Identification of treatment effects with selective participation in a randomized trial

Randomized trials (RTs) are used to learn about treatment effects. This paper studies identification of average treatment response (ATR) and average treatment effect (ATE) from RT data under various assumptions. The focus is the problem of external validity of the RT. RT data need not point identify the ATR or ATE because of selective participation in the RT. The paper reports partial‐identification and point‐identification results for the ATR and ATE based on RT data under a variety of assumptions. The results include assumptions sufficient to point identify the ATR or ATE from RT data. Under weaker assumptions, the ATR or ATE is partially identified. Further, attention is given to identification of the sign of the ATE and identification of whether participation in the RT is selective. Finally, identification from RT data is compared to identification from observational data.     

Estimation of graphical models using the norm

Gaussian graphical models are recently used in economics to obtain networks of dependence among agents. A widely used estimator is the graphical least absolute shrinkage and selection operator (GLASSO), which amounts to a maximum likelihood estimation regularized using the matrix norm on the precision matrix Ω. The norm is a LASSO penalty that controls for sparsity, or the number of zeros in Ω. We propose a new estimator called structured GLASSO (SGLASSO) that uses the mixed norm. The use of the penalty controls for the structure of the sparsity in Ω. We show that when the network size is fixed, SGLASSO is asymptotically equivalent to an infeasible GLASSO problem which prioritizes the sparsity‐recovery of high‐degree nodes. Monte Carlo simulation shows that SGLASSO outperforms GLASSO in terms of estimating the overall precision matrix and in terms of estimating the structure of the graphical model. In an empirical illustration using a classic firms' investment data set, we obtain a network of firms' dependence that exhibits the core–periphery structure, with General Motors, General Electric and US Steel forming the core group of firms.     

Robust tests for deterministic seasonality and seasonal mean shifts

We develop tests for the presence of deterministic seasonal behaviour and seasonal mean shifts in a seasonally observed univariate time series. These tests are designed to be asymptotically robust to the order of integration of the series at both the zero and seasonal frequencies. Motivated by the approach of Hylleberg, Engle, Granger and Yoo, we base our approach on linear filters of the data that remove any potential unit roots at the frequencies not associated with the deterministic component(s) under test. Test statistics are constructed using the filtered data such that they have well defined limiting null distributions regardless of whether the data are either integrated or stationary at the frequency associated with the deterministic component(s) under test. In the same manner as Vogelsang, Bunzel and Vogelsang and Sayginsoy and Vogelsang, we scale these statistics by a function of an auxiliary seasonal unit root statistic. This allows us to construct tests that are asymptotically robust to the order of integration of the data at both the zero and seasonal frequencies. Monte Carlo evidence suggests that our proposed tests have good finite sample size and power properties. An empirical application to UK gross domestic product indicates the presence of seasonal mean shifts in the data.     

A Note on Derivatives of Isoniazid,Rifampicin, and Pyrazinamide Showing Activity Against Resistant Mycobacterium tuberculosis

Drug‐resistant tuberculosis (DR‐TB) is a serious problem that impedes the success of the TB control program. Of note, multidrug‐resistant (MDR)‐TB and extensively drug‐resistant (XDR)‐TB have certainly complicated the scenario. One of the possible strategies to overcome drug resistance in an economic and simple manner would involve modification of existing anti‐TB drugs to obtain derivatives that can work on resistant TB bacilli. These may have improved half‐life and increased bioavailability, be more efficacious, and serve as cost‐effective alternatives, as compared to new drugs identified through conventional methods of drug discovery and development. Although extensive literature is available on the activity of various derivatives of first‐line drugs (isoniazid, rifampicin and pyrazinamide) on drug‐susceptible Mycobacterium tuberculosis (MTB), reports on the activity of derivatives on resistant MTB are very limited, to our knowledge. In light of this, the present review aims to provide a concise report on the derivatives of first‐line drugs that have the potential to overcome the resistance to the parental drug and could thus serve as effective alternatives.     

CCE in panels with general unknown factors

A popular approach to factor‐augmented panel regressions is the common correlated effects (CCE) estimator of Pesaran (2006). In fact, the approach is so popular that it has given rise to a separate CCE literature. A common assumption in this literature is that the common factors are stationary, which would seem to rule out many empirically relevant cases. Moreover, deterministic factors are typically treated as known, which raises the issue of model misspecification. In the current paper, we show how the conditions placed on the factors in CCE can be made much more general than was previously thought possible. In fact, save for some mild regulatory moment conditions, the factors are essentially unrestricted. One implication of this result is that there is no need to discriminate between deterministic and stochastic factors, but that one can instead treat them all as unknown. This is very convenient for practitioners, because it means that under certain conditions they are spared the problem of having to decide which deterministic terms to include in the model.     

Non‐parametric Bayesian inference of strategies in repeated games

Inferring underlying cooperative and competitive strategies from human behaviour in repeated games is important for accurately characterizing human behaviour and understanding how people reason strategically. Finite automata, a bounded model of computation, have been extensively used to compactly represent strategies for these games and are a standard tool in game theoretic analyses. However, inference over these strategies in repeated games is challenging since the number of possible strategies grows exponentially with the number of repetitions yet behavioural data are often sparse and noisy. As a result, previous approaches start by specifying a finite hypothesis space of automata that does not allow for flexibility. This limitation hinders the discovery of novel strategies that may be used by humans but are not anticipated a priori by current theory. Here we present a new probabilistic model for strategy inference in repeated games by exploiting non‐parametric Bayesian modelling. With simulated data, we show that the model is effective at inferring the true strategy rapidly and from limited data, which leads to accurate predictions of future behaviour. When applied to experimental data of human behaviour in a repeated prisoner's dilemma, we uncover strategies of varying complexity and diversity.     

Beyond plausibly exogenous

We synthesize two recent advances in the literature on instrumental variable (IV) estimation that test and relax the exclusion restriction. Our approach first estimates the direct effect of the IV on the outcome in a subsample for which the IV does not affect the treatment variable. Subsequently, this estimate for the direct effect is used as input for the plausibly exogenous method developed by Conley, Hansen and Rossi. This two‐step procedure provides a novel and informed sensitivity analysis for IV estimation. We illustrate the practical use by estimating the causal effect of (a) attending Catholic high school on schooling outcomes and (b) the number of children on female labour supply.     

Column selection approach for related substances determination of progesterone by high‐performance liquid chromatography

In this study, HPLC‐MS/MS with triple‐quadrupole tandem mass spectrometer was used to analyze the base‐catalyzed thermal degradation derivative of progesterone in Chinese Pharmacopoeia. The full‐scan spectrometry revealed that the degradation product was an isomer of progesterone, it was proposed as impurity M ((17α)‐pregn‐4‐ene‐3,20‐dione) in European Pharmacopoeia, and both the derivative and progesterone were neutral molecules. Four kinds of chromatographic column characterization databases including PQRI database using Snyder/Dolan method, the USP chromatographic column database using the SRM 870 tests, the Tanaka/Euerby approach within the ACD program, and the Hoogmartens approach were compared. Combing the principles of column characterization databases with the system requirement of progesterone‐related substances testing, a suitable PQRI‐based method was finally set up for progesterone‐related substances detecting. Our results indicated that PQRI system of Snyder/Dolan method was the most suitable system for related substances detection of progesterone.     

Antibacterial activity and in vivo wound healing potential of phenolic extracts from jaboticaba skin

In this study, different phenolic extracts were obtained from the jaboticaba skin meal (JSM), whose phenolic compounds were characterized and their antibacterial activities were assessed. Moreover, the activity of lyophilized ethanolic extract of jaboticaba skin (EEJS) on wound healing was analyzed in rats. The JSM phenolic extracts were obtained in four ways: aqueous, methanolic, ethanolic, and acetone extracts. The phenolic compounds were characterized in these extracts by high‐performance liquid chromatography, and their antibacterial activities were evaluated. The in vivo experiment was divided into four groups and received the following treatments: G1—silver sulfadiazine (positive control); G2—EEJS at 10%; G3—EEJS at 5%, and G4—EEJS at 2.5%. The aqueous extract did not inhibit the growing of any bacterium. The ethanolic, acetone, and methanolic extracts inhibited the growing of all bacteria tested at the concentrations of 1.25%, 2.50%, and 5.00%, respectively. The ethanolic extract was the one that showed the highest bacterial inhibition potential and the highest contents of phenolic compounds, especially of catechin, epicatechin gallate, and epicatechin. The G3 and G4 treatments presented faster wound healing compared to the G1 one, as it promoted a less intense inflammatory reaction and full closure of the wounds at an accelerated rate.     

Synthesis of honokiol analogues and evaluation of their modulating action on VEGF protein secretion and telomerase‐related gene expressions

A group of 36 biphenyl derivatives structurally related to honokiol were synthesized by means of Suzuki coupling reactions. Their cytotoxicities were evaluated and compared to that of honokiol. Some of the compounds were then evaluated for their ability to downregulate the secretion of the VEGF protein and the expression of the VEGF, hTERT, and c‐Myc genes; the two latter involved in the activation of telomerase in tumoral cells. Some of the synthetized derivatives showed promising pharmacological features as they exhibited IC₅₀ values in low micromolar range, good therapeutic margins, and a multiple mode of action on tumor cells based on the inhibition of VEGF and, at the same time, of the expression of genes related to the activation of telomerase.     

Protein tyrosine phosphatase PTPRB regulates Src phosphorylation and tumour progression in NSCLC

Protein tyrosine‐phosphatases (PTPs) play important roles in various biological processes. Deregulation in PTP function has been implicated in carcinogenesis and tumour progression in many cancer types. However, the role of protein tyrosine phosphatase receptor type B (PTPRB) in non‐small‐cell lung cancer (NSCLC) tumorigenesis has not been investigated. Lentiviral vector expressing PTPRB cDNA or shRNA was infected into A549 and H1299 cell lines, followed by cell proliferation, colony formation, soft agar and invasion assays. A549 xenograft mouse model was used to evaluate in vivo function of PTPRB. Quantitative polymerase chain reaction (PCR) was used to measure PTPRB expression in NSCLC patient samples. Kaplan Meier analysis was performed to assess association between PTPRB expression and patient overall survival (OS). Multivariate analysis was performed to evaluate prognostic significance of PTPRB. Overexpression of PTPRB reduced cell proliferation rate, colony formation efficiency, soft agar growth and cell invasion in A549 and H1299 cells, as well as tumour growth rate in A549 xenograft. Knockdown of PTPRB increased Src phosphorylation and cell invasion, which was reversed by Src inhibitor PP2. Additionally, PTPRB was down‐regulated in NSCLC patient and was associated with patient OS. PTPRB regulates Src phosphorylation and tumorigenesis in NSCLC. PTPRB may serve as an independent prognostic biomarker for NSCLC patients.     

Isolation,functional characterization,and biological properties of MCh‐AMP1, a novel antifungal peptide from Matricaria chamomilla L.

The antimicrobial activities of natural products have attracted much attention due to the increasing incidence of pathogens that have become resistant to drugs. Thus, it has been attempted to promisingly manage infectious diseases via a new group of therapeutic agents called antimicrobial peptides. In this study, a novel antifungal peptide, MCh‐AMP1, was purified by reverse phase HPLC and sequenced by de novo sequencing and Edman degradation. The antifungal activity, safety, thermal, and pH stability of MCh‐AMP1 were determined. This peptide demonstrated an antifungal activity against the tested Candida and Aspergillus species with MIC values in the range of 3.33–6.66 μM and 6.66–13.32 μM, respectively. Further, physicochemical properties and molecular modeling of MCh‐AMP1 were evaluated. MCh‐AMP1 demonstrated 3.65% hemolytic activity at the concentration of 13.32 μM on human red blood cells and 10% toxicity after 48 hr at the same concentration on HEK293 cell lines. The antifungal activity of MCh‐AMP1 against Candida albicans was stable at a temperature range of 30–50°C and at the pH level of 7–11. The present study indicates that MCh‐AMP1 may be considered as a new antifungal agent with therapeutic potential against major human pathogenic fungi.