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The global elite has gathered for a Christmas summit, and the King's final revenge on the world that rejected him is almost at hand! All Tsubasa can do is grab the bomb and run -- but how far will she get before time runs out? And will Arisa and Tsubasa be able to forget the betrayals and go back to being loving sisters again?

Low birth weight (LBW, < 2500 g) infants are at significant risk for death and disability. Improving outcomes for LBW infants requires access to advanced neonatal care, which is a limited resource in low- and middle-income countries (LMICs). Predictive modeling might be useful in LMICs to identify mothers at high-risk of delivering a LBW infant to facilitate referral to centers capable of treating these infants. We developed predictive models for LBW using the NICHD Global Network for Women's and Children's Health Research Maternal and Newborn Health Registry. This registry enrolled pregnant women from research sites in the Democratic Republic of the Congo, Zambia, Kenya, Guatemala, India (2 sites: Belagavi, Nagpur), Pakistan, and Bangladesh between January 2017 - December 2020. We tested five predictive models: decision tree, random forest, logistic regression, K-nearest neighbor and support vector machine. We report a rate of LBW of 13.8% among the eight Global Network sites from 2017-2020, with a range of 3.8% (Kenya) and approximately 20% (in each Asian site). Of the five models tested, the logistic regression model performed best with an area under the curve of 0.72, an accuracy of 61% and a recall of 72%. All of the top performing models identified clinical site, maternal weight, hypertensive disorders, severe antepartum hemorrhage and antenatal care as key variables in predicting LBW. Predictive modeling can identify women at high risk for delivering a LBW infant with good sensitivity using clinical variables available prior to delivery in LMICs. Such modeling is the first step in the development of a clinical decision support tool to assist providers in decision-making regarding referral of these women prior to delivery. Consistent referral of women at high-risk for delivering a LBW infant could have extensive public health consequences in LMICs by directing limited resources for advanced neonatal care to the infants at highest risk.

Abstract Context Lacunar strokes and diabetes are risk factors for cognitive dysfunction. Elucidating modifiable risk factors for cognitive dysfunction has great public health implications. One factor may be glycemic status, as measured by glycated hemoglobin (A1c). Objective The aim of this study was to assess the relationship between A1c and cognitive function in lacunar stroke patients with diabetes. Methods The effect of baseline and follow-up A1c on the baseline and the change in Cognitive Assessment Screening Instrument (CASI) score over time among participants with a median of 2 cognitive assessments (range, 1-5) was examined in 942 individuals with diabetes and a lacunar stroke who participated in the Secondary Prevention of Small Subcortical Strokes (SPS3) trial (ClinicalTrials.gov No. NCT00059306). Results Every 1% higher baseline A1c was associated with a 0.06 lower standardized CASI z score (95% CI, –0.101 to –0.018). Higher baseline A1c values were associated with lower CASI z scores over time (P for interaction = .037). A 1% increase in A1c over time corresponded with a CASI score decrease of 0.021 (95% CI, –0.0043 to –0.038) during follow-up. All these remained statistically significant after adjustment for age, sex, education, race, depression, hypertension, hyperlipidemia, body mass index, cardiovascular disease, obstructive sleep apnea, diabetic retinopathy, nephropathy insulin use, and white-matter abnormalities. Conclusion This analysis of lacunar stroke patients with diabetes demonstrates a relationship between A1c and change in cognitive scores over time. Intervention studies are needed to delineate whether better glucose control could slow the rate of cognitive decline in this high-risk population.

Maternal mortality is a public health problem that disproportionately affects low and lower-middle income countries (LMICs). Appropriate data sources are lacking to effectively track maternal mortality and monitor changes in this health indicator over time. We analyzed data from women enrolled in the NICHD Global Network for Women's and Children's Health Research Maternal Newborn Health Registry (MNHR) from 2010 through 2018. Women delivering within research sites in the Democratic Republic of Congo, Guatemala, India (Nagpur and Belagavi), Kenya, Pakistan, and Zambia are included. We evaluated maternal and delivery characteristics using log-binomial models and multivariable models to obtain relative risk estimates for mortality. We used running averages to track maternal mortality ratio (MMR, maternal deaths per 100,000 live births) over time. We evaluated 571,321 pregnancies and 842 maternal deaths. We observed an MMR of 157 / 100,000 live births (95% CI 147, 167) across all sites, with a range of MMRs from 97 (76, 118) in the Guatemala site to 327 (293, 361) in the Pakistan site. When adjusted for maternal risk factors, risks of maternal mortality were higher with maternal age > 35 (RR 1.43 (1.06, 1.92)), no maternal education (RR 3.40 (2.08, 5.55)), lower education (RR 2.46 (1.54, 3.94)), nulliparity (RR 1.24 (1.01, 1.52)) and parity > 2 (RR 1.48 (1.15, 1.89)). Increased risk of maternal mortality was also associated with occurrence of obstructed labor (RR 1.58 (1.14, 2.19)), severe antepartum hemorrhage (RR 2.59 (1.83, 3.66)) and hypertensive disorders (RR 6.87 (5.05, 9.34)). Before and after adjusting for other characteristics, physician attendance at delivery, delivery in hospital and Caesarean delivery were associated with increased risk. We observed variable changes over time in the MMR within sites. The MNHR is a useful tool for tracking MMRs in these LMICs. We identified maternal and delivery characteristics associated with increased risk of death, some might be confounded by indication. Despite declines in MMR in some sites, all sites had an MMR higher than the Sustainable Development Goals target of below 70 per 100,000 live births by 2030. The MNHR is registered at NCT01073475 .

Due to high fertility rates in some low and lower-middle income countries, the interval between pregnancies can be short, which may lead to adverse maternal and neonatal outcomes. We analyzed data from women enrolled in the NICHD Global Network Maternal Newborn Health Registry (MNHR) from 2013 through 2018. We report maternal characteristics and outcomes in relationship to the inter-delivery interval (IDI, time from previous delivery [live or stillborn] to the delivery of the index birth), by category of 6-17 months (short), 18-36 months (reference), 37-60 months, and 61-180 months (long). We used non-parametric tests for maternal characteristics, and multivariable logistic regression models for outcomes, controlling for differences in baseline characteristics. We evaluated 181,782 women from sites in the Democratic Republic of Congo, Zambia, Kenya, Guatemala, India, and Pakistan. Women with short IDI varied by site, from 3% in the Zambia site to 20% in the Pakistan site. Relative to a 18-36 month IDI, women with short IDI had increased risk of neonatal death (RR = 1.89 [1.74, 2.05]), stillbirth (RR = 1.70 [1.56, 1.86]), low birth weight (RR = 1.38 [1.32, 1.44]), and very low birth weight (RR = 2.35 [2.10, 2.62]). Relative to a 18-36 month IDI, women with IDI of 37-60 months had an increased risk of maternal death (RR 1.40 [1.05, 1.88]), stillbirth (RR 1.14 [1.08, 1.22]), and very low birth weight (RR 1.10 [1.01, 1.21]). Relative to a 18-36 month IDI, women with long IDI had increased risk of maternal death (RR 1.54 [1.10, 2.16]), neonatal death (RR = 1.25 [1.14, 1.38]), stillbirth (RR = 1.50 [1.38, 1.62]), low birth weight (RR = 1.22 [1.17, 1.27]), and very low birth weight (RR = 1.47 [1.32,1.64]). Short and long IDIs were also associated with increased risk of obstructed labor, hemorrhage, hypertensive disorders, fetal malposition, infection, hospitalization, preterm delivery, and neonatal hospitalization. IDI varies by site. When compared to 18-36 month IDI, women with both short IDI and long IDI had increased risk of adverse maternal and neonatal outcomes. The MNHR is registered at NCT01073475 .

Low dose aspirin (LDA) is an effective strategy to reduce preterm birth. However, LDA might have differential effects globally, based on the etiology of preterm birth. In some regions, malaria in pregnancy could be an important modifier of LDA on birth outcomes and anemia. This is a sub-study of the ASPIRIN trial, a multi-national, randomized, placebo controlled trial evaluating LDA effect on preterm birth. We enrolled a convenience sample of women in the ASPIRIN trial from the Democratic Republic of Congo (DRC), Kenya and Zambia. We used quantitative polymerase chain reaction to detect malaria. We calculated crude prevalence proportion ratios (PRs) for LDA by malaria for outcomes, and regression modelling to evaluate effect measure modification. We evaluated hemoglobin in late pregnancy based on malaria infection in early pregnancy. One thousand four hundred forty-six women were analyzed, with a malaria prevalence of 63% in the DRC site, 38% in the Kenya site, and 6% in the Zambia site. Preterm birth occurred in 83 (LDA) and 90 (placebo) women, (PR 0.92, 95% CI 0.70, 1.22), without interaction between LDA and malaria (p = 0.75). Perinatal mortality occurred in 41 (LDA) and 43 (placebo) pregnancies, (PR 0.95, 95% CI 0.63, 1.44), with an interaction between malaria and LDA (p = 0.014). Hemoglobin was similar by malaria and LDA status. Malaria in early pregnancy did not modify the effects of LDA on preterm birth, but modified the effect of LDA on perinatal mortality. This effect measure modification deserves continued study as LDA is used in malaria endemic regions.

Participant engagement influences treatment effectiveness, but it is unknown which intervention design features increase treatment engagement for online smoking cessation programs. We explored the effects of 4 design features (ie, factors) on early engagement with an Internet-based, motivational smoking cessation program. Smokers (N=1865) were recruited from a large health care organization to participate in an online intervention study, regardless of their interest in quitting smoking. The program was intended to answer smokers' questions about quitting in an effort to motivate and support cessation. Consistent with the screening phase in the multiphase optimization strategy (MOST), we used a 2-level, full-factorial design. Each person was randomized to 1 of 2 levels of each factor, including message tone (prescriptive vs motivational), navigation autonomy (dictated vs not), proactive email reminders (yes vs no), and inclusion of personally tailored testimonials (yes vs no). The effects of each factor level on program engagement during the first 2 months of enrollment were compared, including number of visits to the website resulting in intervention content views (as opposed to supplemental content views), number of intervention content areas viewed, number of intervention content pages viewed, and duration of time spent viewing this content, as applicable to each factor. Adjusting for baseline readiness to quit, persons who received content written in a prescriptive tone made the same number of visits to the website as persons receiving content in a motivational tone, but viewed 1.17 times as many content areas (95% CI 1.08-1.28; P<.001) and 1.15 times as many pages (95% CI 1.04-1.28; P=.009). Time spent viewing materials did not differ among groups (P=.06). Persons required to view content in a dictated order based on their initial readiness to quit made the same number of visits as people able to freely navigate the site, but viewed fewer content areas (ratio of means 0.80, 95% CI 0.74-0.87; P<.001), 1.17 times as many pages (95% CI 1.06-1.31; P=.003), and spent 1.37 times more minutes online (95% CI 1.17-1.59; P<.001). Persons receiving proactive email reminders made 1.20 times as many visits (95% CI 1.09-1.33; P<.001), viewed a similar number of content areas as persons receiving no reminders, viewed 1.58 times as many pages (95% CI 1.48-1.68; P<.001), and spent 1.51 times as many minutes online (95% CI 1.29-1.77; P<.001) as those who did not receive proactive emails. Tailored testimonials did not significantly affect engagement. Using a prescriptive message tone, dictating content viewing order, and sending reminder emails each resulted in greater program engagement relative to the contrasting level of each experimental factor. The results require replication, but suggest that a more directive interaction style may be preferable for online cessation programs. clinicaltrials.gov NCT00992264; http://clinicaltrials.gov/ct2/show/NCT00992264 (Archived by WebCite at http://www.webcitation.org/6F7H7lr3P).

Research needs to systematically identify which components increase online intervention effectiveness (i.e., active ingredients). This study explores the effects of 4 potentially important design features in an Internet-based, population-level smoking intervention. Smokers (n = 1,865) were recruited from a large health care organization, regardless of readiness to quit. Using a full factorial design, participants were randomized to 1 of the 2 levels of each experimental factor (message tone [prescriptive vs. motivational], navigation autonomy [dictated vs. not], e-mail reminders [yes vs. no], and receipt of personally tailored testimonials [yes vs. no]) and provided access to the online intervention. Primary outcomes were self-reported 7-day point-prevalent smoking abstinence and confirmed utilization of adjunct treatment (pharmacotherapy or phone counseling) available through the health plan at 1 year. Outcomes were also assessed at 2 and 6 months and were examined among all enrolled participants (intent-to-treat [ITT]) and all who viewed the intervention (modified ITT). At 1 year, 13.7% were abstinent and 26.0% utilized adjunct treatment. None of the contrasting factor levels differentially influenced abstinence or treatment utilization at 12 months. In the modified ITT sample, smokers receiving testimonials were less likely to use adjunct treatment at 6 months (odds ratio = 0.54, 95% confidence interval = 0.30-0.98, p = .04). None of the design features enhanced treatment outcome. The negative effect observed for testimonials is provocative, but it should be viewed with caution. This study offers a model for future research testing the \"active ingredients\" of online interventions.

The rhizosphere constitutes a dynamic interface between plant hosts and their associated microbial communities. Despite the acknowledged potential for enhancing plant fitness by manipulating the rhizosphere, the engineering of the rhizosphere microbiome through inoculation has posed significant challenges. These challenges are thought to arise from the competitive microbial ecosystem where introduced microbes must survive, and the absence of adaptation to the specific metabolic and environmental demands of the rhizosphere. Here, we engineered a synthetic rhizosphere community (SRC1) with the anticipation that it would exhibit a selective advantage in colonizing the host Sorghum bicolor, thereby potentially fostering its growth. SRC1 was assembled from bacterial isolates identified either for their potential role in community cohesion through network analysis or for their ability to benefit from host-specific exudate compounds. The growth performance of SRC1 was assessed in vitro on solid media, in planta under gnotobiotic laboratory conditions, and in the field. Our findings reveal that SRC1 cohesion is most robust when cultivated in the presence of the plant host under laboratory conditions, with lineages being lost from the community when grown either in vitro or in a native field setting. We establish that SRC1 effectively promotes the growth of both above- and below-ground plant phenotypes in both laboratory and native field contexts. Furthermore, in laboratory conditions, these growth enhancements correlate with the transcriptional dampening of lignin biosynthesis in the host. Collectively, these results underscore the potential utility of synthetic microbial communities for modulating crop performance in controlled and native environments alike.

There is increasing evidence that response to pharmacological treatment for nicotine dependence may be moderated by genetic polymorphisms. However, the feasibility, acceptability, and impact of genetically tailoring treatment in real-world clinical settings are unknown. We conducted a multiphased, mixed-methods feasibility study with current smokers to develop and evaluate a patient-centered, theoretically grounded personalized medicine treatment protocol. The initial research phase included formative work to develop intervention materials. The second phase included a randomized pilot trial to evaluate the intervention. Trial participants (n = 36) were genotyped for ANKK1 rs1800497 and were randomized to receive genetic feedback (GF) plus standard behavioral counseling (BC) for smoking cessation or BC without GF. All participants received genetically tailored pharmacotherapy (nicotine patch or bupropion). The intervention was feasible to implement and was acceptable to participants based on satisfaction ratings and objective measures of participation. There was no evidence that the GF resulted in adverse psychological outcomes (e.g., depression, fatalism, reduced perceived control over quitting, differential motivation for quitting) based on quantitative or qualitative outcomes. Study results suggest that it is feasible to offer treatment within a health care setting that includes genetically tailored pharmacotherapy and doing so had no apparent adverse psychological impacts. Further evaluation of pharmacogenetically tailored smoking cessation interventions appears warranted.