Prominent Classes Research Articles

Counting phylogenetic networks with few reticulation vertices: A second approach

Tree-child networks, one of the prominent network classes in phylogenetics, have been introduced for the purpose of modeling reticulate evolution. Recently, the first author together with Gittenberger and Mansouri (2019) showed that the number TC ℓ , k of tree-child networks with ℓ leaves and k reticulation vertices has the first-order asymptotics TC ℓ , k ∼ c k 2 e ℓ ℓ ℓ + 2 k − 1 , ( ℓ → ∞ ) . Moreover, they also computed c k for k = 1 , 2 , and 3. In this short note, we give a second approach to the above result which is based on a recent (algorithmic) approach for the counting of tree-child networks due to Cardona and Zhang (2020). This second approach is also capable of giving a simple, closed-form expression for c k , namely, c k = 2 k − 1 2 / k ! for all k ≥ 0 .

Comparative Morpho-micrometric Investigations in Six Indigenous Ocimum Species of India with DOE Based HPTLC Method for Multi-class Component Analysis.

The Ocimum genus is one of India's prominent botanical classes of traditional medicinal culture comprising medicinally and agronomically important plants. Morphological resemblances, overlapping geographical distribution, and history of traditional nomenclature have necessitated a comprehensive qualitative report for effective quality control and removing the species ambiguity pertaining to this genus. This paper provides detailed morpho-micrometric characteristics used to differentiate between six indigenous Ocimum species of India. Among them, O. gratissimum was distinguished as the only shrub with a fleshy petiole. In green and purple forms, O. tenuiflorum leaves had serrate margins and showed no particular anatomical differences except for the anthocyanins containing epidermal cells of the latter. O. basilicum had glabrous leaves except for the veins, which were puberulous. O. filamentosum had tenuous anther filaments and was the least aromatic while O. africanum had a citrusy odour, which along with the number of xylary rows, size of mesophyll cells, and epidermal cell wall architecture, distinguished it from O.americanum. An HPTLC method was developed using experimental design and validated for quantification of multi-class compounds from terpenoic, phenolic acids, and flavonoids in Ocimum leaves. It was found linear (r 2 > 0.99) with recoveries between 95 - 100% for all compounds. The eluted bands of marker compounds were subjected to HPTLC-MS analysis as a confirmative tool. This is the first anatomical and analytical report of O. filamentosum Forssk. The obtained results could be effectively used for species identification using vegetative characters alone with the anatomical-HPTLC data backing up the former as a rapid and economical tool.

Synthesis of 2, 3-dihydroquinozoline- 4(1H) - Ones using magnetically retrievable nickel based nanocatalyst

Ferrite nanoparticles are important class of inorganic materials having wide variety of applications. Catalysis is one of the major areas where ferrite nanomaterials are employed. Photocatalysis, hydrogenation, oxidation, alkylation etc., are some of the prominent classes of chemical reactions catalyzed by ferrite nanomaterials. Here we introduce Nickel ferrite nanomaterials (NiFe2O4) synthesized by sol-gel auto combustion method as efficient and magnetically retrievable heterogeneous catalyst for the synthesis of bioactive 2, 3-dihydroquinazoline-4(1H)-ones. 2, 3-dihydroquinazoline-4(1H)-ones are biologically relevant organic species with diverse pharmacological applications including anti-tumor, antimalarial, antibacterial and antifungal properties. In this work, we have synthesized 2, 3-dihydroquinazoline-4(1H)-ones using Nickel ferrite catalyst by employing anthranilamide and aryl aldehydes as precursors in ethanol solvent. Due to significant magnetic property, the catalyst can be separated quickly and easily using a low magnetic field. Moreover, the catalyst is found to be recyclable and can be reused without appreciable loss in catalytic activity. This study highlights NiFe2O4 nanoparticles as promising catalysts for intra-molecular cyclization reactions.

Application of 1,1-ADEQUATE and DFT to correct 13 C misassignments of carbonyl chemical shifts for carbapenem antibiotics.

Prior to the development of sensitive proton-detected 2D NMR experiments, assigning 13 C signals could be a significant challenge, and mistakes have occurred even for prominent compound classes. In this study, 1,1-ADEQUATE data were used to unambiguously reassign the 13 C chemical shifts for the β-lactam carbonyl at the C-7 position and the proximal carboxylate at the C-10 position of the carbapenems, meropenem and imipenem. Density functional theory (DFT) was then investigated to provide sufficiently accurate 13 C chemical shift predictions, allowing for the carbonyl signal reassignment of thienamycin.

Surface-Based Post-synthesis Manipulation of Point Defects in Metal Oxides Using Liquid Water.

Initial synthesis of semiconducting oxides leaves behind poorly controlled concentrations of unwanted atomic-scale defects that influence numerous electrical, optical, and reactivity properties. We have discovered through self-diffusion measurements and first-principles computations that poison-free oxide surfaces inject interstitial oxygen atoms into the crystalline solid when simply contacted with liquid water near room temperature. These interstitials diffuse quickly to depths of 20 nm-2 μm and are likely to eliminate prominent classes of unwanted defects or neutralize their action. The mild conditions of operation access a regime for oxide fabrication that relaxes important thermodynamic constraints that hamper defect regulation by conventional methods at higher temperatures. The surface-based approach appears well-suited for use with nanoparticles, porous oxides, and thin films for applications in advanced electronics, renewable energy storage, photocatalysis, and photoelectrochemistry.

Biodegradable polyphosphazene – hydroxyapatite composites for bone tissue engineering

The venture to fabricate potential and functional bone regeneration, annihilating the health complexities in conventional bone grafting, made Bone tissue engineering (BTE), which facilitates meticulous control of the spatial and temporal dissemination of cells and extracellular matrix (ECM), receive incredible consideration in the past few years. Ascribable to their exceptional properties, polymers have gotten significant attention as one of the prominent classes of biomaterials for BTE. The compatible mechanical properties, biocompatibility, bioactivity, and biodegradability of polyphosphazene/hydroxyapatite composite made them candidates for functional bone regeneration. This review demonstrates the synthesis, properties, and application of polyphosphazenes, hydroxyapatite, and composite biomaterial for BTE.

Development and Dental Applications of Spiro Expanding Monomers as Antishrinkage Additives

AbstractVolumetric shrinkage is one of the main reasons cited for the failures and shortening the clinically useful life span of contemporary dental restorations. Owing to the compact and relatively more flexible cyclic structures, expanding monomers (EMs) have demonstrated essentially zero shrinkage or expansion upon polymerization. This article reviews recent studies on the new low shrinkage dental resin with spiro EMs as antishrinkage additives. This includes the most prominent classes of EMs, namely, spiroorthoesters, spiroorthocarbonates and bicycloorthoesters, along with the mechanism of expansion polymerization. A brief introduction of the development of copolymerization mechanism between EMs and dental resin is given, followed by an introduction to the cutting‐edge development and application of EMs with different side chain groups in dental materials. Furthermore, the effect of low‐shrinkage resin modified by EMs on the mechanical and biological properties was found to be within an acceptable range. The dental resins modified by spiro EMs can avoid adverse impact from the volumetric shrinkage of polymers during curing. They are materials with great potential for a variety of biomedical and clinical applications and provide guidance for the synthesis of new low shrinkage dental resin materials with good mechanical properties.

제주 고산리 돌화살촉의 분류와 계통수 분석

Phylogenetic analyses have been successfully applied to establishing lineages and trajectories of changes of archaeological materials. The present study attempts to apply principles and techniques of phylogenetics to archaeology and produce phylogenetic trees of a large collection of chipped stone arrowheads from Gosan-ri, Jeju. Recent excavations provided new lights on human occupations at Gosan-ri: radiocarbon dates and artifacts suggest that the site was formed by repeated visits of hunter-gatherers spanning almost 5000 years of the Neolithic. More than 1300 arrowheads, or points, were collected and they were made by the same chipped stone technology based on essentially same hunting and gathering way of subsistence economy with no evidence of external migration or notable diffusion. This is why we believe that a phylogenetic tree can adequately depict the persistence and change of artifact lineages. Based on paradigmatic classification using attributes and attribute states such as maximum length, morphology of haft elements, and angle of base and stem, we use PAUP* to produce workable phylogenetic trees of stone arrowhead classes. The result shows that stemmed arrowheads and those with no stem are the two most prominent classes that were likely diverged early and many varieties evolved subsequently in the branches. We also discuss the issue of homology and analogy (homoplasy) and how to distinguish the two from archaeological situations. We expect that the present endeavor will encourage future studies of reconstructing and discussing lineages based on archaeological cases by applying phylogenetic analysis.

Lipid Nanoparticles as Platforms for Theranostic Purposes: Recent Advances in the Field

Lipid nanoparticles (LNPs) are the first approved nanomedicines and the most well-studied class of nanocarriers for drug delivery. Currently, they are in the frontline of the pandemic fight as vaccine formulations and therapeutic products. However, even though they are so well-studied, new materials and new modifications arise every day that can improve their properties. Their dynamic nature, especially the liquid crystal state of membranes, is under constant investigation and it is that which many times leads to their complex biological behavior. In addition, newly discovered biomaterials and nanoparticles that possess promising effects and functionalities, but also toxicity and/or poor pharmacokinetics, can be combined with LNPs to ameliorate their properties. As a result, many promising theranostic applications have emerged during the past decade, proving the huge potential of LNPs in the field. In the present review, we summarize some of the most prominent classes of LNPs for nanotheranostic purposes, and present state-of-the-art research examples, with emphasis on the utilized biomaterials and the functionality that they confer to the resultant supramolecular nanosystems, in relation to diagnostic and therapeutic modalities. Although there has been unprecedented progress in theranostics, the translational gap between the bench and the clinic is undeniable. This issue must be addressed by experts in a coordinated way, in order to fully exploit these nanomedicines for the benefit of the society.

Learning with tree tensor networks: Complexity estimates and model selection

Tree tensor networks, or tree-based tensor formats, are prominent model classes for the approximation of high-dimensional functions in computational and data science. They correspond to sum-product neural networks with a sparse connectivity associated with a dimension tree and widths given by a tuple of tensor ranks. The approximation power of these models has been proved to be (near to) optimal for classical smoothness classes. However, in an empirical risk minimization framework with a limited number of observations, the dimension tree and ranks should be selected carefully to balance estimation and approximation errors. We propose and analyze a complexity-based model selection method for tree tensor networks in an empirical risk minimization framework and we analyze its performance over a wide range of smoothness classes. Given a family of model classes associated with different trees, ranks, tensor product feature spaces and sparsity patterns for sparse tensor networks, a model is selected (\`a la Barron, Birg\'e, Massart) by minimizing a penalized empirical risk, with a penalty depending on the complexity of the model class and derived from estimates of the metric entropy of tree tensor networks. This choice of penalty yields a risk bound for the selected predictor. In a least-squares setting, after deriving fast rates of convergence of the risk, we show that our strategy is (near to) minimax adaptive to a wide range of smoothness classes including Sobolev or Besov spaces (with isotropic, anisotropic or mixed dominating smoothness) and analytic functions. We discuss the role of sparsity of the tensor network for obtaining optimal performance in several regimes. In practice, the amplitude of the penalty is calibrated with a slope heuristics method. Numerical experiments in a least-squares regression setting illustrate the performance of the strategy.

Isolation, Structure Elucidation and Antimicrobial Evaluation of Natural Pentacyclic Triterpenoids and Phytochemical Investigation of Different Fractions of Ziziphus spina-christi (L.) Stem Bark Using LCHRMS Analysis.

Ziziphus spina-christi L. (ZSC-L) is a tree with thorny branches, belongs to the family Rhamnaceae and grows in the sub-tropics. The purpose of this research is to isolate and partially purify bioactive components from the crude ethanol extract of the stem bark of ZSC-L. Besides, bioassay-guided fractionation of ZSC-L stem bark was conducted using different solvents. The solvents were reutilized to minimize the production cost and environmental harm. In addition, the antimicrobial activities of the fractions were analyzed, followed by metabolic profiling using LC-HRMS. The n-butanol fraction showed the highest antimicrobial efficacy, so it was subjected to further purification. For the first time, two major compounds were isolated from the stem bark of ZSC-L and identified as lupane-type pentacyclic triterpenoids betulinic acid and betulin. Both compounds were used as antibacterial and anticancer agents and considered as a green product as the extraction procedure reduced the use of hazardous chemicals. Metabolic characterization of ZSC-L and its bioactive fractions were performed using LC-HR-ESI-MS and the results revealed the dereplication of 36 compounds belonging to different chemical classes. Flavonoids and triterpenes were the most prominent metabolite classes in the different fractions. The molecular docking results were obtained by studying the interaction of betulin and betulinic acid with antimicrobial receptors (4UYM, 1IYL, 1AJ2, 6J7L, 1AD4, 2VEG) to support the in vitro results. Our study highlights that Ziziphus spina-christi and its phytoconstituents, especially triterpenoids, act as a promising antimicrobial candidate in pharmaceutical and clinical applications.

Disinhibitory Circuitry Gates Associative Synaptic Plasticity in Olfactory Cortex.

Inhibitory microcircuits play an essential role in regulating cortical responses to sensory stimuli. Interneurons that inhibit dendritic or somatic integration act as gatekeepers for neural activity, synaptic plasticity, and the formation of sensory representations. Conversely, interneurons that selectively inhibit other interneurons can open gates through disinhibition. In the anterior piriform cortex, relief of inhibition permits associative LTP of excitatory synapses between pyramidal neurons. However, the interneurons and circuits mediating disinhibition have not been elucidated. In this study, we use an optogenetic approach in mice of both sexes to identify the inhibitory interneurons and disinhibitory circuits that regulate LTP. We focused on three prominent interneuron classes: somatostatin (SST), parvalbumin (PV), and vasoactive intestinal polypeptide (VIP) interneurons. We find that LTP is gated by the inactivation SST or PV interneurons and by the activation of VIP interneurons. Further, VIP interneurons strongly inhibit putative SST cells during LTP induction but only weakly inhibit PV interneurons. Together, these findings suggest that VIP interneurons mediate a disinhibitory circuit that gates synaptic plasticity during the formation of olfactory representations.SIGNIFICANCE STATEMENT Inhibitory interneurons stabilize neural activity during sensory processing. However, inhibition must also be modulated to allow sensory experience shape neural responses. In olfactory cortex, inhibition regulates activity-dependent increases in excitatory synaptic strength that accompany odor learning. We identify two inhibitory interneuron classes that act as gatekeepers preventing excitatory enhancement. We demonstrate that driving a third class of interneurons inhibits the gatekeepers and opens the gate for excitatory enhancement. All three inhibitory neuron classes comprise disinhibitory microcircuit motifs found throughout the cortex. Our findings suggest that a common disinhibitory microcircuit promotes changes in synaptic strength during sensory processing and learning.

Differential metabolome landscape of Kadsura coccinea fruit tissues and potential valorization of the peel and seed tissues

Kadsura coccinea (Lem.) is a woody wine plant with a peculiar fruit enriched in important health-promoting compounds. The non-editable part of the fruit, i.e., the seed and peel, represents more than 60% of the fruit and is considered a biowaste. This significantly restricts the development of the K. coccinea fruit industry. Clarifying the metabolic components of the different fruit parts can help to improve the utilization rate and valorization of K. coccinea. Herein, we evaluated K. coccinea fruit peel, pulp, and seed using widely-targeted metabolomics and quantified a set of 736 bioactive compounds from 11 major metabolite classes. The most prominent metabolite classes included lipids, amino acids, flavonoids, and lignans. Furthermore, our results emphasized a significant accumulation of flavonoids in pulp tissues, while alkaloids and lignans were abundant in peel and seed tissues, respectively. A total of 183 metabolites were differentially accumulated among the three tissues. Procyanidin C2, rutinoside, 2-hydroxyoleanolic acid, 5-hydroxymethyluracil, nootkatol, isoquercitrin, isohyperoside, quercetin-7-O-glucoside, hyperin, and rutin showed elevated accumulation in the peel. In the seed, kadsuralignan G, kadcoccilactone A, kadsuralignan H, lysoPE 20:5, iso-schisandrin ethyl alcohol, and kadangustin were significantly enriched. Our results highlight the diverse metabolome composition of K. coccinea fruit parts, which can be further exploited for its valorization in various industries.

Differential metabolome landscape of Kadsura coccinea fruit tissues and potential valorization of the peel and seed tissues

Kadsura coccinea (Lem.) is a woody wine plant with a peculiar fruit enriched in important health-promoting compounds. The non-editable part of the fruit, i.e., the seed and peel, represents more than 60% of the fruit and is considered a biowaste. This significantly restricts the development of the K. coccinea fruit industry. Clarifying the metabolic components of the different fruit parts can help to improve the utilization rate and valorization of K. coccinea. Herein, we evaluated K. coccinea fruit peel, pulp, and seed using widely-targeted metabolomics and quantified a set of 736 bioactive compounds from 11 major metabolite classes. The most prominent metabolite classes included lipids, amino acids, flavonoids, and lignans. Furthermore, our results emphasized a significant accumulation of flavonoids in pulp tissues, while alkaloids and lignans were abundant in peel and seed tissues, respectively. A total of 183 metabolites were differentially accumulated among the three tissues. Procyanidin C2, rutinoside, 2-hydroxyoleanolic acid, 5-hydroxymethyluracil, nootkatol, isoquercitrin, isohyperoside, quercetin-7-O-glucoside, hyperin, and rutin showed elevated accumulation in the peel. In the seed, kadsuralignan G, kadcoccilactone A, kadsuralignan H, lysoPE 20:5, iso-schisandrin ethyl alcohol, and kadangustin were significantly enriched. Our results highlight the diverse metabolome composition of K. coccinea fruit parts, which can be further exploited for its valorization in various industries.

Leaf morphology, wax composition, and residual (cuticular) transpiration of four poplar clones

Key messageWe identified two poplar clones of the same species as highly comparable, yet clones of two further species of the same genus to be distinctly different regarding multiple morphological and ecophysiological traits.Leaf morphology, wax composition, and residual (cuticular) transpiration of four poplar clones (two clones of the hybrid species P. × canescens, P. trichocarpa, and P. euphratica) were monitored from the beginning to end of the growing season 2020. A pronounced epicuticular wax coverage was found only with P. euphratica. As the most prominent substance classes of cuticular wax primary alcohols, alkanes and esters were identified with P. × canescens and P. trichocarpa, whereas esters and alkanes were completely lacking in P. euphratica. Wax amounts were slightly decreasing during the season and significantly lower wax amounts were found for newly formed leaves in summer compared to leaves of the same age formed in spring. Residual (cuticular) transpiration was about five to tenfold lower for P. × canescens compared with the two other poplar species. Interestingly, with three of the four investigated species, newly formed leaves in summer had lower wax coverages and lower rates of residual (cuticular) transpiration compared to leaves of exactly the same age formed in spring. Our findings were especially surprising with P. euphratica, representing the only one of the four investigated poplar species naturally growing in very dry and hot climates in Central Asia. Instead of developing very low rates of residual (cuticular) transpiration, it seems to be of major advantage for P. euphratica to develop a pronounced epicuticular wax bloom efficiently reflecting light.

The Influences of Loaded Words in Tragic News Headlines on Readers’ Emotions

In tragic news, the use of loaded words is one prominent device in constructing effective news headlines to draw interests and provoke readers’ emotions (Clark, 2007). Nevertheless, with a dearth of research studies in this phenomenon, the aims of this qualitative study are to investigate 1) what word classes of loaded words are found in tragic news headlines, and 2) how these loaded words provoke emotions and reactions in news readers. First, 180 tragic news headlines were purposively selected from all news headlines on nine websites between July to October 2019 and analyzed. The findings revealed that nouns and verbs were the two most prominent word classes used as loaded words (48.18% and 33.64%, respectively). Moreover, these loaded words were found at both word and phrase levels. Second, to explore news readers’ emotions, the two main instruments were used: 1) online questionnaire with 20 news headlines were uploaded, finally, 52 male and female respondents from 22 countries participated and 2) semi-structured interview with 4 (7.69%) interviewees was conducted with another 20 news headlines to explore more in-depth responses. Their overall reflections revealed that, with the impacts of loaded expressions, four related main factors helped provoke their emotions: 1) strong emotive meanings of loaded words, 2) textual context of a news headline, 3) news readers’ experiences, and 4) news readers’ cultural and social backgrounds. Overall, this seems to suggest that not the use of loaded words alone is a prominent language device in creating enough impacts in writing news headlines, but textual and socio-cultural contexts also play essential roles in provoking their emotions and influencing further reactions. That is, news writers should be aware that integrating these strategies together is very important in writing news headlines.

An Optimistic Security Model for Improving Cyber Security Using Adaptive Algorithms to Prevent SQL Injection Attacks

Throughout today's economic and social life, the use of web-based services (such as e-commerce, online banking, and web-based communications, to name a few) has become a common habit. Countless applications operate worldwide on millions of servers, and their numbers are steadily increasing. It has become a focus of attackers and hackers for the attacks because of the huge growth of internet usage. It is necessary for all companies to develop and protect their applications in order to maintain their credibility and keep their products relevant for users. Web applications have brought in new classes of computer security vulnerabilities, such as SQL injection (SQLIA), and it has exceeded previously prominent vulnerability classes in recent years. SQL injection is the instance of the broader class of vulnerabilities that are based on input validation. The primary purpose of this research is to study the vulnerabilities of SQL injection and to propose an optimistic security model for secure data transmission. In this work, the authors proposed an adaptive algorithm to prevent SQL injections.

Voltammetric studies of selected porphyrin G-quadruplex ligands and their interaction with DNA in solution and at the mercury electrode surface

With the increasing interest in DNA G-quadruplexes (G4) as important regulatory elements and prospective therapeutical targets, DNA structure-sensitive electrochemical methods can be advantageously used for studying of their structure or screening for interactions with G4 ligands developed as candidate drugs. Porphyrin derivatives are among the most prominent classes of G4 ligands. Interactions of porphyrins H2-TMPy2PP and Cu-TMPy2PP with oligodeoxynucleotides (ODNs) either forming or not forming G4 were investigated in this work. For this purpose, cyclic voltammetry at hanging mercury drop electrode (HMDE) complemented by UV-vis and CD spectroscopy was applied. Both porphyrins were found to interact strongly with G4 in solution by UV-vis titrations. However, Cu-TMPy2PP appears to interact also with double-stranded and single-stranded ODNs. Accordingly, cyclic voltammetry was able to distinguish between free and ODN-bound forms of Cu-TMPy2PP, but not between binding of the ligand to ODNs with or without G4 propensity.

Rage Against the Mean – A Review of Distributional Regression Approaches

Distributional regression models that overcome the traditional focus on relating the conditional mean of the response to explanatory variables and instead target either the complete conditional response distribution or more general features thereof have seen increasing interest in the past decade. The current state of distributional regression will be discussed, with a particular focus on the four most prominent model classes: (i) generalized additive models for location, scale and shape, (ii) conditional transformation models and distribution regression, (iii) density regression, and (iv) quantile and expectile regression. Characteristics of the different distributional regression approaches will be provided to establish a structured overview on the similarities and differences with respect to the required assumptions on the conditional response distribution, theoretical properties, and the availability of software implementations. In addition, challenges arising in the interpretability of distributional regression models will be discussed and all four approaches will be illustrated with an application analyzing determinants of income distributions from the German Socio-Economic Panel (GSOEP).

Nonurgent Patients' Preferences for Emergency Department Versus General Practitioner and Effects of Incentives: A Discrete Choice Experiment.

Objective. This study investigates potential of a new financial incentive policy, the GP-referral discount scheme introduced in Singapore, in reducing nonurgent emergency department (ED) visits, and compares it with alternative interventions. Methods. A discrete choice experiment (DCE) was designed to elicit patients’ preferences for ED and general practitioner (GP) under hypothetical nonurgent medical conditions. Through latent class multinomial logistic regression, choice models were estimated to quantify how patients’ choices are influenced by GP-referral discount, other ED/GP attributes (waiting time, test facilities, and payment), patient demographics, and their perception of severity. The choice models were used to predict uptake of the GP-referral discount scheme and other countermeasures suggested by these models. Results. Survey responses from 849 respondents recruited from a public hospital in Singapore were included in the study. The choice model identified two prominent classes of patients, one of which was highly sensitive to GP-referral discount and the other to test-facility-availability. Patients’ perceptions of severity (“critical” v. “not critical” enough to go to ED directly) were highly significant in influencing preference heterogeneity. Predictive analysis based on the choice model showed that GP-referral discount is more effective when patients visit ED expecting “shorter” waits, as opposed to test-facility provision at GPs and perception-correction measures that showed stronger effects under “longer” expected waits. Conclusions. The new GP-referral financial incentive introduced in Singapore can be effective in reducing nonurgent ED visits, if it reasonably covers the (extra) cost of visiting a GP. It may serve as a complement to test-facility provision at GPs or perception-correction measures, as the financial incentive and the latter two measures appear to influence distinct classes (discount-sensitive and facility-sensitive) of patients.