Coercive control is characterised by negative behaviours which intimidate, threaten, and humiliate a person or restrict a person’s liberty. In addition to being a known risk factor for experiencing other forms of violence, research has linked coercive control to symptoms of psychological distress and suicidality. In the UK, coercive and controlling behaviours within intimate and familial relationships have been legislated as offending behaviours. However, there still exists a lack of international evidence on wider public knowledge and understanding of coercive control. The Northern Ireland Life and Times Survey (NILT) is an annual cross-sectional representative survey of social policy topics. Participants are adults aged 18 years or over. Concerning coercive control, respondents were presented with two relationship scenarios: obvious and less obvious coercive control. Following each scenario, respondents indicated their level of agreement to ten statements covering attitudes towards coercive control, victims of coercive control, talking about coercive control, and whether coercive control is a crime. Respondents indicated whether they had heard of the term ‘coercive control’. Predictors of coercive control awareness were assessed using multinomial logistic regression. Mixed analysis of variance assessed if agreement levels to the ten statements varied by type of coercive control and victim gender. Most respondents said that they had heard of the term coercive control and knew what it meant. Those who had not heard of coercive control at all were more likely to be on a lower income, less qualified and younger, when compared to those who said they knew what the term meant. Significant interactions between coercive control type and victim gender were evident for all ten statements. While most respondents are aware of the term coercive control, a significant number have not and are therefore unlikely to recognise the signs of this type of abuse. The concept of coercive control dates back many decades, perhaps most notably established by scholarly feminists who highlighted the significance of power and control within abusive relationships  and abuse more broadly, including questions raised as to its gendered nature Hamby, . Such coThe negative consequence of IPV victimisation to both physical and mental health have been well established  suggesting that the offence is being used across the Criminal Justice System . Cases that had been prosecuted mainly involved other co-occurring offences such as violence against the person. The report authors provide research recommendations which included the need for better robust estimates and characterisation of coercive control as well as further awareness raising and understanding of coercive control among the general population. If those working within police and prosecution services are finding it difficult to recognise and evidence coercive control, so too will victims who are therefore unlikely to continue to report such experiences, particularly in the absence of physical harm  regions and Ireland have developed and implemented legislation which makes an offence of coercive and controlling behaviours within intimate and familial relationships. This pattern of behaviour may include a combination of physical and sexual violence, as well as psychological and emotionally abusive behaviours and tactics which would be considered by a reasonable person to likely have a serious effect on a person  is an annual cross-sectional survey of adults aged 18 years or over living across Northern Ireland. Founded in 1998, the survey uses a two-stage sampling methodology due to the absence of an appropriate individual-level sampling frame. Firstly, a systematic random sample of 15,000 addresses was selected from the Postcode Address File (PAF) list of private addresses. This is the most up-to-date listing of private addresses in Northern Ireland. Secondly, one person aged 18 years or over was randomly selected in each household using the ‘next birthday’ rule. Each letter sent to the selected addresses clearly stated that only the person with the next birthday was eligible to complete the survey online.All previous years of NILT were undertaken using Computer Assisted Personal Interviews (CAPI) within a face-to-face interview, followed by a short self-completion questionnaire. However, the public health restrictions in response to the COVID-19 pandemic necessitated a move to a multi-modal approach in 2020. The survey was designed to be as inclusive as possible, and participants could choose to complete the survey in one of several ways: an online questionnaire, a phone interview or a video call. Where possible, and within government COVID-19 guidelines, face-to-face interviewers also called directly to selected households to encourage participation.The 2020 Northern Ireland Life and Times Survey involved 1,292 interviews with adults aged 18 years or over. 95% of respondents completed the online questionnaire, whilst 5% of respondents participated via a phone or video call interview. A pilot was undertaken from 8–15 October 2020, with the fieldwork being undertaken between 11 November and 8 December 2020. All respondents were offered a £15 shopping voucher as a thank you for taking part. Advance letters were sent to 15,000 households, of which 411 refused to participate. However, the number of respondents was limited by the amount of funding available for the shopping vouchers, and so the survey was closed when 1,300 questionnaires had been completed. Eight surveys were unusable, meaning that 1,292 took part and a response rate of 9%. Full technical details are available at Devine . The datThe 2020 Northern Ireland Life and Times Survey received ethical approval from the Ethics Committee of the School of Social Sciences, Education and Social Work, Queen's University Belfast, where the survey coordinator is based. Respondents were reminded that their participation was voluntary, and that they could withdraw at any time. The sensitive nature of the coercive control questions was also highlighted, and a link was provided to a leaflet providing appropriate sources of support.The survey includes questions on a range of social policy topics, with the range of topics changing each year in order to reflect contemporary social and policy debates. The questions on coercive control were informed by the findings of a consultation with a range of stakeholders with responsibility for relevant policy and service provision in NI. These were from both the statutory sector , and non-governmental organisation sector .https://www.ark.ac.uk/nilt/2020/Coercive_Control/). Respondents were randomly assigned to one of two groups. Group A were presented with two scenarios involving a female victim and a male perpetrator. The two scenarios presented to Group B involved a male victim and a female perpetrator. Following each scenario, respondents indicated their level of agreement or disagreement using a 5-point scale  to ten statements covering attitudes towards: coercive and controlling behaviours; victims of coercive control; talking about coercive control; and whether coercive control is a crime  and less obvious coercive control (scenario 2)  and 519 were male (41% weighted). Responses were not limited to binary options, and two respondents said that they would describe themselves ‘in another way’. However, the ‘in another way’ response was excluded from analysis due to the small number of respondents. Respondents’ age was recoded into a 6-way classification: 18–24-year (8%) 25–34 years (18%), 35–44 years (18%), 45–54 years (20%), 55–64 years (19%), and 65 years or more (17%). 28% of respondents were Catholic, 41% were Protestant, and 27% had no religion. In addition, 13 respondents (1%) were from non-Christian religions. 4% of respondents said that they considered themselves to be a member of a minority ethnic community. The small number of respondents within specific groups (e.g. non-Christian) reflect the wider religious profile of NI, but unfortunately means that the number of respondents is too small to include in statistical analysis. The majority of respondents (93%) reported that they were heterosexual, with 3% saying that they were gay or lesbian, and 2% saying that they were bisexual.Respondents were asked to identify their highest educational qualification, and this was recoded into the following categories: degree level or higher (54%), higher education (11%), A level or equivalent (8%), GCSE grades A to C or equivalent (16%), GCSE grades D to G or equivalent (7%), other qualifications (3%), and no qualifications (4%). For the purposes of the multivariate analysis, this variable was reverse coded ranging from 1  to 6 (degree level or higher), and the ‘other qualification’ and ‘don’t know’ responses were excluded. Self-reported income level responses were 1: low income (7%), 2: middle income (62%) and 3: high income (28%), with 4% indicating that they didn’t know. An urban/rural indicator, as defined by the Northern Ireland Statistics and Research Agency, was applied based on the respondent’s postcode.Legal relationship status was assigned based on responses to a question on legal status: 1: single (never married) (28%); 2: married and living with spouse (59%); 3: civil partner in legally-registered partnership (1%); 4: married and separated from spouse (3%); 5: divorced (6%); 6: widowed 4%): 7: in legally-recognised civil partnership and separated from civil partner (0%); 8: formerly a civil partner, the civil partnership now legally dissolved (0%); 9: surviving civil partner as partner having since died (9%). Those respondents giving responses 2 or 3 (59%) were classified as in a legal relationship.https://www.nisra.gov.uk/publications/chs-results).The results of the most recent Census of Population (undertaken in April 2021) are not yet available, and so comparison must be made with appropriate robust large-scale sample surveys. The demographic profile of the NILT respondents reflects the profile of the wider population as evidenced by the Continuous Household Survey (CHS) survey  and B  were compared using chi-squared tests for gender, income, urban/rural and legal relationship, and via independent samples t-tests for the age and qualification variables.Multinomial logistic regression models were used to examine predictors of coercive control awareness. The reference category was ‘yes, and I know what it means’, and this was compared against ‘yes, but I am unsure what it means’, and ‘no’, responses. ‘Don’t know’ responses to the awareness of coercive control question were excluded from the multinomial regression models as their rarity (1%) increased the risk of biased estimates. Predictors included in the models were age, income, qualifications, legal relationship , gender , and urban/rural (reference = urban). Income and qualification variables were treated as continuous by excluding the small proportion of people who ticked ‘don’t know’ to the income question (4%) and those who ticked ‘other’ to the qualification question (3%). There were < 0.1% ‘don’t know’ responses to the age, gender, legal relationship and urban/rural questions; such responses were excluded from the analyses.Mixed analysis of variance models assessed if agreement levels to the ten statements varied by type of coercive control (obvious vs less obvious) and victim gender  and respondent gender . In these models ‘don’t know’ responses were excluded so that the dependent variables could be treated as continuous. Separate analyses were conducted to examine if victim gender was associated with the likelihood of responding ‘don’t know’ to the statements presented in the obvious and less obvious coercive control scenarios.Listwise deletion was used in all analyses as levels of missing data on the coercive control questions (0.4–0.7%) and demographic questions (0.0–2.1%) were very low.Descriptive statistics for Samples A and B are displayed in Table n = 811; 62.9%). The remainder had heard of coercive control but did not know what it meant ; had never heard of it  or responded ‘don’t know’ . Predictors of coercive control awareness were examined via multinomial logistic regression (Table The majority of respondents said that they had heard of the term coercive control and knew what it meant (frightened (t (1267) = 4.54, p < 0.001, d = 0.27); physical harm (t (1250) = 3.33, p = 0.001, d = 0.19); tell friends & family (t (1264) = 3.37, p = 0.001, d = 0.19); friends/family consider it domestic abuse (t (1257) = 3.29, p = 0.001, d = 0.17); report to police (t (1255) = 4.07, p < 0.001, d = 0.22); police view behaviour as criminal (t (1194) = 3.34, p = 0.001, d = 0.19); behaviour should be a crime (t (1258) = 2.37, p = 0.018, d = 0.13). All of these effects were small in nature  = 12.02, p < 0.001, d = 0.68); physical harm (t (1175) = 11.13, p < 0.001, d = 0.64); mental health (t (1266) = 7.60, p < 0.001, d = 0.43); tell friends & family (t (1262) = 9.43, p < 0.001, d = 0.54); friends/family consider it domestic abuse (t (1233) = 10.68, p < 0.001, d = 0.61); report to police (t (1205) = 9.92, p < 0.001, d = 0.57); police view behaviour as criminal (t (1174) = 7.42, p < 0.001, d = 0.43); behaviour is domestic abuse (t (1239) = 9.20, p < 0.001, d = 0.53); behaviour should be a crime (t (1219) = 10.46, p < 0.001, d = 0.60). Generally speaking, these effect sizes correspond most closely with a medium sized effect  = 4.75, p < 0.001, d = 0.29).For the less obvious abuse scenarios, agreement was higher when the victim was described as female as opposed to male for nine of the ten statements: t Cohen, . In the commonplace (10.8%) and police view behaviour as criminal (6.9%). In the less obvious coercive control ‘don’t know’ represented < 5% of responses for five of the ten statements presented, and were somewhat higher for commonplace (10.3%), physical harm (8.3%), report to police (6%), police view behaviour as criminal (8.5%), and behaviour should be a crime (5.1%). Chi-squared difference tests showed no significant association between victim gender and the tendency to respond ‘don’t know’ in the obvious coercive control scenarios. In less obvious coercive control scenarios, for three of the ten statements a greater proportion of respondents chose ‘don’t know’ when the victim was female as opposed to male: physical harm  = 4.00, p = 0.045); report to police  = 9.66, p = 0.002); police view behaviour as criminal  = 15.80, p < 0.001).‘Don’t know’ responses constituted < 5% of responses to the statements presented in the obvious coercive control scenario, with the exception on police view behaviour as criminal, reflecting generally higher levels of agreement for the obvious scenarios and for female respondents. The interaction between respondent gender and coercive control type was significant for the other statements. While the interaction effect for commonplace was significant, the independent samples t-tests used to explore this interaction showed no significant difference between males and females for the obvious and the less obvious conditions. A significant interaction was also evident for report to police; however, the effect size was negligible. For the other seven statements, in both the obvious and less obvious coercive control scenarios, female respondents expressed higher levels of agreement than males. The gender difference was greater for the less obvious than the obvious scenarios as evidenced by visual inspection of the interaction plots and the independent t-tests used to unpick the interactions: frightened—obvious (t (1265) = -5.21, p < 0.001, d = 0.31); frightened – less obvious (t (1243) = -5.68, p < 0.001, d = 0.33); physical harm—obvious (t (1248) = -4.19, p < 0.001, d = 0.25); physical harm – less obvious (t (1173) = -5.38, p < 0.001, d = 0.32); mental health—obvious (t (1269) = -4.86, p < 0.001, d = 0.27); mental health – less obvious (t (1264) = -9.31, p < 0.001, d = 0.53); tell friends & family—obvious (t (1262) = -4.75, p < 0.001, d = 0.29); tell friends & family – less obvious (t (1260) = -7.81, p < 0.001, d = 0.45); friends/family consider it domestic abuse—obvious (t (1255) = -3.44, p = 0.001, d = 0.21); friends/family consider it domestic abuse – less obvious (t (1231) = -4.62, p < 0.001, d = 0.27); behaviour is domestic abuse—obvious (t (1266) = -4.19, p < 0.001, d = 0.23);Mean agreement scores to the coercive control statements by coercive control type and respondent gender are displayed in Table behaviour is domestic abuse – less obvious (t (1237) = -7.15, p < 0.001, d = 0.41); behaviour should be a crime – obvious (t (1256) = -5.98, p < 0.001, d = 0.34); behaviour should be a crime – less obvious (t (1217) = -7.88, p < 0.001, d = 0.47).Whilst there is a growing body of work geared towards conceptualisation and measurement of coercive control . Whilst it is encouraging that 63% had heard of the term and understood what it means, the present study did find that awareness rates were significantly lower than this for certain demographic groups; specifically, young people, males, those who are less qualified, and those from a low income background. These findings are perhaps unsurprising given the body of evidence which discusses the links between low income households, education and younger age as a vulnerability factor for IPV victimisation . Additionally, early educational interventions which can be embedded into the curriculum which focus on the development of both healthy and unhealthy relationships should be considered in order to forearm those potentially most at risk of IPV. Such education programmes focusing of sex and relationships have a long history (Meyer & Stein, The level of analysis available from the current data limits in depth exploration of the societal reasons that may underlie the gender bias towards male and female victims of IPV among this population. That said, recent evidence following from a Fundamental Rights Survey FRA,  on crimeGiven the nature of population surveys, there is always a degree of uncertainty as to the accuracy of the responses received. We cannot rule out the possibility of social-desirability bias in the answers given, which may have led to an overestimation of the level of awareness of coercive control. The limitations with the questions used to ascertain knowledge of coercive control should also be acknowledged. It is difficult to fully elicit participant’s awareness of coercive control in a survey. The question asked if they thought it was commonplace but does not clarify how common they thought it was. Future research should explore differences in perceptions of the prevalence of coercive control across different genders and other groups. Also asking if someone has heard of the term coercive control is a quite basic measure of awareness. Other questions could be asked to unpick this further, but to properly explore awareness, qualitative methods would allow for a deeper understanding of awareness.Finally, attitudes to domestic abuse vary across cultures. Due to the limited diversity in the Northern Ireland population, it was not possible to analyse data to compare levels of knowledge and understanding across different ethnic groups. Future research should therefore extend to other countries to explore differences in those from different cultural backgrounds.The experience of domestic abuse is seldom the result of an isolated incident. Coercive control as a form of domestic abuse generally becomes apparent when associated behaviours develop into a pattern over time, by which stage the importance of identifying the early ‘minor’ acts of coercion and control have become clear Stark, . This tyResearch continues to reflect on the difficulty in operationalising coercive and controlling behaviour (Stark & Hester,


Lactobacillus acidophilus  or monensin on performance of replacement beef heifers. Heifers received a total mixed ration containing either LaP (n = 77) or monensin . Heifers were fed for 71 d in a GrowSafe unit, so individual feed intake could be measured. Heifers were weighed every 2 wk and feed efficiency calculated by residual feed intake (RFI). At the end of the RFI trial, heifers remained on their diets for an additional 27 d and were estrus synchronized using the 14-d CIDR + PG protocol and bred by artificial insemination (AI) followed by natural service. Prior to estrous synchronization, reproductive tract scores  were measured. Continuous variables were analyzed using generalized mixed models, whereas categorical data were analyzed by logistic regression. Body weights, average daily gain, feed intake, and RFI value were similar (P > 0.30) among MON- and LaP-supplemented heifers. Across treatments, heifers gained 0.9 ± 0.1 kg/d while consuming 9.3 ± 0.5 kg of diets daily. Reproductive development as indicated by RTS was similar (P > 0.28) between treatments. However, estrus response increased (P < 0.01) and AI pregnancy rates tended to be greater (P < 0.07) for MON compared to LaP heifers. In contrast, the percentage of heifers pregnant by 60 and 100 d  was not different (P > 0.33) for MON and LaP heifers. In conclusion, addition of LaP to replacement heifer diets may result in growth and reproductive performance similar to an ionophore, if dietary energy is adequate for normal heifer growth.The objective of the experiment was to compare the effect of dietary inclusion of a prebiotic fermentation product of  Developing replacement heifers is a critical and expensive enterprise of the cow-calf operation. Nutrition during the postweaning development phase will impact heifer reproductive development as well as direct costs . AdditioPrebiotics and probiotics may offer an alternative to ionophores in growing cattle diets. These feed additives alter rumen microflora populations and resulting fermentation products . HoweverL. acidophilus prebiotic product  compared to steers supplemented with monensin  in steers supplemented with a monensin . The expAll procedures were approved by the University of Idaho Animal Care and Use Committee (protocol numbers 2017-61 and 2018-27).n = 162) were stratified by age, weight, and previous preweaning and backgrounding treatments and then randomly assigned to receive diets containing either monensin  or LaP  feed additive. Heifers were born to Angus × Hereford dams and sired by Angus, Hereford, or SimAngus sires. Heifers previously had been used on projects which involved different preweaning grazing locations  in age and weight averaging 322.1 ± 2.1 d of age and 285.5 ± 13.8 kg.Crossbred replacement beef heifers  provided minerals, vitamins, and MON or LaP . Diets wThe MON and LaP diets were mixed in separate feed trucks to eliminate possibility of cross contamination of diets. Feed was delivered at 0700, 1400, and 2000 h daily. Bunks were cleaned once weekly, and all orts discarded. To minimize variation in treatment, the same lots of ground hay and wheat middlings were used for both diets. However, variation in diets can occur due to small errors in the loading and mixing procedures . Feed saAll heifers were fed in a GrowSafe System  consisting of 5 nodes per pen and 2 pens per MON and LaP treatment for a total of 4 pens. Each pen was designed to provide enough physical and GrowSafe bunk space to support 40 to 45 heifers per pen. A 14-d warm-up period was followed by a 98-d experimental period. After the 14-d warm-up period, 6 heifers were removed from the experiment due to failure to eat out of the GrowSafe bunks resulting in 77 MON and 79 LaP heifers, respectfully.Heifers were weighed on two consecutive days at the beginning of the experiment (days 1 and 2), at the end of the residual feed intake trial (days 70 and 71), and end of the experiment (days 97 and 98). Consecutive weights were averaged. In addition, heifers were weighed every 2 wk during the experiment. Beginning and final weights were used to calculate trial ADG. Individual animal feed intakes were recorded daily. Diet dry matter was determined daily for each diet and used to calculate individual animal daily DMI. Fat thickness between the 12th and 13th ribs was measured by ultrasound at the conclusion of the residual feed intake (RFI) trial. Residual feed intake was calculated based on methodology previously used in our laboratory . The finn = 3 MON; n = 5 LaP) were eliminated from breeding due to size or an RTS = 1. Heifers were estrus synchronized using the 14-d CIDR + PG protocol  16 d after CIDR removal and artificially inseminated (AI) with one of two Angus bulls at 72 h after PGF2α administration. An estrus detection aid  was applied to each heifer at the time of PGF2α administration. Fourteen days after AI, clean-up bulls were introduced for an additional 30 d. Pregnancy status was determined via ultrasonography at 60 d and via palpation at 100 d after AI. Ultrasound examination at 60 d was used to differentiate AI sired fetuses from natural service sired fetuses.After the conclusion of the RFI feeding period, heifers remained in their respective pens and were fed the same diet until the conclusion of artificial insemination. Prior to estrous synchronization, heifers were weighed, body condition scored, and reproductive tracts scored. Body condition scores were from 1 = emaciated to 9 = obese . Reproduprotocol . BrieflyAnimal was the experimental unit as the GrowSafe system allows for calculation of individual animal intakes. The data analysis for this paper was generated using SAS software (v9.4), Copyright © 2016 SAS Institute Inc., Cary, NC. Body weights were analyzed by generalized mixed model with repeated measures using MIXED procedures. The model included feed additive, time and feed additive × time interaction as fixed effects with feed additive × backgrounding regime, sire breed, summer grazing location, and feed additive × backgrounding regime × time as random effects. Generalized mixed model was used to analyze each weighing event ADG, trial ADG, and trial weight gain included fixed effect of feed additive, backgrounding regime, and feed additive × backgrounding regime interaction with pen × feed additive, sire breed, and summer grazing location as random effects.Residual feed intake and DMI were analyzed by generalized mixed model with fixed effect of feed additive, backgrounding regime, and feed additive × backgrounding regime interaction with pen, sire breed, and summer grazing location as random effects. General mixed model (GLIMMIX) analysis using a multinomial categorical model was used to compare percentage of heifers LaP and MON heifers in each RFI group. Logistic regression modeling the probability of pregnancy at AI, 60 d, and 100 d was used. Models were adjusted for body condition, BW, and age.For all analyses, a 95% confidence interval was used with P < 0.05 considered significant and P < 0.10 considered a tendency.P > 0.50) of preweaning grazing location or backgrounding regime or their interactions with feed additive. However, these fixed effects remained in the model.Across all analyses, there were no effects (P = 0.169) for heifers receiving MON or LaP at all weighing events. Body weights increased (P < 0.0001) over time (P = 0.99). Overall experiment ADG was similar (P < 0.99) between MON and LaP heifers averaging 0.9 ± 0.1 kg/d. Average daily gain by weighing event was not affected (P > 0.26) by feed additive; however, gains among weighing events varied  between heifers receiving MON and LaP averaging 9.2 ± 0.5 and 9.4 ± 0.5 kg/d, respectively. Average RFI did not differ (P = 0.45) between feed additives . Percentage of heifers in RFI groups was not affected (P = 0.54) by feed additive. Distribution by RFI group for MON and LaP, respectively, was Efficient , Average , and Inefficient .Dry matter intake was similar (P > 0.28) between MON and LaP heifers (P < 0.01) for LaP compared to MON heifers (P < 0.01) in MON compared to LaP. There was a tendency for more MON heifers to conceive to AI than LaP heifers (P < 0.07). However, pregnancy rates were similar at 60 d (P = 0.33) and 100 d (P = 0.66) after AI for heifers consuming MON or LaP, and across feed additives averaged 80.4% and 90.5% for 60 and 100 d, respectively.Prebreeding BW and RTS were not different  or prebiotics (n = 8) on performance and health in calves. Although 71% of the probiotic trials examined resulted in increased weight gain compared to controls, only 25% of the prebiotic studies demonstrated a growth advantage. Only 25% of both prebiotic and probiotic studies reported increases in feed efficiency, whereas 50% of trials indicated health benefits.Animal response to prebiotics or probiotics can be highly variable and may be dependent on a variety of factors including health or age of the animal, percentage of concentrates in the diet, or type of prebiotic/probiotic provided . Uyeno eLactobacillus and Bifidobacterium with concomitant reductions in Salmonella and E. coli . Based on this information, it is not clear what components of this product may have the greatest effect on animal response or the precise mechanism of action. Previously, we reported reductions in production of propionate and increases in butyrate, valerate, and isovalerate in vitro between LaP compared to MON supplementation (Lactobacillus acidophilus produces the bacterioncins lactocin B, lactacin F, acidocin A, and acidocin B (The prebiotic used in the present study is a entation . Lactobaidocin B . WhetherL. acidophilus fermentation product as a prebiotic may be a viable substitute for ionophores in replacement heifer diets. Based on the conditions of the present study, growth and reproductive responses to this type of prebiotic appear to be similar to monensin in diets containing sufficient energy to support recommended growth rates in heifers. Further investigation on L. acidophilus fermentation products on growth as well as focusing on dose-response, rumen function, and mechanisms of action is warranted.In summary, the use of a


Belonolaimus longicaudatus and Meloidogyne incognita in greenhouse, microplot, and field settings over 2018 and 2019. Both greenhouse evaluations demonstrated multiple rates of fluazaindolizine reduced B. longicaudatus population density, and one of the two M. incognita trials showed multiple rates of fluazaindolizine reduced nematode population density. Fluazaindolizine was also effective at reducing population density of both B. longicaudatus and M. incognita in microplot settings for both 2018 and 2019, and a significant improvement in turf quality was observed for both visual turfgrass ratings and NDVI. Field trials demonstrated a significant reduction for both B. longicaudatus and M. incognita population density by multiple rates of fluazaindolizine, but no significant differences in turf quality ratings were observed. Overall, fluazaindolizine shows promise as a chemical nematicide for plant-parasitic nematode management on turfgrass.Plant-parasitic nematodes are a major pest of turfgrass in the United States, yet there are few options for successful management. Most current management strategies rely on the use of a limited number of chemical nematicides, so finding a new management option for nematode suppression would be extremely valuable for turfgrass managers. The aim of this study is to evaluate a new nematicide, fluazaindolizine (Reklemel™ active), for its ability to reduce plant-parasitic nematode population density and improve turfgrass quality. Separate research trials were conducted on bermudagrass infested with  HoweverMeloidogyne incognita juveniles compared to untreated juveniles, and greenhouse assays of fluazaindolizine on tomato have lowered M. incognita’s reproductive factor  , a novel sulfonamide recently discovered to have nematicidal properties  . Assessmdensity) . Fluazai carrots . Hajihas control .M. incognita and Belonolaimus longicaudatus population density on bermudagrass was evaluated. The overall objective of this study was to evaluate the potential of fluazaindolizine as a chemical nematicide for turfgrass in greenhouse, microplot, and field settings. The determination of fluazaindolizine efficacy as a turfgrass nematicide was evaluated by both its ability to reduce plant-parasitic nematode population density, and its ability to improve overall turf health.With such a limited number of chemical nematicide options available for plant-parasitic nematode management on turfgrass, fluazaindolizine would be a beneficial addition for nematode management. Thus, the ability of fluazaindolizine to reduce both M. incognita and B. longicaudatus population density throughout the study. Fluopyram  was included as a chemical control, and an additional treatment of tap water was used as a negative control. Treatments for the experiments were (1) 4 applications of fluazaindolizine at a rate of 1.1 kg ai/ha at 0, 4, 8, and 12 weeks after trial initiation, (2) 2 applications of fluazaindolizine at a rate of 2.25 kg ai/ha (weeks 0 and 8), (3) 1 application of fluazaindolizine at a rate of 4.5 kg ai/ha (week 0), (4) 2 applications of fluopyram at 0.25 kg ai/ha (weeks 0 and 8), and (5) an untreated tap water control.The fluazaindolizine test substance used in these studies was a candidate suspension concentrate formulation containing 500 g/L of the active ingredient. Three rates of fluazaindolizine were evaluated for their ability to reduce both B. longicaudatus, and the other M. incognita. In all, 500 cm3 polystyrene pots were filled with 100% sand. Each pot was then seeded with 1 gram of ‘Princess 77’ bermudagrass seed. Pots were watered daily as needed to allow for germination, and given 6 weeks for root establishment before trial initiation. Pots were also fertilized every 14 days using 24-8-16 (N-P2O5-K2O) at a rate of 0.5 kg N per 100 m2 per growing month and trimmed once a week to a height of 2.54 cm. Lighting was supplied via 1,000-watt halide bulbs producing 110,000 lumens for 14 h per day and temperatures in the greenhouse ranged from 24 to 35°C. Nematicide treatments were applied as foliar sprays via a handheld spray bottle, and treatments were diluted so that two sprays from the bottle was the calibrated rate.Two separate greenhouse trials were conducted in 2018 and repeated in 2019 at the Plant Science Research Center (PSRC) at Auburn University, Auburn, AL. One trial evaluated the efficacy of fluazaindolizine on Meloidogyne incognita race 3, originally isolated from an infested field at the Plant Breeding Unit (PBU) at E.V. Smith Research Center of Auburn University and maintained on corn “Mycogen 2H723”  in 500 cm3 polystyrene pots in the greenhouse, was used as inoculum in the first experiment  with five replications. Turfgrass vigor was calculated using the National Turfgrass Evaluation Program (NTEP) guidelines . Visual ratings consisted of a 1–9 rating scale, where 1 was very poor quality turf, 6 was minimal acceptable turf quality, and 9 was exceptional turf quality . The norescribed . ExtractM. incognita eggs were inoculated at a rate of 50,000 eggs per pot on a weekly basis for 4 weeks to build up nematode population density in half of the microplots. The remaining microplots received an inoculation rate of 100 B. longicaudatus nematodes per pot on a weekly basis for 4 weeks. After the 4-week inoculation period, a 100-cm3 soil sample was taken from each plot to confirm M. incognita or B. longicaudatus presence. Treatments were applied as foliar sprays via a handheld spray bottle, and treatments were diluted so that two sprays from the bottle was the calibrated rate for each treatment per microplot. Treatment regimen was identical in application rates and timing as greenhouse experiments. Each microplot received water at 30 mL/min by an automated drip irrigation system adjusted throughout the season to run for 30 min twice a day every other day. Grass was trimmed twice a week to a height of 2.5 cm.The same treatments used in the greenhouse experiments were used for trials conducted in a microplot setting. Microplot trials were conducted in two separate years (2018 and 2019) at the PSRC in Auburn, AL. All plots were arranged in a RCBD with five replications. For these trials, 26.5-liter plastic tree pots were used as microplots. Pots were nested one on top of the other with a brick in between to limit root growth by air pruning. The nested pot design was buried in the ground with one inch of the pot above the soil surface. Microplots were then filled with 100% medium-coarse sand (0.25–1.0 mm). ‘Tifway’ hybrid bermudagrass sod was established in each plot and given 10 weeks for root establishment. At the end of the 10-week period, Visual turfgrass ratings and NDVI ratings with the handheld sensor were taken throughout the trial starting at trial initiation followed by 7-day increments. Nematode population density was determined at three time points during the trial in 2018 , and four time points in 2019 . Nematode extraction and population density determination was performed as previously described.Belonolaimus longicaudatus was conducted on common bermudagrass grown under fairway conditions at the Auburn University Gulf Coast Research and Extension Center (GCREC) in Fairhope, AL after confirming B. longicaudatus presence. The treatments for both greenhouse and microplot trials were also used for the field evaluation. Individual plots were 1.5 meters by 3 meters, with a 0.6-meter border between adjacent plots. The trial was set up as a randomized complete block design with five replications. Each treatment was mixed with water to a total volume of one gallon and sprayed on the plots with a CO2-powered backpack sprayer .In 2018, a field trial evaluating fluazaindolizine as a turfgrass nematicide for Belonolaimus longicaudatus evaluations, and an adjacent location with a confirmed population density of Meloidogyne spp. The treatment list remained the same as previous studies for both nematode trials.Two field trials were conducted in 2019 for evaluating fluazaindolizine as a turfgrass nematicide. Trials were conducted at GCREC in the same location as 2018 for 3 subsample and enumerated as previously described.Data collection was the same for both years. Visual turfgrass ratings and NDVI values with a handheld sensor were taken at the start of the experiment, followed by approximately 2-week intervals throughout the trial as previously described. Along with these measurements, field trials were mapped with a DJI Phantom 4 Professional drone . This drone was equipped with a MicaSense RedEdge-M sensor . Image processing was performed with Pix4Dmapper , and image analysis was carried out with ArcMap , providing NDVI and NDRE ratings for each plot. Nematode samples were taken at three time points in 2018  and four time points in 2019 , approximately at 4-week intervals. Nematode samples consisted of seven 2.22-cm-diameter × 10-cm-deep cores from each plot. Samples were thoroughly mixed, and nematodes were extracted from a 100 cmB. longicaudatus per 100 cm3 soil, M. incognita per 100 cm3 soil, visual turf quality, and NDVI. The fixed effect was nematicide treatment, and random effects included replication, test repeat, and location. Student panels were generated to determine the normality of residuals. For greenhouse and microplot evaluations, LS-means were compared between treatments by Tukey’s multiple range test for each evaluation date (P ≤ 0.05). For the microplot evaluation, visual turfgrass quality and NDVI ratings were compared statistically by linear correlation at each nematode sample date .Data collected from greenhouse, microplot, and field evaluations were analyzed using the PROC GLIMMIX procedure . Dependent variables included M. incognita population density compared to the untreated control in 2018 greenhouse evaluations (P ≤ 0.05)  (P ≤ 0.05). In 2019, the 2.25 kg ai/ha and 4.5 kg ai/ha rates of fluazaindolizine as well as the fluopyram control significantly reduced B. longicaudatus population density compared to the untreated control (P ≤ 0.05) (All nematicide treatments significantly reduced  ≤ 0.05) . However ≤ 0.05) . Fluopyr ≤ 0.05) .M. incognita microplot evaluations, all nematicide treatments significantly reduced population density compared to the untreated control at both the August and September evaluation date (P ≤ 0.05) (P ≤ 0.05) (P ≤ 0.05) (In the 2018  ≤ 0.05) . For vis ≤ 0.05) . Six of  ≤ 0.05) .M. incognita population density in the microplot trial. The 4.5 kg ai/ha rate of fluazaindolizine and the fluopyram treatment significantly reduced M. incognita population density compared to the untreated control at the August, September, and October sample dates, and the 2.25 kg ai/ha rate of fluazaindolizine significantly lowered population density at the October sample date (P ≤ 0.05) (P ≤ 0.05) (P ≤ 0.05). For the NDVI evaluations, significant differences between treatments were observed at all evaluation dates, with fluopyram having the numerically largest value throughout the entire trial (P ≤ 0.05)  . Of the  ≤ 0.05) . This wa ≤ 0.05) .Belonolaimus longicaudatus population density was significantly reduced by all nematicides in the 2018 microplot trial at both evaluation dates after trial initiation (P ≤ 0.05) (P ≤ 0.05)   (P ≤ 0.05) ( ≤ 0.05) . Visual  ≤ 0.05) . NDVI wa ≤ 0.05) . In the  ≤ 0.05) . This le ≤ 0.05) .M. incognita and B. longicaudatus population density when compared to both visual turfgrass quality and NDVI  and NDVI (P ≤ 0.01) in 2018, and all four nematode sample dates in 2019 (P ≤ 0.05). For B. longicaudatus evaluations, two of the three sample dates had a significant correlation with both visual quality and NDVI in 2018 (P ≤ 0.01), and all four nematode sample dates in 2019 (P ≤ 0.001).Significant linear correlations were observed in the microplot trials throughout 2018 and 2019 for both and NDVI . In geneB. longicaudatus population density at the September and October sample dates, and the 2.25 kg ai/ha rate of fluazaindolizine significantly reduced population density at the October sample date (P ≤ 0.05). In both the B. longicaudatus and M. incognita 2019 field trials, three of the four nematicide treatments significantly reduced nematode population density compared to the untreated control at the August evaluation date, and all nematicides significantly reduced population density at the September and October evaluation dates (P ≤ 0.05)  .B. longicaudatus and M. incognita below the standard 10 and 80 per 100 cm3 of soil. In the microplot trials, both visual turfgrass quality ratings and NDVI were significantly improved by multiple rates of fluazaindolizine. Thus, with a reduction in both B. longicaudatus and M. incognita population density, and a general improvement in plant health, both efficacy criteria for fluazaindolizine evaluation were met.The results from both year’s greenhouse, microplot, and field evaluations of fluazaindolizine indicate that there is a strong potential for its use in plant-parasitic nematode management in turfgrass. Plant-parasitic nematode population density was significantly lowered when compared to an untreated control in all three settings. These significant population declines did overall reduce numbers of B. longicaudatus and M. incognita trials. A numerical rate response was also observed, with higher rates of fluazaindolizine leading to lower final population density in all trials. While a significant reduction in M. incognita population density was not observed compared to the untreated control in the 2019 trial, no final population density for any of the evaluated fluazaindolizine rates were at levels that traditionally are of concern for a turfgrass manager in the southeastern United States  to confirm the findings of this study.This research confirms previous studies that have shown a similar efficacy of fluazaindolizine to d tomato . Howeveroutheast . For thiM. incognita and B. longicaudatus population density, higher initial application rates of fluazaindolizine were more consistent at both lowering nematode population density and improving plant health quality. While these results show promise for this product, more studies need to be conducted. Overall, fluazaindolizine appears to have strong potential for including in a turfgrass nematode integrated management program.To our knowledge, this is the first published study on fluazaindolizine efficacy as a turfgrass nematicide. These findings indicate that while each rate evaluated was successful at lowering both


The effect of low‐level pretransplant donor‐specific antibody (DSA) on kidney transplant outcomes is not well described. The goal of this study was to compare outcomes among patients of varying immunologic risk, based on the level of pretransplant DSA.SUM < 100]), low‐level DSA (MFISUM 100–1000), and positive DSA (MFISUM > 1000). Rejection, infection, graft, and patient survival were outcomes measured.We retrospectively reviewed all adult kidney transplant recipients who had undergone a transplant at our center between January 2013 and May 2017. Patients were grouped as negative DSA . The rate of BK viremia was highest in the positive DSA group (39.7%), followed by the low‐level group (30.4%) and the negative DSA group (25.6%), (p = .025). None of the other outcomes, including graft or patient survival, were different between the groups.Of 952 patients, 82.1% had negative DSA, 10.7% had low‐level DSA, and 7.1% had positive DSA. The positive DSA group had the highest rate of antibody‐mediated rejection (10.3%), followed by low‐level DSA (7.8%) and the negative DSA group (4.5%) . Also, the rate of BK viremia was highest in the positive DSA group (39.7%), followed by the low‐level group (30.4%) and the negative DSA group (25.6%), (p = .025).The presence of pretransplant donor‐specific antibody (DSA) represents a significant barrier to kidney transplantation for highly sensitized patients as they are less likely to undergo transplants compared with their nonsensitized counterparts. The goal of this study was to compare outcomes among patients of varying immunologic risk, based on the level of pre‐transplant DSA. The positive DSA group had the highest rate of antibody‐mediated rejection (10.3%), followed by low‐level DSA (7.8%) and the negative DSA group (4.5%) ( ABMRantibody‐mediated rejectionATGantithymocyte globulinBMIbody mass indexCITcold ischemia timeCMVcytomegaloviruscPRAcalculated panel reactive antibodiesDBDdonation after brain deathDGFdelayed graft functiondnDSAde novo donor‐specific antibodyDSAdonor‐specific antibodyHLAhuman leukocyte antigenKDPIkidney donor profile indexMFImean fluorescence intensityPRApanel reactive antibodiesSABsingle antigen beadTCMRT‐cell mediated rejectionVXMvirtual crossmatch1The presence of pretransplant donor‐specific antibody (DSA) represents a significant barrier to kidney transplantation for highly sensitized patients as they are less likely to undergo transplants compared with their nonsensitized counterparts.sum]); and (3) positive DSA ( >1000 MFIsum). The goal of this study is to compare the incidence of rejection, graft survival, patient survival, and infection complications among patients stratified by the DSA level.Previous studies have described the association between pretransplant DSA and increased risk of antibody‐mediated rejection (ABMR); however, there is a lack of data demonstrating at what level of DSA patients are at risk for developing rejection or infectious complications. Therefore, it is critical to better understand the relationship between both low and high‐level pretransplant DSAs and the risk of rejection and infectious complications. Our institution has implemented a pretransplant DSA protocol that stratifies patients based on the intensity of pretransplant DSA.22.1sum 100–1000), and positive DSA (MFIsum > 1000)  of all pretransplant DSA, when more than one bead with pretransplant DSA was present. All patients with low‐level DSA had a negative flow crossmatch and those with positive DSA had a negative or low positive flow crossmatch .This was a single‐center, longitudinal cohort study of patients undergoing kidney transplantation at our institution between January 2013 and May 2017. Data were obtained from the prospectively collected Wisconsin Allograft Recipient Database and electronic medical records at the University of Wisconsin Hospital. Institutional review board approval was obtained before the study. The activities in this paper conform to the Principles of the Declaration of Istanbul. Patients were excluded if they were not tested for DSA pretransplant or if they were less than 18 years old at the time of transplant. Patients were then grouped according to their pretransplant DSA level as follows: negative DSA (MFI < 100), low‐level DSA , or mixed rejection based on the most recently available Banff criteria.2.3Choice of induction therapy is based on patient‐specific variables including immunological risk, age, primary cause of end‐stage renal disease (ESRD), and plan for early steroid withdrawal. Patients with pretransplant DSA or glomerulonephritis as a cause of ESRD are more likely to receive induction with antithymocyte globulin (ATG). Recipients planned for an early steroid withdrawal are likely to receive alemtuzumab for induction. Alemtuzumab is given as a single intraoperative 30 mg dose for induction. Dosing of ATG for induction at our institution involves an intraoperative dose of 1.5 mg/kg followed by daily postoperative dosing to a goal of 4.5–6 mg/kg based on immunological risk. Basiliximab is given as a single intraoperative 20 mg dose with an optional additional 20 mg dose given on postoperative Day 3, per surgeon discretion. The protocolled posttransplant maintenance immunosuppressive regimen at our center is a triple‐drug regimen consisting of tacrolimus, mycophenolate, and corticosteroids. Institutional protocol dictates tacrolimus troughs range between 5 and 12 ng/ml for the first year after transplant, with higher targets earlier posttransplant.2.4sum 100–1000 as a low level and more than 1000 as a positive group. Recipients in the low‐level DSA group receive T‐cell depleting induction with alemtuzumab or ATG, and if a living donor transplant is planned, start tacrolimus 2 mg oral twice daily and mycophenolate 720 mg oral twice daily 1 week before transplant. Recipients in the positive DSA group receive an additional 2 or 3 treatments of plasmapheresis in addition to intravenous immunoglobulin, pre‐and posttransplant, depending upon the types of transplant and feasibility. All patients with pretransplant DSA get close DSA monitoring and protocol biopsy at 3 and 12 months posttransplant, as described before.We have published our desensitization protocol previously.2.5DSA were detected pre‐ and posttransplant using Luminex SAB (One Lambda) performed according to the manufacturer's instructions with a reduced volume of beads (3 vs. 5 μl).The strength of dnDSA were represented as the sum of the MFI value of all DSA. Since 2014, routine posttransplant monitoring of DSA was performed on all transplant recipients at 6 and 12 months, and annually thereafter. Patients with a pretransplant cPRA more than 0 were tested at an additional 3‐week time point. In addition, patients with pretransplant DSA were tested at 6 weeks and 3 months posttransplant. Patients with dnDSA underwent transplant biopsy. All patients undergoing renal transplant biopsy for other reasons had DSA testing done as a part of the biopsy visit. The yearly DSA monitoring included patients transplanted before 2014.2.6At our institution, posttransplant quantitative serum BK PCR is monitored every 2 weeks for the first 3 months, monthly from months 3–12, and at the time of a for‐cause kidney allograft biopsy as described before.Throughout the study period, CMV prophylaxis protocols at our center were relatively stable. Valganciclovir for CMV prophylaxis or acyclovir for herpes virus prophylaxis were used based on the induction immunosuppression used and risk for infections as described before.2.7p values less than .1 in univariable analyses were included in multivariable analyses. Pretransplant DSA was included in all multivariable analyses regardless of p value in univariable analyses. Multivariable analyses were carried out using Cox proportional hazards regression models. p values less than .05 were considered to be statistically significant.Differences between DSA groups were assessed with ANOVA for continuous variables and Fisher's exact tests for nominal variables. The methods of Kaplan–Meier were employed to estimate the incidence of ABMR, ACR, graft survival, patient survival, bacterial infection, viral infection, and fungal infection. Log‐rank test was used to compare rates between DSA groups. Variables with 3n = 782; 10.7% (n = 102) had low‐level DSA and 7.1% (n = 68) had positive DSA  patients who underwent kidney transplant from January 2013 to May 2017 at our center. Approximately 195 patients had no available pretransplant DSA testing, so 952 patients were included in our cohort. The majority of patients had no pretransplant DSA  and donors (p < .004) compared with the negative and low‐level DSA groups. Overall, the negative DSA group had the lowest rates of previous sensitization events of blood transfusion, previous transplant or pregnancy compared with both low level and positive DSA groups. The majority of patients in both low‐level and positive DSA groups received antithymocyte globulin for induction therapy at 58.8% (n = 60) and 67.7% (n = 46), respectively (p < .0001).Demographic data and baseline characteristics for recipients, donors, and graft variables are presented in Tables n = 281) compared with both low‐level DSA at 22.5% (n = 23) and positive DSA at 25.0% (n = 17) (p < .022) (Table The negative DSA group had a significantly higher rate of living donors at 35.9% n = 81 compar3.2n = 66) of patients having Class I only DSA, 29.0% (n = 29) with Class II only and 5.0% (n = 5) with both Class I and II DSA. In the positive DSA group, median MFI was 1576 (interquartile range 1211–2239); 52.2% (n = 36) had Class I only, 27.5% (n = 19) Class II only, and 20.3% (n = 14) with both Class I and II DSA.Median MFI in the low‐level DSA group was 500 (interquartile range 339–696) with 66.0% (3.3p = .63). Similarly, in a subgroup analysis, there was no difference in the rate of rejection between low‐level DSA, with 15.4% in DSA MFI 100–500 group compared with 16% (p = .99) in the DSA MFI more than or equal to 500–1000 group. Compared with the DSA negative group, ABMR rates were higher in the low‐level DSA group and highest in the DSA positive group. This is demonstrated by Kaplan–Meier analysis , and was true at all time points at 1‐year posttransplant and later. At 1 year, ABMR was found in 1.7% of patients with negative DSA, 4.9% with low DSA, and 8.3% with positive DSA (p = .033). At the end of the study period, ABMR was found in 4.5% of those with negative DSA, 7.8% with low DSA, and 10.3% with positive DSA (Table p = .034). Compared with the negative DSA group, although not statistically significant, those with low‐level pretransplant DSA also had an increased rate of ABMR, 4.5% versus 7.8% (p = .09). Similarly, in a subgroup analysis, there was no difference in the rate of ABMR between low‐level DSA, with 7.7% ABMR in DSA MFI 100–500 group compared with 8% in the DSA MFI more than or equal to 500–1000 group (p = .96). Also, there was no difference in the rate of ABMR comparing the DSA MFI 100–500 group (7.7%) versus the negative DSA group (4.5%) (p = .19) or DSA MFI more than or equal to 500–1000 group (8%) versus the negative DSA group (4.5%) (p = .21). In the adjusted analysis, the low‐level DSA group had a two‐fold increased risk of developing ABMR compared with the DSA negative group, but this difference did not reach statistical significance (p = .07). Positive DSA patients had a 2.5‐fold increased risk of developing ABMR compared with negative DSA  . Similarly, in a subgroup analysis, there was no difference in the rate of TCMR between low‐level DSA, with 11.5% TCMR in DSA MFI 100–500 group compared with 10% (p = .74) in the DSA MFI more than or equal to 500–1000 group. Also, no significant difference in graft . Similarly, in a subgroup analysis, there was no difference in the rate of graft survival between low‐level DSA, with 94.2% in the DSA MFI 100–500 group compared with 92% in the DSA MFI more than or equal to 500–1000 group (p = .73). Additionally, at 1 and 3 years, there were no significant differences in serum creatinine, eGFR, among DSA groups, except urine protein to creatinine ratio was higher in the DSA positive group. Recipient age at transplant and blood transfusion was not associated with an increased risk of ABMR. Induction therapies alemtuzumab and basiliximab were associated with a 2.7‐ and 2.3‐increased risk of TCMR compared with antithymocyte globulin  compared with 10.8% and 11.4% in the low level and negative DSA groups  (Table p = .006) (Table p = .039) (Table p = .25).The rates of BK viremia were roughly correlated with the strength of pre‐transplant DSA MFI, in that the highest rate was found in the positive DSA group 39.7%), intermediate rate in the low‐level DSA group (30.4%), and lowest in the DSA negative group 25.6%)  Table . The pos%  Table . Additio4sum 100–1000) had an intermediate risk of ABMR (7.8%) compared with rejection rates seen in the negative (4.5%) and positive DSA (MFIsum > 1000) (10.3%) groups. Not surprisingly, patients with positive DSA had the highest rate of ABMR. Similarly, the risk of BK viremia was higher in the low level and positive DSA groups, which is likely the result of more aggressive immunosuppression regimens used in these groups, who are thought to be at increased risk of rejection. This association was independent of other risk factors including age at transplant, donor type, and previous blood transfusion. Despite these findings, no significant difference was found between DSA groups for graft or patient survival, presumably reflecting the successful application of more aggressive induction immunosuppression in patients with higher DSA. Also, in a subgroup analysis, there was no difference in the outcomes between patients with low‐level DSA with MFI 100–500 group compared to DSA MFI more than or equal to 500–1000.Here, we examined kidney allograft outcomes between groups of varying levels of pretransplant DSA. Our results suggest that there is a graded risk of ABMR, such that the higher the pretransplant DSA, the higher the risk of rejection. In our study, patients with low‐level pre‐transplant DSA (MFIsum 100–1000) more closely resembles negative (MFIsum < 100) or positive (MFIsum > 1000) DSA groups, or if the risk is proportional to the strength of DSA. The goal of this study was to determine the relative risk of low‐level pretransplant DSA compared with negative and positive pretransplant DSA.It has previously been established that patients with pretransplant DSA are at increased risk of ABMR, graft failure, and chronic rejection.It is estimated that 30%–40% of potential recipients in the US have pretransplant DSA, which leads to longer wait‐list time and increases the need for desensitization before transplant.max < 1000, 1000–2999, and ≥3000) had higher rates of acute rejection. However, in multivariable analyses, MFImax less than 3000 and negative pretransplant DSA was not associated with significant differences in acute rejection. Regardless of pretransplant DSA status, no difference in 5‐year graft survival was seen. Our findings presented here are not inconsistent with the conclusion presented by Adebiyi et al.,Adebiyi et al.Pneumocystis jirovecii pneumonia, and CMV viremia compared with both CDC and flow crossmatch negative recipients. In another study from our institution among 254 kidney transplant recipients, we found pretransplant DSA with MFI more than 500 was associated with an increased risk for the development of BK or CMV infection in the univariate analysis. However, after the adjustment of multiple confounding factors, this association was lost.Although it has been well‐established that pretransplant DSA is associated with increased risk of rejection and inferior graft survival outcomes, limited data exist on the risk of infections in this population. In one study comparing the outcomes among CDC flow crossmatch positive recipients, who had undergone desensitization before transplant, Kim et al.There are several limitations to address in this study. Although the negative DSA group was not associated with significantly higher incidences of graft failure or patient death compared with other groups at 1 year, these could potentially become significantly different over the long term. This study is also limited by the inherent biases associated with retrospective studies. Also, due to the nature of our study, there was some heterogeneity in the recipient's baseline characteristics as the presence of pretransplant DSA is common among recipients with blood transfusion, previous transplants, or pregnancies among females. And per the institutional protocol, depleting agents were chosen for the induction among these recipients. However, to the best of our knowledge, this is the largest series from a single center comparing both rejection and infection outcomes among kidney transplant recipients with varying levels of DSA. Additionally, our single‐center data reflects a more homogeneous clinical approach to patient selection, surgical technique, and medication management, in contrast to registry data involving multiple centers.In summary, our graft and patient survival outcomes remain quite good regardless of a patient's pre‐transplant DSA status, which is likely the result of our graded approach to induction therapy. While low‐level DSA is not an absolute barrier to transplantation and does not affect graft or patient survival, the increased risk of rejection conferred by low‐level pretransplant DSA should not be ignored. To reduce the risk of rejection, more potent induction immunosuppression may be used in these patients with the caveat that patients may require increased surveillance for infectious complications. Kidney transplant recipients should be aware of these complications before transplant and the alternatives for risk reduction, including paired kidney exchange.The authors of this manuscript have no conflict of interests to disclose as described by the Immunity, Inflmmation and Disease.Sandesh Parajuli: Participated in research design, writing of the article, and performance of the research. Natalie M. Bath: Participated in research design, writing of the article, and performance of the research. Luis Hidalgo: Participated in research design and writing of the article. Glen Leverson: Participated in research design, performance of the research, and data analysis. Neetika Garg: Participated in research design, writing of the article, and performance of the research. Robert R. Redfield III: Participated in research design and writing of the article. Didier Mandelbrot: Participated in research design, writing of the article, and performance of the research.


We expect these findings will help improve work productivity in the New Normal era.The coronavirus disease 2019 (COVID‐19) pandemic has drastically changed work styles and environments. Given the coexistence of work in the office and work from home (WFH) in the future, studies are needed to identify ways to increase productivity when working in both places. We conducted a questionnaire survey and environment measurements of 916 workers in 22 offices across 2 weeks in November–December 2020 in Japan. While average workdays at the offices decreased from 4.9 to 3.9 days/week, those at homes increased from 0.1 to 1.1 days/week due to COVID‐19, indicating an increase in the relative importance of WFH. Compared to the office, the satisfaction rate was lower for lighting, spatial, and information technology (IT) environments, but higher for thermal, air, and sound environments at home. Although it was easier to concentrate on work and to refresh at home, workers experienced challenges associated with business communication from home. Meanwhile, in the office, satisfaction with COVID‐19 countermeasures was significantly associated with work productivity. Furthermore, lower PM At home, the spatial, sound, and information technology (IT) environment were important for work productivity.In the office, in addition to the spatial, sound, and IT environment, satisfaction with COVID‐19 countermeasures was important for work productivity.2.5 concentration was associated with greater satisfaction with COVID‐19 countermeasures.Lower PM2 concentration is considered as an important index of poorly ventilated closed spaces which is one of the risk factors for COVID‐19.At present, CO2.5 may be an important index of workers’ satisfaction with COVID‐19 countermeasures and productivity.PM1Since 2020, the coronavirus disease 2019 (COVID‐19) pandemic has threatened public health worldwide, and caused drastic changes to work styles and work environments. With regard to work style, COVID‐19 has accelerated the recent trend to work from home (WFH). According to the International Labour Organization, only 7.9% of the world's workforce worked from home on a permanent basis prior to the COVID‐19 pandemic.COVID‐19 has also changed the work environment. Many workplaces have introduced countermeasures based on the modes of transmission of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2): physical distancing as a countermeasure for droplet transmission, and cleaning and disinfecting surfaces as a countermeasure for contact transmission. In addition, evidence on airborne transmission is increasing,Furthermore, Japan enforced the “Work Style Reform Law” in April 2019, indicating the urgent need to enhance productivity. Given the drastic changes to work styles and work environments during compared to before the COVID‐19 pandemic, it would be interesting to examine productivity in current work styles and work environments. While many studies have examined the relationship between the work environment in the office and productivity before the COVID‐19 pandemic,We conducted a survey on work style, work environment and productivity in the offices and at home during the COVID‐19 pandemic. The purpose of this study was to investigate the link between different work styles and work environments and productivity during the COVID‐19 pandemic, and to explore ways to improve productivity in the New Normal era.22.1This survey was conducted across 2 weeks in November and December 2020 (during the COVID‐19 pandemic). Figure 2.2Two types of questionnaires were administered, one to building operators and the other to office workers. The questionnaire items are shown in Table 2.32 concentration, and PM2.5 mass concentration were used as office environment factors. Indoor temperature, relative humidity, and CO2 concentration were measured at 5‐min intervals for 2 weeks using a logger  placed on the desk of a representative worker. At the same time, PM2.5 mass concentration was measured at 1‐min intervals using a logger placed next to TR‐76Ui . These loggers were kept away from heat‐generating or aerosol‐generating devices such as printers because printers are a source of PM2.5 in the office. They were also placed away from direct sunlight because it may affect measurements of temperature and data measured using laser light scattering methods. Office environment factors from 9 a.m. to 5 p.m. on weekdays were averaged and used in the analyses to take the regular work hours into consideration. Outdoor temperature and humidity values were obtained from the closest local meteorological observatory, and outdoor PM2.5 from the closest local Atmospheric Environmental Regional Observation System (AEROS) to each building.Indoor temperature and humidity, CO2.4Proportions of related samples were compared using the marginal homogeneity test, an extension of McNemar's test. Multiple linear regression analysis was used to examine the association between satisfaction with the office/home environment and productivity. Model A to E included productivity as a dependent variable and satisfaction with the environment as an independent variable. Models were adjusted for age; gender; work type (engineer or not); sleep condition (AIS score); and physical activity (IPAQ Short).2 concentration and PM2.5 mass concentration). Office worker‐level variables were centered around the mean for each office, while office‐level variables were centered around the overall mean. Regression coefficients were estimated using the maximum likelihood method. All p values were two‐sided, and a two‐sided p value less than 0.05 was considered statistically significant. All analyses were performed using SPSS Ver. 26 .The association between office environment factors and satisfaction with COVID‐19 countermeasures was analyzed using a multilevel linear regression model. The dependent variable was satisfaction  with COVID‐19 countermeasures. A two‐level random intercept model was used in which office worker‐level variables , work style (work days at the office) and lifestyle (AIS score)) were nested within office‐level variables , spatial (room size), and IT environment (Internet connection speed and stability) at home  of the Act on Maintenance of Sanitation in Buildings. Average relative humidity was 36.1%, and 13 out of 21 buildings had levels below 40% (air environment requirement is 40–70%). Average CO2 concentration was 666 ppm, and only 1 building had an average reading above 1000 ppm (air environment requirement is ≤1000 ppm). Average PM2.5 mass concentration was 4.3 µg/m3.Figure 3.3The results of multiple linear regression analyses are shown in Table 3.42 concentrations , PM2.5 mass concentration was significantly correlated with satisfaction with COVID‐19 countermeasures (p = 0.009). For reference, we show the concrete COVID‐19 countermeasures conducted in 20 buildings except for 2 buildings whose information could not be collected or disclosed ; (d) satisfaction with COVID‐19 countermeasures in the office was significantly associated with productivity; and (e) lower PM2.5 mass concentration was significantly correlated with higher satisfaction with COVID‐19 countermeasures (p = 0.009).This study analyzed the association between productivity and work environment in the office and at home during the COVID‐19 pandemic (November–December 2020). Cross‐sectional analyses of 916 workers in 22 buildings showed that (a) compared to their work style before COVID‐19, the average number of workdays in the office decreased from 4.9 to 3.9 days/week, while those at home increased from 0.1 to 1.1 days/week; (b) compared to the office, the satisfaction rate was lower for lighting, spatial, and IT environments, but higher for thermal, air, and sound environments at home; (c) all buildings met the air environment requirements for temperature (17–28℃) and all except one met the air environment requirements for CO4.2In 2019, only 4.8% of workers had engaged in WFH practices, compared to 49.2% as of November/December 2020. Similarly, 25.1% of workers engaged in online meetings in 2019, compared to 77.3% in November/December 2020. Work styles have drastically changed and the relative importance of WFH has increased; both offices and homes are now essential workplaces.Workers showed lower satisfaction with lighting, spatial, and IT environments at home than in the office. Given that the home is classically a place for rest, standard light fixtures and Internet infrastructure may be unsuitable for work. Furthermore, according to an international comparison, the total floor area of houses in Japan is small,2 concentration. In contrast, about 30% of buildings exceeded the recommended CO2 concentration of 1000 ppm before COVID‐19, according to a report on air environment in 2017.2 concentrations as a COVID‐19 countermeasure for airborne transmission. Concurrently, all buildings in the present study met the requirement for indoor temperature, while about 30% of buildings were outside the required range of 17–28℃ in 2017.Regarding office work environments, almost all buildings examined in the present study met the requirements for CO4.32.5 mass concentration was strongly correlated with higher satisfaction with COVID‐19 countermeasures. Although PM2.5 is invisible to the human eye, countermeasures for reducing PM2.5 such as installing medium efficiency air filters and air purifiers may increase satisfaction with COVID‐19 countermeasures and work productivity. One of the possible reasons is that the Society of Heating, Air‐Conditioning and Sanitary Engineers of Japan has conducted awareness‐raising activities on the air filter and the air purifier since the beginning of the pandemic,2 concentration is considered as an important index of poorly ventilated closed spaces which is one of the risk factors for COVID‐19. Similarly, PM2.5 may be an important index in terms of satisfaction with COVID‐19 countermeasures and productivity during the pandemic. Focusing only on the COVID‐19, we guess that the association between PM2.5 and satisfaction with COVID‐19 countermeasures/productivity might weaken when the world turns to be normal. However, given that the pandemic occurred again and again in history, we believe our findings is useful when it comes to the future pandemic.The present results showed that satisfaction with COVID‐19 countermeasures was significantly associated with productivity in the office. This suggests that increasing satisfaction with COVID‐19 countermeasures may increase productivity in the office. Furthermore, the present study also indicated that a lower PM4.4The present study shows that both the type of work and work environment must be considered to ensure sufficient productivity in a workplace. As shown in Figure 4.5This study has several limitations. First, because the majority of workers in this study were engineers, the present results may have some bias. For example, the type of work and work style of engineers differ from those of non‐engineers; thus, the present results may not be applicable to non‐engineers. We also compared the distributions of age and gender in the present survey with those in the Labor Force Survey in Japan.52.5 concentration was associated with greater satisfaction with COVID‐19 countermeasures, indicating that appropriate management of PM2.5 may increase work productivity as a result of improving satisfaction with COVID‐19 countermeasures. We expect these findings will help improve work productivity in the New Normal era.This survey of 916 workers in 22 buildings in Japan showed that the COVID‐19 pandemic has caused substantial changes to work styles , leading to the coexistence of work in the office and WFH (3.9 days/week vs 1.1 days/week). Both at home and in the office, spatial, sound, and IT environments were important for work productivity. However, spatial and IT environments at home and sound environment in the office had room for improvement compared with one another. Furthermore, in the office, satisfaction with COVID‐19 countermeasures, in addition to spatial, sound, and IT environments, was important for work productivity. Besides, lower PMNo conflict of interest has been declared by the authors.Wataru Umishio: Conceptualization‐Equal, Data curation‐Lead, Formal analysis‐Lead, Investigation‐Lead, Methodology‐Lead, Validation‐Lead, Visualization‐Lead, Writing‐original draft‐Lead. Naoki Kagi: Conceptualization‐Equal, Investigation‐Supporting, Methodology‐Supporting, Resources‐Lead, Validation‐Supporting, Writing‐review & editing‐Lead. Ryo Asaoka: Data curation‐Supporting, Formal analysis‐Supporting, Investigation‐Supporting, Validation‐Supporting, Visualization‐Supporting, Writing‐review & editing‐Supporting. Motoya Hayashi: Conceptualization‐Equal, Project administration‐Lead, Supervision‐Lead, Writing‐review & editing‐Supporting. Takao Sawachi: Funding acquisition‐Lead, Project administration‐Supporting, Supervision‐Supporting, Writing‐review & editing‐Supporting. Takahiro Ueno: Funding acquisition‐Supporting, Project administration‐Supporting, Supervision‐Supporting, Validation‐Supporting, Writing‐review & editing‐Supporting.https://publons.com/publon/10.1111/ina.12913.The peer review history for this article is available at Table S1‐S4Click here for additional data file.