSA. The tests for linear trend were performed by entering the tertiles of each category of nontraditional lipid profile as continuous data in the models. Interaction and subgroup analyses were conducted according to sex, age (<65 and ≥65 years), BMI . No significant differences were found in terms of age, diabetes mellitus, coronary artery disease, and evening BP.The clinical and biochemical data are shown in Table 3.2The results of univariate analysis are shown in Table 3.3p for trend<0.05). Further analyses by restricted cubic spline confirmed the linearly positive association between nontraditional lipid profiles and the risk of severe OSA , while the test for interactions was not significant for age, BMI, smoking, alcohol drinking, hypertension, diabetes mellitus, coronary artery disease, and cerebral vascular disease . TG/HDL‐C was a risk factor for severe OSA in female . None of the stratified variables, including age, sex, BMI, smoking, alcohol drinking, hypertension, diabetes mellitus, coronary artery disease, and cerebral vascular disease significantly modified the association between nontraditional lipid profiles  with the risk of severe OSA  , but only in males with normal weight.Researchers found an independent correlation between OSA severity and TC/HDL‐C ratio in a cross‐sectional study.ρ = 0.28, p < 0.001) and negatively with the lowest arterial oxyhemoglobin saturation(L‐SpO2)  in a research conducted in both cross‐sectional and longitudinal study, while multivariate regression analysis showed that AHI (or L‐SpO2) was independently associated with LDL‐C/HDL‐C.2 and mean SaO2. Meanwhile, there was a linear correlation between the LDL‐C /HDL‐C ratio and the risk of severe OSA. These findings suggested that the increment in LDL‐C/HDL‐C ratio is proportional to the severity of OSA, which could partially increase the risk of cardiovascular events in patients with OSA. Non‐HDL‐C contained all the atherogenic lipoproteins, such as chylomicron, VLDL, LDL, and intermediate‐density lipoprotein (IDL). It was a recognized risk factor for CVD.The relationship between the severity of OSA and LDL‐C/HDL‐C ratio has been rarely studied. LDL‐C/HDL‐C ratio correlated positively with AHI  seems to be a key factor linking OSA to dyslipidemia, systemic inflammation, oxidative stress, endothelial dysfunction, and the progression of atherosclerosis in both in vitro and in vivo models.This study has several limitations. Firstly, it is a retrospective research. The mechanism of dyslipidemia in OSA could not be further explored. Secondly, there were no control group for OSA. Nonetheless, in consideration of the recognized fact of the association between OSA and dyslipidemia, the study is not intended to analyze such association. Thirdly, the influence of continuous positive airway pressure (CPAP) treatment was not evaluated on nontraditional lipid indices levels. Fourthly, there were fewer female subjects than male subjects in our study. Finally, the lipid‐lowering drugs we employed were not classified.5In conclusion, all of the nontraditional lipid indices  were positively associated with the severity of OSA. Besides, the TG/HDL‐C, TC/HDL‐C, and AI could predict the risk of severe OSA better than other nontraditional lipid indices. The utilization of mentioned nontraditional lipid profiles, which were lower‐cost and easier to calculate in clinical practice, could help to determine the risk of cardiovascular diseases, and select suitable candidates for aggressive lipoprotein‐lowering therapy in OSA patients.Table S1–S5Click here for additional data file.


There are limited studies about the association between nonalcoholic fatty liver disease (NAFLD) and corrected QT interval (QTc) prolongation worldwide.Therefore, we designed the current study to determine this association in a large cohort of a generally healthy population.We analyzed the data of 4603 individuals aged 35–70 who participated in the Fasa Cohort Study (FACS). Based on 12‐lead electrocardiograms, QT intervals were calculated and corrected by Bazzet's formula. A QTc interval of more than 430 ms in men and 450 ms in women was considered prolonged. The Fatty Liver Index was used to identify the participants with NAFLD.p < .001). After adjusting for a wide range of confounders, including age, gender, smoking status, physical activity, total cholesterol, high‐density lipoprotein‐cholesterol levels, diabetes, and hypertension status, in linear regression analysis, the standardized β coefficient of QTc interval among participants with NAFLD was 2.56 ms . After controlling the same confounders, the odds ratio of NAFLD for a prolonged QTc interval in men was 1.47  and in women was 1.39  using logistic regression analysis.Of all participants, 1550 (33.6%) met the NAFLD criteria. In subjects of both genders with NAFLD, the mean values of the QTc interval were considerably higher than in those without NAFLD (NAFLD was a risk factor for QTc interval prolongation. Awareness about the risk of NAFLD in increasing the potential cardiac arrhythmias should be raised to lower cardiac mortality. We studied the data of 4603 individuals. In subjects with NAFLD, the QTc interval is, on average, 2.56 ms longer than in those without NAFLD. The chance of QTc interval prolongation among males and females with NAFLD is 1.47 and 1.39 folds more than those without NAFLD, respectively. As QTc prolongation is associated with cardiac mortality, monitoring individuals with NAFLD is crucial. ALTalanine transaminaseASTaspartate aminotransferaseBMIbody mass indexCIconfidence intervalFACSFasa Cohort StudyFBSfasting blood sugarGGTgamma‐glutamyl transferaseHDLhigh‐density lipoproteinIPAQInternational Physical Activity QuestionnaireLDLlow‐density lipoproteinNAFLDnonalcoholic fatty liver diseaseTGtriglyceride1Nonalcoholic fatty liver disease (NAFLD) was initially described as “a less known and until now an anonymous hepatic disease.”The time between ventricular depolarization and repolarization in the ECG is known as the QT interval. It is measured as the time from the start of the QRS complex to the end of the T wave. Due to the effect of heart rate (HR) on QT interval, a corrected QT interval (QTc) adjusted for the HR is mainly used.The association between NAFLD and an increased risk of cardiovascular mortality has been reported in previous studies.22.1n = 9059). Subjects who met one or more of the following criteria were excluded (n = 4456): missing data, alcohol intake of 30 g/day or more in men and 20 g/day or more in women (safety levels of consumption to prevent Alcoholic Liver Disease),The Fasa Cohort Study (FACS) enrolled 10 138 patients aged between 35 and 70 from October 2014 to September 2016. Details of the study's design and methods are described elsewhere.2.2Each participant completed an internet‐based questionnaire that collected basic information such as age, gender, smoking status, history of alcohol consumption, and chronic diseases such as diabetes and hypertension.All medication taken within the past 2 weeks before registration was asked about and recorded. According to CredibleMeds, a database of drugs with a risk of QT prolongation, drugs with a known or potential risk for torsades de pointes have been listed and used to identify the taken medication with influential QTc prolongation factors.The MET‐value of each activity was multiplied by its duration to calculate MET‐min. Total physical activity (MET/24 h) was the sum of all activities. The average daily intake of 125 food parameters was measured per a validated quantitative Food Frequency Questionnaire (FFQ)2.32). Waist circumference (WC) was measured by a tape measure at the midpoint of the inferior border of the lowest rib to the anterior superior iliac spine.For anthropometric calculations, height was measured by a stadiometer, and a digital scale measured weight with an accuracy of 0.1 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated as weight in kilograms divided by the square of the body height in meters , triglyceride (TG), high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, gamma‐glutamyl transferase (GTT), total cholesterol, aspartate aminotransferase (AST), and alanine transferase (ALT). The Mindray BS380 autoanalyzer measured total cholesterol and HDL . TG was determined by enzymatic method and reported in mg/dL. AST and ALT were measured by the kinetic method and GGT by an enzymatic method based on SZASZ's approach. A glucose oxidase test was used for laboratory testing of FBS. Moreover, the Friedewald formula was used for the assessment of LDL.2.51/2).An expert technician obtained a 12‐lead ECG from each participant after they rested for 15 min. A computer‐based device (Cardiax®) performed ECGs. Participants were asked to shave the precordium area and refrain from moving or talking for better electrode attachment. The computer software  interpreted and reported the ECGs, then exported them to the central data collection software. We used ECG data that includes HR (bpm), QT interval duration (ms), and QTc interval duration (ms), which were approved by a cardiologist.2.6FLI, a cost‐effective, noninvasive method, was used to determine participants with or without NAFLD as a standard predictor of hepatic steatosis severity. This score is calculated using BMI, serum TG levels, WC, and GGT by the following formulaOptimal cut‐off values of FLI in Iranian society have been assumed to be 46.9 in men  and 53.8 in women .2.7t test or Mann–Whitney U test, as appropriate, for continuous variables and χ2 for categorical variables. Linear regression analysis determined the relationship between NAFLD and QTc interval duration. Logistic regression analysis was performed to determine the association between NAFLD and normal or prolonged QTc. Standardized β coefficient (β) in linear regression analysis was calculated. Logistic regression analysis calculated the odds ratio (OR) and 95% confidence interval (95% CI). Then, different regression models were adjusted using the most critical confounders, including age, sex, smoking status, physical activity, total cholesterol, HDL‐C, AST, ALT, diabetes mellitus, and hypertension history. p Values less than .05 were considered statistically significant. All statistical analyses were performed using SPSS 26.0 (IBM Corp.).Data were presented as mean (SD) or median (interquartile range [IQR]) for continuous variables based on normality and counts and percentages for categorical variables. Comparisons were made using the independent Student's 2.8Our study protocol adhered to the Helsinki Declaration, and the Fasa University of Medical Sciences Research Council and Ethics Committee approved it . In addition, the subjects provided written informed consent to participate in this study.3p < .001). Women comprised more than half of the NAFLD participants (56.9%). The prevalence of diabetes and hypertension was higher, while smoking was lower in NAFLD participants than non‐NAFLD participants (p < .001). The amount of physical activity was significantly lower in subjects who had NAFLD (p < .001). As shown in Table p > .05).Four thousandsix hundred and three participants were studied, with 2095 (45.5%) males and 2508 (54.5%) females. The mean age was 47.65 years old SD 9.10 years). Table 0 years. p < .001 for both). On the contrary, the QT interval in males with NAFLD was significantly lower than in males without (p < .001). Among females, HR and QTc interval were significantly higher in participants with NAFLD than those without NAFLD . Furthermore, although the QT interval in females with NAFLD was shorter than in those without NAFLD, the difference was not statistically significant (p = .154).Table p = .015). According to the multiple logistic regression analysis, there is a significantly positive relationship between the presence of NAFLD and a prolonged QTc interval in males >430 ms  and females >450 ms  after adjusting for age, smoking status, physical activity (MET 24 h), total cholesterol, HDL‐cholesterol, ASL, ALT levels, and diabetes and hypertension status.Table 4We investigated the association between NAFLD and prolonged QTc interval in a large cohort of a generally healthy population in southern Iran. After controlling for a wide range of potentially confounding variables, our study found a positive relationship between NAFLD and prolonged QTc interval in the aimed population.Our findings are consistent with the previous studies investigating the association between NAFLD and QTc prolongation.Although previous studies in Western or far East Asian countries with mostly fewer subjects found a significantly positive association between NAFLD and an increased risk of QTc prolongation, this is the first study in Western Asia. In this study, we confirmed the positive relationship between NAFLD and a prolonged QTc interval of 4603 generally healthy Iranians. There are several possible explanations for the association between NAFLD and QTc prolongation. Diabetes, smoking, systolic and diastolic blood pressure, hemoglobin A1c, high‐density lipoprotein concentration, BMI, and WBC count are associated with developing QTc prolongation in individuals with NAFLD.Our findings could improve clinical management and outcomes in patients with NAFLD or cardiovascular diseases. Nevertheless, there are also some limitations to our study. First, because this was an observational study, we needed to determine a possible causal relationship between NAFLD and QTc prolongation. Second, although FLI has good sensitivity and specificity for detecting NAFLD compared with abdominal ultrasonography, it has a lower sensitivity and specificity than liver biopsy, which is the gold standard for NAFLD diagnosis.5We confirmed the relationship between NAFLD and QTc interval prolongation in a generally healthy Iranian population. As QTc prolongation is associated with an increased risk of ventricular arrhythmia, and SCD, we recommend that individuals with NAFLD change their lifestyle and undergo regular ECG monitoring. Early identification of QTc prolongation in the electrocardiogram, as a predictor of potential cardiac arrhythmias, can lead to early treatment, consequently lowering the risk of cardiac mortality.The authors declare no conflict of interest.


Enterobacteriaceae, bacteria of the genus Salmonella spp., Clostridium botulinum, and lactic acid bacteria) were conducted during 12 months of storage. The best results in TCM were observed in the oil flavored by fresh garlic (0.24 log CFU/mL). The highest counts of anaerobic sporulates were detected in the dried rosemary olive oil (1.10 log CFU/mL). The flavoring materials have significantly higher counts of microorganism than flavored oils (p < .05). The obtained results demonstrated that microorganisms are capable to survive in flavored olive oil and the method of flavoring can affect their growth in a selective way according to the chemical characteristics.Flavoring olive oil is an increasing trend in olive oil processing. Growing consumer interest in flavored olive oils by natural material brings the need to evaluate the key limiting factors which is its microbiological stability. The present research compares the microbiological quality of olive oil flavored by 3 flavors , prepared by 3 methods to determine changes during storage. The comprehensive microbiological analyses , anaerobic sporulates, yeasts, molds, bacteria of the familly Enterobacteriaceae, bacteria of the genus  Coliform bacteria can survive and reproduce in virgin olive oil containing low levels of phenolic compounds.Antimicrobial properties of various oils were tested  are among the most frequently occurring microorganisms in olive oils, and the presence of fungi (genus Aspergillus) has also been observed.Ciafardini et al.  conducteo et al.  observedi et al. , yeasts Olive oil blending is widely used for the production of sufficient quantities of olive oil with a balanced taste to meet the demands of the global market. In the study  variety Aayrouni, handpicked from the olive orchards located in the region North Lebanon. Aayrouni is an old variety still found in some ancient Lebanese groves. It is mainly cultivated in the North, and the Mount Lebanon regions. This cultivar is characterized by the high oil content of fruit, ranging from 34% to 37% expressed on fresh weight. This determines their use mainly for the oil production  were purchased from local gardening store . The garlic cloves (Allium sativum L.) were obtained from a family farm , and organic lemons (Citrus limon L.) were purchased at local store . Olive oil was obtained from Lebanese Genco Olive Oil . The acidification treatment by citric acid solution  of flavoring as following: fresh and dry material have same origin and is from the same batch, fresh material was processed accordingly , fresh garlic 4.7 g/100 mL of olive oil, 1.3 g/100 mL of dried garlic, and 50 μL/100 mL (0.05% w/v) of garlic essential oil , fresh rosemary 2 g/100 mL, dried rosemary 0.7 g/100 mL, rosemary essential oil  50 μL/100 mL (0.05% w/v), fresh lemon peel 4 g/100 mL, dried lemon peel 1 g/100 mL, and lemon essential oil  150 μL/100 mL (0.15% w/v) as described in Table 2.1.1Samples were stored for a year. They have been analyzed in 3 months intervals. First analysis T0 of unflavored oils and flavoring materials were analyzed separately according to Witkowska et al. .Salmonella spp., a 25 g of sample was added in the homogenization bag with 225 mL peptone water (Interscience), the bags were left for 24 h at 42°C in a thermostat (Schoeller instruments) to allow the pre‐multiplication. In the case of detection of other microorganisms, 10 g of the sample and 90 mL of physiological saline were added to the homogenization bag, homogenized, and a series of decimal dilutions were made. In the determination of sporulating anaerobic microorganisms, the tubes with appropriate dilutions were heated in a water bath (Julabo TW 20 Schoeller instruments) for 20 min at 80°C to eliminate vegetative forms of spore‐forming bacteria and other microorganisms.In case of evidence of 2.1.2Clostridium botulinum isolation) were added to sterile agar to determine Clostridium botulinum. A 1 mL of the sample was pipetted (Thermo scientific) into the petri dishes, poured with the appropriate nutrient medium (soil pouring method), and mixed in a circular motion. After solidification, the plates were placed in a thermostat (Thermo Scientific).A mixture of nutrient medium was weighed into a glass bottle and flooded with distilled water in a certain ratio according to the manufacturer's instructions. The culture medium was mixed and sterilized at a steam sterilizer at 121°C. Yolk emulsion and CBI supplement . Results were expressed in units of CFU/mL.2.2The determination of the total number of microorganisms was performed according to the standard ČSN EN ISO 4833‐1: 2.3The determination of the number of anaerobic sporulating microorganisms was performed according to EN ISO 4833‐1: 2.4The determination of yeasts and molds was performed according to the ČSN ISO 21527‐2: 2.5Enterobaccteriaceae bacteria, VRBG soil (Violet Red Bile Glucose) was used according to ČSN EN ISO 21528‐2  was used for the detection of lactic acid bacteria in accordance with ČSN ISO 15214: 2.9Statistical evaluation was performed using Statistica 14 and Microsoft Excel 2019. For better clarity, the results were converted to log CFU/mL. Basic statistical characteristics were calculated , and one‐factor ANOVA analyses of variance, including Duncan's post hoc test, was used to compare individual files.33.1The effect of the flavoring method on the number of microorganisms in oils flavored with rosemary, garlic, and lemon was evaluated Figure . Data wep < .05) in the oil flavored with rosemary essential oil (0.29 log CFU/mL) compared to the unflavored oil (0.82 log CFU/mL). The highest (p < .05) count was found for the oil flavored with fresh rosemary (1.39 log CFU/mL) as shown in Figure p < .05) of anaerobic sporulating microorganisms were in the oil flavored with dried rosemary (1.10 log CFU/mL) comparing to the unflavored oil (0.28 log CFU/mL).The total count of microorganisms was lower (p < .05) counts of total number of microorganisms 0.24 CFU/mL  than unflavored oil.The oil flavored with fresh garlic contained the lowest . Numbers of anaerobic sporulates were detected ranging from 0.24 log CFU/mL (oil flavored with dried lemon) to 0.64 log CFU/mL (oil flavored with fresh lemon). There was no difference (p > .05) in the numbers of anaerobic sporulating microorganisms between the oils we analyzed.The lemon flavored oils are compared in Figure p > .05). Counts ranged from 0.07 log CFU/mL (unflavored oil) to 0.22 log CFU/mL (oil flavored with dried lemon). The method of flavoring did not affect the presence of microorganisms, this hypothesis was not confirmed in lemon flavored oils.When comparing oils flavored with different forms of lemon and unflavored oil, no differences in yeast and molds counts were observed  was carried out and then added to the olive oil. Data were compared regardless of the time of sampling.p < .05) between the numbers of microorganisms in fresh rosemary and oil with added rosemary for all groups of microorganisms studied  than in the flavoring material alone. While rosemary contained total counts of microorganisms ranging from 2.36 to 4.08 log CFU/mL, the oil with rosemary contained TCM ranging from 0.22 to 1.39 log CFU/mL. The numbers of anaerobic sporulates in rosemary were found to range from 1 to 3.25 log CFU/mL, and in the oil with added rosemary from 0.45 to 0.83 log CFU/mL. Yeasts and molds in fresh rosemary and rosemary essential oil reached values of 3.28 and 1.30 log CFU/mL, respectively, and were not detected in dried rosemary. Yeasts and molds were detected in fresh and dried rosemary oils at an average of 0.09 log CFU/mL. Bacteria of the Enterobacteriaceae family were detected only in fresh rosemary (3.08 log CFU/mL) and dried rosemary (2 log CFU/mL). Enterobacteriaceae were detected at 0.02 and 0.03 log CFU/mL in oils with dried rosemary and essential oil.There was a significant difference  compared to oils samples . The numbers of aerobic microorganisms were 0.33 log CFU/g in the fresh lemon and 0.53 log CFU/mL in the oil after its addition. As for molds and yeasts, the counts were 0.44 log CFU/g in fresh lemon and 0.14 log CFU/mL in oil. The counts of anaerobic sporulates in the fresh lemon were 0.05 log CFU/g, counts increased (p < .05) after the addition of the oil to 0.64 log CFU/mL. The increase might be caused by the unflavored olive oil, its values are TCM 0.38 CFU/mL, anaerobic sporulates 0.52 CFU/mL, and yeasts and molds reaching 0.07 CFU/mL.Comparing counts of fresh lemon and oil with the addition of fresh lemon, the numbers of TCM, fungi and yeasts, respectively, were balanced (p > .05) to 0.73 log CFU/mL. The counts of anaerobic sporulates and fungi and yeasts were comparable in both dried lemon and oil after its addition (p > .05). The counts of fungi and yeasts were 0.22 log CFU/g in dried lemon and 0.27 log CFU/mL in oil with its addition. Higher yeasts and molds count 2.12 and 2.91 log CFU, respectively, were observed at commercial lemon flavored oil  from 0.33 to 0.64 log CFU/g or mL in the case of the oil. Anaerobic sporulates and yeasts and molds were not detected in the essential oil, but counts were higher (p < .05) in the oil after its addition, with 0.27 log CFU/mL for anaerobic sporulates and 0.21 log CFU/mL for yeasts and molds. It can be assumed that the anaerobic sporulates originate solely from the extra‐virgin olive oil used in the experiment.The numbers of microorganisms of the observed groups were higher in olive oil with the addition of lemon essential oil, compared to essential oil. The numbers of aerobic microorganisms increased  but also against beneficial microorganisms such as Lactobacillus acidophilus and Bifidobacterium bifidum. Otherwise, most of the foodborne pathogens tested  did not survive after 1 h of contact with olive oils. In another study of Karaosmanoglu et al. , including toxin forming Clostridium botulinum. Due to the fact that the detailed production conditions of flavoring material were not possible to control, the effect of only one independent variable on the above‐mentioned parameters was considered: the method of flavoring. The flavoring method factor did not affect the count of yeasts and molds in the oil samples. The three tested flavored oils had different effects on counts of microorganisms: total counts of microorganisms and anaerobic sporulates (p < .05) were significantly affected by method of flavoring only at rosemary and garlic flavored oil groups. However, no clear trend was observed in lemon flavored oil either in the TCM or anaerobic sporulates. The method of flavoring affects the microorganism persistency, independently of the primary contamination. Such a characteristic can be particularly observed when using flavoring material with high antimicrobial activity. This confirmed the natural antimicrobial property of garlic and its positive impact on microbiological quality of flavored olive oils.In conclusion, the present complex study has examined the effect of three flavoring methods  and storage time  on the microbiological quality of olive oil using three flavors . The parameters of interest were TCM, anaerobic sporulates, yeasts, molds and also counts of microorganisms typical for flavored olive oil ; formal analysis ; investigation ; methodology ; validation ; visualization (lead); writing – original draft (lead). Alzbeta Jarosova: Methodology (supporting); supervision ; validation ; writing – review and editing . Olga Cwikova: Data curation ; formal analysis ; investigation ; methodology (lead); supervision ; validation ; writing – review and editing . Gabriela Franke: Supervision (supporting); validation (supporting); writing – review and editing . Tereza Soumarova: Formal analysis ; investigation ; writing – original draft .The authors declare that there is no conflict of interest.


The coronavirus disease 2019 (COVID‐19) pandemic is responsible for huge morbidity and mortality throughout the world. Several serious complications of this disease have been reported. It can cause hypercoagulability, which may lead to venous and arterial thromboembolic diseases. This hypercoagulability state is also associated with high morbidity and mortality. Arterial thrombosis in COVID‐19 is poorly described compared to venous thrombosis and pulmonary embolism. We report a case of an extensive arterial thrombosis leading to a limb ischemia with extremely high D‐dimer in a COVID‐19 patient. A 69‐year‐old man was hospitalized for febrile dyspnea. He is a hypertensive and diabetic patient. On admission, pulse oxygen saturation was 72% on room air. He had cyanosis of the left foot up to the mid‐thigh. The left pedal, posterior tibial, popliteal and femoral pulses were abolished. Chest CT scan was in favor of COVID‐19. He has a high D‐dimer level of 257,344 ng/mL. Arterial Echo‐Doppler found an extensive intraluminal thrombus along the arterial axes of the left lower limb, completely obstructing them, starting from the primitive iliac artery just after its bifurcation with the aorta, and extending distally . The patient was diagnosed with COVID‐19 critical form, associated with ischemia of the left lower limb secondary to an extensive arterial thrombosis. He was receiving anticoagulation, and underwent surgical amputation of the ischemic limb. The patient survived the event; however, he was on long‐term oxygen therapy at home. Arterial thrombosis may occur during COVID‐19 and may be responsible for peripheral or central ischemia aggravating morbidity and mortality. The occurrence of these events is related to the D‐dimer value. Anticoagulation is an important part of the management of COVID‐19, especially in severe forms in order to limit the occurrence of these thromboembolic diseases.  Apart from the respiratory complications which are responsible for most of the deaths, several serious complications have been reported including compressive emphysema or acute pancreatitis. COVID‐19 can also induce a hypercoagulable state, at the origin of venous and arterial thromboembolic events. This hypercoagulability is associated with high morbidity and mortality.2A 69‐year‐old man was hospitalized with febrile dyspnea at the military hospital of Antananarivo. He reported close contact with a confirmed case of COVID‐19 5 days before the onset of symptoms. His history included hypertension treated with Losartan 100 mg per day, type 2 diabetes treated with Metformin 1500 mg/day, alcoholism and smoking cessation for 10 years (9.5 pack‐years). He has no known history of peripheral artery disease. For 13 days prior to his admission, he presented with a dry cough, shortness of breath at rest without orthopnea, fever, asthenia, and anorexia. Two days before hospitalization, he felt a spontaneous severe pain with swelling of the left lower limb. Physical examination revealed a body mass index of 28.7 kg/m2, a pulsed oxygen saturation of 72% on room air, a respiratory rate of 23/min, a high temperature of 38.9°C, a heart rate of 117 beats/min, a blood pressure of 135/80 mmHg and bilateral clinical signs of pneumonia. He presented a cyanosis of the left foot up to the mid‐thigh  reverse transcriptase‐polymerase chain reaction (rt‐PCR) performed on admission was negative. The complete blood count showed a hemoglobin level of 13.3 g/dL (13.5–17.5 g/dL) a white blood cells count of 11.81 G/L (5–10 G/L) and a platelet count of 81 G/L (150–400 G/L). The C‐reactive protein was 82.6 mg/L (<6 mg/L). The creatinine was 187 μmol/L (65.4–119.3 μmol/L). The blood sodium level was 141 mmol/L (135–145 mmol/L) and the blood potassium level was 4.9 mmol/L (3.6–5.2 mmol/L). The glycated hemoglobin was 7.5% (<6%). The D‐dimer was 514 times the upper normal limit (220–500 ng/mL). The troponin was normal. The electrocardiogram showed a regular tachycardia with a heart rate of 103 bpm. Chest CT scan was in favor of COVID‐19 showing ground glass images with 50–75% involvement Figure . The pat3We report here a case of a hypertensive and diabetic patient presenting a severe form of COVID 19 associated with an ischemia of the left lower limb with an extremely high D‐dimer level.High D‐dimer value is associated with severe infection and high risk of thromboembolic events during COVID‐19.Gold DD. et al. reported a series of cases of arterial thrombosis. The first case had a thrombosis of the two renal arteries, the superior mesenteric artery and the celiac trunk. The second case had a thrombosis of the aorta, the celiac trunk, hepatic, and the splenic arteries. The third case had a cerebral, pulmonary, splenic, and renal thrombosis. The fourth case had a thrombosis of the lung, the spleen, and the kidney. The last case was a peripheral thrombosis with an occlusion of the radial and ulnar arteries.One limitation associated with this case report is that we have not been able to perform any serology test for covid 19 to strengthen the diagnosis made by chest CT scan, due to unavailability of this test. Farther hypercoagulable workup aside from D‐dimer should have been done also, but could not be due to the patient's financial situation and the country's technical facilities. Some tests were not available. As a result of this challenge, it was mainly the tests that were available and that the patient could afford that were carried out.We report a case of an extensive peripheral arterial thrombus with an extremely high D‐dimer during COVID‐19. Arterial thrombosis can occur during COVID‐19, causing peripheral or central ischemia with increased morbidity and mortality. The occurrence of these events is related to the D‐dimer value.Johary Andriamamonjisoa Andriamizanaka: Methodology; validation; visualization; writing – original draft; writing – review and editing. Etienne Rakotomijoro: Investigation; methodology; validation; writing – original draft; writing – review and editing. Volatiana Andriananja: Validation; visualization; writing – review and editing. Mihaja Raberahona: Validation; visualization; writing – review and editing. Radonirina Lazasoa Andrianasolo: Validation; visualization; writing – review and editing. Rivonirina Andry Rakotoarivelo: Validation; visualization; writing – review and editing. Jean de Dieu Randria Mamy: Validation; writing – review and editing.None.None of the authors declare any conflict of interest.Written informed consent was obtained from the patient to publish this report in accordance with the journal's patient consent policy.


In this randomized, double‐blind, sham‐controlled trial, we explored the effect of 20 Hz transcutaneous auricular vagus nerve stimulation (taVNS) on gait impairments in Parkinson's disease (PD) patients and investigated the underlying neural mechanism.In total, 22 PD patients and 14 healthy controls were enrolled. PD patients were randomized (1:1) to receive active or sham taVNS (same position as active taVNS group but without releasing current) twice a day for 1 week. Meanwhile, all subjects were measured activation in the bilateral frontal and sensorimotor cortex during usual walking by functional near‐infrared spectroscopy.PD patients showed instable gait with insufficient range of motion during usual walking. Active taVNS improved gait characteristics including step length, stride velocity, stride length, and step length variability compared with sham taVNS after completion of the 7‐day therapy. No difference was found in the Unified Parkinson's Disease Rating Scale III, Timed Up and Go, Tinetti Balance, and Gait scores. Moreover, PD patients had higher relative change of oxyhemoglobin in the left dorsolateral prefrontal cortex, pre‐motor area, supplementary motor area, primary motor cortex, and primary somatosensory cortex than HCs group during usual walking. Hemodynamic responses in the left primary somatosensory cortex were significantly decreased after taVNS therapy.taVNS can relieve gait impairments and remodel sensorimotor integration in PD patients. The 20 Hz transcutaneous auricular vagus nerve stimulation (taVNS) could relieve gait impairments and remodel sensorimotor integration in PD patients. The results provided insights into the neural mechanism of taVNS and a new neuromodulation method for treating gait impairments in PD patients. Given that taVNS could induce widespread, diffuse cortical effects through nucleus tractus solitarius (NTS) and locus coeruleus (LC),22.1This was a pilot, randomized, double‐blind, and sham‐controlled study (registration no. NCT05561348). Eligible PD patients were recruited and then randomly (1:1) assigned to the taVNS stimulation group or sham stimulation group. A researcher who did not participate in the evaluations and statistical analysis used SPSS v25.0 software (IBM) to get the random number and was responsible for the interventions for two groups of patients. Our study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University (2022‐SR‐535). Written informed consent was signed by all participants prior to the study. Investigators and all PD patients were blinded to the interventions during the study.Right‐handed patients with idiopathic PD, visiting the Neurology Department of the First Affiliated Hospital of Nanjing Medical University were enrolled. The following inclusion criteria should be satisfied: (1) meet the diagnostic criteria of idiopathic PD according to the Movement Disorder Society (MDS) Clinical Diagnostic Criteria for PD2.2The study flow is shown in Figure Specifically, all PD patients were assessed for the severity of motor symptoms by the Unified Parkinson's Disease Rating Scale section III (UPDRS‐III),Subsequently, 26 PD patients were randomly allocated to receive active‐taVNS or sham‐taVNS stimulation in the outpatient department of Neurology . taVNS was conducted by transcutaneous electrical stimulation therapy instrument . Two modified dot‐like electrodes delivered the stimulation to the cymba conchae of left ear in the vicinity of the auricular branch vagus nerve Figure . Stimula2.3A portable Inertial Measurement Unit (IMU) system (GYENNO Science) during a 5‐m timed TUG test was used to access gait feature. IMUs were placed on the chest, back, wrists, thighs, ankles, and insteps of the subjects via Velcro straps in order. Wirelessly transmitted mobility data were stored and analyzed by a laptop that controlled the protocols. The mean value and variability  of gait feature including step length, stride velocity, stride length, arm range of motion (ROM) maximum, double support time, gait cycle, turning average duration, and turning average duration velocity were calculated .2.4A 35‐channel portable fNIRS device  was utilized. The sample frequency was 11 Hz, and the wavelengths were 760 and 850 nm. Given that prefrontal and sensorimotor cortex activity was correlated with gait impairments in PD,2) and deoxyhemoglobin (HHb) based on the modified Beer–Lambert law. Since HbO2 was the most used indicator to reflect alterations of cortical activity related to walking2 was used in the subsequent analysis. We excluded the 5 s immediately before and after the instruction.2 was subtracted from the experimental task to assess the relative change in HbO2 (ΔHbO2) in the walking task.2 was often considered a proxy for cortical activation.The experiment conducted in a quiet room with soft light included two phases: (1) participants were instructed to stand quietly, look straight ahead, and think of nothing for 15 s and (2) when hearing the ‘start’ command, participants walked for 65 s at their comfortable pace back and forth over a 5‐m distance, with a 180‐degree turn at each end. Notably, participants were required to stand still for at least 1 min to ensure stable blood pressure before each experiment. An internal software named NirSpark (Huichuang) was used to preprocess the fNIRS data. The steps are as follows2.52 within the bilateral PFC, PMA, SMA, M1, and primary somatosensory cortex during the walking task.The primary outcome measure was the effect of taVNS on gait parameters, UPDRS‐III, TUG, Tinetti Balance, and Tinetti Gait scores. The secondary outcomes included determination of effects of taVNS on ΔHbO2.6Safety was evaluated by recording the number of each participant's headaches, dizziness, tinnitus, ear irritation, or skin toxicity.2.7A sample size of at least 13 patients per group was required .χ2 test and Fisher's exact test were used for discrete variables. One‐way analysis of variance (ANOVA), Kruskal–Wallis, two‐sample t‐test, and Mann–Whitney test were used for continuous variables.All data were analyzed using SPSS v25.0 software (IBM) and Shapiro–Wilks test was performed to assessed for normality. For baseline demographic and clinical characteristics, t test or Mann–Whitney test was performed on gait parameters between PD patients and HC. Besides, we compared the difference of ΔHbO2 between PD patients and HCs using two‐sample t test to verify the existing findings and provide a basis for exploring the treatment mechanism. Since the comparison of ΔHbO2 was performed at the channel level, we corrected the p‐value by false discovery rate (FDR).Later, to evaluate the severity of gait impairments in PD patients, two‐sample 2, two‐way ANOVA, with group (taVNS stimulation vs. sham stimulation) and condition (pre‐stimulation vs. post‐stimulation) as the factors, was conducted. Specifically, the group main effect was assessed by comparing gait parameters, motor symptoms, and ΔHbO2 in the taVNS stimulation group with those in the sham stimulation group. Similarly, the stimulation condition main effect was determined using gait parameters, motor symptoms, and ΔHbO2 before or after taVNS stimulation, regardless of grouping. More importantly, the interactive analysis combined group and stimulation conditions. Effect sizes (η2) were also reported. Multiple comparisons were analyzed by Bonferroni post hoc tests. Statistical significance was defined as two‐tailed p < 0.05.Finally, to determine the effect of group and stimulation conditions on gait parameters, motor symptoms, and ΔHbO33.1Twenty‐two PD patients and 14 HCs who finished the entire procedures were included in this study. Table 3.2p = 0.023), arm ROM maximum (p = 0.017), and turning average duration velocity (p = 0.001), while increased turning average duration (p = 0.001) compared with HCs group  and gait cycle (p = 0.012) compared with HCs group .The inter‐group comparison showed that PD patients had decreased step length p = 0.02, arm ROM3.32 in channel S5‐D4 , S6‐D5 , S6‐D11 , S11‐D5 , and S13‐D14  than HCs .PD patients showed increased ΔHbO3.4F = 4.506, p = 0.040, η2 = 0.101), stride velocity , stride length , and step length variability   and double support  , stride length (p = 0.025), and stride velocity (p = 0.011) compared with those in the pre‐stimulation , stride length (p = 0.022), and stride velocity (p = 0.003) and decreased step length variability (p = 0.008) than those in the sham stimulation group  and double support (p = 0.016) than those in the sham stimulation group  Table . We also8) Table . No diffn Figure . Moreovep Figure . For grop Figure .p > 0.05, Figure No difference was found in the group main effect, condition main effect, or interaction when analyzing the motor symptoms including UPDRS‐III, TUG, Tinetti Balance, and Gait scores      Figure . Further) Figure . No diff) Figure . In addi) Figure .3.6taVNS possessed good tolerance since there were no reports of adverse events caused by stimulation.42 in the left dorsolateral prefrontal cortex (DLPFC), PMA, SMA, M1, and primary somatosensory cortex than controls during usual walking. Furthermore, we found that hemodynamic responses of primary somatosensory cortex in PD patients during usual walking were significantly decreased by taVNS, which might be related to the improvement of gait impairments.This study investigated the effect of taVNS on gait impairments and brain activity in PD. First, PD patients had decreased step length, arm ROM maximum, and turning average duration velocity, while increased turning average duration, stride velocity variability, and gait cycle relative to the HCs group. Simultaneously, improvements in gait characteristics, including step length, stride velocity, stride length, step length variability, gait cycle, and double support after 7‐day taVNS therapy, were significant. Second, PD patients had higher ΔHbOAccumulating literature uncovered that PD patients showed impaired pace, step length, and rhythmicity compared with age‐matched healthy adults.Cerebral gait control is mainly accomplished through direct and indirect pathways: the direct pathway from the M1 to the central pattern generators of the spinal cord participates in the automatic control of gait, and the indirect pathway from the PFC and PMA to the basal ganglia, and then to the brainstem motor center can regulate gait based on challenging situations.Apart from small sample size, some limitation should be considered. First, limited detection depth of fNIRS system hindered the detection of activation in subcortical structures. However, the portable fNIRS enabled us to capture functional alterations in the subjects' cerebral cortex during actual walking, which was beneficial for us to understand the neural mechanism of gait impairments in PD better. Second, dopaminergic therapies might modulate cortical function,5Our findings suggested that taVNS could relieve gait impairments and remodel sensorimotor integration in PD patients. The results provided insights into the neural mechanism of taVNS and a new neuromodulation method for treating gait impairments in PD patients.Heng Zhang: Conceptualization, Data acquisition, Formal analysis, interpretation, Writing‐original draft, Writing‐review & editing. Xing‐yue Cao: Conceptualization, Data acquisition, Writing‐review & editing. Li‐na Wang, Qing Tong, Hui‐min Sun, and Cai‐ting Gan: Data acquisition, Writing‐review & editing. Ai‐di Shan: Grouping and intervention of participants. Yong‐sheng Yuan: Conceptualization, Data acquisition, Writing‐review & editing, Funding acquisition. Ke‐zhong Zhang: Conceptualization, Data acquisition, safety assessment, Writing‐review & editing, Study supervision, Funding acquisition.This work was funded by the National Natural Science Foundation of China (82271273) and the Jiangsu Social Development Project (BE2022808).Authors declare no conflict of interest.Written informed consent for publication was obtained from all participants.Tables S1–S3Click here for additional data file.


Convolutional neural networks (CNN) for computer‐aided diagnosis of polyps are often trained using high‐quality still images in a single chromoendoscopy imaging modality with sessile serrated lesions (SSLs) often excluded. This study developed a CNN from videos to classify polyps as adenomatous or nonadenomatous using standard narrow‐band imaging (NBI) and NBI‐near focus (NBI‐NF) and created a publicly accessible polyp video database.We trained a CNN with 16,832 high and moderate quality frames from 229 polyp videos (56 SSLs). It was evaluated with 222 polyp videos (36 SSLs) across two test‐sets. Test‐set I consists of 14,320 frames . Test‐set II, which is publicly accessible, 3317 video frames , which was benchmarked with three expert and three nonexpert endoscopists.P = 0.01) with no significant difference with experts.Sensitivity for adenoma characterization was 91.6% in test‐set I and 89.7% in test‐set II. Specificity was 91.9% and 88.5%. Sensitivity for diminutive polyps was 89.9% and 87.5%; specificity 90.5% and 88.2%. In NBI‐NF, sensitivity was 89.4% and 89.5%, with a specificity of 94.7% and 83.3%. In NBI, sensitivity was 85.3% and 91.7%, with a specificity of 87.5% and 90.0%, respectively. The CNN achieved preservation and incorporation of valuable endoscopic innovations (PIVI)‐1 and PIVI‐2 thresholds for each test‐set. In the benchmarking of test‐set II, the CNN was significantly more accurate than nonexperts (13.8% difference [95% confidence interval 3.2–23.6], A single CNN can differentiate adenomas from SSLs and hyperplastic polyps in both NBI and NBI‐NF. A publicly accessible NBI polyp video database was created and benchmarked. Approximately 60% of polyps detected during colonoscopy are diminutive (≤5 mm), with two‐thirds of these adenomas.Recent years have demonstrated the potential of deep‐learning to characterize polyps using narrow‐band imaging (NBI), resulting in optimism that it can support nonexpert endoscopists to achieve PIVI.This study aims to develop an artificial intelligence (AI) model to characterize polyps, including SSLs, as adenoma or nonadenoma in both standard NBI and NBI‐NF and to create a publicly accessible NBI polyp video database.Unaltered endoscopy videos were prospectively collected from April 2019 to February 2021 at University College London Hospital to develop various AI algorithms for colonoscopy. Procedures used a high‐definition endoscope , an Olympus EVIS LUCERA‐CV290(SL) processor and were recorded with a high‐definition video recorder . CF‐HQ260L endoscopes provide standard NBI, whilst CF‐HQ290L also includes NBI‐NF, a 40‐fold magnification of standard NBI  of the convolutional neural network (CNN). Patients were recruited from April 2019 to November 2020, with periodic pauses in recruitment secondary to COVID. Patients were not screened beforehand, as all patients were eligible for inclusion. All procedures recorded during this timeframe were reviewed for inclusion. A total of 437 patients had no polyps, and 212 had histologically confirmed polyps in NBI  in the remaining 199 patients and 31,152 moderate/high‐quality frames. The polyps were separated into training (~50%), validation (~10%) and testing set (40%) with no overlap of data or patients , consisting of 149 adenomas, 56 SSLs, 35 hyperplastic and one TSA polyp from 121 patients and 16,832 frames . Test‐set I consisted of 157 polyps (111 diminutive) from 78 patients and 14,320 frames . These polyps are separate from those in the training and validation dataset.To create a robust publicly accessible dataset (test‐set II), NBI polyps were collected from 75 consecutive cases between December 2020 and February 2021. Forty‐four patients were found to have no polyps, and 31 patients had histologically confirmed polyps in NBI. The test‐set includes a total of 65 polyps (41 diminutive) and 3317 moderate/high‐quality frames. To benchmark the public dataset, we compared the CNN performance to three expert national bowel cancer screening program (BCSP) accredited colonoscopists (adenoma detection rate >45%) and three nonexpert colonoscopists accredited for independent colonoscopy by the UK Joint Advisory Group on gastrointestinal endoscopy. Further details of this benchmarking process are available in Appendix We developed a CNN to characterize polyps as adenoma or nonadenoma. In brief, an image is passed through a series of concatenated convolutional layers that output a feature vector Fig. . The vecThe CNN performance for each test‐set was measured on a per‐frame and per‐polyp level. Analyses included polyps of all sizes, diminutive polyps, each polyp category, each NBI modality, and performance compared to PIVI thresholds. For the per‐polyp analysis, we analyzed the proportion of annotated frames for each polyp that the CNN correctly characterized. A correct diagnosis was defined as ≥50% of frames correctly characterized by the CNN. For test‐set II, we compared the accuracy of the CNN to the expert and nonexpert endoscopists for all polyps, high‐confidence (HC) diagnoses, diminutive polyps, and HC diagnoses of diminutive polyps.P‐values of ≤0.05 were deemed statistically significant. Statistical analyses were performed using Python  and Stata .The agreement between the CNN‐predicted and histological diagnoses was evaluated using sensitivity, specificity, accuracy, Cohen's kappa coefficient, and area under the curve (AUC). Further information on calculation of these metrics is available in Appendix From 157 polyps, the CNN characterized adenomas with a sensitivity, specificity, and AUC of 90% or above in the per‐frame Fig.  and per‐From 111 diminutive polyps in test‐set I, the CNN characterized adenomas with a sensitivity, specificity, and AUC of 89% or above in the per‐frame and per‐polyp analysis. Eleven of the aforementioned 13 polyps misclassified were diminutive: seven adenomas, two SSLs, and two hyperplastic. The CNN sensitivity and specificity were higher in NBI‐NF compared to NBI: 89.4% vs. 85.3% and 94.7% vs. 87.5% . The CNN sensitivity to characterize diminutive adenomas was 89.5% in NBI‐NF and 91.7% in NBI.P = 0.01), HC diagnoses , diminutive polyps irrespective of OD confidence , and HC OD of diminutive polyps . In all analyses, the accuracy of the CNN was numerically higher than the expert BCSP endoscopists, but there was no significant difference.For test‐set II, the CNN was significantly more accurate than nonexperts Table . This waFor test‐set I (111 diminutive polyps) and test‐set II (41 diminutive polyps), there was 97% and 94% respective concordance between the CNN‐predicted colonoscopy surveillance intervals compared to histology‐derived intervals using the US Multi‐Society Task Force guidelines Table .16 TheIn this study, a CNN was developed and tested to differentiate adenomas from SSL and hyperplastic polyps in standard NBI and NBI‐NF using a total of 451 polyp videos and 34,469 video frames. To our knowledge, this is the largest dataset in the literature of polyp videos and frames annotated using NBI. In the per‐polyp analysis, the CNN characterized diminutive adenomas in each test‐set with a sensitivity and specificity greater than 87% and generalized well to both standard NBI and NBI‐NF. Surprisingly, standard NBI was more accurate than NBI‐NF for test‐set II (89.7% vs. 87.5%), which may reflect the difficulty of polyps as not all polyps were visualized in both modalities. For the benchmarking of the publicly accessible test‐set II, the CNN was significantly more accurate than nonexpert endoscopists with no significant difference to expert endoscopists. The CNN in this study also achieved PIVI thresholds. This level of performance could potentially be helpful in improving the generalizability of the ‘resect and discard’ strategy. However, our results should be interpreted with caution as clinical trials are required, with appropriate statistical powering, to evaluate PIVI when the endoscopists' OD is supported with the CNN.Several studies have demonstrated the potential of CADx to characterize polyps in NBI.The classification we used (adenoma vs. nonadenoma) allows the implementation of both PIVI strategies. As suggested by experts,Our CNN achieved favorable results without using a confidence threshold despite a smaller sample size of polyps for training than other models. A plausible explanation is that annotating high‐ and moderate‐quality video frames compensated for the modest number of polyps.Annotating high‐ and moderate‐quality frames also allowed us to identify that the orientation that a polyp is visualized, irrespective of adequate visualization to the human eye, can influence the CNN's performance. Over three‐quarters of polyps in each test‐set were correctly characterized in at least 80% of frames annotated, but the performance was more variable for 15% of polyps in test‐set I and 11% in test‐set II, with only 50–79% of annotated frames correct. For CADx to bridge the OD accuracy of experts and nonexperts, it should be consistent in its characterization in various views; however, this is poorly understood as CADx models are usually evaluated with only one or a few high‐quality images per polyp. If similar results are reproduced in other studies, future research should identify the optimal number of images required for CADx to provide a consistent characterization without significantly prolonging the procedural time.Our CNN performed favorably compared to several other CADx systems using NBI, but direct comparison is meaningless without assessing with the same test‐set. Publicly accessible datasets for CADx are essential to enable this comparison. They also advance research by helping to overcome barriers such as the generalizability of CADx models to new clinical settings.There are several limitations of this study. First, data is limited to a single center and endoscopy system (Olympus), and further evaluation with external datasets is warranted. Further publicly accessible datasets, such as the WEISS database, would help to overcome this limitation. Second, the study is subject to selection bias due to the retrospective nature of the study and the subjectivity in categorizing the quality of frames. However, we reduced this by collecting data prospectively, curating test‐set II from consecutive cases and not restricting analysis to a single optimal image per polyp. Third, the CNN classification is limited to polyps and does not incorporate characterization of invasive malignancy, limiting its role to supporting ‘resect and discard’ and ‘diagnose and leave’ strategies. Fourth, evaluation in patient characteristics such as age and sex were not performed. Lastly, whilst the histopathology was assessed by expert gastrointestinal histopathologists, a consensus diagnosis would be more robust given the interobserver variability in differentiating SSL and hyperplastic polyps.In conclusion, we demonstrated that a single CNN can differentiate adenoma polyps from nonadenomas in both NBI and NBI‐NF. A robust, publicly accessible NBI polyp video database was curated and benchmarked. Further evaluation in a clinical trial is warranted.Author L.B.L is the chair for the British Society of Gastroenterology Artifical Intelligence (AI) Task Force, a minor shareholder in Odin Vision, received research grants from Medtronic, Pentax Medical, and DynamX, and served on the Scientific Advisory Boards for Dynamx, Odin Vision, and Ninepoint Medical. R.K. is the secretary for the British Society of Gastroenterology AI Task Force. D.S. is a shareholder in Odin Vision and Digital Surgery Ltd. M.H. received speaker fees from Cook Medical. A.C.‐M., P.B., S.H., J.G.‐B.P., D.T., and P.M. are employees of Odin Vision Ltd. The other authors declare no conflict of interest for this article.This study was supported by the Wellcome/EPSRC Centre for Interventional and Surgical Sciences at UCL (203145Z/16/Z) and Innovate UK (26673). Author L.B.L. is supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre and the CRUK Experimental Cancer Medicine Centre at UCL.Appendix S1. Supplementary material.Click here for additional data file.


Microorganisms are known to be natural agents of biocorrosion and mineral transformation, thereby potentially affecting the safety of deep geological repositories used for high‐level nuclear waste storage. To better understand how resident microbial communities of the deep terrestrial biosphere may act on mineralogical and geochemical characteristics of insulating clays, we analyzed their structure and potential metabolic functions, as well as site‐specific mineralogy and element composition from the dedicated Mont Terri underground research laboratory, Switzerland. We found that the Opalinus Clay formation is mainly colonized by Alphaproteobacteria, Firmicutes, and Bacteroidota, which are known for corrosive biofilm formation. Potential iron‐reducing bacteria were predominant in comparison to methanogenic archaea and sulfate‐reducing bacteria. Despite microbial communities in Opalinus Clay being in majority homogenous, site‐specific mineralogy and geochemistry conditions have selected for subcommunities that display metabolic potential for mineral dissolution and transformation. Our findings indicate that the presence of a potentially low‐active mineral‐associated microbial community must be further studied to prevent effects on the repository's integrity over the long term. Biocorrosion and microbial mineral transformation can affect the safety of deep geological repositories for high‐level nuclear waste storage. We analyzed the composition and evaluated the importance of mineral‐associated microbial communities in Opalinus Clay for safety purposes. Rock‐attached communities were dominated by phyla capable of corrosive biofilm formation. Based on the abundance of potential iron‐reducing bacteria and available electron acceptors, iron reduction appeared to be the most important process. Site‐specific mineralogy and geochemistry have selected for subcommunities and specific metabolic functions. Most countries have yet to develop and implement a safe long‐term waste management strategy  that could increase the gas pressure causing damage to the structural integrity of the repository and the surrounding rock. On the other hand, processes such as microbial sulfate reduction or hydrogenotrophic methanogenesis could reduce the gas pressure build‐up   and element analysis (inductively coupled plasma atomic emission spectroscopy) to explore the microbial community composition of OPA in the context of its physicochemical constraints.22.12.1.1Two drill cores from the sandy and shaly facies of OPA as well as the Passwang formation (PW), a limestone stratigraphically located above the OPA formation, were recovered from the boreholes BMA‐3 and BMA‐4 at Mont Terri underground research laboratory . The 15 m long core BMA‐3 was drilled in niche 5 of gallery 18 Figure . The cor−13 m s−1 , we applied a contamination control using a fluorescent particle tracer similar to Stroes‐Gascoyne et al. , total organic carbon (TOC), and total carbon (TC) analyses. Some of the powder was further homogenized with a micronizing mill to a grain size of <10 µm. This grain size was used for quantitative XRD analysis.Subsampling and sample preparation for microbiological purposes were performed in an N2.22.2.1θ from 4.6° to 85°. The mineralogy was first determined with the software EVA (version 11.0.0.3) by Bruker. Rietveld refinement for quantitative analysis was performed using the program BGMN and the graphical user interface Profex  were obtained between 3.45 and 9.30 m from the gallery wall, while samples of the shaly facies (BMA‐4) were obtained between 3.97 and 9.13 m from the gallery. A PANalytical Empyrean XRD was used for the measurements, operating at 40 kV and 40 mA with Cu‐Kα radiation and a step size of 0.013°22.2.22O and CO2 were calculated. Additionally, sulfur was analyzed using an Eltra CS 2000 instrument, and nitrogen using a Euro EA 3000 elemental analyzer.Major elements and some minor elements were analyzed on fused beads using an AXIOS advanced XRF spectrometer . The quantification level for the wt% range is 0.02 wt% and 10 ppm for minor elements. The analysis resulted in an abundance of oxides which were later transformed into element concentrations. H and C were analyzed using a Euro EA Elemental Analyzer. Hg and the supernatant was filtered through a 0.22 µm cellulose acetate filter . Anions were analyzed using a Sykam S 155 ion chromatograph with an integrated suppressor. As a mobile phase, we used an eluent containing 636 mg/L Na2CO3 and 7.5 mg/L NaSCN with a flow rate of 1 mL/min. A Sykam SykroGel Ax300 AB‐A01 column suitable for quantification of anions F−, Cl−, Br−, NO2−, NO3− SO42−, and PO43− was used at a temperature of 60°C. Triplicates of 50 µL leachate and several certified multielement standards were injected using a Sykam S 5300 sample injector. Concentrations were determined via peak area evaluations.To determine anion concentrations, sample material was leached according to Blume et al. . Five gr2.2.3A mass spectrometer DELTA V Advantage from Thermo Fisher Scientific and the Element analyzer EA Isolink were used for TC and TOC analyses. For the TC sample preparation, ca. 5 mg material was analyzed in Sn‐capsules with an analytical precision of TC < 0.1%. For TOC, 5 mg material was weighed in Ag‐capsules, in situ acid treated using first 3% and second 20% HCl, and analyzed with an analytical precision of TOC < 0.2%. The difference between TC and TOC results in total inorganic carbon (TIC) contents. With the TIC contents, the calcite contents were calculated using the relative atom masses.2.32.3.1DNA was extracted from three biological replicates of each OPA facies and one sample from the PW. Replicates were obtained from different depth locations of the drill cores: samples representing the sandy facies were obtained from core BMA‐3 3.85, 5.70, and 7.25 m from the gallery wall and are referred to as OPA sandy‐1 to OPA sandy‐3. The sample from the PW formation (PW) was obtained from the same core at 10.75 m from the gallery wall. The samples OPA shaly‐1 to OPA shaly‐3 were sampled from core BMA‐4 4.26, 6.46, and 8.90 m from the gallery.TM filters (Merck Millipore) used to filter the N2 gas from the anaerobic chamber before sample preparation (inflow) and afterward (outflow).Total genomic DNA was extracted using the DNeasy PowerSoil Pro Kit (Qiagen). The lysate of five extraction replicates was pooled on one MB spin column to enhance the yield of DNA. In addition to the samples, DNA was extracted from different negative controls (NCs): a blank kit extraction without adding any sample (kit NC) and from Sterivex2.3.2Recovered DNA was amplified using the primer pair 515F and 806R  using the R package labdsv implementing the algorithm of Dufrene and Legendre  plot before duplicates were merged for the microbial community analysis Figure . For staLegendre . The co‐33.1x‐axis, which explained 48.4% of the variance. The separation between OPA and PW was mainly caused by the high abundance of quartz and plagioclase in the PW formation and higher abundances of illite and kaolinite in the OPA samples , calcite, pyrite, and feldspar (orthoclase and plagioclase) at different concentrations , carbon , and calcium carbonate (CaCO3) content as well as the concentrations of different elements including nitrogen (N) and sulfur (S)  was characterized by the highest pyrite (FeS2) content and concomitantly the highest sulfur and iron contents.To further describe the environmental conditions of the seven samples used for microbial community analysis, we determined anion concentrations, water (H) Figure . Results3.22O, TOC, N, P, Na, Ni, Rb, and Zr. Along the x‐axis of the ordination plot, the variance of the microbial communities was correlated mainly with plagioclase and partly with quartz and Zr, which were enriched in the PW sample , and Methanosaeta (1). Bacterial ASVs were affiliated with Nocardioides (1), Rhodoferax (1), Luteolibacter (2), and unclassified Verrucomicrobiaceae (1). The 10 indicator ASVs represented about 40% of the entire community of the PW formation. Luteolibacter ASVs had an abundance of 17.6%, while ASVs affiliated with the methanogens Methanobacterium and Methanosaeta made up 9% of the total community.An indicator species analysis on the ASV level revealed the occurrence of unique taxa in the PW formation Table . We foun3.3r = 0.94, r = 0.84, r = 0.92, and r = 0.88) and plagioclase  , kaolinite  and illite  being less abundant in the PW formation. Illite, the main clay mineral in OPA, was positively correlated with some of the most abundant bacterial phyla in OPA such as Actinobacteria (r = 0.85), Bacteroidota (r = 0.85), and Proteobacteria (r = 0.90). Other abundant bacterial phyla in the OPA facies, such as Firmicutes, did not correlate with the clay minerals directly but showed an inverse correlation with quartz (r = −0.79). Acidobacteriota and the less abundant Chloroflexi as well as Deinococcota were positively correlated with pyrite , which was enriched in the sample OPA sandy‐1  . Within the phylum Bacteroidota, the class Bacteroidia was most abundant and responsible for the correlation with illite (r = 0.85). Clostridia were not the most abundant class of the Firmicutes but like the phylum, their abundance negatively correlated with quartz (r = −0.85). In addition, Clostridia showed a negative correlation with the mineral plagioclase (r = −0.87) and a positive correlation with the clay minerals illite (r = 0.78) and chlorite (r = 0.83). Although Alphaproteobacteria were less abundant than Gammaproteobacteria, they were responsible for the positive correlation of Proteobacteria with illite (r = 0.91).Within the phylum Actinobacteroidota, the class Actinobacteria was most abundant and thus responsible for the correlation with illite  Figure . Thermolp = 0.018, Pearson's r = 0.84). Potential iron reducers were diverse with 73 ASVs belonging to the genera Acinetobacter (25 ASVs), Acidiphilium (3), Acidibacter (1), Anaeromyxobacter (4), Bacillus, Bryobacter (3) Clostridium sensu stricto 1 (3) and Clostridium sensu stricto 8 (1), Desulfosporosinus (1), Desulfovibrio (2), Paenibacillus (4), Paludibaculum (1), Pseudomonas (17), Sulfurospirillum (1), Treponema (2), and Vibrio (1) , Methanobrevibacter (1), unclassified Methanofastidiosa (1), Rice Cluster I (1), Methanoregula (1), Methanosaeta (5), Methanohalophilus (1), Methanosarcina (12), and unclassified Methanomassilliicoccaceae (2). In OPA, methanogens were mainly affiliated with Methanosarcina and Methanobacterium. The PW sample was also dominated by Methanobacterium with about 9% relative abundance. Methanosaeta represented almost 4% of that sample. Due to a higher quartz and plagioclase content and a lower chlorite and illite content in the PW formation compared to OPA, methanogenic archaea were positively correlated with quartz  and plagioclase , while they were negatively correlated with chlorite  and illite .Since microbial processes such as corrosion, mineral alteration, or gas pressure changes can affect the integrity of engineered and geological barriers in a final repository, we aimed at evaluating the potential for specific microbial processes in OPA. Therefore, we focused on the relative abundance of functional microbial traits including IRB, SRB, and methanogenic archaea Figure . We foun3.4r > 0.6) and was constructed using the Walktrap community finding algorithm . 156 out of 1675 ASVs were finally employed in the network analysis. The co‐occurrence was explored based on strong correlations  and thus with the Fe and S content, which were enriched in that sample , Methanosaeta (3.2%), and two ASVs affiliated with Luteolibacter (11.9% and 5.7%), that were also identified as indicator species. The remaining modules were not dominated by single ASVs. Most abundant ASVs (>2%) across all modules were affiliated with the phyla Acidobacteriota, Actinobacteria, Bacteroidota, Cyanobacteria, Alpha‐ and Gammaproteobacteria, Planctomycetota, and Verrucomicrobiota  was in accordance with the number of rock samples analyzed. Each module had a unique composition of co‐occurring ASVs, which predominated only at one sample location Figure . For thie Figure . Higher 2 Figure , which iria Data . At the ria Data  were sigria Data . A higheria Data . Module 44.12 gas atmosphere during sample preparation and different controls during DNA extraction and amplification. Hence, our study strongly expands the knowledge of the rock‐attached microbial communities in unperturbed OPA.The present study provides a comprehensive insight into OPA rock as a microbial habitat, the mineralogical constraints, as well as potential consequences on the safety of a repository. Different measures for contamination control were applied to guarantee the reliability of our results. Measures included the application of contamination tracers during drilling, sampling, and sequencing of the NDespite the harsh living conditions in OPA rock, we identified a diverse microbial community Figures , and A7 Methanobacterium was very abundant within the PW formation.We observed relatively homogenous microbial communities in both OPA facies Figure , therebyExiguobacterium, Bacillus, Microbacterium, Nocardioides, Alicyclobacillus , can be involved in MIC of copper , which is known for chemolithoautotrophic methanogenesis using solely CO2 and H2. Hydrogen can be produced abiotically through water–rock interactions or biotically through fermentation processes  and negatively correlated with quartz and plagioclase. The carbonate mineral calcite could serve as an inorganic carbon source. Carbonate dissolution can result in the localized formation of CO2 from CO32−, which are supposedly associated with methane oxidation  in clays  could be the dominant electron acceptor for microbial respiration also in OPA  reduction could reduce the risk of overpressure and corrosion processes related to abiotically formed H2 in a potential repository.The reduction and dissolution of structural iron present in clay minerals such as illite, illite–smectite, kaolin, and chlorite could affect the integrity of insulating clays in a repository such as a bentonite barrier or the OPA host rock. The dominant occurrence of potential IRB supports a previous assumption that iron reduction could be the most safety‐relevant process in a DGR  and all potentially corrosive biofilm‐forming orders were common not only in the overall communities but also in the site‐specific subcommunities ; formal analysis ; methodology ; visualization (lead); writing—original draft (lead); writing—review and editing . Steffi Genderjahn: Formal analysis ; investigation ; methodology ; writing—review and editing . Anja M. Schleicher: Conceptualization ; investigation ; methodology ; writing—review and editing . Alexander Bartholomäus: Data curation ; methodology ; visualization ; writing—review and editing . Jens Kallmeyer: Formal analysis ; methodology . Dirk Wagner: Conceptualization ; funding acquisition ; supervision ; writing—review and editing .The authors declare no conflict of interest.None required.Data S1. Geochemical and mineralogical parameters of samples used for microbial community analysis. i–s, illite–smectite mixed layers; calcite, including siderite & ankerite; LOI, loss of ignition.Click here for additional data file.Data S2. Genus‐level microbial community composition and their relative abundance.Click here for additional data file.Data S3. The abundance of co‐occurring ASVs in each rock sample representing one module. ASVs with > 2% abundance are highlighted in red. Indicator species of the Passwang Formation are highlighted in orange in module 7.Click here for additional data file.Data S4. Read counts (>20) and taxonomy of ASVs found in the negative controls including a blank kit extraction, blank PCR, and DNA extracts from N2 gas of the anaerobic chamber used for sample preparation. The table only includes ASVs that were filtered from the sample's ASVs.Click here for additional data file.


We demonstrate that laser ablation creates a ring of damaged tissue around the wound that is cleared by fibroblasts prior to wound closure. This process is dependent on ROCK and dynamin activity, suggesting a phagocytic or endocytic process. Transmission electron microscopy of fibroblasts that have entered the wound area reveals large intracellular vacuoles containing fibrillar extracellular matrix. These results demonstrate a new model to study matrix clearance by fibroblasts in a 3D soft tissue. Because aberrant wound healing is thought to be caused by an imbalance between matrix degradation and production, this model, which captures both aspects, will be a valuable addition to the study of wound healing.Although the mechanisms underlying wound healing are largely preserved across wound types, the method of injury can affect the healing process. For example, burn wounds are more likely to undergo hypertrophic scarring than are lacerations, perhaps due to the increased underlying damage that needs to be cleared. This tissue clearance is thought to be mainly managed by immune cells, but it is unclear if fibroblasts contribute to this process. Herein, we utilize a 3D  I.Dermal wound healing is a sequential process characterized by hemostasis, inflammation, new tissue formation, and remodeling, four overlapping phases that must occur in a timely manner to restore barrier function and prevent infection. While these phases are considered to be preserved regardless of the type and location of the wound,Despite the pervasive clinical presentation of various types of wounds, such as ulcers, abrasions, lacerations, and burns, there are few studies comparing tissue damage and the wound healing response between different injury modalities. Early animal studies comparing burn wounds to excision wounds show that burns heal more slowly than skin excision woundsDuring the inflammatory phase, necrotic tissue, including dead cells and damaged ECM, and pathogens are removed from the wound bed,μm) without dislodging the suspended microtissue. We first demonstrate that transection and laser ablation cause different degrees of tissue damage, which results in altered wound healing dynamics. While healing occurred in both wound types, laser ablated wounds exhibited a prolonged opening phase after injury compared to transected wounds, wherein fibroblasts invade and remodel the damaged tissue surrounding the wound. Closer examination with transmission electron microscopy revealed that fibroblasts engulfed damaged ECM from laser ablated wounds through a process that was mediated by RhoA and dynamin activity. These data suggest a previously unappreciated role for fibroblasts in wound clearance.To begin to address this question, we set out to study tissue repair in the presence of varying amounts of damaged tissue in our previously reported biomimetic model for stromal wound healing.II.A.In our previous studies, stromal microtissues were injured using a microdissection knife mounted to an xyz-micromanipulator.2 for 532 and 1064 nm, respectively . Thus, the ablation threshold of collagenous microtissues was similar for both wavelengths. Because laser pulse energies were measured before each experiment, we reported laser pulse energies, and not estimated fluences, in the x-axis of the graphs. At the minimum energies, the gaps created were smaller  than those created by knife (41 600 ± 3980 μm2). At intermediate energies, 0.4 and 0.55 mJ at 532 nm and 2 mJ at 1064 nm, the average gap size  was on the same scale as knife injuries. Further increase in the pulse energy for both wavelengths yielded initial gap areas that were much larger than what the knife was capable of creating [To establish a protocol for reproducibly inflicting full-thickness gaps with laser light, microtissues were injured with laser pulses of different wavelengths (532 or 1064 nm) and pulse energies ranging from 0.25 to 3 mJ, two parameters that affect the energy density of the focused laser pulse. Phase contrast images were captured following injury , and thecreating . To assecreating . The arecreating . TogetheB.Gap closure in our model system is initiated by the fibroblasts adjacent to the wound edge.μm2/h. For 532 nm injuries, the closure rate during this phase was −890 ± 820 μm2/h (p < 0.001 compared to knife). For 1064 nm injuries, the closure rate during this first phase was −870 ± 390 μm2/hour (p < 0.001 compared to knife). During the closure phase, the closure rates were not significantly different between injury modes [To quantitatively assess tissue closure between the different conditions, we compared closure rates during two phases of the healing process. We defined the initial phase between 0 and 4 h because ∼80% of tissue gaps reached their maximum area by 4 h. We considered the closure phase to occur between 6 and 16 h post injury as most tissue gaps (>90%) reached the maximum area by 6 h, and the closure rate was linear for the ensuing 10 h . The ratry modes  right. TC.To investigate the gap opening in laser inflicted wounds, we carefully analyzed the time lapse phase contrast images during the opening phase and observed a darker band of damaged tissue at the periphery of the gap  that corμm) than for laser (152 ± 18 μm) injuries (p < 0.001). Qualitatively, the knife-injured tissues appear to have a higher density of fibers than do ablated tissues [μm region closest to the gap edge was divided into subregions and the density of each calculated. The histogram showing fiber density within these subregions reveals that laser injuries contain more empty space than do knife injuries [μm of the gap edge. This analysis revealed that the majority of fibers in knife-injured tissues aligned along the long axis of the tissue, parallel to the direction of movement of the knife. The peak alignment angle shifts to about −20°, and a wider spread of orientation angles was observed for ablation injuries compared to mechanical injuries [From the time-lapse images in  tissues , suggestWe wondered next how the fibrous matrix structure changes as the fibroblasts remodel the microtissue at the gap edge. Using reflection microscopy, we performed live microscopy and captured images every 10 min [μM), myosin light chain kinase (MLCK) inhibitor peptide 18  or Y27632 (10 μM), and a Rho-associated kinase (ROCK) inhibitor were added prior to microtissue ablation. Interestingly, blebbistatin and P18 did not significantly affect the tissue opening rate, while Y27632 significantly decreased the mean tissue opening rate to 50% ± 1% of the vehicle control, DMSO (p < 0.001). These results suggest that ROCK activity, but not cellular contractility, is required for wound clearance in our system. In addition to modulating cellular contractility, ROCK II activity is also an important regulator of phagocytosis of FN-coated beads in fibroblasts.μM) to inhibit dynamin activity, which is necessary for phagocytosisGiven the fiber breakages and compaction of the damaged matrix, we postulated that actomyosin contractile forces were required for tissue clearance . The datD.μm in diameter), and the fibrillar structures appeared to have a similar morphology to those of the surrounding damaged extracellular matrix. At 20 h after ablation, cells at the wound edge lacked vacuoles, but instead contained numerous organelles, including mitochondria [To further corroborate the hypothesis that fibroblasts clear wounds by engulfing ECM, we performed transmission electron microscopy (TEM) on uninjured microtissues and at the wound edge of laser injured microtissues at 0, 4, and 20 h post injury . Immediachondria . This obIn order to determine whether ECM phagocytosis occurred at all times in the microtissues, or whether it was an injury-specific response, we quantified the number of vacuoles that contained distinct fibrillar structures as in  for 10 fIII.In this study, we explored laser ablation as a method to create full thickness wounds in engineered stromal microtissues and found that fibroblasts first clear the wound from damaged ECM before a new provisional matrix is assembled to close the wound. Previous studies have established a critical role for phagocytic macrophagesIn vitro wound healing models have been instrumental tools to parse out mechanisms of cell migration,in vitro platforms to gain such insight and to identify new therapeutic targets for chronic healing and fibrotic diseases.Analogous to the healing dynamics of burn wounds in animals,IV.A.2, and pillars had 0.62 and 1.0 mm between pillar centers. Pillar diameter was 120 μm for the first layer with a height of 110 μm, and cap diameter was 180 μm with a height of 80 μm.As previously described,B.2 in growth medium for 16–20 h prior to injury, during which time they spontaneously compact, as previously described.3T3 cells (ATCC #CCL-92) were grown in Dulbecco's modified eagle medium  with 10% bovine (Sigma #B9433) or calf serum (ATCC #30-2030) and 1% penicillin/streptomycin (Life Technologies #15140-122). Cells were mixed with rat tail tendon collagen I (Corning #356236) at a final concentration of 2.2 mg/ml (pH ∼ 7.5). Then, 900 K cells were added to each device and centrifuged to drive cells into the microwells. Excess collagen solution was removed, and collagen in the microwells was allowed to polymerize at room temperature for 10 min, then at 37 °C for 10 min. Microtissues were cultured at 3 °C with 5% COC.For knife injury, a diamond dissection knife  mounted to an XYZ-micromanipulator  was used to tear a full-thickness wound in the microtissues . Laser aD.2). Gap area was measured every hour in ImageJ, manually, using the polygon selection tool. The closure rate was determined as the slope of the line of best fit through data from 0 to 4 h and from 0 to 16 h.For closure experiments, time-lapse images were taken every 30 min for 18 h on a Nikon Ti Eclipse microscope fitted with an environmental chamber  parallel to the tissue long axis, and a width of 25 μm adjacent to the gap edge. Next, a Gaussian blur was applied to images to reduce pixelation effects, then the local pixel intensity gradient was used to determine a perpendicular normalized vector, which was then used to calculate the local nematic tensor for each pixel. The region was then subdivided into 10-pixel × 10-pixel subregions and the average nematic tensor for each subregion was calculated. The largest eigenvector corresponding to the largest eigenvalue of this average describes the alignment direction. Data are reported as a histogram of subregion alignment angles for all 25 × 148 μm regions. For fiber density, an automatic threshold was applied in ImageJ, and the pixel density for the same 10 pixels × 10 pixels subregions was calculated. Data are reported as a histogram of subregion signal density for all 25 × 148 μm regions.The fiber alignment analysis was performed in MATLAB  using a previously reported MATLAB code that was based on the Fibril Tool.F.μM. Myosin light chain kinase inhibitory peptide 18  was used at 10 μM. ROCK inhibitor Y27632  was used at 10 μM. Nocodazole  was used at 100 nM. Dynasore (Sigma #D7693) was used at 60 μM. Latrunculin A (Sigma #428026) was used at 1 μM.Inhibitors were added in fresh growth medium 30 min prior to injury. DMSO (Fisher Scientific #BP231) was added at 0.2% (v/v) as a vehicle control. Blebbistatin  was used at 100 G.® BioWave  at 100 W for 4 min. A subsequent incubation in 1% osmium in 0.1M PB in the BioWave was performed, and samples were then subject to a gradual ethanol dehydration sequence: 50% ethanol for 10 min, 2% uranyl acetate in 70% ethanol for 40 min, 85% ethanol for 10 min, 95% for 10 min, and 100% for 30 min. Samples were embedded in EM812 epoxy resin (Electron Microscopy Sciences) with 2,4,6-tris-(dimethylaminomethyl) phenol (DMP-30) and cured at 60 °C for 48–72 h. Samples were sectioned with a Leica UCT Ultracut ultramicrotome into 1 μm sections and imaged using a JEOL JEM-1400 Flash TEM. The TEM embedding, sectioning, and imaging were performed by the Integrated Biomedical Imaging Services (IBIS) at the Boston University Medical School Campus. The Transmission Electron Microscope was funded by the NIH Award No. S10OD028571.For transmission electron microscopy (TEM), samples were fixed at specified time-points in 2% PFA/2.5% glutaraldehyde overnight. The samples were washed thrice in 0.1 M phosphate buffer (PB) and a secondary (post) fixation was performed in a 1.5% potassium ferricyanide:1% osmium in 0.1M PB in a PelcoH.Statistical tests were performed in JMP Pro 15 software. First, the Shapiro–Wilk test was performed on each dataset to determine if the data were normally distributed. The specific statistical tests used are specified in figure captions; generally, the Dunnett's test with control was performed for normally distributed data, and the Steel test with control was performed for non-normally distributed data. A p-value < 0.05 was considered significant. For supplementary material for details, which includes an explanation of how laser fluence was calculated, which includes Fig. S1: details of laser ablation system and Table S1: measured laser power and calculated laser fluence. Next are supplementary figures cited in the Results section: Fig. S2: quantification of damaged tissue area, Fig. S3: treatment of microtissues with latrunculin A, and Fig. S4: ethidium staining following gap closure.See the