Daphnia has long been a model of energy allocation studies due to its important position in the trophic cascade of freshwater ecosystems. However, the loci for controlling energy allocation between life history traits still remain unknown. Here, we report CRISPR/Cas-mediated target mutagenesis of DNA methyltransferase 3.1 (DNMT3.1) that is upregulated in response to caloric restriction in Daphnia magna. The resulting biallelic mutant is viable and did not show any change in growth rate, reproduction, and longevity under nutrient rich conditions. In contrast, under starved conditions, the growth rate of this DNMT3.1 mutant was increased but its reproduction was reciprocally reduced compared to the wild type when the growth and reproduction activities competed during a period from instar 4 to 8. The life span of this mutant was significantly shorter than that of the wild type. We also compared transcriptomes between DNMT3.1 mutant and wild type under nutrient-rich and starved conditions. Consistent with the DNMT3.1 mutant phenotypes, the starved condition led to changes in the transcriptomes of the mutant including differential expression of vitellogenin genes. In addition, we found upregulation of the I am not dead yet (INDY) ortholog, which has been known to shorten the life span in Drosophila, explaining the shorter life span of the DNMT3.1 mutant. These results establish DNMT3.1 as a key regulator for life span and energy allocation between growth and reproduction during caloric restriction. Our findings reveal how energy allocation is implemented by selective expression of a DNMT3 ortholog that is widely distributed among animals. We also infer a previously unidentified adaptation of Daphnia that invests more energy for reproduction than growth under starved conditions.The cladoceran crustacean  Major life history traits are growth trajectories (size from the time of birth through life), age and size at maturity, age- and size-specific mortality patterns, age- and size-specific fecundity patterns5. Those traits are known to be negatively related to each other and these antagonistic relationships are called trade-offs13. Evolutionary ecologists have studied how an organism allocates the limited energy resources among competing traits16. Based on energy utilization at an individual level, a theory called the Dynamic Energy budget, which can predict population dynamics, has been proposed17. In addition to those studies at the individual and population levels, genes affecting life history traits have been investigated in model organisms including Drosophila melanogaster, which led to the identification of genetic factors controlling lifespan and fecundity such as Insulin-like receptor19, Forkhead box O (Foxo)20, and I am not dead yet (Indy)21.A life history trait is a major factor in determining Darwinian fitnessDaphnia magna has long been used for studies of energy allocation. It occupies an important position in the trophic network of freshwater ecosystems, linking producers and secondary consumers. It can be easily propagated as a clone individual with a short life cycle by parthenogenetic reproduction. In addition, it can be easily manipulated both in a field and laboratory. Energy allocation of Daphnia fed with various amounts of algae has been investigated in order to develop a model of the interaction between the algae and D. magna populations25. Under caloric restriction conditions, daphnids use less energy for growth and reproduction and more for maintenance (respiration and carapace formation)25. Recently the D. magna genome has been sequenced27 and Crispr/Cas-based genome editing technology has been established to introduce indel mutations at the targeted locus29. However, these genetic tools have not yet been used to analyze genes involved in energy allocation.The cladoceran crustacean 30. There are at least 3 functional orthologs, DNMT1, DNMT3A, and DNMT3B. DNMT1 maintains DNA methylation patterns after DNA replication, while DNMT3A and DNMT3B establish new methylation by using unmethylated DNA as their templates30. De novo methylation by the DNMT3 family is necessary for spatio-temporal gene expression guiding cell differentiation and organogenesis in mouse embryos32. It is also required for phenotypic changes in response to environmental stimuli35. In mice, homozygous mutants of DNMT3A resulted in multiple organ defects and lethality several weeks after birth36. Disruption of DNMT3B led to embryonic lethality36. DNMT3 orthologs harboring the mammalian DNMT3A/B-like domain structure are widely distributed in the animal kingdom37. In contrast to vertebrate genomes in which more than 80% of CpG dinucleotides are methylated, invertebrate genomes are sparsely methylated39. Functional analyses of DNMT3 have been performed only in two social insects by RNA interference41, but both knockdown experiments did not lead to embryonic lethal phenotypes. However, in the honeybee (Apis mellifera), silencing of DNMT3 altered the developmental fate of workers-destined larvae towards queen-like traits33.DNA (cytosine-5) methyltransferases  are the enzymes that catalyze the DNA methylation and generate 5-methylcytosines (5mCs) to regulate gene expressionD. magna has the two DNMT3 orthologs42, DapmaDNMT3a.1 (Dapma7bEVm011900t1) and DapmaDNMT3a.2 (Dapma7bEVm006722t1). DapmaDNMT3a.1 lacks the PWWP domain and DapmaDNMT3a.2 has the diverged methyltransferase (MTase) domain43. Because both of the domains are essential for DNMT3A function, we had renamed DapmaDNMT3a.2 and DapmaDNMT3a.1 as DNMT3.1 and DNMT3.243, respectively. Previously, we had found upregulation of DNMT3.1 expression in response to starvation43, suggesting that DNMT3.1 may play an important role under caloric restriction. To further investigate the functions of DNMT3.1 under this condition, we silenced DNMT3.1 by CRISPR/Cas-mediated mutagenesis. Phenotypic analyses of this biallelic mutant demonstrated that DNMT3.1 controls life span and the trade-off between reproduction and growth only when reproduction and growth compete.DNMT3.1 in D. manga, we attempted to mutate this gene using the CRISPR/Cas system. As with the DNMT3L in mammals, DNMT3.1 lacks five out of six characteristic motifs of the MTase domain in catalytically active DNMT3 proteins except motif VI  comprising the purified Cas9 proteins and targeting gRNA into 48 parthenogenetic female eggs, of which 15 survived until the adult stage. G2 progenies of these potential founder lines were used for genotyping. We cloned and sequenced genomic PCR products encompassing the gRNA-targeted site to find mutant lines. Of the 15, we found one founder animal that produced offspring harboring biallelic indel mutations around the targeted site . We cultured the wild type and DNMT3.1−/− for 14 days and divided this culturing period into two phases, (1) growth phase (0–4 day) and (2) growth and reproduction phase (4–14 day) where growth and reproduction compete for energy from the food. The growth rate was measured in each phase and the number of offspring was counted in each clutch. In the growth phase, the growth rate of DNMT3.1−/− was similar to that of wild type (P = 0.14)  in addition to the number of offspring at each clutch or their cumulative clutch size (P = 0.7) between wild type and mutant lines  . The starved daphnids produced a smaller number of eggs since the second clutch  between the wild type and the mutant in the growth phase   , with a median lifespan of 54 and 56 days, respectively  with a median lifespan of 50 days compared to 61 days of the wild type line  (ftz-f1), that showed an upregulation in the mutant under starved conditions (Table solute carrier family 13 member 5 (Dapma7bEVm010715t1), known as Slc13a5 or INDY (I’m not dead yet). The Daphnia INDY ortholog showed reduced expression in the wild type but upregulated expression in the mutant under starvation , and 7 other genes related to lipid transport were included in this cluster (Supplementary File target of brain insulin (Dapma7bEVm003111t1) known as tobi, an α-glucosidase. Finally, genes in cluster E were upregulated in the wild type under starved conditions, which included genes related to protein turnover (proteolysis)  known as epsilonTry.To examine how many genes were affected at mRNA level by the DNMT3.1 mutation, we performed RNA-Seq analysis to find differentially expressed genes (DEGs) between wild type and mutant lines in the second phase, growth and reproduction phase. In nutrient rich and starved conditions, numbers of differentially expressed genes were 220 and 2770 respectively, demonstrating that, in the starved condition, disruption of DNMT3.1 showed a much larger effect on the transcriptome. Amongst the DEGs in starved animals, 1432 annotated genes were identified and we performed clustering of these by k-Means. 1364 genes passed the filter  and were divided into five clusters Fig. . Furtheron Table . Genes iD. magna, energy allocation among competing life history traits under starved conditions has been extensively investigated. We have previously shown that Daphnia DNMT3.1 was up-regulated in response to starvation, suggesting a potential function of this gene for energy allocation. In this study, we introduced a mutation into DNMT3.1 and analyzed phenotypes of its mutant under caloric restriction. We demonstrate that this gene is a key regulator for life span and energy allocation between growth and reproduction.Despite the long history of research on energy allocation, genes affecting energy allocation still remain largely unknown. In the cladoceran crustacean 25. Interestingly, the DNMT3.1 mutant showed a higher growth rate and lower clutch size compared to wild type when both processes competed during a period from instar 4 to 8, indicating that DNMT3.1 allocates more energy to reproduction. These results suggest that DNMT3.1 controls the trade-off between growth and reproduction when growth and fecundity compete for energy from the food. Larger clutch size has a positive impact on expanding its population size, which in turn would lead to an increase in fitness. The correlation of DNMT3.1 gene activity with phenotypes in the natural population needs to be examined to further understanding of the functions of this gene in an ecological context.The trade-off between growth and reproduction occurred in both wild-type and DNMT3.1 mutants under different food levels, which is in line with previous reportsD. melanogaster, starvation reduced I am not dead yet or INDY expression and in turn led to extension for longevity49. INDY functions as a citrate transporter of the Krebs cycle and modulates energy production during the life span50. Interestingly, in D. magna, we found upregulation of INDY in short-lived DNMT3.1 mutants under starved conditions. Thus, we hypothesize that, in the wild type, DNMT3.1 downregulates INDY and extends its life span under starved conditions. To test this hypothesis, functional analysis of the Daphnia INDY ortholog would be needed in the future.The life span of the wild type was longer than that of DNMT3.1 mutant under starved conditions. In Caenorhabditis elegans and D. melanogaster lack the DNMT3 ortholog and DNA methylation on the genome. In D. magna, DNMT3.1 mutant is viable and did not show any developmental changes under nutrient-rich conditions. Consistent with this phenotype, knockdown of DNMT3 orthologs in social insects did not reduce survivability41. Although we need to confirm how much the DNMT3.1 protein level has been reduced in the DNMT3.1 mutant, in arthropods, the DNMT3 ortholog may not function in basal development, unlike mammalian DNMT3. In flies, InR and FOXO are known to control life span and fecundity20. Since a potential FOXO binding site has been found in a promoter region of DNMT3.1, core components like the FOXO signaling pathway which influence life history traits may be conserved and linked to DNMT3.1 as a downstream component. Functional analyses of DNMT3 orthologs in other pancrustaceans under stressed conditions including starvation will lead to a better understanding of the functions of this gene in the control of life history traits.DNMT3 orthologs are phylogenetically distributed even in invertebrates but their functions still remain unclear because invertebrate models such as Daphnia has shown 115 genes with significantly hypermethylated regions under starved conditions in D. magna51. Under the starved condition, of the 115, only 8 showed reduced expression in wild type but were de-repressed upon DNMT3.1 mutation  activation, has essential roles in developmental regulation and various aspects of insect adult life55. Vtg1 encodes vitellogenin, a precursor of a major yolk protein56, and has been used as an indicator of fecundity57. The downregulation of Vtg genes was consistent with the severe decrease of fecundity in mutants in response to the starved condition. trypsin encodes digestive protease in the gut of D. magna58 and has been listed as involved in starvation resistance gene in flies59.Among the potential DNMT3.1 target genes under starved conditions, we listed five notable genes including DY Table . ftz-f1,Daphnia species.Our study demonstrates the physiological function of DNMT3.1 in extending longevity and energy allocation to reproduction under starved conditions. Although DNMT3.1 lacks an evolutionarily conserved sequence of the MTase domain, it changes the global transcriptome in response to starvation. In the future, the gene regulatory mechanisms can be investigated not only by investigating DNA methylation but also by chromatin immunoprecipitation for the identification of direct targets of this protein. We anticipate that this work will contribute to understanding the molecular mechanisms underlying energy allocation in the ecologically important Daphnia magna strain (NIES clone) was obtained from the National Institute for Environmental Studies  and cultured under laboratory conditions for many generations by using ADaM as the culture medium60. Briefly, for maintenance of this strain, 80 individuals were cultured in the 5 l ADaM medium and daily fed with 160 μl of 7 × 109 cells ml−1Chlorella (Chlorella vulgaris) algae. The mutant line was maintained similarly by culturing 40 individuals in 2.5 l ADaM medium and daily feeding with 80 μl of 7 × 109 cells ml−1Chlorella (Chlorella vulgaris) algae. These cultures were performed at 22–24 °C, under a light/dark photoperiod of 16/8 h.The 28. For the preparation of the DNMT3.1-targeting Cas9 RNPs, we purified Cas9 proteins as described elsewhere61. For the synthesis of the gRNA, DNA templates with the T7 promoter and target site , was amplified by PCR28 and purified by phenol/chloroform extraction. These DNA fragments were used as templates for in vitro transcription with mMessage mMachine T7 Kit , followed by column purification with miniQuick Spin RNA columns , phenol/chloroform extraction, ethanol precipitation, and reconstitution in DNase/RNase-free water . We incubated 2 μM gRNA with 1 μM Cas9 protein to generate Cas9 RNPs and injected them into parthenogenetic female eggs according to established procedures62. Accordingly, the eggs were collected from 2–3 weeks daphnids after ovulation and placed in an ice-chilled M4 medium containing 80 mM sucrose (M4-sucrose). Approximately 0.2 nL volume of the generated Cas9 RNPs were injected by using N2 gas pressure through a glass needle. After injection, to investigate the Cas9-induced mutations, G2 offspring were homogenized in 90 μL of 50 mM NaOH with zirconia beads. The lysate was heated at 95 °C for 10 min and then neutralized with 10 μl of 1 mM Tris–HCl (pH 7.5). This crude DNA extract was centrifuged at 12,000 rpm for 5 min and then used as a template in genomic PCR. The targeted genomic regions in the DNMT3.1 locus were amplified by PCR with Ex Taq Hot Start Version  and the following primers; DNMT3.1-U-gDNA 5′-TCCGGGTCGTGGTACTCC-3′ and DNMT3.1-D-gDNA 5′-AGACAAGAAACGAGCAGGTGAATAG-3′. The PCR products were analyzed by polyacrylamide gel electrophoresis and DNA sequencing.Impairment of the DNMT3.1 gene was done with CRISPR/Cas9 technology by introducing a frameshift and premature STOP codon as described previouslyDaphnia of each line were cultured in 2.5 l ADaM medium and daily fed with 1.5 × 109 cells ml−1Chlorella algae for at least 3 generations. Neonates from the third clutch were randomly assigned, transferred individually to a 50 ml conical tube containing 40 ml ADaM medium, and subjected to nutrient rich or starved treatments. Under the nutrient rich condition, 5.12 × 107 cells were given to each daphnid daily. For starvation, daphnids were fed with the eightfold lower amounts of the algae. During culture, the medium was changed every day in order to avoid carbon  accumulation that could differentially affect resource availability. For life-history traits observation, 15 and 20 neonates were randomly collected from culture under nutrient rich and starved conditions, respectively. Under the nutrient rich condition, the body length of daphnids was measured on days 0, 4, 7, and 14. The clutch size was recorded by counting the number of offspring produced from the 1st to 3rd clutch. During culturing, due to handling, one wild type and one mutant were killed. Therefore, we recorded the life span of 14 individuals of wild types and mutants. For starvation experiments, the body length of daphnids was measured at the two more time points, day 18 and day 22, in addition to day 0, 4, 7, and 14. Clutch size was recorded from 1st to 5th clutch. In this treatment, we could record the life span of 20 individuals both from wild types and mutants. For expression analysis by quantitative real-time PCR and RNA-seq, 5 daphnids were also cultured individually in each condition until producing 2nd clutch (day 12). Eggs were removed before homogenization for RNA extraction. Each treatment was repeated 3 times for triplicates of sampling.Before culturing under starved conditions, in order to control for maternal effects, 40 D. magna growth, we measured body length from the center of the eye to the base of the tail63 using a microscope and the ImageJ software (http://rsb.info.nih.gov/ij/). The growth rates of juvenile and adult daphnids were determined by using their body length on day 0–day 4 and day 4–day 14, respectively, and calculated asL1 and L0 are the final and the initial body lengths, respectively, and t is the time in days from the first to final observation64.To examine the effect of starvation on To extract total RNA, 5 female adult daphnids were collected and briefly washed. Homogenization was performed with beads using a Micro Smash machine MS-100  in the presence of Sepasol-RNA I reagent . Total RNA was isolated according to the manufacturer’s protocol, which was followed by phenol/chloroform extraction. One μg of purified total RNA was converted into the first-strand cDNA with PrimeScript II Reverse Transcriptase  and random primers  according to the manufacturer’s recommended protocol.DapmaDNMTs transcript level to the transcript level of ribosomal protein L3265. The oligonucleotide sequences for qRT-PCR were used by the previous study43 and combined with DapmaDNMT1 primers (DapmaDNMT1-forward 5′- GAAGATTCCCTTCTGCGCTATG -3′ and DapmaDNMT1-reverse 5′- CACGGGCTGAGAATAAGTGGT-3′).Total RNA purification and cDNA synthesis in adult samples treated with different food levels were performed as described above. PCR was performed using a Power SYBR Green PCR Master Mix  with Mx3005P Real-Time PCR System . In the presence of the appropriate primer pairs, real-time PCR amplifications were performed in triplicate at the following conditions: 2 min at 50 °C and 10 min 95 °C, followed by 40 cycles of 15 s at 95 °C and 1 min at 60 °C. Gel electrophoresis and dissociation curve analyses were performed to confirm the correct amplicon size and the absence of non-specific bands. The relative mRNA levels of juvenile samples and adult samples treated by different food levels were analyzed by normalization of the D. magna, which is available from wFleaBase.org66.9 total RNA samples were extracted from triplicate samples of each of the three treatments (wild types in starved condition and mutants either nutrient rich or starved condition) were used for RNA-seq provided by Novogene service (Novogene (HK) Company Limited, based on Illumina NovaSeq platforms with paired-end 150 bp sequencing strategy (en.novogene.com). Before proceeding with the sequencing, all 9 samples passed the QC Criteria from the company and met the requirement of library construction. A summary of counted reads and percentage of total reads mapped is shown in Supplementary Table Daphnia culturing condition as in this study67. The Daphnia magna genome that is available from wFleaBase.org66 was used as a reference for mapping the reads. Mapping options were set at mismatch cost 2, insertion cost 3, depletion cost 3, length fraction 0.8, similarity fraction 0.8, expression value set to total counts. Differential expression analysis was performed with the ‘Transcriptomics Analysis’ toolbox, and comprised ‘experimental set-up’, where treatments pairs were analyzed with the option ‘All group pairs’. This setting uses the Wald test and reports the expression mean of each gene with a fold change between the treatment pair. Expression values were normalized using the options ‘by totals’ and ‘state numbers in read 1,000,000′. The normalized values were transformed using the “Add a Constant” set at the value ‘1′. In order to identify the differential expressed genes (DEGs) between a pair of treatments, Anova and Likelihood ratio test were performed on the transformed values for each mapped gene, and DEGs were filtered based on false discovery rate (FDR) p-value cutoff FDR P < 0.05 and fold change cutoff FC ≥ ∣1.5∣. k-Means clustering was performed by iDEP(v.9)68. A list of gene ID of DEGs merged counts was uploaded to iDEP and parameters for analysis were set following a previous study69. Accordingly, counts were filtered out by criteria of at least 0.5 counts per million in one of the samples and transformed by VST (variance stabilizing transform). Heatmap was visualized by blue-white-red color scheme and k-Means was clustered for all of the filtered genes by choosing 5 clusters. The gene ID from the Daphnia magna genome was annotated by NCBI homologs using Blast2GO features within OmicsBox 1.2.470. The annotated genes in each cluster were examined for the enrichment of GO terms within the subsets of the assembled sequences via Fisher’s Exact Test executed within OmicsBox 1.2.471.Sequencing data from 9 libraries of the above samples were analyzed using CLC Genomics Workbench 12 (Qiagen) (accession number: GSE158129). The other 3 libraries of the triplicates from wild type in nutrient rich condition (accession number: GSE150821) had been prepared and sequenced elsewhere by the same methods including 72. Growth rate, clutch size, and median lifespan were analyzed by pairwise t-test and Student’s t-test with Welch’s correction. Fitted von Bertalanffy growth was performed by the “FSA” R package73. The boxplots were generated by “ggplot2” R package74. Kaplan Meier survival curves and log-rank test analysis were performed by the “survival” R package75. Two-way ANOVA and Fisher’s LSD test were performed by “agricolae” R package76. The level of significance was P < 0.05.Statistical analyses were conducted using statistical program R version 3.2.5Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.


When a drone is used for inspection of facilities, there are often cases in which high-voltage power lines interfere, resulting in the drone being caught or falling. To prevent this type of incident, drones must be capable of detecting high-voltage power lines. Typically, a strong electric field is formed around the high-voltage lines. To detect the electric fields around high-voltage lines, this study proposes an electric field sensor that may be integrated within the body of a drone. In a laboratory environment, a voltage of 25 kV was applied to an overhead line, and the induced voltage in the proposed sensor was measured at various electric field intensities. Over an electric field range of 0.5 to 10.1 kV/m, a voltage of 0 to 0.77 V was measured with each proposed sensor. In addition, the electric field and the voltage induced in the sensor were measured in a real-world railway environment with overhead lines. Under these conditions, the proposed sensor has the compensated value of 4.5 when the measured electric field was 4.05 kV/m. Therefore, the proposed sensor may be applied in drones to measure large electric fields and to detect the presence of high-voltage lines in its vicinity. Recently, more and more drones are used for the inspection of electrical facilities. However, when these drones approach a facility to obtain high-resolution photos, the distances between the power lines and drone are not accurately identified, which may lead to the drone becoming caught in the lines during maneuvers. If the drone becomes caught in a high-voltage power line, the drone may be destroyed; furthermore, the high-voltage lines may be damaged, thereby affecting numerous electrical facilities connected to these high-voltage lines. Therefore, a method for detecting power lines is required when drones are used in the vicinity of high-voltage power lines.A commonly used method for the detection of high-voltage lines utilizes images or videos taken during the drone operation. This method acquires image data near the drone and extracts information involving the voltage lines using algorithms such as the Hough transform, Radon transform, and Line Segment Detector ,2. By exSeveral previous studies have proposed the measurement of the voltage of high-voltage lines via non-contact methods ,4,5,6. HIn the case of high-speed railways, power at 60 Hz and 25 kV is supplied to the overhead line. When such a high voltage is applied to the overhead line, a strong electric field is generated around the overhead line. In this study, we propose a method for measuring electric fields such that drones may be able to detect high-voltage lines in their vicinity. Upon measuring an electric field, the presence of high-voltage lines in the surrounding area may be detected using the relative intensity of the measured electric field. Several methods have been proposed to obtain electric field measurement ,10,11,12In this study, we proposed a method involving the use of a component of a drone to measure the electric field generated by high-voltage power lines. If the body of the drone is used as an electric field sensor, the size of the sensor can be made large; thus, it has the advantage of increasing the induced voltage of the sensor. Moreover, there is no need to reserve additional space for the electric field sensor. If the electric field is constantly monitored, the presence of high-voltage lines in the vicinity of the drone can be inferred when the measured electric field is higher than a set threshold value. The drone may then avoid high-voltage lines based on the measured electric field values. The remainder of this paper is structured as follows. OCV is the voltage, E(ω) is the electric field, ω is the angular frequency, and h is half of the total length of the small dipole antenna.Electric fields and induced voltages are closely related. The structures most commonly applied for sensors used to measure electric fields are small dipole antenna. In addition, two parallel plates separated by a set distance can also be used as sensors for electric field measurements, although this type of the sensor is not commonly used. E(ω), then the following relationship holds for the voltage OCV [Similarly, in the case of an electric field sensor composed of two parallel plates, the electric field formed between the parallel plates is directly related to the voltage applied between the two parallel plates. If the distance between the parallel plates is d and the magnitude of the electric field formed between the two parallel plates is tage VOC :(2)VOC(ωAssuming that the electric field is constant from Equations (1) and (2), it can be seen that the induced voltage increases when the dipole antenna is lengthened or the distance between two parallel plates is increased.When a dipole and a parallel plate capacitor are used at a location with a uniform distribution of an electric field, the magnitude of the induced voltage varies depending on the orientation of the sensors. For the following simulations, the orientation of the sensors was varied, as shown in LZ(ω) is expressed by the following equation.PC, the sensor impedance expressed by the following equation.The horizontal and vertical lengths of the plate were 200 cm, and the distance between the two plates was set to 40 cm. The voltage was applied through port 1, and 1000 V were applied in the simulation. Although the frequency of a real-world overhead power line voltage is 60 Hz, it is difficult to observe clear characteristics under these conditions via simulation because the induced voltage in the sensor is low at frequency of 60 Hz. Because the induced voltage in the sensor is generally proportional to the frequency, a frequency of 60 kHz  was used in the simulations. The increase in induced voltage according to the increase in frequency can be derived from the equivalent circuit model. For the structures of From the Equation (5), as the frequency increases, the Considering the device under test (DUT), a small dipole antenna and parallel palate capacitor were used, and these were placed in the middle of the electric field generator. The length of the small dipole was set to 20 cm, and the dimensions of the parallel plate capacitor were 20 cm in width and length and 5 cm in height. Next, each sensor was connected to port 2 with a load resistance of 1 MΩ to simulate the induced voltage. The simulations were performed using CST Studio Suite, which is a commercial software package for electromagnetic (EM) analysis. The results of the simulations are presented in By examining the voltages of the sensors induced in the simulations, it can be seen that, in the small dipole antenna, a voltage of 127 V is induced in the vertical orientation, while for the parallel plate capacitor, a voltage of 108 V is induced in the horizontal orientation. No voltage was induced in the horizontally placed dipole antenna or the vertically placed parallel plate capacitor. Therefore, it can be observed that the small dipole antenna and parallel plate capacitor have structures that detect electric fields that are generated in specific orientations.−1. A Raspberry Pi 4.0 board was used as an embedded board for ease of data processing.The structure of the sensor for measuring the relative intensity of an electric field is illustrated in The induced voltages for the different orientations of the proposed sensor were simulated. The simulation environment was the same as in In the case of the dipole antenna, it is obvious that the induced voltage decreases as the length becomes shorter. Since the structure for z-axis uses upper metal plates and metal posts, it is necessary to investigate how the induced voltage changes according to the length change in this structure. The induced voltage of the sensor according to the length change is shown in To measure the voltage induced in the sensor with respect to the electric field, an experimental setup was constructed, as shown in e, as indicated in To examine the relationship between the proposed sensor and the measured electric field, the measured electric field and sensor voltages were compared with respect to changes in the supply voltage at position a to f, as indicated in Next, the electric field and sensor voltage were measured from positions Mx, My, and Mz, and the voltage induced from the sensor in each direction is set as Vx, Vy, Vz, the relationship between electric field and the induced voltage can be expressed as follows.A is weighting matrix. If the coefficient of A is determined, the electric field in each direction can be calculated from the voltage of the sensor. Using this, the magnitude of the total electric field can be calculated from the following equation.The proposed sensor has a structure that receives the electric field of each axis. However, since the distance between the ADC and the sensor exists when installing the sensor on the drone, lead wires are needed to electrically connect it. This lead wire also works as a part of the sensor. No matter how well the designed sensor receives only one-direction electric field, if it is manufactured, it can receive an electric field in the other direction. If the magnitude of the electric field measured in each direction is d, e, and f in V vector and M vector can be expressed in the form of a 3 × 3 matrix, the A matrix can be calculated from the following formula.To obtain the A matrix, the measured sensor values and electric field values from three points A are shown on the right side of a to f show similar trends. For positions d to f, which are located at a distance of 0.7 m in the horizontal direction from positions a to c, the values of the electric field are observed to not be significantly affected by the height. The measured electric field and sensor voltage decrease as it approaches point f. The compensated sensor values extracted from the calculated From the above results, it can be seen that the proposed sensor produces compensated sensor values that are 7 V or greater in a large electric field environment. Therefore, if a system is designed such that it provides an indication when the measured sensor value is above a pre-determined value, a drone may be able to detect approaching the high-voltage lines. In this study, the measured voltage of the sensor was made in units of 0.01 V. Because this unit is not affected by ambient noise. If this value is roughly converted to an electric field value, it corresponds to 0.3 kV/m. Therefore, it can be seen that the proposed sensor has the resolution to distinguish an electric field of 0.3 kV/m.In this study, a sensor for use in drones to measure electric fields in their surroundings is proposed to prevent contact between drones and high-voltage power lines. Because the voltage measurements achieved by the sensor are determined by the length of the sensor, a method for incorporating the body of the drone as a part of the sensor was proposed. In the structure of the proposed sensor, two dipole antenna structures were used to detect the electric field in the horizontal direction. In addition, to measure the electric field in the vertical direction, a structure using a metal plate and a metal post was proposed.The voltage induced in the proposed sensor with respect to the electric field was measured in both laboratory and real-world railway environments. In the laboratory environment, the voltage of the proposed sensor was measured to be 0 to 0.77 V for an electric field in the range of 0.5 to 10.1 kV/m. In the real-world railway environment, the measured electric field was 4.05 kV/m at a height of 0.8 m, and the compensated sensor value was 4.54. The sensor proposed in this study may be used such that drones can detect high-voltage power lines through measurements of high electric fields.


Small or large birth weight for gestational age has been linked with later cardiovascular disease risk. However, cardiovascular risk markers from childhood to adulthood according to birth weight in diverse longitudinal settings globally have not been extensively studied.To examine the relationship between birth weight and cardiovascular risk profile from childhood until young adulthood in two geographically and socioeconomically distinct cohorts.Data were derived from two longitudinal birth cohort studies; one from southern Finland  and one from northern Australia comprising Indigenous Australians . The sample included 747 Finnish participants and 541 Indigenous Australians with data on birth weight, gestational age and cardiovascular risk factors (body mass index [BMI]), waist-to-height ratio [WHtR], lipid profile, blood pressure) collected at ages 11, 18 and 25 or 26 years. Carotid intima-media thickness (cIMT) was assessed at age 18 or 19 years. Participants were categorised according to birth weight for gestational age . Associations between birth weight category and cardiovascular risk markers were studied using a repeated measures ANOVA.p=.003 for STRIP and p<.0001 for ABC). In the ABC, higher birth weight category was also associated with higher WHtR (p=.004). In the ABC, SGA participants had lower systolic and diastolic blood pressure than AGA participants  and lower systolic blood pressure than LGA participants (p=.046) at age 25. In the STRIP cohort, SGA participants had lower cIMT than LGA participants (p=.024).Higher birth weight category was associated with higher BMI later in life in both cohorts (The strongest association between birth weight and later cardiovascular risk profile was manifested as differences in body mass index in two culturally and geographically distinct cohorts.Foetal growth is a determinant for later cardiovascular health in diverse populations, indicating a need to focus on maternal and foetal health to improve cardiovascular health worldwide.Birth weight can predict future cardiovascular risk profile in diverse populations. Thus, it needs to be included in targeted public health interventions for tackling the obesity pandemic and improving cardiovascular health worldwide. The British epidemiologist David Barker proposed in 1990 that foetal undernutrition leading to disproportionate foetal growth, predisposes to coronary heart disease later in life ,3. FoetaJ- or U-shaped rather than inverse, indicating that both low and high birth weight are risk factors for cardiovascular disease [Cardiovascular disease is the leading cause of death worldwide . Individ disease ,7. The a disease , but it  disease .In this study we examined links between birth weight status and cardiovascular health markers including arterial intima-media thickness at ages 11, 18 and 25 to 26 in two prospective birth cohorts from opposite sides of the globe, Finland and Australia. The two cohorts are nearly contemporaneous but differ considerably in terms of geography, culture, and socioeconomic circumstances, thus providing a unique research setting. Our hypothesis was that disproportionate foetal growth predisposes to poor cardiovascular health irrespective of geographical or cultural setting.The Finnish cohort comes from an urban area with nutritional security and high levels of education . In contThe ABC study was created to investigate the possible developmental origins behind the high rates of non-communicable disease in the Aboriginal population in Australia. It is one of the longest running and largest indigenous birth cohorts in Australasia. Between 1987 and 1990, 686 of the 1,238 singleton babies born to Indigenous mothers at the Royal Darwin Hospital were recruited into the study. There were no significant differences in mean birth weight and sex ratio between those recruited and those not recruited. The majority of the participants (75%) resided in remote communities across the sparsely populated northern Australia and 25% lived in urban Darwin or its immediate surroundings at the time of recruitment, comparable to the Northern Australian Indigenous population . There hn = 551) [The STRIP study is a continuing dietary intervention trial that was launched in 1989 in Turku, an urban area in southwest Finland. The aim of the intervention was to promote cardiovascular health by introducing a heart-healthy diet beginning from infancy. Recruitment of the children and their parents was done at well-baby clinics by nurses during a 5-month visit. Between February 1990 and June 1992, 1,062 babies were enrolled and equally allocated to an intervention or control group. Thereafter, the intervention was continued for 20 years, and extensive data focussing on diet and cardiovascular health were obtained at least annually to the age of 20 years . After tn = 551) .p=.20) or birth weight category (p=.83) between the groups.In this study, the STRIP intervention and control groups were treated combined as there was no difference in birth weight  and infants with extremely low birth weight  were excluded. In total, 541 infants from the ABC and 747 infants from the STRIP study were included in the analyses.This study was approved by the Human Research Ethics Committee of the Northern Territory Department of Health and Menzies School of Health Research, including the Aboriginal Ethics Sub-committee with the power of veto . The investigation complied with the National Health and Medical Research Council National Statement on Ethical Conduct in Human Research (2007) and the Helsinki Declaration of 1975 (2008 revision). Informed written consent was obtained from all participants or (until the age of 18 years) their mothers. The STRIP study was approved by the associated university and hospital district ethical authorities. Written informed consent was obtained from parents at study entry, and from the participants at ages 15, 18, and 26 years.In the ABC, infant birth weight was measured within 2 h of delivery. Birth weights were recorded to the nearest gram using a balance scale. A neonatal paediatrician performed a gestational age assessment on the participants according to the Dubowitz scoring system  within 4Using an international growth reference Intergrowth-21st, the participants from both cohorts were classified as small for gestational age , appropriate for gestational age , or large for gestational age  according to sex .In the ABC, venous blood samples were collected for assessing serum lipid levels  by enzymatic methods . Blood pressure was measured three times during each follow-up  with an automatic oscillatory unit ; the mean systolic and diastolic values were included in the analyses. Weight was measured to 0.1 kg with a digital scale  while the participant was barefoot and in light clothing. Height was measured with a portable stadiometer to the nearest millimetre. Waist circumference was measured to the nearest millimetre using a flexible tape measure at the midpoint between the lowest rib and iliac crest at the end of exhalation ,17. CIMTIn the STRIP study, established clinical laboratory methods were used to measure serum lipid levels  from venous blood samples taken after an overnight fast . LDL-cho2), and WHtR was calculated as waist (m) divided by height (m). Pulse pressure was reported as the difference between mean systolic and mean diastolic pressure. All participants were categorised as hypertensive or non-hypertensive at age 25 or 26, based on a definition by the American Heart Association (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥80 mmHg) [For both cohorts, BMI was calculated as weight (kg) divided by the square of height . Statistical significance was inferred at a 2-tailed P-value <.05.Characteristics of study participants are reported as means with standard deviations (SDs) for continuous variables and as proportions for categorical variables. Differences between the two cohorts and between the STRIP intervention and control groups in birth weight and gestational age were analysed using t-tests, while for birth weight category, the Cochran-Mantel-Haenszel method was applied. The Cochran-Mantel-Haenszel method was also used for analyzing the association between birth weight category and elevated blood pressure at age 25 or 26. The main analyses examined the associations between birthweight category and longitudinal data on cardiovascular markers. For this purpose, a repeated measures ANOVA was used. Compound symmetry was used as covariance structure. In each model, one of the cardiovascular markers was included as the outcome variable along with birth weight category , sex and assessment time point (study wave in the ABC and assessment age in STRIP). Finally, an interaction term between assessment time point and birth weight category was included in the model to calculate least square means (adjusted means) with 95% confidence intervals for each assessment time point and to yield group-wise comparisons between the birth weight categories.Additionally, to assess potential mediation, all models were adjusted for BMI. Linear regression analysis adjusted for sex was used to analyse effect of birth weight on cIMT and differences in cIMT between the birth weight categories.p<.0001). Mean birth weight was also lower in the ABC participants . There were more SGA babies (22.4% vs 2.4%) and less LGA babies (8.3% vs. 29.2%) in the ABC than in the STRIP cohort (p<.0001).Characteristics of the participants are reported in p<.0001 for ABC and p=.003 for STRIP) with higher BMI found for higher birth weight category. Group-wise comparisons of the birth weight categories showed that participants who were LGA had higher BMI compared to the SGA participants in both the ABC and the STRIP study at all follow-ups. In the ABC, the sex and study point adjusted mean for BMI in the LGA group at age 11 was 19.5 kg/m2 (95%CI 17.9–21.0) vs. 16.2 kg/m2  in the SGA group; at age 18 it was 24.9 kg/m2 (23.3–26.5) vs. 20.1 kg/m2 , and at age 25, 26.0 kg/m2 (24.3–27.7) vs. 22.3 kg/m2 . BMI was higher in the AGA group compared to the SGA group at age 18: 21.6 kg/m2 (21.1–22.2) vs. 20.1 kg/m2 (p=.01) and at age 25: 24.3 kg/m2 (23.8–24.9) vs. 22.3 kg/m2 (p=.0005). LGA participants had higher BMI than AGA participants at age 11 . In the STRIP study, BMI in the LGA group at age 11 was 18.4 kg/m2 (17.9–18.9) vs. 16.2 kg/m2  in the SGA group; at age 18, 22.7 kg/m2 (22.1–23.2) vs. 20.3 kg/m2  and at age 26, 25.1 kg/m2 (24.6–25.7) vs. 22.3 kg/m2 . BMI was higher in the AGA group compared to the SGA group only at age 26: 24.4 kg/m2 (24.1–24.8) vs. 22.3 kg/m2 (p=.024). LGA participants had higher BMI than AGA participants at ages 18  and at age 26   .p=.004) with higher WHtR levels found for higher birth weight category. This association persisted after adjusting for BMI (p=.004). In contrast, there was no association between birth weight category and WHtR in the STRIP study (p=.33).Similar to BMI, birth weight category was associated in a step-wise manner with WHtR in the ABC (p=.007) and 18 . Similarly, the LGA participants had higher WHtR than the AGA participants at ages 11  and 18 . There were no differences in WHtR between the SGA and AGA participants at any studied age and no differences between any of the birth weight categories were found at age 25.In the ABC, group-wise comparisons between the birth weight categories showed that WHtR was higher in the LGA participants compared to the SGA participants at ages 11  and AGA  participants. These associations did not persist after adjusting for BMI.The associations between birth weight category and serum lipid levels are summarized in The associations between birth weight category and future blood pressure levels are presented in p=.046), and in the AGA group compared to the SGA group . Systolic blood pressure was higher in the LGA group compared to the AGA group . These associations did not persist after adjusting for BMI.The longitudinal analyses revealed that birth weight category was not associated with systolic blood pressure levels in either cohort. Group-wise comparisons of the birth weight categories, however, showed that in the ABC cohort at age 11, systolic blood pressure was higher in the LGA group compared to the SGA group . In the STRIP study, LGA participants had higher diastolic blood pressure than AGA participants at age 11   . These aN = 127) and in the ABC 12.9% (N = 70) of participants had elevated blood pressure at age 25 or 26. There was no association between birth weight category and elevated blood pressure in either cohort .In the STRIP study, 17.0% (p = 0.72). Similarly, group-wise comparisons revealed no differences in cIMT between the birth weight categories.Mean values for cIMT with 95% confidence intervals at age 18/19 years for each birth weight category are presented in p=.19). However, in the group-wise comparisons, SGA participants had a tendency for lower cIMT than AGA participants  and had lower cIMT than LGA participants .In the STRIP study, there was no association between birth weight category and cIMT , higher birth weight was associated with both higher BMI and higher fat mass index [The observed association between birth weight and BMI from childhood to adulthood is in line with prior studies showing that high birth weight may lead to obesity later in life . In a crss index  and a stss index . Moreovess index .Collectively, genetic and epigenetic properties are thought play an important role in the association between birth weight and later CVD risk. The association between low birth weight and later CVD has been documented in numerous epidemiological studies  Foetal eA large multi-cohort study from Finland and the UK examined the role of birth weight adjusted for gestational age on later metabolic profile and found that lower birth weight was adversely associated with cardiometabolic biomarkers such as lipid levels and inflammatory markers in adulthood. The magnitude of this association, however, was modest, similar to that caused by high BMI in adulthood. It was suggested similar molecular pathways may underlie both low birth weight and adulthood overweight .N = 300.000), genome-wide association study using data from the EGG consortium and the UK biobank found evidence to support that the inverse association between birth weight and blood pressure is attributable both directly to the foetal genotype and indirectly to maternal genetic factors that produce an adverse intrauterine environment. According to the study, it is possible that some of the same alleles that are associated with lower birth weight might also cause higher blood pressure later in life [Somewhat unexpectedly, only few associations between birth weight category and blood pressure or lipid levels were found in the present study, whereas previous studies have reported inverse associations between these variables. In the Bogalusa Heart Study (Louisiana), lower birth weight was associated with both higher blood pressure levels   from chi in life . The lacThe finding that birth weight was associated with WHtR in the ABC but not in the STRIP cohort, may be explained by different patterns of fat accumulation in the populations. In a previous study examining the prevalence of metabolic syndrome in the ABC, it was noted that large waist circumference was quite common despite low rates of overweight and the relative underweight nature of the cohort. It was suggested that there could be a susceptibility for central fat accumulation in the population and that central adiposity could serve as a better predictor of metabolic and cardiovascular disorders than BMI also in Indigenous Australians . AnotherA key finding of this study was that larger babies, although born in completely different global contexts, tend to have larger BMIs already in childhood, putting these individuals at greater risk for obesity-related disorders such as type 2 diabetes and cancer ,43. A prA particular strength of this study is that we were able to compare two unique cohorts that were established almost simultaneously on opposite sides of the globe in very different socioeconomic and cultural settings. Both of these longitudinal studies began in infancy, and have had good retention rates and systematically structured follow-ups. We acknowledge that comparisons between the cohorts remain observational, as the methodologies to assess anthropometrics and blood pressure, blood sampling and carotid ultrasonography were not standardised across the cohorts to allow for statistical comparisons. As the sample sizes of both studies and especially the number of SGA infants in the STRIP cohort and the number of LGA infants in the ABC were quite low, it is possible that some existing associations were not found. Parental effects on birth weight were not analysed although especially maternal risk factors such as gestational diabetes and maternal BMI could add important information about the intergenerational inheritance of cardiovascular risk. Finally, clinical relevance of the cardiovascular risks described in this paper remain to be analysed in later studies, as the participants were still young with little cardiovascular morbidities.Collectively, findings of this study suggest that birth weight category is associated with later cardiovascular risk profile with the most robust associations seen in nutritional status indicated by BMI and WHtR. This finding supports targeted prevention strategies for those individuals at risk to improve cardiovascular health worldwide. Additional research on the longitudinal health trajectories of small and large birth weight infants is needed for evaluation of the extent of cardiovascular risk related to birth weight. Future research endeavours may focus on the possibilities of incorporating birth weight into CVD risk assessment and on the impact of targeted intervention strategies for individuals at risk based on their birth weight.Click here for additional data file.


Until now, the comparison of environmental impact and influence of electric transport means on the power systems was not fully addressed in the case of Poland. The purpose of the study is to describe, analyse and assess electric vehicles (EV) operation against performance indicators in Poland, especially the influence of electric transport means (ETM)  on power system and environment. The influence on the power system was investigated for the Polish National Powers system using the simulation of different scenarios of loads generated by EV charging. The energy demand of the National Power System and daily load variability indices were determined. Based on the data of ETM powers consumption and emissions of energy production, the emissions of harmful gases per one km and per one person were calculated, as well as the financial outlays for energy necessary to drive 1 km per 1 passenger. To assess and compare the environmental impact of the selected ETM life cycle, the life cycle assessment method was used. The results of environmental impacts were determined for selected assessment methods: CML 2 and IPCC 2013 GWP 100. The functional unit in this study is one selected ETM with a service life of 100,000 km. Comparison of trams, trolley buses, buses and electric passenger cars indicates that most beneficial are electric buses which do not need rails or overhead lines, thus investment costs are lower.Currently, electric vehicles are a rapidly growing alternative to those with combustion engines and can contribute to reduction of CO The first model of an electric motor vehicle dates back to the early 19th century  [The number of electric vehicles in Europe is constantly growing. Actions are being taken to introduce this type of vehicles into public transport systems ,3. TheseInfrastructure necessary for electric vehicles to operate has been developing for the last few years . UnfortuNew solutions should be devised to improve the already high energy efficiency of drives and the range of electric vehicles shortening the battery charging time. The capacity and charging time of batteries are still no match for the refuelling time in combustion vehicles.Efficiency is one of operational criteria relating to the organisation, course and acquisition of useful and useless products of operation, in this case, electric transport. Efficiency is defined as a situation in which a person, company, factory, etc. uses resources such as time, materials or labour well, without wasting any. In relation to machines and devices it is understand as the difference between the amount of energy that is put into a machine in the form of fuel, effort, etc., and the amount that comes out of it .Economic factors—cost of operation, repair, insurance, etc.;Organisational factors—organisation of a way, line and stops, optimal selection of a transport mode for a line, etc.;Social factors—to include society structure, vehicle age, aesthetic impression (vehicle appearance), innovation (access to WiFi hotspots in vehicles), safety, etc.Factors influencing the efficiency of electric transport are divided into technical and non-technical factors . TechnicElectric vehicles are considered more environmentally friendly than cars equipped with an internal combustion engine due to lack of direct emissions into the environment. They, however, require supply of electrical energy whose production is burdened with harmful emissivity . Use of Apart from economic and ecological effects, the growing number of electric vehicles, mostly the need to chargé them by using energy from power grid involves changes and disruptions in its functioning ,28. ManyBasically, no publications have been found for comparison of the effects of different electric transport forms, e.g., electric cars, trams or trolley-buses, nor overall assessments of their environmental impact and influence of using and charging the electric vehicles on the power grid in Poland. Therefore, the authors of this study have undertaken an attempt to evaluate and compare a few forms of electric transport in terms of environmental impact and influence on the power system select Poland as regional border.2 emission and other harmful gases and dust for electric cars, trams, trolley-buses and electric buses was presented, as well as the comparative life cycle assessment for selected transport means for 11 impact categories. The influence on the power grid was shown through a simulation of the electric car charging for four variants of 24 h load of power grid in order to indicate the most convenient time for charging.In the light of the above statements from the state of the art and technology the purpose of the article is to describe, analyse and assess electric vehicles operation against performance indicators in Poland. In this work the comparison of COIndication of the impact of the appearance of a significant number of electric cars and the need to charge them on the Polish power systems;2, SO2, NOx, CO and dust) related to the use of electric means of transport in Poland per road unit and per passenger, taking into account the Polish energy mix and various scenarios of the share of renewable energy sources in the electricity produced;Estimation of emissions of harmful substances , whereaTrams operate in 12 cities and two metropolitan areas in Poland—the Upper Silesian Industrial Region (13 cities) and the Łódź Metropolitan Area (6 locations)—whereas trolley buses only operate in three cities: Gdynia, Lublin and Tychy ,41.Polish companies are key players on the trolley bus and tram manufacturing market. PESA Bydgoszcz S.A.  is a leading company manufacturing and modernising railway vehicles, including trams. PESA trams operate in Polish, Russian, Ukrainian, Romanian, Bulgarian and Hungarian cities . SolarisOn the one hand, a solution to the problem of qualification of positive and negative effects of the system with electric vehicles, mainly electric cars and buses, refers to power system loading and relief, and, on the other hand, to the innovation of solutions. A million electric vehicles that will be operated from 2025, fitted with batteries of the capacity of approximately 30 kWh charged in a 10-h cycle, will load the system with additional 3 GW at the currently available power of approximately 43.4 GW (as of 31 December 2017 ). Electrdsrm, which is defined as:Average daily load degree–dmmin,dsrP—average daily load, MW; dPmin—minimum daily load, MW; and dPmax—maximum daily load, MW.Energy consumption variability index–On the basis of daily power system load variability profiles, a number of indicators of variable positive effects can be determined to assess the variability of power system loads used in a classical analysis, e.g., :Average First variant—vehicles will be charged from 12:00 at night to 10:00 a.m.;Second variant—charging will be spread out over rush hours from 07:00 a.m. to 05:00 p.m.;Third variant—the charging process moved to picture the night low period, i.e., from 10:00 p.m. to 8:00 a.m.;Forth variant—vehicles will be charged evenly round-the-clock.In order to picture the impact of electric vehicles on the Polish power grid a simulation was carried out to select an optimal vehicle charging period during 24 h. It was assumed that the number of electric vehicles was 1 million and the battery capacity was 30 kWh. System data of the energy demand by the National Power System dated 06.06.2018 was used for the analysis . The Pol2 emission yield per 1 km, COq2:Unit COx emission yield per 1 km, SOxq:Unit SOx emission yield per 1 km, NOxq:Unit NOCOq:Unit CO emission yield per 1 km, Dq:COm2—equivalent weight of CO2 emitted during transport in g or kg; Soxm—equivalent weight of SOx emitted during transport in g or kg; NOxm—equivalent weight of NOx emitted during transport in g or kg; COm—equivalent weight of CO emitted during transport in g or kg; Dm—equivalent weight of dust emitted during transport in g or kg; and Tl—transport road in km.Unit micro- and nano-dust yield per 1 km, In assessment of variable negative effects of the electromobility system, the following indicators are taken into consideration:2 emission yield per transported person or kWh of consumed energy and its cost:2 emission yield per person in a vehicle, osq:Unit CO2 emission yield per 1 kWh of consumed electric power, kWhq:Unit COEEk:COm2—equivalent weight of CO2 emitted during transport in g or kg; Tl—transport road in km; osl—number of transported persons, pcs; kWhl—amount of electric power consumed by vehicle, kWh; EEk—cost of electric energy consumed per 1 km of a transport road, PLN·km−1; and CK—total cost of electric energy consumed for transport of persons on a road lkm, e.g., 100 km, in PLN.Cost of consumed electric energy after driving 1 km per 1 passenger, Convenient indicators for assessment of negative effects of transport may be emission yields referring to a person, e.g., COThe analysis of emissions during the operation of an electric car was carried out on the example of a 2018 Nissan Leaf. The basic parameters of the car are presented in 2 emission per 1 kWh considering that energy comes only from renewable energy sources, with different share of electric energy form biogas plant and from wind power plant. The last three columns are the emissions of CO2 emission per 1 kWh considering energy mix (which include the mix of electric energy form fossil fuels and renewable energy sources) for Poland, China and Germany. An assumption was made that a renewable energy source, e.g., biogas, is fully controllable. To ensure self-sufficiency of a charging system based on renewable energy sources and independence from supply by an external power system, the power of a wind turbine and a biogas plant should be properly selected.When assessing effects of operation of electric vehicles and cars, a few scenarios were considered: the supply by renewable energy sources with different share of cooperated RES installation (biogas and wind)  and the 2 emissions in the world [2 per year [An assumption was made that a charging system  with supply operates as a power co-operative. This is a type of a commune co-operative that is established to improve relations in the environment (reduce emissions), satisfy energy demands of members and electric vehicles and sell power/energy. Usually, energy co-operatives are associated with production of energy from renewable sources. Examples of such co-operatives are: ‘Bywind Energy Co-operative’ from the United Kingdom or ‘Nasza Energia’ from Poland. Emissivity of the Polish, Chinese and German power mix is given as references values in he world  and in 2he world . Germanyper year  and prodper year  ) and unit CO2 emission yield per 1 kWh of consumed electric power, kWhq (Equation (9)) were determined.The values of unit COIn order to assess and compare selected electric transport means, different types of vehicles were chosen and their basic technical data are given in 2, SO2, NOx, CO and dust emission related to production of electric energy that is needed for each transport mode to cover a distance of 1 km;The comparison of the CO2 emission amount during production of electric energy necessary for travel by each transport mode per one passenger;The comparison of COThe calculation of cost of travelling 100 km per 1 passenger for each type of vehicle;The comparative life cycle assessment of selected electric transport means.The assessment includes:2, SO2, NOx, CO and dust related to production of electric energy that is needed to supply the selected electric means of transport (Equations (3)–(7)) was calculated based on the data about vehicle energy consumption per kilometre , prices of parts, toll fees, level of remuneration in transport companies, etc.Operation costs, as significantly important in transport, depend on many factors which can be divided into :InternalBased on electric energy consumption , costs oThe functional unit in this study is one passenger car with a service life of 100,000 km. The system boundary covers selected stages of the vehicle’s life cycle, combustion and operation . The incdsmr, and the energy consumption variability index, dminm, indicate a power system load curve fitting degree—the closer the value to the unity, the more even the course of the curve [The average daily load degree, he curve . From a he curve . It has he curve .The assumptions accepted in this study allow us to determine the period of electric car charging which is most advantageous for the power grid. Thus, all electric cars should be charged at night, which is rather difficult to do, due to the needs of electric cars users such as accessibility of charging stations and travel range of the cars. Similar conclusions are presented by Jain et al. in work , where tBoth development of electric vehicle charging infrastructure and storage of braking energy in containers, while considering the SmartGrid idea, fit in very well with the Vehicle to Grid (V2G) solution. The V2G interface, a telemetry and telecommunications engineering solution with a bidirectional energy flow: vehicles are charged in a so-called night low period of the power system load; in peak load periods, electric vehicles constitute a source of energy for the system. Vacheva et al.  indicate2 per one kWh consumed by electric vehicle and per one kilometre for scenario where the supply comes from the renewable energy sources with different shares of energy from biogas and wind power plant. As can be seen from 2 emissions connected with electric car operation. The emissions for different shares of energy from biogas and wind power plant suggests that the type of RES installation used for energy production have an influence on the CO2 emissions. When the energy for supplying electric car will in 100% come from the wind power plant the emissions factors per kWh and per kilometre will be the lowest from considered scenarios , while for supply of 100% by biogas plant will be the highest .2 per road and energy emitted by vehicles powered by conventional fuels, i.e., diesel oil and petrol, was presented  ) being EWhen starting the analysis under impact categories, particular attention was paid to assessing which of the ten considered categories may be the source of the greatest number of negative or positive environmental consequences in the life cycle and transport processes of selected road transport vehicles ,79.It was noticed that the highest level of potential harmful effects on the environment, in the case of all tested objects, is characterized by one category: marine aquatic ecotoxicity 340.3688 kg 1.4-DB eq for electric car, 62.5702 kg 1.4-DB eq for transport by trolleybus, 61.78502 kg 1,4-DB eq for transport by tram and 15.91686 kg 1,4-DB eq for electric bus. The results of the remaining impact categories from the life cycle assessment point of view show a very low level of significance, hence no further assessment was carried out. 2 eq/km , while the highest emissions were connected with trams . However, when calculating the amount of CO2 emission during production of electric energy necessary for travel by each transport mode per one passenger the lowest CO2 emissions is connected with electric bus transport (17.573 g/per person) and the highest for electric cars (49.594 g/per person).The cost analysis showed that the electric buses have the lowest cost of traveling 100 km per 1 passenger equal to EUR 0.19 compared to electric cars (ranging from EUR 0.76 to EUR 2.62 depending on the charging option), trams (EUR 0.44) and trolley bus (EUR 0.21). For the electric the emissions of toxic compound during production of one of electric energy that is needed for each transport mode to cover a distance of 1 km was the lowest (CO2 eq—IPCC method). On the other hand, the lowest greenhouse gas emissions are connected with tram transport (0.088 CO2 eq—IPCC method).Based on the LCA results it was found that the highest level of potential harmful effects on the environment, in the case of all tested transport means, is characterized by one category: marine aquatic ecotoxicity 340.3688 kg 1.4-DB eq for electric car, 62.5702 kg 1.4-DB eq for transport by trolleybus, 61.78502 kg 1,4-DB eq for transport by tram and 15.91686 kg 1,4-DB eq for electric bus. The greatest total negative environmental impact was caused by transport by electric car and the smallest negative environmental damage by an electric bus. For the electric cars the greenhouse gas emissions during life cycle were also the highest (0.223 kg COAssessment of tested electric transport modes for power, economic and ecological efficiency is ambiguous and depends on many variables. Therefore, it is difficult to compare public means of transport and electric cars. Electric cars provide better driving comfort and shorter travel times, although not always as they can get stuck in a traffic jam. This is where public transport, in particular trams, buses and trolley buses running in specially designated lanes come to the forefront. Individually, electric cars are vehicles which consume less electric energy; thus, unit costs of operation and emission of pollutants are lower. It is obvious, however, that electric means of public transport are of a greater carrying capacity which increases the efficiency of such vehicles.Comparison of trams, trolley buses, buses and electric passenger cars indicates that the most beneficial are electric buses, which do not need rails or overhead lines, thus initial investment costs are lower. The following charging methods can be applied to electric buses: plug-in, inductive charging, and charging with a pantograph. This brings positive effects of charging buses both from a municipal network of overhead lines and using standard charging stations.


Background: Infections, as well as adverse birth outcomes, may be more frequent in migrant women. Schistosomiasis, echinococcosis, and hepatitis E virus (HEV) seropositivity are associated with the adverse pregnancy outcomes of fetal growth restriction and premature delivery. Methods: A cohort study of 82 pregnant women with a history of migration and corresponding delivery of newborns in Germany was conducted. Results: Overall, 9% of sera tested positive for anti-HEV IgG. None of the patients tested positive for anti-HEV IgM, schistosomiasis, or echinococcus serology. Birth weights were below the 10th percentile for gestational age in 8.5% of the neonates. No association between HEV serology and fetal growth restriction (FGR) frequency was found. Conclusions: In comparison to German baseline data, no increased risk for HEV exposure or serological signs of exposure against schistosomiasis or echinococcosis could be observed in pregnant migrants. An influence of the anti-HEV serology status on fetal growth restriction could not be found.  The European Community (EU) is facing the greatest influx of refugees and migrants since the Second World War . A totalS. haematobium ova excretion in their urine [Schistosomiasis is a helminthic infection, with about 249 million people each year requiring preventive antiparasitic therapy in 78 countries, and is associated with significant morbidity worldwide. Prolonged urogenital schistosomiasis is known as a risk factor for bladder cancer . Schistoir urine ,11, no tir urine ,13. An air urine ,15,16,17Echinococcosis is a neglected tropical disease. In the developed countries of the northern hemisphere, cystic echinococcosis is imported predominantly by migrants and has a very low incidence . In GermHepatitis E is an infectious disease with worldwide occurrence, caused by the hepatitis E virus (HEV). Contaminated drinking water transmits HEV genotypes 1 and 2, and outbreaks are mostly associated with precarious hygienic conditions, while genotypes 3 and 4 are mainly found in industrialized countries and are spread zoonotically. The anti-HEV IgG seroprevalence is estimated to range between 2% and 38% in Middle Eastern and North African countries , whereasThe purpose of this research was the examination of the schistosomiasis, echinococcosis, and hepatitis E seropositivity prevalence and their association with the adverse pregnancy outcomes of premature delivery and fetal growth restriction (FGR). In total, 82 pregnant women with medical care in Germany and the corresponding newborns were included. Recruitment took place at five sites in Germany, including Jena (n = 35), Walsrode (n = 21), Halle (n = 13), Munich (n = 8), and Berlin (n = 5). Smoking was reported in 3.7% of the sample . No alcohol consumption was described in 95.2% of the sample, while monthly consumption or less was reported among 4.9%. Hypertension (1.2%), diabetes (3.7%), and previous anemia  were evident medical conditions. A total of 75.6% of women reported one or more previous pregnancies .One woman reported being HIV positive. HIV testing was unknown in 53.7% and negative in 45.1% of the sample. No positive test result for hepatitis B or C was evident .A total of 8.5% of the women reported gestational diabetes. Pregnancy-induced hypertension was evident in 2.4% and pre-eclampsia in 1.2% of the patients. Medication during pregnancy consisted of magnesium (9.8%), methyldopa (4.9%), and others (26.8%). No use of acetylsalicylic acid or metoprolol was reported. Serology was performed for schistosomiasis in 82 samples and for Echinococcus and hepatitis E in 62 samples, respectively. All samples tested negative for schistosomiasis and Echinococcus. Six of the 62 (9.7%) sera tested positive for anti-HEV. According to ethnicity, 1/3 (33.3%) of African, 4/34 (11.8%) of Oriental Asian, 0/12 (0%) of Caucasian, and 1/13 (7.7%) of “other” ethnicities tested positive for anti-HEV IgG.The sex of the newborns was equally distributed . Vaginal delivery occurred in 59.7% of the sample . C-section was necessary in 40.3% of cases . Newborns had a median gestational age at birth of 39.71 weeks (IQR 2.43), a median length of 51 cm (IQR 3.0), a median birth weight of 3318 g (IQR 623), and a head circumference of 35 cm (IQR 2.0). The median placental weight was 500 g (IQR 105.0). A total of 21% of newborns were admitted to the NICU. No neonatal death was reported. The median APGAR was 10 at 5 and 10 min. The arterial umbilical cord pH was reported as 7.29 (IQR 0.14). Preterm birth (<37 weeks) concerned five neonates (6.1%) with birth at a median gestational age of 32.3 weeks (IQR 6.5). Five neonates (6.1%) had low birth weight (<2500 g); four of them were simultaneously preterm born. Low birth weight infants had a median birth weight of 1700 g (IQR 1265) with a median percentile for birth weight of 35.0 (IQR 37.25), a birth height of 38.0 cm (IQR 40.00), and a head circumference of 42.5 cm (IQR 41.25). th percentile, a difference between the newborn´s gender of female  or male  was observed, but did not reach no significance (p = 0.25). The 10th percentile of birth weight by gestational age was underrun by seven newborns (8.5%) without any of them having a preterm birth (<37 weeks). In birthweight below the 10The examination of neither the birthweight nor the placenta/birthweight ratio for the anti-HEV IgG positive and negative subgroup revealed any significant differences, as displayed in p = 0.32), respectively. HEV Serology in the five preterm birth cases was negative. Serology in the low birth weight outcome (<2500 g) was negative in 4/5 cases (in one case serology was not conducted). FGR, defined as birth weight below the percentile, was observed in 5.3% and 16.7% for the anti-HEV IgG seropositive and seronegative subgroups (p = 0.04). The examination of newborns’ length and head circumference for the anti-HEV IgG positive and negative subgroups revealed no differences. There were no differences between subgroups for APGAR values after 10 min. For APGAR values after 5 min, the median was 10 in the HEV negative group (range 7 to 10) and 9 in the anti-HEV positive group (range 5 to 10). The difference demonstrated statistical significance  and more than a quarter from Oriental Asian (28%) countries of origin, with different modes of transport—was serologically investigated. Although no positive serology for schistosomiasis or echinococcosis was found in the reported cohort of 82 pregnant migrants, anti-HEV IgG tested positive in 9.7% of cases. These data demonstrate that, in comparison to the German anti-HEV-IgG seroprevalence of 15–20%, the prevalence in the reported mothers was not increased . These dAccording to ethnicity, 1/3 (33.3%) of African, 4/34 (11.8%) of Oriental Asian, 0/12 (0%) of Caucasian, and 1/13 (7.7%) of “other” ethnicities tested positive for anti-HEV IgG.Both birth outcome and FGR did not differ significantly between previously HEV-exposed and non-exposed women. The FGR rate of 6.5% (4/62) is in line with the referenced birth collective of Jena University Hospital during the recruitment interval (March 2017 to September 2018) of 7.7%. The impression of 16.7% FGR in the anti-HEV positive group could not determine a statistical trend or significance due to the limited group size of only six hepatitis E positive women. The statistically significant difference found in the five-minute APGAR value is not of clinical relevance, while the median was 9 vs. 10 in anti-HEV positive or negative women, respectively. The 6 anti-HEV IgG positive women  showed no differences in origin, transportation method during migration, or other demographic or outcome parameters compared with the 56 seronegative women.As shown in our previous work, the birth weight percentile outcome is influenced by height, the weight of the mother at delivery, migration transport modality, the count of previous pregnancies and previous births, pregnancy-induced and previous hypertension, preeclampsia, and previous diabetes . There aBirth outcome studies in migrant women are heterogeneous in results. A population-based Belgic study  reported an increased rate of perinatal mortality but no LWB (<2500 g) in the migrant group. Sub-Saharan African mothers’ offspring showed an elevated risk for LBW in comparison to Belgian mothers’ offspring . A systeDespite multicentric recruitment over 18 months, the sample size and, therefore, the generalizability of the result has to be considered as limited. Furthermore, it has to be mentioned that seroprevalence (IgG), and not present or recent infection (IgM), in association with adverse birth outcomes was addressed.A prospectively cross-sectional cohort study was performed examining pregnant women with migration history and their corresponding newborns between March 2017 and September 2018. Country of origin was defined as endemic for schistosomiasis according to the World Health Organization (WHO) . InclusiDemographics, age, and medical history were collected using a patient questionnaire in participants’ origin language. A standardized case report form (CRF) was used for data collection, and pseudonymization took place at the source. Items were: maternal height and weight, the country of origin, ethnic origin, smoking and alcohol consumption, medical conditions or medication, fetal gender, and pregnancy history, including gravidity and parity status as well as gestational age . Laboratory values were noted, if available, from maternity records or the clinical routine for the following: hemoglobin, eosinophils, HIV, hepatitis B (Hbs-Ag) and C status (Anti-HCV). After birth, primary (birth weight percentiles) and secondary pregnancy outcomes  were assessed. Calculation of birth percentiles for height, weight, and head circumference were performed according to Voigt et al. . Blood wThe Ethical Committee of the University Hospital Jena, Germany reviewed and approved the study . Study sites in Berlin, Munich, Halle, and Walsrode obtained concomitant votes. An Informed Consent Form in participants’ native language was signed by each woman, permitting data and serum sample use for scientific purposes. t-test was performed. For non-normally distributed metric data, a Mann–Whitney U-test was used. Nominal or ordinal data was analyzed using a χ2 test. Fisher’s exact test was performed for contingency tables. Significance was considered at a p-value < 0.05 (*). The statistical analysis was performed using SPSS Statistics Version 25. First, normal distribution assessment was completed using a Kolmogorov–Smirnov test. For normally distributed metric data and independent variables, a Data collection originally aimed at the evaluation of association between schistosomiasis seropositivity and adverse pregnancy outcomes. The detection of specific antibodies in serum samples was performed using a commercial ELISA assay . Tests were conducted according to the manufacturer’s instructions. The entire study cohort (n = 82) showed negative schistosomiasis serology.Serological testing for anti-HEV IgG and anti-HEV IgM antibodies was completed using the commercially available WANTAI enzyme-linked immunosorbent assay . The assay was performed according to the manufacturer’s recommendations. Absorbance was measured using a Microplate Reader  at 450 nm and 450/630 nm. Three serum samples underwent relevant hemolysis, inhibiting the serological anti-HEV testing; thus, anti-HEV results are only available for 62 patients.Echinococcus-ELISA IgG, reactivity Ratio >1.0 positive, Lübeck, Germany) was used for screening, followed by a Western Blot  for the confirmation of ELISA positive or borderline samples. A total of 62 samples were tested.For the serological diagnosis of echinococcosis, an enzyme-linked immunosorbent assay (Euroimmun, Anti-In comparison to German reference data, no elevated anti-HEV seroprevalence was observed in pregnant patients with a migration background, while testing for schistosomiasis and echinococcosis serology was completely negative. No influence of the serology status on FGR or birth outcome was found. Advanced serologic testing in relation to migration should be considered in prenatal care. The risk of migrants acquiring HEV infection, schistosomiasis, or echinococcosis during the escape to Germany should not be overestimated.


While previous studies identified risk factors for diverse pregnancy outcomes, traditional statistical methods had limited ability to quantify their impacts on birth outcomes precisely. We aimed to use a novel approach that applied different machine learning models to not only predict birth outcomes but systematically quantify the impacts of pre- and post-conception serum thyroid-stimulating hormone (TSH) levels and other predictive characteristics on birth outcomes.We used data from women who gave birth in Shanghai First Maternal and Infant Hospital from 2014 to 2015. We included 14,110 women with the measurement of preconception TSH in the first analysis and 3,428 out of 14,110 women with both pre- and post-conception TSH measurement in the second analysis. Synthetic Minority Over-sampling Technique (SMOTE) was applied to adjust the imbalance of outcomes. We randomly split (7:3) the data into a training set and a test set in both analyses. We compared Area Under Curve (AUC) for dichotomous outcomes and macro F1 score for categorical outcomes among four machine learning models, including logistic model, random forest model, XGBoost model, and multilayer neural network models to assess model performance. The model with the highest AUC or macro F1 score was used to quantify the importance of predictive features for adverse birth outcomes with the loss function algorithm.th, 6th, and 7th among 14 features, respectively, in predicting birthweight, induction, and preterm birth, and 3rd among 19 features in predicting low Apgar score.The XGBoost model provided prominent advantages in terms of improved performance and prediction of polytomous variables. Predictive models with abnormal preconception TSH or not-well-controlled TSH, a novel indicator with pre- and post-conception TSH levels combined, provided the similar robust prediction for birth outcomes. The highest AUC of 98.7% happened in XGBoost model for predicting low Apgar score with not-well-controlled TSH adjusted. By loss function algorithm, we found that not-well-controlled TSH ranked 4Our four machine learning models offered valid predictions of birth outcomes in women during pre- and post-conception. The predictive features panel suggested the combined TSH indicator (not-well-controlled TSH) could be a potentially competitive biomarker to predict adverse birth outcomes. Thyroid hormones are vital for human metabolism, energy production, early placental development, and fetal neurodevelopment . ThyroidThe mechanism behind any effect of TSH levels on birth outcomes has not been revealed completely yet . Dysfunc2017 Guidelines of the American Thyroid Association (ATA) for the Diagnosis and Management of Thyroid Disease During Pregnancy and the Postpartum referred a TSH of 2.5 mIU/L as the upper limit for TSH control in the first trimester  or birth outcomes, and 14,110 pregnant women were included finally. The second way of analysis included 3,428 subjects from the first analysis who also had TSH data in the first trimester. The study protocol was approved by the ethics committee of the Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine.vs full-term delivery , neonatal low Apgar scores (<7) vs normal Apgar Score (>=7), and neonatal birthweight . According to the Chinese Perinatal Medical Association, TSH in early pregnancy was recommended to be controlled within 0.1–2.5 mIU/L  subjects’ demographic features such as age, occupation, and ethnicity (2); previous pregnancy history such as gravidity, parity, and cesarean scar uterus (3); symptoms and comorbidities such as gestational diabetes, gestational hypertension, preeclampsia, fever, renal disease, and placenta previa (4); number of fetus (5); pre- and post-conception TSH. The outcome characteristics included neonatal Apgar scores (0–10), neonatal birthweight (g), gestational age (week), and labor induction. We used one-hot encoding to convert the polytomous variables among the predictive variables into dummy variables in order to facilitate machine identification. For the dependent variables, we converted them into dummy or categorical variables: preterm birth  .5 mIU/L ; hence, The outcome variables showed class imbalance at large; for instance, among the 14,110 pregnant women included in the first analysis, only 5.9%, 835 subjects, had a preterm birth. We used Synthetic Minority Over-sampling Technique (SMOTE) to balance the categorical data . After aWe used various machine learning predictive models, including logistic model, random forest model, XGBoost model, and deep learning neural network models to predict the birth outcomes. Eighteen converted dummy predictive variables including demographic features, previous pregnancy history, symptoms and comorbidities, number of fetus, and TSH conditions were adjusted for each model. In the first analysis, we included abnormal preconception TSH as a predictive feature. In the second analysis, we included abnormal preconception TSH or not-well-controlled TSH as a predictive feature. We established the confusion matrix of the test set and calculated the accuracy, precision, recall, F1 score, and AUC for test set in each model. Then the model with the best performance—highest AUC for dichotomous outcomes or macro F1 score for categorical outcomes—was selected to sort each feature’s importance with the loss function algorithm.The structure of the multilayer neural network model consisted of six layers . The parameters used to build the model were optimized using stochastic gradient descent (SGD) algorithm using a batch size of 128.Whereas many models came with the algorithms that calculated feature importance, most of them were complex and rarely represented the significance of a feature directly. In this study, the indicator “percentage increase of loss (%incloss)” after a feature removal was employed to describe the importance of a feature (variable). The loss function for dichotomous and polytomous outcome variables is cross entropy , and theThe calculation formula of cross entropy for the dichotomous outcome variables isiy is the outcome variable, ip is the predicted probability of outcomes, and n is the number of outcomes.where The calculation formula of cross entropy for the polytomous outcome variables isiy is the outcome variable, ip is the predicted probability of outcomes, n is the number of outcomes, and c is the number of categories.where The calculation formula of the percentage increase of loss isj is the number of feature variables, jloss is the model loss before feature removals, and j-1loss is the model loss after a feature removal.where If %incloss>0, the feature is considered necessary for model prediction; if %incloss=0, this feature is considered not affecting the model prediction; if %incloss<0, this feature is considered unnecessary for model prediction and the performance of the model would improve after removing this feature.We did all analyses using Python (version 3.7.3).Predictive characteristics including pre- and post-conception TSH levels for subjects in the first and second analyses were shown Table 1.We also incorporated tables with both predictive characteristics and outcomes for the first and second analyses 2. We foIn the first analysis, the XGBoost model showed the best performance with the highest AUC compared to others except predicting induction, and it also displayed better performance in predicting low Apgar scores (<7) and birthweight with multiple categories Table 2.In the second analysis, we then compared the AUC (or macro F1 score) of the prediction of birth outcomes adjusted for two different derivatives from pre and post TSH levels (1): abnormal preconception TSH (2), not-well-controlled TSH  than that of other models. It was also indicated in The difference in predictive characteristics ranking between both analyses of subjects with abnormal preconception TSH could be attributed to the difference in underlying conditions of two groups of subjects. The subjects in the second analysis were the subgroup of the subjects in the first analysis. Although subjects in both analyses shared the similar age structure, the levels of preconception TSH in the second analysis were significantly higher than that in the first analysis. Abnormal preconception TSH and not-well-controlled TSH showed similar rankings to predict birth outcomes, while the latter had potential to predict induction. Although the mechanism behind this was not clear, the combined TSH indicator could be a competitive biomarker for maternal health.th out of 14 in both analyses and showed the capability of predicting preterm birth. Also, it had the third place in the prediction of birthweight in the second analysis. Therefore, it can be concluded that the importance of preconception TSH levels in predicting adverse birth outcomes was beyond average level. This finding was consistent with the existing literature on the relationship between pre-pregnancy TSH and birth outcomes, such as preterm birth. Chen et al. introduced 2.5 mIU/L as a cutoff for preconception TSH levels in their study, where they found that compared with mothers with a TSH level between 0.48 and 2.50 mIU/L, those with a TSH level of 2.50–4.29 mIU/L prior to conception had a higher risk of preterm birth   . Further04–1.15) . A cohor04–1.15) . TherefoIn the second analysis, we defined either pre- or post-conception TSH beyond 0.1–2.5 mIU/L was considered as not-well-controlled TSH, which indicated a higher risk of thyroid dysfunctions (hyperthyroidism or hypothyroidism). Although some papers may argue hyperthyroidism is defined as suppressed  thyrotropin (TSH) and elevated levels of triiodothyronine (T3) and/or estimated free thyroxine (free T4) , 23, we Many studies have discussed the effects of hypothyroidism pre- and post-pregnancy on the maternal and offspring’s health outcomes. Kiran et al.  found thHowever, there were still some limitations in this study. First, the study did not consider incorporating FT4 and anti-thyroid antibodies in the prediction of birth outcomes. The recently published paper implied that FT4 had more impacts on birth outcomes (like birthweight) than TSH did . TSH migIn conclusion, we examined four machine learning models to predict birth outcomes, namely, preterm birth, birthweight, low Apgar score, and induction. The XGBoost model provided the most robust prediction overall and performed better on categorical outcomes. We also created a novel indicator, not-well-controlled TSH, by combining pre- and post-conception TSH. The novel indicator performed well, and the highest AUC of 98.7% happened in XGBoost model for predicting low Apgar score with this TSH indicator. The predictive panel suggested not-well-controlled TSH had top ranks in predicting specific adverse birth outcomes. This competitive biomarker and machine learning tools are expected to be more widely used in the realm of precisely perinatal medicine. More novel indicators from thyroid hormones including T4 and anti-thyroid antibody are waiting to be excavated. And the quantifications of predictive features on maternal and offspring’s health will be thriving in future studies.jinlp01@163.com.The data analyzed in this study is subject to the following licenses/restrictions: The application to the dataset should be approved by the Shanghai First Maternity and Infant Hospital. Requests to access these datasets should be directed to The studies involving human participants were reviewed and approved by the Ethics Committee of Shanghai First Maternity and Infant Hospital. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.YS: study conception and design; project administration; data collection; data analysis; writing—original draft preparation. WZ: study conception and design; project administration; data collection; data analysis; writing—original draft preparation. LZ: data analysis. HZ: data collection and cleaning. XL: data collection and cleaning. CZ: model validation. WM: model validation. DT: data analysis and checking. K-HY: writing—review and editing. SX: manuscript review and revision. LJ: study conception and design; project administration. JH: study conception and design; project administration. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China , the Shanghai Municipal Commission of Health and the Family Foundation for Fifth Round of the Three-Year Public Health Action Plan of Shanghai (GWV-1.1 and GWV-10.1-XK08 and 202040186), and for Young Talents (2017YQ023). K-HY was supported by the Harvard Data Science Fellowship. Natural Science Foundation of Shanghai (21 ZR 1438400).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.