The Robert-Koch-Institute reports that during the summer holiday period a foreign country is stated as the most likely place of infection for an average of 27 and a maximum of 49% of new SARS-CoV-2 infections in Germany.Cross-sectional study on observational data. In Germany, summer school holidays are coordinated between states and spread out over 13 weeks. Employing a dynamic model with district fixed effects, we analyze the association between these holidays and weekly incidence rates across 401 German districts.We find effects of the holiday period of around 45% of the average district incidence rates in Germany during their respective final week of holidays and the 2 weeks after holidays end. Western states tend to experience stronger effects than Eastern states. We also find statistically significant interaction effects of school holidays with per capita taxable income and the share of foreign residents in a district’s population.Our results suggest that changed behavior during the holiday season accelerated the pandemic and made it considerably more difficult for public health authorities to contain the spread of the virus by means of contact tracing. Germany’s public health authorities did not prepare adequately for this acceleration. To a small extent, this is because traveling via bus, train or plane adds to the risk of becoming infected.The Robert-Koch-Institute (RKI) reports that over Germany’s entire summer school holiday period in ~27% of weekly cases reported to the Institute a foreign country was mentioned as the most likely place of infection.We complement the RKI’s analysis by studying the extent to which summer school holidays have accelerated the pandemic in Germany. In order to estimate the effect of summer school holidays on the weekly incidence rate, we employ an ecological analysis of variation in the weekly SARS-CoV-2 confirmed case incidence rate across German districts . Germany provides an excellent case study since we can exploit a particular feature of its system of school holidays, namely that they are not uniform across the Federal Republic but vary in their start and therefore also their end date from state to state in a pre-determined way. This idiosyncratic feature allows us to disentangle the effect that holidays have had on incidence rates in German districts located in states that are or have been on holiday from the general upward trend in new infections in Germany.We test the following four hypotheses: First, school holidays have a positive effect on incidence rates. Second, the later parts of any given holiday season have a larger effect than its earlier parts given that there is a delay until holiday travelers return home and given infections are on the rise in practically all holiday travel destinations, both within and outside Germany, thus increasing the risk of catching the virus as the holiday season proceeds. Third, the holiday season does not merely increase individual risks. Travel associated with the holiday season should also have a lasting effect on the epidemic situation in the home districts because any infected returning traveler increases the probability of additional infections. Thus, the effects of holidays and holiday-related travel on incidence rates do not disappear when the holiday season is over. And fourth, school holidays will have a stronger effect on incidence rates in districts that are richer on average and in which a larger share of the resident population are foreigners. Richer people can afford better to go on holiday for longer and foreign citizens are likely to use the holiday season for returning to their home country for family visits (possibly in addition to taking other holidays) not least because the lockdown in the spring of 2020 prevented most of them from seeing family abroad over the Easter holiday period.,There is surprisingly little existing evidence on the impact of public holidays on the SARS-CoV-2 pandemic. Early research has shown that the extension of the Lunar New Year holidays in China has contributed to the country’s successful containment of the pandemic.www.rki.de). They are based on confirmed positive tested cases. While the number of confirmed cases can be a problematic measure for the pandemic’s dynamics, we know of no reason why testing would systematically vary across German districts.Our dependent variable is the weekly incidence rate (per 100 000 people) in a German district. Data are sourced from the RKI website  and terminating with the weekly incidence rate on Wednesday 23 September (week 38). We deliberately define the week to end in a Wednesday rather than Sunday or Monday to avoid noise from occasional corrections made on Mondays or Tuesdays to compensate for under-reporting to the RKI over the weekend. For each district, we analyze the period ranging from 2 weeks prior to the beginning of holidays to 2 weeks after the end of the holidays. Our panel thus has In Germany, the dates of the summer school holidays are chosen years in advance by each of the 16 states in close consultation with each other. The intention is to reduce the probability and length of traffic jams on Germany’s crowded motorways during the summer months. In each state, schools close for ~6 weeks. In 2020, the summer school holiday season began on June 22 in Mecklenburg-Vorpommern and ended September 9 in Baden-Württemberg. Hence, Germany spreads the holidays over almost 13 weeks see the .The average weekly incidence rate across all German districts over the entire sample period is 6.38 cases per 100 000 people with a standard deviation of 10.14. In Germany as a whole, the number of new infections had been stable at around 500 per day until the end of July. In August, the number of daily confirmed cases begun to rise reaching ~1500 new cases at the end of August and ~2000 new daily cases at the end of September.This upward trajectory in Germany coincides with the summer school holiday season. It is unlikely, however, that the return of rising incidence rates has been determined by school holidays alone. To isolate the predicted effects from other influences, we include a lagged dependent variable to account for the common trend in the data.,Most of our estimation models are based on a specification with a dummy variable that is set to 1 if a district is located in a state in which schools are on summer holidays in that week as well as a dummy variable for the 2-week period after the holidays. This specification can be interpreted as a Chow-type model,This relatively simple specification with two dummy variables only is handy for extensions where we allow their effect to vary by state and allow their effect to be conditioned by two district-level variables that are likely to impact on the number of holiday-related travels undertaken from each district (on which more below). It is not an optimal specification however given it presumes the effect to be constant within the holiday period. Empirical evidence suggests that the average length of holiday stay of German tourists is ~12–14 days.We estimate our models with a linear fixed effects estimator that absorbs any variation across districts that is time-invariant such as demographic, geographic and socio-economic factors that render some districts more generally exposed to the pandemic than others.In Model 1, which pools all holiday weeks together, masks that the effect is likely to vary and to increase over the holiday period. Model 2 is more appropriately specified as it allows the effect of the holiday season to vary week-by-week. We find that the effect increases in later weeks of the school holidays, consistent with our second hypothesis. The effect is close to zero in the first 2 weeks, rises from week three onwards, becomes statistically significant from week 4 onwards and increases to 4.15 cases per 100 000 people in week 6. The coefficients of the first and the second week after school holidays finish show that the increases in incidence rates brought about by the school holidays do not disappear but continue to rise to 5.13 cases per 100 000 people in the second week after school holidays end. In terms of substantive importance of this finding, an increase in the incidence rate of 4.15 cases in the final week of the holiday season equates to 44.7% of the average incidence rate across German districts during their sixth week of holidays, which is higher than the average incidence rate during the entire sample period and therefore represents the more appropriate benchmark against which the substantive effect size should be assessed so as not to overstate it. For the first and second week after holidays, the equivalent computation would suggest effects that equate to 46.0 and 45.3% of the average weekly incidence rate in those weeks.In model 3, reported in Overall, only two states in our sample do not show a statistically significant positive holiday effect: Brandenburg and North Rhine-Westphalia. Of these two cases, North Rhine-Westphalia appears to be an outlier. The state had high incidence rates before the holidays begun due to super-spreader events in a slaughterhouse of the Tönnies company in the districts of Gütersloh and Warendorf. If we drop the two districts of Gütersloh and Warendorf from the estimations then both coefficients of the holiday and post-holiday periods become statistically significantly positive for this state.Thuringia and Bavaria differ in many respects. Bayern is richer, more industrial, more urbanized, and it also hosts a larger share of foreign residents. In Model 4, reported in We have found that by the end of the holiday period the estimated effect equates to around 45% of the average incidence rate across German districts during their respective final week of holidays and their respective first 2 weeks after holidays end.The RKI reports that the maximum of new infections for which a country abroad is stated as the most likely place of infection during Germany’s holiday season is around 49% in week 35 in mid-August with close to 45% in the 2 weeks either side of this maximum.Based on a research design that captures the effect of holidaying both within and outside Germany, our central estimates are slightly lower than the maximum of new infections for which a country abroad is stated as the most likely place of infection in reports to the RKI. Despite very different research designs, the two approaches find similar substantive average effects. Disaggregating the effect week-by-week, we find that the effect increases over the holiday period and does not revert back to what it was from before the holiday period in the 2 weeks after holidays end. We have demonstrated effects differ across German states with statistically significant holiday effects in at least 12 of the 14 German states with more than one district in our dataset. The stronger effects take place in the Western German states. Two main hypothesized reasons for this heterogeneity across German states were that the states with a stronger effect consist of districts that tend to be both richer and have a larger share of foreign residents amongst their population, both of which spurs holiday-related travel. Corroborating this, we have shown that the higher is per capita income and the higher the share of foreigners in a district, the larger the increases in the growth rate of infections.First, there are the well-known limitations of any ecological study like ours. Ideally, one would employ individual- rather than district-level data, however no such data exist and—due to privacy protection policies—cannot be collected. Second, we can only capture the effect of holiday-related travels triggered by public summer school holidays. Families with children of school-age in particular are dependent on school holidays for their holiday travel and the same holds for the employees of firms that close down for company holidays over that period. Thus, the majority of holiday travels will take place during school holidays. Yet, not all of holiday-related travel takes place during school holidays, which potentially biases downwards our estimate of the effect of holiday-related travels on Sars-CoV-2 infection.The impact that summer school holidays have had on incidence rates were entirely predictable and yet Germany’s public health authorities were not prepared for re-starting travel in the era of Covid-19.Article_for_Journal_of_Public_Health_supplementary_document_fdab080Click here for additional data file.


The present systematic review and meta-analysis of randomized clinical trials (RCTs) aimed to investigate the effects of pulmonary rehabilitation in individuals with chronic obstructive pulmonary disease (COPD).The RCTs of pulmonary rehabilitation programs published between 1999 and 2021 were retrieved from electronic databases . Two reviewers independently assessed the topical relevance and trial quality and extracted data for meta-analysis using the Stata software version 14.0.A total of 39 trials involving 2,397 participants with COPD were evaluated. We found that patients who received pulmonary rehabilitation program had significant improvement in the 6-min walk test (6MWT), St. George Respiratory Questionnaire score, and the modified British Medical Research Council score as compared to those who received usual care. Yoga and Tai Chi showed significant improvement in the forced expiratory volume (FEV1)% in 1 s predicted value. However, no significant difference was detected in the modified Borg score, forced vital capacity (FVC), and FEV1/FVC predicted value between the pulmonary rehabilitation and usual care groups.A total of 39 trials involving 2,397 participants with COPD were evaluated.We found that patients who received pulmonary rehabilitation program had significant improvement in the 6MWT, St. George Respiratory Questionnaire score, and the modified British Medical Research Council score as compared to those who received usual care.Yoga and Tai Chi showed significant improvement in the FEV1% predicted value.No significant difference was detected in the modified Borg score, FVC, and FEV1/FVC predicted value between the pulmonary rehabilitation and usual care groups.Yoga and Tai Chi showed a significant improvement in the FEV1% predicted value. Also, pulmonary rehabilitation program improved the exercise capacity, the quality of life, and dyspnoea in patients with COPD. Chronic obstructive pulmonary disease (COPD) is a common chronic disease characterized by persistent respiratory symptoms and airflow limitation . COPD isIn COPD therapy, pulmonary rehabilitation is regarded as the hallmark of treatment in all patients . TypicalThe main purpose of pulmonary rehabilitation training is to formulate a corresponding pulmonary rehabilitation plan according to the actual situation of the patient, thereby improving the patient’s quality of life and exercise endurance and the symptoms of dyspnoea . In addiSupplementary Table S1. No restrictions were applied to the language, and cross-references and reviews were assessed to gather all the eligible publications.The databases, including PubMed, Embase, and Cochrane Library, were queried using the keywords “chronic obstructive pulmonary disease/COPD”, “pulmonary rehabilitation”, “exercise training”, “Yoga”, “Tai Chi”, and “randomized controlled trial/RCT”. The search was updated until August 2021. The detailed search strategy is shown in Studies were included if the following criteria were fulfilled : includeAll available data were extracted independently by two researchers according to the inclusion criteria. Any differences were resolved through discussions with the third author. The following data were extracted from each article: first author’s name, year of publication, research design, country, gender, mean age, mean forced expiratory volume in one second (FEV1), sample size, follow-up time, and outcomes assessed. Also, we assessed the risk of bias using the Cochrane Collaboration tool for risk of bias assessment .I2 statistic . If the heterogeneity was significant, the random-effects model was adopted, otherwise fixed-effects model was adopted. The sequential removal of each study for sensitivity analysis was carried out to assess the relative impact of each study comprehensively. Egger’s linear regression test and Begg’s test are used to demonstrate the publication bias; if p < .05, we used the trim and fill method for corrections [The weighted mean difference (WMD) and 95% confidence interval (CI) were calculated for continuous data. Then, the data were combined according to random-effects (DerSimonian and Laird’s method) or fixed-effects model depending on the significance of the rections . The stavia manual search. The duplicates were excluded, and after screening the abstracts of the remaining articles, 59 full-text articles were obtained for further review  in the pulmonary rehabilitation group compared to the control group (The changes in the exercise capacity from baseline were measured using 6MWT in 34 studies. The 6MWT distance was significantly improved (weighted mean difference (WMD), 36.34; 95% confidence interval (CI): 26.51–46.17; ol group .p < .001; 2I= 78%)  .p < .001; 2I= 76.8%)  .p < .001; 2I= 76.4%) was detected between the pulmonary rehabilitation group and the control group   .p < .001; 2I= 82.8%) between the pulmonary rehabilitation group and the control group  was observed between the pulmonary rehabilitation and the control groups .Sensitivity analysis was performed to examine whether the removal of each study would cause a significant change in the overall trend. However, the results were not altered after the sequential removal of each study, suggesting the reliability and stability of the results in this meta-analysis , Tai Chi , and the conventional exercises  group   and Tai Chi groups   group . For the= 73.6%)  but not = 73.2%)  but nonep = 0.343; Egger’s test p = .63)   (Egger’s linear regression test and Begg’s test showed no publication bias for 6MWD (Begg’s test p = .63) , SGRQ (B = .389) , and FEV = .746) .A comprehensive search was performed for RCTs that evaluated the efficacy of pulmonary rehabilitation in patients with COPD, and finally, 39 trials involving 2,397 COPD patients met our inclusion criteria. This meta-analysis showed that Yoga and Tai Chi significantly improved the FEV1% predicted value. Patients who received the pulmonary rehabilitation program had a marked improvement in the exercise capacity, quality of life, and dyspnoea compared to those who received usual care. Our study verifies known effects of the traditional PR, but that Yoga and Tai Chi can have significant improvement and may have benefit in FEV1 which PR does not do.Pulmonary rehabilitation was first defined by the American College of Chest Physicians Committee in 1974. It is a proactive method that minimizes COPD symptoms, improves HRQOL, and increases physical and emotional participation in daily life ,58. In tThe efficacy of pulmonary rehabilitation in patients with COPD has been investigated by previous meta-analyses. To the best of our knowledge, this is the largest meta-analysis to investigate the efficacy of pulmonary rehabilitation in patients with COPD, encompassing 2,397 patients in 39 RCTs. Recently, Dong et al.  conductePulmonary rehabilitation is a healthy approach for patients with COPD. The main purpose of pulmonary rehabilitation training is to formulate a corresponding program according to the actual situation of the patient to improve the patient’s quality of life and exercise endurance and improve the symptoms of dyspnoea . In clinIn COPD Dyspnoea is one of the main respiratory symptoms. At present, several scales can be used to classify and characterize dyspnoea: clinical scale (such as MRC) and psychophysical scale  are the most commonly used scales in daily clinical practice . HoweverNevertheless, the present meta-analysis has some limitations. First, we did not look for unpublished literature, which is not in line with Cochrane’s method. Second, the heterogeneity of different types of pulmonary rehabilitation programs, their intensity, duration, and quality of learning were prepared for intervention. These factors are incommensurable in the majority of the experiments. Furthermore, the duration of treatment regimens was inconsistent in different studies. Also, although we have summarized the results of all trials, the sample size in the current review might not be sufficient to exclude any significant experimental errors. Finally, although a series of outcome measures are used, the impact of the smallest clinically significant difference based on each indicator may not be reflected.Despite the limitations, this meta-analysis confirmed that Yoga and Tai Chi have significantly improved the FEV1% predicted value. The pulmonary rehabilitation program improves the exercise capacity, the quality of life, and dyspnoea in patients with COPD. However, additional studies on large datasets and well-designed models are required to substantiate these findings.Click here for additional data file.


Resistance to oxaliplatin is a major obstacle for the management of locally advanced and metastatic colon cancer (CC). Although long noncoding RNAs (lncRNAs) play key roles in CC, the relationships between lncRNAs and resistance to oxaliplatin have been poorly understood yet.Chemo-sensitive and chemo-resistant organoids were established from colon cancer tissues of the oxaliplatin-sensitive or -resistant patients. Analysis of the patient cohort indicated that lnc-RP11-536 K7.3 had a potential oncogenic role in CC. Further, a series of functional in vitro and in vivo experiments were conducted to assess the effects of lnc-RP11-536 K7.3 on CC proliferation, glycolysis, and angiogenesis. RNA pull-down assay, luciferase reporter and fluorescent in situ hybridization assays were used to confirm the interactions between lnc-RP11-536 K7.3, SOX2 and their downstream target HIF-1α.In this study, we identified a novel lncRNA, lnc-RP11-536 K7.3, was associated with resistance to oxaliplatin and predicted a poor survival. Knockout of lnc-RP11-536 K7.3 inhibited the proliferation, glycolysis, and angiogenesis, whereas enhanced chemosensitivity in chemo-resistant organoids and CC cells both in vitro and in vivo. Furthermore, we found that lnc-RP11-536 K7.3 recruited SOX2 to transcriptionally activate USP7 mRNA expression. The accumulative USP7 resulted in deubiquitylation and stabilization of HIF-1α, thereby facilitating resistance to oxaliplatin.In conclusion, our findings indicated that lnc-RP11-536 K7.3 could promote proliferation, glycolysis, angiogenesis, and chemo-resistance in CC by SOX2/USP7/HIF-1α signaling axis. This revealed a new insight into how lncRNA could regulate chemosensitivity and provide a potential therapeutic target for reversing resistance to oxaliplatin in the management of CC.The online version contains supplementary material available at 10.1186/s13046-021-02143-x. Colon cancer (CC) is the fifth most common malignancy and the fifth leading cause of cancer-related mortality among 36 types of cancer worldwide . OxaliplLong non-coding RNAs (lncRNAs) are RNA molecules, which are longer than 200 nucleotides without a protein coding potential. Emerging evidence has indicated that lncRNAs play significant roles in multiple physiological and pathological processes by distinctive mechanisms , 11. NotTissue microarrays were collected from patients with CC who were admitted to Fudan University Shanghai Cancer Center  from 2007 to 2009. Clinical data are summarized in Supplementary Table SChemo-sensitive organoids in our study were collected from chemo-sensitive patients’ CC tissues in the first surgery. The chemo-resistant organoids were gained from CC patients, who underwent reoperation after failure of oxaliplatin-based chemotherapy. Then, the organoids were cultured as described below and drug-resistance testing was performed with oxaliplatin the treatment for 25 days.2 and 95% air at 37 °C, and medium was changed every 2 ~ 3 days. The splitting ratio was 1:3.After that, fresh tumor tissues were immediately cultured in advanced Dulbecco’s modified Eagle’s medium (DMEM)/F12 supplemented with 1% penicillin streptomycin. Tissues were diced into approximately 2–3-mm sections, and then, digested at 37 °C for 1 h by trypsin. The digested tissues were filtered through a 70-μm filter . The cell suspension was then spun at 1000 rpm for 5 min to create a cell pellet. The pellet was washed with red blood for 2–3 times. Cells in solid tumor were then mixed with growth factor reduced Matrigel , and cellular concentration was set to 10,000 ~ 20,000 cells/50 μL. Once the Matrigel was solidified, 500 μL of general (DMEM)/F12 culture medium was added. Patient-derived organoids (PDOs) were kept in a humidified atmosphere of 5% COt-test or one-way analysis of variance (ANOVA), followed by Tukey multiple comparison tests. Clinicopathological data were analyzed using SPSS 24.0 software . The Kaplan–Meier method and the log-rank test were employed to estimate OS. Variables with P-values < 0.05 in univariate analysis were included in subsequent multivariate analyses based on the Cox proportional-hazards model. A probability with value of less than 0.05 was considered statistically significant.Data were statistically analyzed by using GraphPad Prism software  and presented as mean ± SD. Comparisons between control and treatment groups were performed via the paired See online In order to investigate mechanisms of resistance to oxaliplatin through a model with a superior genetic and phenotypic recapitulation, chemo-resistant and -sensitive organoids derived from CC patients were established. Representative images of hematoxylin-eosin (HE) staining of oxaliplatin-resistant and -sensitive human CC tissues are shown in Fig. STo gain a deep insight into the molecular mechanism and dysregulated pathways of oxaliplatin resistance, genome-wide analysis of lncRNA expression was carried out in 3 oxaliplatin-resistant and 3 -sensitive organoids of CC patients. Circos plot was employed to display distribution and expression of lncRNAs on human chromosomes Fig. A. It wasUsing patient-derived organoids and drug-resistant tumor cell line models, we attempted to determine the influence of lnc-RP11-536 K7.3 on resistance to oxaliplatin in a robust manner. Oxaliplatin-resistant RKO (CR-RKO: Chemo-resistant RKO) CC cell line was established by treating cells with increasing concentrations of oxaliplatin. Compared with parental cells, CR-RKO cells responded poorly to oxaliplatin, as evidenced by an increased half maximal inhibitory concentration (IC50) value Fig. A. We theIn the current study, proteomic analysis of organoids revealed that glycolysis and angiogenesis were closely correlated with chemo-resistance . TherefoIn order to interrogate the activity and mechanism of lnc-RP11-536 K7.3, we performed high-throughput RNA sequencing on lnc-RP11-536 K7.3 knocked out organoids. It was noted that lncRNAs could influence the expressions of neighboring genes . As no nTo explore the underlying regulatory mechanism of lnc-RP11-536 K7.3 on the promoter activity of USP7, we conducted RNA pull-down assay and mass spectrometry analysis to search for the potential mediators binding to lnc-RP11-536 K7.3 using chemo-resistant CC organoids. The results indicated that lnc-RP11-536 K7.3 specifically pulled down SOX2 protein Fig. D. FurtheBy the analysis of RNA-Sequencing assay, we found that deubiquitinating enzyme USP7 was a potential target gene of SOX2. To confirm the exact region within the USP7 promoter that SOX2 binds, we performed ChIP assays and identified two SOX2 binding sites existed at approximately 900–1500 bp upstream of the open reading frame of USP7. Fig. G-I MutatTo further explore putative substrates of USP7, we generated HEK293T cells overexpressing HA-USP7 to perform immunoprecipitation (IP) and mass spectrometry analysis and found that HIF-1α was a potential USP7-interacting protein Fig. A. As expTo further evaluate the effects of lnc-RP11-536 K7.3 on tumorigenesis and chemo-resistance in vivo, lnc-RP11-536 K7.3 knocked out chemo-resistant CC organoids, CR-RKO cell lines, and control groups were then injected subcutaneously into nude mice .Additional file 2. Supplementary Methods.Additional file 3: Figure S1. Chemo-resistant and -sensitive organoids derived from CC patients. (A) Hematoxylin-eosin (HE) staining of oxaliplatin-resistant and -sensitive organoids of CC tissues . (B) Images of oxaliplatin-resistant and -sensitive organoids derived from CC patients with or without 1 uM oxaliplatin treatment for 21 days. (C) Cell viability assay of organoids treated with 1 uM oxaliplatin in different time intervals. (D) HE staining of oxaliplatin-resistant and -sensitive organoids of CC patients. (E) Immunohistochemistry of CK20 and β-catenin in oxaliplatin-resistant and -sensitive organoids of CC patients.Additional file 4: Figure S2. Immunohistochemistry staining of human colon cancer markers and the survival analysis of lnc-RP11-536 K7.3 in different cancer patients. (A) Immunohistochemistry staining of CK20 and β-catenin in oxaliplatin-resistant and -sensitive human colon cancer tissues. (B) Survival analysis of lnc-RP11-536 K7.3 in different cancer patients in TCGA database. (C) The expression of lnc-RP11-536 K7.3 in cancer tissues and the adjacent sites in TCGA database.Additional file 5: Figure S3. Overexpressing lnc-RP11-536 K7.3 in the depleted cells/organoids restores glycolysis and angiogenesis. (A-D) Determination of glucose uptake (A), ATP (B), NADPH (C), and lactate production (D) in CC organoids and cells as indicated. Data were presented as mean ± SD of triplicate measurements repeated three times with similar results. Statistical significance was assessed via the Student’s t-test (**P < 0.01). (E-F) Measurement of ECAR (E) and OCR (F) in CC organoids and cells as indicated. (G) Statistical analysis of tube formation in different groups (**P < 0.01).Additional file 6: Figure S4. Effect of lnc-RP11-536 K7.3 knockout, SOX2 overexpression on oxaliplatin-sensitivity, glycolysis and angiogenesis in chemo-resistant colon cancer organoids and cells. (A) Cell viability assay of chemo-resistant colon cancer organoids treated with 1uM oxaliplatin in different time intervals. (B) Values of IC50 of oxaliplatin. Colon cancer cells were treated with different. Concentration of oxaliplatin for 48 h. (C) Relative colony formation efficiency of chemo-resistant colon cancer organoids and cells treated with or without 2uM oxaliplatin for 7 days. (D) Determination of glucose uptake, ATP, NADPH and lactate production as described in Methods. Data are means ± SD of triplicate measurements repeated 3 times with similar results. Statistical significance was assessed with two-tailed Student’s t test. (E-F) ECAR (E) and OCR (F) were determined as described in Methods.Additional file 7: Figure S5. Immunofluorescence assay of nude mice transplanted tumor tissues. (A) Immunofluorescence assay indicated the association between SOX2 and USP7 in nude mice transplanted tumor tissues. (B) Immunofluorescence assay indicated the association between SOX2 and CD31 in nude mice transplanted tumor tissues.Additional file 8: Figure S6. Immunofluorescence assay of human colon tissues. (A) Immunofluorescence assay indicated the association between SOX2 and USP7 in lnc-RP11-536 K7.3 high expressed chemoresistant colon cancer tissues and lnc-RP11-536 K7.3 low expressed chemosensitive colon cancer samples. (B) Immunofluorescence assay indicated the association between SOX2 and HIF-1α in lnc-RP11-536 K7.3 high expressed chemoresistant colon cancer tissues and lnc-RP11-536 K7.3 low expressed chemosensitive colon cancer samples. (C) Immunofluorescence assay indicated the association between SOX2 and CD31 in lnc-RP11-536 K7.3 high expressed chemoresistant colon cancer tissues and lnc-RP11-536 K7.3 low expressed chemosensitive colon cancer samples. (D) Immunofluorescence assay indicated the association between USP7 and CD31 in lnc-RP11-536 K7.3 high expressed chemoresistant colon cancer tissues and lnc-RP11-536 K7.3 low expressed chemosensitive colon cancer samples.


EG00229, for which the inhibition of the CendR peptide binding to NRP1 was also experimentally confirmed. These compounds present a good starting point for the design of small-molecule antagonists against the SARS-CoV-2 viral entry.Furin cleavage of the SARS-CoV-2 spike protein results in a polybasic terminal sequence termed the C-end rule (CendR), which is responsible for the binding to neuropilin 1 (NRP1), enhancing viral infectivity and entry into the cell. Here we report the identification of 20 small-molecule inhibitors that emerged from a virtual screening of nearly 950,000 drug-like compounds that bind with high probability to the CendR-binding pocket of NRP1. In a spike NRP1 binding assay, two of these compounds displayed a stronger inhibition of spike protein binding to NRP1 than the known NRP1 antagonist  Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the coronavirus-induced disease 2019 (COVID-19) , it is cSARS-CoV-2 primarily utilises angiotensin-converting enzyme 2 (ACE-2) to mediate cell uptake , but altThere exist two very similar isoforms, NRP1 and NRP2, which share 44% amino acid sequence identity and exhibit a similar structural domain organisation consisting of N-terminal extracellular domains, a single transmembrane domain, and a small intracellular C-terminal domain . The ind164-NRP1 and SARS-CoV-2-NRP1   × 100. The screening was performed at a potential antagonist concentration of 100 μM. The VEGF-A antagonist EG00229 (21) [22 [The selected compounds were obtained from MolPort Inc.   and comp16 and 17 displayed more than 60% inhibition and were more active than the EG00229 control (compound 21), a known antagonist that prevents VEGF-A binding to NRP1 and has also been shown to block spike protein binding to NRP1. These results represent starting hit compounds suitable for additional in vitro and cell-based biological evaluations, with the ultimate goal of discovering and optimizing small-molecule inhibitors of SARS-CoV-2 spike-NRP1 binding with in vivo activity. As the COVID-19 pandemic seems to be far from over, novel medicinal chemistry approaches and the design of new drugs or biochemical probes are urgently needed.In the present work, we identified novel small-molecule inhibitors of spike S1 protein binding to NRP1 that could weaken SARS-CoV-2 infectivity. Compounds


Action research (AR) is an established research framework to introduce change in a community following a cyclical approach and involving stakeholders as coresearchers in the process. In recent years, it has also been used for eHealth development. However, little is known about the best practices and lessons learned from using AR for eHealth development.This literature review aims to provide more knowledge on the best practices and lessons learned from eHealth AR studies. Additionally, an overview of the context in which AR eHealth studies take place is given.A semisystematic review of 44 papers reporting on 40 different AR projects was conducted to identify the best practices and lessons learned in the research studies while accounting for the particular contextual setting and used AR approach.Recommendations include paying attention to the training of stakeholders’ academic skills, as well as the various roles and tasks of action researchers. The studies also highlight the need for constant reflection and accessible dissemination suiting the target group.This literature review identified room for improvements regarding communicating and specifying the particular AR definition and applied approach. The way health care is organized and executed is of great societal concern, as it affects our quality of life. Hence, health care systems and eHealth technologies used to support health care should be designed in a way that meets the needs and expectations of their stakeholders. One way of doing this is through action research (AR). According to Bradbury and Lifvergren , AR in heHealth projects cover a wide variety of topics and technologies and can therefore greatly benefit patients, professionals, and many other health care stakeholders. However, to gain the most from eHealth systems and technologies, it is crucial that they match with what is needed in practice . To ensu.Definitions of AR have changed over the years. AR originated with Kurt Lewin , who desWithin AR, different variations exist, such as action design research (ADR) or participatory action research (PAR). Usually, there is agreement on the main principles of AR explained earlier, but some authors or groups emphasize some aspects over others. For example, as the name suggests, ADR incorporates elements of design research into AR , whereasIn general, AR and AR approaches such as ADR are similar to participatory design (PD) approaches that are used in human computer interaction (HCI) research. However, AR emphasizes reflection on and learning from the process that was carried out, whereas the main aim of PD is to create a solution . AR, as What is the context of AR eHealth projects?How do eHealth AR studies define and operationalize AR?What are the best practices for conducting AR in concrete eHealth studies?What are the lessons learned from conducting AR in concrete eHealth studies?The search was carried out in June 2020. PubMed, Scopus, and Google Scholar were searched using combinations of the search terms “action research” or “participatory design” and “eHealth,” “health technology,” “digital health,” or “telemedicine.” PubMed was chosen for its extensive medical database, and Scopus and Google Scholar were chosen as large scientific databases. Searching for “action research” turns up articles that include similar and related keywords like “participatory action research,” “action design research,” or “action-based research.” “Participatory design” was included as a search term because PD has significant overlap with AR, and both are sometimes used to supplement each other. The list of synonyms for “eHealth,” although not exhaustive, is expected to cover the various facets of the field. The initial search yielded 739 results. Articles were included if they (1) used and explicitly mentioned AR and (2) were about eHealth or health technology. Papers were excluded if they (1) were not written in English, (2) only included a study protocol but did not report results, or (3) only included a review of other articles. Full-text screening of the same 15 articles was performed by 2 authors (KO and CG); the authors discussed whether to include the studies until an agreement was reached. Next, the first author screened the full texts of the remaining articles, with some exceptions where a second opinion was necessary. These were again discussed between the first and second authors until an agreement was reached. Ultimately, 44 articles were included, reporting on 40 different projects. For each study, the definition of AR that was provided by the authors, and the related AR approaches that they cited (if any) were extracted. Additionally, information about contextual variables of the study was derived. Specifically, we identified the topic, country, organizational context, project duration, types of stakeholders involved, the main target group of the research, and methods used. The types of involved stakeholders were grouped according to the framework described by Schiller et al , in whicA general overview of all the included studies describing the AR approach, AR definition, and contextual variables was obtained. The contextual variables  were categorized. Furthermore, the studies were mapped in a matrix based on the study duration and the types and number of different stakeholders that participated in the study. The contextual data were coded and categorized inductively. To identify which AR approach was the most used, the citation frequency of each approach in the included studies was recorded. Furthermore, the cited AR approaches that were available were accessed and checked for cross-referencing. All cited AR definitions were mapped to show the relationship between them. The AR definitions used, best practices, and lessons learned were coded by 1 author (KO). The best practices and lessons learned were coded individually first and then combined for both categories.The setting of the included studies was described based on 6 categories . We identified 9 broader categories of the research topics in the 44 included studies  followed by the United States (n=4) and Canada, Sweden, and the United Kingdom . Some studies from nonwestern countries, like Tanzania or Colombia were included, but no country was represented more than once or twice. Within the different countries, studies took place in various contexts, the most prevalent of which were rural areas (n=6) and hospitals (n=5). All contexts and countries can be found in Tables 2.2 and 2.3 of Among the 44 studies, 2 studies explicitly focused on 2 different target groups at the same time, whereas all other studies had 1 main target group. In most cases, the target groups were patients (n=11). Of these, the most common group was patients with cancer (n=3). There were 6 studies each focusing on clinicians as well as children and young adults, and 5 studies targeted older adults . Studies that did report the duration (n=33) lasted from a few months (n=5) to more than 10 years (n=2). The majority (n=13) of these studies reported a project duration between 2 and 3 years, and the average project duration was 2.7 years. In . Interviews were used most frequently (n=24), followed by focus groups (n=22), workshops (n=14), and surveys (n=13). On average, studies used nearly 3 different methods (average 2.8). All methods can be found in Table 2.6 of As mentioned earlier, AR is a framework that does not advise the use of a single methodology, and studies can therefore include a variety of different research methods. Most of the 44 included studies indeed used several methods, with some studies employing up to 6 different methodsThe articles contained 44 definitions of AR. They could be grouped according to 4 different aspects that they emphasized. First, 21 studies emphasized that in AR projects, practitioners and other stakeholders become (co)researchers (n=21). Second, AR is a cyclical process that includes different stages (n=19). Third, 14 studies described how AR focuses on solving a practical issue and aims to extend research knowledge. The fourth aspect was that AR takes place in a community setting (n=10). Further, 2 studies included 3 of these aspects in their definitions, and only 2 other studies mentioned all 4 aspects. Most studies included either 1 (n=16) or 2 (n=17) of the aspects, whereas 7 studies included none of these points in their definition or did not at define AR in detail. As previously described, an activity was identified as a “best practice” if researchers already planned their project with this in mind . Lessons learned were those points that researchers came to know during their project. These were mostly reported in the discussion section. In total, 85 best practices and 66 lessons learned were identified, which were clustered into 22 categories of best practices and 16 categories of lessons learned. Among the 44 papers, 3 papers did not indicate any best practices that they followed, whereas 12 papers did not include any identifiable lessons learned. There were 8 overlapping categories, identified as best practices in some articles and as lessons learned in others. These will be discussed in more detail below.The identified best practices in the 44 studies were most often related to the use of a specific method (n=9), namely personas (n=2), world café, journey mapping, role play, scenarios, case studies, design cards, and mixing different types of data collection methods . Other best practices were a continuous evaluation of the project and a reflection on the process by the research team (n=8). The importance of establishing active contact between researchers and stakeholders and raising the confidence and skills of stakeholders was emphasized by 7 studies. The improvement of stakeholder skills mainly referred to research and analytical skills, allowing stakeholders to set up their own studies or continue the work after the project was finished. There were several specific suggestions to improve the regular project team meetings, for example, to always use the same agenda or to share a common area (office space) to make contact easier. Some other best practices concern the reporting and presentation of outcomes (n=6). The complete list of best practice categories can be found in Apart from the best practices, the lessons learned from each study were identified. The most common lessons learned were increasing stakeholder knowledge and skills (n=8) and continuous evaluation of the project and reflection on the process (n=6). Both of these had been identified as best practices in other articles (more on this overlap below). Recommendations for the use of specific methods were also common (n=5). Lessons learned regarding reporting, adapting the project to fit the needs of stakeholders, fostering a welcoming environment, and the questionable replicability of the research were each mentioned 4 times. All lessons learned are shown in As stated earlier, some aspects were identified as best practices in some articles and as lessons learned in others. In total, we identified 7 such overlapping aspects. Overall, the most mentioned aspect was the importance of raising stakeholder skills and confidence . Many articles reported the need for stakeholders to learn new skills, for example related to academic research, or the need to be convinced about their ability to perform these tasks. Almost all the studies that reported this as a best practice or lesson learned involved health care professionals as stakeholders. Other commonly mentioned points were recommendations for specific methods, even though the suggested methods differed  and there was continuous reframing and evaluation of the project . Continuous reframing often referred to the iterations of planning, action, and evaluation in AR projects. Studies that described this mostly did not include this cyclical nature of AR in their definition of it. In total, there were 10 recommendations regarding the reporting and presentation of results (best practices=6 and lessons learned=4), for example calling for open and accessible publishing of outcomes. The best practices and lessons learned included recommendations about meeting regularly , adapting to the needs of stakeholders , and investing in the relationship between partners .When observing the publication timeline, most of the overlapping aspects appeared as a lesson learned in earlier publications, and then as a best practice in papers published at a later point in time. This was the case regarding stakeholder skills, appearing as a lesson learned in 1999  and as aTo identify recommendations on how to conduct AR in eHealth studies, this literature review analyzed the setting, AR description, and best practices and lessons learned in 44 studies. The most important recommendations from this review, which will be discussed in more detail below, are as follows: actively raising stakeholder skills and confidence; fulfilling multiple roles and tasks as a researcher; fostering constant reflection and evaluation; ensuring open and accessible dissemination; reporting in a more structured and comprehensive way.These recommendations are not exclusively related to eHealth, despite them being derived from a review of eHealth AR studies. Hence, it is possible that the recommendations are also relevant for AR in various other fields. Therefore, where possible, examples from different disciplines are discussed below to explain or supplement a recommendation.Being involved in a project as coresearcher can potentially increase stakeholders’ confidence, besides teaching them new skills . HoweverDifferent aspects of the role and tasks of the researcher in an AR project are discussed. Brydon-Miller and Aragón describe the many different tasks that action researchers need to fulfil as their “500 hats” . These aThe importance of continuous reframing and evaluation of the project was emphasized in several studies. Although evaluation is 1 of the AR cycles, studies providing recommendations on this topic rarely included this in their definition of AR. Owing to the lack of reports on AR cycles, which will be discussed below, it is unclear if these studies still followed the AR cycles without reporting on them. However, sometimes, it seems that periodic planned evaluation is not enough. Instead, the participants need to regularly reflect on the current status of the project and their role in it. Therefore, new AR projects should create suitable spaces for evaluation and reflection in ways that fit the projects and stakeholders. This is especially important because reflection can become difficult once a person is in the middle of the project . HolemanAnother important aspect concerns paying attention to open and understandable dissemination of results within the community and among researchers. Action researchers need to communicate findings to the academic world while also finding ways to inform the target group about the project in ways that suit the target users’ needs. An example of open and accessible dissemination can be found in Canto-Farachala and Larrea . They prThe different way of describing AR studies also leads to another issue, incomplete and elusive reporting. Although most studies did provide at least a short description of what they saw as AR, 7 studies provided no definition at all. Additionally, there were only 4 studies that included 3 or all of the 4 aspects of the AR definition in their description. Even the most mentioned aspects appeared in less than half of the included papers. Even though most papers did cite an AR approach of definition, some did not. In combination with the often-limited descriptions of AR, this makes it difficult to obtain a clear picture of how AR is perceived and performed in a particular study. This resonates with what Bradbury and colleagues  describeApproximately a third of the included papers (14 out of 44) were published more than 10 years ago. This also means that some of the technologies that are described in the older papers are now relatively old. However, this literature review focuses mainly on the AR methodology and lessons learned about doing action research. Therefore, there was no exclusion criterium regarding the publication date of the papers.The search yielded several PD-related papers. These papers could have been included, given that some definitions of PD are very similar to AR. However, as our aim was to provide an overview of how AR is done, these were excluded as the researchers of these studies themselves did not identify their studies as being related to AR . Although this offers a clearer picture of how researchers conduct AR, it also creates a potential limitation in that best practices and lessons learned could be enriched from PD literature.This overview of AR approaches focuses mostly on the interconnectedness among the approaches, without a comprehensive comparison of the content. Comparing the approaches with regard to the specific aspects of AR that they describe would be a review in and of itself, going beyond the scope of this current review. Therefore, we decided to focus on the definitions that the authors themselves provided even when they also cited AR approaches, as these are most likely to reflect their own vision of AR.This review illustrates how AR is conducted in eHealth studies. Studies that fulfilled the inclusion criteria mainly took place in western countries and lasted for 2 to 3 years. Different stakeholders were involved, but the most commonly involved groups were health care professionals and patients. As for the methods used, most studies opted for focus groups and interviews. Even though many studies cited the AR approach proposed by Reason and Bradbury , their o


TR-1 to TR-9) have been synthesised via the diazo-coupling approach between substituted aromatic amines with phenol or naphthol derivatives. The compounds were evaluated for their therapeutic applications against alpha-glucosidase (anti-diabetic) and pathogenic bacterial strains E. coli (gram-negative), S. aureus (gram-positive), S. aureus (gram-positive) drug-resistant strain, P. aeruginosa (gram-negative), P. aeruginosa (gram-negative) drug-resistant strain and P. vulgaris (gram-negative). The IC50 (µg/mL) of TR-1 was found to be most effective (15.70 ± 1.3 µg/mL) compared to the reference drug acarbose (21.59 ± 1.5 µg/mL), hence, it was further selected for the kinetic studies in order to illustrate the mechanism of inhibition. The enzyme inhibitory kinetics and mode of binding for the most active inhibitor (TR-1) was performed which showed that the compound is a non-competitive inhibitor and effectively inhibits the target enzyme by binding to its binuclear active site reversibly.In the present study, a series of azo derivatives ( Debnath et al. evaluated the antimicrobial efficacy of triorganotin(IV) azo-carboxylatesS. aureus) and the fungus (F. oxysporum) with significant antimicrobial properties compared to the standard antibiotics. Similarly, Ispir and colleagues examined the anti-oxidant and anti-proliferative potential of azo-azomethine ligands and their metal complexes with Zn(II), Co(II) and Cu(II)Aromatic azo compounds have been extensively studied in recent years due to their broad-spectrum pharmaceutical applicability mainly because of their cost-effective, simplistic and reproducible synthetic procedure. The combination of aromatic substituted amines with coupling agents could yield a variety of azo compounds having versatile biological properties50 5.69 ± 0.5 µM) with the competitive mode of inhibition50 range 20.44 − 333.41 µM) were evaluated as good candidates for targeting α-glucosidase enzyme50 value 36.11 μg/mL)50 range 2.21 ± 0.06 − 9.97 ± 0.08 μM)Diabetes Mellitus (DM) is a well characterised metabolic disease that results in defects in insulin output i.e. insulin secretion (type-1 diabetes) and insulin action (type-2 diabetes) or both. Type-2 diabetes accounts for 70–80% of all diabetic patients worldwide and it leads to postprandial hyperglycaemia. One of the critical strategies to prevent postprandial hyperglycaemia is to inhibit the enzymes which are responsible for the carbohydrate hydrolysis e.g. α-amylase and α-glucosidase. In this interest, several α-glucosidase inhibitors are being administered in the treatment of type-2 diabetes such as acarbose , voglibose  and miglitol (desoxynojirimycin). However, the prolonged use of these agents could result in various side effects such as vomiting, pomposity, diarrhoea and flatulence. Therefore, the discovery and development of new and potent α-glucosidase inhibitors have gained immense attention in pharmaceutical chemistry,2-adrenergic receptor agonists, antiseptic and antimicrobial agents respectively,in vitro against six clinical bacterial strains including the drug-resistant P. aeruginosa. It was revealed from the experimental data that some of the azo-phenol compounds significantly inhibited the growth of drug-resistant bacteria compared to the standard drug trimethoprim-sulfamethoxazoleN-monosubstituted carbamates have proven to be effective anti-mycobacterial drug targets against broad-spectrum mycobacterial strains Phenolic compounds are simple and naturally occurring organic compounds bearing an aromatic ring with one or more hydroxyl groups (with or without side chain), received considerable attention due to their biological functions such as anti-carcinogen, antimicrobial, anti-ageing, anti-diabetic, anti-mutagen and immunostimulatory roles50 values ranging from 122–341 µg/mL. The promising anti-inflammatory (89% after 4 h of treatment) and radical scavenging potential (IC50 54.12 µg/mL) highlighted the multifunctional role of hydroxytriazenes. It was also concluded that the polar functionalities like –OH around the heterocyclic rings of triazene compounds enhanced the inhibition potential against glucosidase and amylaseHydroxytriazenes are a class of compounds containing alpha hydroxyl group relative to the diazo group, have versatile pharmacological properties including lipid-lowering, antidiabetic, antioxidant, anti-inflammatory, antimicrobial and analgesic agents. In view of this, an attempt has been made to study the anti-diabetic, anti-inflammatory and antioxidant effects of sulpha drugs based hydroxytriazenesin vitro biological assays with kinetic and in silico structure-activity relationship studies.Keeping in view the synthetic feasibility of azo derivatives and diverse therapeutic properties of phenolic compounds fused with azo moiety, the present study aims at the synthesis, spectroscopic characterisation, biological evaluation, kinetic and molecular docking studies of diaryl azo-phenol derivatives. The structural identification of the synthesised azo-phenol derivatives was done by spectroscopic techniques  and the detailed screening was carried out by various 2.2.1.2.1.1.1H and 13C) were recorded in DMSO-d6 using Varian spectrometer 400 MHz. The high-resolution accurate-mass (HRAM) detection was performed on the Thermo Scientific Q Exactive apparatus. ELISA reader (BioTek) Epoch 2 by Agilent technologies, USA.All solvents and chemicals were of analytical grade and purchased from Sigma-Aldrich and Merck. Melting points were adjusted using a calibrated thermometer by digital melting point apparatus  and stated in degrees centigrade (°C). Pre-coated silica TLC plates  for determining purification, magnetic stirrer (VELP Scientific England) for stirring and micropipettes (ZX58143 and ZX57677) for quantitative transfer of liquid were used. The NMR spectra  were mixed with the cold aqueous solution of sodium nitrite (10 mmol) in a 100 mL round bottom flask at 0–5 °C. To this reaction mixture, 3 M HCl was added drop-wise with continuous stirring for 20 min until the formation of the diazonium salt at the same temperature. Then immediately, the cold basic solution of respective phenol derivatives  (10 mmol) was slowly added to the diazonium salt mixture and the stirring was continued for another 3 h at 0–5 °C. TLC was employed to monitor the progress of the reaction by the combination of various solvent systems. Once the reaction is completed, the resulting crude azo derivatives were filtered off, washed several times with deionised water, air-dried and purified by recrystallization.The general procedure for the synthesis of asymmetric aromatic azo compounds followed the traditional approach i.e. the coupling of aryl diazonium salts with electron-rich aromatics such as resorcinol and naphthol derivatives2.1.2.1.Rf: 0.78 ; 1H-NMR  δ: 6.37 , 6.51 , 7.69 , 8.05 , 8.36 , 10.87 , 12.12 ; 13C-NMR  δ: 103.10 (Ar-C), 110.17 (Ar-C), 122.48 (Ar-C), 125.04 (Ar-C), 133.35 (Ar-C), 147.12 (C), 154.64 (C), 158.73 (C), 164.93 (C); IR : 3441.43 , 1627.41 (C=C), 1514.81 (N=N), 1336.05 (C–N). HR–MS  Calcd. For C12H9N3O4 [M + H] 260.06658. Found [M + H] 260.06653.Orange crystals, yield 83%, melting point: 200–204 °C; 2.1.2.2.Rf: 0.82 ; 1H-NMR  δ: 6.72 , 7.50 , 7.61 , 7.72 , 7.93–7.98 , 8.32 , 8.42 , 15.68 ; 13C-NMR  δ: 117.28 (Ar-C), 122.30 (Ar-C), 125.65 (Ar-C), 126.24 (Ar-C), 127.71 (Ar-C), 128.49 (Ar-C), 129.50 (Ar-C), 129.89 (Ar-C), 131.19 (Ar-C), 132.49 (Ar-C), 143.63 (Ar-C), 143.93 (C), 179.28 (C); IR : 3437.49 , 1624.21 (C=C), 1507.92 (N=N), 1402 (C–N). HR–MS  Calcd. For C16H11N3O3 [M + H] 294.08732. Found [M + H] 294.08729.Red crystals, yield 55%, melting point: 260–265 °C2.1.2.3.Rf: 0.86 ; 1H-NMR  δ: 6.72 , 7.50 , 7.61 , 7.72 , 7.93–7.98 , 8.32 , 8.43  15.69 ; 13C-NMR  δ: 117.29 (Ar-CH), 122.30 (Ar-C), 125.66 (Ar-C), 126.24 (Ar-C), 127.72 (Ar-C), 128.49 (Ar-C), 129.50 (Ar-C), 129.90 (Ar-C), 131.19 (Ar-C), 132.58 (Ar-C), 143.63 (Ar-C), 143.94 (C), 148.01 (C), 179.28 (C); IR : 3432.58 , 1600.21 (C=C), 1507.41 (N=N), 1207.01 (C–N). HRMS  Calcd. for C16H11N3O3 [M + H] 294.08732. Found [M + H] 294.08736.Red crystals, yield 78%, melting point: 245–252 °C2.1.2.4.Rf: 0.77 ; 1H-NMR  δ: 2.38 , 7.01 , 7.37 , 7.46 , 7.82 , 7.97 , 15.60 ; 13C-NMR  δ: 20.89 (–CH), 119.69 (Ar-C), 121.23 (Ar-C), 122.94 (Ar-C), 125.47 (Ar-C), 127.10 (Ar-C), 128.77 (Ar-C), 128.87 (Ar-C), 130.33 (Ar-C), 132.93 (Ar-C), 138.14 (Ar-C), 138.90 (Ar-C), 147.13 (Ar-C), 164.14 (C–OH); IR : 3441.80 (OH), 1625.00 (C=C), 1511.02 (N=N), 1280 (C–N). HRMS  Calcd. For C17H14N2O [M + H] 263.11789. Found [M + H] 263.11796.Red crystals, yield 60%; melting point: 99–100 °C; 2.1.2.5.Rf: 0.73 ; 1H-NMR  δ: 2.38 , 7.01 , 7.37 , 7.47 , 7.62 , 7.82 , 7.97 , 8.60 , 15.60 ; 13C-NMR  δ: 20.89 (–CH), 119.69 (Ar-C), 121.23 (Ar-C), 122.94 (Ar-C), 125.47 (Ar-C), 127.82 (Ar-C), 128.77 (Ar-C), 128.87 (Ar-C), 130.33 (Ar-C), 132.64 (Ar-C), 138.67 (Ar-C), 138.90 (Ar-C), 144.13 (Ar-C), 164.69 (C-OH); IR : 3391.78 , 1629.61 (C=C), 1463.84 (N=N), 1281 (C–N). HRMS  Calcd. For C17H14N2O [M + H] 263.11789. Found [M + H] 263.11780.Orange-red crystals, yield 46%, melting point: 110 °C2.1.2.6.Rf: 0.8 ; 1H-NMR  δ: 2.38 , 6.34 , 6.49 , 7.34 , 7.66 , 7.75 , 10.50 , 12.44 ; 13C-NMR  δ: 20.96 (–CH), 102.97 (Ar-C), 108.94 (Ar-C), 121.64 (Ar-C), 129.96 (Ar-C), 130.04 (Ar-C), 132.08 (Ar-C), 140.24 (Ar-C), 148.63 (Ar-C), 156.07 (C), 162.64 (C); IR : 3476.11 , 1627.19 (C–C=C), 1458.76 (N=N). HRMS  Calcd. For C13H12N2O2 [M + H] 229.09715. Found [M + H] 229.09710.Reddish orange crystals, yield 60%, melting point: 98 °C; 2.1.2.7.Rf ; 0.80; 1H-NMR  δ: 6.38 , 6.56 , 7.58 , 7.73 , 8.25 , 8.47 , 10.94 , 12.61 ; 13C-NMR  δ: 103.00 (Ar-C), 110.15 (Ar-C), 124.41 (Ar-C), 126.05 (Ar-C), 130.57 (Ar-C), 133.46 (Ar-C), 142.85 (C), 148.07 (C), 150.19 (C), 157.46 (C), 164.76 (C); IR : 3403.94 , 1635.34 (C–C), 1575.56 (N=N), 1407 (C–N). HRMS  Calcd. For C11H8ClN3O2 [M + H] 250.03778. Found [M + H] 250.03790.Orange-brown crystals, yield 98%; melting point: 187–189 °C; 2.1.2.8.Rf = 0.81 ; 1H-NMR  δ: 6.78 , 7.47 , 7.56–7.60 , 7.71 , 7.95 , 8.30 , 8.47 ; 13 C-NMR  δ: 122.11 (Ar-C), 124.84 (Ar-C), 125.14 (Ar-C), 125.24 (Ar-C), 127.29 (Ar-C), 128.29 (Ar-C), 129.34 (Ar-C), 129.73 (Ar-C), 131.58 (Ar-C), 132.31 (Ar-C), 137.16 (Ar-C), 139.87 (Ar-C), 142.81 (C), 146.46 (C), 175.47 (C); IR : 3301.93 , 1631.42 (C=C), 1513.94 (N=N), 1332 (C–N). HRMS  Calcd. For C15H10ClN3O [M + H] 284.05852. Found [M + H] 284.05845.Orange crystals, yield 71%, melting point: 170–175 °C; 2.1.2.9.Rf: 0.75 ; 1H-NMR  δ: 6.79 , 7.47 , 7.57–7.60 , 7.72 , 7.95 , 8.30 , 8.48 ; 13C-NMR  δ: 122.14 (Ar-C), 124.87 (Ar-C), 125.17 (Ar-C), 125.27 (Ar-C), 127.33 (Ar-C), 128.31 (Ar-C), 129.38 (Ar-C), 129.78 (Ar-C), 131.61 (Ar-C), 132.33 (Ar-C), 137.19 (Ar-C), 139.89 (Ar-C), 142.85 (C), 146.50 (C), 175.51 (C); IR : 3475 (OH), 1626 (C=C), 1456 (N=N), 1208 (C–N). HRMS  Calcd. for C15H10ClN3O [M + H] 284.05852. Found [M + H] 284.05862.Reddish orange crystals, yield 70%; melting point: 180–182 °C; 2.2.Saccharomyces Cerevisiae (0.2 U/mL) was prepared in 0.05 M sodium phosphate buffer pH 6.8. In microtitre plate, 70 µL of phosphate buffer, 10 µL of enzyme and 10 µL of varying concentrations of azo derivatives  were mixed and incubated at 37 °C for 15 min. After incubation, 10 µL of the substrate, p-nitrophenyl α-D-glucopyranoside  was added to the aboveprepared mixture and incubated again under the same experimental conditions. The reaction was stopped with the addition of 0.1 M Na2CO3 and OD405 was taken by a 96-well ELISA reader. The experiment was performed in triplicate. Acarbose was used as positive control while DMSO was a negative control. The extent of inhibition showed by the tested azo derivatives was calculated by % inhibition formula and IC50 (µg/mL) was determined by Graph pad Prism 6.0.The α-glucosidase inhibition assay was performed as described previously2.3.,V) versus the inverse of substrate concentration 1/[S] mM−1, and the inhibition constant Ki was determined by two ways (Dixon plot of 1/V versus inhibitor concentrations) as well as secondary replot of slope versus inhibitor concentrations from Lineweaver–Burk plot.A series of kinetic assays was performed to determine the inhibition kinetics of the most active inhibitor from the series of tested compounds by following method2.4.The inhibitory mechanism against α-glucosidase by most active inhibitor from the tested series of azo derivatives was investigated. The plot of the remaining enzyme activity versus the concentrations of the enzyme at different inhibitor concentrations  was calculated.2.5.2.5.1.http://www.rcsb.org/4j5t). The retrieved protein structure was minimised by using the conjugate gradient algorithm and amber force field in UCSF Chimaera 1.10.1The crystal structure of α-glucosidase having PDBID: 4J5T was accessed from the Protein Data Bank (PDB) (2.5.2.TR1-9) were sketched in drawing ACD/ChemSketch tool and retrieved in PDB format. Furthermore, the UCSF Chimaera 1.10.1 tool was employed to energy minimisation of each drug separately having default parameters such as steepest descent steps 100 with step size 0.02 (Å), conjugate gradient steps 100 with step size 0.02 (Å) and update interval was fixed at 10. Finally, Gasteiger charges were added using Dock Prep in drugs to obtain a good structural conformation for docking analysis. A molecular docking experiment was employed on synthesised ligands against α-glucosidase by using PyRx virtual screening tool with AutoDock VINA Wizard approach X= −19.2552, Y= −21.0275 and Z = 4.2779, respectively. We have adjusted sufficient grid box size big enough on biding pocket residues to allow the ligand to move freely in the search space. The default exhaustiveness value = 8 was adjusted in both dockings to maximise the binding conformational analysis. In all docked complexes, the drug’s conformational poses were keenly observed to obtain the best docking results. The docked complexes were evaluated on the lowest binding energy  values and structure-activity relationship analyses. The graphical depictions of all the docking complexes were carried out using Discovery Studio (2.1.0).The designed ligands ) and gram-negative , P. vulgaris). All the strains were confirmed by biochemical identification and drug susceptibility methods. The antibacterial evaluation was done by agar disc diffusion method,600, of the above-mentioned bacterial strains was spread on the solidified trypticase soy agar media and Whatman no. 1 filter paper discs (5 mm in diameter) soaked with the title compounds (10 µL/disc of 10 mg/mL) were placed on the plates. Ampicillin and moxifloxacin were used as positive controls and DMSO as negative control respectively. The plates were incubated at 37 °C for 48 h, post-inoculation and diameters for the zone of inhibition were calculated in millimetres (mm) and MIC (µg/mL) was determined for the most active compounds.The prepared azo derivatives were screened for their antibacterial activity against six bacterial strains obtained from hospital isolates i.e. gram positive ) and gram-negative ). In brief, 10 µL bacterial suspension, 100 µL trypticase soy broth and 10 µL (10 mg/mL) of test compounds were added in the wells in duplicates and incubated at 37 °C overnight. Ampicillin and moxifloxacin were used as positive controls. After the aspiration of planktonic cells, the biofilm was fixed with 99% methanol. The wells were then washed with 0.1 M sterile PBS (pH = 6.9) thrice and air-dried. Then, 200 µL of crystal violet solution (2%) was added to all wells. After 15 min, the excess of the crystal violet dye was removed and the wells were washed again with PBS. Then, the cell-bound crystal violet was dissolved in 33% acetic acid. The biofilm growth was quantified in terms of OD575 nm using an ELISA plate reader and biofilm hydrolysis was calculated by % inhibition formula.The antibiofilm activity of the synthesised azo derivatives was assessed by microtitre plate-based crystal violet method3.3.1.p-toluidine and 3-amino,2-chloro pyridine) with phenol derivatives  produced azo-phenol compounds in moderate to good yields (40–80%). The purification of the synthesised compounds was achieved through re-crystallization and TLC was employed to confirm the purification status. The structures of the purified diaryl azo-phenol derivatives were elucidated by FTIR, 1H-NMR, 13C-NMR and mass spectrometry (HRMS). The FTIR spectra were recorded in the range of 4000–600 cm−1, the characteristic prominent peaks of synthesised azo-phenol derivatives were observed. The disappearance of NH2 stretch at ∼3500 cm−1, a broad OH stretch overlapped with the aromatic C–H stretching vibrations around 3300–3000 cm−1 and a characteristic N=N peak at ∼1500 have been observed in all FTIR spectra indicating the presence of the said functional groups. In the 1H-NMR spectra, recorded in deuterated DMSO, the disappearance of NH2 signal in the range of 5.0−4.0 ppm characteristic for the used amines was observed, while the amount and type of signals in the range of 6.0−9.0 ppm correspond exactly to the number of aromatic protons. Similarly, the numbers of signals in the 1 C-NMR spectra for the obtained derivatives were consistent with their structure. High-resolution mass spectrometry (HRMS) was also used to identify and confirmed the structure of azo compounds. The obtained spectroscopic data was found consistent with the reported literature in this regard1H and 13C-NMR, HRMS) are given in Supplementary material.The targeted diaryl aromatic azo compounds were synthesised by the facile diazo-coupling approach  describe3.2.TR-1 to TR-9) were evaluated for their inhibitory potential against α-glucosidase enzyme. At a concentration of 250 µg/mL, almost all the tested azo-phenol derivatives exhibited 60–98% anti-diabetic activity, except TR-4 (43%) and TR-5 (56%). It was noticed that the diaryl azo derivatives with two hydroxyl groups at ortho and meta-positions  have enhanced α-glucosidase inhibition potential with IC50 values 15.70 ± 1.3, 53.7 ± 3.2 and 29.7 ± 2.8 respectively, compared to the other active derivatives  with one hydroxyl group at any position on the phenyl ring. The present results were found to be in good agreement with the previous studies establishing the fact that the number and position of hydroxyl groups on the phenyl ring could increase or decrease the inhibitory activity of the compounds against α-glucosidase by effecting the magnitude of hydrogen bond interactions with the proteinTR-7, TR-8 and TR-9, the notable anti-diabetic potential could possibly be due to the introduction of the nitrogen-containing heterocyclic pharmacophoreTR-7, TR-8 and TR-9 is also justified by the minimum binding energy values −7.50, −8.20 and −8.30 Kcal/mol respectively. The following trend in the decreasing order of IC50 (µg/mL) was observed: TR-5>TR-3>TR-2>TR-9>TR-6>TR-8>TR-7>TR-1. The IC50 of TR-1 was found to be effective (15.70 ± 1.3 µg/mL) compared to the reference drug acarbose (21.59 ± 1.5 µg/mL) (All the title compounds (5 µg/mL) , hence, 3.3.Ki).To understand the inhibitory mechanism of the most potent compound against α-glucosidase, kinetic studies were conducted. Kinetic studies showed a concentration-dependent inhibition of α-glucosidase by the inhibitors. Continuous monitoring of the reaction showed a marked decrease in reaction rate in the presence of the inhibitors, which is ultimate, indicated the decrease in the final absorbance when compared with controls containing no inhibitor. The potency of inhibition exhibited by the compounds varied depending on the presence and position of different substitutions and on the class of compounds Inhibition kinetics was analysed by Lineweaver–Burk plot and Dixon plots to determine the type of inhibition and inhibition constant  and psi (ψ) angles among the coordinates of target protein 3.4.2.A molecular docking experiment is the best approach to study the binding conformation of ligands against target proteinGgauss: attractive term for dispersion of two gaussian functions, ΔGrepulsion: square of the distance if closer than a threshold value, ΔGhbond: ramp function – also used for interactions with metal ions, ΔGhydrophobic: ramp function, ΔGtors: proportional to the number of rotatable bonds. In docking, energy results compound selected as best having more than 2.5 Kcal/mol energy value different compared to other compounds. The standard error for Autodock is reported as 2.5 Kcal/mol (http://autodock.scripps.edu/)in vitro and in silico docking energy results, deltamethrin and permethrin were ranked as the best drugs that showed good inhibitory potential against targeted enzyme as compared to all other derivatives. The docking energy values of the synthesised ligands (TR1-9) against α-glucosidase are presented in Here, Δ3.4.2.TR1-9) bind within the active region of α glucosidase which ensures the stability and reliability of docking results. In most of the ligands, oxygen atoms were confined at the outer region of the binding pocket whereas, the benzene ring part showed inside the binding pocket.in vitro results, TR-1 has selected for detail binding interactions. The docking results showed that TR-1 formed two at different residual positions hydrogen bond. The hydroxyl group of TR-1 formed a hydrogen bond with Gly546 and Trp690 having bond distances of 1.87 and 1.92 Å, respectively. In docking results, TR-1 binds within the active site and the bond lengths were comparable with the standard value (<3 Å) (Based on e (<3 Å) . Our docSupplementary data (S1): The α-glucosidase Ramachandran graph is presented the residual position in the favour region (pink boundary) by evaluating the Psi (φ) and Phi (ψ) angles. Most of the residues (green circle) lie in favour region while only ten poor rotamers are present in the outer region.3.5.S. aureus, P. aeruginosa, E. coli and P. vulgaris). Among the studied title compounds, TR-1, TR-4, TR-6 displayed promising antibacterial potential with an average MIC value of 125 µg/200 µL and was found to be dose-dependent, compared to the standard drugs i.e. ampicillin and moxifloxacin (MIC 62.5 µg/200 µL). It was also observed that the detrimental effect of derivatives on bacterial strains was due to the electron-withdrawing groups on the phenyl ringsThe antibacterial results of the prepared azo-phenol derivatives are displayed in  and are 3.6.P. aeruginosa (DR), P. aeruginosa (DS); it was found that at the concentration of 0.5 mg/mL, all the derivatives except TR-4 and TR-7 (P. aeruginosa (DS) in biofilm inhibition (>70%) compared to the standard drug penicillin, which showed 60% inhibition at 0.5 mg/mL, however, against P. aeruginosa (DR) most of the azo derivatives were active (∼70%) in degrading biological membrane but TR-5 and TR-8 efficacy was found to be highest (80%) compared to the standard i.e. moxifloxacin (8b). Interestingly, the compound TR-7 showed 55% anti-biofilm potency against the drug-resistant strain of P. aeruginosa which was not found active against P. aeruginosa (DS). However, the rest of the tested derivatives were found less efficient in this regard.The ability to produce biofilm increases the resistance of microbial cells against harmful environments. Bacterial adhesion to the surface, as well as cell-cell interaction via biological membrane, occurs due to electrostatic interactions. In order to inhibit biofilm formation, one strategy is to break the adhesive forces between bacterial cells and the surface which can be achieved with the use of various antimicrobial agentsand TR-7  were higS. aureus (DS) and S. aureus (DR) biofilm hydrolysis efficiencies, TR-1, TR-3, TR-8 showed potential greater than 70% compared to a penicillin (65%) and all the derivatives except TR-5, TR-7 and TR-8 showed efficacy equal to moxifloxacin (85%) at 0.5 mg/mL concentration respectively. It was also observed that the efficiency of the compound TR-8 was drastically decreased when it was challenged with the drug-resistant strain of S. aureus . To the best of our knowledge, the anti-diabetic and antimicrobial activities of the reported derivatives were not evaluated earlier. Hence, the title compounds were biologically screened in vitro against α-glucosidase and pathogenic bacterial strains i.e. E. coli (gram-negative), S. aureus (gram-positive), S. aureus (gram-positive) drug-resistant strain, P. aeruginosa (gram-negative), P. aeruginosa (gram-negative) drug-resistant strain and P. vulgaris (gram-negative). The experimental data showed that the compounds under consideration have promising pharmacological properties to be used as potential drug leads for the treatment against diabetes mellitus (DM). The title compounds can also serve as the functional template in the antimicrobial resistance (AMR) issue as they have been screened against broad-spectrum bacteria including drug-resistant strains and exhibited good to moderate antimicrobial potential as almost all the compounds exhibited dose-dependent broad-spectrum activity against screened pathogens (MIC 125 µg/200 µL) and biofilm hydrolysis potential (>60 − 80%). The presence of an aromatic hydroxyl group and a heterocyclic pharmacophore fused with the azo moiety confirmed their high inhibitory potency against the α-glucosidase enzyme. The enzyme inhibitory kinetics, mode of binding and docking studies of the most potent inhibitors could help out to design good inhibitors against α-glucosidase to overcome the worldwide health problem of diabetes.In summary, a series of azo derivatives were synthesised Click here for additional data file.


H-pyridothiazin-4-ones was prepared at room temperature by T3P-mediated cyclization of N-phenyl-C-aryl imines with thionicotinic acid, two difficult substrates. The reactions were operationally simple, did not require specialized equipment or anhydrous solvents, could be performed as either two or three component reactions, and gave moderate–good yields as high as 63%. This provides ready access to N-phenyl compounds in this family, which have been generally difficult to prepare. As part of the study, the first crystal structure of neutral thionicotinic acid is also reported, and showed the molecule to be in the form of the thione tautomer. Additionally, the synthesized compounds were tested against T. brucei, the causative agent of Human African Sleeping Sickness. Screening at 50 µM concentration showed that five of the compounds strongly inhibited growth and killed parasites.A series of fourteen 2-aryl-3-phenyl-2,3-dihydro-4 H-pyridothiazin-4-one scaffold  of this and related compounds, having a great deal of conservation with other eukaryotes and a variety of tools for genetic manipulation and screening. In addition, these compounds may serve as a method to probe the highly orchestrated cell cycle and cell biology of these important pathogens.The 2,3-dihydro-4scaffold  featuresdo,3thiazin4-one 1j , R = H thiazin-4-ones reported in the literature, and the number grows quite small when there is an aryl group on the nitrogen of the 1,3-thiazin-4-one ring ,3thiazinone ring ,9,10. A lic acid . Howeverl imines ,13,14. Fat 95 °C . H-1,3-thiazin-4-ones thiazin-4-ones thiazin-4-ones.Where both of these methods involved specialized equipment  and high temperature, we have previously reported simple, room temperature synthesis of various 2,3-diaryl-2,3-dihydro-4n-4-ones ,12,13,14n-4-ones ,15, usinn-4-ones . Taylor’n-4-ones ,18,19, bH-pyridothiazin-4-ones 1, with a variety of substituents in the meta and para positions on the C-aryl ring, as well as one in the ortho position , the reactions were performed as three-component couplings, forming the imine in situ from an aldehyde and aniline rather than preparing it separately. As we have reported previously in the similar reaction of 3-mercaptopropionic acid methylidene}aniline (2e): Recrystallization from hexanes provided light yellow crystals . mp: 45.6–47.8 °C (lit. 47–47.5 °C 2-Aryl-3-phenyl-2,3-dihydro-4thiazin-4-ones: A two-necked 25 mL round-bottom flask was oven-dried, cooled under N2, and charged with a stir bar. Aniline  and a substituted benzaldehyde (6 mmol) were added. 2-Methyltetrahydrofuran (2.3 mL) was added and the solution was stirred. Thionicotinic acid  was added. Pyridine  was added. Finally, 2,4,6-tripropyl-1,3,5,2,4,6-trioxatriphosphorinane-2,4,6-trioxide (T3P) in 2-methyltetrahydrofuran  was added. The reaction was stirred at room temperature and followed by TLC, then poured into a separatory funnel with dichloromethane (20 mL). The mixture was washed with water (10 mL). The aqueous was then extracted twice with dichloromethane (10 mL each). The organics were combined and washed with saturated sodium bicarbonate (10 mL) and then saturated sodium chloride (10 mL). The organic was dried over sodium sulfate and concentrated under vacuum to give a crude mixture. Further purification was carried out as indicated below for each compound.H-pyrido2-(3-Bromophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1g): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave off-white crystals . mp: 142.6–143.5 °C. 1H NMR (CDCl3): δ(ppm): δ 8.53 , 8.48 , 7.63 , 7.47–7.37 , 7.34 , 7.24 , 7.18 , 6.12 . 13C NMR (CDCl3): δ(ppm): δ 163.1 (C=O), 156.2 (Ar), 153.0 (Ar), 141.8 (Ar), 141.5 (Ar), 138.1 (Ar), 131.8 (Ar), 130.1 (Ar), 129.7 (Ar), 129.5 (Ar), 127.7 (Ar), 126.0 (Ar), 125.6 (Ar), 125.1 (Ar), 123.0 (Ar), 121.5 (Ar), 64.3 (C2). HRMS (m/z): [C19H13BrN2OS+H]+ of 397.0001 is consistent with calculated [M+H]+ of 397.0005. IR : 1667 (C=O). Rf (50% EtOAc/hexanes) = 0.52.H-pyrido2-(3-Methylphenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1l): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave off-white crystals . mp: 114.8–116.2 °C. 1H NMR (CDCl3): δ(ppm): δ 8.55–8.40 , 7.41 , 7.35 , 7.33–7.23 , 7.23–7.13 , 7.08 , 6.13 , 2.31 . 13C NMR (CDCl3): δ(ppm): δ 163.4 (C=O), 156.8 (Ar), 152.8 (Ar), 142.0 (Ar), 139.1 (Ar), 138.5 (Ar), 137.9 (Ar), 129.4 (Ar), 129.3 (Ar), 128.4 (Ar), 127.4 (Ar), 127.3 (Ar), 126.1 (Ar), 125.7 (Ar), 123.6 (Ar), 121.2 (Ar), 64.9 (C2), 21.5 (CH3). HRMS (m/z): [C20H16N2OS+H]+ of 333.1067 is consistent with calculated [M+H]+ of 333.1061. IR : 1662 (C=O). Rf (50% EtOAc/hexanes) = 0.57.H-pyrido2-(3-Methoxyphenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1n): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave an off-white powder . mp: 153.0–153.6 °C. 1H NMR (CDCl3): δ(ppm): δ 8.51 , 8.47 , 7.41 , 7.36 , 7.31 , 7.24–7.18 , 7.04 , 6.99 , 6.81 , 6.13 , 3.76 . 13C NMR (CDCl3): δ(ppm): δ 163.3 (C=O), 159.8 (Ar), 156.7 (Ar), 152.8 (Ar), 142.0 (Ar), 140.8 (Ar), 138.0 (Ar), 129.6 (Ar), 129.3 (Ar), 127.5 (Ar), 126.2 (Ar), 125.7 (Ar), 121.3 (Ar), 118.9 (Ar), 114.0 (Ar), 112.5 (Ar), 64.9 (C2), 55.3 (OCH3). HRMS (m/z): [C20H16N2O2S+H]+ of 349.1008 is consistent with calculated [M+H]+ of 349.1005. IR : 1661 (C=O). Rf (50% EtOAc/hexanes) = 0.52.General Procedure for Two-Component Coupling to PrepareH-pyrido2-Aryl-3-phenyl-2,3-dihydro-4thiazin-4-ones: A two-necked 25 mL round-bottom flask was oven-dried, cooled under N2, and charged with a stir bar, an imine (6 mmol), and thionicotinic acid . 2-Methyltetrahydrofuran (2.3 mL) was added and the solution was stirred. Pyridine  was added. Finally, 2,4,6-tripropyl-1,3,5,2,4,6-trioxatriphosphorinane-2,4,6-trioxide (T3P) in 2-methyltetrahydrofuran  was added. The reaction was stirred at room temperature and followed by TLC, then poured into a separatory funnel with dichloromethane (20 mL). The mixture was washed with water (10 mL). The aqueous was then extracted twice with dichloromethane (10 mL each). The organics were combined and washed with saturated sodium bicarbonate (10 mL) and then saturated sodium chloride (10 mL). The organic was dried over sodium sulfate and concentrated under vacuum to give a crude mixture. Further purification was carried out as indicated below for each compound.H-pyrido2-(4-Nitrophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1a): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave an off-white powder . mp: 190.0–191.3 °C. 1H NMR (CDCl3): δ(ppm): δ 8.53 , 8.48 , 8.18 , 7.68 , 7.44 , 7.39–7.30 , 7.26 , 6.23 . 13C NMR (CDCl3): δ(ppm): 163.0 (C=O), 155.8 (pyridine ring), 153.1 (pyridine ring), 147.9 (Ar), 146.4 (Ar), 141.6 (Ar), 138.3 (Ar), 129.6 (Ar), 127.9 (Ar), 127.5 (Ar), 125.9(Ar), 125.5 (Ar), 124.0 (Ar), 121.8 (Ar), 64.3 (C2). HRMS (m/z): [C19H13N3O3S+H]+ of 364.0751 is consistent with calculated [M+H]+ of 364.0756. IR : 1652 (C=O). Rf (50% EtOAc/hexanes) = 0.50.H-pyrido2-(3-Nitrophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1b): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from a mixture of ethyl acetate and hexanes gave a white solid . mp: 149.7–149.9 °C. 1H NMR (CDCl3): δ(ppm): δ 8.55–8.52 , 8.50 , 8.37 , 8.15 , 7.82 , 7.51 , 7.45 , 7.39–7.32 , 7.26 , 6.25 . 13C NMR (CDCl3): δ(ppm): 162.9 (C=O), 155.8 (Ar), 153.1 (Ar), 148.4 (Ar), 141.7 (Ar), 141.6 (Ar), 138.3 (Ar), 132.1 (Ar), 129.8 (Ar), 129.7 (Ar), 127.9 (Ar), 125.9 (Ar), 125.7 (Ar), 123.7 (Ar), 121.8 (Ar), 121.6 (Ar), 64.2 (C2). HRMS (m/z): [C19H13N3O3S+H]+ of 364.0754 is consistent with calculated [M+H]+ of 364.0756. IR : 1654 (C=O). Rf (50% EtOAc/hexanes) = 0.30.H-pyrido2-(2-Nitrophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1c): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from a mixture of ethyl acetate and hexanes gave light yellow crystals . mp: 195.7–1196.4 °C. 1H NMR (CDCl3): δ(ppm): δ 8.52 , 8.51 , 8.18 , 7.64 , 7.57 , 7.53–7.46 , 7.47–7.40 , 7.38–7.30 , 7.26–7.21 , 7.15 . 13C NMR (CDCl3): δ(ppm): 163.9 (C=O), 156.4 (Ar), 153.2 (Ar), 146.2 (Ar), 142.0 (Ar), 138.1 (Ar), 135.4 (Ar), 133.4 (Ar), 129.7 (Ar), 129.6 (Ar), 128.0 (Ar), 127.5 (Ar), 127.1 (Ar), 125.8 (Ar), 124.9 (Ar), 121.4 (Ar), 60.6 (C2). HRMS (m/z): [C19H13N3O3S+H]+ of 364.0750 is consistent with calculated [M+H]+ of 364.0756. IR : 1663 (C=O). Rf (50% EtOAc/hexanes) = 0.49.H-pyrido3-Phenyl-2-[4-(trifluoromethyl)phenyl]-2,3-dihydro-4thiazin-4-one (1d): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave slightly off-white crystals . mp: 185.2–186.1 °C. 1H NMR (CDCl3): δ(ppm): δ 8.52 , 8.48 , 7.69–7.54 , 7.49–7.39 , 7.39–7.31 , 7.24 , 6.20 . 13C NMR (CDCl3): δ(ppm): δ 163.0 (C=O), 156.0 (Ar), 152.8 (Ar), 143.2 (Ar), 141.7 (Ar), 138.4 (Ar), , 121.6 (Ar), 64.4 (C2). 19F NMR (CDCl3): δ(ppm): δ -62.8. HRMS (m/z): [C20H13F3N2OS+H]+ of 387.0775 is consistent with calculated [M+H]+ of 387.0778. IR : 1652 (C=O). Rf (50% EtOAc/hexanes) = 0.54.H-pyrido3-Phenyl-2-[3-(trifluoromethyl)phenyl]-2,3-dihydro-4thiazin-4-one (1e): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave a white powder . mp: 119.2–120.2 °C. 1H NMR (CDCl3): δ(ppm): δ 8.52 , 8.48 , 7.73 , 7.67 , 7.55 , 7.44 , 7.37–7.30 , 7.24 , 6.21 . 13C NMR (CDCl3): δ(ppm): δ 163.1 (C=O), 156.1 (Ar), 153.0 (Ar), 141.7 (Ar), 140.4 (Ar), 138.1 (Ar), , 129.6 (Ar), 129.5 (Ar), 129.2 (Ar), 127.8 (Ar), , 126.0 (Ar), 125.7 (Ar), , , 121.6 (Ar), 64.5 (C2). 19F NMR (CDCl3): δ(ppm): δ -62.8. HRMS (m/z): [C20H13F3N2OS+H]+ of 387.0773 is consistent with calculated [M+H]+ of 387.0778. IR : 1653 (C=O). Rf (50% EtOAc/hexanes) = 0.59.H-pyrido2-(4-Bromophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1f): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave off-white crystals . mp: 171.6–173.6 °C. 1H NMR (CDCl3): δ(ppm): δ 8.59–8.39 , 8.18 , 7.68 , 7.44 , 7.39–7.31 , 7.26 , 6.23 . 13C NMR (CDCl3): δ(ppm): δ 163.2 (C=O), 156.4 (Ar), 152.9 (Ar), 141.8 (Ar), 138.3 (Ar), 138.1 (Ar), 131.8 (Ar), 129.5 (Ar), 128.2 (Ar), 127.6 (Ar), 126.0 (Ar), 125.6 (Ar), 122.8 (Ar), 121.5 (Ar), 64.5 (C2). HRMS (m/z): [C19H13BrN2OS+H]+ of 397.0009 is consistent with calculated [M+H]+ of 397.0005. IR : 1652 (C=O). Rf (50% EtOAc/hexanes) = 0.59.H-pyrido2-(4-Fluorophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1h): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave white crystals . mp: 127.8–128.4 °C. 1H NMR (CDCl3): δ(ppm): δ 8.52 , 8.46 , 7.48–7.39 , 7.34 , 7.26–7.16 , 6.99 , 6.17 . 13C NMR (CDCl3): δ(ppm): δ , 129.4 (Ar), 129.1 (Ar), , 128.2, 127.6, 126.0, 125.7, 125.3 (Ar), 121.4 (Ar), , 64.5 (C2). 19F NMR (CDCl3): δ(ppm): δ −112.79 . HRMS (m/z): [C19H13FN2OS+H]+ of 337.0812 is consistent with calculated [M+H]+ of 337.0805. IR : 1652 (C=O). Rf (50% EtOAc/hexanes) = 0.48.H-pyrido2-(3-Fluorophenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1i): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from ethyl acetate and hexanes gave an off-white solid . mp: 118.8–121.2 °C. 1H NMR (CDCl3): δ(ppm): δ 8.52 , 8.47 , 7.46–7.40 , 7.40–7.26 , 7.24 , 7.20 , 7.01–6.95 , 6.15 .13C NMR (CDCl3): δ(ppm): δ , 163.1 (C=O), 156.3 (Ar), 152.9 (Ar), , 141.8 (Ar), 138.2 (Ar), , 129.5 (Ar), 127.6 (Ar), 126.0 (Ar), 125.6 (Ar), , 121.5, , , 64.4 (C2). 19F NMR (CDCl3): δ(ppm): δ −111.41 . HRMS (m/z): [C19H13FN2OS+H]+ of 337.0806 is consistent with calculated [M+H]+ of 337.0805. IR : 1646 (C=O). Rf (50 % EtOAc/hexanes) = 0.51.H-pyrido2,3-Diphenyl-2,3-dihydro-4thiazin-4-one (1j): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from 2-propanol gave an ivory solid . Data previously reported 2-(4-Methylphenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1k): Recrystallization from 2-propanol gave an orange–yellow solid . mp: 128–130 °C. 1H NMR (CDCl3): δ(ppm): δ 8.61–8.35 , 7.47–7.25 , 7.25–7.16 , 7.10 , 6.15 , 2.29 . 13C NMR (CDCl3): δ(ppm): δ 163.3 (C=O), 156.7 (Ar), 152.4 (Ar), 141.9 (Ar), 138.6 (Ar), 138.2 (Ar), 136.0 (Ar), 129.4 (Ar), 127.4 (Ar), 126.2 (Ar), 125.7 (Ar), 121.2 (Ar), 64.9 (C2), 21.0 (CH3). HRMS (m/z): [C20H16N2OS+H]+ of 333.1054 is consistent with calculated [M+H]+ of 333.1061. IR : 1657 (C=O). Rf (50% EtOAc/hexanes) = 0.49.H-pyrido2-(4-Methoxyphenyl)-3-phenyl-2,3-dihydro-4thiazin-4-one (1m): After chromatography on 30 g silica gel with mixtures of ethyl acetate and hexanes, recrystallization from 2-propanol gave a yellow solid . mp: 142.5–143.0 °C. 1H NMR (CDCl3): δ(ppm): δ 8.51 , 8.46 , 7.43–7.30 , 7.21 , 6.81 , 6.15 , 3.77 . 13C NMR (CDCl3): δ(ppm): δ 163.4 (C=O), 159.7 (Ar), 156.9 (Ar), 152.8 (Ar), 141.9 (Ar), 137.9 (Ar), 130.9 (Ar), 129.3 (Ar), 127.9 (Ar), 127.4 (Ar), 126.1 (Ar), 125.7 (Ar), 121.2 (Ar), 114.0 (Ar), 64.7 (C2), 55.3 (OCH3). HRMS (m/z): [C20H16N2O2S+H]+ of 349.1006 is consistent with calculated [M+H]+ of 349.1005. IR : 1644 (C=O). Rf (50% EtOAc/hexanes) = 0.48.Cell Culture: Bloodstream form T.bruceibrucei strain 90–13 were cultured at 37 °C in 5% CO2 in HMI-9 supplemented with 15% fetal bovine serum [5 cells/mL in 1 mL, treated with 50 µM of each compound in triplicate, and counted over 3 days using a hemacytometer. The average of 4 replicates for the DMSO vehicle control and 3 replicates for treated samples was plotted with standard deviation shown as error bars  has been demonstrated. The reactions run at room temperature, are simple to perform, and do not require dry solvents or special equipment such as a microwave oven or an ultrasonicator. A series of compounds with various electron-donating and electron-withdrawing groups on the C2-aryl ring was prepared in moderate–good yields. The reactions can be run as either a two- or three-component reaction, although yields were somewhat lower for the three-component reactions. A new, simple preparation of 2-aryl-3-phenyl-2,3-dihydro-4T. brucei, an important animal pathogen closely related to other species and subspecies that cause disease in humans. These compounds are good candidates for further study as pharmacological agents.Some of these compounds strongly inhibited growth of the parasite 3 yielded the first crystal structure of the neutral species and showed it to be in the thione form 3T.X-ray crystallographic studies of