Intensive lifestyle interventions (ILI) improve weight loss and cardiovascular risk factors, but health systems face challenges implementing them. We engaged stakeholders to cocreate and evaluate feasibility of primary care implementation strategies and of a pragmatic randomization procedure to be used for a future effectiveness trial.The study setting was a single, urban primary care office. Patients with BMI ≥ 27 and ≥ 1 cardiovascular risk factor were sent a single electronic health record (EHR) message between December 2019 and January 2020 offering services to support an initial weight loss goal of about 10 pounds in 10 weeks. All patients who affirmed weight loss interest were pragmatically enrolled in the trial and offered “Basic Lifestyle Services” (BLS), including a scale that transmits weight data to the EHR using cellular networks, a coupon to enroll in lifestyle coaching resources through a partnering fitness organization, and periodic EHR messages encouraging use of these resources. About half (n = 42) of participants were randomized by an automated EHR algorithm to also receive “Customized Lifestyle Services” (CLS), including weekly email messages adapted to individual weight loss progress and telephonic coaching by a nurse for those facing challenges. Interventions and assessments spanned January to July 2020, with interference by the coronavirus pandemic. Weight measures were collected from administrative sources. Qualitative analysis of stakeholder recommendations and patient interviews assessed acceptability, appropriateness, and sustainability of intervention components.Over 6 weeks, 426 patients were sent the EHR invitation message and 80 (18.8%) affirmed interest in the weight loss goal and were included for analysis. EHR data were available to ascertain a 6-month weight value for 77 (96%) patients. Overall, 62% of participants lost weight; 15.0% exhibited weight loss ≥ 5%, with no statistically significant difference between CLS or BLS arms (p = 0.85). CLS assignment increased participation in daily self-weighing (43% versus 21% of patients through 12 weeks) and enrollment in referral-based lifestyle support resources (52% versus 37%).This preliminary study demonstrates feasibility of implementation strategies for primary care offices to offer and coordinate ILI core components, as well as a pragmatic randomization procedure for use in a future randomized comparative trial. Health systems also have incentives to intervene before cardiovascular risk factors cause symptoms, functional impairments, or costly health complications.9 However, health systems face challenges implementing ILI,12 which require dedicated personnel, space, supplies, and technologies that generally do not “fit” within the existing structure and routines of healthcare delivery.U.S. health systems are a natural partner for ILI implementation because 5 in 6 adults complete office visits each year,17 These strategies have slightly lower effectiveness than more intensive interventions studied in randomized controlled trials (RCTs),18 but also cost less and reach more people.20 Despite increasing numbers of ILI programs nationally, clinicians refer very few patients to ILI, and most people who may benefit remain unaware.19 There is an immense need for research that identifies feasible and acceptable strategies for health systems to implement ILI.Past research has investigated strategies to simplify the role of health systems in ILI delivery. Examples include reducing the frequency or duration of behavioral coaching contacts or shifting the source of coaching to outside healthcare settings, such as via wellness professionals employed by community organizations or virtual coaching delivered using a computer or smartphone.22 Such an approach may expand reach to patients who are initially unable or unwilling to enroll when referred to a full-scale program offered in a single format or location. Core components of ILI include support for: an initial weight loss goal of at least 5 to 10 kg (11 to 22 pounds) at a pace of about 0.5 to 2 pounds per week;1 resources and training for individuals to self-monitor dietary, activity, and weight changes;23 and longitudinal coaching . Coaching serves to create accountability,24 develop self-regulation and problem-solving skills,26 suggest refinements to behavioral strategies, and build self-efficacy and mastery over behaviors;23 coaching can be effective when offered face-to-face or via a technology platform, with individual participants or groups.1One approach used to improve implementation of multi-component behavioral interventions is to distill them to their core components, and devise simpler implementation strategies for each component that both fit within health system constraints and offer a broader array of ways for patients to engage.Over the past 3 years, we engaged with health system and fitness industry leaders, managers, and service professionals to co-create and evaluate the feasibility of an array of practical implementation strategies for health systems to support ILI core components. To our knowledge this is the first such effort in which all intervention components are imbedded within or coordinated directly by an Electronic Health Record management system. We report on the collaborative approach used for creation of the ILI implementation strategies, as well as preliminary data for feasibility and acceptability of this approach.Our research involves both stakeholder-engaged “co-creation”  of implementation strategies using collaborative design principles and a small pilot trial to demonstrate feasibility and acceptability of the strategies in a single general internal medicine practice setting in downtown Chicago, Illinois. The trial involved pragmatic recruitment, enrollment, and data collection strategies. Eligible patients were enrolled from December 2019 – January 2020; data were collected through January 2021. The experimental services were offered to patients beginning January 2020, and access to some services (details below) were interrupted by the coronavirus pandemic stay-at-home order in March 2020.23 and co-create implementation strategies for sustainable delivery of each core component in busy primary care practice settings. Recurring meetings of a “design team” included behavioral and social scientists, health system nursing supervisors, a practicing primary care physician, two wellness program leaders from the partnering fitness club network, and health system employees who develop and manage new tools and applications within the electronic health record (EHR) system. Individual meetings were held with additional stakeholders, including health system leaders, medical group and practice leaders, and the CEO and wellness program leaders from a regional fitness club network. Research staff members organized meetings, kept detailed notes, verified recommendations and action steps with participants, and integrated ideas into an array of design themes and concepts that informed intervention prototypes, pretests, and refinements.11From September 2016 to December 2019, we engaged stakeholders to consider research evidence for ILI core componentsA clinical data manager utilized EHR reporting tools to generate lists of eligible patients. Inclusion criteria were: age 18–75 years; ≥1 log-in within the past 6 months to MyChart ; completion of ≥ 1 office visit in the past 6 months at the participating primary care practice site; measured weight and height at the most recent office visit indicating body mass index (BMI) ≥ 27.0 kg/m2; and ≥ 1 cardiometabolic risk factor . Patients were ineligible if their last blood pressure was ≥ 180/105 mmHg or last hemoglobin A1c was ≥ 10.9%. Patients were also ineligible if they received cancer treatment in the past 2 years, were hospitalized in the past 3 months, were pregnant, or had personal history of an eating disorder or serious mental illness.The data manager used EHR messaging tools to send each physician a list of their own eligible patients, asking them to reply within 1 week if they wished to remove patients whom they believed offering support for lifestyle change may be inappropriate. After 1 week, the data manager used the EHR’s batch patient messaging tool to transmit a standardized outreach “goal setting” message to each patient remaining on the list. The message encouraged healthy eating and physical activity changes with a weight loss goal, and it offered free-of-charge access to technologies and coaching support to help recipients achieve the goal. The message also prompted patients to click an embedded link if they wished to adopt a weight loss goal and receive support. Because limited resources were available to support intervention costs during feasibility testing, we limited recruitment by releasing MyChart messages to 100–200 patients every 2 weeks until a target sample size of 80 patients had affirmed interest in receiving the intervention services. All 80 patients were included in the pragmatic trial evaluation; all received a bundle of Basic Lifestyle Support (BLS) services (below), and about half (N = 42) of patients were randomly assigned by a “silent” EHR algorithm to also receive additional, more Customized Lifestyle Support (CLS) services (below).2 and perceived by stakeholders as technically feasible, acceptable, and financial sustainable.27 This approach followed collaborative design principles,11 and produced ILI implementation strategies for support of weight loss goal setting, self-weighing, and recurring coaching support. Stakeholders advised using the EHR to identify eligible patients, to message them to encourage weight loss goal setting, inspire accountability, and increase engagement in support services, as well as to track and monitor progress as means to offer alternative, higher intensity services to patients facing challenges with automated support alone . Stakeholders cautioned that encouragement of a weight loss goal in a MyChart message could be perceived as inappropriate by some patients; they advised framing the goal and offering resources as means to improve cardiovascular risk factor control. They also advised recommending a relatively simple initial goal of “about 10 pounds over 10 weeks,” believing this would be acceptable, appropriate, and achievable for most patients. Stakeholders advised exploring the feasibility of receiving data from a wireless scale and analyzing that data directly within the EHR as means to inform more personalized feedback about self-weighing, as well as to increase accountability and to identify and target patients needing alternative forms of intervention support. They advised providing all patients with free-of-charge access to coaching services offered by a partnering fitness organization and assigning a practice nurse to provide telephonic coaching to patients who do not make progress towards their weight goal. They emphasized that we evaluate the quality of all new resources, if patients perceive them as appropriate, and if their costs are sustainable.Design goals were to co-create ILI implementation strategies that are evidence-based,Additional File 1) were all deployed or coordinated by the EHR. Interventions commenced when a patient received the introductory MyChart goal-setting message (above) and clicked the link to affirm interest in a weight loss goal. All 80 patients received a bundle of Basic Lifestyle Support (BLS) services. Specifically, they were shipped a wireless weight scale , which had been programmed to transmit weight data back to their electronic chart using cellular networks. Each patient received a follow-up MyChart message, with simple instructions for using the scale to weigh themselves daily, as well as a “coupon code” to enroll free-of-charge in longitudinal lifestyle coaching and support resources offered by a regional fitness organization partner. Patients could choose to access the referral services in 2 formats: face-to-face access to a dietician and fitness coach at 11 facility locations or fully “virtual” access to the same professionals via video chat with a smartphone, tablet, or personal computer. The face-to-face option provided full health club facility access, and the virtual option provided a suite of healthy food preparation and physical activity tips, tracking tools, and videos. Each patient also received instructions for messaging a dedicated nurse-coach at the primary care practice if they had problems using the support services or if they wanted more personalized support for reaching dietary, physical activity, or weight loss goals.The resulting intervention components  of patients who had been randomized to receive “Customized Lifestyle Support” (CLS) services. Specifically, for the first 12 weeks, each patient in the CLS arm was sent an automated weekly MyChart message with coaching tips customized to their use of the eScale in the prior week, whether they had made weight loss progress (defined as ≥ 0.5 pounds of weight loss from the first to last weight measure during the prior week), and whether they had enrolled in referral-based services offered by the fitness partner. A practice nurse used an EHR dashboard to monitor the entire CLS group and attempted to call patients to offer customized “step-up” telephone coaching if either: (1) they had not used their scale in the prior week; or (2) for 2 consecutive weeks they had not achieved ≥ 0.5 pounds of weight loss.28We collected quantitative data from administrative sources and qualitative information from interviews with randomly selected subsets of representative patients. Beginning approximately 12 weeks after launch of the trial, we conducted semi-structured telephone interviews with 15 representative patients to assess perceptions of the appropriateness, ease of access, ease of use, acceptability, desirability, credibility, and usefulness of the intervention components in helping them achieve health related goals.Several electronic sources provided data for patient characteristics and outcomes. EHR data spanning +/− 15 months of the launch of the trial provided information on the baseline characteristics, service utilization patterns, and metabolic and biometric outcomes. The partnering fitness network provided data about patient participation in the two coaching support options and facility use. Analysis of body weight changes utilized data from the EHR and electronic scales . The last EHR weight measure prior to each patient’s randomization date served as the baseline body weight, and the EHR weight measure closest to the date of randomization plus 6 ± 3 months served as the follow-up weight. For patients who did not have such a follow up EHR weight value, we estimated the 6-month value as one-half the difference between the baseline value and the EHR weight value closest to 12 ± 3 months. For participants missing both a 6- and 12-month weight value in the EHR, we used the eScale weight value closest to 6 ± 3 months. Finally, if individuals were missing all those weight values, we assumed that the participant failed to reach 5% weight loss.Multiple data sources were used to describe intervention activities and activity-related costs. Input from health system leaders and study team members identified the specific personnel, supplies, contract services, and facility and administrative inputs needed to implement each intervention component. Administrative data systems captured the number and type of contacts made between nurses and study participants. Staff members were interviewed to estimate the amount of time they spent supporting different intervention activities over 6 and 12 months. Costs of eScales, community intervention program fees, and development costs for health IT components were determined from invoice amounts. Maintenance costs for IT support was estimated from interviews of IT staff members, who were asked to estimate hours per week spent supporting the intervention components.We examined univariate and bivariate descriptive statistics and conducted chi-square tests to compare all patients randomized to CLS and BLS arms on the proportion that reached the dichotomous primary outcome of ≥ 5% weight loss at 6 months. Transcripts of interviews with patients were analyzed to summarize perspectives raised about acceptability, appropriateness, and feasibility of ILI implementation strategies. Example themes and representative quotes were selected by group deliberation and consensus.The eligibility list for the feasibility trial included 2,146 patients. Over 6 weeks, the clinical data manager sent names of 442 patients to 34 primary care clinicians for pre-review; clinicians asked that only 16 (3.6%) of these patients not be contacted. A single outreach Mychart message was sent to each of the remaining 426 patients, of whom 315 (73.9%) opened the message within 4 weeks, and 80 (18.8%) affirmed interest in the weight loss goal .Demographic characteristics of the 80 participants  approximated the characteristics of the overall target population, with slight over-representation of women and those identifying as Hispanic/Latinx, non-Hispanic Black, or non-Hispanic Asian . In the All but 3 (3.8%) patients were able to initialize their eScale and register a baseline weight. Over the 12-week MyChart messaging phase of the intervention, 11 (14%) of participants did not use their scales for self-weighing, 7 (9%) participated in weighing in some but not all weeks, and 62 (78%) engaged in self-weighing during all 12 weeks. Self-weighing daily (5 to 7 days per week) was performed by 26 (33%) of patients during all 12 weeks; more patients assigned to CLS (customized weekly messaging) performed daily self-weighing in all weeks (43% versus 21% of those offered BLS).Overall, 36 (45%) patients (37% of the BLS arm and 52% of the CLS arm) enrolled in one of the two referral-based coaching platforms offered by the fitness industry partner; 22 (27.5%) elected the face-to-face option and 14 (17.5%) elected fully virtual access. Patients enrolled in these services between 15 and 77 days after receiving the initial outreach MyChart message. Access to fitness facilities  was disrupted by a coronavirus pandemic stay-at-home order beginning the third week of March 2020. At that time, patients had been enrolled in the referral-based services for 19 to 75 days; the 22 patients in face-to-face support had completed an average of 3 (range 1 to 6) individual coaching sessions and attended a partnering fitness facility 0 to 24 times; the 14 patients receiving “virtual” support had completed an average of 4 (range 2 to 5) individual coaching sessions prior to the pandemic but were able to complete an average of 3 additional (range 0 to 5) coaching sessions after the pandemic began.Among patients randomized to CLS, 41 (98%) received at least one step-up telephonic nurse coaching call; 19 (45%) received ≥ 5 nurse calls  over the 12-week intensive support phase.Despite lower than usual office visit rates during the early phase of the coronavirus pandemic, 44 (55%) of feasibility trial patients had an office weight measure recorded in the EHR at 6 ± 3 months from their trial enrollment. Among the remaining 36 patients, 26 (72%) had a weight recorded at 12 ± 3 months, and of the remaining 10 patients, 7 (70%) had an eScale weight received at 6 ± 3 months. Thus, our pragmatic data capture strategy enabled estimation of a 6-month weight change for 77 (96%) of all trial participants. The average time between trial enrollment and the weight used for 6-month data analysis was 184.5 days. Overall, 62% of participants had lower weight at follow up than at baseline; 15.0% exhibited a weight loss of ≥ 5% of baseline weight, with no statistically significant difference between CLS or BLS arms (p = 0.85).Using eScale data and assuming that the 14% of patients who did not self-weigh also did not lose weight, 28 (35%) of all participants achieved ≥ 10 lbs of weight loss  and 24 (30%) achieved ≥ 5% of weight loss at some point during the 12-week automated messaging phase. Thus, half of patients who achieved a 5% weight loss during the 12 weeks of active support maintained the loss at 6 months.Additional File Table 3. Mean health system costs to offer the intervention as delivered during the feasibility trial were estimated at $335 per person over the first 6 months  and $150 per person over the second 6 months .Direct medical costs associated with offering each intervention component are summarized in Additional File Table 2.Among the 80 feasibility trial participants, 30 were randomly selected and approached before 15 agreed to complete the telephone interview; 11 were unreachable, 5 declined participation, 2 asked to be re-contacted at a future time. Respondents included 5 men and 10 women, with demographic and clinical characteristics generally representative of the overall target population . PatientTrust in the person or organization providing lifestyle support services emerged as an important theme. Importantly, some patients expressed being distrustful when offered resources for “free” from a commercial partner, unless it was clear that their doctor or the health system were recommending and coordinating the activities. Others indicated that they had not initially realized they could access dietary and physical activity coaching at the partnering fitness organization and were unsure how to engage with the practice nurse if they had problems.Most patients described the Mychart messages and website resources as generally easy to understand and navigate. However, some reported feeling frustrated or less engaged by not having a clear understanding upfront for how the different intervention components were coordinated or should be utilized. . weight loss goal was motivated by other health or social goals, such as reducing the need for more pills to treat high blood pressure.Nearly all patients reported that an initial weight loss goal of about 10 pounds in 10 weeks was appropriate and achievable. Some expressed interest in larger weight loss goals and access to services beyond 10 to 12 weeks. Many patients reported that their critical importance of supportive accountability in successfully changing behavior. They emphasized the practice nurse, registered dietitian, and physical trainers as key sources of supportive accountability, more so than the automated messages. Patients expressed strengths and limitations of the automated messages, highlighting that the messages were a helpful reminder or source of encouragement when making progress but were insufficient or even demoralizing when not making progress.Several patients highlighted the frustration when they viewed eScales (and self-weighing) as a direct source of support, rather than as a means for healthcare providers and coaches to track and customize their support. Importantly, some viewed daily weighing as a source of stress and felt that no matter how closely they followed diet and physical activity plans, their daily weight remained unpredictable. Several patients highlighted failure expectations stemming from negative experiences with prior weight loss attempts. Those patients recommended a greater focus on recognizing and addressing failure expectations, as well as de-emphasizing a focus on the daily weight readings as a sign of success or failure, while offering more immediate support beyond automated messaging. Relatedly, some patients highlighted how emotions have a larger influence on dietary behaviors than reminders to eat healthy. Those patients recommended greater focus on acknowledging and addressing emotions both as drivers and consequences of attempts to lose weight and change diet.Many patients viewed self-weighing as an additional source of accountability. Some expressed interest in more elaborate electronic scales or integration with other technologies, such as smartphone apps that provide immediate and customized support. Other patients indicated that they preferred support coming from a member of the healthcare or fitness center team. Generally, patients expressed the coronavirus pandemic presented a profound barrier to healthy behaviors and weight loss. Many indicated frustration with becoming more sedentary, adopting ‘stress eating’ behaviors, and gaining weight. The pandemic restrictions eliminated access to fitness facilities, which added to frustration.Finally, all patients indicated that the abrupt start of gain was common.32This preliminary work demonstrates the feasibility of several pragmatic implementation strategies for primary care offices to support the core components of intensive lifestyle interventions. After a single outbound MyChart message was sent to encourage a weight loss goal by overweight or obese adults with cardiovascular risk factors, 3 in 4 recipients opened the message, and 25% of those who opened it affirmed interest in receiving support services lose weight. Among those patients, 30% achieved ≥ 5% weight loss in the first 12 weeks and, despite the disruptive impacts of a pandemic, about 15% still exhibited ≥ 5% weight loss at 6 months, at a time when weight Weekly “nudging” of patients with a customized MyChart message plus step-up telephone coaching by a practice nurse increased participation in daily self-weighing (43% versus 21% of patients through 12 weeks) and enrollment in referral-based lifestyle support resources offered by a partnering fitness organization (52% versus 37%). Though this small feasibility trial did not demonstrate whether patients are more likely to reach weight loss goals when provided these more customized services, this approach warrants further study.17 but we are unaware of other examples where the intervention components have been fully embedded within an EHR system. Our approach employed design thinking with service professionals, health system leaders, health payers, and researchers to create practice components that not only are evidence-based but also desirable to implementers, technically feasible, and financially sustainable.11 Design prototypes were iteratively pre-tested and refined with stakeholder collaboration, and a small feasibility trial demonstrated strong promise for both effectiveness and sustainability.Our work is consistent with other recent studies of pragmatic, technology-facilitated lifestyle interventions in primary care settings,36 However, most past research focused on referrals to a comprehensive program bundle, such as the National Diabetes Prevention Program (NDPP), often offered in a single format or location.37 Offering a multi-component program like NDPP requires considerable community organizational capacity and financial investment, which imposes implementation barriers,39 particularly when enrollment is low or third party payment is limited. Another unique aspect of our approach was to distill ILI programs down to core components and to develop implementation strategies for each component to minimize demands placed on the implementing organization.22 We also considered how to offer the resulting services using an array of different channels  to maximize reach by appealing to different segments of the target population.Our work also builds on past research evaluating referral linkages between health systems and community-delivered intensive lifestyle interventions.41 It will be important for future research to evaluate these dimensions of implementation in the context of a larger and more definitive effectiveness trial.Conceptually, the development of discreet implementation strategies for individual ILI components has appeal if they successfully minimize workflow disruptions, distribute costs of the new activities across different partners, and map costs to existing pathways for health payer reimbursement. Possible disadvantages are that the individual components may not prove as effective in isolation, and additional strategies must be developed to coordinate staff roles, technologies, and patient transitions among the practice components. Some patients may still face access barriers if, for example, referral-based resources are limited or health payers do not provide reimbursement for remote weight monitoring or lifestyle counseling activities by non-physicians.This preliminary research indicates that strategies to implement ILI core components are feasible for primary care practices and generally acceptable to patients. Further research should seek to optimize implementation strategies to maximize feasibility, acceptability, sustainability, and reach, as well as to demonstrate effectiveness and cost-effectiveness compared with alternative service models. Engaging stakeholders in co-creation of these strategies holds promise to improve both implementation and reach of ILI components in new ways that achieve population health and health equity for millions of Americans who are currently overweight or obese and already engaged by the healthcare sector.


Pompe disease is a rare glycogen storage disorder caused by deficiency of the lysosomal enzyme acid alpha-glucosidase (GAA), leading to glycogen deposition in multiple tissues. Infantile-onset Pompe disease (IOPD) patients present within the first year of life with profound hypotonia and hypertrophic cardiomyopathy. Treatment with enzyme replacement therapy (ERT) has significantly improved survival for this otherwise lethal disorder. This study aims to describe the clinical and molecular spectrum of Malaysian IOPD patients, and to analyze their long term treatment outcomes.GAA gene was performed by polymerase chain reaction and Sanger sequencing. Structural modelling was used to predict the effect of the novel mutations on enzyme structure.Seventeen patients diagnosed with IOPD between 2000 and 2020 were included in this retrospective cohort study. Clinical and biochemical data were collated and analyzed using descriptive statistics. GAA enzyme levels were performed on dried blood spots. Molecular analysis of the Our cohort had a median age of presentation of 3 months and median age of diagnosis of 6 months. Presenting features were hypertrophic cardiomyopathy (100%), respiratory insufficiency (94%), hypotonia (88%), failure to thrive (82%), feeding difficulties (76%), and hepatomegaly (76%). Fourteen different mutations in the GAA gene were identified, with three novel mutations, c.1552-14_1552-1del, exons 2–3 deletion and exons 6–10 deletion. The most common mutation identified was c.1935C > A p.(D645E), with an allele frequency of 33%. Sixteen patients received ERT at the median age of 7 months. Overall survival was 29%. Mean age of death was 17.5 months. Our longest surviving patient has atypical IOPD and is currently 20 years old.This is the first study to analyze the genotype and phenotype of Malaysian IOPD patients, and has identified the c.1935C > A p.(D645E) as the most common mutation. The three novel mutations reported in this study expands the mutation spectrum for IOPD. Our low survival rate underscores the importance of early diagnosis and treatment in achieving better treatment outcomes. GAA gene cause deficiency of the lysosomal enzyme acid alpha-glucosidase (GAA), leading to glycogen deposition in multiple tissues } + 0.6/BSA  with patients in a study in Taiwan who were diagnosed via newborn screening and given very early ERT prior to symptom onset . These pThe long term morbidities experienced by the patients in our cohort are similar to those reported in previous studies, which include musculoskeletal, cardiac, respiratory, oropharyngeal, speech, hearing and neurocognitive dysfunction . While tSeveral long term follow-up studies of IOPD patients on ERT have reported neuroimaging abnormalities, including ventricular enlargement, extra-axial cerebral fluid accumulation and delayed myelination, which resolved with time . PerivenThis is the first study that analyzes the genotype and phenotype of IOPD patients in Malaysia, and has established the c.1935C > A p.(D645E) mutation as the most common mutation, with an allele frequency of 33%. The novel mutations identified in this study expands the mutation spectrum for IOPD. Our low survival rate of 29% highlights the importance of early diagnosis and initiation of treatment. Newborn screening for Pompe disease is the way forward to achieving better survival and long term outcomes.


RNF213 and neurofibromatosis type 1 (NF1) patients. While deleterious RNF213 variants were associated with a severe MMA clinical course with early symptom onset, frequent posterior cerebral artery involvement and higher stroke rates in multiple territories, NF1 patients had a similar infarct burden compared to non-NF1 individuals and were often diagnosed incidentally during routine MRIs. Additionally, we found that MMA-associated RNF213 variants have lower predicted functional impact compared to those associated with aortic disease. We also raise the question of MMA as a feature of recurrent as well as rare chromosomal imbalances and further support the possible association of MMA with STAT3 deficiency. In conclusion, we provide a comprehensive characterization at the genetic and clinical level of a large exclusively pediatric MMA population. Due to the clinical differences found across genetic subgroups, we propose genetic testing for risk stratification as part of the routine assessment of pediatric MMA patients.Pediatric Moyamoya Angiopathy (MMA) is a progressive intracranial occlusive arteriopathy that represents a leading cause of transient ischemic attacks and strokes in childhood. Despite this, up to now no large, exclusively pediatric MMA cohort has been subjected to systematic genetic investigation. In this study, we performed molecular karyotyping, exome sequencing and automated structural assessment of missense variants on a series of 88 pediatric MMA patients and correlated genetic, angiographic and clinical (stroke burden) findings. The two largest subgroups in our cohort consisted of  Moyamoya angiopathy (MMA) is a progressive intracranial occlusive arteriopathy characterized by a stenosis of the distal portion of the internal carotid artery and involvement of the anterior, middle, and posterior cerebral arteries. To compensate for the reduction in blood flow, the brain develops a compensatory angiogenetic response, thus producing an intracerebral network of small-caliber collaterals, which is responsible for a cloud-like appearance (“Moyamoya” in Japanese) in angiograms . Due to Although MMA represents an isolated manifestation in otherwise healthy individuals in approximately 50-75% of cases, it has also been found enriched in conjunction with a number of diverse conditions such as neurofibromatosis type 1 (NF1), sickle cell disease, Trisomy 21, congenital cardiac anomalies, renal artery stenosis and giant cervicofacial hemangiomas ) received an incidental MMA diagnosis at MRI while one (68632) was a symptomatic NF1 patient who carried an additional possibly deleterious RNF213 variant as well.Nine patients were excluded from the analysis of age at onset. Of these, 8 patients .MMD patients were on average 24.9 months (2.1 years) younger at onset compared to MMS patients  and 1.6 times younger than non-RNF213 patients with MMD (p = 0.0418). The proportion of individuals with (possibly) deleterious RNF213 variants as well as the age at onset did not differ significantly by sex or when the area of origin  was considered. Of notice, no deleterious RNF213 variants were detected in the 8 non-European patients.As visible in Fig. NF1 patients and all non-NF1 individuals in the cohort was present . Although RNF213 patients were on average younger at onset than NF1 patients (35.2 ± 35.5 versus 64.4 ± 41.3 months), this difference did not reach statistical significance as a result of incidentally diagnosed patients being excluded from the analysis (p = 0.0521).No significant difference in the age at onset between N = 88), ACA and MCA were the most commonly involved vessels , while ischemic areas localized most frequently in the cortical (29%) and subcortical (31%) MCA territories. On the contrary, the PCA was involved on average in 32% of cases. Both NF1 patients with (possibly) deleterious RNF213 variants, in whom PCA involvement was also seen, were excluded from further analysis of arterial involvement and strokes.In the overall cohort  in RNF213 patients compared to the non-RNF213 group. This difference in PCA involvement resulted in a higher number of total ischemic areas , with cortical PCA territorial, cortical MCA-PCA watershed and cortical territorial MCA strokes  of age. PCA arterial involvement as well as MCA cortical territorial and MCA-PCA cortical watershed strokes remained significant in this age subgroup as well  and tended to be lower when compared to all other MMS patients .In contrast to nts Fig. . NeverthRNF213 to MMD patients only, the differences shown in Fig. Similar to the findings for age at onset, restricting the angiographical and stroke pattern analysis of RNF213 patients and neurofibromatosis patients represented the two largest subgroups. A comparison of the relative frequencies with previous large sequencing studies is hampered by differences in the probands’ age as well as in the inclusion criteria used. In particular, no shared consensus exists on the definition of MMD and MMS, with the presence of common genetic or clinical findings such as Factor V-Leiden having been considered sufficient by other authors to classify a patient as having MMS. While the prevalence of RNF213 deleterious variants in our MMD patients (31%) lies either above or in line with what was detected in mixed pediatric/adult populations  in4810Lys) ¸ the at RNF213 variants in cis had mid-aortic syndrome (73577), indicating that extracranial arterial involvement may either represent chance associations or a mutation-specific phenotype. In support of the latter hypothesis, our in silico analysis of previously published RNF213 variants suggests that aortic vascular manifestations may only present in heterozygotes for more deleterious variants.In the last few years, the p.(Arg4810Lys) variant has been associated with other intra- and extracranial vascular manifestations as well, thus suggesting that it could lead to a wider phenotypic spectrum than previously recognized . Among oRNF213 patients, no differences in age at onset of MMA and infarct burden were seen compared to non-NF1 patients; thus we could not directly confirm previous suggestions that NF1-associated MMA follows a milder course with lower infarct burden [RNF213 could lead to a more severe phenotype. Because of this MRAs should be taken into consideration as part of the standard of care in pediatric NF1 patients.Although MMA became clinically manifest in NF1 patients on average later than in t burden . Nevertht burden , the preCASZ1, which is located in 1p36.22, plays a role in the immune system [CASZ1 is expressed in the vasculature and was identified as a risk locus for blood pressure and stroke [Furthermore, for several recurrent and rare CNVs we raise the question of association with MMA. Ouellette and colleagues showed recently how haploinsufficiency of the murine 16p11.2 ortholog leads to altered angiogenesis as well as functional cerebrovascular anomalies in vivo and human-derived endothelial cells display faulty angiogenetic activity . CASZ1, e system , acts ase system , and true system . Additiod stroke , so thatSTAT3 deficiency associated with MMA [STAT3-, IGF-1-, and PTEN-signaling were shown to be downregulated in cases, suggesting an involvement of these pathways in the pathogenesis of MMA [STAT3 in mediating the effects of VEGF on endothelial cells [Moreover, we provide an additional report of with MMA , thus stwith MMA  and arguwith MMA , who firs of MMA . The rolal cells  and, amoal cells , provideRNF213 variants we prove that this gene is associated with a more severe clinical presentation, characterized by early onset, posterior involvement and higher stroke rates in multiple territories. Because of these profound phenotypic differences, the employment of genetic testing in pediatric MMA cases could have multiple advantages. First, it would allow for the planning of tighter follow-up schedules in RNF213-positive children that do not present with multi-territorial involvement at diagnosis, as this is expected to appear at higher rates in this group. Second, it would allow for a cascade screening of family members, thus possibly leading to the identification of additional asymptomatic or misdiagnosed MMA cases. In the absence of evidence-based published recommendations, we would recommend performing MRI-MRA screening in asymptomatic siblings of patients with inherited RNF213 (likely) pathogenic variants once with no further follow-up if normal. Since sedation needed may be considered too risky for asymptomatic, very young siblings, the timepoint of MRI-MRA scanning should be based on collective decision making with informed parental consent. Otherwise, except for identical twins, MRI-MRA screening is recommended in siblings of moyamoya children only if they are symptomatic [RNF213 deleterious variants may provide clinical benefits when extended to MMS cases as well, as demonstrated by the two children with neurofibromatosis, RNF213 variants and PCA involvement in our cohort. Hence, we consider comprehensive genetic testing as an indispensable tool to be employed at time of diagnosis together with brain MRIs and angiographies.In conclusion, by describing a large group of children carrying predicted deleterious ptomatic . A searcRNF213 variants could allow for better variant classification. Finally, the penetrance of genetic risk variants should be tested in prospective cohorts.Despite the considerable achievements in the last years in unraveling the genetics of MMA, multiple areas remain open for discovery. Novel genes as well as somatic mosaicism for mutations in known MMA genes may play a significant role in its pathogenesis. Furthermore, the development of reliable functional testing for Supplemental Figure S1Table S1Table S2Table S3Table S4Table S5Legend to Supplemental Figure S1


The main aim of my PhD thesis was to describe the extent of the injury and illness problem in competitive adolescent (13–18 years old) distance runners . My thesis also: (1) examined the validity of session rating of perceived exertion (sRPE), to quantify internal training load, and (2) explored psychosocial responses to running-related injury (RRI).Despite the health benefits and popularity of distance running,A total of four articles were included in my thesis, related to three separate studies. The first study examined the effects of measurement timing and concurrent validity of sRPE.serious RRI (>28 days to 6 months of time loss) in a subsample of athletes. A total of 19 (12 women) athletes volunteered to participate, whereby each interview was split into two main sections—(1) background information and (2) injury experiences—and a thematic analysis approach was used to analyse interview transcripts.The second study used a mixed-methods study design, whereby 113 64 women) competitive adolescent distance runners across England completed an online questionnaire to generate initial insight into the epidemiology of RRI and to assess training practices. women coThe third study was a 24-week prospective cohort study, throughout which 136 73 women) competitive adolescent distance runners across England self-reported health problems and training practices on a weekly basis.3 women cIn study one, it was found that sRPE provides a valid measure of internal training load in competitive adolescent distance runners, irrespective of whether reported 0-min, 15-min or 30-min post-session completion.performance uncertainty, (2) injury (mis)management and (3) contested identity—support several theoretical relationships proposed in the integrated model of response to sport injury,serious RRI.The second study initially indicated that RRI is common in competitive adolescent distance runners  and that a large proportion of athletes (58%) self-reported a high level of specialisation. In the qualitative part of this study, analysis led to the development of three themes  and an oThe key findings from the third study were that: (1) the incidence of RRI per 1000 hours of exposure was markedly higher when compared with similar samples of adolescent endurance athletes; (2) at any time, 24% of athletes reported a health problem, with 11% having experienced a health problem that had a substantial negative impact on training and performance; (3) female athletes reported noticeably more illness compared with male athletes, including higher prevalence, incidence, time loss and severity; (4) regardless of sex, the most burdensome health problems included lower leg, knee and foot/toes injuries, alongside upper respiratory illnesses; and (5) the mean weekly prevalence of time loss was relatively low, irrespective of health problem type or sex.Based on the last key finding from the third study, it is feasible that a large proportion of health problems did not cause athletes to miss training or competition. This implies that competitive adolescent distance runners could be training and/or competing while also experiencing a health problem—acknowledged as a ‘silent issue’ that needs to be addressed and supported by further research.When combining the results from this thesis with other relevant literature, it becomes clear that measures aimed at reducing the risk of RRI in competitive adolescent distance runners need to be developed and integrated within broader ‘health promotion’ initiatives.


Science article, Wang and colleagues showed that the dipeptidyl peptidase 4 (DPP4) enzyme produced by the gut microbiota can interfere with the effect of host glucagon-like peptide-1 (GLP-1) involved in stimulating insulin secretion, and the specific inhibitor of microbial DPP4 (mDPP4), combined with clinical inhibitors of host DPP4 isoenzymes, further promotes blood glucose homeostasis.1 These results point out why certain patients respond inadequately to an antidiabetic medication.In a recent 2), and, currently, there is no cure for T2D. Beyond lifestyle interventions, diabetes medications or insulin therapy are used to help manage the disease. Among the antidiabetic drugs, metformin is frequently applied, but specific DPP4 inhibitors including alogliptin, sitagliptin, saxagliptin and linagliptin3 can also be utilized. A serious limitation of using these drugs is the inability of certain individuals to respond to the treatment.Type 2 diabetes (T2D), also known as adult-onset diabetes, is a common metabolic disorder characterized by the inability of cells to respond properly to insulin hormone mediating cellular glucose uptake and/or insufficient insulin production by pancreatic beta cells. As a consequence, the affected patients exhibit elevated levels of blood glucose (hyperglycemia), so their cells degrade other substances besides glucose (sugar), like lipids, to gain energy. The pathology affects millions worldwide . Such a microbial enzyme identified was mDPP4. In the host, the hDPP4 isozyme normally degrades GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) hormones, collectively called endogenous incretins as they stimulate insulin secretion in the presence of glucose  raised the question whether current therapeutic treatment against hDPP4  also works against mDPP4. Activity assays and structural studies performed by Wang and colleagues showed that the microbial isozyme cannot be inhibited with sitagliptin, necessitating a fundamentally novel therapeutic approach, in which both DPP4 isozymes (hDPP4 and mDPP4) are simultaneously inhibited to get a higher efficacy.1 Indeed, co-administration of a newly developed, specific mDPP4 inhibitor, Dau-d4 (a daurisoline derivative), and sitagliptin could further decrease blood glucose levels.Wang and colleagues demonstrate a specific mechanism that may explain the lowered efficacy of antidiabetic DPP4 inhibitors.5 It has been known for long that certain gut microbiota members (often belonging to the Bacteroides genus) possess enzymes that have the same or similar functions to human enzymes even with substantially different amino acid sequences. Identifying such isozymes is highly challenging. Using a newly established enzyme activity screening platform, Wang and colleagues tested stool-derived ex vivo microbial communities and identified more than 70 bacterial enzymes with functional activity.1 Among these microbial enzymes, mDPP4 was the top hit statistically. The detailed analysis of mDPP4 pointed out that it is mostly produced by Bacteroides spp (predominantly by Bacteroides thetaiotaomicron strains). A medically relevant observation was that these mDPP4 proteins normally do not cross the gut barrier. However, upon local inflammation or metabolic disorders (conditions associated with T2D), there is a patchy breakdown of the epithelial barrier causing the so-called leaky gut phenomenon when luminal content, including mDPP4, enters the gut mucosal layer and degrades GLP-1. This condition-specific effect of mDPP4 is useful for targeting it, as it means under normal conditions mDPP4 is in the gut lumen and probably has no physiological role. But upon a leaky gut situation, mDPP4 enters the host and its pharmacological inhibition could increase the response rate for sitagliptin in T2D patients.Understanding how the gut microbiota influences host physiology remains a fundamental problem in biology with significant medical implications.4 and emphasize the importance of developing therapies that simultaneously target a gut microbial and host isozyme pair to achieve greater clinical effectiveness.1One of the major strengths of the study was to demonstrate that a group termed sitagliptin low responders (SLRs) has a considerably higher fecal DPP4 activity. However, it remains unanswered whether plasma GLP-1 activity is also changed in these SLR patients. In addition, measuring fecal DPP4 activity may predict the therapeutic potential of sitagliptin treatment in T2D patients. Another clinical relevance of this observation is the importance of a healthy gut during sitagliptin treatment as mDPP4 could not cause problems in a normal epithelial barrier. Hence, diet and probiotic supplements that support the healthy epithelial layer could increase the efficiency of sitagliptin treatment. Thus, probably clinical intervention studies will be based on the detailed mechanisms uncovered by Wang and colleagues. Together, these results uncover a general mechanism that underlies the variable response in certain patients to an antidiabetic medication,4 has at least three important implications. First, factors that seriously change the composition of the gut microbiome can heavily influence host homeostasis and cause disease. For example, an antibiotic treatment or unbalanced nourishment can lead to the overgrowth of a certain bacterial taxon in the gut microbiome, and the enzyme produced by this community enhances or weakens the function of its host counterpart to pathological levels. Second, circumstances causing damage to the gut structure  may enable the transit of bacterial metabolites and proteins with undesired biological activity through the intestinal wall. Third, future pharmacological innovations should consider the fact that several protein targets share redundant roles with their corresponding microbial counterparts even if the latter display no significant homology at the level of amino acid sequence. In this case, inhibitors for both host and bacterial proteins should be simultaneously developed, to reach sufficient efficacy. Alternatively, further studies should focus on developing inhibitors with dual activity against both hDPP4 and mDPP4. Such a combined treatment, supported by establishing and keeping a healthy gut microbiota and gut epithelial barrier, is critical to restore and maintain normal physiology in the host.Appreciating the role the microbiome plays in normal physiology and pathology


Karimi-Rouzbahani H, Woolgar A, Rich AN. 2021. Neural signatures of vigilance decrements predict behavioural errors before they occur. Published 8 April 2021distance to object analyses on correct trials, classifiers were trained and tested using data from across timepoints (since each distance was a bin spanning multiple timepoints) and trials. Signal samples from all trials and timepoints within each distance were randomly allocated to one of the 10 folds to be used in the 10-fold cross-validation process. This meant that, on any given iteration of cross-validation, a single sample was never in both the training and the testing set, but samples in the training and testing set could be drawn from different timepoints of the same experimental trial. Autocorrelation in the data over time could therefore have inflated the decoding accuracy. To correct this, we have re-run the analysis decoding distance to object ensuring that training and testing sets drew from independent trials, and re-ran all analyses that drew on these decoding results. Analyses that did not decode distance to object are not affected, and analyses decoding distance to object on error trials are also not affected.In the decoding We replicate our main finding of being able to use neural patterns to predict the occurrence of errors, along with all the effects of attention. The interaction indicating decreased distance decoding for late vs early blocks in monitoring but not active conditions has decreased in strength from being evident (BF >3) at two consecutive time-windows to one (BF = 6.7) and there is no longer a main effect of target frequency. The link we reported between behaviour and informational connectivity is no longer present.Underline indicates differences between corrected and original text.This necessitated the changes outlined below. Abstract][Corrected text: #1][subtle evidence of this also in the neural decoding using Magnetoencephalography: for one time-window (of 80ms) coding of critical information declined more during monitoring versus active conditions.There was Original text: #1][This was mirrored in neural decoding using Magnetoencephalography: coding of critical information declined more during monitoring versus active conditions along the experiment.Results: Effects of Target Frequency on criticaldistance to objectinformation][Corrected text: #1][[--deleted text--]Original text: #2][The main effect of Time on Task reflected decreased decoding in later blocks .Corrected text: #3][Original figure: Figure 3][Corrected figure: Figure 3—figure supplement 1B][Original figure: Figure 3—figure supplement 1][Corrected figure: Figure 3—figure supplement 2B][Original figure: Figure 3—figure supplement 2][Corrected text: #1] trials in which the dots are in the distractor (Unattended) colour, in which the attentional load is low, result in less informational connectivity between occipital and frontal brain areas compared to [--deleted text--] Attended trials. This is consistent with a previous study , which suggested that large-scale functional brain connectivity depends on the attentional load, and might underpin or accompany the decrease in information decoding across the brain in the unattended condition.Results showed strong evidence  for higher informational connectivity for trials with Attended compared to Unattended dots, and moderate evidence for higher connectivity in Active compared to Monitoring conditions . There was insufficient evidence to determine whether there was a main effect of Time on Task . There was moderate evidence for no two-way and three- way interactions between the three factors . These results suggest that Monitoring conditions and trials in which the dots are in the distractor (Unattended) colour, in which the attentional load is low, result in less informational connectivity between occipital and frontal brain areas compared to Active conditions and Attended trials, respectively. This is consistent with a previous study , which suggested that large-scale functional brain connectivity depends on the attentional load, and might underpin or accompany the decrease in information decoding across the brain in these conditions.Results showed strong evidence . In addition, there was moderate evidence for no effect of Time on Task and Target Frequency , as well as for two-way and three-way interactions between the three factors . [--deleted text--] Therefore, in contrast to an auditory monitoring task which showed decline in univariate graph-theoretic connectivity before behavioural errors , we observed no change in informational connectivity on error. Note that, the number of trials is equalized across the 8 conditions in each of our analyses separately.Original text: #2][Original figure: Figure 5][Corrected figure: Figure 5—figure supplement 1][Original figure: Figure 5—figure supplement 1][Corrected figure: Figure 5—figure supplement 2B][Original figure: Figure 5—figure supplement 2][Results: Can we predict behavioural errors using neuroimaging?][Corrected text: #1][0.4 standard deviation below the average accuracy on the other participants’ validation  sets .This was ~Original text: #1][This was ~1.5 standard deviation below the average accuracy on the other participants’ validation  sets .Corrected text: #2][Corrected Figure 6 caption sections][Corrected figure: Figure 6—figure supplement 1][Original figure: Figure 6—figure supplement 1][Discussion][Corrected text: #1][moderate evidence for no change in connectivity between correct and error trials. [--deleted text--] Informational connectivity is unaffected by differences in absolute levels of information encoding . It could be sensitive to different levels of noise between conditions, but there was no evidence for that in this case. Apart from sensory information coding and sensory-based informational connectivity, which were evaluated here, there may be other correlates we have not addressed.Our information-based brain connectivity method showed Original text: #8][We statistically compared the two types of trials and showed a large advantage in the level of information contained at individual-trial-level in correct vs. miss trials.Our error prediction results showed a large decline in the crucial task-relevant  …Corrected text: #11][We observed that the neural representation of critically relevant information in the brain [--deleted text--] was particularly poor on trials where participants missed the target.Original text: #12][We used this observation to predict behavioural outcome of individual trials and showed that we could predict behavioural outcome…Original text: #13][We used this observation to predict behavioural outcome of individual trials and showed that we could accurately predict behavioural outcome…Corrected text: #14][momentary lapses in attention impact information coding in the brain and propose an avenue for predicting behavioural errors using novel neuroimaging analysis techniques.These results provide new insights about how Original text: #14][These results provide new insights about how vigilance decrements impact information coding in the brain and propose an avenue for predicting behavioural errors using novel neuroimaging analysis techniques.Materials and Methods][Added text: #1][Each distance covered a time window of ~80ms (varied slightly as dot trajectories varied in angle) which consisted of 4 or 5 signal samples depending on which of the 15 predetermined distances was temporally closest to each signal sample and therefore could incorporate it.Added text: #2][0.4 (±0.07) times the SD below the decoding accuracy on the validation set across participants.The optimal threshold was Original text: #1][The optimal threshold was 1.54 (±0.2) times the SD below the decoding accuracy on the validation set across participants.Supplementary Materials][Corrected text: Source text file for Figure 3—figure supplement 1B][distance information for all attended conditions was greater than chance  across all 15 distance levels with the exception of distance 8 in the late monitoring condition . There were also timepoints with greater than chance decoding for the unattended conditions but these were far less consistent .There was moderate or strong evidence that decoding of Original text: Source text file for Figure 3—figure supplement 1B][distance information for all conditions was greater than chance  across all 15 distance levels .There was moderate or strong evidence that decoding of


To investigate the association between folate levels and the risk of gestational diabetes mellitus (GDM) risk during the whole pregnancy.In this retrospective cohort study of pregnant women, serum folate levels were measured before 24 gestational weeks (GW). GDM was diagnosed between 24th and 28th GW based on the criteria of the International Association of Diabetes and Pregnancy Study Groups. General linear models were performed to examine the association of serum folate with plasma glucose (i.e. linear regressions) and risk of GDM  after controlling for confounders. Restricted cubic spline regression was conducted to test the dosage–response relationship between serum folate and the risk of GDM.A sigle, urban hospital in Shanghai, China.A total of 42 478 women who received antenatal care from April 2013 to March 2017 were included.P-for-trend < 0·001). The positive association between serum folate and GDM remained when stratified by vitamin B12 (adequate v. deficient groups) and the GW of serum folate measurement (≤13 GW v. >13 GWs)Consistent positive associations were observed between serum folate and plasma glucose levels . The adjusted relative risks (RR) and 95 % CI of GDM across serum folate quartiles were 1·00 (reference), 1·15 ), 1·40 ) and 1·54 ), respectively (The findings of this study may provide important evidence for the public health and clinical guidelines of pregnancy folate supplementation in terms of GDM prevention. Unable to synthesise folate, human beings depend on dietary intake and/or supplementation to meet the folate requirement for maintaining normal biological functions. The metabolic demand for folate increases during pregnancy due to rapid maternal and fetal cellular growth and development.Folate, a B vitamin, serves as a cofactor and coenzyme in various physiologic processes, including genome maintenance and repair, gene expression regulation, amino acid metabolism, neurotransmitter synthesis and myelin formation. Strong evidence from different countries has shown that periconceptional supplementation of folic acid (FA) dramatically reduced the risk of pregnancies complicated with neural tube defects,6. Based on these findings, public health agencies worldwide issued recommendations advising women to take FA supplements at a dose of 400 μg/d for 4–12 weeks before pregnancy and 8–12 weeks during early pregnancy,8.Periconceptional folate deficiency has been linked with increased risks of neural tube defects. For instance, a study from the Boston Birth Cohort showed that over half of the mothers took FA supplementation almost daily during the second and third trimesters, resulting in a wide range of maternal plasma folate levels approximately 23 % elevated (>45·3 nmol/l). Another recent survey from China reported that 30·7 % of women took FA for 12–24 weeks during pregnancy,12.Nevertheless, most women take FA for longer periods than recommended. Many continue taking FA as a prenatal vitamin and mineral supplement throughout pregnancy, concerns about its possible adverse effects on other pregnancy and birth outcomes are rising. For example, a recent study from the Shanghai Preconception Cohort with 1058 participants showed that higher maternal erythrocyte folate levels were positively associated with the risk of gestational diabetes mellitus (GDM) in early pregnancy. Affecting approximately 5 % to 17 % of all pregnancies worldwide, GDM is a major gestational complication associated with short- and long-term adverse outcomes for both mothers and neonates,17. However, studies focusing on the folate levels of the first and second trimesters are scarce.Although FA supplementation was considered safe for pregnant women, after which time there is no proven benefit of taking FA. Compared with the first trimester, it is all the more essential to weigh the pros and cons of FA supplements in the subsequent trimesters. Based on the above findings, this study examined the association between serum folate and GDM risk during the first and second trimesters in a large Chinese cohort.The neural tube normally closes 24–28 d after conception, while other major malformations develop within 12 weeks of gestationn 43 846) who received prenatal care at a tertiary level A grade hospital in Shanghai, China, between April 2013 and March 2017. Women without serum folate data before the 24th week of gestation  were excluded, and a total of 42 478 women with live births and no glucose levels suggestive of type 2 diabetes were included in this study. At their first prenatal visit, all participants provided informed consent to use their electronic medical record in future research. This study was approved by the Human Ethics Committee of the Hospital in October 2017.The participants were selected from a cohort derived from the electronic medical records of pregnant women  were extracted from the electronic medical records of the Hospital Information System.12 levels were measured using the chemiluminescence method in an ARCHITECT i2000SR immunoassay analyzer . The inter-assay CV were 3·4 % to 9·6 %, and the intra-assay CV were 2·0 % to 3·6 % for serum folate . Serum folate and vitamin B12 levels were extracted from the Laboratory Information System.As a part of the routine blood test in their first prenatal visits to identify vitamin deficiencies, serum folate and vitamin B. Briefly, all participants underwent a 75-g oral glucose tolerance test between the 24th and 28th GW. Participants with fasting plasma glucose ≥ 5·1 mmol/l, 1-h plasma glucose (1-h PG) ≥ 10 mmol/l or 2-h plasma glucose (2-h PG) ≥ 8·5 mmol/l after the oral glucose tolerance test tests were diagnosed as GDM.GDM was screened using a one-step method and diagnosed according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criterian (%), for categorical variables and mean (sd) for continuous variables. To compare the baseline characteristics between the excessive folate group (>45·3 nmol/l) and the normal folate group (≤ 45·3 nmol/l), we conducted the Student’s t-test or the Kolmogorov–Smirnov test (variables with skewed distribution) for continuous variables and Pearson’s Chi-squared test for categorical variables.For the lack of a specified cut-off for folate levels during pregnancy, serum folate levels were typically categorised into two groups according to the upper level of optimal serum folate (45·3 nmol/l) among women of reproductive age. We presented the descriptive data as frequencies, sd) and plasma glucose  in oral glucose tolerance test. Log-binomial regression models were conducted to estimate the relative risks (RR) for GDM. The 95 % CI were adopted for serum folate (quartiles). We excluded in vitro fertilisation  or multiple pregnancies  from the primary analysis and adopted the following potential confounders for the multivariate models: BMI status , fetal gender, parity, vitamin B12, maternal age and maternal education. The significance of the linear trends across quartiles of serum folate levels was evaluated using the median value for each quartile and analysed as a continuous variable in the multivariate models.The main exposure, serum folate, was treated as both continuous and categorical variables (quartiles). Linear regression models were performed to analyse the association between serum folate (per 12 levels (< 148 v. ≥ 148 pmol/l) or the trimester when serum folate was measured (≤13 v. >13 GW). Second, we used Rubin’s causal model to quantify the robustness of causal inferences and interpret how much the bias must be to invalidate an inference in terms of replacing observed cases with counterfactual cases or cases from an unsampled population. Third, we assessed the folate-GDM association by including IVF and multiple pregnancies. Additionally, restricted cubic spline regressions were performed with five knots  to investigate whether there was a threshold between serum folate and GDM risk.We also conducted several sensitivity analyses. First, we stratified our analyses by serum vitamin BP < 0·05 was considered statistically significant.Statistical analyses were performed on Stata 15.0 , and restricted cubic spline was implemented with R (version 4.0.3). 12 level and the GW of folate measurement, were significantly different between the two groups. The three oral glucose tolerance test values, i.e. fasting plasma glucose, 1-h blood glucose and 2-h blood glucose, were significantly higher in the excessive serum folate group than in the normal serum folate group  developed GDM. The GDM incidence of the excessive serum folate group (13·9 %) was higher than that of the normal serum folate group (10·2 %). Most characteristics, including maternal age, nullipara, IVF, singleton or twins, fetal gender, maternal education, serum vitamin B12 status and the GW of folate measurement. The associations between serum folate and 1-h plasma glucose levels were the most obvious, while associations between serum folate and fasting plasma glucose levels were the least significant.The linear associations between serum folate and plasma glucose levels are shown in Table P-trend < 0·001). The positive association was persistent and the trend remained statistically significant after adjusting for pre-pregnancy BMI status, fetal gender, parity, maternal age, vitamin B12 level and maternal education: the adjusted RR across serum folate quartiles were 1·00 (reference), 1·15 ), 1·40 ) and 1·54 ), respectively (P-trend < 0·001).The median serum folate level by quartiles (nmol/l) was 25·08, 38·82, 50·37 and 56·30, respectively. We found a positive association between maternal serum folate levels and GDM risk (Table 12 (adequate v. deficient groups) and the GW of serum folate measurement (≤13 GW v. >13 GW). Rubin’s causal model results showed that to invalidate the inference, 81·12 % of the estimate would have to be due to bias or 30 920 cases would have to be replaced by cases with zero effect. Sensitivity analyses with IVF (n 1731) and multiple pregnancies (n 860) included showed that the association between serum folate and GDM risk remained positive and generally unchanged ).As shown in Table . The restricted cubic spline regression results showed a linear relationship (P = 0·808) between serum folate and GDM risk without any threshold  among women of reproductive age instead12 status and the GW of folate measurements. The association between serum folate levels and GDM risk was linear without a significant breakpoint or threshold. Sensitivity analysis, stratified analysis and Rubin’s causal model showed good robustness of the estimates.In this study on 42 478 Chinese pregnant women, we observed a positive association between serum folate and GDM risk. The RR of GDM increased across serum folate quartiles regardless of vitamin B,22, our findings are in line with the results of two Chinese cohort studies recognising positive associations between gestational folate supplementation and GDM risk. A China-Anhui Birth Cohort Study (C-ABCS) associated daily FA supplement consumption in the first trimester with increased risks of GDM ). The Tongji Maternal and Child Health Cohort (TMCHC) revealed a significant correlation between prolonged intake of FA > 800 mg/d and higher risks of GDM ). However, measurements of folate exposure were self-reported (FA supplement) in both of the two studies above. Therefore, we used serum folate instead, which is an objective measure of circulating folate level and could reflect the women’s biological response to both folate from food and supplements. In addition, serum folate mirrored recent folate status and was preferred over erythrocyte-folate as it can be precisely measured using immunological or chromatography methods. Our results are also consistent with the results of Shanghai Preconception Cohort, which most recently reported that daily folate supplementation in early pregnancy increases the risk of GDM ) and higher maternal erythrocyte folate in early pregnancy is significantly associated with the risk of GDM. In the meantime, this study also extended and supplemented the Shanghai Preconception Cohort study with the association between folate and GDM in the second trimester.Although previous cohort studies have associated higher pre-pregnancy supplemental folate intake with lower risks of GDM in American women. Animal experiments indicated that excessive maternal folate supplementation could cause offspring cognitive impairment through the epigenetics pathways and offspring insulin resistance through the mitochondrial damage mechanisms. A recent meta-analysis pointed out that the effects of folate supplementation on fasting insulin levels are stronger in women than in men, with similar trends for fasting glucose and the Homeostatic Model Assessment of Insulin Resistance. Granted that these randomised controlled trials are performed in non-pregnant women, they offer very strong evidence against a causal interpretation of the findings presented in this study. The specific mechanism by which excessive gestational folate supplementation affects maternal metabolism has not been reported. The potential effects of folate supplementation on glycaemia warrant investigation in the future.The mechanism through which high serum folate levels cause GDM risks is still unclear. Previous studies mostly focused on the adverse health effects of excessive gestational folate supplementation on neonate. The polymorphism of genes involved in folate metabolism (e.g. methylene tetrahydrofolate reductase and methionine synthase reductase) is associated with various diseases . The epidemiology of the polymorphism of C677T varies with geography and ethnicity, which might contribute to the opposite associations between folate supplementation and GDM in different countries or regions–23. However, the interference of polymorphism of genes involved in folate metabolism with the results cannot be ruled out in this study. Therefore, the effects of folate metabolism-related gene polymorphisms should be considered when evaluating the association between folate supplementation and GDM in the future. Secondly, although serum folate levels were measured, supplement-derived folate and dietary-derived folate could not be distinguished. This study also failed to detect unmetabolised folate levels. Studies have associated unmetabolised plasma FA with decreased natural killer cell activity, which has also been suggested to be involved in the pathogenesis of GDM. Thus, the potential effects of unmetabolised FA need to be further studied. In addition, as with all retrospective studies, we cannot completely rule out all potential confounding factors, such as gestational weight gain and nutritional status, previous GDM and other socio-economic factors. Only maternal education has been considered. Nevertheless, the result of Rubin’s causal model indicated that the correlation between folate and GDM risk was unlikely to be caused by potential confounding factors. Therefore, the conclusion of this study needs to be further verified by RCT and related mechanism research.Although this study revealed a robust association between high folate levels and high GDM risks during the first two trimesters in a large cohort of Chinese pregnant women, it is not without limitations. Firstly, it has been reported that the determinants of folate status may be multiple, including genetic, biological and socio-economic componentsBased on the above, we observed a positive association between serum folate and GDM risk during the first and second trimesters in a large retrospective cohort study of 42 478 Chinese pregnant women. Adverse effects of excessive folate should be considered from a GDM prevention perspective. The optimal threshold of folate level, especially after the first trimester, and the mechanism behind the association warrant further examination.


Small angle X-ray scattering (SAXS) wasused to probe the presence of crystalline drugs in suspension duringdigestion. In particular, the impact of one drug on the solubilizationof the other was elucidated to reveal potential drug–drug interactionsin a drug combination therapy. Our results showed that lopinavir andritonavir affected the solubilization of each other during digestionin lipid-based formulations. While addition of ritonavir to lopinavirimproved the overall solubilization of lopinavir, the impact of lopinavirwas to reduce ritonavir solubilization as digestion progressed. Thesefindings highlight the importance of assessing the solubilizationof individual drugs in a combined matrix in order to dictate the stateof drugs available for subsequent absorption and metabolism. Enhancementin the solubilization of lopinavir and ritonavir in a drug combinationsetting  Consumption of milk inthe early stages of life is ubiquitous and, as such, has often beenused as a vehicle for drug administration. Assessing the performanceof drugs following intake of milk (and other similar foods) is thereforerecommended in the development of pediatric drug formulations, aswas recently outlined by the Food and Drug Administration (FDA).7 which can facilitate drug solubilization during digestion in thegastrointestinal tract to enhance oral bioavailability.10 Our group has previously shown that solubilization of poorly watersoluble drugs such as artefenomel (OZ439),9 ferroquine,10 and clofazimine11 in the small intestinal condition during digestionwas improved when coadministered with full fat milk, and similar behaviorhas also been observed in vivo.13 The enhanced solubilization of these drugs was primarily attributedto the release of fatty acids during the digestion of triglyceridesin milk by the gastrointestinal enzymes.10 However, giventhe inherent variability of milk composition, translating milk asa viable lipid-based formulation in clinical settings is challenging.Hence, consideration of alternative milk-like systems including infantformula is an important development in this area.Milk has also been exploredas a formulation excipient for poorlywater soluble lipophilic drugs since it is a natural lipid-based formulation,14 Itwas found that the extent to which drugs could be solubilized in milkand infant formulas during digestion was greatly dependent on theamount and types of fatty acids constituting the triglycerides andon the presence of a partner drug in a combination drug therapy wheretwo or more drugs were coadministered. For example, in a fixed dosecombination of antimalarial drugs artefenomel/ferroquine, the solubilizationand oral bioavailability of artefenomel was found to be reduced whenferroquine was administered concurrently.14 This highlighted the importance of understanding the fate of drugswhen combined in a lipid-based formulation.Recent studieshave explored the use of infant formulas as potentialmilk substitutes to deliver poorly water soluble drugs by investigatingkey lipid components that dictate drug solubilization in milk andinfant formulas during digestion.15 andritonavir (ABT-538)16 are protease inhibitorsthat are used in a combination drug therapy to treat HIV (human immunodeficiencyvirus) infection in adults and children. The pharmacokinetics of lopinavirand ritonavir have been widely reported,19 and it has been widely accepted that ritonavir isa “pharmacokinetic booster” for lopinavir, i.e., coadministrationof ritonavir with lopinavir improved the oral bioavailability of thelatter by inhibiting the cytochrome P450 3A (CYP3A) enzymes in theintestine and liver, thereby reducing the first-pass metabolism oflopinavir.20 However, in vitro studies designed to indicate any contribution of mutual enhancementor inhibition of solubilization of lopinavir and ritonavir in theGI tract to changes in absorption and bioavailability are still lacking.In the context of milk and infant formula as potential vehicles forthese drugs in low economy settings, this question is important forthis combination of drugs and also for future combination therapiesmore generally.Lopinavir in vitro digestion was investigated with the aim to (1) understand how thedigestion of milk and infant formula can affect drug solubilizationand (2) elucidate the impact of ritonavir on solubilization of lopinavirand vice versa at different dose ratios. in situ during in vitro digestion under simulated smallintestinal conditions. The concentration of drugs partitioned intothe digestion phases of the lipid-based formulations were separatedby ultracentrifugation, viz. solid precipitate, aqueousphase containing different colloidal structures, and residual lipidphase, were measured using high performance liquid chromatography(HPLC) to quantify the amount of drugs dissolved in each phase.Therefore, in this study, the solubilizationbehavior of lopinavirand ritonavir in milk-based formulations undergoing 22.114 Medium chain triglyceridescontaining caprylic/capric acids  were a giftfrom Gattefossé . Long chain triglyceridesrich in sn-2 palmitate  were a giftfrom Enzymotec Ltd., . Milk fat globular membrane was kindly provided by Arla Foods Ingredients Group P/S . Trizma maleate reagent grade, 4-bromophenylboronic acid, ammonium acetate for HPLC, sodium taurodeoxycholatehydrate , and sodium azide (>99%) were purchasedfrom Sigma-Aldrich . DOPC  was purchased from Cayman Chemical. Sodium chloride (>99%) was purchased from ChemSupply. Calcium chloride dihydrate (>99%)andsodium hydroxide pellets (min. 97%) were purchased from Ajax Finechem. Hydrochloric acid (36%) was purchasedfrom LabServ . Lipase (USPgrade pancreatic extract) was purchased from Southern Biologicals. Methanol HPLC grade (LiChrosolv) and dichloromethane(DCM) were purchased from Merck. Water was deionized and distilled using a Milli-Q waterpurification system . All the chemicals wereused without further purification.Lopinavir (>99%) andritonavir(>99%) were purchased from Haihang Industry Co. Ltd. ;and the drugs were micronized with mortar and pestle prior to experiments.Bovine milk  was purchased froma local supermarket . Infant formula  was provided by Medicinesfor Malaria Venture (MMV). Nutritional information and fatty acidcompositions of the infant formula have been previously reported (IF2in the reference).2.2Lopinavir (50 mg), ritonavir(50 mg), or mixtures of lopinavir:ritonavir at specified ratios 1 were ad21 Lipids from the MCT or LCT (0.76 g) were mixedwith 0.11 g of MFGM in 10 mL of tris buffer , and the mixtures were sonicated at 25 amplitude,2 s on/off for 3 min (for MCT) or 4 min (for LCT) using a MisonixS-4000 ultrasonic processor . Samples for LCT wereincubated in a 60 °C oven for 5–10 min prior to sonicationto melt the lipids. The resulting volume of the dispersed MCT andLCT after sonication was adjusted to 20 mL using tris buffer . The MCT or LCT emulsions (17.5mL) were subsequently added to the acidified lopinavir and/or ritonavirsuspensions, and the drug/lipid mixtures were digested using 2.25mL of lipase. The pH of the samples during digestion was maintainedat 6.5 using either 2.0 M NaOH (for MCT) or 0.2 M NaOH (for LCT).Suspensions of lopinavir and ritonavir in simple triglycerideemulsions(3.8 w/v% fat MCT and LCT) were prepared in tris buffer in the presenceor absence of bile salt micelles (4.7 mM NaTDC and 0.98 mM DOPC).2.32.3.1q range between 0.04 and1.96 Å–1, where Q is the scatteringvector defined as (4π/λ)sin(2θ/2), 2θ is thescattering angle, and λ is the X-ray wavelength. The 2D SAXSimages recorded were reduced to functions of I(q) versus q by radial integration usingthe in-house software ScatterBrain (version 2.71). X-ray scatteringpatterns of lopinavir and ritonavir powders after dispersion in 0.1M HCl solution were also obtained to observe any solid-state changesoccurring under gastric conditions: the powdered drugs were incubatedfor 3 h in 0.1 M aqueous HCl and filtered using a nylon membrane  and the solids were driedovernight in a vacuum oven at room temperature before being transferredto a capillary for scattering measurements.Lopinavirand ritonavir drug powders were loaded into glass capillaries .The capillaries were mounted in the X-ray beam of the SAXS/WAXS beamlineat the Australian Synchrotron (ANSTO) , and scatteringpatterns of the powders were acquired with a 1 s acquisition timeusing a Pilatus 2 M detector. The sample-to-detector distance wasabout 560 mm to cover a 2.3.2in vitro digestion of the drug/lipidformulations (details in q range of 0.04 < q < 1.96 Å–1. 2D SAXS images were recorded using the Pilatus 2M detector with 5 s acquisition time and 15 s delay between measurements(one measurement every 20 s); and the raw data was reduced to I(q) versus q by radialintegration using the in-house software ScatterBrain version 2.71.The areas of characteristic diffraction peaks from each drug in the I(q) versus q plots wereintegrated using Origin software, version 2020b.The pH-STATapparatus used for 2.4in vitro digestion of milk, infant formula, andsimple triglyceride emulsions containing the drugs was performed usingthe methods described in To quantify the amount of lopinavir andritonavir partitioned into digested phases of the lipid-based formulations,the 33.124 which can potentially affect their dissolution behavior and oralbioavailability. Identification of the solid-state forms of lopinavirand ritonavir and changes that can potentially occur following exposureto gastrointestinal conditions is therefore imperative for oral formulationdevelopment. 23 and a typeIII desolvated crystal form for lopinavir.24 Microscopy images of the nonmicronized drug crystals are shown in Figure S1. The diffraction peak positions forlopinavir and ritonavir (summarized in Table S1) remained consistent during dispersion and digestion in milk, infantformula, and triglyceride-based formulations, suggesting no solid-statechanges occurred. Similarly, dispersions of lopinavir and ritonavirpowders in 0.1 M HCl aqueous solution representing gastric pH alsodid not lead to polymorphic transformations .As with many small molecule drugs, lopinavir and ritonavir areknown to exist as different polymorphic/pseudopolymorphic forms,3.2Synchrotron small-angle X-ray scattering was used to monitor thesolubilization behavior of lopinavir during digestion of lipid-basedformulations by tracking the disappearance of the characteristic Braggpeaks shown in q = 0.52 Å–1 (the peakwith the strongest intensity) during the digestion of milk and infantformula are shown in Changes in the peak area attributable to lopinavirat Figure S3).Milk and infant formula contain a complex mixtureof triglycerides,and to gain further insight into the role of fatty acid chain lengthon solubilization of lopinavir, solubilization during digestion wasinvestigated using formulated emulsions prepared using medium chaintriglycerides and long chain triglycerides. Figure S4).25 The implication of the sedimenting of the lipid to form a pelletrather than creaming to form a separate lipid layer means that itwas not possible to discriminate between precipitated drug and drugsolubilized in the lipid digestion phases. Therefore, the amount ofdrug in the ‘lipid+supernatant’ measurement is artefactuallylow for the MCT emulsion in Typically, when centrifugingemulsions after digestion, a lipidlayer and an aqueous supernatant layer may exist from which drug ishypothesized to be available for absorption, and a pellet layer containingsolid precipitated drug may also be present, which is assumed to representthe unavailable fraction, with the goal of formulation being to maximizethe amount of drug in the lipid+supernatant layers. Quantificationof lopinavir in the different layers using HPLC showed in the caseof the digested LCT emulsion that a higher amount of drug was presentin the lipid+supernatant layer compared to milk and infant formula3f. These3.3q = 1.26Å–1). The exception was the case of ritonavir+MCTwhere drug precipitation occurred (peak area increased during digestion).The results also indicated that the area of the characteristic ritonavirpeak  was generallylarger when lopinavir was added to the system prior to lipase injection(time <0 min) but comparable values were observed after digestion.Similar trends were observed when excess lopinavir was present at4:1 lopinavir:ritonavir weight ratios, as seen in Figure S5).Solubilization of ritonavir was incomplete in allthe lipid formulationstested, regardless of whether lopinavir was also present 4. While in situ X-ray-based measurement.Attempts to use HPLC to quantifythe amount of ritonavir in thedifferent layers of digested infant formula after centrifugation wascomplicated by the preferential localization of ritonavir crystalsin the upper lipid phase after ultracentrifugation. Unlike lopinavir,where excess drug crystals sedimented into the bottom of the separatedphases, ritonavir crystals were found to partially reside in the upperlipid phase after digestion. This is shown in the crossed polarizedmicroscope images in 426 Lopinavir andritonavir are poorly water soluble protease inhibitors that have beenused to treat HIV infection.16 Lopinavir is categorizedeither as a class 2 or class 4 drug in the Biopharmaceutics ClassificationSystem (BCS).27 Lopinavir has an aqueoussolubility of about 3–4 μg/mL, which is not significantlyaffected by pH due to the nonionizable nature of the molecule.28 Meanwhile, ritonavir is a weakly basic drugwith thiazole moieties that can be ionized at gastric pH (pKa 1.8 and 2.6) but is un-ionized at the pH ofthe small intestine. Its aqueous solubility at pH 1.2 and 7.0 hasbeen reported to be about 400 μg/mL and 2 μg/mL respectively,28 and is categorized as a BCS class 4 drug.27 The poorly water soluble nature of lopinavirand ritonavir has therefore led to the development of various formulationstrategies to improve their oral bioavailability. These include, amongothers, amorphous solid dispersions29 and lipid-basedformulations.31Oral bioavailability ofactive pharmaceutical ingredients is oftenlimited by the poor solubility of the compounds in the gastrointestinaltract, thereby limiting the amount of drug available for absorptionfrom the small intestine.2 With the renewedappreciation of the importance of digestion in understanding theirperformance as well as contemporary approaches for in situ measurement of drug solubilization during digestion, the developmentof these materials as drug delivery systems is gaining momentum. Notably,infant formula is manufactured in a highly regulated environment asa dry preparation, providing the opportunity for its use as an excipientfor solid dosage forms, such as blended powder in a sachet or a dispersibletablet. It has a further advantage in providing potential for tastemasking; ritonavir has been reported as having a bitter taste andis recommended to be given to children with chocolate milk.Milk and infant formula-basedformulations are gaining interestas a formulation option for poorly water soluble drugs for use inpediatric and low economy settings due to their favorable safety andcost attributes compared to commercial lipid formulations containingsurfactants and solvents.in situ X-ray scattering. These studies are necessary todetermine whether milk-based formulations are expected to providea benefit in enhancing the solubilization of lopinavir/ritonavir inthese complex media during and after digestion. It should be notedthat while a broad correlation between drug solubility and oral bioavailabilitycan generally be drawn , the data show thatthe drug is not completely dissolved in the formulations prior todigestion, so dissolution into the lipid phase prior to digestionis not anticipated to completely drive absorption and digestion isa critical requirement to provision of a solubilizing environmentto maximize solubilization and consequently absorption. Solubilizationof poorly water soluble drugs in these systems is dominated by theidentity of the triglycerides present in the lipid droplets in theemulsions, specifically the monoglycerides and fatty acids producedon digestion.32 Thus, it was expected thatdifferent milk-like systems and lipid emulsions would have differenteffectiveness in solubilizing the two drugs during digestion. Thestudies presented here indicate that lopinavir is far more effectivelysolubilized by medium chain lipids . Ourprevious studies using MCT as a vehicle for artefenomel (performedunder the same in vitro digestion conditions as usedhere) showed that artefenomel was more efficiently solubilized inthe digested MCT than in LCT.14 This isconsistent with the studies presented here and suggests that MCT fortifiedinfant formula may present a particularly useful vehicle for the deliveryof lopinavir/ritonavir combination therapy.Consequently, we investigated the solubilization behaviors of lopinavirand ritonavir in milk-based lipid formulations during digestion using 23Generally, digestionof milk and infant formula with 3.8% (w/v)fat (75.2 mg of drug/g of fat) did not exert a significant impacton the solubilization of lopinavir, but addition of ritonavir to thesample mixtures improved the overall solubilization of lopinavir.This can be observed from the decrease in peak area characteristicof lopinavir, i.e., loss of drug crystallinity, after digestion ofinfant formula containing lopinavir/ritonavir mixed drugs at both1:1 and 1:4 (excess ritonavir relative to lopinavir) weight ratios3. Our fiPlopinavir = 4.56 and log Pritonavir = 5.98).33 These observations agree well with previous findings, where lopinavirwas more soluble in fed-state human intestinal fluid compared to ritonavir.34 It was also shown that both lopinavir and ritonavirpossess greater drug solubility in the fed-state human intestinalfluid compared to the fasted state, which was consistent with ourfindings, where lopinavir and ritonavir are poorly soluble in theblank samples when no lipids were present .Besides the impact of onedrug on the other, the type and amountof lipids present also plays an important role in determining theextent of drug solubilization, which could point to the potentialimpact of food on the oral bioavailability of lopinavir and ritonavir.Results from our studies suggested that while both medium chain andlong chain triglyceride emulsions enhanced the solubilization of lopinavirand ritonavir during digestion, the extent of drug solubilizationwas greater in lopinavir when compared to ritonavir in a mixed drugsystem (log S5). Additionally, our studies showed that inthe absence of lopinavir precipitation of ritonavir occurred duringdigestion in MCT emulsions  showed that an increase in the lamellarpeak area due to the formation of fatty acid-calcium soaps coincidedwith the decrease of the ritonavir peak area. This observation hintedat an interaction of ritonavir crystals with the lamellar structure,resulting in fewer drug crystals in suspension being exposed to theX-ray beam. Preferential localization of ritonavir (but not lopinavirdespite the similar densities) in the lamellar phase soaps was observedfrom the microscopy images in In particular, we demonstrated that digestion ofLCT led to greatersolubilization of ritonavir compared to MCT, which (as was expected)was further enhanced upon addition of bile salts due to micellar solubilizationinto the long chain fatty acids/bile salts mixed micelles 4 and S5.mulsions 4c. This 0.21 Å–1 S8 showed35 In another study, a reduction in the exposureof ritonavir was observed when a fatty meal was administered withthe ritonavir powder formulation.36 Therefore,effects of formulation excipients on drug solubilization should alsobe systematically assessed. Nevertheless, our studies confirmed thatsolubilization of lopinavir/ritonavir in lipid-based formulationswas affected not only by the amount and types of lipid in the formulationsbut also the presence of partner drug and the relative ratios of lopinavirto ritonavir in the mixed drug system.Finally, it should be noted that although our findings showed theimpact of digestion of lipids on solubilization of lopinavir and ritonavirin mixed drug settings (which were consistent with other BCS class2 and class 4 drugs) that may lead to improved oral bioavailability,there is a gap in the literature directly relating the postdigestionsolubilization afforded by milk-like systems with absorption whichwould need to still be clearly established as the literature is conflicting.It is however understood with confidence that a failure to providedrug in a solubilized form for such poorly soluble drugs will certainlybe limiting for bioavailability. For example, administration of lopinavir/ritonavirwith a moderate fat meal increased the exposure (AUC) of lopinavirby about 60% relative to fasting conditions when formulated as a softgelatin capsule, compared to about 27% for the lopinavir/ritonavirtablet. A similar effect was observed for ritonavir with an increasedAUC of about 15–24% following administration of the drug tablet.5in vitro solubilization of lopinavirand ritonavir in a mixed drug setting during digestion and the solubilizationof lopinavir and ritonavir were influenced by the presence of oneanother. Specifically, the solubilization of lopinavir was enhancedduring the digestion of formulations containing ritonavir, suggestingthe potential for solubilization to add to the enzymatic inhibitioneffect of ritonavir that is an accepted mechanism for boosting thebioavailability of lopinavir. The studies also showed that the digestionof MCT enhanced the solubilization of lopinavir, while for ritonavir,LCT was favored over MCT from a solubilization standpoint. The studiespresent further weight to the potential for milk-lipid-based formulationsto deliver lopinavir and ritonavir in combination to children.In this study, the effectsof ritonavir on the solubilization oflopinavir (and vice versa) during digestion of milk and infant formula,as prototypical pediatric friendly lipid formulations, were determined.Lipids enhanced the