Quantifying the extent of health care resource utilization (HCRU) and costs associated with Huntington disease (HD) is vital for providers, decisionmakers, and payers to understand unmet treatment needs and to ensure limited resources can be used to benefit the maximum number of people with HD.To quantify HCRU and costs for people with HD, overall and by disease stage, and compare these with non-HD controls.This was a retrospective cohort study using administrative claims data from the IBM MarketScan Commercial, Multi-State Medicaid, and Medicare Supplemental Databases from January 1, 2009, to December 31, 2018. People with an HD claim between January 1, 2010, and December 31, 2017, were selected for this analysis and matched with non-HD controls for comparison. The HD cohort and the non-HD controls were exact matched on their follow-up duration and propensity score matched 1:4 to create the final analytical cohort. Index date was the first HD diagnosis for the HD cohort (proxy index date assigned to controls), and all individuals were required to have continuous enrollment for 12 or more months pre-index (baseline) and 3 or more months post-index. Proportions of all-cause HCRU  in the 6-months post-index and HCRU counts and costs per patient per month (PPPM) over the entire follow-up were calculated for each cohort.P < 0.0001. The mean number of HCRU PPPM for all measured healthcare services was significantly higher in people with HD compared with non-HD controls (P < 0.001). Mean total costs (2018 USD PPPM) for the HD cohort  were twice the total costs in the non-HD cohort  (P < 0.0001) and were highest across all disease stages.A total of 2,473 individuals with HD and 9,522 matched non-HD controls were identified. HCRU in 6 months post-index was significantly greater in people with HD compared with non-HD controls for all health care service categories; This study provides current comprehensive HCRU and cost estimates in individuals with HD relative to those without the disease, thus demonstrating the high economic burden imposed by HD. This study examined health care use in people with and without Huntington disease (HD) in the United States. Researchers found that people with HD used more health care services than people without HD. This included medical appointments, hospitalizations and emergency department visits, scans, and the use of drug treatments. The costs and amount of health care use were higher in people in the middle or late stage of HD than people in the early stage of HD. Implications for managed care pharmacyThis study provides current comprehensive evidence of the high economic burden that HD exerts on individuals and health care systems. Furthermore, it corroborates previous research that has shown that disease burden worsens as HD progresses. Taken together, these findings offer a compelling argument for providing better care and access to new treatments that can slow or stop disease progression in HD.2 An inherited autosomal disease, HD is caused by a cytosine-adenine-guanine trinucleotide repeat expansion at the 5’ end of the huntingtin gene (HTT) resulting in a toxic version of the huntingtin protein (HTT), known as mutant HTT.4 Cytosine-adenine-guanine expansion length has been cited as the strongest risk factor for developing HD, with increased repeat size number associated with reduced onset age and clinical progression.5Huntington disease (HD) is a rare, genetic, neurodegenerative disorder characterized by a triad of cognitive, behavioral, and motor symptoms.6 Prevalence of HD in Australia, North America, and Western Europe has increased between 10% and 20% each decade since 1930, which can be attributed to increased life expectancy and the advent of diagnostic testing.8 Estimates from 2014 and 2016-2017 report HD prevalence at 13.1 per 100,000 US Medicare beneficiaries ,9 with the true prevalence of HD in the US estimated to be between 21,000 and 40,000 individuals.10A recent study of privately insured US individuals published in 2019 reported an age-adjusted cumulative incidence rate of 1.22 per 100,000 person-years (95% CI = 1.53-1.65).1 However, symptoms can manifest in early child-hood11 or later in life.12 HD results in increasing disability, loss of independence, and death, with a median survival of 15 years after the onset of unequivocal motor symptoms, such as involuntary movements  and defects in coordination.14 A person’s ability to conduct activities of daily living is severely reduced by the resultant disability, profoundly impacting health-related quality of life.15 Furthermore, HD treatment is complex, requiring a multidisciplinary approach.16 There are no disease-modifying treatments that can slow, halt, or reverse disease progression,11 so the goals of HD management are to relieve symptoms, maximize function, and improve quality of life where possible.17 Current treatments include tetrabenazine and deutetrabenazine for the treatment of chorea, active and passive physiotherapy for treatment of dystonia, antipsychotic medications such as olanzapine and risperidone for ideational perseverations, and cognitive behavioral therapy for treatment of obsessive-compulsive phenomena.17 The presence and severity of all motor, cognitive, and behavioral symptoms should be considered by physicians when forming a treatment plan. Furthermore, the fact that a patient’s requirements can change over time means that an individualized treatment strategy specific to their needs is often required.18Clinical diagnosis of HD typically occurs when people are in the prime of life, usually between the ages of 30 and 50 years.19 The economic burden exerted by HD is substantial, but there is a paucity of data on the extent of the health care resource utilization (HCRU) and costs associated. Existing evidence suggests that HCRU and costs increase as HD progresses, with costs being highest during end-of-life care.20 Other previous analyses that investigated HCRU and costs in HD24 and juvenile HD25 have shown that people with HD require substantial long-term care, which drives up health care costs. However, these studies were subjected to several limitations, including individuals only being classified into a single stage,20 limited sample size,22 or lack of a comparison group.22 Furthermore, the most recent study examining the costs and HCRU associated with HD was conducted in 2016 and contained data from 2013,24 highlighting the need to collect contemporary data in order to better understand how disease burden translates into direct health care costs and resource use. Recent, comprehensive estimates of HCRU and costs are therefore vital to understanding unmet treatment needs, maximizing limited resources, and ensuring the greatest number of people can be treated effectively.Optimal allocation of resources is vital to improving overall outcomes for the greatest number of patients, and real-world data are a valuable tool for informing health care policymakers when formulating treatment pathways.The objectives of this study are to quantify HCRU and costs for people with HD in the United States, overall and by stage, and compare these with matched non-HD controls.This was a retrospective cohort study using administrative claims data from the IBM MarketScan Commercial, Medicare Supplemental, and Multi-State Medicaid Databases from January 1, 2009, to December 31, 2018 (study period). These databases form a family of research datasets that contain records of fully adjudicated, deidentified, patient-level health care claims data, reflecting real-world utilization of health care services, treatments, and costs.26 The IBM MarketScan Medicare Supplemental database contains data for the Medicare-covered portion of payment , employer, and out-of-pocket patient expenses for US Medicare beneficiaries with Medicare Supplemental insurance paid by employers.26 The IBM MarketScan Medicaid Multi-State database contains data on medical, surgical, and prescription drug experience for more than 47,000,000 Medicaid enrollees from multiple states.26The IBM MarketScan Commercial database contains annual pharmacy and medical claims data for several million individuals, including employees, their spouses, and their dependents who are covered by employer-sponsored private health insurance in the United States. A variety of health plans are represented, including fee-for-service, fully capitated and partially capitated health plans such as preferred provider organizations, exclusive provider organizations, point of service plans, indemnity plans, health maintenance organizations, and consumer-directed health plans.HD Cohort/Cases. People with a claim of HD 28 between January 1, 2010, and December 31, 2017 (identification period), were selected for analysis. At the time of analysis, the ICD-9-CM was the official system of assigning codes to diagnoses and procedures associated with hospital utilization in the United States.29Supplementary Figure 1, available in online article).The first date of HD diagnosis in the identification period was the index date. All participants in the HD cohort were required to have continuous enrollment of 12 or more months pre-index (baseline period) and 3 or more months post-index and have no HD diagnosis in the pre-index period . From this pool, controls with eligible dates were selected for further matching, specifically if the continuous enrollment criteria were met . Following this, cases and controls were exact matched 1:100 based on follow-up duration. From this pool of cases and controls, propensity scores were created and cases were propensity score matched to controls 1:4 to create the analytical cohort. Controls are matched without replacement. The propensity scores were created based on the following variables: age at index/proxy index, sex, Charlson Comorbidity Index (CCI [score only]), HCRU during baseline , and costs during baseline .All participants were required to be aged 18 years or older at index and to not switch insurance plans throughout the study period. All participants were followed until the end of continuous enrollment or end of data (follow-up period), whichever occurred first.HD Staging. People with HD were initially categorized at baseline into early, middle, and late stage by modifying a previously published algorithm of disease severity.20 This algorithm, developed and validated by Divino et al, categorized disease markers based on a review of clinical literature, exploratory analyses of the data, and expert clinical input. Use of nursing home care, use of a feeding tube, incontinence, bedsores, use of hospice care, evidence of 2 or more falls within 1 month, and dysphagia were all late-stage markers. Use of home assistance, physical therapy, dementia, gait disorder, dysarthria, speech therapy, or evidence of any falls were all middle-stage markers. Individuals with late-stage disease were identified first, followed by individuals with middle-stage disease, based on the presence of any late- or middle-stage disease markers, respectively. Individuals without any late- or middle-stage disease markers were categorized as having early-stage disease.HD stage post-index was determined using the same algorithm. However, people were allowed to progress during follow-up; people that were in early or middle stage at baseline advanced in stage whenever the appropriate disease marker(s) for the more advanced stage appeared during follow-up. For these people, follow-up time was characterized by the amount of time they were in each stage before transitioning. People who began at late stage remained in late stage for the remainder of the follow-up period.Non-HD controls were given a proxy stage at baseline using the same algorithm. In order to compare with the dynamic staging of their matched HD cases, non-HD controls also had their follow-up time characterized by different “stages” and transitioned to a different proxy stage whenever their matched HD case experienced a stage change . This approach was implemented to estimate the incremental burden associated with HD at each stage of the disease, compared with their non-HD controls.All-Cause HCRU and Costs. The following all-cause HCRU post-index were assessed for individuals with HD and non-HD controls : outpatient visits , inpatient visits , ED visits , pharmacy fills (any claims billed in the pharmacy setting), HD-related pharmacy fills (full list of HD-related medications in Supplementary Table 1), radiology , and physical/occupational therapy.The following all-cause costs post-index were assessed for individuals with HD and non-HD controls : outpatient costs , inpatient costs , pharmacy costs, HD-related pharmacy costs, long-term care (LTC) or nursing home costs, and skilled nursing facility costs.30 SAS v9.4 (SAS Institute) was used for all analyses.HCRU and costs were reported descriptively for both the HD cohort and non-HD controls. Proportions of patients by HCRU service were assessed in the 6-months post-index (among those with ≥ 6 months of follow-up) overall and by baseline disease stage. Mean (SD) and median HCRU and costs were assessed per patient per month (PPPM) to account for variable follow-up in the cohort, accounting for dynamic disease staging approach. Fisher’s exact tests were used to compare HCRU proportions in the 6 months post-index among individuals with HD vs non-HD controls. Wilcoxon signed-rank tests were used to compare HCRU counts and costs PPPM between HD cohorts and their controls. Costs were adjusted to 2018 USD values using the medical component of the consumer price index.Supplementary Figure 1) and were matched with 9,522 non-HD controls  (P < 0.0001). The proportion of people with inpatient visits was more than 3 times greater in people with HD compared with non-HD controls . The proportion of people with ED visits was almost doubled in individuals with HD compared with non-HD controls    . Outpati 0.0001) . The pro 0.2356) .P < 0.0001) (Supplementary Table 2). Mean HCRU PPPM for all health care services was significantly higher in the HD cohort vs non-HD cohort at each disease stage  (Supplementary Table 2). The greatest mean values were for outpatient visits (2.13 vs 1.23), all-cause pharmacy fills (1.86 vs 1.19), and HD-related pharmacy fills (0.67 vs 0.18) in the HD and non-HD cohorts, respectively .People with HD had a significantly higher mean HCRU PPPM for all measured health care service categories when compared with non-HD controls (P < 0.0001). Outpatient costs followed by pharmacy and inpatient costs accounted for the majority of costs in the HD cohort. Similarly, total median health care costs PPPM were more than doubled in the HD cohort compared with the non-HD controls   for the HD cohort  were twice the total costs in the non-HD cohort  . OutpatiP < 0.0001)  . In the  0.0001) .This study provides comprehensive estimates of HCRU and direct medical costs among individuals with HD in comparison with their matched non-HD controls. We found that HCRU was significantly greater in individuals with HD compared with those without HD, across all measured health care service categories. Additionally, mean total health care costs were more than doubled among individuals with HD compared with their matched non-HD controls. These findings highlight the considerable economic burden of HD.16 which may result in increased costs and HCRU when compared with individuals without HD. Furthermore, increased costs and HCRU in the HD cohort may be due to a higher comorbidity burden, as shown by the higher overall mean (SD) baseline CCI scores observed in the HD vs non-HD cohort: 0.95 (1.78) and 0.78 (1.48), respectively. These results are supported by a study conducted by Zielonka et al, which shows that individuals with HD have a significantly higher percentage of coexisting conditions in comparison with healthy controls.31HCRU was significantly higher in the HD cohort compared with the non-HD cohort, specifically outpatient visits (mean number of visits: 2.13 vs 1.23), all-cause pharmacy fills (mean number of fills: 1.86 vs 1.19), and HD-related pharmacy fills (mean number of fills: 0.67 vs 0.18). The majority of costs in the HD cohort were attributed to outpatient (mean PPPM: $945), followed by pharmacy  and inpatient ($615) costs, which were substantially higher than those in the non-HD cohort. In particular, mean outpatient PPPM costs made up 42% of the total cost burden in the HD cohort. There could be several explanations for this. First, management of individuals with HD requires care from multidisciplinary teams,Supplementary Table 2). One explanation could be that progressive motor dysfunction observed in individuals with middle-stage disease results in increased risk of falls causing injury, therefore requiring greater use of health care services.33 Risk of falls may be reduced in late-stage disease as individuals are more likely to be using wheelchairs or walking aids or be bed bound.1 Alternatively, as a patient progresses from early- to middle-stage HD, their symptoms may begin to interfere with their daily lives and thus prompt them to seek further medical attention. This could lead to more aggressive treatment, necessitating higher HCRU and costs. Another potential explanation may be the shifting of care from acute inpatient settings to nursing home care in late-stage disease,23 as evidenced by increased mean costs in long-term care, nursing home, and skilled nursing facility categories in individuals with late-stage vs middle-stage HD. Also, increased mean health care costs in people with middle-stage disease could be a statistical anomaly driven by outliers, as shown by the large SDs and wide ranges we observed in the mean total costs and mean inpatient costs for each stage in the HD cohort. Indeed, total median costs increased incrementally by stage, as did outpatient HCRU, highlighting the large variation in HCRU and costs data in this study population.We allowed HD stage to change over time in order to explore the incremental burden associated with disease progression when compared with non-HD controls. This approach provides insights into the specific drivers of increased costs and HCRU at each disease stage in people with HD, thus helping to account for disease progression when estimating economic burden associated with HD. As expected, mean total costs were significantly higher across all disease stages in the HD cohort relative to their non-HD controls. The greatest mean costs were observed in middle-stage disease among individuals with HD. Increased mean total costs for individuals with middle-stage disease were mainly driven by higher mean inpatient costs. Furthermore, there was an increase in the mean number of inpatient visits in the middle-stage HD cohort  total annualized cost per patient increased by disease stage  and that outpatient costs were the primary health care cost component. In our analysis, mean inpatient costs were greatest in the early and middle stages, with outpatient costs only being greatest in late-stage disease. Furthermore, total mean costs (PPPM) in the early, middle, and late stages were $3,686, $7,728, and $3,905, respectively, meaning total mean costs were greatest in the middle stage of disease and were driven by higher inpatient costs. The reasons for these discrepancies remain unclear but may be attributed to differences in study characteristics including study period and population. For example, Divino et al examined MarketScan Commercial and Medicaid claims between 2002 and 2009, whereas the current study used MarketScan Commercial, Medicaid, and Medicare Supplemental Databases from 2009 to 2018. Moreover, Jones et al24 found that the greatest proportion of HD-related costs comprised informal care  and that these informal costs were much higher than all other categories. Indirect costs were not examined here or by Divino et al,20 as claims data repositories do not hold these data, but they do clearly form a key component of HD care and should be the subject of future research. Johnson et al35 found that people with HD were more likely than non-HD individuals to be enrolled in LTC facilities and that people with HD were far more likely to die in these facilities than non-HD counterparts. Although they only analyzed individuals in hospice care, our results show that increased LTC and nursing home costs were observed in individuals with late-stage disease compared with the non-HD cohort, thus corroborating their findings. Finally, Anderson et al34 did not have a non-HD comparator group in their study, but their findings still support our assertion that HCRU increases with disease stage.Overall, our findings of significant HCRU and cost burden associated with HD are consistent with previous research.Our results demonstrate that HCRU and costs are substantially higher in individuals with HD compared with matched non-HD controls. This difference between the 2 cohorts indicates the extent of economic burden imposed by HD, as well as an unmet medical need, specifically an effective treatment that can slow or stop the progression of HD and thus avoid some of the HCRU and costs associated with disease progression.24 Considering that HD primarily affects people at the peak of their working age (between 30 and 50 years), productivity loss as a result of HD could be substantial and should be analyzed in future research. Second, the generalizability of the results to people in the United States with other types of insurance beyond commercial insurance, uninsured people, or individuals outside of the US health care system is difficult. Third, use of LTC and nursing homes may not be fully captured in these claims data, as these services are not typically covered by commercial insurance plans; therefore, costs reported here may be underestimated, particularly among individuals with late-stage disease. Fourth, owing to a lack of clinical data in administrative claims, disease staging was assessed using disease markers from a previously developed, validated, and published claims-based algorithm.20 Clinical assessment of disease progression using the total functional capacity scale36 thus provided the underlying concept for the claims-based algorithm used in our study. Although these disease markers are considered a reliable proxy for indicating the decline in a patient’s functional status, there is the potential in our study for mis-classification of disease stage and thus inaccurate HCRU and costs reporting. Similar to previous research,20 we also relied on 1 diagnosis code to identify individuals with HD, which could result in inclusion of individuals with a misdiagnosis of HD. Another limitation was the relatively short follow-up period of approximately 2 years, which may not capture the full extent of HD burden given the progressive nature and long natural history of the disease. It should also be noted that although every effort was made to match the cohorts as closely as possible, they were not exactly matched on some vital characteristics. For instance, the 21% of individuals in the HD cohort had a CCI of 2 or more, compared with 18% of the non-HD cohort. This meant that the HD cohort was already a “sicker” population, which may have added some unintended bias to the results. Also, we tried to make the case and control populations comparable by accounting for the higher costs and HCRU an individual with HD could be expected to accrue in the 12 months prior to diagnosis in the propensity score matching. However, by doing so we may have inadvertently selected patients (both with and without HD) who were more likely to have higher HCRU/costs compared with a normal healthy population. Without the utilization and costs criteria that we specified for baseline matching, HCRU/costs would be even higher overall among patients with HD. Finally, these results are subjected to limitations inherent to retrospective claims-based analyses, including misclassification or coding errors. In this case, misclassification could have occurred when individuals were being assigned to the HD or matched control groups, resulting in potential overestimations of HCRU and costs for controls and underestimations of HCRU and costs in the individuals with HD.This study is subjected to limitations that should be mentioned. First, we did not evaluate indirect costs of HD including productivity loss and caregiving costs, which may be an extensive component of the total burden of HD.In conclusion, this study demonstrates the high economic burden among those with HD relative to individuals without the disease. Our findings also support and update previous research showing increased health care burden with HD disease progression, as evidenced by the increasing HCRU and costs with disease stage, which remained substantially higher relative to controls across all stages of the disease. The greater burden of illness for people with HD compared with those without HD underlines the need for better care and access to new treatments that can slow or stop disease progression.


Lacticaseibacillus rhamnosus GG (LG), Limosilactobacillus reuteri ATCC 55730 (LR), Bifidobacterium animalis subsp. lactis BB-12 (Bb), and Propionibacterium jensenii 702 (PJ), either alone or in multi-species combinations included in orange juice (OJ), were assessed during storage in refrigerated conditions and compared with bottled water (BW). The tolerance of probiotics included in refrigerated OJ to simulated gastrointestinal conditions was also examined. LG and LR viabilities were significantly higher in OJ than in BW (p ≤ 0.001), while the reverse was evident for PJ. Bb maintained high viability in both drinks. LG-PJ in both drinks and Bb-PJ in BW resulted in greater viabilities among the paired combinations compared to their respective monocultures when incorporated separately (p ≤ 0.001). The viability of LG in the LG-Bb-PJ combination improved significantly in BW compared with LG alone (p ≤ 0.001). OJ did not alter bacterial tolerance to simulated gastric juice but diminished tolerance to simulated intestinal juice (SIJ). In all combinations, tolerance of LG and LR to SIJ was improved, whereas tolerance of PJ declined significantly compared with respective monocultures (p ≤ 0.001). In conclusion, probiotic storage stability and gastrointestinal transit tolerance were species-dependent and affected by carrier type and combinations. These effects should be considered when formulating probiotic products.Little is known about how combining probiotics affects the storage survival and functional performance of individual probiotics when incorporated into non-dairy drinks. Viability of  Develop product  or 109 Con point . It is, on point .The viability of single strains of probiotics has been studied in fruit juices and fruit drinks, in which their survivability was shown to be genus, species, or strain dependent; viability is also affected by the type of fruit juice and its intrinsic parameters such as pH and the presence of particular compounds, and extrinsic factors such as storage temperature and duration ,7,8,9,10For beneficial probiotic effects that are dependent on the viability and activity of probiotics in the intestine, it is critical that they survive hostile conditions of the upper gastrointestinal tract, such as gastric acid and exposure to bile salts and proteolytic enzymes in the duodenum . Prior sSince probiotic organisms vary in the type and level of their health-promoting effects, it is likely that probiotic combinations may potentially offer even greater benefits to the consumer than single-strain preparations . As suchThe objective of the present study is to examine the viability and in vitro gastrointestinal transit tolerance of multi-species probiotics incorporated into orange juice and drinking water during storage under refrigeration (both carriers) or at room temperature (only drinking water). Orange juice was used as it is the most popular fruit beverage worldwide  and has A timeline schematic of experimental procedures is presented in Lacticaseibacillus rhamnosus GG , Limosilactobacillus reuteri ATCC 55730  and Bifidobacterium animalis subsp lactis BB-12® , as well as probiotic candidate Propionibacterium jensenii 702  were used in this study. Lactobacillus strains (LG and LR) and Bb were grown overnight at 37 °C in MRS and RCM broths , respectively. PJ was grown in yeast extract lactate (YEL) [te (YEL)  at 30 °Cg for 15 min at 4 °C), and bottled spring drinking water  were used in this study. The OJ with pulp is composed of 10.8% carbohydrates, including 8.6% sugars, 0.7% protein, 0.1% total fat, sodium 1 mg 100 mL−1, and vitamin C 20 mg 100 mL−1. Fifty (50) mL aliquots of the OJ with and without pulp) and BW were then dispensed into sterile screw cap high-density polypropylene containers  and refrigerated (4 °C) prior to further preparation. Bacterial cells were grown and harvested in their stationary phases by centrifugation  and washed three times with PBS, pH 7.0 . Viable bacterial cells were enumerated in PBS culture stocks and after adding to the products to ensure the viable cell counts for each species remained constant across the preparations. An aliquot of each bacterial suspension in PBS was incorporated into the 50 mL portions of the carriers to achieve final concentrations of ~1 × 108, ~1 × 108, ~1 × 107, and ~3 × 108 live cells mL−1 of the product for LG, LR, Bb, and PJ, respectively. Eleven preparations were made for each carrier as follows, LG, LR, Bb, PJ, LG + Bb, LG + PJ, LR + Bb, LR + PJ, Bb + PJ, LG + Bb + PJ, and LR + Bb + PJ  with pulp , pulp-free OJ prepared from the commercial OJ with pulp  (MRS-V) after anaerobic incubation of the plates at 43 °C for 24 h [−1.Bacterial viable cell counts were determined by plating of decimal dilutions prepared from OJ and BW at storage days 0, 1, 4, 7, 14, 21, 28, 42, and 56 . LactobapH values of the OJ and BW were measured on the same days as the survival determinations. Titratable acidity of orange juices was determined in the beginning (time point 0) and at the end of refrigerated storage (week 8) by titration of the juices with 0.1 N NaOH to the phenolphthalein endpoint (pH 8.2) also monitored using a pH-meter. Total soluble solids or Brix was determined by the refractometry method of the Association of Analytical Chemists  using a −1 to sterile PBS. The pH value was then adjusted to pH 2.0 with 0.2N HCl (Sigma-Aldrich). SGJ tolerance was determined by adding an aliquot of 1.0 mL probiotic OJ to 9 mL SGJ followed by vortex mixing for 10 s and incubation at 37 °C [Due to technical difficulties (frequent pipette tip blockage) with orange juice containing pulp, we performed a GI transit tolerance test only on pulp-free OJ products. The test was conducted by exposing probiotic pulp-free OJ preparations to simulated gastric juice (SGJ) and simulated intestinal juice (SIJ) at storage days 0, 10, 20, and 30 . SGJ wasat 37 °C  for 20 mat 37 °C . Immedia−1. The mixture was then centrifuged at 2000× g for 15 min at 4 °C. Bile Salts No 3 (Sigma-Aldrich) was added to a final concentration of 3.0 g L−1 to the decanted supernatant and the pH adjusted to 8.0 with 1.0N NaOH (Sigma-Aldrich). Tolerance to the intestinal conditions was determined by transferring a 2.5 mL aliquot of each probiotic OJ preparation to 7.5 mL of a mixture of SGJ (45 mL), SIJ (60 mL), and 1.0M NaHCO3 (6.1 mL). The final mixture was vortex mixed for 10 s and incubated at 37 °C for 180 min. The viable bacterial cell counts were then determined, as described in To determine the tolerance of probiotics to the simulated intestinal conditions, the method of de Palencia et al.  was follp ≤ 0.001.Statistical analyses were performed using SPSS software Ver. 18 . Data were analyzed using the linear mixed model procedure to run a general linear model (GLM). In order to give protection against potential false positives , the Bonferroni adjustment was used, and the significance level (α) was set at p ≤ 0.001) (p ≤ 0.001). A similar result was observed for Bb in the Bb-PJ combination and for PJ in the LG-PJ combination after week 2 and week 6, respectively  . Where aectively .Apart from LR monoculture, insignificant differences were observed between the survival of probiotic monocultures included in OJ, either with or without pulp. Hence, the results on strain-dependent differences in viability are presented in pulp-free OJ . In orde−1, reducing by about 10% across the 8 weeks of storage   .Lactobacillus viabilities were found to remain above the effective threshold level (106 CFU mL−1) up to 4 weeks of storage, but at room temperature (23 °C), their viabilities dropped to zero within 2 weeks of storage (In refrigerated BW (4 °C),  storage . Bb viab storage . In cont storage .Due to little if any difference between the results obtained in OJ with or without pulp see  and poorIn pulp-free OJ, the viability of the LG was not affected by the presence of Bb and/or PJ. When combined, LR and Bb viabilities declined significantly, as was the case for the Bb-PJ combination. In contrast, the triplet combination (LR-Bb-PJ) produced no decline in the viability of either LR or Bb and a significant enhancement to the viability of PJ, which in this case remained constant throughout the entire 8-week storage .p ≤ 0.001).In OJ, the viability of PJ improved in all combinations except for Bb-PJ compared with PJ monoculture. However, LR viability declined significantly in the LR-PJ combination (p ≤ 0.001). In the BW, the LR-Bb and LR-Bb-PJ combinations appeared to be slightly less favorable for both Bb and PJ, although in these cases, decreases in viability were only evident beyond day 42. In all other cases, in both OJ and BW, the bacterial viability appeared to be largely unaffected by the presence of other probiotic species , titratable acidity (ranged from 1.15–1.22%), and Brix (ranged from 10.3–10.7) values of OJ preparations, and pH values of water (under refrigeration) were relatively constant across the entire data set.p ≤ 0.001) (p ≤ 0.001)  A. Howeve≤ 0.001) B. When i≤ 0.001) .The results have been presented as two sets of figures , one forA high tolerance of monoculture preparations to SGJ was maintained throughout the storage period . The preA steady reduction in the tolerance of LG was observed between the initial (day 0) and final (day 30) measurements .In several cases, combining probiotics had a substantial impact on the intestinal transit tolerance of individual probiotics . For exap ≤ 0.001).The viability loss of LR exposed to SIJ reduced significantly after 10 days of storage compared with day 0 and remained unchanged by the end of storage . The tolIn general, combining both Bb and PJ appeared to provide a favorable outcome for the lactobacilli with little impact on Bb, while the tolerance of PJ to SIJ was adversely affected to a varying extent in combinations with lactobacilli .Fruit juices have been considered a promising delivery vehicle for probiotics. However, maintaining the viability of probiotics incorporated into fruit juices during storage has been identified as the main limiting factor due to the low pH values of the products . The preRefrigerated storage of fruit juices is required to prevent the growth and activity of microorganisms . ConsistBifidobacterium animalis subsp lactis strains, including Bb, have been reported to be more resistant to low pH values [Our results on species-dependent variation in bacterial viability are also in agreement with previous studies evaluating fruit juices as probiotic carriers ,9, in whH values . In contH values .Apart from the pH, the higher survival of lactobacilli in orange juice than in drinking water is consistent with viability-promoting effects of organic components such as sugars , and antLactobacillus strains but did so for Bb and PJ. These results would certainly be associated with the differences in the compositional and physicochemical properties between orange juice and drinking water. The lack of organic compounds such as sugars and antioxidants in water could result in compromised viability for lactobacilli. The higher survival rate of PJ and Bb in water is likely due to entering a dormancy state induced by carbon starvation [Refrigerated drinking water did not support the survival of the arvation ,38.The effect of combining probiotics on the viability of individual strains appeared to be dependent on species, carrier matrix, and the composition of the probiotic combination. In paired combinations included in orange juice, the viability of at least one of the probiotics significantly declined, except for LG-PJ, in which PJ viability improved with no effect on LG. Interestingly, the viabilities of individual probiotics in the triplet combinations  were not adversely affected. In particular, PJ viability, which was poor in orange juice, was significantly improved in triplet combinations. It, therefore, was apparent that the adverse viability effects of pairing probiotics could be overcome by formulating triplet combinations. In drinking water, paired and triplet combinations comprising LG, Bb, and PJ appeared to have no adverse effects on the viabilities of Bb or PJ and significantly improved the viability of LG. Suboptimal growth temperatures, such as refrigerated storage, result in decreases in the metabolic activity of probiotics, thus extending the survival of probiotics ,29. UndeThe present study also reports significant variation in the viability of probiotics in drinking water under different storage temperatures. When compared with refrigerated water, the decline in the viability of LG, LR, and Bb was found to be more dramatic under storage at room temperature. In spite of the suitability of room temperature for the growth of bacteria, the absence of carbon energy sources , nitrogen sources, and other substances necessary for bacterial growth and maintenance in drinking water could result in starvation and, ultimately, bacterial death. Interestingly, PJ and Bb were much more stable than the lactobacilli in drinking water at both temperatures. Prolonged survival of propionibacteria has been reported when stored at room temperature under carbon starvation which may induce bacterial dormancy , thus exThe presence of pulp in orange juice was not identified as an influential factor in the viability of probiotics in most of the probiotic preparations. However, where significant variations were observed, viability was found to decline more rapidly in the orange juice containing pulp. It has been shown that orange pulp contains essential oils, such as citrullene and limonene, which can exert a potent antimicrobial activity ,43.6 CFU mL−1 throughout the shelf life of the product [6 CFU mL−1. In most cases, pulp did not affect the shelf life of the probiotic orange juices. Orange juices containing monocultures of LG, LR, or Bb, paired combinations of LG-Bb and LR-PJ, and triplet combinations, all maintained the minimum effective level of viable cell counts of all probiotic constituents beyond week 6. In some cases (PJ monoculture and LG-PJ), the viability of at least one of the probiotic constituents dropped below the minimum recommended level between days 28 and 42. Since the exact day of declining below the effective threshold was unknown in these cases, they may be considered marginal.Based on the viability data, we also evaluated the shelf lives of the probiotic products. It has been recommended that the number of viable probiotic cells present in the food must be maintained above a minimum level of 10 product . AccordiIn refrigerated drinking water preparations, both Bb and PJ and paired and triplet combinations containing both exhibited shelf-lives greater than 6 weeks. At room temperature, however, only PJ monoculture exhibited an acceptable shelf-life .In the present study, we also assessed in vitro gastrointestinal transit tolerance of probiotic combinations incorporated into orange juice. While not a requirement in pre-clinical assessments , survivaWe also showed that the specific carrier matrix could impact the tolerance of the probiotics to simulated gastrointestinal conditions. The enhanced tolerance of LG and PJ included in orange juice to SGJ, compared to those included in PBS, is likely associated with the compositional and physicochemical properties of orange juice. It has been reported that components such as sugars and vitamin C that are present in orange juice can enhance the survival of probiotic lactobacilli and bifidobacterial in acidic environments ,35. AnotOn the contrary, exposure to orange juice appeared to significantly decrease or have no effect on the tolerance of LG, LR, and PJ to SIJ. This result is consistent with previous studies where pre-exposure of lactobacilli, bifidobacterial, and propionibacteria to low pH values resulted in a decrease or no effect in their tolerance to simulated intestinal juice (1.4% bile in PBS) ,49. LoweThe present study also showed that the duration of refrigerated storage of the probiotic species  included in orange juice did not have an adverse impact on the bacterial tolerance to SGJ and SIJ over one month of storage compared with their tolerance at the baseline. Similar unchanged bacterial tolerance to SIJ was previously reported for probiotic lactobacilli included in a fruit juice blend . HoweverLastly, we also showed that combining probiotics may favorably or adversely affect the tolerance of individual probiotics to SIJ but not SGJ. To the authors’ knowledge, this is the first report showing that the tolerance to intestinal conditions of probiotic strains included in a non-dairy carrier vehicle may be influenced by the presence of other strains. While this effect can be attributed to biophysical contact and/or biochemical interaction between the probiotics that may protect or have a detrimental effect on the tolerance of the bacteria to SIJ, potential underlying mechanisms are yet to be investigated.The present study reports that the incorporation of probiotic combinations in non-dairy drinks may result in distinct outcomes in the performance of probiotics, such as viability and GI transit tolerance which could not be predicted based on findings from the inclusion of individual probiotics separately. However, additional studies are needed to further investigate the underlying mechanism of interactions. In light of a need for developing non-dairy probiotic products for consumers who are allergic or intolerant to milk components or have no desire to eat dairy foods, developing new probiotic food products with probiotic combinations should be carefully considered by the functional food industry so that the performance of individual probiotics including storage stability and tolerance to the gastrointestinal conditions is not, at least, compromised by the presence of other probiotics. Such products may also result in offering greater health-promoting effects to the consumer than single-strain preparations. However, the effect of the inclusion of probiotic combinations into non-dairy carrier vehicles on the sensory characteristics of the product and functional properties of probiotics in the digestive tract  needs to be further investigated.


Recently, multimodal chromatography using restricted access media (RAM) for the purification of nanoparticles, such as viruses has regained increasing attention. These chromatography resins combine size exclusion on the particle shell and adsorptive interaction within the core. Accordingly, smaller process‐related impurities, for example, DNA and proteins, can be retained, while larger product viruses can pass unhindered. We evaluated a range of currently available RAM, differing in the shells’ pore cut‐off and the core chemistry, for the purification of a cell culture‐derived clarified model virus, namely the Orf virus (ORFV). We examined impurity depletion and product recovery as relevant criteria for the evaluation of column performance, as well as scale‐up robustness and regeneration potential for evaluating a multiple use application. The results indicate that some columns, for example, the Capto Core, enable both a high DNA and protein removal, while others, for example, the Monomix Core 60 (MC60), are more suitable for DNA depletion. Furthermore, column regeneration is facilitated by using columns with larger shell pores (5000 vs. 700 kDa) and weaker binding interactions . According to these findings, the choice of RAM resins should be selected according to the respective feed sample composition and the planned number of application cycles. CC (700 / 400)Capto Core (size cut‐off 700 / 400 KDa)CVcolumn volumeDSPdownstream processingMC60Monomix Core 60ORFVOrf virusRAMrestricted access mediaUSPupstream processingVLPvirus‐like particleVPViralPolish1Several medical challenges are currently targeted by using viruses or virus‐like particles (VLPs), which can be classified as biological nanoplexes. These include, among others, classical vaccination approaches with (live) attenuated viruses , VLPs, aDue to a complex impurity composition, the DSP of cell culture‐derived viruses usually involves several steps, employing a combination of various techniques, such as chromatography, extraction, filtration, and centrifugation procedures . AlthougTo reduce the challenges for optimization, for scale‐up, as well as for a process transfer to a production facility, scalable modular platform approaches are preferable. These are particularly beneficial in the case of different virus products or different genotypes of the same virus, as viral vector platforms allow for a modification of the virus composition, for example, the expression of certain  proteins .Chromatographic RAM provide a scalable possibility to gently process virus particles, while successfully removing major contaminants such as host cell DNA and proteins. We compared different RAM resins with a varying shell pore cut‐off and core ligand binding chemistry for the purification of cell culture‐derived Orf virus particles. From this, conclusions can be drawn for future applications in the field of virus purification with respect to the product and the applied manufacturing process. Furthermore, we show the reproducibility of the virus recovery and the impurity depletion during single‐use and after repeated cleaning, and compared two different process scales. This allows other users to select the appropriate column matrix with regard to their application and process requirements.One potential solution to overcome the above‐mentioned challenges of the referred classical chromatography methods is the purification of viruses by mixed‐mode resins using restricted access media (RAM) . GeneralIn all currently published RAM applications, Capto Core (CC), the first commercially available RAM resin was used. CC is based on cross‐linked agarose beads with the core ligands consisting of octylamine , 25. TheIn a recent study, the CC700 performance was compared to other commonly applied chromatographic methods in terms of recovery, impurity depletion , and witAs RAM resins promise a straightforward translation to the required process scale and a suitability for a broad range of different viruses, we evaluated to what extent a purification of the model ORFV is affected by variations in the RAM ligand and the shell composition. For this purpose, currently, commercially available RAM resins were compared for an application as a purification step following clarification. All resins had an inert polysaccharide‐based particle shell and varied in the shells’ pore size (400 to 5000 kDa), the binding chemistry of the core  and the column size (due to the availability of columns). The performance of the purification procedure was characterized with regard to product recovery and impurity depletion as well as the individual columns’ capacity during sample loading. Furthermore, the repeated utilization with intermediate cleaning was examined, in order to evaluate whether the columns are more suitable for multiple‐use applications, or whether a single‐use application might be recommended. This is of particular interest, if continuous chromatography methods are to be used.22.12 and infected with a multiplicity of infection of 0.05. Five days after infection, the cells were disrupted by one freeze/thaw cycle  and the supernatant was collected.The ORFV, which expresses a green fluorescent protein in infected cells, was selected as a model virus and propagated in an adherent cell culture, as previously described . BrieflyThe virus harvest was then clarified, using a serial two‐step depth filtration with decreasing pore sizes (5 and 0.65 μm). Polypropylene filters  were applied and the filtration process was carried out at a constant feed pressure of 0.05 MPa, using the Sartoflow Smart system operated by the Biopat MFCS 4 software (Sartorius Stedim Biotech GmbH). Harvests of different culture flasks were pooled, aliquoted, and stored at −80°C after clarification. For all subsequent experiments, the same clarified feed suspension was used.2.2An Äkta Pure 25 system (Cytiva), operated by the Unicorn 7.7 software, with online monitoring of UV (280 nm), conductivity, and light scattering , was used for the chromatographic runs. Before usage, all buffers were filtered through a 0.2 μm bottle top filter (Corning) and degassed by ultrasonication .−1 (1 mL min−1). The procedure comprised the following six steps: (i) equilibration, using 20 mM TRIS supplemented with 180 mM NaCl at a pH of 7.4 for 5 CV, (ii) loading of the clarified ORFV harvest, (iii) washing, with the equilibration buffer for 5 CV, (iv) elution of the bound impurities, with 7 CV of 20 mM TRIS supplemented with 2 M NaCl, pH 7.4, (v) cleaning, with 5 CV of 1 M NaOH, and (vi) washing, with 6 CV water. The loading (ii) was done until an increase in the protein breakthrough of 10%–20% of the feed material was detected by UV280 monitoring. This resulted in different load volumes, ranging between 8 and 20 mL, depending on the column type  RAM columns were obtained from Cytiva (Capto Core) and BioToolomics  A/B) with the specifications indicated in Table  mL RAM cThe performance of the CC400 and CC700 columns was evaluated in triplicates, using a new column for each run to estimate the error of replicates. As, accordingly, the batch deviation of product recovery and impurity depletion for fresh columns was negligible, subsequently, all other columns were analyzed with single runs, using fresh columns only.2O cleaning.Furthermore, the regenerability of selected columns  was evaluated by re‐using the same column three times after NaOH (1 M) and H−1 or was set to the maximum possible flow rate, resulting in 3.7 mL min−1 for the CC700, corresponding to 477 cm h−1, the maximum for that column, and 4.2 mL min−1 for the MC60, corresponding to 570 cm h−1, half of the maximum. To support the online monitoring, the flow‐through was fractionated, and samples were taken for each loaded CV.Ultimately, the small‐scale experiments were supplemented for evaluations on a larger scale, using 4.7 mL CC700 (Cytiva) and 4.2 mL Monomix Core 60  columns. The chromatographic procedure was equal to the smaller scale with regard to the number of CV of buffer and feed in the individual steps. The flow rate was adjusted volumetrically to equal 1 CV min2.3The chromatographic fractions  of all runs were analyzed for the contained amount of the infective viruses, total protein, and DNA. The protein and DNA levels were determined using the Pierce BCA Protein Assay and the Quant‐iT PicoGreen dsDNA Assay Kits (both Thermo Fisher Scientific) according to the manufacturers’ instructions, as previously described .−1, the medium blank, or the respective chromatography sample. After 16 h of incubation, the percentage of fluorescent cells, due to the GFP expression after virus infection, was determined, using a flow cytometer (Guava easy Cyte HT). The infective virus concentration of the chromatographic samples was estimated by a linear calibration curve, based on an in‐house standard. The general standard deviation of the assay for duplicate measurements was less than 10%.The quantification of infective virus particles was done by an automated flow cytometry‐based approach, as previously described . Briefly33.1At first, twelve different 1 mL RAM columns were assessed Table . Under tThe wash and elution fractions of all columns contained minor virus amounts with less than 5%–9% Table . Accordi280 signal indicating an exponential increase of about 10%–20% of the maximum signal , up to 20% of the proteins were to be expected in the breakthrough. Accordingly, this value could be further reduced, by stopping the loading before a more pronounced breakthrough occurs. This, in turn, would impair the process productivity, as less feed material can be handled while the column capacity is not fully exploited. In return, the obtained data suggests a constant protein breakthrough of 4%–7% from the start of the loading procedure for the best performing columns. In the case of the cationic DUO S column, it is unlikely to achieve an improvement at neutral pH conditions, requiring an alteration of the pH value of the sample [protein mL−1, whereas in the present experiments, residence times of 1 min were applied, using feed containing more than 2 mg mL−1 contaminating proteins in order to reduce the process time.Considering the impurity removal, the highest protein amounts of 48%–65% in the product fraction were observed with DUO Q 400, 700, and DUO S 5000 columns Table . The lowe sample , 30. ForThe DNA recovery in the flow‐through (product fraction) was between 17% and 92% Figure . As for In summary, the VP A and B columns delivered the highest capacity compared to the columns tested, considering the applicable amount of feed volume and the best impurity removal, at the cost of an impaired product yield. For the other columns, the infective virus recovery was comparable at 70%–90%. The differences in their capacity and in their protein and DNA depletion deviated only slightly Table . An incr3.22O) and re‐equilibrated up to two times for an additional usage. Only the largest available cut‐offs were evaluated for each column, as they performed best in the previous study, and it can be assumed that these show the greatest regeneration potential due to a higher diffusion rate [Following the evaluation of the general column suitability for the model virus purification, the selected RAM columns were cleaned  and elution  , and to assess the MC60, which was commercially not available in a 1 mL size. Both columns were loaded until the protein breakthrough increased to about 10%–20% of the maximum, just as for the 1 mL columns. Accordingly, the CC700 could be loaded with about 41 mL (8.7 CV), and the MC60 with about 34 mL (8 CV). Thus, the loading volumes can be considered to be comparable for these two columns, as well as for the two different tested CC700 scales with 8 CV of feed material being loaded on the 1 mL column, and 8.7 CV loaded on the 4.7 mL column.−1 was used, but the maximum possible flow rate. This was done because a high throughput of feed material was desired. In order to further optimize the impurity retention and to avoid diffusion limitations, the flow rate could be further decreased. A comprehensive optimization, however, was not part of the column screening presented here.For both tested columns, CC700 and MC60, about 90% of the infective product viruses were found in the flow‐through Figure . ConcernFinally, it was determined for both columns that the retained impurities could only be removed from the column to a maximum of 20% during wash and elution. Particularly for the MC60, the elution did not enable a notable impurity recovery Figure . With thFor the CC700, the data suggests a high comparability for different scales, as not only the capacity of the column (see above), but also the ORFV recovery and the impurity depletion were similar for both column sizes. In addition to the technical triplicate runs on a small scale, this indicates a high reproducibility of the CC700 application. As the separation principle is the same for all RAM techniques with no direct binding interaction between the virus and the resin due to the inert shell material, a straightforward scalability can be assumed for the other tested materials as well. However, this assumption has to be verified in upcoming evaluations. Previously, the CC700 was applied for various viral targets and different column sizes , 31, 34.4RAM greatly improve DSP procedures for virus‐based therapeutics and enable a fast and gentle processing of the product while removing major contaminants, such as DNA and proteins. We evaluated the performance of various commercially available RAM columns for the purification of a clarified ORFV harvest with regard to the impurity removal and product recovery. The tested RAM columns feature individual characteristics in terms of pore size distribution in the shell and ligand chemistry within the cores. This allows a tailored process integration of the RAM technology depending on the product requirements, as DNA and proteins are depleted with different efficiencies. For the model virus, ORFV, RAM materials with anion exchange or multimodal ligand interactions are preferable, as cation exchange core ligands do not enable the retention of impurities  at a neutral pH value, and pH adjustments would affect the stability of the virus. Additionally, in the described studies, a clarified feed solution was applied, which challenges the column with excessive amounts of protein and DNA. The results show that some of the columns might be better suitable for a residual impurity removal . Furthermore, the data suggests that most of the columns are more suitable for a single‐use application instead of multiple usages, in order to enable a reproducible process conduction. This is caused by an irreversible adsorption of components to the core ligands, which requires an extensive cleaning procedure. For a repeated usage, RAM columns without a multimodal ligand, but with anion exchange binding mechanisms, are preferential, as a streamlined cleaning procedure is possible. For the evaluated model ORFV, CC700 provides the most reliable technique for product recovery and impurity depletion, when applied during a primary purification in single‐use. For repeated usages, the DUO Q 5000 is preferential due to an easier column regeneration. Additionally, the DUO Q 5000 and the MC60 provided a remarkable DNA depletion and would, thus, be particularly suitable at later DSP stages.In summary, when choosing a suitable column and proper process conditions, for example, considering the residence times, the RAM technology offers a potential platform methodology as part of a DSP procedure for a gentle purification of cell culture‐derived viruses. The results for product yield and contaminant depletion permit the assumption that the technique might take its firm place in viral production processes in the future. The presently commercially available matrices with different characteristics support this possibility.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Pulicaria jaubertii (PJ) is a medicinal plant used as a synthetic antioxidant and as a traditional medicine due to its bioactive compounds. The objective of this study was to investigate the effects of PJ on carcass traits and breast meat quality parameters of broiler chickens. Two hundred and forty male broilers (1 day old) were divided into four groups . Performance indicators were evaluated during the feeding stages, and carcass characteristics and physiochemical and qualitative parameters of breast meat were measured at 36 days old. The results showed that PJ improved performance parameters such as weight gain, feed conversion ratio, and production efficiency index (p < 0.05) in the finishing stage. The diets supplemented with PJ were associated with better carcass characteristics (p < 0.05), but some body parts, such as legs (6 and 9 g PJ) and backs (3–9 g PJ) decreased (p < 0.05). Temperature and initial pH were decreased by PJ (p < 0.05). Meat color was not affected by PJ (p > 0.05), although the yellowness and saturation index were lower at 9 g PJ. Total saturated fatty acid content was higher at 3 g PJ, while total polyunsaturated fatty acids and unsaturated to saturated fatty acid ratio were lower at 3 and 6 g PJ (p < 0.05). Total monounsaturated fatty acid content increased at 6 and 9 g PJ. Omega-6 fatty acids and the ratio of omega-6 to omega-3 were lower at 3 g PJ. PJ resulted in higher weight loss on cooking (6 and 9 g PJ) and shear force (3–9 g PJ). In conclusion, PJ had a positive influence on performance, carcass characteristics, and fatty acid profile, and some meat quality traits were generally improved by PJ, but knowledge of its mode of action is still limited and therefore requires further investigation. Currently, there is an increasing interest in modern broiler chicken production, focusing on nutrition and nutritional supplementation to produce a greater quantity of meat, provided it is of high quality and safe for human consumption ,2. HowevPulicaria jaubertii (PJ), considered an aromatic medicinal plant, belongs to the Asteraceae family and is widely distributed as a wild plant in Yemen and Saudi Arabia [Pulicaria gnaphalodes powder [Pulicaria undulata powder [Eucalyptus globulus oil [i Arabia ,12. Tradi Arabia ,14,15. Ai Arabia  found thi Arabia ,18. The s powder , Pulicara powder , and Euculus oil , has demTo the best of our knowledge, no previous studies have investigated the use of PJ as a natural feed additive and its effects on carcass characteristics and breast meat quality of broiler chickens. The present study may provide evidence for future applications of PJ powder as a feed additive to improve broiler chicken performance and meat quality, which is the basis of the hypothesis of this study. Therefore, the aim of this study is to investigate the effect of PJ, as an aromatic medicinal plant, on performance, carcass characteristics, and breast meat quality in broilers.All methods and procedures used in this study were approved by the Scientific Research Ethics Committee of King Saud University (KSU-SE-21-47).PJ was collected directly as a whole plant  from the valleys around Ibb City, Republic of Yemen. It was then identified in the Kingdom of Saudi Arabia by the Herbarium of the College of Science at KSU, as it is considered a wild plant in southern Saudi Arabia (classification reference: 24544); dried at room temperature; and ground into a fine powder.A total of 240 1-day-old male Ross 308 broiler chicks were used. Each chick was weighed; then, the chicks were randomly divided into four levels of PJ powder  with ten replicate cages per level and six chicks per cage. The Ross 308 Management Guide  recommends three feeding stages for the basal diet: starter (1–10 days old), growth (11–24 days old), and finisher (25–36 day old). The basal diet was prepared as mash to meet nutrient requirements during the study in accordance with these guidelines see . The curIn three feeding stages , live body weight and feed consumption were recorded to calculate the weight gain , feed intake , and feed conversion ratio (feed intake/body weight gain) according to Diler et al. . FurtherAt the finisher stage (36 days old), all broilers were fasted overnight. Ten chickens were randomly selected for slaughter from each PJ level at a rate of one chicken per cage . According to the method of Liu et al. , the pre2 + (redness − 0.43)2 + (yellowness − 3.98)2), saturation index (Sqrt (redness)2 + (yellowness)2), hue angle (tan − (yellowness/redness)), and browning index ((100 × (χ − 0.031)/0.17), where χ = redness + (1.75 × lightness)/(5.645 × lightness) + redness − (3.012 × yellowness)) using the color measurements. The chemical properties of breast meat (10 samples from each PJ level), including moisture, protein, fat, ash, and organic matter (100 − ash) were determined [pH and temperature were measured initially and after slaughter  using a pH meter , and color  was measured using a Minolta Chroma Meter  according to Tashla et al. . The apptermined . The tot× χ − 0.0/0.17), wtermined . Analysi2) and texture profile analysis according to Lee et al. [Ten samples of breast meat from each PJ level were analyzed after being cooked in an electric oven until an internal temperature of 70 °C was reached for measurement of cooking loss (difference between sample weight before and after cooking multiplied by 100) and shear force  was tested. Duncan’s multiple range test was used to analyze differences between means of PJ levels at p > 0.05) on the parameters of growth performance, except for body weight and production efficiency index, which were higher (p < 0.05) in the diet supplemented with 3-9 g and 3 g PJ/kg, respectively, compared with the non-supplemented basal diet (0 g PJ/kg) during the starter phase of 1 to 10 days old. In the grower phase (11–24 days old), PJ levels had no effect on body weight gain, feed intake, or production efficiency index (p > 0.05), whereas the feed conversion ratio improved when the diet was supplement with 9 g PJ/kg compared with non-supplemented basal diet (p < 0.05) but was not significantly different from the other levels (3 and 6 g PJ/kg). At 25–36 days old (finisher stage), performance indicators  increased, and the feed conversion ratio improved under a 3–9 PJ/kg basal diet compared with a non-supplemented basal diet (p < 0.05), while PJ levels had no effect on feed intake (p > 0.05).The effects of PJ levels on broiler performance indicators are shown in p < 0.05). Diets supplemented with 3 to 9 g PJ had no effect on relative weights of dressing yield and breast compared with the non-supplemented basal diet (p > 0.05). Relative leg weight decreased at levels of 6 and 9 g PJ, and relative back weight was also lower at 3 to 9 g PJ compared with a non-supplemented basal diet (p < 0.05). The 9 g PJ/kg basal diet was associated with lower abdominal fat compared with 3 g PJ (p < 0.05).The effects of PJ levels on carcass traits and body components of broilers are shown in p < 0.05). The diet supplemented with 9 g PJ/kg of the basal diet had a lower ultimate pH (p < 0.05), but the diet supplemented with 3 g PJ/kg had a lower pH difference between initial and ultimate compared with the other supplements (p < 0.05). Breast meat color was not affected by PJ either initially or ultimately (p > 0.05), except 24 h after slaughter (ultimate), at which point yellowness and the saturation index were lower in broilers fed 9 g PJ/kg compared with broilers on a non-supplemented basal diet (p < 0.05).The effects of PJ levels on the physical properties of broiler breast meat are shown in p > 0.05). The results also showed that the individual fatty acids, such as capric acid, lauric acid, palmitic acid, heptadecanoic acid, stearic acid, pristanic acid, lignoceric acid, myristic acid, pentadecanoic acid, tetradecenoic acid, myristioleic acid, palmitoleic acid, vaccenic acid, oleic acid, linoleic acid, arachidonic acid, and linolenic acid, were not significantly different between diets supplemented with 3 to 9 g PJ . Total monounsaturated fatty acids increased at levels of 3 and 9 g PJ compared with a non-supplemented basal diet (p < 0.05). Omega-6 fatty acids and the ratio of omega-6 to omega-3 decreased at levels of 3 g PJ compared with a non-supplemented basal diet (p < 0.05).The effects of PJ levels on the chemical properties of broiler breast meat are shown in p > 0.05). On the other hand, the results show that broiler diets supplemented with PJ were associated with higher cooking water loss percentages (6 and 9 g PJ/kg) and shear force values (3 to 9 g PJ/kg) compared to non-supplemented basal diet (p < 0.05).The effects of PJ levels on broiler breast meat quality are shown in Pulicaria undulata (a species of the genus Pulicaria) [Aromatic medicinal plants have been used since ancient times, but they are still used today in the pharmaceutical industry, for traditional treatments, and as dietary supplements . These plicaria) . No studlicaria)  and Tashlicaria) , who foulicaria) . Diets slicaria) .Indicators of physical properties of chicken breast meat, including pH and color, may play a critical role in determining the quality of fresh meat at the time of sale . The maiOur findings indicate that the chemical properties of breast meat, such as moisture, crude protein, crude fat, ash, and organic matter, were not affected by the addition of PJ to the diet. One of the most crucial indicators of meat quality is the fatty acid composition of breast meat . The levImproving meat quality by focusing on nutrition and supplementation is a very important strategy for broiler production, the food industry, human consumption, and purchasing power . Breast The results indicate that growth performance parameters  improve when broilers are fed PJ, especially in the finishing phase. In addition, carcass characteristics and some meat quality parameters were generally improved by PJ supplementation. The addition of PJ to the birds’ diets also enhanced their fatty acid profiles. Overall, the inclusion of PJ in broiler diets had a positive effect on most carcass and meat quality indices. Therefore, it is strongly recommended that further studies be conducted to validate the potential applications of PJ in improving broiler performance and meat quality.


Inactivation of influenza A virus by radiofrequency (RF) energy exposure at levels near Institute of Electrical and Electronics Engineers (IEEE) safety thresholds has been reported. The authors hypothesized that this inactivation was through a structure-resonant energy transfer mechanism. If this hypothesis is confirmed, such a technology could be used to prevent transmission of virus in occupied public spaces where RF irradiation of surfaces could be performed at scale. The present study aims to both replicate and expand the previous work by investigating the neutralization of bovine coronavirus (BCoV), a surrogate of SARS-CoV-2, by RF radiation in 6–12 GHz range. Results showed an appreciable reduction in BCoV infectivity (up to 77%) due to RF exposure to certain frequencies, but failed to generate enough reduction to be considered clinically significant. This need was made especially evident during the global COVID-19 pandemic where a coronavirus, SARS-CoV-2 spread quickly in part due to its ability to maintain viability for hours in contaminated areas3. Current technologies to clean infected spaces include chemicals or ultraviolet treatments5. Although efficient, these methods require direct contact or line-of-sight with the contaminated area and can be harmful to humans, which limits their deployment in occupied public spaces such as grocery stores and restaurants. Therefore, it is essential to identify technologies that can inhibit viral subsistence safely when employed in such spaces.Sanitization of virus-contaminated spaces is essential to slow the spread of disease6. Previous studies have shown virus neutralization following RF exposure by thermal denaturation (i.e. heat)9. Specifically, early studies of a retrovirus  showed exposure to pulsed RF  neutralized RSV under conditions that generated heat9. Furthermore, more than 90% inactivation of aerosolized MS2 bacteriophage was shown following exposure to 2.45 GHz  by inflicting damage to the viral surface visible under electron microscopic examination8. However, the power density of the exposure was high enough to generate heat in the virus suspension. Additionally, 2.45 GHz has been shown to neutralize suspensions of hepatitis C virus and human immunodeficiency virus  when exposures induced > 60 °C heating for 3 min7. While these studies showed promising evidence that RF heating can induce neutralization of several viruses, the exposure conditions tested in these studies would not be amenable to the creation of a deployable RF technology in occupied spaces, as they generated fields well above IEEE safety standards10.A prospective technology capable of wide area viral decontamination is electromagnetic (EM) radiation-based systems in the radiofrequency (RF) range. RF fields are non-ionizing and have the ability to transmit through a range of materials12. Specifically, a focusing reflectarray antenna was used to expose a suspension of influenza A type H3N2 virus to a range of continuous wave (CW) RF frequencies (6–18 GHz) at a low power density 11. The results of this study showed peak virus neutralization at 8 GHz (93%), which the authors defined as the microwave resonant absorption (MRA) frequency of H3N211. A similar effect was also reported by Yang et al., in a study that exposed H3N2 to RF fields (in the range of 6–12 GHz) to excite confined acoustic vibrations (CAVs) inside the virus via a MRA phenomenon12. The authors proposed a structure-resonant energy transfer (SRET) mechanism inducing CAVs within the virus by the RF field resulting in physical fracturing of the virus particles12. Recently, it has been shown through modeling and experimentation that EM fields can also impact on spike protein confirmation, which is critical for host cell attachment and infection14. In light of these results, we suggest a similar mechanism could be applicable to the neutralization of coronaviruses, as H3N2 is structurally similar to coronaviruses  core. Both virions are similar in size, existing as 80–120 nm spherical particles19. Based on these similarities, we investigated the neutralization of bovine coronavirus (BCoV), a surrogate for SARS-CoV-2, by exposure to RF fields from 6–12 GHz, using an identical exposure setup to that described by Yang et al.12 We performed a comprehensive dosimetric analysis of the CW system to enable comparison of any biological trends observed to RF dose. To assess viral infectivity, we performed cytopathic effects (CPE) analysis on HRT-18G host cell cultures infected with BCoV.Recent research has reported that RF fields can neutralize viruses under exposure conditions without significant bulk heating of viral samples2 in air. The media and its components were purchased from ATCC .Homo sapiens ileocecal colorectal adenocarcinoma cells  were obtained from ATCC . HRT-18G cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 5% fetal bovine serum (FBS) and 100 U/mL penicillin/streptomycin at 37 °C with 5% CO2, 95% relative humidity (RH)) and 1.8 mL of EMEM containing 2% FBS was added to each well. The cells were then incubated for 6 days  to allow infection, as evidenced by the appearance of CPE, described in more detail below. This process was repeated twice with reinfection in successively larger cell culture vessels to create a large volume of BCoV stock for experiments. BCoV stock titer was determined and small volume aliquots were prepared and frozen at − 80 °C until needed for experimentation. Before RF exposure, BCoV samples, depending on exposure configuration, were either placed at 1 mL total volume in 1 × 1 × 4 cm plastic cuvettes  for suspension (solution) samples or were spotted on 25 × 75 mm glass slides (coupon)  and allowed to dry under the laminar flow hood at room temperature for surface samples.BCoV  was acquired from BEI Resources . All experiments containing BCoV were conducted in Eagle’s Minimum Essential Medium  supplemented with 100 U/mL penicillin/streptomycin. BCoV was propagated to create a virus stock via passage in HRT-18G cells. Specifically, HRT-18G cells were grown to confluent monolayers in 6-well plates. Prior to infection, cell monolayers were rinsed twice with serum-free media (SFM) and inoculated with 200 µL of BCoV BEI stock. Virus inoculated cells were incubated for 1 h   was added in line with coaxial source cable before entering the horn antenna. The RF system was placed within a P2 class flow hood. The antenna was directed toward the side for suspension sample exposures , amplified by a 40-W solid state GaN power amplifier  and radiated from a horn antenna . This experimental setup was chosen as it mirrored that used by Yang et al.®, Remcom®, State College, PA), where a Computer-aided Design of the EM6969 horn was used to propagate microwave energy in a free-space environment. We scaled the simulation runs such that the propagated power matched the forward power measurements acquired during the experiments. For each of the eight frequencies , we recorded the simulated power density distribution in a plane 5 cm away from the horn.We performed three-dimensional (3D) computational modeling of the empirical exposure conditions to characterize the spatial distribution of incident fields at the viral sample location. Simulations were performed within a commercial Finite-Difference Time-Domain (FDTD) simulation package  in the exposed solution for each voxel,0–10−4 in SFM and added to HRT-18G cells . Prior to infection, cell monolayers were rinsed twice with SFM and then inoculated with 20 µL of BCoV samples. Cells were incubated for 1 h  and 80 µL of EMEM containing 2% FBS was added to each well. Virus inoculated cells were incubated for 6 days to allow infection to occur. On Day 6 post-inoculation (D6 pi), three independent researchers evaluated each well microscopically to determine if a CPE was present. To prevent bias, researchers were blind to the identity of the samples. After evaluation, the titer of infectious virus was quantified by calculating the TCID50/mL for each condition using the Reed-Muench equation22. To compare results between multiple experiments , we converted the TCID50/mL values to % Inactivation (ratio), as follows:After RF, sham, or heat exposure, each BCoV sample was diluted from 1050/mL) or % inactivation for each RF or heat exposure were compared to sham using one-way analysis of variance with Dunnett’s multiple comparisons test and Student’s t-test. The criterion for significance was set at a p-value < 0.05 for type I error.All experiments were repeated a minimum of three separate times  and the high and low values were subtracted from each condition to eliminate outliers. Data are reported as mean values with error bars representing the standard error of the mean (± S.E.M.). Pairwise comparisons of virus titers  or % Infectivity in any of the exposed conditions compared to sham  exposure where the sample was placed in front of the horn in the experimental configuration, but the RF source remained off. This condition served as a negative control. As described in the methods section, we exposed solutions of BCoV in plastic cuvettes to RF using a system that was tunable to specific frequencies between 6 and 12 GHz. Exposures were performed in triplicate at each frequency and, since two cuvettes were exposed at one time, we achieved an n = 6 for each experimental condition. Figure 12. To accomplish this, we increased the applied power to 30 W (max power generated by our system) at 8.4 GHz, which increased the temperature of the BCoV solution to 54 °C at the end of the exposure  to be considered clinically significant.Since initial experiments did not achieve clinically relevant levels of BCoV neutralization , we refined the frequency sampling interval to investigate whether a resonant peak for inactivation could be found in the 6.5–8.5 GHz range. Therefore, the experiment was repeated in half GHz frequency steps . Results show a significant reduction in virus titer  at 7 GHz (our most effective frequency) and evaluated virus titer/% inactivation. Results show a significant reduction in virus titer Fig. A and a cAs a final investigation of the effects of RF on the neutralization of BCoV, we reduced and/or extended exposure time to see if changing the duration of exposure would change reduction in infectivity. Exposures were conducted at 7 GHz at either 0.02 W Fig. A–B or 6.12. To investigate this effect in the context of coronavirus, we exposed BCoV in solution and dried on a surface using the same RF exposure system and geometry12. Our dosimetry shows we were able to match the power densities reported by Yang et al. (880 ± 44.0 W/m2 versus 810 W/m2 at 8 GHz)12. Additionally, we validated that our conditions did not produce sufficient heating to neutralize BCoV at clinically relevant levels  exposed to RF frequencies between 6–12 GHz range were 100% inactivated, which was hypothesized to be due to induced electromechanical forces disrupting the viral membranels Figs. D–F. Ther10 kill (< 90%), which translated to roughly 30–60% inactivation, depending on the exposure conditions. With respect to antiviral technologies, and to put these results into a broader context, true antiviral technologies must achieve at least 3 log10 (> 99.9%) reduction in infectivity to be considered reasonably effective. Therefore, although we achieved neutralization of BCoV, levels of inactivation would not be considered biologically relevant in the context of antiviral resolutions. Specifically, under the conditions utilized within the present study, the maximum effect achieved was a 77.4 ± 2.9% inactivation, which did not meet the criteria of clinical significance. Notably, even when we significantly increased the RF dose by varying the exposure duration or power level, we did not find greater than 77% neutralization of the BCoV sample  to better match the shape and size of SARS-CoV-2  containment to handle the virus. While these studies were informative, differences in virus composition between non-enveloped viruses such as MS2 made it difficult to conclude that similar effects would occur when treating coronavirus. Therefore, we selected BCoV as a surrogate for SARS-CoV-2 based upon similarities in size and composition between the two beta-coronaviruses  reduction in virus inactivation as observed in the Yang et al.’s study00% reduc28. Very recent work has modeled SARS-CoV-2 virus for mechanical resonance and found that 80–120 MHz to be the optimum frequency, well below that being used in this study13. Using these two results as endcaps for the resonance argument, we hypothesis that the up to 70% reduction in viral infectivity observed in our studies is not due to DNA damage or whole virus resonance (as reported14). As evidenced by our data, we saw very little change in infectivity in bulk exposure of virus within the cuvette, which also carried less thermal rise than would be expected to denature the virus directly24. However, upon placing the virus on a coupon, to simulate a surface, and allowing it to dry, we observed some changes in viral infectivity. From this, we hypothesize two possible mechanism(s). The first is that water left within the sample (amongst proteins and lipid membranes) is heated by the RF exposure creating a thermal gradient resulting in damage. This hypothesis should be tested through modeling of the nanometer scale thermal environment of the virus during exposure. The second hypothesis is that RF is having a direct impact on spike protein orientation limiting its effectiveness to bind to the host cell26. This hypothesis could be tested by analyzing changes in spike protein orientation within viral particles via FRET or Raman methods.From this study, we cannot prove that SRET is occurring within BCoV upon exposure to RF fields. However, we did find that the overall effect appeared to be much less defined than in previous publications, with a “specific” frequency region being much less convincing. This would suggest that the resonant frequency of the virus is either very broad or that another mechanism can account for the loss of viral infectivity during RF exposure. Our measure of viral infectivity could arise from multiple disruption mechanisms like viral DNA damage, inhibition of spike protein binding to the host cell, or whole virus destruction by heat or SRET. Recent models of DNA and RNA from virus show resonant frequencies of 180 GHz required to cause damage, notably higher than what was used in this studyIn conclusion, we evaluated whether low power, CW, RF exposures could inactivate a surrogate coronavirus in the 6–12 GHz range. We observed a statistically significant reduction in viral inactivation on surface preparations; however, this neutralization does not reach clinical significance (> 99% inactivation). Further, the results of the present study, in combination with a lack of definitive theoretical mechanism from previous work, suggest that large area RF exposure would not limit the viability of virus on surfaces and objects under the conditions tested herein. Therefore, at this time we cannot recommend the use of RF technologies to neutralize coronavirus under the conditions tested within the present study. Future studies will focus on virion-level analysis during and after EM field exposure to study mechanism(s) of action resulting in the observed inhibition. Determination of which physical forces are acting on or within the virion will enable more precise tuning of exposure parameters, which may enable clinically-relevant inhibition levels. Additional validation of this mechanism across other virus species should also be performed, to not only aid in determination of mechanism of interaction, but also validate whether or not such mechanism can be broadly applied as an anti-viral technology.