Aromatic white wines contain monoterpenes that can alter aroma qualities based on their concentration and enantiomeric ratios. Limonene has been identified as a monoterpene that is used to differentiate monovarietal white wines. The aim of this study was to evaluate the influence of limonene on aroma perception at different enantiomeric ratios. Its interaction with linalool and α-terpineol compounds was also investigated. Eighteen model wines were created with different ratios and/or concentrations of limonene and diverse concentrations of linalool and α-terpineol. Triangle tests, check-all-that-apply (CATA) and descriptive analysis were used to evaluate the aroma of the wines. Results show that different limonene ratios had no influence on wine aroma. Descriptive analysis showed that the addition of only limonene influenced citrus characteristics depending on the concentration. Linalool addition did not alter aroma quality when the limonene was at low concentrations, but it did change aroma perception at high limonene levels. α-Terpineol only altered the aroma of the wine at medium and high concentrations. At high concentrations, linalool and α-terpineol presented tropical aromas with some floral notes, irrespective of limonene levels. Depending on the desired aroma qualities of the wine, altering the monoterpene content resulted in very different aromatic wines. Monoterpenes are volatile compounds found in grapes and are fundamental aroma compounds for varietal wines such as Muscat, Riesling, Chardonnay, Pinot gris, and Gewürztraminer ,2,3. TheIn wines, the effect of combining such a large variety of aroma compounds makes differentiating the causes of specific aromas a complex process. The high degree of complexity has kept much of the research on aroma causes in wine focused on individual aroma compounds rather than their combined perceptions . The infChemical composition and aroma perception have also been major research focuses for their potential impacts using odor activity values (OAV) or the aroma thresholds of compounds . OAVs alPinot gris is an aromatic wine originating from France and typically has honey and apricot aromas ,14. ManyThe objectives of this research were: (1) to evaluate the sensory perception of four ratios of limonene to assess its aroma quality differences and (2) to obtain the aroma quality of limonene when in mixtures with other monoterpenes . This work focuses on expanding our understanding of how monoterpenes influence the aroma perception of white wine. By understanding the causes of specific aroma qualities, it will be possible to determine how viticultural and winemaking processes may alter those qualities in future research.The following chemical standards were used in the aroma base and were obtained from Sigma-Aldrich Co. : ethanol (≥99%), 2,3-butanedione (97%), hexan-1-ol (98%), methionol (≥98%), butanoic acid (≥99%), decanoic acid (≥98%), 2-methylpropanoic acid (99%), 2-methylbutanoic acid (98%), 3-methylbutanoic acid (99%), 2-methylpropyl ethanoate (≥97%), ethyl phenylacetate (≥99%), ethyl 3-methylbutanoate (98%), ethyl 2-methylpropanoate ((≥98%), ethyl 2-methylbutyrate (99%), ethyl butanoate (≥98%), ethyl decanoate (≥99%), ethyl hexanoate (≥99%), ethyl octanoate (≥98%), hexanoic acid (99%), octanoic acid (≥99%), 2-methylpropan-1-ol (≥99%), ethyl acetate (≥99%) and isoamyl acetate (≥99%). Acetic acid (≥99%) was obtained from VWR International . The terpenes compound added to the model wine for the treatments were: (S)-(−)-limonene (96%), (R)-(+)-limonene (97%), linalool (≥97%) and α-terpineol, which were purchased from Sigma-Aldrich Co. .−1. Wines with resin were stirred for 24 h before filtering out the resin. Dearomatized wines were checked using GCMS prior to use to ensure aroma compounds were removed. Dearomatized wines were stored in stainless ball lock kegs  sparged with nitrogen at 4 °C for later use.Wine aroma compounds were removed using two methods. Aroma compounds were removed from the wine as described by Tomasino et al. . LiChrolA week prior to sensory analysis, the aroma base  was addeStock standard solutions of all chemicals used in the aroma base and wine models were prepared as described by Chigo-Hernandez et al. . ConcentAll sensory analysis was approved by the Oregon State University Internal Review Board #8606). Panelist inclusion criteria, room parameters and software are the same as described in Chigo-Hernandez et al. . The. The7]. From the CATA2 results, 13 aroma descriptors were selected for further descriptive analysis using line scales. Attributes with their training standards and images used in training can be found in Triangle tests, CATA and PCA results were calculated as described in Chigo-Hernandez et al. .Limonene has been found in Pinot gris at different ratios; this is an important aspect to investigate since the variation in enantiomers percentages can lead to a diversity of aroma perceptions when in combination with other mixtures ,7. Four CATA was specifically used to determine aromas for further descriptive analysis investigating the intensities of specific aromas. The original compound concentrations used for CATA1 showed no statistical significance. The fact that the concentrations used in CATA1 showed no sensory differences suggests we did not reach the differential or perception thresholds for these compounds, as stated above for triangle tests .It was not until the concentrations were increased in CATA 2 that aroma perception differences were achieved. The increased concentrations are still within those measured in Pinot gris wines . The resThe first three variates of correspondence analysis explained 50.28% of the total variance . Based oDifferences were found between the model wines; the first two variates of discriminant analysis explained 43% of the total variance. A third dimension was included to increase the total variance to 58.7%. Based on the Scree plot for the analysis, additional dimensions did not add greatly to the total variance after the 3rd dimension. The wine models were classified into three clusters, using K-means clustering , althougAlong F1 and F2, the blue cluster sits between multiple vectors, suggesting some floral, dried fruit and lemon aromas. By incorporating F3, it appears that model 9 is characterized by a lime aroma and models 6 and 18 by a melon aroma. While models 7, 11, 13 and 15 are in one cluster (green), models 7 and 13 are characterized more by lavender and honeysuckle aromas and models 11 and 15 by grapefruit, tropical fruit and some lilac aromas. By incorporating F3, it appears that models 15 and 13 are more associated with floral and tropical fruit aromas and models 11 and 7 also have rose and lime characteristics. The orange cluster, with the greatest number of models, is characterized by ginger, stone fruit, pome, and dried fruit aromas. These same descriptors are associated with the models when including F3.To compare the different wine models, it is important to take the results across the three dimensions into consideration. The aroma base model (model 18) has clear lemon and melon notes, and when both low and high concentrations of limonene (models 5 and 9) are present, citrus aromas (lime and lemon) are dominant. This suggests that the addition of limonene does alter the aroma away from melon to more dominant citrus aromas. This was anticipated as limonene is found in the peel of citrus fruits , and it By comparing model 7 and model 17, it can be seen that the addition of limonene to the same concentration of α-terpineol shows a shift from pome, lime, and dried fruit aromas to more floral and grapefruit aromas. An increase in the concentration of limonene to high levels when the concentration of α-terpineol is reduced does not result in a change in aroma since models 7 and 11 are in the same cluster across the three dimensions. It is when α-terpineol is increased to high concentrations (model 14) does the aroma alter to ginger, lime and dried fruit. These are the aroma descriptors for α-terpineol in F3 (model 17), indicating that high limonene concentration increases these aromas. α-Terpineol on its own is associated with lilac aromas , which wThe wine model with linalool at medium concentrations presented ginger aromas. This is interesting since linalool, in combination with geraniol, are the main aroma compounds associated with ginger . The addWhen all three compounds are found together, models 8, 12 and 15, several things can be noted. When both α-terpineol and linalool are in combination with limonene but at low and medium concentrations, the aromas are similar as they are found in the same cluster. When all compounds are at high concentrations, tropical fruit, lilac and honeysuckle aromas are noted. This is interesting as these compounds are not traditionally thought to cause tropical fruit aromas. As stated previously, linalool and α-terpineol are associated with floral aromas, and they are most likely contributing to the lilac and honeysuckle aromas noted in this study . AlthougThis work has shown that the different enatiomer ratios of limonene do not alter the aroma of Pinot gris wine at concentrations measured in these wines. Additionally, limonene only contributes to the aroma perception of Pinot gris wines when other monoterpenes are found at low or medium concentrations. Once linalool and α-terpineol are found at higher concentrations, they mask any aromas that are caused by linalool. The information in this work helps to provide an understanding of how aroma chemical data can be interpreted, as well as providing additional support that high concentrations of linalool and α-terpineol in combination are a cause of tropical fruit aromas in white wines. Understanding the causes of specific aroma qualities will allow winemakers to choose the process to achieve their desired qualities for their wine process.


Tamarix articulata (TA) extract against toxicity induced by beauty products in skin fibroblasts (Hs27). MTT and Crystal violet (CV) assays were used to determine the dose-dependent cytotoxic effects of beauty products against Hs27 fibroblasts. DNA fragmentation assay and annexin-V staining were conducted to determine the mode of cell killing induced by evaluated beauty products. Quantification of reactive oxygen species (ROS) and antioxidant enzyme levels were used to evaluate the oxidative stress. Chemical analysis and heavy metals were evaluated to determine beauty products. Pre-treatment with TA extract for different time points followed by time-dependent exposure with beauty products to assess the protective effect of TA extract in Hs27 cells was analyzed by MTT and CV assays. Owing to the presence of various harmful heavy metals such as arsenic (As), chromium (Cr), cadmium (Cd), nickel (Ni), and lead (Pb) in beauty products, our results revealed that all beauty products induce significant cytotoxicity over time  in a dose-dependent  manner. DNA fragmentation assay, quantification of apoptosis by annexin-V staining, determination of ROS and antioxidant enzymes  revealed that the induced cytotoxicity was caused by oxidative stress-mediated apoptosis. However, pre-incubation with a safe dose (50 μg/mL) of TA for different times  followed by exposure to various doses  of beauty products for different times  revealed significant  protection against beauty product-mediated cytotoxicity. The effect was more pronounced for 1 h exposure to beauty products compared to 4 h. Our study demonstrates that the due to the presence of heavy metals in synthetic beauty products exhibit marked toxicity to skin fibroblasts due to oxidative stress-mediated apoptosis. However, the presence of abundant bioactive polyphenols with promising antiscavenging activity in TA extracts significantly nullifies cytotoxicity promoted by examined beauty products in skin fibroblasts (Hs27).The current study evaluates the cytotoxicity, mode of cell death and chemical analysis of selected beauty products and evaluation of the protective effect of  Skin is the largest, fast-growing organ and covers externally the whole human body to regulate body temperature, while fluid balance restricts the dangers posed by agents including chemicals, microbes, and protects against harmful sunlight-driven ultra-violet (UV) radiation. Besides protecting from various mechanical and harmful chemicals, skin provides thermoregulation, sensing stimulation, vitamin D synthesis as well as immune surveillance and provides personal identity thereby reflects social interference among individuals of a society . WhereasBeauty products comes in existence the date human civilization comes in the world . CurrentTamaricaceae is Tamarix articulata (TA). Phytochemical analysis revealed that the TA extract is rich in polyphenolic compounds which display promising pharmacological activities. TA is a halophytic plant abundantly found in the deserts of Saudi Arabia. Traditionally, TA has been used as a folk medicine by a tribal population–the Tafilalet in Morocco—against various ailments including skin diseases [Before the emergence of synthetic cosmetic products, natural ingredients derived from plant sources are used as beauty products in many societies. Consumers in the present scenario are more concerned about their health, thus demanding and advocating incorporation of bioactive natural constituents in cosmetic and beauty products for the betterment of their health . Owing tdiseases . Owing tdiseases –17. WithTamarix and species: Tamarix articulata was collected in August 2019 from the deserts of Qassim province in the Kingdom of Saudi Arabia. A methanolic extract derived from the dry leaves was prepared as per the standard protocol published in our previous work [The plant material TA is scientifically well characterized belongs to clade: angiosperms, order: Caryophyllales, family: Tamaricaceae, genus: ous work . After cTA plant parts  were used in this study and were collected in December 2019 from the Qassim region of Saudi Arabia along with dried leaves found on the ground . The ideLiquid chromatography-mass spectrometry (LC–MS) was carried out as described in our recently published studies , 25, 26.A total of six beauty products (lipstick products)—three beauty products from famous brands Huda Beauty, Revlon, and Maybelline (Saudi market–August-2019) and other three are unbranded—were collected from a local market. Beesline lipstick product served as the standard sample (made in Lebanon) which is tested and devoid of heavy metals and other deleterious chemicals. The ingredients of Beesline lipstick are carnauba wax, beeswax, wheat germ oil, carrot, sweet almond oil, honey, and vitamin E. The analyzed original brand lipstick samples were manufactured in Italy, USA, and Paris, while the unbranded lipstick products taken from the market have unknown manufacturer source. The prices of the original brand lipstick samples ranged from $28.00 to $11.37 USD per sample, while the unbranded samples ranged from $3.00 to $2.00 USD. All the samples were transferred to the laboratory for the analysis of their cytotoxicity and heavy metals.All beauty product samples including standard sample (100 mg/mL) were dissolved in methanol and heated to 50 °C. The mixture is filtered in hot condition through 20 μm sterile cell culture filter membrane (Millipore) to obtain a clear sterile solution as filtrate. Each lipstick filtrate was diluted 100 times before the experiment in cell culture media to avoid any toxicity induced by methanol. The mixture was filtered by using sterile 20 μm filtered membrane to avoid any contamination to skin fibroblasts (Hs27 cells) used for experiments.The cell culture media Rosewell Park Memorial Institute (RPMI)-1640, antibiotics (penicillin-streptomycin), phosphate-buffered saline (PBS), and fetal bovine serum (FBS) were procured from Invitrogen. DNA fragmentation assay kit, annexin V FITC kit, ROS kit, GSH-Px, CAT, SOD and MTT were procured from Abcam. All other reagents and chemicals required for assays were purchased from Sigma-Aldrich.2 incubator in sterile tissue culture T75 flasks. Hs27 cells were periodically checked for Mycoplasma contamination.Human skin fibroblast cell line Hs27 cells were procured from ATCC. The cell line was maintained in culture media -1640) supplemented with 10% FBS and 1% penicillin-streptomycin to avoid any bacterial contamination. The cells were grown and incubated in a 5% humidified CO4 cells per well and incubated in a 5% humidified CO2 incubator at 37°C. Next morning culture media was aspirated from each well of the microplate and replaced with fresh media containing varying doses  of beauty products, previously dissolved in cell culture media to decrease the concentration of methanol to avoid any toxicity effect induced by methanol for 1, and 4 h to determine cytotoxicity along with vehicle control to nullify any toxicity effect induced by methanol. However, for protection assay Hs27 cell after overnight incubation, cells adhered in wells of the 96-well microplate were preincubated with non-toxic doses (50 μg/mL) of TA extract for different times . This was followed by exposure to varying doses  of beauty products for 1 h and 4 h to determine the level of protection against beauty product-induced cytotoxicity.Human skin fibroblasts Hs27 cells were cultured overnight to adhere to the surface of a flat bottom 96-well microplate at a density of 104 Hs27 cells were seeded per well in the 96-microplate well which allowed the cells to adhere to the microplate’s bottom surface. The culture media in each well was aspirated and had fresh media added to it, containing varying doses of beauty products  and a non-toxic dose of TA extract (50 μg/mL) for different times  and , respectively. Following the completion of times, the wells containing cells incubated with 20 μl MTT dye (2.5 mg/mL) for 3–4 h at 37°C in 5% CO2 incubator. The formazan crystals formed during incubation were dissolved in DMSO (150 μl) by gentle vortex to ensure complete dissolution. The purple-colored solution formed in each well was measured at 570 nm by multiplate reader.The cell viability of human skin fibroblasts Hs27) was determined by MTT assay as per the standard protocol [ was dete4 cells were seeded in each well of the 96-microplate well to determine cell viability utilizing CV assay. After overnight incubation to the cells and properly adhering to the bottom surface of the plate well, Hs27 skin fibroblasts were exposed to different concentrations of beauty (lipstick) products for varying times (1 and 4 h). The cells in each well were washed with PBS gently and then incubated with 50 μL of 0.5% CV solution in methanol for 10 min at room temperature. The wells of the 96-microplate well plate was washed with distilled water and then air-dried. After the plate wells were air-dried 50 μL distaining solution (33% acetic acid) was added. The blue color solution thus obtained was measured by multiplate reader at a wavelength of 570 nm.Briefly, 103 and HClO4  were adjusted so that they could digest the lipstick samples [The sample preparation for heavy metal analysis was done according to the standard method , 29 by u samples . All the6 Hs27 cells were exposed to certain doses (250 and 500 μg/mL) of beauty products for 4 h and then harvested. DNA isolation of treated cells was done as per the manufacturer’s instructions stated in Apoptosis DNA Ladder Assay kit purchased from Abcam. After the isolation of genomic DNA from cells exposed to varying doses of beauty products, the samples from each treatment were resolved and analyzed by 2% agarose gel electrophoresis containing ethidium bromide (EtBr). After resolving was completed the agarose gel was analyzed by gel doc to generate an image.The assay served to determine whether the cytotoxicity induced by beauty products was due to apoptosis or necrosis. Briefly, 0.5 ×106 cells were plated in each well of 6-well plates which contains sterile coverslips to allow cells grow on coverslips. Upon treatment with a beauty product along with positive control H2O2 and untreated control for 4 h, Hs27 cells were incubated with DCFH-DA (10 μM) at 37°C for 30 min in the dark. Next cells were washed in PBS and were first taken for absorbance at 485/535 nm and later accumulation of ROS in treated cells were viewed by fluorescence microscope  for images.Detection and quantification of ROS using DCFH-DA dye as described previously . A stabl6 Hs27 cells were seeded in each well of a 6-well plate and allowed to adhere to the bottom surface of the well overnight at 37°C. The next morning, cells were exposed to beauty products and camptothecin (10 μM) as positive control alone, along with untreated control, for 4 h. Treated cells were harvested, washed with PBS, and subjected to Annexin V FITC/PI staining as per manufacturers protocol and were analyzed using BD Aria II flow cytometry.Detection and quantification of apoptotic cells were analyzed by using Annexin V and FITC apoptosis detection kit. As per the manufacturer’s instructions, briefly 0.5 ×105 Hs27 cells were seeded in each well of a 12-well plate and allowed to adhere to the bottom surface of the well overnight at 37°C, followed by treatment with beauty products for 4 h. After the treatment, Hs27 cells were harvested by cell scraper and washed with pre-cooled PBS followed by centrifugation and resuspension in distilled water. Resuspended cells were subjected to sonication for 15 seconds after every five second pause at 4°C followed by centrifugation at 14000 rpm for 10 min. The supernatant thus obtained was subjected to protein estimation by the Bradford method. After protein quantification from each beauty product treated cell sample aliquot were used to estimate glutathione peroxide (GSH-Px), superoxide dismutase (SOD), and catalase as manufactures protocol purchased from Abcam.For the measurement of oxidative stress markers, briefly 1.0 ×10All the experiments reported in the current study were done in triplicate. The results of the current study were calculated, processed by one-way ANOVA, and represents the mean of ± SEM. Statistical analysis was performed using GraphPad Prism software version 8, and a p-value of <0.01 was considered significant.Liquid chromatography-mass spectrometry (LC–MS) was carried out as described in our recently published studies , 25, 26.in-vitro skin cellular model (Hs27 cells). The MTT assay evaluated the cell viability against varying doses of beauty products. After seeding, Hs27 cells at a density of 104 cells per well were put into 96-well microplates and allowed to adhere properly to the bottom surface overnight at 37°C in a 5% humidified CO2 incubator. Hs27 cells in the 96 wells were exposed to varying doses  of beauty products for a period of  along with untreated control and a standard compound 16, which is known to exert an insignificant cytotoxic effect on human skin fibroblasts due to the absence of heavy metals and other toxic chemicals.The cytotoxic effects of beauty products were determined by the MTT assay against the p ≤ 0.05) was induced by beauty products at all doses and time points  after the treatment when compared with untreated control and a standard compound 16. The latter revealed less cytotoxicity (Our MTT assay results demonstrate that significant cytotoxicity (toxicity . To veritoxicity . Togethe2O2 as a positive control and untreated control as a negative control. We observe significantly intense DCFHDA fluorescence of Hs27 cells exposed to beauty product samples compared to standard sample No 16 (Beesline lipstick product) and untreated cells. However, positive control H2O2-treated Hs27 cells were markely more intense DCFHDA staining when compared to control untreated Hs27 cells  of personal care products for 4 h along with untreated control and positive control camptothecin (10 μM) to analyze the mode of cell death in Hs27 cells. We executed DNA fragmentation assay by gel electrophoresis which is one of the most reliable methods for detecting apoptosis. Our results reveal that after resolving genomic DNA by electrophoresis in 1% agarose gel a smear pattern appeared, and no DNA ladder formation appeared in cell extract samples exposed to larger doses  of beauty products. Nonetheless we observed a clear DNA ladder formation pattern in a lane of cell extract exposed to positive control camptothecin (10 μM) . These fTo further investigate the mechanistic evaluation of cell death in beauty product-treated Hs27 cells, we performed an annexin-V FITC assay for the quantification of apoptotic cells. A significant increase in apoptotic cell population was observed in Hs27 cells treated with beauty products  when compared with untreated control (3.99%) . Howeverbeauty products by the ICP-OES system, our results revealed that a small concentration of all five heavy metals was not only present in the fake beauty products (lipstick) but also in the branded ones , cadmium (Cd), chromium (Cr), lead (Pb), and nickel (Ni)—were performed using concentrated perchloric and nitric acid (1:4 ratio) to analyze these heavy metals. After analyzing the ded ones , yet theOwing to the presence of various polyphenols and flavonoid compounds that possess promising antioxidant properties, numerous plant products when combined with synthetic beauty products prevent the formation of ROS and other adverse effects on skin fibroblasts. We intended to determine whether TA extract could offer protection against beauty products-induced cytotoxicity to skin fibroblasts Hs27. To do this, we preincubated skin fibroblasts Hs27 with a safe dose (non-toxic) dose of TA extract (50 μg/mL) for different lengths of time , followed by exposure to varying doses  of beauty products for different times . This was done to evaluate how well TA protects against cytotoxicity induced by the examined products.Our results revealed that TA extract significantly protects skin fibroblasts against the toxicity induced by all doses of beauty products at both times  . HoweverExposure to numerous environmental pro-oxidants such as pollutants, radiation, chemicals, drugs, and cosmetic products causes oxidative stress in human beings, specifically at the cellular level in various organs including the skin and liver . These pTherefore, we set out to evaluate the chemical composition, cytotoxicity induced by beauty products against Hs27 skin fibroblasts as well as ROS-mediated oxidative stress and associated cell death. Our results revealed that a significant amount of cytotoxicity was induced by examined products when Hs27 skin fibroblasts were exposed to higher doses of the beauty products for 1 and 4 h. Under normal circumstances skin fibroblasts have a good enough antioxidant system to neutralize ROS species . HoweverTo analyze the chemical analysis of the selected products, our results revealed that the cell-killing induced was due to the presence of a collective concentration of heavy metals in personal care products. Previous reports suggest that the toxicological data of some chemical compounds such as benzalkonium chloride and diazolidinyl urea induces cytotoxicity and activates ROS-mediated mitochondrial-dependent apoptosis in cells , 39. AvoChemical and heavy metal analysis is currently an important parameter for establishing the safety of cosmetic products . AlthougIntriguingly, our results revealed that negligible As was detected in beauty products investigated in the current study. Cd is another heavy metal found in beautyproducts and long-term exposure to these products causes serious damage to kidneys. The concentration of Cd in the samples ranged from 1–9 ppb which is well below the desired concentration . Cr and Products contain natural ingredients consisting of plant extracts, fruits, etc., that are rich in polyphenols and terpenes which act as antioxidants. The primary function of these compounds is to neutralize free radical species such as ROS, RNS, etc., and maintain the cell integrity free from any oxidative stress . MechaniOwing to the presence of abundant polyphenols and flavonoid compounds in TA extract, we intended to evaluate the protective effect of TA extract in Hs27 skin fibroblasts against the toxicity induced by beauty products. Our results demonstrated that preincubation with a non-toxic dose of TA for different periods of time  followed by exposure to various doses  of beauty products for 1 h and 4 h, indicated significant protection against beauty product-mediated cytotoxicity. The effect was more pronounced with 1 h exposure to beauty products when compared to 4 h. Together, these results suggest that the presence of abundant bioactive polyphenols with promising anti-scavenging activity in TA extracts significantly nullifies cytotoxicity promoted by personal care products in skin fibroblasts.This study has demonstrated that synthetic beauty products (lipstick products) exhibit significant cytotoxicity against in-vitro cellular model Hs27 fibroblasts. The toxicity to the in-vitro skin fibroblast model by synthetic products was due to the collective effect of traces of heavy metals present in beauty products. It is confirmed here that the cytotoxicity induced by the examined products was due to oxdative stress-mediated apoptosis. Additionally, we observe TA extract, which is rich in antioxidant compounds, offers a protective effect and neutralizes any toxicity of skin fibroblasts induced by beauty products. Owing to the presence of toxic chemicals and heavy metals that trigger various adverse effects on the skin and other vital organs, there is an urgent need to assess the safety of beauty products. This can be done by incorporating natural plant extracts into the formulations of beauty products to neutralize any adverse effects.S1 File(DOCX)Click here for additional data file.S1 Raw image(PDF)Click here for additional data file.


Additionally, we observed an increase in the abundance of numerous bacterial genera under high protistan pressure. Our findings provide empirical evidence that protistan predation significantly promotes antibiotic resistance in soil bacterial communities and advances our understanding of the biological driving forces behind the evolution and development of environmental antibiotic resistance.Understanding how antibiotic resistance emerges and evolves in natural habitats is critical for predicting and mitigating antibiotic resistance in the context of global change. Bacteria have evolved antibiotic production as a strategy to fight competitors, predators and other stressors, but how predation pressure of their most important consumers  affects soil antibiotic resistance genes (ARGs) profiles is still poorly understood. To address this gap, we investigated responses of soil resistome to varying levels of protistan predation by inoculating low, medium and high concentrations of indigenous soil protist suspensions in soil microcosms. We found that an increase in protistan predation pressure was strongly associated with higher abundance and diversity of soil ARGs. High protist concentrations significantly enhanced the abundances of ARGs encoding multidrug ( Antibiotic resistance represents one of the most significant global health challenges of the 21st century, with the worldwide spread of antibiotic resistance potentially causing up to 10 million deaths by 2050 if timely action is not taken . Soils, In natural habitats, bacteria face a wide range of biotic and abiotic stressors including competition, predation and changes in abiotic environmental conditions  , 7. SincTo test our hypothesis, we assessed the influence of soil protists on the ARGs and bacterial community by establishing soil microcosm incubations using isolated indigenous protists (a size range of 1.2–5.0 µm) and bacterial communities. We collected the indigenous bacterial and protist communities from a forest soil that had limited anthropogenic disturbance using a filtration approach. We then established the soil microcosms by inoculating a gradient of three protist concentrations  into sterilized indigenous soils for a period of 90 days Fig. . We usedWe collected forest soil samples from Bunyip State Park (37°58'59.7“S 145°38'48.4“E), Victoria, Australia, at a depth of 0–10 cm, which served as a presentative sample of natural soils with minimal human impacts. Soil samples were transported on dry ice to the laboratory and were divided into three portions for microbial filtration, soil physicochemical analysis and soil microcosm incubation. All soil samples were sieved through a 2 mm mesh to remove roots, plant residues, macrofauna and stones before analysis of soil basic properties . The forg for 10 min, and collected the supernatants to obtain a mixture of protist and bacterial suspension and only bacterial suspension, using a series of filtration steps . Se. Se16].  results . The relThe absolute abundance  of 18S rRNA genes (protists) and 16S rRNA genes (bacteria) across different time points  was quantified by qPCR using the qPCR primer sets including TAReuk454FWD1/TAReukREV3 , 20. TheBacterial and protist communities in raw soil (three replicates) before the incubation and soil samples collected during the incubation were characterized using the primer sets 515 F/806 R  and TARehttps://cytoscape.org/). The number of unique and shared ARGs was calculated and visualized using the package “VennDiagram” [p < 0.05) in SPSS (version 28.0.1.1). Two-way ANOVA was performed to evaluate the effects of different factors  on the abundance and number of ARGs, as well as the bacterial community composition and diversity.Most of graphs in this study were visualized using the “ggplot2”  and “VenDiagram” . The bacDiagram” . The comp < 0.01) was confirmed using the “A3” package in R. The co-occurrence network analysis was constructed based on Spearman’s correlation with correlation coefficients of ≥ 0.3 and ≤ −0.3  among affected ARGs, protist and bacterial genera across all samples. This analysis included three replicates per treatment, resulting in a total of 15 replicates at five time points, and then visualized in Cytoscape [p < 0.001).To assess the importance of protist concentrations and community composition on bacterial communities and sampling time in shaping the bacterial composition and number of ARGs, random forest modellings with 5,000 trees per model was performed using the “randomForest” package . The sigytoscape . To unraActinobacteria across all treatments like the raw soil  such as Mycobacterium, Nocardia and Streptomycetaceae . The ARG richness was enhanced over the incubation time, compared to day 0 . In high protist treatments, the abundances of genes encoding multidrug (oprJ and ttgB genes) and tetracycline (tetV) efflux pump were enriched by 608%, 724% and 3052%, respectively, compared to the low treatments  and beta-lactamase resistance genes (blaTEM and ampC-04) conferring antibiotic deactivation were enriched in the medium and high protist treatments, but several multidrug resistance genes  decreased their abundances in the medium protist treatment. A similar pattern was detected for the vanWG and vanC-03 genes functioning cellular protection by altering antibiotic target sites [The high protist concentration treatment significantly increased the abundance of ARGs encoding antibiotic deactivation and the ARG number encoding efflux pump ; ttgB with bacterivorous Spongomonas (Spongomonadidae); oprJ with undetermined Cercozoa; tetV with Allantion (Glissomonadida); and vanWG with Sandonidae (Glissomonadida) and Acanthamoeba (Centramoebida). The most abundant gene, blaTEM, which encodes antibiotic deactivation, was negatively associated with bacterivorous Cercomonadidae (Cercomonadida).We further estimated the effects of protists on bacterial community and ARGs. Random forest analysis revealed that the incubation time, protist concentrations and community were important predictors of the ARG composition, explaining 59.6% of the variation Fig. . MoreoveOur study investigated the role of soil protists in the development of the soil resistome, which is important for understanding the spread of antibiotic resistance in natural environments. We found that the enrichment of natural undiluted protistan inoculants exerted a high pressure on bacterial communities. Protists significantly enriched the profile of ARGs, including those conferring resistance to widely used antibiotics such as beta-lactams, aminoglycosides, tetracyclines and multidrug resistance. Our results also showed that the overall bacterial community composition and the relative abundance of specific bacterial taxa were changed by the grazing pressure of protists. Overall, our study provides compelling evidence that soil protists play a crucial role in driving the development of the bacterial antibiotic resistance in natural habitats, and highlights the need to consider these predators in efforts to mitigate the spread of antibiotic resistance.Streptomyces, Bacillus, become resistant to grazing while other grazing-susceptible and antibiotic-susceptible bacterial taxa are preferably consumed by predatory protists. These predator-prey interactions could explain negative associations between susceptible bacterial genera and protistan consumers  could increase bacterial competition, inducing antibiotic production to kill others [Our results support the hypothesis that soil protists enhance the development of soil ARGs at the community level by significantly influencing both the composition and functions of bacterial communities. Firstly, the higher grazing pressures of protists, especially the predominance of omnivorous or bacterivorous Cercozoa Fig. S may trigers Fig. . We recol others . Our resl others , as suppPseudomonas fluorescens CHA0 and Q2-87 produced antibiotics 2,4-diacetylphloroglucinol (DAPG), pyoluteorin and pyrrolnitrin to impede protist growth or repel the protists’ predation under in vitro conditions [We found the highest abundance of ARGs in all treatments on day 15 Fig.  during tnditions , 38. Thenditions , 38, 45.oprJ and ttgB genes) and tetracycline efflux pump (tetV) in soil treatments with high protist levels. These efflux pump genes can transport specific or multiple antibiotics out of bacterial cells [oprJ) found in pristine environments without anthropogenic disturbance [vanWG and vanC-03 genes which provide cellular protection by altering antibiotic target sites [Our study revealed the significant importance of soil protists in shaping the profile of soil ARGs, particularly those involved in multidrug efflux pump and antibiotic deactivation – two of the most common and ancient mechanisms of antibiotic resistance found in soils worldwide . We obseal cells , 48, andturbance , 50. In turbance , 51. A set sites , 34. Moset sites , highligPseudomonas fluorescens CHA0 [Acanthamoeba castellanii was found to impose a stronger selection pressure than the competition among P. fluorescens CHA0, leading to the production of the antibiotic DAPG. P. fluorescens wild strains are more resistant to predators and competitors than non-DAPG-producing mutant bacteria [The top-down control, including the predation and the presence, of protists can be as a selection pressure for the development of bacterial antibiotic resistance. Predation by protists is a primary regulator of bacterial community structure and lead to the decreasing abundance and richness of specific bacterial taxa , 52. To ens CHA0 , have bebacteria . These tbacteria . Both APbacteria . These ibacteria . Our worbacteria .In summary, our study provides novel evidence that soil protists, which are often overlooked, play a critical role in inducing the development of antibiotic resistance in bacterial communities at the community level. This work advances our understanding of the complex biological interactions that underlie the evolution of antibiotic resistance in natural environments and highlights the need for further research to explore the mechanisms by which protists exert selection pressure on bacterial population. By shedding light on the role of soil food web interactions in the spread of antibiotic resistance, our study has important implications for efforts to mitigate the growing threat of antibiotic-resistant infections.Supplementary fileFigure S1Figure S2Figure S3Figure S4Figure S5Figure S6Figure S7Table S1


Improvements in the Centers for Medicare & Medicaid Services (CMS) star ratings Part D medication adherence measures may affect performance in Part C intermediate outcome measures for which the Part D targeted medication classes are prescribed.To determine if Part D medication adherence measures are associated with corresponding Part C intermediate outcome measures.This was a cross-sectional analysis using the CMS 2015 star ratings report (based on 2013 benefit year plan data) for Medicare contracts. The measures of interest included the Part D adherence measures for diabetes medications, antihypertensive agents, and statins and the Part C intermediate outcome measures for controlled blood sugar, blood pressure, and cholesterol. All Medicare Advantage Prescription Drug (MAPD) contracts with complete data for all Part C and D measures of interest were included. Contracts with ≥ 25% of total enrollment with MA-only benefit were excluded. Linear and logistic regression models were used to assess the association between 2015 Part D adherence measures and Part C intermediate outcome measures (n = 366). The regression models were adjusted for low-income subsidy (LIS) beneficiary enrollment and log-transformed  total contract enrollment.2) of variance. Including LIS and total contract enrollment in the regression models increased the R2 to 30%-36%. The multivariate logistic regression models showed that each percentage point of improvement in the 2015 Part D adherence measures was associated with a 4.13 to 4.69 greater odds of performing in the top quartile in corresponding 2015 Part C measures.Bivariate linear regression models demonstrated moderate positive associations between each of the 2015 Part D adherence scores and related 2015 Part C measures that explained 27%-29% (RModerate positive associations were observed between the Part D and Part C scores in the same benefit year. MAPD plans may observe improved Part C intermediate outcome measures with strategies that improve Part D medication adherence measures. What is already known about this subjectCenters for Medicare & Medicaid Services (CMS) have placed an emphasis on several Part C and D measures related to medication therapy by weighting these measures 3 times as much as CMS’s process measures.Randomized and observational studies to date have demonstrated the impact of interventions targeting medication adherence to diabetic medications, antihypertensive agents, and statins on improving blood sugar, blood pressure, and low-density lipoprotein cholesterol control.A recent analysis has demonstrated the association between health plan measures of adherence and outcomes.What this study addsThe results of this study indicate that high ratings in Part D adherence measures are associated with high ratings in related Part C measures.Health plans may be able to improve multiple star ratings measures and overall plan performance with strategies aimed at improving medication adherence rates.2 The star ratings system is one of several industry programs aimed at defining quality health care, assessing plan performance in various quality measures, and rewarding positive outcomes. CMS star ratings measures are derived from measures developed and endorsed by various health care quality organizations, including the Pharmacy Quality Alliance (PQA) and the National Committee for Quality Assurance (NCQA) Healthcare Effectiveness Data and Information Set (HEDIS).2 CMS assigns numeric scores on individual performance measures  and assigns 1 to 5 stars to individual measures and groups of related measures to summarize overall performance, with 5 stars indicating excellent performance, 3 stars indicating average performance, and 1 star indicating poor performance.2In 2007, the Centers for Medicare & Medicaid Services (CMS) developed the star ratings system to measure health plan performance related to outcomes, patient experience and satisfaction with care, and patient access to health care services.4 beginning with the 2015 star ratings, only plans with 4 or more stars were eligible for QBPs.4 Additionally, star ratings affect Medicare beneficiaries’ choices in enrolling in insurance plans. Reid et al. (2013) found an increased likelihood for new Medicare beneficiaries to select plans with higher star ratings and continuing enrollees to switch to plans with higher star ratings.5 Medicare enrollment in higher-rated plans is increasing; in 2015, 61% of Medicare beneficiaries were enrolled in plans with 4 or more stars, a 25% increase from 2013.6 Revenue from QBPs, which are required by Medicare to be used only for providing additional benefits to members,3 may provide the means for plans to implement additional quality programs and further improve star ratings, which will likely attract more Medicare beneficiaries. Furthermore, contracts with consistently poor plan performance  receive the low-performing icon on the Medicare Plan Finder website and are subject to termination by CMS in 2016.7Therefore, improvement of star ratings has a potentially significant material effect on plan revenue and market share in the Medicare insurance marketplace.Plan performance on CMS star ratings measures is of considerable interest to Medicare plan sponsors for several reasons. First, the Affordable Care Act of 2010 entitles high-performing plans to quality bonus payments (QBPs);1 Specifically, CMS’s outcome and intermediate outcome measures are highly weighted measures that are weighted 3 times as much as CMS’s process measures.2 For the 2015 star ratings, CMS’s triple-weighted measures included Part D medication adherence measures for diabetes medications, renin-angiotensin system (RAS) antagonists, and statins and Part C measures related to intermediate outcomes commonly associated with these classes of medications: Diabetes Care – Blood Sugar Controlled, Diabetes Care – Cholesterol Controlled, and Controlling Blood Pressure.2 The greater contribution of these triple-weighted measures to a plan’s Part C and Part D summary ratings and overall star rating creates additional incentives for plans to place emphasis on quality programs aimed at improving medication adherence.In 2012, CMS began weighting specific Part C and D measures related to outcomes, intermediate outcomes, and patient access, indicating CMS’s greater emphasis on certain quality indicators.1Because of the anticipated effect of medication adherence on achieving positive outcomes from prescribed drug therapy, health plan strategies to target Part D medication adherence measures may potentially affect performance across multiple related Part C intermediate outcomes measures. The purpose of this analysis was to determine if a relationship exists between triple-weighted Part D medication adherence measures and corresponding Part C measures.Despite research supporting the association between medication adherence and improved clinical outcomes, there are limited data on the association between plan-level medication adherence and outcomes quality measures. Stakeholder discussions on CMS star ratings measures have suggested the importance of medication adherence in influencing Part C intermediate outcome measures and overall star ratings.This was a cross-sectional analysis using the CMS 2015 star ratings report that reflected contract performance data for the 2013 benefit year.8 The star ratings report is named for the upcoming benefit year and reflects plan data from the previous benefit year. For example, the 2015 star ratings report was released in late 2014 and reflects plan performance data for the 2013 benefit year. Performance data are reported at the contract level, and each contract receives a numeric score and a star rating (1 to 5 stars) for individual Part C and D star ratings measures. A star rating also is assigned to contracts for groups of related measures  and for overall performance . For the 2015 star ratings report, there were 46 measures (33 Part C measures and 13 Part D measures) in 9 domains.2 Medicare Advantage (MA) contracts and Prescription Drug Plans (PDPs) are rated based on performance in Part C or Part D measures, respectively, while Medicare Advantage Prescription Drug (MAPD) contracts are rated on all Part C and D measures.CMS publishes Medicare plan performance data each October before the annual open enrollment period on the CMS website.2PDC is an adherence metric that has been developed by PQA and endorsed by the National Quality Forum.2 The measure also is being used as a quality measure under the URAC PBM Accreditation and the Quality Rating System for Qualified Health Plans.10 The Part C intermediate outcome measures for the 2015 star ratings report were adopted by CMS from the NCQA HEDIS 2014 Technical Specifications Manual as follows: Diabetes Care – Blood Sugar Controlled (percentage of plan members with diabetes whose most recent hemoglobin A1c [A1c] lab test results showed controlled blood sugar [A1c ≤ 9%]); Diabetes Care – Cholesterol Controlled (percentage of plan members with diabetes whose most recent low-density lipoprotein cholesterol [LDL-C] level during the measurement year was less than 100 mg/dL); Controlling Blood Pressure (percentage of plan members with a diagnosis of hypertension who achieved adequately controlled blood pressure [<140/90] during the measurement year).2 Of the Part C and D measures of interest, the Part C Diabetes Care – Blood Sugar Controlled, Part C Diabetes Care – Cholesterol Controlled, and Part D Medication Adherence for Diabetes Medications measures include only beneficiaries with diabetes, while all other measures include beneficiaries regardless of diabetes diagnosis.The 2015 star ratings measures of interest for this analysis included the Part D medication adherence measures for diabetes medications, RAS antagonists, and statins and Part C Diabetes Care – Blood Sugar Controlled, Controlling Blood Pressure, and Diabetes Care – Cholesterol Controlled measures . Each ofAll MAPD contracts contained in the 2015 CMS star ratings report that had base-level numeric data for all the Part C and Part D measures of interest were included in this analysis. Contracts with “No data available,” “Not enough data available,” “Plan too new to be measured,” “Plan too small to be measured,” or “CMS identified issues with this plan’s data” for any of the Part C and D measures of interest were excluded from this analysis. Additionally, since MA plans are not required to report performance in Part D measures, contracts with 25% or more of total contract enrollment with MA-only benefits were specified a priori to be excluded from the analysis .2 Multivariate linear and logistic regressions using each Part D measure as the independent variable were used to model the probability of performing in the top quartile of the Part C measure. Independent variables included total contract size and low-income subsidy (LIS) beneficiary enrollment. Total contract size was transformed using the natural logarithm, which normalized the distribution of contract size. The regression models were performed using SAS version 9.4 , and a 2-sided P value of < 0.05 was considered statistically significant.Bivariate linear regressions were performed using each 2015 star ratings Part D measure base-level score as the independent variable and each corresponding Part C base score as the dependent variable to assess the association between Part D and related Part C measures in the 2015 star ratings report (2013 benefit year). The 2015 star ratings measures of interest were collected by CMS in the same measurement period from January 1, 2013, to December 31, 2013.A total of 366 Medicare contracts were included in the analysis, representing 53% of the 691 total Medicare contracts meeting criteria. Most contracts were local coordinated care plans (95.1%), mid-sized , and had less than 40% of total enrollment with LIS beneficiaries 72.1%; . Mean s. Mean S.2 = 0.29, P < 0.001); Controlling Blood Pressure ; and Diabetes Care – Cholesterol Controlled . The multivariate regression models adjusted for LIS enrollment and total contract enrollment showed improved associations that accounted for 30%-36% of variance between the corresponding measures ; Controlling Blood Pressure ; and Diabetes Care – Cholesterol Controlled .The bivariate linear regression models demonstrated moderate positive associations that accounted for 27%-29% of variance between each Part D medication adherence and related Part C measure : Diabetemeasures : DiabeteThe logistic regression models adjusted for LIS beneficiary enrollment and the natural logarithm of total contract enrollment showed that for each unit increase of medication adherence, the odds of performing in the top quartile of the corresponding Part C intermediate outcome measure increased by a factor of 4.63 , 4.13 (95% CI = 2.44-6.98), and 4.69 (95% CI = 2.79-7.91) for the Controlling Blood Pressure, Diabetes Care – Cholesterol Controlled, and Diabetes Care – Blood Sugar Controlled measures, respectively . High LI14 While this analysis found positive associations between Part D adherence and Part C intermediate outcome measures in the same benefit year, this association does not indicate causality. Other factors, such as regular testing and access to better quality care, may contribute to improved performance in Part C intermediate outcome measures. The absence of strong associations between the Part D medication adherence and Part C intermediate outcome measures also may be accounted for in the differences in the specifications for the Part D and corresponding Part C measured populations.To our knowledge, this is the first study to examine the relationship between Part D medication adherence and Part C intermediate outcome star ratings measures. This analysis showed moderate positive associations between the 3 Part D medication adherence measures and the corresponding Part C intermediate outcome measures in the 2015 star ratings report (2013 benefit year). The positive associations found between the Part D and Part C measures are consistent with literature findings that have demonstrated improved LDL-C, blood pressure, and blood sugar control with high levels of adherence  to each of the Part D medication classes.2 = 0.36, P < 0.001). However, trends in blood sugar control reflected in the Part C measure are not fully explained, possibly because of the exclusion of individuals taking insulin in the Part D diabetes medication adherence measure. Excluding patients with diabetes taking insulin has been shown to eliminate a large number of beneficiaries in star ratings measures.15 In addition, insulin treatment is associated with improved glycemic control,18and methods for measuring insulin adherence using the PDC calculation have recently been described.20 While measuring insulin adherence in patients concurrently receiving noninsulin therapies may introduce additional complexity to diabetes medication adherence measurement in quality measures, unmeasured insulin adherence may confound the observed association between medication adherence for diabetic medications and blood sugar control measured in the Part D and C measures, respectively.The strongest association was observed between the Part D diabetes medication adherence and Part C Diabetes Care – Blood Sugar Controlled measures  indicate TZDs and CCBs as first-line options for the treatment of hypertension.24 In addition, combination regimens consisting of multiple antihypertensive drug classes are commonly required to achieve adequate blood pressure control. Gu et al. (2012) found that individuals in National Health and Nutrition Examination Surveys from 2001 to 2010 receiving multidrug antihypertensive regimens were 26%-55% more likely to achieve JNC 7 blood pressure goals compared with individuals receiving monotherapy.21 Therefore, the effect of unmeasured adherence to other antihypertensive agents may have a significant contribution to the Part C Controlling Blood Pressure measure performance.Similarly, the Part D Medication Adherence for Hypertension measure is limited to the measurement of adherence to angio-tensin-converting enzyme inhibitors, angiotensin receptor blockers, and direct renin inhibitors, which likely excludes a large number of beneficiaries who receive other antihyperten-sive treatments. Published studies have noted an increasing use of thiazide-type diuretics (TZDs) and calcium channel blocker s (CC Bs). 25 Patients with diabetes using statins without history of dyslipidemias may confound the association between statin adherence and LDL-C levels.The beneficiary population included in the Part C Diabetes Care – Cholesterol Controlled measure consists of patients with diabetes, while the Part D Medication Adherence for Cholesterol measure includes beneficiaries with 2 or more fills of statins, regardless of diabetes diagnosis. This subpopulation of beneficiaries with diabetes that is included in the Part C measure may have different characteristics compared with the entire population of statin users included in the Part D statins adherence measure. Statins are also standard of care treatment for patients aged 40-75 years with diabetes regardless of lipid levels.26 For these measures, however, the association between dual/LIS enrollment and star ratings measure performance decreased after controlling for disability,26 which suggests the potential contribution of additional patient-level factors and other plan demographics in driving the association between star ratings adherence and intermediate outcome measures. Additionally, our finding that larger contracts have an increased odds of achieving a higher Part C score is consistent with a previous report by Xu et al. (2015), which found that large contract size, maturity, and nonprofit status were associated with higher star ratings for MAPD contracts.27Adjusting for LIS enrollment and total contract enrollment in the regression models improved the associations between each of the 2015 Part D and Part C measures, and both variables were associated with performance in the Part C measures. The observed association between LIS enrollment size with star ratings measures is consistent with preliminary analyses conducted by CMS, which have noted a statistically significant negative association between dual/LIS enrollment and performance in a subset of star ratings measures, including the Part C Diabetes Care – Blood Sugar Controlled and Part D adherence measures for diabetes medications, RAS antagonists, and statins.1 Efforts to improve medication adherence likely require a multidimensional approach, innovative strategies, and high-touch interventions, such as clinician case management. Effective interventions have emerged from strategic partnerships between health plans, pharmacy benefit managers (PBMs), and pharmacies. A comprehensive pharmacy intervention using PBM pharmacy claims data, member outreaches by a health plan care management team, and mail order pharmacy delivery of medications led to significant improvements in performance in all Part D medication adherence measures for a dual-eligible Medicare Special Needs Plan.28 Randomized and observational studies to date have demonstrated the impact of interventions, including personalized pharmacist consultations and patient education, targeting medication adherence to diabetes medications, antihypertensive agents, and statins on improving blood sugar, blood pressure, and LDL-C control.30 Additionally, a recent analysis of private health plan claims data by Seabury et al. (2015) demonstrated the association between higher average adherence rates and lower hospitalization rates in plan-level quality measures.31 The cumulative evidence suggests that strategies in improving medication adherence are also likely to improve intermediate outcome quality measures.Despite CMS’s emphasis on these triple-weighted Part D medication adherence and Part C intermediate outcome measures, improvement of these measures is typically challenging for health plans because of the need for greater member engagement in order to achieve positive outcomes.2 — did not report data for all the Part C and D measures of interest and were therefore excluded from this analysis. This lack of reporting may limit the applicability of the results if new or low enrollment contracts have different characteristics than those in our sample.This analysis contains the following limitations. First, approximately 47% of Medicare contracts present in the 2015 CMS star ratings report were excluded from this analysis because of the incomplete reporting of base-level numeric data for all Part C and D measures of interest. New and low enrollment contracts — defined by CMS as contracts with less than 1,000 enrollees for 2015 star ratings measures that are derived from HEDIS32 Also, in response to the release of the JNC 8 Guideline for the Management of High Blood Pressure,7 CMS has modified the methodology of the Part C Controlling Blood Pressure measure to reflect the percentage of beneficiaries aged 18-59 years and 60-85 years with diabetes who have a blood pressure reading of <140/90 and members aged 60-85 years without diabetes who have a blood pressure reading of <150/90 during the measurement year.32Second, the applicability of these results is limited by changes affecting the Part C and D measures of interest for the 2016 star ratings report (2014 benefit year). Following the release of the new American College of Cardiology/American Heart Association Guidelines on the Treatment of Blood Cholesterol, as well as the retirement of 3 NCQA measures related to LDL-C control for HEDIS 2015, CMS has retired the Part C Diabetes Care – Cholesterol Controlled measure for the 2016 star ratings.32 These methodological changes may result in higher performance, on average, across contracts in these Part C and D measures for the 2016 star ratings. For HEDIS-derived Part C measures that include all the Part C intermediate outcome measures of interest, CMS has redefined low-enrollment contracts to include contracts with ≥ 500 enrollees,32 which would result in more contracts being eligible for inclusion in the 2016 star ratings Part C measures.In relation to Part D measures, sodium glucose cotransporter 2 inhibitors will be included in the diabetes medication adherence measure, and beneficiaries with end-stage renal disease coverage will be excluded from the Part D adherence measures for diabetes and hypertension medications.32 Future studies should assess the impact of these changes on the association between Part C and D measures in future star ratings reports.Also, the actual beneficiary date of death or disenrollment, instead of the last day of the month of disenrollment, will be used to define the end of the beneficiary’s measurement period for the PDC adherence calculation, although this likely will have minimal impact on adherence rates and performance in the Part D measures.14Third, the PDC calculation used in the Part D adherence measures may not fully capture adherence to combination therapy. Limitations in the PDC methodology may be especially important for the Part D Medication Adherence for Diabetes Medications measure. Specifically, the PDC calculation may appear to artificially inflate adherence in the Part D Medication Adherence for Diabetes Medications measure, since this measure requires the supply of only 1 diabetes medication in the measurement period. Despite these limitations, PDC has been shown to be a reliable indicator of drug exposure and predictive of measurable clinical outcomes in diabetes, hypertension, and hyperlipidemia.Fourth, this study used publicly available Medicare contract performance results that are reported at the contract level and do not include demographic or patient-level data. As a result, we were not able to control for socioeconomic differences in patient populations other than LIS beneficiary enrollment. More research is needed to understand the association between Part D and C measures in the context of an intervention where patient-level data are available.Finally, this study focused on the Medicare-eligible elderly population. Therefore, the results of this analysis may not be generalizable to other plan populations, such as commercial plans on federal or state exchanges and Medicaid populations outside of dual-eligible plans.1the findings of this study indicate that MAPD plan sponsors may experience improved performance in Part C measures with strategies that improve performance in Part D medication adherence measures. This analysis suggests the potential added value of improving medication adherence in influencing Part C intermediate outcome measures and overall plan performance. Plan sponsors may use this information to guide strategies for achieving higher star ratings. The association between triple-weighted Part D medication adherence measures and Part C measures underscores the importance of innovative quality improvement strategies aimed at improving medication adherence.In the context of national stakeholder discussions promoting the importance of medication adherence in influencing Part C intermediate outcome measures related to medication therapy,


The purpose of this study is to demonstrate the feasibility of using noninvasive, diffuse optical spectroscopy measurements of CBF and cerebral oxygenation during the conduct of ACP in human neonates undergoing the Norwood procedure.Surgical procedures involving the aortic arch present unique challenges to maintaining cerebral perfusion, and optimal neuroprotective strategies to prevent neurological injury during such high-risk procedures are not completely understood. The use of antegrade cerebral perfusion (ACP) has gained favor as a neuroprotective strategy over deep hypothermic circulatory arrest (DHCA) due to the ability to selectively perfuse the brain. Despite this theoretical advantage over DHCA, there has not been conclusive evidence that ACP is superior to DHCA. One potential reason for this is the incomplete understanding of ideal ACP flow rates to prevent both ischemia from underflowing and hyperemia and cerebral edema from overflowing. Critically, there are no continuous, noninvasive measurements of cerebral blood flow (CBF) and cerebral oxygenation (StO2) using two non-invasive optical techniques, namely diffuse correlation spectroscopy (DCS) and frequency-domain diffuse optical spectroscopy (FD-DOS). Changes in CBF and StO2 due to ACP were calculated by comparing these parameters during a stable 5 min period of ACP to the last 5 min of full-body CPB immediately prior to ACP initiation. Flow rates for ACP were left to the discretion of the surgeon and ranged from 30 to 50 ml/kg/min, and all subjects were cooled to 18°C prior to initiation of ACP.Four neonates prenatally diagnosed with hypoplastic left heart syndrome (HLHS) or a similar variant underwent the Norwood procedure with continuous intraoperative monitoring of CBF and cerebral oxygen saturation (StO2 of −3.6% (12.3) compared to a baseline period during full-body cardiopulmonary bypass (CPB). The four subjects demonstrated varying responses in StO2 due to ACP. ACP flow rates of 30 and 40 ml/kg/min (n = 3) were associated with decreased CBF during ACP compared to full-body CPB. Conversely, one subject with a higher flow6Di rate of 50 ml/kg/min demonstrated increased CBF and StO2 during ACP.During ACP, the continuous optical monitoring demonstrated a median (IQR) percent change in CBF of −43.4% (38.6) and a median (IQR) absolute change in StOThis feasibility study demonstrates that novel diffuse optical technologies can be utilized for improved neuromonitoring in neonates undergoing cardiac surgery where ACP is utilized. Future studies are needed to correlate these findings with neurological outcomes to inform best practices during ACP in these high-risk neonates. One in 100 neonates worldwide are born with congenital heart defects (CHD), a third of which require surgery or other interventions in early infancy . AlthougPotential reasons for the lack of superiority of ACP over DHCA include an incomplete understanding of neurological injury following neonatal cardiac surgery and widely discrepant methods in the conduct of ACP among different institutions. Specifically, reports have shown ACP flow rates that vary from 20 to 94 ml/kg/min –13, and quantify tissue concentration of oxy and deoxy-hemoglobin which allows for quantification of tissue oxygen saturation  newborns with pre- or postnatally diagnosed hypoplastic left heart syndrome (HLHS) or variants admitted to the cardiac intensive care unit at the Children's Hospital of Philadelphia were screened for study inclusion and approached for participation as early as possible. Exclusion criteria included: birth weight <2 kg, a history of neonatal depression , perinatal seizures, evidence of end-organ injury, preoperative cardiac arrest, and significant preoperative intracerebral hemorrhage such as grade 3 or 4 intraventricular hemorrhage. Infants with identified or suspected genetic syndromes were not excluded. Patient demographics are shown in n = 1), 40 ml/kg/min (n = 2), and 50 ml/kg/min (n = 1). ACP flow rates were not adjusted throughout the ACP period and the flow rate choice was not influenced by this study. ACP was delivered either through an expanded polytetrafluorethylene shunt sewn to the innominate artery (n = 3), or via direct cannulation of the innominate artery (n = 1) with occlusion of the innominate artery proximal to the cannulation site for selective ACP administration. pH- stat blood gas management was used during cooling and while hypothermic; alpha stat was used during rewarming and at normothermia per institutional protocol. Patients were cooled to a target nasopharyngeal (NP) temperature of 18°C prior to initiating ACP. FD-DOS and DCS data were collected continuously but were not disclosed to the clinical team and were not used to guide any clinical management.The study protocol for this study was similar to a previously published study looking at cerebral physiology during DHCA . All proThis study employs a hybrid optical research device combining two techniques: frequency-domain diffuse optical spectroscopy (FD-DOS) and diffuse correlation spectroscopy (DCS). These techniques, which utilize near-infrared light to noninvasively probe static and dynamic physiological properties of cortical brain tissue, have been described in depth previously , 19, 20.2), as opposed to commercial oximeters that employ continuous-wave NIRS (CW-NIRS or NIRS) to monitor trends in cerebral oxygen saturation. FD-DOS uses photon diffusion theory to relate the measured amplitude attenuation and phase shift of modulated and multiply scattered light detected on the tissue surface to determine the wavelength-dependent tissue absorption (µa) and scattering (µ's) properties. These properties are determined by fitting to the semi-infinite medium solution of the photon diffusion equation for a homogeneous medium. The phase and AC amplitude (AC) of the detected light quantify the optical properties of the tissue. Specifically, the slope of the phase vs. source-detector separation on the tissue surface (r) and the slope of the ln(AC ×  r2) vs. r were determined and used to compute µa and µ's, respectively. Data were discarded if the linear fits had a Pearson correlation coefficient R2 < 0.975, which was usually caused by probe dislodgement during patient repositioning.Multi-distance FD-DOS is capable of accurate quantification of cerebral tissue oxygen saturation , in turn, depends linearly on oxy- [(HbO2)] and deoxy-hemoglobin [(Hb)] concentration. Therefore, measurements of the tissue absorption at multiple wavelengths yield these 2 concentrations in absolute units. From [HbO2] and [Hb], we also derived total hemoglobin concentration (THC = [HbO2] + [Hb]) and cerebral tissue oxygen saturation [StO2 = (HbO2)/THC]. The FD-DOS device employed in the present study  is amplitude modulated at 110 MHz and employs source lasers at 4 wavelengths, λ = 688, 725, 785 and 830 nm.The wavelength and time-dependent absorption coefficient, µi, measured in units of cm2/s). Although this index does not have traditional physiological units of CBF, recent studies have shown that CBFi can be calibrated in absolute units, and that it correlates strongly with other gold standard measures of CBF  uses near-infrared light to noninvasively monitor cerebral blood flow (CBF). DCS measures the temporal fluctuations  of the light intensity at the tissue surface which is primarily caused by moving red blood cells. The correlation diffusion equation and its semi-infinite solutions were employed along with the tissue optical absorption and scattering measured in real-time with FD-DOS to convert these temporal fluctuations into an index of cerebral blood flow , with 4 source fibers  and 1 detection fiber. For DCS, 8 single-mode detection fibers were bundled and placed on the tissue surface 2.5 cm away from the source fiber.2 due to ACP was calculated by comparing StO2 during a stable 5 min window during ACP to a 5 min baseline period during full-body CPB immediately prior to the initiation of ACP using the following formula:The change in StO2 and CBFi due to ACP compared to CPB for all four subjects. We observed a decrease in CBFi during ACP in 3 of the 4 patients with ACP flow rates of 30 and 40 ml/kg/min. 2 and CBFi for Subject #3 where the ACP flow rate was 30 ml/kg/min. In this subject, CBFi is lower during ACP than it was during full-body CPB, however StO2 does not significantly change which suggests that cerebral oxygen demand is being met despite the decrease in cerebral oxygen delivery.Our hybrid FD-DOS/DCS device was used for continuous intraoperative monitoring in four neonates with HLHS or similar variants during the Norwood procedure. 2 and CBFi for Subject #2 where the ACP flow rate was 50 ml/kg/min. In this subject, we observed an increase in CBFi during ACP compared to the baseline period on full-body CPB. Interestingly in this subject we also observed an increase in StO2 from the period of full-body bypass to ACP, suggesting that the cerebral oxygen delivery was exceeding cerebral oxygen demand.2 during ACP compared to baseline, while the subjects with lower ACP flow rate experienced varying degrees of decreased CBF and less change in StO2 compared to the baseline full-body CPB period. While this sample size is too small to derive any conclusions on optimal flow rate, these cases demonstrate the variance in cerebral hemodynamic response to various ACP flow rates among different neonates as well as the feasibility to quantify these changes non-invasively with hybrid FD-DOS/DCS.In this report, we demonstrate the first use of hybrid FD-DOS/DCS for continuous, noninvasive cerebral monitoring in four neonates undergoing cardiac surgery requiring ACP. We observed different trends in cerebral oxygen saturation and blood flow among the four subjects. Perhaps unsurprisingly, the one subject with the highest ACP flow rate experienced higher CBF and StOThe lack of accurate neuromonitoring during neonatal cardiac surgery, specifically during procedures where ACP and DHCA are employed, leads to numerous and critical gaps in the understanding of the neonatal brain's metabolic and physiologic needs at such extremes of cardiovascular physiology. This issue is further exacerbated by widely disparate practices concerning the conduct of cardiopulmonary bypass, flow rates during ACP, operative and perioperative anesthetic regimens that may affect cerebrovascular reactivity, temperature at which ACP is initiated, duration of cooling and rewarming before and after ACP, and many other patient-specific factors that can lead to different cerebral metabolic needs and responses to cardiopulmonary bypass. Current neuromonitoring techniques have failed to improve neurodevelopmental outcomes according to a recent systemic review , which bWhile the use of hybrid FD-DOS/DCS provides more precise and potentially useful data than existing neuromonitoring strategies, there are also limitations to its use that are important to discuss. Firstly, these data are experimental, and critical values that warrant investigation or intervention have not yet been established. The issue of critical values for intervention has also not yet been resolved with conventional NIRS and TCD; while some centers have proposed such criteria , there iDespite the inherent limitations associated with novel technology in its infancy, the ability to obtain absolute measurements of key neurovascular and neurometabolic indices without technological limitations or assumptions represents a very promising breakthrough in neuromonitoring. By overcoming many of the shortcomings of existing neuromonitoring technologies, hybrid FD-DOS/DCS may prove invaluable as a way to match cerebral perfusion to metabolic demand. Matching supply with demand has the most direct effect on optimizing ACP delivery during neonatal cardiac surgery, but this technology may also be applicable to other disease states where perfusion to different organ beds may be compromised.