Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children’s Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario’s newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable. The need for new methods to accurately assess gestational age in low resource settings has been identified as critical to ongoing efforts to improve global data on the burden of preterm birth5.Reliable estimates of gestational age are critical in determining population burden of preterm birth, and informing policies for resource allocation and prioritization of interventions in low resource settings. In many low- and middle-income countries, maternal access to quality antenatal care (ANC) may be limited. In particular, gestational dating ultrasound is not routinely available and thus gestational age is often estimated using less accurate methodologies such as date of last menstrual period (LMP), symphysis-fundal height or postnatal examination of the infant’s biophysical characteristicsIn addition, accurate estimates of gestational age allow for distinction between preterm infants and those who are small for gestational age (SGA). This is an important difference when allocating resources for maternal and infant healthcare and ensuring the availability of appropriate interventions. The medical needs and achievement of developmental milestones may significantly differ between preterm and SGA infants; thus, accurately identifying at-risk infants at birth is important for informing the course of their postnatal care.6. We have since developed and internally validated a second generation of models using a machine learning algorithm and have conducted external validation of model performance in newborn data from two cohorts from Zambia and Bangladesh7. The successful use of cord blood in estimating gestational age is of particular interest as we encountered barriers to heel prick sample collection in these populations. In particular, it was difficult to collect the heel prick sample in the recommended 24–72 hour window due to early hospital discharge. We also encountered parental reluctance to subject their infants to a heel prick sample collection, especially in preterm infants6.One component of our research group has developed a metabolic gestational age algorithm using biomarker data obtained from routine newborn metabolic screening in a cohort of nearly 150,000 infants born in Ontario, Canada. This approach has been previously validated in cohorts in Bangladesh and Zambia. In the Bangladeshi cohort, the model correctly estimated ultrasound-validated gestational age to within one week in the majority of infants, and within two weeks in 90–95% of infants using heel prick and cord blood metabolomic markers7, suggests potential value in using dried blood-spot-derived analytes for gestational age assessment, some key questions need to be answered before attempting to utilize this approach widely as a surveillance tool for preterm birth:While our previous work, and that of others1. Is the approach feasible for implementation at primary birthing facilities in low-resource settings?2. Does application of the approach at primary birthing facilities provide an accurate estimate of the preterm birth rate in the population?3. What is the accuracy of metabolic gestational age assessment using cord blood relative to infant heel-prick blood?4. Can the approach distinguish SGA from appropriate-for-gestational age (AGA) and large-for-gestational age (LGA) infants?5. Can the performance of the algorithm be enhanced by including additional measures, such as anterior lens vascularity assessment, Ballard scoring, and anthropometric measurements?The goal of this study is to pilot a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from a population-representative cohort in health and demographic surveillance sites in low-resource settings.If successful, this will achieve the following objectives:Primary objectives1. Assess the feasibility of large-scale implementation of metabolic gestational age screening.2. Estimate population-level burdens of preterm birth within select low-resource areas.Secondary objectives1. Estimate population-level burdens of SGA infants within low-resource settings through validation of a newly developed algorithm that simultaneously classifies infants as SGA/AGA/LGA while estimating gestational age.2. Estimate population-level burdens of treatable, rare metabolic diseases.3. Identify and treat infants at risk for these treatable life-threatening/altering metabolic diseases4. Generate a large international newborn metabolic dataset that could be leveraged for future preterm birth researchAt a population level, utilization of metabolic analysis for gestational age dating could support surveillance of the burden of preterm birth and research into the development of effective resource management strategies. We will seek to determine whether this is feasible in low-and middle- income settings.This study was approved by the Ottawa Health Sciences Network Research Ethics Board (20180330-01H), Children’s Hospital Of Eastern Ontario Research Ethics Board (18/58X), the Stanford University School of Medicine Institutional Review Board (44656), the Kenya Medical Research Institute Scientific and Ethics Review Unit (SSC 2880), the University of Zambia Biomedical Research Ethics Committee (015-06-17), the Bangladesh Institute of Child Health (BICH-ERC-01-01-2019), and the Research Council of Zimbabwe (03744).The Ottawa Hospital Research Institute (OHRI) has received funding from the Bill & Melinda Gates Foundation to cover project coordination costs in Ontario, Canada, including but not limited to sample analysis, gestational age estimation model execution and project management (OPP1184574). Stanford University received funding from the Bill & Melinda Gates Foundation to operationalize the project including site selection, protocol training, subcontracting to international sites, oversight and communication with international sites (OPP1182996).This project is led by the OHRI with services provided by Newborn Screening Ontario (NSO), in partnership with the Department of Pediatrics, Stanford University and supported by the Bill & Melinda Gates Foundation. Sample collection sites include: Mirzapur, Bangladesh led by the Child Health Research Foundation; Kisumu, Kenya led by a team from the Kenya Medical Research Institute (KEMRI) and Center for Disease Control and Prevention (US CDC) collaboration; Lusaka, Zambia led by UNC-GPZ; and Harare, Zimbabwe led by researchers from University of Zimbabwe.Investigators at Stanford University were responsible for identifying and training international partners in sample collection at facilities located in South Asia and sub-Saharan Africa. Identification of eligible site partners was based on capacity for sample collection from population representative cohorts and the ability to collect samples from both hospital and primary birthing facilities in order to evaluate whether metabolic gestational age dating approaches were valid estimates of population-level preterm birth rates.We evaluated 19 sites for inclusion in the study. Sites were deemed acceptable if they met the following specific criteria: early pregnancy registration, ultrasound capacity, ability to obtain newborn heel-prick and cord blood samples, capacity to store and ship blood spot cards and cord blood samples, ability for patient follow up and demographic surveillance, and ability for follow-up testing for screen positive results for treatable metabolic diseases. Four sites were identified that broadly met our inclusion criteria. All sites were trained on cord blood and heel-prick derived dried blood spot collection. Mizapur, Bangladesh. The Child Health Research Foundation is a demographic surveillance site (DSS) with births occurring at the Kumudini Hospital, local clinics, and at home. The DSS sites covers 374 km2, with a population of close to 300,000 people. One data collector covers approximately 400 households and visits every four months to collect demographic information. The preterm birth rate at this site is estimated to be 18–19% based on LMP. Half of the study population will be enrolled at the time of birth at the birthing center at the Kumudini Hospital, and half will be enrolled at 20 or before weeks’ gestation through the DSS to allow for early trimester ultrasound validation. Women enrolled at 20 weeks gestation will be transported to Kumudini Hospital for ultrasound examination. Heel prick samples will be collected for all infants, and cord blood samples will also be collected for infants born at Kumudini Hospital. An estimated 840 cord and 1455 heel prick samples will be collected from this site over an estimated 12-month period.Kisumu, Kenya. The Kenya research center is located in Kisumu, at the KEMRI Center for Global Health Research. Field research sites are located in Siaya county where a maternal-infant surveillance platform hosting a prospective cohort of pregnant women and their infants is implemented from two community hospitals; Siaya County Referral Hospital (SCRH) and Bondo sub-County Hospital (BSCH). The SCRH is the main referral hospital for the county region. Bondo Hospital, located 23 km south, serves as a primary birthing center and enrollment site for the community. Prior studies have estimated the preterm birth rate to be 19% by a combination of LMP and ultrasound. Participants are enrolled at their first ANC visit or by research nurses or through trained community health workers (CHWs) who administer home-based urine pregnancy testing and refer pregnant women to the study clinics for further screening and enrollment. Eligible participants at this site include pregnant women 15–49 years of age, coming from a 10 km radius of the research facility, willing to deliver in the research hospital and not planning to relocate/migrate within one year of enrollment into the surveillance program. Women are typically enrolled prior to 20 weeks’ gestation at which time they undergo ultrasound, and are offered treatment for common illnesses including malaria, urinary tract infections and sexually transmitted infections. It is expected that 10% of babies will be born at home, with infants evaluated within 72 hours. Expected enrollment is approximately 780 cord and heel samples with paired ultrasounds for all women collected over one year.Lusaka, Zambia. Building on prior work of our pilot project nested in the ZAPPS-1 study, we partnered with UNC-GPZ to implement metabolic analysis for the participants of two existing study cohorts: the Zambian Preterm Birth Prevention Study (ZAPPS-2) and Improving Pregnancy Outcomes with Progesterone (IPOP)9. This site has an estimated preterm birth rate of 15% by ultrasound10. Inclusion criteria for ZAPPS-2 and IPOP are women 18 years of age or older, residing in Lusaka with no plans to relocate. Women in the ZAPPS-2 cohort are HIV uninfected, whereas women enrolled in the IPOP study are HIV-1 positive and receiving antiretroviral therapy. HIV status and anti-retroviral therapy will be accounted for in the analysis phase. All enrollees are recruited prior to 24 weeks’ gestation in this cohort, and ultrasound occurs at the time of enrollment. Enrollment occurs over eight district clinics with delivery in the Lusaka University Hospital, creating a population representative sample for peri-urban Zambian women. The goal sample size for this site is estimated to be 600 cord and heel samples, all paired with ultrasound. Sample collection is expected to occur over one year.Harare, Zimbabwe. The Zimbabwe site consists of two primary birthing clinics and the referral hospital with a large volume of community and hospital deliveries. Most pregnancies are registered after 24 weeks of gestation. Ultrasound is not routinely available unless complications are identified or by self-pay in a private clinic. Extensive laboratory capacity exists for follow-up testing of screen positive results; however, mass spectrometry is not available. The estimated preterm birth rate is 12% based on LMP. Half of participants in the Zimbabwe cohort will be enrolled at birth from the referral hospital and half will be enrolled during their first ANC visit at primary care clinics, at which time they will undergo ultrasound, yielding a total sample size of. Participants enrolled at primary care clinics will be transferred to the referral hospital if they go into preterm labour. The target sample size for this site is approximately 1000 participants (1000 heel and 500 cord samples) and we expect sample collection to occur over nine months.11 and based on typical birth rates at each site and number of ultrasounds that could be obtained. A pragmatic sample size of n=20 was planned for the smallest subgroup in which model performance metrics were to be calculated (ie.GA <34 weeks). This ensured sufficient sample size to calculate reasonably robust summary (i.e. mean and CI) of the reported performance metrics in each planned subgroup. Determining sample size requirements for an each site was guided by Steyerburg (2010)At all sites, parental informed consent will be sought prior to enrollment in the study, and consent forms will be available in local languages. All liveborn infants will be eligible for inclusion in this study. Women will be enrolled by research nurses during the first ANC visit or at delivery (depending on site enrollment criteria). Participants will be made aware that participation is voluntary, and the risks and benefits of enrollment will be discussed. Those choosing not to participate will continue to receive ANC and treatment according to local clinical standards. Participants will be assured that all reasonable measures will be taken to protect their personal information and that of their newborn. Participants enrolled at the Bangladesh, Zambia, and Kenya sites will also consent to storage and future use of their samples for perinatal research under authorization of presiding institutional committees.Consenting parents will be informed that heel-prick collection may cause temporary discomfort to their newborn and will also be informed of the possibility that their child may be identified to be at risk of one or more treatable metabolic conditions. Participants will be informed that such incidental findings will be communicated to the study investigators and recommendations will be made to confirm diagnoses and help guide any necessary treatment of their infant. At the time of consent, participants will be informed of their right to request the full details of the screening results for their newborns.12. In brief, cord blood will be collected within 30 minutes of delivery of the placenta into an uncoated, sterile syringe. Blood from the syringe (4–5 drops) will be applied to designated filter paper within pre-printed circles. Newborn heel-prick samples will be collected ideally between 24–72 hours after birth or prior to discharge if the newborn is released from hospital within 24 hours of delivery. The newborn’s heel will be warmed at the identified skin-puncture site to promote increased blood flow. The puncture site will be cleaned and air-dried. A sterile lancet or heel incision device will be used to puncture the lateral aspect of the plantar surface of the newborn’s heel. The first small drop of blood formed will be cleaned away and the formation of a second large drop of blood will be encouraged by intermittently applying gentle pressure to the newborn’s lower leg and heel. A filter card will be applied gently against the blood drop to soak through. Each preprinted circle on the filter card will be filled by subsequently formed drops of blood. Following heel-prick sample collection, the newborn’s foot will be elevated above the body and a sterile gauze pad or cotton swab will be pressed against the puncture site until the bleeding stops. No more than 500µL of blood of each sample type (heel prick or cord) will be required for this study. To reduce newborn discomfort during the heel prick sample collection, mothers will be encouraged to hold the baby close or breastfeed the baby before and during the procedure.Study personnel will collect, handle and transport heel-prick and cord dried blood spot samples from participants according to study-specific standard operating procedures . Sample 13. Appropriate shipping standards will be communicated to the collection sites to minimize the risk of compromised sample integrity during shipping.Labels with unique site-specific de-identified participant identifiers (ID) will be affixed to each filter card at the time of collection. Samples will be air-dried for 3–4 hours or overnight after which they will be transported to a designated secure study location  and stored in a room temperature setting prior to shipping. Samples will be shipped at room temperature from the collection sites to NSO every seven days by a preferred courier service. We have previously found samples to be stable for up to two months at room temperature in climate-controlled conditionsAn electronic shipment manifest containing clinical and demographic information essential for clinical interpretation of newborn metabolic profiles will be relayed to NSO and OHRI ahead of shipping and included as a hard copy in the shipment . Upon re14. NSO is Ontario’s provincial newborn screening program, located at the Children’s Hospital of Eastern Ontario Research Institute (CHEO RI). All samples collected will be directed to NSO for laboratory analysis. NSO is equipped with sufficient personnel and laboratory resources to accommodate the inclusion of international clinical and research samples into the organization's standard workflow. The organization is currently providing newborn screening services to remote communities in other Canadian provinces/territories, and has piloted international screening services16. Each sample received will be reviewed for specimen quality and quantity. Newborn screening test calculations assume that the blood is evenly distributed within the circle and completely saturates both sides of the filter paper, and so a satisfactory newborn screening specimen will have blood fully soaked through to the back of the filter paper. Only satisfactory samples will be used for study analysis. Samples can be deemed unsatisfactory for several reasons as outlined inNSO will refer to organization and international standards to guide quality management of samplesNSO will generate Quality Reports summarizing the quality of samples received in each shipment. These reports will be sent electronically to the collection site and used to address issues of sample collection, handling and storage prior to shipment. The Report will summarize the Batch ID for the batch of samples received, specimen details and the quality of the samples, as outlined inStandard practice at NSO is to screen each sample for metabolites indicative of risk for approximately 30 treatable conditions. Full-panel analyses as per standard NSO practice will be executed on samples when sample quality is satisfactory.Quarterly Reports summarizing study progress will be generated by NSO and electronically shared with the study sites, Stanford University and OHRI. Quarterly Reports will include a summary of the analytical results collected up to the end of that quarter, and summarize the total number of samples received, sample collection data (time of collection), newborn characteristic data  and the number and distribution of samples excluded from analysis based on ‘unsatisfactory’ quality.The conditions screened as part of the NSO screening panel are rare. It is possible that an infant will be identified to be at high risk for one of these screened conditions through sample analysis. Such risk poses clinical and ethical considerations for gathering newborn screening data for research purposes. While this study involves newborn screening, this study is not being undertaken as a newborn screening initiative and is designed explicitly as a non-interventional study. 17. Based on the above considerations, three high-priority conditions have been identified for real-time reporting: congenital hypothyroidism (CH), hemoglobinopathies, and medium-chain acyl-CoA dehydrogenase deficiency (MCADD).Real time notification of incidental findings will be made for conditions that can be feasibly treated at the collection sites. Sample integrity, potential for confirmatory testing and potential for intervention were all taken into consideration when determining the feasible management of incidental findings, and our approach and rationale have been described in detail elsewhereIn brief, in the event that an infant screens positive for a priority condition, second-tier analysis of samples, including repeat confirmatory testing, CFTR mutation analyses, TBX1 and purine profile assays, will be executed as per a modified workflow based on standard NSO practice, provided sufficient sample is available from the original blood spot card. Electronically encrypted Alert Reports will be provided as soon as analysis is complete, and the screening results have been interpreted. The Alert Report will indicate the disease for which the infant is at high risk, the flagged analyte, the analyte level, and the reference ranges and thresholds for the flagged analyte. To ensure that communication of clinically relevant findings between investigators is successful, the collection site will confirm receipt of all Alert Reports within 24 hours. The report will recommend that positive screen results be communicated to the participant’s family, and that appropriate follow-up testing be conducted along with any necessary medical intervention, implemented in accordance with local treatment guidelines. The collection site will report back to the lead site with a completed Alert Report identifying confirmatory testing and medical follow-up.Upon completion of sample collection, sites will provide OHRI and Stanford with a detailed data collection form with maternal and neonatal covariates required for model validation and analysis . The datThe research team at the Ottawa Hospital Research Institute (OHRI) will lead primary data analyses for the generation of gestational age, preterm birth and SGA estimates, and all regulatory activities required at OHRI and CHEO RI, including but not limited to research contracts, data/material sharing agreements and ethics approvals. Each site will be provided with copies of their own cohort data for use in future analyses in consultation with the overall group.Model-based gestational age estimation and classification of preterm birth, SGA/AGA/LGA using clinical covariates and newborn screening metabolites. Newborn gestational age will be estimated from models derived using multivariable regression coupled with elastic net regularization and including the following covariates:1. Model 1: Birth weight, sex, multiple birth status and pairwise interactions2. Model 2: Sex, multiple birth status, newborn screening analytes and pairwise interactions3. Model 3: Birth weight, sex, multiple birth status and newborn screening analytes18.Classification of preterm birth, as well as SGA/AGA/LGA is conducted using an iterative multitask classification machine learning algorithm that simultaneously derives classification models for both preterm birth status and SGA/AGA/LGA and uses the prediction of one to inform the prediction of the other. These models include birthweight, sex, multiple birth status and newborn screening analytes as predictors, similar to Model 3 above. The model classifying preterm birth status will also use the prediction of SGA/AGA/LGA from the other model, and vice versa, improving the accuracy of both predictions, and will also employ an elastic net or lasso regularization approach similar to gestational age estimation models. Gestational age size classification (SGA/AGA/LGA) will be based on the INTERGROWTH-21 standardsModels were trained and internally validated in independent training and validation/test cohorts of infants from Ontario, Canada. These pretrained models can then be applied to the data for infants from the external cohorts to produce gestational age estimates. In order to evaluate the accuracy of gestational age estimates calculated from the models, the model estimate will be compared to the ultrasound reference gestational age for each infant, and the residual error calculated . These residuals can be squared, absolute value taken, summed and averaged to calculate different metrics including: mean square error (MSE); standard error of estimation, also known as root mean square error (RMSE); and mean absolute error (MAE), which is the average of the absolute value of the residual across all subjects (or subsets of subjects). Additionally, we will calculate the proportion of model-derived estimates that fall within ± 1 and ± 2 weeks of reference ultrasound gestational age for those samples with gestational age available. MAE will be the main performance metric we will use to evaluate model accuracy, but multiple metrics will be calculated and reported to facilitate comparisons to other models developed by our group and others. Model-derived frequency of preterm birth will be compared to the preterm birth frequency based on reference ultrasound gestational age by dichotomizing the model and reference gestational age values, where preterm is defined as gestational age <37 weeks and term is defined as gestational age ≥37 weeks.For classification models predicting preterm birth status and SGA/AGA/LGA, we will report area under the ROC curve, as well as sensitivity/specificity and positive predictive values. We will assess model calibration by constructing and visually inspecting calibration plots of and through calculation of the calibration slope and intercept for a regression of model gestational age vs. reference gestational age, and for predicted vs actual probabilities of preterm birth and SGA/AGA/LGA for classification models.Assessment of other gestational age measures. We will collect additional assessments of gestational age, including anterior lens vascularity, Ballard score, anthropometric measures, LMP and first trimester ultrasound to compare the accuracy of gestational age estimates with our algorithm.Knowledge Translation will be facilitated through the relationships between researchers, funding organization, and the communities involved in the project. Our findings will be disseminated through publication in peer-reviewed Open Access journals and presentations at academic conferences. We will promote awareness of our findings through press release within our institutions, locally and abroad. The data is collectively owned by OHRI, CHEO and Stanford. Third party de-identified data sharing is possible with the expressed written agreement of all applicable parties and with the development of the appropriate Data Sharing Agreements.6. Sample collection in Zimbabwe was planned to start in March 2020 but study initiation was delayed due to the COVID-19 global pandemic.All ethics approvals and contracts are in place between all partners. NSO began receiving samples from Zambia, Bangladesh and Kenya in April 2019 and sample collection is nearing completion at these sites. For Kenya and Bangladesh we have not observed the same hesitancy to perform heel prick blood sampling as in our previous studies19 and being born too early or too small has long-term health and economic consequences20. Accurate estimates of the population burden of preterm birth are critical to inform resource allocation and prioritize interventions for preterm birth. This project will provide critical insight into the feasibility of the large-scale implementation of metabolic gestational age screening in low resource settings and will inform the logistical requirements and feasibility of scaling up our protocol and algorithms for population surveillance of preterm birth and SGA estimates in low-resource settings.Preterm birth continues to be a leading cause of mortality in children under fiveBy comparing estimates obtained from primary birthing centers and DSS, insights will be gained into the feasibility of obtaining accurate estimates of population-level preterm birth rates through enrollment at primary birthing centers. We will also compare the accuracy of estimates of gestational age derived from cord blood samples and infant heel-prick samples, which will be important for accommodating local preferences for specimen collection method in future studies.This project will also generate a large international database of newborn screening data that could be leveraged for future preterm birth research.18. In the current cohorts, diagnostic capabilities and treatment are available at all sites. Screening cut-offs are set higher for international sites compared to normal NSO diagnostic criteria to allow for blood spot screening to have a high positive predictive value.Our protocol for screening of certain diseases will both inform on the prevalence of these conditions and identify and treat afflicted infants for potentially life-threatening/life altering conditions that would have otherwise gone undiagnosed. In our previous prospective cohort study, 61 infants were identified with congenital hypothyroidism and hemoglobinopathies in a cohort of 1661 samples from a rural community in BangladeshAt present, options for the treatment of either SGA or preterm infants remain limited in low- and middle-income countries. The inability to distinguish preterm and SGA infants due to unreliable gestational age estimation precludes different treatment strategies for these two populations. Interventions, such as Kangaroo-Mother Care, are targeted at low birth weight infants and thus likely capture both SGA and pre-term infants. Better distinction between these two populations in low-resource settings could contribute to more targeted approaches and potentially better outcomes.6 which further informs the feasibility of this approach for preterm birth classification. Coyleet al. found that the incremental annual cost of adopting the metabolic algorithm was $100,031 . This amounts to $11,542 per preterm infant correctly identified or $688 per SGA infant correctly identified. The cost of the algorithm is potentially improved when a targeted approach is used by screening infants between 2500-3600g, as infants <2500g can be correctly identified using a basic algorithm and infants >3600g are never preterm21. Ultimately, decision makers and potential funders will have to consider the cost of various interventions compared to their benefits when deciding whether to implementing metabolic screening for gestational age.We have conducted a cost-effectiveness analysis of our previous work in BangladeshFinally, this study will also inform the proper sample handling, storage and processing procedures for accurate assessment of preterm birth and newborn screening and thus could inform the feasibility for implementing newborn screening practices in low-resource settings either on site or with international partners.In summary, this protocol provides details on an important prospective cohort study to estimate gestational age in low resource settings and will provide valuable insight into the utility of newborn screening analytes in evaluating preterm birth rates in low-resource settings.No data are associated with this article. This paper presents a study protocol to validate the metabolic gestational age assessment using cord blood relative to infant heel-prick blood in low-resource settings. Current challenges for gestational age assessment were described, as well as prior steps of this new approach. This feasibility study started already, expecting a large-scale implementation of metabolic gestational age screening. If it has not started, please inform the expected date. Low-resources birth settings claim for prompt and easy-to-implement solutions with the potential to indicate neonatal risk, facing unknown or unreliable gestational age. I consider this program a possible response to such complaints.Secondary objective number 3 is unclear to me - “Identify and treat infants at risk for these treatable life-threatening/altering metabolic diseases.” During the first 48 hours of life, very early blood samples are associated with false-negative screening for diseases as congenital hypothyroidism, phenylketonuria. Newborn heel-prick samples will be collected ideally before discharge, mostly within 24 hours of delivery. How will researchers deal with this issue?How will the study conduct treatment of rare neonatal diseases screened in low-income countries? • Is the study design appropriate for the research question?Yes, I consider the study design appropriate for the primary objective. I suggest the study registration in the WHO Clinical Trials Platform. • Are sufficient details of the methods provided to allow replication by others?  In methods, details of antenatal ultrasound assessment are not clear. Ultrasound dating uses fetal size to determine gestational age based on the assumption that fetuses grow at the same rate in early pregnancy. Which fetal growth curve will be used, and who will assess fetuses with the ultrasound?Regarding SGA, AGA, and LGA assessment using algorithms, what is the reference curve for fetal growth standardized in the study?Ballard's score inter-observer error cannot be overlooked, and the exam demands health professional experience. How will the study reduce the bias of the observer's expertise?About the sample size, is there any estimate to achieve significant results? My questions and suggestions:Is the study design appropriate for the research question?YesIs the rationale for, and objectives of, the study clearly described?YesAre sufficient details of the methods provided to allow replication by others?PartlyAre the datasets clearly presented in a useable and accessible format?Not applicableReviewer Expertise:I am experienced in Maternal and Child Health, and Medical Informatics, acting on the following topics: medical informatics, scientific methodology, and women's health.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This manuscript describes the pilot testing of metabolic gestational age assessment using DBS in low-income settings. GA assessment is challenging in resource-limited settings where ultrasonography is typically unavailable and routinely based on clinical assessment; as such this manuscript addresses an important public health concern by presenting a potential option for GA assessment in low-income settings. This is a well-written manuscript and I only have the following minor comments/queries:Background:Repetition of the following paragraph: “while our previous work, and that of others, suggests potential value…widely as a surveillance took for preterm birth".Methods:Perhaps the authors could provide the target sample sizes for samples from each site - the justification/calculations for each site are not clear.Could there be standardization of language/structure of the site descriptions in terms of the site (which facilities), site’s PTB rate, timing of enrolment, eligibility/inclusion criteria, sample size of samples vs participants?“...Kumudini Hospital, and half will be enrolled at 20 weeks gestation.....to allow for first trimester ultrasound validation”at 20 weeks or at20 weeks or earlier - if the former perhaps first trimester ultrasound should be changed to early ultrasound.Were these women enrolledBangladesh“Participants enrolled at their first ANC visit....”Were women enrolled at this visit enrolled regardless of gestational age? Linked to point above “Women are typically enrolled prior to 20 weeks gestation” - what is the procedure for late presenters? Are they enrolled? If yes do they have an ultrasound assessment?KenyaSimilar to the comment above are there any GA restrictions for women enrolled at first ANC visit?Does this mean the goal sample size is estimated to be 1000 heel and cord samples?“Yielding a total sample size of approximately 1000 participants”.ZimbabweSite-specific comments:“Classification of preterm birth, as well as SGA/AGA/LGA….”Which standards will be used for classification of size for gestation age - is it an international standard like INTERGROWTH-21st or regional standards?Is the study design appropriate for the research question?YesIs the rationale for, and objectives of, the study clearly described?YesAre sufficient details of the methods provided to allow replication by others?YesAre the datasets clearly presented in a useable and accessible format?YesReviewer Expertise:perinatal epidemiology, maternal and child healthI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This is a well-written manuscript and I only have the following minor comments/queries:Background:Repetition of the following paragraph: “while our previous work, and that of others, suggests potential value…widely as a surveillance took for preterm birth".Response: Thank you for noticing the paragraph repetition, it appears to be an error during publication.Methods:Perhaps the authors could provide the target sample sizes for samples from each site - the justification/calculations for each site are not clear.Response: We have added a subsection to the methods providing further details on the sample size calculations. The estimated sample size provided for each site is the target sample size for each population. For sample size requirements for an external validation, we followed the general philosophy and guidance of Steyerburg’s Clinical Prediction Models. The estimated preterm birth rates at each site and number of ultrasounds that could reasonably be obtained were also considered. We were guided by a pragmatic target sample size of 20 observations in the smallest subgroup as this sample size is sufficient to calculate a robust summary (e.g. mean and CI) of the reported performance metrics in each subgroup of interest, for continuous GA, without requiring an unachievably large sample size. For example, if the rate of <34 weeks was 5%, this would require an overall sample size of n=400 (20/0.05) for that site.   This subsection is presented following the site selection section in the Methods.Could there be standardization of language/structure of the site descriptions in terms of the site (which facilities), site’s PTB rate, timing of enrolment, eligibility/inclusion criteria, sample size of samples vs participants?Response:e have structured the information, so it follows a similar pattern for each site – site details, estimated PTB, enrollment details, target sample size.  W  “...Kumudini Hospital, and half will be enrolled at 20 weeks gestation.....to allow for first trimester ultrasound validation”at 20 weeks or at 20 weeks or earlier - if the former perhaps first trimester ultrasound should be changed to early ultrasound.Were these women enrolled BangladeshSite-specific comments:Response:Thank you, we have edited this to say ‘enrolled at or before 20 weeks to allow for early ultrasound validation.“Participants enrolled at their first ANC visit....”Were women enrolled at this visit enrolled regardless of gestational age?Linked to point above “Women are typically enrolled prior to 20 weeks gestation” - what is the procedure for late presenters? Are they enrolled? If yes do they have an ultrasound assessment?KenyaResponse:At this site, participants are typically enrolled prior to 20 weeks. Some participants are enrolled outside of the recommended range. All participants enrolled undergo ultrasound, and the date of ultrasound will be considered during analysis.Similar to the comment above are there any GA restrictions for women enrolled at first ANC visit?ZimbabweResponse:Ultrasound enrollment target is <20 weeks, however enrollment beyond this gestational age may occur if this is necessary to achieve sample size goals. This would be accounted for in the analysis.Does this mean the goal sample size is estimated to be 1000 heel and cord samples?“Yielding a total sample size of approximately 1000 participants”.Response:We have updated this to add ‘…with 1000 heel and 500 cord samples  “Classification of preterm birth, as well as SGA/AGA/LGA….”Which standards will be used for classification of size for gestation age - is it an international standard like INTERGROWTH-21st or regional standards?Response:We will use intergrowth-21 standards for gestational age classification, we have added this to the statistical analysis section. not exceedingly rare and my concerns about how cost effective this would be to sustain after the project in LMICs where it would be most needed. Additionally I would have considered adding G6PD testing to their batteries of tests because although not treatable per say, knowing the infants status is important over their lifetime in terms of medicines they avoid and problems they watch for.I think this article is scientifically sound, well written and easy to follow. The only comments I have are not related to the soundness of the proposal but rather their comments that the metabolic diseases they are choosing to screen for are exceedingly rare - hemoglobinopathies like sickle cell disease areIs the study design appropriate for the research question?YesIs the rationale for, and objectives of, the study clearly described?YesAre sufficient details of the methods provided to allow replication by others?YesAre the datasets clearly presented in a useable and accessible format?Not applicableReviewer Expertise:NAI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Thank you for your review of our article.exceedingly should be removed from the manuscript, and we will do this. We agree with the reviewer that The definition of a rare disease varies by country . The prevalence of hemoglobinopathies are much higher in African then the rest of the world (10.74 vs. 2.73 per 1000) . We have conducted a cost effectiveness analysis  of our previous study in Bangladesh . This paper is currently under review, and we will add details to the discussion when it is published. There are a number of things to consider when considering different options for preterm birth surveillance including cost and health outcomes. Ultimately the decision about whether to undertake such an initiative will be up to policy makers and global funders. Implementation studies such as this will inform governments and global health funders into the usefulness of these initiatives. G6PDH is not on the disease panel in Ontario, which is why it was not included in this study.


Preterm birth is the leading cause of perinatal mortality and neonatal morbidity worldwide. Many factors have been associated with preterm birth, including parity. The aim of the present study was to investigate associations between parity and risk of spontaneous preterm birth.We conducted a retrospective study including live singleton births (≥22 weeks) of women with a first, second, third, fourth or fifth pregnancy in The Netherlands from 2010 through 2014. Our primary outcome was risk of spontaneous preterm birth < 37 weeks. Secondary outcomes were spontaneous preterm birth < 32 and < 28 weeks.We studied 802,119 pregnancies, including 30,237 pregnancies that ended spontaneously < 37 weeks. We identified an increased risk for spontaneous preterm birth < 37 weeks in nulliparous women  and women in their fifth pregnancy  compared to women in their second pregnancy. Similar results were seen for spontaneous preterm birth < 32 and < 28 weeks.Our data show an independent association between nulliparity and spontaneous preterm birth < 37, < 32 and < 28 weeks. Furthermore, we observed an increased risk for spontaneous preterm birth in women in their fifth pregnancy, with highest risk for preterm birth at early gestational age. Preterm birth, defined as birth before 37 weeks of gestation, is the leading cause of perinatal mortality and neonatal morbidity worldwide, mostly due to respiratory immaturity, intracranial hemorrhages and infections , 2. MorbPreterm birth is considered a syndrome that can be initiated by multiple mechanisms such as intrauterine infection and inflammation, uteroplacental ischemia and hemorrhage, uterine overdistension, cervical insufficiency, hormonal disorders, and other immunologically mediated processes . DefininThere are many maternal characteristics that have been associated with preterm birth, including demographic characteristics (i.e. low socioeconomic status), low or high body-mass index (BMI), smoking and a previous preterm birth , 7. PariThe principal aim of the present study was to investigate associations between parity and risk of spontaneous preterm birth, assessing first, second, third, fourth and fifth pregnancies, using a large population-based study.This study was based on data from the Netherlands Perinatal Registry (PERINED). This database is a population based registry that covers approximately 97% of all deliveries in The Netherlands and contains information on deliveries at ≥22 weeks of gestation and birth weight of ≥500 g. Furthermore, all admissions to the neonatology care unit are registered until 28 days after birth. The perinatal database is obtained by a validated linkage of 3 different registries: the midwifery registry (LVR1), the obstetrics registry (LVR2), and the neonatology registry (LNR) of hospital admissions of new-born infants , 14. It The data in the perinatal registry are anonymous; therefore, ethical approval was not mandatory under Dutch law. The Netherlands Perinatal Registry gave their approval for the use of their data for this study .We studied singleton first, second, third, fourth and fifth pregnancies (P0 through P4) resulting in delivery between 22 and 43 weeks of gestation in the 5-year period from 2010 through 2014. We excluded multiple pregnancies and pregnancies that were complicated by congenital abnormalities or stillbirth.Our primary outcome was risk of spontaneous preterm birth < 37 weeks of gestation per parity. Other outcome variables were spontaneous preterm birth < 32 and < 28 weeks. We performed additional analyses for the outcome late spontaneous preterm birth between 34 and 37 weeks to assess pregnancies in women that were not offered additional screening or treatment to prevent recurrent preterm birth. The PERINED registry contains data on whether a delivery started spontaneous  or iatrogenic .correction model A) including maternal age , non-White ethnicity, low socioeconomic status (SES), and, in multiparous women, a prior preterm birth. Additional analysis were performed to adjust for potentially mediating factors occurring in the pathway between the independent (parity) and dependent (spontaneous preterm birth) variables (correction model B). Correction model B included the maternal confounders as in model A and in addition artificial reproductive techniques (ART), male fetal gender, hypertension, preeclampsia and small for gestational age (SGA) < p10. All variables were extracted from PERINED, including SES which was based on the 4 digit postal code of the woman’s home address. SES was divided into low (< 25%), middle (25–75%) and high (> 75%) status.To estimate the effect of parity on spontaneous preterm birth < 37, < 32 and < 28 weeks (and between 34 and 37 weeks), we used a univariate logistic regression model and expressed the effect estimates as odds ratios (OR) and corresponding 95% confidence intervals (CI). We used multivariate logistic regression analysis to adjust for the most common known risk factors for preterm birth that were available in the national perinatal registry that we used for our study. The chosen variables were based on previous studies about risk factors for (spontaneous) preterm birth , 15, 16.In multiparous women (P1 through P4), we used the Cochran-Armitage Trend Test to test for a trend in parity on the incidence of spontaneous preterm birth < 37, < 32 and < 28 weeks (and between 34 and 37 weeks). The data were analyzed with the SAS statistical software package .n = 367,676) in P0, 36.1%  in P1, 13.1%  in P2, 3.8%  in P3 and 1.2% (n = 9453) in P4  or congenital abnormalities . The total of first, second, third, fourth and fifth pregnancies (P0 through P4) with complete follow-up data was 802,119, of which 30,237 (3.8%) were spontaneous preterm births < 37 weeks of gestation. The proportion of pregnancies per parity was 45.8% (p < .0001). The percentage of non-white ethnicity increased with higher parity, 17.3% non-White in P0 compared to 39.8% in P4 (p < .0001). Also the percentage of women with a low SES increased with higher parity, 24.9% low-SES in P0 increasing to 34.0% in P4 (p < .0001). Hypertension and preeclampsia occurred more often in nulliparous women while these rates remained relatively stable in multiparous women  had a prior preterm birth and 92% were new preterm births  as reference; the results are demonstrated in Table Both nulliparous women and women in their fifth pregnancy had the highest risk for all preterm birth outcomes. Preterm birth risk in nulliparous women slightly increased after adjusting for confounders compared to the unadjusted risk, whereas in women in their fifth pregnancy the risk slightly decreased after correcting for the same confounders Table .model A and model B in all parity groups and outcomes  and women in their fifth pregnancy  , < 32 weeks (p < .0001) and < 28 weeks (p < .0001), with increasing parity in multiparous women  was independently associated with an overall increased risk for spontaneous preterm birth compared to women in their second pregnancy (P1). We also observed an increase in incidence of spontaneous preterm birth < 37, < 32 and < 28 weeks with higher parity in multiparous women, with highest risk for spontaneous preterm birth < 28 weeks in women in their fifth pregnancy.The association between nulliparity and spontaneous preterm birth is supported by other studies , 18. OurThe conflicting results of the different studies point to the complexity of the association between possible risk factors, including parity, and spontaneous preterm birth. It also highlights the possible influence of factors that contribute to a higher risk of spontaneous preterm birth, such as ethnicity and socio-economic status. However, in the current study we found an association between high parity and spontaneous preterm birth while adjusting for established risk factors such as ethnicity and socio-economic status. This possibly points to other factors that may contribute to a higher risk of spontaneous preterm birth. One of the factors that may play a role could be a damaged cervix. The cervix plays an important role in maintaining pregnancy. It is well known that damage to the cervix, for instance by dilatation and curettage or loop excisions of the cervix for premalignant lesions, contributes to a higher risk of spontaneous preterm birth . The risThe overall risk for spontaneous preterm birth was significantly increased in nulliparous women compared to women in their second pregnancy, including the risk of birth between 34 and 37 weeks. According to the national prevention of preterm birth protocol in The Netherlands, women with a prior spontaneous preterm birth between 34 and 37 weeks are not offered additional screening or treatment  and receive similar obstetric care as women without a prior preterm birth . Also, iAlthough our results show that nulliparity and high parity is associated with an increased risk for spontaneous preterm birth, we observed remarkable differences between the association with nulliparity compared to high parity. While the risk of spontaneous preterm birth < 37, < 32 and < 28 weeks in nulliparous women is relatively similar, women in their fourth and women in their fifth pregnancy have a particularly high risk of spontaneous preterm birth occurring at early gestational age , including first, second, third, fourth and fifth pregnancies, and 30,237 spontaneous preterm births < 37 weeks of gestation.The strengths of this study include the high quality of data in the PERINED registry which covers approximately 97% of all deliveries in the Netherlands. We were able to study a large recent set of pregnancies  in our analyses. The general incidence of smoking in The Netherlands is 22.4% in the population > 18 years old, 19.2% of all women are smokers . The incPregnancies ending < 22 weeks were not included in our national database. Although we corrected for a prior preterm birth, which was available in our dataset, we did not have information on multiple occurrence nor severity of the prior preterm birth. Because no longitudinal linked obstetric database was available, pregnancies could not be related to the level of the individual woman in this study. We therefore could not identify women that were included multiple times due to multiple pregnancies between 2010 and 2014 which may have influenced our results.Our findings indicate that high parity, as well as nulliparity, is involved as a risk factor in the complex pathways that lead to spontaneous preterm birth. These results highlight the importance of the effect of parity on spontaneous preterm birth and may assist in preterm birth risk stratification and counseling.


ObjectivesThere are several factors that may affect the length and height of the infant. Maternal factors include a wide array of factors , which can affect newborn health determinants. The objective of this study was to evaluate the frequency of normal birth length and its determinants in newborns.MethodsThis retrospective cross-sectional study was carried out at the Obstetrics and Gynaecological Department of Hamdard Hospital, Karachi, Pakistan, from March 1, 2019, to August 31, 2019. The relevant data were gathered by trained data collectors with the help of a structured questionnaire designed specifically for the study after taking written informed consent from all the participants. Data analysis was performed using Statistical Package for Social Sciences Version 20. Binary logistic regression was applied to develop a risk assessment model for the study outcome.ResultsOut of 195 pregnant mothers, 57 (29.2%) had low birth weight infants. Mean age of mothers was 29.29±5.22 years, 142 (72.8%) had BMI of 25.0 or more, 102 (52.3%) had hemoglobin between 10 to 11 mg/dL, 172 (88.2%) used to take vitamin C and iron during pregnancy, 136 (69.7%) consumed extra meals during pregnancy, and only 5 (2.6%) were tobacco smokers/chewers. Hundred (51.3%) newborns had normal birth length, i.e., >48 cm. The mother's mid-arm circumference > 22 cm , consumption of extra meals during pregnancy , hemoglobin > 11 mg/dL , and adequate rest during pregnancy  were significantly associated with normal birth length of the infants, i.e., >48 cm.ConclusionsMother's mid-arm circumference > 22 cm, consumption of extra meals during pregnancy, hemoglobin > 11 mg/dL, and adequate rest during pregnancy were found to be significant predictors of normal birth length of the infants. The average normal birth length is defined as the full-term length of a newborn measuring 19-20 inches or 49-50 centimeters. However, a length of around 18.5-20.9 inches or 47-53 centimeters is also considered as normal birth length [The terms SGA and LGA refer to the lower and higher weight, height, and head circumference of the infant’s body as compared to the expected length and weight, respectively . Babies The specific growth patterns for growth realignment in infants born with SGA and LGA are still not much known. However, different studies revealed several associated factors such as the infants born with LGA have a higher potential to be obese in their later life . FurtherThere are several factors that may affect the length and height of the infant. In this way, genetics play a major role as infants are more likely to be of similar height to their parents. However, it is not always apparent and a tall adult may reveal a shorter length at birth and in the first two years of his life . Other tAnother factor includes the evaluation of mid-arm circumference. Kanawati and McLaren were the first authors who proposed the mid-arm circumference/head circumference (MAC/HC) ratio, which can be measured by using non-expensive equipment and with simple training . EvaluatAnother factor that affects the baby’s health and physical appearance is maternal rest during pregnancy. It has been suggested that due to maternal stress or less rest during pregnancy, babies are physically affected. Moreover, the development of the offspring can be affected both positively and negatively depending upon the maternal energy level . MoreoveTherefore, the aim of this study is to evaluate the frequency of normal birth length and different associated factors that affect the length and growth in newborns such as maternal BMI, mid-arm circumference, consumption of extra meals, level of hemoglobin, and adequate rest during pregnancy.This retrospective cross-sectional study was carried out at the Obstetrics and Gynaecological Department of Hamdard Hospital, Karachi, Pakistan, from March 1, 2019, to August 31, 2019. A total of 195 healthy mothers and their newborns were included in the study. Institutional Review Board of the hospital gave the ethical approval of the study. Written informed consent was taken from all of the participants prior to their inclusion in the study.The percentage frequency of the study outcome was taken as 50% for the most liberal estimate, with 95% confidence level and 7% precision, and the minimum sample size was calculated to be 196 participants.Healthy pregnant females with either singleton or multiple pregnancies with at least three antenatal checkups were included, whereas females giving birth at gestational age less than 34 weeks or above 41 weeks and six days or with a complicated pregnancy were excluded from the study. All the pregnancies were followed up to the delivery. All the relevant data were gathered by trained data collectors with the help of a structured questionnaire, and the weight and height/length of the mothers and children were also measured.Data were analyzed using Statistical Package for Social Sciences Version 20.0 . Descriptive analysis was performed by generating means and standard deviations for continuous variables, and frequencies and percentages for categorical variables. Binary logistic regression was applied to develop a risk assessment model for the study outcome while keeping the significance level at 0.05.There were a total of 195 pregnant females selected for the study. Frequency of low birth weight infants was found to be 57 (29.2%) in these women. The mean age of the mothers was 29.29±5.22 years; 142 (72.8%) of them had BMI of 25.0 or more, 102 (52.3%) had hemoglobin between 10 to 11 mg/dL, 172 (88.2%) used to take each of vitamin C and iron during pregnancy, 136 (69.7%) consumed extra meals during pregnancy, and only 5 (2.6%) were tobacco smokers/chewers (Table Hundred (51.3%) of the newborns had normal birth length, i.e., >48 cm.The study results further showed that mid-arm circumference > 22 cm , consumption of extra meals during pregnancy , hemoglobin > 11 mg/dL , and adequate rest during pregnancy  were significantly associated with normal birth length of the children, i.e., > 48 cm, whereas mothers who had mid-arm circumference > 22 cm, consumed extra meals during pregnancy, had hemoglobin >11 mg/dL, or took adequate rest during pregnancy had significantly higher odds of having a child with normal birth length than those who did not . The study concluded that the infants of overweight mothers were reported to have greater body fat mass as compared with the infants of lean mothers, which suggests that maternal obesity might be a predisposing factor for fetal metabolism to favor fat storage . In contA study determined to find out the possible reasons for mothers affecting newborns’ anthropometric measurements reported that a substantial association was observed between maternal anthropometry and neonatal anthropometry. Maternal height, birth order, BMI, eating extra meals, taking adequate rest during pregnancy, maternal hemoglobin, and mid-arm circumference were all found to be significantly linked to newborn’s birth weight. Likewise, a positive history of iron or multivitamin intake, folic acid, and vitamin C, and negative history of smoking were seen to have positive effects on newborn’s birth length as well as overall health . SimilarIn addition to the aforementioned maternal factors affecting birth length of newborns, studies have reported that maternal blood pressure throughout pregnancy, hypertension, coronary or any other cardiovascular disease status, and insulin resistance in diabetic mothers also tend to have substantial effects on the infants’ health . GeneticLimitationsA small sample size and non-probability sampling method are acknowledged to be the prime limitations of the study.Mid-arm circumference > 22 cm, consumption of extra meals, hemoglobin > 11 mg/dL, and adequate rest during pregnancy were found to be significant predictors of normal birth length of the children. Careful evaluation of the factors that need assessment during antenatal visits is recommended in order to have a better chance of having newborns with normal birth length.


Cytokines are mediators of inflammation that contribute to a low-grade inflammation in different disorders like major depression and obesity. It still remains unclear which psychological and medical factors interact with cytokine regulation. In the current investigation, the association between levels of pro-and anti-inflammatory cytokines and anthropometrics, mood state (depressiveness), physical activity and sleep were investigated in a sample of community-dwelled adults.via physical examination, depressiveness was assessed via Beck Depression Inventory (BDI)2, parameters of physical activity  and sleep  were measured via a 1-week actigraphy.Forty-nine subjects met the inclusion criteria for analyses and were assessed at two time-points (baseline (T1) and follow-up (T2), average T1-T2-interval = 215 days). Serum cytokine measures included the pro-inflammatory cytokines interleukin (IL)-2, IL-12, IFN-γ and TNF-α, the anti-inflammatory cytokines IL-4, IL-5, IL-10 and IL-13 and the granulocyte-macrophage colony-stimulating factor (GM-CSF); anthropometrics were assessed Correlation analyses showed low-to moderate significant relationships between the majority of cytokines and the BDI2 at T1, positive correlation with weight and BMI at T1 and T2, and negative correlations with the number of steps and METs at T2 and T2. Regression analyses for T1 revealed that the BDI2 score was the best positive predictor for the concentrations of all nine cytokines, followed by the number of steps and the nightsleep duration as negative predictors. At T2, the amount of steps was found to be negatively associated with IL-4, IL5, IL-10, GM-CSF, IFN-γ, and TNF-α, whereas the BMI could significantly predict IL-12 and IL-13. The BDI2-score was not significantly associated with any of the cytokines. No associations could be found between dynamics in cytokines from T1 and T2 and changes in any of the variables.The present results indicate an influence of physical activity, subjective well-being and body composition on inflammatory mediators. Since there was no standardized intervention targeting the independent variables between T1 and T2, no assumptions on causality can be drawn from the association results. Cytokines are a category of heterogeneous peptides produced by various cells, such as macrophages, T lymphocytes, B lymphocytes and mast cells, which are critically involved in cell signaling and immune response. Previously, it could be demonstrated that both, subjects suffering from major depression and subjects with obesity show elevations in their cytokine profiles –5. This Although a lot of research has been performed to shed light on the multilateral facets of cytokines, and meta-analyses confirm certain assumptions , theTo shed light on different factors that may be related to cytokine regulation, the associations between nine different pro- and anti-inflammatory cytokines and anthropometrics, mood states (depressiveness), physical activity, energy expenditure and parameters of sleep were examined in a sample of community-dwelled adults at two different time points. We further aimed to investigate if dynamics in these parameters between the two measurements were associated with changes in cytokine levels.For the present study, data were used from the OBDEP sub-project , which was conducted at the Department of Psychiatry and Psychotherapy of the University Hospital Leipzig within the framework of the Integrated Research and Treatment Center for Adiposity Diseases Leipzig (IFB Adiposity). The study was approved by the Leipzig University Ethics Committee (#015–10–18012009). All participants were aged 18 to 70 years and gave written informed consent. The OBDEP project comprised of two assessment points (baseline and follow-up), in which participants were requested to fill out questionnaires related to mood and diet  , 24, to via announcements [details on the recruitment and pre-screening process can be found elsewhere  by qualified healthcare professionals. Weight [kg] was determined in underwear and without shoes using a digital scale calibrated and standardized using a weight of known mass. Height [cm] was recorded using a stadiometer with participants standing on a flat surface at a right angle to the vertical board of the stadiometer. BMI  or sleep [yes/no]. Furthermore, amount of steps and MET levels are given for each 1-min timeframe. Several studies have demonstrated that the SWA provides accurate estimates of energy expenditure during rest and daily life activities, comparable to the gold standards of indirect calorimetry and doubly labeled water (On both occasions (baseline and follow-up), a 1-week actigraphy recording was performed, using the SenseWeared water –33.steps (=sum of steps per 1 min-segment) and METs  were calculated. Afterwards daily values of these four measures were averaged to obtain mean values for the total week. Datasets were only included in the analysis if the averaged values comprised of at least 4 NSI/DTI-cycles, respectively, with at least one NSI/DTI-cycle during the weekend.Scored data were entered into a customized Excel-Template for further data preparation. Participants had kept a sleep and activity diary throughout the recording period and according to the respective information provided by the participants, nightsleep intervals (NSI) was estimated (ranging from first minute to last minute scored as laying down in close proximity to the noted bed times within the sleep diary). Accordingly, the daytime interval (DTI) was determined as duration between two consecutive NSI. Sleep duration (SD) was calculated for each NSI and each DTI (=sum of minutes scored as sleep within the NSI or DTI). Total sleep duration (TSD) was calculated by adding night sleep duration within one NSI (e.g. nightsleep from Friday to Saturday) with daytime sleep duration of the following DTI (e.g. daysleep on Saturday). In addition, for each DTI, the variables The Kolmogorov-Smirnov (K-S) test was used to examine whether the cytokine levels were normally distributed or not. Therefore, in a first step, outliers cases (± 2 standard deviations) were detected and removed from the respective analysis. Since most outliers (e.g. 9 out of 10 outliers at T2) could be attributed to two specific participants, these two participants were post-hoc excluded from all analyses. After outlier removal, the K-S test still attested for non-Gaussian distribution, therefore cytokine values were normalized using a square root (SQR) or logarithmic (LN) transformation. Based on K-S results, the best transformation was determined for each cytokine level .The association between cytokine levels (response variables) and anthropometric, psychometric and actigraphic parameters (independent variables) were tested using multiple linear regression (MLR) models. The initial MLR models included all independent variables. A stepwise backwards linear regression method was used: the variables which contributed least to the aforementioned model had been removed in subsequent steps until only statistically significant variables remained (p < 0.05). In order to assess multicollinearity of the independent variables, tolerance statistics like the variance inflating factor were also calculated.Changes between baseline (T1) and follow-up (T2) were quantified by calculation difference scores (Δ=T2-T1). The K-S test showed a Gaussian distribution in all cytokine change scores but Δ IL-5. This non-Gaussian distribution could be attributed to one outlier case which was therefore excluded from the respective MLR analysis.For correlation analyses of cytokine levels and independent variables, Spearman rank correlation coefficients were calculated, since most independent variables also exhibited a non-Gaussian distribution. Therefore, non-transformed cytokine levels were used for all correlation analyses. For similar reasons, differences between T1 and T2 values were tested using the Wilcoxon test. All analyses were conducted by using the statistical software SPSS 23 ). Also, the significance level was taken to be α=0.05 (two-tailed).Forty-nine participants were included in the final analyses in this study , mean age 41.64 years . On average, the follow-up assessment (T2) of the included participants was performed 215.76 days  after their baseline assessment (T1).Results concerning the anthropometrics , psychometric test (BDI2 score), and actigraphy results  measured at T1 and T2 are depicted in Correlations between cytokine levels and BMI, BDI2 score and actigraphy parameters at T1 are depicted in Correlations between cytokine levels and BMI, BDI2 score and actigraphy parameters at T2 are depicted in When changes in cytokine levels between T1 and T2 were correlated with changes in the independent variables see Table 2CT1 = 0.954, rhoT2 = 0.950, rhoΔ=0.961; night/total sleep duration: rhoT1 = 0.934, rhoT2 = 0.908, rhoΔ=0.899; steps/METs: rhoT1 = 0.861, rhoT2 = 0.821, rhoΔ=0.659). To avoid multicollinearity, only 4 independent variables  were included in the initial MLR models.The relationship between cytokine levels and anthropometric, psychometric and actigraphic parameters (independent variables) were tested using multiple linear regression (MLR) models. As expected, several of the independent variables highly correlated  are summarized in Results of the  MLR models for cytokine levels at T2 are presented in MLR models for changes in cytokine levels (T2–T1) are presented in In this investigation, we examined the impact of the four factors BMI, depressiveness, physical activity, and sleep duration on the serum levels of nine different pro- and anti-inflammatory cytokines in a sample of 49 community-dwelled subjects at two different time points. Further, we investigated if dynamics in any of the variables between the two time points were accountable for changes in cytokine levels.Regarding the correlation analyses, the majority of cytokines were found to weakly correlate with the BMI and weight in a positive direction at both time points. The number of steps and METs correlated in a negative direction at both T1 and T2. The results for the BDI2, however, were inconsistent with significant weak correlations at T1 which were absent at T2. In the regression analyses, the physical activity could explain IL-2, IL-10, and TNF-α at T1 and was negatively involved in all cytokines except IL-12 and IL-13 at T2. On the other hand, the mood state assessed with the BDI2 showed a disparity between the two cross-sectional time points, as the significant positive association with all cytokines at T1 could not be repeated for any of the cytokines in the follow-up assessment. For all analyses, the direction of the association of the parameters did not depend upon the pro-or anti-inflammatory characteristics of the cytokines. Concerning changes in any of the four factors included into the analyses, none was found associated with dynamics in cytokines from T1 and T2.the analyses on of the baseline assessment of the same study sample , Germany, FKZ: 01EO1001. This study was supported by the Integrated Research and Treatment Centre for Adiposity Diseases (IFB), University of Leipzig which is funded by the Federal Ministry of Education and Research . The authors acknowledge support from the German Research Foundation (DFG) and Universität Leipzig within the program of Open Access Publishing. HH has received salary support from the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) and King’s College London. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Special Issue ‘Insect physical control: electric field-based pest management approach’ was launched to showcase valuable new research on pest control using applied electrostatic engineering. Some phenomena generated in static and dynamic electric fields can be used to build new devices to capture or kill target insects using an attractive force or a force striking insects entering an electric field. This research field is new, and there are few researchers currently working within it. Consequently, this editorial introduces the history and general principles of electric field generation. I then discuss future directions for this field. A conductor can be electrified by connecting it to a grounded negative- or positive-voltage generator. A voltage generator is used to increase the initial voltage to achieve the desired voltage using a transformer (coil) and a Cockcroft circuit integrated into an electric circuit in the voltage generator. The difference between negative- and positive-voltage generators is that the Cockcroft circuit is set so that negative electricity  moves in the reverse direction. A negative-voltage generator draws free electrons from the ground  and supplies electrons to the conducting wire. A negative charge accumulates on the surface of the conductor. With an insulated conductor, negative charges on the conductor induce dielectric polarisation of the insulated coating of the conductor, negatively electrifying the outer surface of the insulator. A positive-voltage generator pushes free electrons to ground (an infinite sink of electrons) to positively charge the conductor (positive electrification). The surface of the conductor becomes positively charged due to electrostatic induction. In an insulated conductor, positive electrification of the conductor causes the insulating coating to become positively charged as a result of dielectric polarisation.A dynamic electric field causes the discharge of charged conductors. Factors related to the discharge of substances include the (1) voltage applied, (2) distance between poles, (3) potential difference between the two poles, (4) capacitance of the recipient receiving electricity, (5) air conductivity, and (6) volume resistivity of the insulator used for coverage. Of these factors, if an earthed conductor is one of the poles, discharge occurs more readily, as the earth receives electricity without any restriction. Assuming air is the medium, the volume of the conductive substances involved affects the insulation resistance of the air . A major factor is the vapour concentration in the air . The conductivity of the air increases with the vapour concentration, and an electric current is generated more easily in air under these conditions. Discharge is defined as electric current generation between opposite poles as a result of the dielectric breakdown of gases in the electric field by the potential difference between the poles. In a positively charged conductor, a corona discharge can change from a glow discharge (corona discharge surrounding the tip) to a streamer discharge via a brush-like discharge by increasing the applied voltage or decreasing the distance between the poles. The discharge finally breaks down into an arc discharge between the two poles. If the conductor is negatively charged, the corona is induced at lower voltages than at a positive needle pole. Although a glow corona with a short streamer discharge is generated, it does not grow and is followed by a complete breakdown in the form of an arc discharge. The strong force of a high-voltage-mediated arc discharge can dismember pests that enter an electric field.The electric field screen, first introduced in 2006, is an air-shielding apparatus based on the principles and techniques of applied electrostatic engineering . InitialThe two types of electric field screen used for insect capture were first reported in 2008  and 2011Dynamic electric fields also have potential for novel physical measures to control insect pests. Two works ,26 have Escherichia coli O-157, over postharvest crops within facilities in the food supply chain. This requires replacing the heavy metal wires passed through an insulator tube with light materials to reduce the weight of the screen. Coating the inner surface of the insulator tube with a conductive paste is a potential alternative. The use of water in an insulative tube for the screen is another possible alternative, given its high conductivity. Interestingly, various water-soluble colourings can render the screen luminous, which may be useful for analysing insect photo-selectivity. A combination of insulated and uninsulated conductive fibres could be woven into the plastic sheet of an electric field screen. These are only several possible electric field-based pest control measures. Hopefully, this editorial leads to valuable research in this new field.Future research may cover many topics. One is the installation of electric field screens on unmanned aerial vehicles for remote-controlled insect monitoring, especially flies transmitting human pathogens, like


Every year an estimated 7.9 million babies are born with birth defect. Of these babies, more than 3 million die and 3.2 million have disability. Improving nationwide information on prevalence of birth defect, risk factor and consequence is required for better resource allocation for prevention, management and rehabilitation. In this study, we assess the prevalence of birth defect, associated risk factors and consequences in Nepal.This is a prospective cohort study conducted in 12 hospitals of Nepal for 18 months. All the women who delivered in the hospitals during the study period was enrolled. Independent researchers collected data on the social and demographic information using semi-structured questionnaire at the time of discharge and clinical events and birth outcome information from the clinical case note. Data were analyzed on the prevalence and type of birth defect. Logistic regression was done to assess the risk factor and consequences for birth defect.Among the total 87,242 livebirths, the prevalence of birth defects was found to be 5.8 per 1000 live births. The commonly occurring birth defects were anencephaly (3.95%), cleft lip (2.77%), cleft lip and palate (6.13%), clubfeet (3.95%), eye abnormalities (3.95%) and meningomyelocele (3.36%). The odds of birth defect was higher among mothers with age < 20 years (adjusted Odds ratio (aOR) 1.64; 95% CI, 1.18–2.28) and disadvantaged ethnicity . The odds of birth asphyxia was twice fold higher among babies with birth defect  in reference with babies without birth defect. The odds of neonatal infection was twice fold higher among babies with birth defect  in reference with babies without birth defect. Babies with birth defect had three-fold risk of pre-discharge mortality .Maternal age younger than 20 years and advantaged ethnicity were risk factors of birth defects. Babies with birth defect have high risk for birth asphyxia, neonatal infection and pre-discharge mortality at birth. Further evaluation on the care provided to babies who have birth defect is warranted.Swedish Research Council (VR). Birth defects are anomalies in morphogenesis during early foetal life resulting in structural, behavioural, functional and metabolic disorders that can be detected prenatally, at birth or later in infancy . GloballSouth-East Asia has higher prevalence of cleft lip and palate , whereasTo the best of the present evidence, therapy, medication, surgery, or assistive technology are different services available for management of birth defects and in most cases essential paediatric surgery can avert early mortality and long-term disability . The HumIn LMICs, lack of diagnostic and national screening programmes has led to paucity of nationally representative data, a major hurdle for in-depth understanding of the epidemiology . In NepaA prospective cohort study was conducted in 12 public hospitals across Nepal to evaluate the efficacy of scale up of Helping Babies Breathe Quality Improvement Project from 1 July 2017 to 17 October 2018 [All babies born in the 12 hospitals during the study period were selected for this study. Structural birth defect  categorized as birth defect in the hospital registry was included as birth defect. Stillborn babies, out-born babies and babies whose mothers did not consent or avail themselves were excluded from the study.In the selected hospitals, a data surveillance system, including data collectors and data coordinators, was setup for collection of data on the mothers and newborns. Obstetric data were collected through patient files and maternity register in the maternity wards using a data retrieval form. Socio-demographic data were collected through face-to-face interviews with mothers before discharge. Semi-structured interviews were conducted. Data coordinator assess the completed forms for completeness, which are then indexed, sealed and sent to the head office for further action. In the central office, the data management team, led by a data manager, sort, index, file and reassess for completeness. Data entry operators enter the indexed forms based on the hospitals in Census and Survey Processing System (CSPro). The entered data are cleaned and exported to Statistical Package for the Social Sciences (SPSS) for further data analysis.Liveborn babies with birth defects were the variable of interest for this study. Demographic variables included age of mother , ethnicity , education (literate and illiterate) type of fuel used for cooking in household (clean or polluted) and smoking habit. Antenatal variables included antenatal care (ANC) check-up by doctor/nurse and timing of first ANC visit , parity of mothers  and severe anemia during pregnancy (7.5 mg/dl). Intrapartum variables included multiple deliveries and sex of the baby. Low birth weight was defined as birth weight less than 2500 g. Birth asphyxia was defined as apgar score less than 7 at 1 min. Neonatal infection was defined as clinical signs of infections at admission to sick newborn care units. Pre-discharge mortality included deaths of newborn with birth defects before discharge.p< 0.05. All variables with p< 0.2 in the univariate analysis were considered for multi-variable logistic regression analysis.Prevalence of birth defects was calculated based on the total number of congenital cases reported and total number of live births in the same period. Cross-tabulation was done for socio-demographic, obstetric and neonatal characteristics. Binary logistic regression was performed to analyze the level of association between the characteristics and birth defects. The significance was determined at All mothers were consented in written before the start of the data collection and confidentiality was maintained. Ethical approval was received from Ethical Review Board of Nepal Health Research Council (reference number 26–2017).Out of the total 104,223 admissions, a total of 87,989 deliveries were conducted during the study period of which 87,242 deliveries were live births and 747 deliveries were stillbirths. Among them, there were 506 reported cases of birth defects . Women with one previous birth (p=0.002) and two or more birth (< 0.001) were significantly associated with birth defects. Multiple delivery was significantly associated with birth defects (p=0.02).  with birth defects. Female child was significantly associated with birth defects  to be associated with birth defects compared to mothers 20-< 35 years of age. Mothers of ethnicity other than Brahmin/Chhetri were 1.78 times more likely  to have babies with birth defects. Female child had 1.35-fold risk  of having birth defects compared to male child. Compared to women with no previous birth, the risk of birth defect was higher among women with 1 previous birth  and women with 2 or more previous birth . Also, mothers with multiple deliveries had 1.8-fold risk of having babies with birth defect compared to mothers with single deliveries .  in reference with babies without birth defect. Babies with birth defect have 1.82-fold risk of neonatal infection . The risk of pre-discharge mortality for babies with birth defects was 3.31 folds  higher compared to babies without any birth defects  among newborn babies in the same way as reported elsewhere. Various socio-demographic factors like adolescent age and disadvantaged ethnic group are associated with birth defect. Obstetric factors like being female child and number of previous birth are associated with birth defect. Babies with birth defect have high risk for birth asphyxia, neonatal infection and pre-discharge mortality at birth. There is a need to evaluate the services available for babies with birth defect for better identification and management of these babies. Birth defects are major causes of neonatal mortality and morbidity, and national surveillance is very important.


In this paper, we investigated the effect of strong electric fields on material responses and the Bloch oscillation resonance in high field conductivities. For this purpose, a high-order accurate explicit modal discontinuous Galerkin (DG) solver is employed for solving the quantum Boltzmann transport equation (BTE) in the context of electron transport at nanoscales under strongly out-of-equilibrium conditions. Here, we study the transient behavior and the convergence of a steady-state response to an external oscillating electric field switched on at time zero. We first benchmark our numerical results with known analytic steady-state responses at low fields. The computational results show that the present DG scheme is in excellent agreement with analytic solutions over the whole range of parameters and to an extremely high precision, allowing us to achieve good agreement even for the fifth-order response at low fields. We then extend the method to strong electric fields and show how the responses are deviated from the low-field ones and the transition to a dampened Bloch oscillation regime. Most importantly, we report the observation of a new regime induced by the resonance between the standard low-field response and Bloch oscillations. Transport phenomena in solids are the focus of an extremely wide range of research topics. The transport of quasi-particles  in nanotechnology, plasmonics, quantum computer technology, and microelectromechanical systems (MEMS) is of great importance due to their tremendous technological and scientific applications ,2,3. TraThe quantum Boltzmann equation has been widely proven to have the power and flexibility to describe a very wide range of dynamics of quasi-particle excitations in solids. It allows researchers to describe transport and thermalization even in heterogeneous systems. However, its application has been limited to approximated cases. The most famous is the calculation of conductivities in uniform systems, as a perturbation of the equilibrium state. However, when solved far from equilibrium, the Boltzmann equation becomes quickly numerically challenging. Here, we apply a relatively new numerical approach, discontinuous Galerkin, to the Boltzmann equation. Such method has been shown to have a number of technical and numerical advantages, such as hp-adaptivity, conservative, stable, robust with strong mathematical supports, weak approximation of boundary conditions, and built-in parallelism which permits coarse-grain parallelization ,16,17,18Finally, we use the method to highlight the evolution of the responses as the system moves further from equilibrium. We show how the material response can be analyzed in terms of conductivity and nonlinear conductivities even in the presence of increasing electric fields. We show how the responses are altered further from equilibrium. The key finding is that a clear electric field amplitude-dependent resonance appears in the conductivity and nonlinear conductivities. We identify its origin as arising from the resonance between a more standard low-field driven response and dampened Bloch oscillations.e is the absolute value of electron charge, ℏ is the reduced Planck constant, The time evolution of quasi-particle excitations in materials is described by a distribution function on (BTE) ,20,1)∂∂feglected . Here, eIn the present study, we want to (a) benchmark the numerical method for physically relevant observables and (b) observe the behaviour of the system as it is driven progressively further and further from equilibrium. For this purpose, we address only the one-dimensional BTE in the absence of magnetic field, i.e., In the present work, we are concerned with testing the capability of the numerical technique to produce accurate predictions for transport properties and investigate the effect of strongly out-of-equilibrium configurations on transport. To be able to have analytical benchmarks close to equilibrium, we adopt a simple collisional model: the so-called relaxation time approximation (RTA) for the collisional operator which is defined asT the absolute temperature, and Here, In the present study, the electric field For the numerical simulations, we consider a simple tight-binding dispersion relation, N uniform and nonoverlapping elements as follows:In order to discretize Equation , the doml in element l and is given by The grid is defined by Equation  is appro the BTE  is multiEquation  for fh,ion n·F≡Here, the superscripts (+) and (−) respectively denote the inside and outside of an elemental interface.Several numerical techniques—such as Newton-Cotes, Monte Carlo, trapezoidal, quadrature, etc.—are available in literature ,23 to coaccuracy ,15.By assembling all of the elemental contributions together, the semi-discrete DG formulation for the BTE system  yields aHere, stepping . The expstepping  is emplorelation :Δt≤CFL for the electric field; one over nanometer Flow parameters—the electric field, the inverse temperature, and the chemical potential—play a critical role in ultrafast nonequilibrium electron dynamics. Therefore, we conducted a detailed investigation into the effects of these Flow parameters on BTE dynamics. To demonstrate the effects of the electric field on BTE dynamics, four different electric field values, At a low electric field As the electric field value increases to When the electric field value increases to To analyze the effects of the inverse temperature Interestingly, one can clearly distinguish the transition between two regimes. At very high temperature, the steady-state distribution shape is strongly smoothened due to the temperature. On the other hand, at very low temperature, the steady-state solution becomes completely dominated by the electric field: as can be observed in Further, we show the results for several positions of the chemical potential for a strong electric field. Here, we analyze in more detail the effect of high electric fields onto the material responses, focusing on the effect on the induced current. We first focus on the transient behavior. At a small electric field We now address the steady-state response, which is reached after the transient response. It can be observed that there are significant differences in time evolution of the current density with increasing electric field value. The first evident effect is the appearance of response at higher harmonics. This is expected even in the small perturbation regime, since the responses of the system at higher harmonics are proportional to higher powers of the field amplitude, and become more and more relevant at higher fields. However, there is a further effect playing an important role: the proportionality constants of the lower harmonics (conductivity) are importantly altered in high fields.At low frequencies, the conductivity decreases see a as it eThe most interesting regime is between the abovementioned ones. It is easier to understand the physics behind this regime by first analyzing the dynamics of an electron in a static electric field. As an electron is accelerated across the Brillouin zone due to a static electric field, its velocity changes in time, generating a time-dependent contribution to the current which oscillates with a Bloch oscillation periodThe effect appears in the higher-order conductivities as well, but it can be observed to be triggered at lower external field’s frequencies. This is indeed understandable since, as mentioned, the Bloch oscillation frequency is dependent only on the amplitude of the external field and always gives a response at that frequency. When the electric field’s frequency is one third of the Bloch oscillation frequency, the third-order response in the current happens to be exactly resonant with the Bloch oscillations, giving the peak observed in As a further comment, let us highlight that in the higher-order responses, if the electric field is small, the overall high-frequency component of the current becomes too small and the computed response simply shows the numerical error.Finally, we analyze how the high-field conductivity depends on the other parameters of the system. The dependence on the chemical potential in This study focused on an investigation of the strong electric field’s effect on material responses and the Bloch oscillation resonance in high-field conductivities. For this purpose, a high-order accurate explicit modal discontinuous Galerkin is applied to study the transport quantum Boltzmann equation far from equilibrium. We first focused on the analysis of performance of the presented method by testing its precision to close-to-equilibrium conditions. We have compared the method to analytic results for the low-field steady-state regime and showed that it achieves extremely high precision, even if the method is devised for strong excitations and not optimized for extremely small deviations from equilibrium. Secondly, we have performed an extensive range of numerical simulations to investigate the effects of strong electric fields, and the dependence of the response on a range of physical parameters. In particular, we have shown how corrections to conductivity arise at high fields. This allowed us to identify a new regime, appearing at high electric fields, triggered by the resonance of typical material responses and dampened Bloch oscillations. Experimental confirmation of the appearance of such resonance requires the choice of a material with a relatively long scattering lifetime  in order to allow the effect to be present at not too high frequencies where different contributions to conductivity start playing important roles.