QUANTITATIVE DETERMINATION AND PREPARATIVE ISOLATION OF TWO MAJOR ALKALOIDS FROM THE VIETNAMESE MEDICINAL HERB EVODIAE FRUCTUS

Objective: To develop a simple and accurate HPLC-DAD method for simultaneous determination, the content of major components: limonin, evodiamine, and rutaecarpine in Evodiae fructus and evaluation the quality of Evodiae fructus sold in markets. Methods: Open column chromatography was used to separate and purify rutaecarpine and evodiamine, the two major alkaloids from Evodiae fructus extract as a laboratory standard. Chromatographic separation was achieved using a Germini C18 column (150 mm × 4.6 mm I.D., 5 µm), detected at 210 nm. The mobile phase consisted of acetonitrile (A), methanol (B), and water (C). The validated method simultaneously determined alkaloid content in 40 batches of samples collected from markets in different regions of Vietnam. Results: In one-step purification, our method yielded 326 mg of rutaecarpine and 128 mg of evodiamine from 3.2 g of crude extract, with purities of 98.9 and 98.5%, respectively. The structures of these compounds were identified using 1H NMR and 13C NMR. There was a significant correlation between alkaloid content and fruit size, with a Spearman correlation coefficient of>0.5 (p<0.001), and there was a large difference in alkaloid contents between three maturity degrees of the fruit. Open-mouth fruits and fruits with average sizes of 4 to 6 mm had the highest alkaloid contents, whereas closed-mouth fruits had the lowest. Conclusion: This study provided information on the standardization and quality control of evodiamine and rutaecarpine in Evodiae fructus, as well as a foundation for further pharmacological and toxicological studies

Development of Diagnostic Tests for Detection of SARS-CoV-2

One of the most effective ways to prevent the spread of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is to develop accurate and rapid diagnostic tests. There are a number of molecular, serological, and imaging methods that are used to diagnose this infection in hospitals and clinical settings. The purpose of this review paper is to present the available approaches for detecting SARS-CoV-2 and address the advantages and limitations of each detection method. This work includes studies from recent literature publications along with information from the manufacturer\u27s manuals of commercially available SARS-CoV-2 diagnostic products. Furthermore, supplementary information from the Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO) is cited. The viral components targeted for virus detection, the principles of each diagnostic technique, and the detection efficiency of each approach are discussed. The potential of using diagnostic tests that were originally developed for previous epidemic viruses is also presented

Influence maximization under fairness budget distribution in online social networks

In social influence analysis, viral marketing, and other fields, the influence maximization problem is a fundamental one with critical applications and has attracted many researchers in the last decades. This problem asks to find a k-size seed set with the largest expected influence spread size. Our paper studies the problem of fairness budget distribution in influence maximization, aiming to find a seed set of size k fairly disseminated in target communities. Each community has certain lower and upper bounded budgets, and the number of each community's elements is selected into a seed set holding these bounds. Nevertheless, resolving this problem encounters two main challenges: strongly influential seed sets might not adhere to the fairness constraint, and it is an NP-hard problem. To address these shortcomings, we propose three algorithms (FBIM1, FBIM2, and FBIM3). These algorithms combine an improved greedy strategy for selecting seeds to ensure maximum coverage with the fairness constraints by generating sampling through a Reverse Influence Sampling framework. Our algorithms provide a (1/2 - epsilon)-approximation of the optimal solution, and require O(kT log ((8 + 2 epsilon)n ln + 2/delta + ln(nk)/epsilon(2))), O(kT log n/epsilon(2)k), and O(T/epsilon log k/epsilon log n/epsilon(2)k) complexity, respectively. We conducted experiments on real social networks. The result shows that our proposed algorithms are highly scalable while satisfying theoretical assurances, and that the coverage ratios with respect to the target communities are larger than those of the state-of-the-art alternatives; there are even cases in which our algorithms reaches 100% coverage with respect to target communities. In addition, our algorithms are feasible and effective even in cases involving big data; in particular, the results of the algorithms guarantee fairness constraints.Web of Science1022art. no. 418

Efficient streaming algorithms for maximizing monotone DR-submodular function on the integer lattice

In recent years, the issue of maximizing submodular functions has attracted much interest from research communities. However, most submodular functions are specified in a set function. Meanwhile, recent advancements have been studied for maximizing a diminishing return submodular (DR-submodular) function on the integer lattice. Because plenty of publications show that the DR-submodular function has wide applications in optimization problems such as sensor placement impose problems, optimal budget allocation, social network, and especially machine learning. In this research, we propose two main streaming algorithms for the problem of maximizing a monotone DR-submodular function under cardinality constraints. Our two algorithms, which are called StrDRS1 and StrDRS2, have (1/2 - epsilon) , (1 - 1 /e - epsilon) of approximation ratios and O(n/epsilon log(log B/epsilon ) log k), O(n/epsilon log B), respectively. We conducted several experiments to investigate the performance of our algorithms based on the budget allocation problem over the bipartite influence model, an instance of the monotone submodular function maximization problem over the integer lattice. The experimental results indicate that our proposed algorithms not only provide solutions with a high value of the objective function, but also outperform the state-of-the-art algorithms in terms of both the number of queries and the running time.Web of Science1020art. no. 377

Point-of-care C-reactive protein testing to reduce inappropriate use of antibiotics for non-severe acute respiratory infections in Vietnamese primary health care: a randomised controlled trial

Background Inappropriate antibiotic use for acute respiratory tract infections is common in primary health care, but distinguishing serious from self-limiting infections is diffi cult, particularly in low-resource settings. We assessed whether C-reactive protein point-of-care testing can safely reduce antibiotic use in patients with non-severe acute respiratory tract infections in Vietnam. Method We did a multicentre open-label randomised controlled trial in ten primary health-care centres in northern Vietnam. Patients aged 1–65 years with at least one focal and one systemic symptom of acute respiratory tract infection were assigned 1:1 to receive either C-reactive protein point-of-care testing or routine care, following which antibiotic prescribing decisions were made. Patients with severe acute respiratory tract infection were excluded. Enrolled patients were reassessed on day 3, 4, or 5, and on day 14 a structured telephone interview was done blind to the intervention. Randomised assignments were concealed from prescribers and patients but not masked as the test result was used to assist treatment decisions. The primary outcome was antibiotic use within 14 days of follow-up. All analyses were prespecifi ed in the protocol and the statistical analysis plan. All analyses were done on the intention-totreat population and the analysis of the primary endpoint was repeated in the per-protocol population. This trial is registered under number NCT01918579. Findings Between March 17, 2014, and July 3, 2015, 2037 patients (1028 children and 1009 adults) were enrolled and randomised. One adult patient withdrew immediately after randomisation. 1017 patients were assigned to receive C-reactive protein point-of-care testing, and 1019 patients were assigned to receive routine care. 115 patients in the C-reactive protein point-of-care group and 72 patients in the routine care group were excluded in the intention-to-treat analysis due to missing primary endpoint. The number of patients who used antibiotics within 14 days was 581 (64%) of 902 patients in the C-reactive protein group versus 738 (78%) of 947 patients in the control group (odds ratio [OR] 0·49, 95% CI 0·40–0·61; p<0·0001). Highly signifi cant diff erences were seen in both children and adults, with substantial heterogeneity of the intervention eff ect across the 10 sites (I²=84%, 95% CI 66–96). 140 patients in the C-reactive protein group and 137 patients in the routine care group missed the urine test on day 3, 4, or 5. Antibiotic activity in urine on day 3, 4, or 5 was found in 267 (30%) of 877 patients in the C-reactive protein group versus 314 (36%) of 882 patients in the routine treatment group (OR 0·78, 95% CI 0·63–0·95; p=0·015). Time to resolution of symptoms was similar in both groups. Adverse events were rare, with no deaths and a total of 14 hospital admissions (six in the C-reactive protein group and eight in the control group). Interpretation C-reactive protein point-of-care testing reduced antibiotic use for non-severe acute respiratory tract infection without compromising patients’ recovery in primary health care in Vietnam. Health-care providers might have become familiar with the clinical picture of low C-reactive protein, leading to reduction in antibiotic prescribing in both groups, but this would have led to a reduction in observed eff ect, rather than overestimation. Qualitative analysis is needed to address diff erences in context in order to implement this strategy to improve rational antibiotic use for patients with acute respiratory infection in low-income and middle-income countries

Esophagectomy without mortality: What can surgeons do?

Introduction: Surgical resection remains the mainstay treatment for patients with localized esophageal cancer. It is, however, a complex procedure. Mortality rate used to be high, but in recent years, death rate has been reduced to below 5% in specialized centers. Methods: Outcome of esophagectomy can be improved by paying attention to (1) appropriate patient section, (2) choice of surgical techniques and their execution, and (3) optimizing perioperative care. A volume-outcome relationship is also evident. Surgeons can perform esophagectomy without mortality, but a multi-disciplinary team management is essential to achieve this goal. © 2009 The Society for Surgery of the Alimentary Tract.postprin

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Acidolysis of Poly(ethylene terephthalate) Waste Using Succinic Acid under Microwave Irradiation as a New Chemical Upcycling Method

A novel method of chemical upcycling of used poly(ethylene terephthalate) (PET) bottles by acidolysis with succinic acid (SA) was performed under microwave irradiation. The long polyester chain of PET was efficiently fragmented into small molecules and oligomers, such as terephthalic acid and α,ω-dicarboxylic acid oligo(ethylene succinate-co-terephthalate) (OEST). Various input molar ratios of SA/PET from 1.0 to 2.5 were used, and the product mixtures were separated successfully. The recovered terephthalic acid can be reused as a basic chemical. The α,ω-dicarboxylic acid OEST was used as a curing agent for epoxy resin. The recovered SA can be reused for further PET acidolysis. Structures of OEST were identified by Fourier transform infrared (FTIR) spectroscopy, 1H NMR spectroscopy, and electrospray ionization–mass spectrometry (ESI–MS). The presence of succinic anhydride as a side product was confirmed by FTIR and ESI–MS analyses. The evaporation of SA and the formation of volatile succinic anhydride compete with the acidolysis of PET. The minimum SA/PET ratio of 1.0 was selected so that the acidolysis was effective and without the SA recovery step by MEK treatment. OEST-1.0 was used for curing diglycidyl ether of bisphenol A. The structures and thermal properties of cured adducts were confirmed by FTIR and differential scanning calorimetry (DSC). This chemical upcycling method of PET is eco-friendly without the use of a solvent and a catalyst for the reaction, and all materials were recovered and they could be reused for novel polymer preparation

Multiple benefit thresholds problem in online social networks: An algorithmic approach

An important problem in the context of viral marketing in social networks is the Influence Threshold (IT) problem, which aims at finding some users (referred to as a seed set) to begin the process of disseminating their product's information so that the benefit gained exceeds a predetermined threshold. Even though, marketing strategies exhibit different in several realistic scenarios due to market dependence or budget constraints. As a consequence, picking a seed set for a specific threshold is not enough to come up with an effective solution. To address the disadvantages of previous works with a new approach, we study the Multiple Benefit Thresholds (MBT), a generalized version of the IT problem, as a result of this phenomenon. Given a social network that is subjected to information distribution and a set of thresholds, T = {T-1, T-2, ..., T-k}, Ti > 0, the issue aims to seek the seed sets S-1, S-2, ..., Sk with the lowest possible cost so that the benefit achieved from the influence process is at the very least T-1, T-2, ..., T-k, respectively. The main challenges of this problem are a #NP-hard problem and the estimation of the objective function #P-Hard under traditional information propagation models. In addition, adapting the exist algorithms many times to different thresholds can lead to large computational costs. To address the abovementioned challenges, we introduced Efficient Sampling for Selecting Multiple Seed Sets, an efficient technique with theoretical guarantees (ESSM). At the core of our algorithm, we developed a novel algorithmic framework that (1) can use the solution to a smaller threshold to find that of larger ones and (2) can leverage existing samples with the current solution to find that of larger ones. The extensive experiments on several real social networks were conducted in order to show the effectiveness and performance of our algorithm compared with current ones. The results indicated that our algorithm outperformed other state-of-the-art ones in terms of both the total cost and running time.Web of Science106art. no. 87