Given the little variability among commercialised eggplants mainly in developed countries, exploring, and structuring of traditional varieties germplasm collections have become a key element for extending ecotypes and promoting biodiversity preservation and consumption. Thirty-one eggplant landraces from Spain were characterised with 22 quantitative and 14 qualitative conventional morphological descriptors. Landraces were grouped based on their fruit skin colour . Landraces B7, B20, and B24 were left out for their distinctive fruit characteristics. Wide variation for plant, leaf, flower, and fruit phenology traits was observed across the local landraces, and fruit descriptors were considered the most important ones. In a second experiment, landraces, B14, B16, and B17 were selected to determine fruit quality. By contemplating the benefits provided by antioxidants and sugars for human health, pulp antioxidant capacity, total phenolic, ascorbic acid, carotenoid, flavonoid, and total sugar content were determined. Significant differences were observed across these three landraces, and B14 was highlighted for its antioxidant properties, while B17 stood out for its high sugar content. B16 did not stand out for any traits. The results indicate the wide variability in eggplants for their phenotypic and nutritional characteristics, which emphasises the importance of traditional varieties as the main source of agricultural biodiversity. Nutritional habits have vastly changed, and the consumption of fruit and vegetables has grown thanks to the abundance of health-promoting compounds found in them  has become a highly appreciated crop. Of 120 vegetables evaluated to determinate their antioxidant capacity, eggplant was ranked in the top 10 for its oxygen radical absorbance capacity, mediated mainly by fruit's phenolic constituents  as the biodiversity of the territory has been severely diminished by widely cultivated commercial hybrids. In this context, 31 eggplant landraces were selected from the plant resources stored in the genebank of the Institute for the Conservation and Improvement of Valencian Agrobiodiversity  and the Valencian Institute for Agrarian Research . Even if the majority of the selected eggplants had black-purple or striped skin, other less common varieties were included in the assay, since having a high degree of diversity was advantageous, both for their possible use in breeding programmes and for promoting their conservation. Once the phenotypic data had been collected, the nutritional and nutraceutical characteristics of three selected landraces were determined in order to gain benefits derived from their use.The work herein presented is divided into two main experiments: one focuses on phenotypic characterisation and the other on nutritional quality. They were carried out in two consecutive years (2019 and 2020).S. melongena L.) were provided by the genebanks at the COMAV and the IVIA (Spain). The passport data are indicated in 1:5 at 25°C: 0.289 dS m−1.Seeds of eggplant landraces (−1) of 200 N, 50 P2O5, 250 K2O, 110 CaO, and 35 MgO, as recommended by Maroto Borrego (http://riegos.ivia.es/) , For the first-year experiment, 31 eggplant landraces were sown on 5 March 2019 and seedlings (8 plants per landrace) were planted on 2 May 2019. Plants were grown in single rows placed 120 cm apart leaving 60 cm between each plant. Irrigation of plants satisfied 100% of the crop evapotranspiration (ETc) as described in Penella et al.  with a d Borrego . The avehttp://riegos.ivia.es/) , During the second-year experiment, landraces B14, B16, and B17 were chosen as being representative of the main fruit colour groups, namely, G1: black-purple, G2: striped and G3: white, to analyse fruit quality and to, thus, provide verified information on their added value and to facilitate their trade. Landraces from G4 group and outliers  were not considered due to their reduced number of representatives and unsuitable qualities for cultural practises and market observed in experiment 1 . Seeds were sown on 7 March 2020 and seedlings (10 plants per landrace) were planted on 13 May 2020. Agronomic culture practises were similar as in the first-year experiment. The average range of the minimum and maximum temperatures was 11–31°C for May, 14–31°C for June, 18–33°C for July and 19–34°C for August , a* (red/green chromatic coordinates) and b* (yellow/blue chromatic coordinates) measures were recorded in order to determine leaf colour. L*a*b* standard for colour measurement was chosen as it is perceptually uniform and device-independent  on the central part of the adaxial face. Two independent colour measures were taken in each plant, which gave 16 data per landrace. The percentage of dry weight (DW), pulp colour, antioxidant capacity, and total phenolic, flavonoid, ascorbic acid, carotenoid and sugar contents, were analysed in the mid-part of the pulp of harvested fruits in B14, B16, and B17 to determine if there were significant differences among them.In order to establish the percentage DW in fruits, the fresh weight (FW) of eggplants was recorded. Samples were dried at 65°C for 72 h in a laboratory oven. The DW percentage was calculated as (DW/FW) × 100.L* (lightness), a* (red/green chromatic coordinates), and b* (yellow/blue chromatic coordinates) measures were recorded in order to determine pulp colour immediately after eggplants were cut  at 15,000 g for approximately 1 min. Final extracts were divided into aliquots of 2 g, frozen in liquid nitrogen and stored at −80°C until further determinations were made.−5 M of 2,2-diphenyl-1-picrylhydrazyl (DPPH) in 80% methanol. The decrease in absorbance at 515 nm contrasted with a blank solution containing 80% methanol with no extract after a 30-min reaction time at room temperature and in the dark using a spectrophotometer . Antioxidant capacity was expressed as the 149 percentage reduction of the initial DPPH absorption in extracts.Antioxidant capacity was measured following the method reported by Brand-Williams et al.  with a f−1). Total phenolic content was expressed as mg gallic acid equivalent (GA) g−1 FW.Phenolic content was analysed as described by Dewanto et al.  with som2 0.5 M, and 0.15 mL of AlCl3. Next 6H2O 0.3 M was added and vortexed. Samples were incubated for 5 min at room temperature. Afterwards 1 mL of NaOH 0.1 M was added to the mixture. The absorption of solution was measured at 506 nm in a spectrophotometer . Total flavonoid concentration was compared to a standard curve using rutin (Merck Co.) as the standard (4.7–300 mg L−1). Flavonoid content was expressed as mg rutin equivalent g−1 FW.Flavonoid content was measured following the method reported by Du et al.  with som3PO4, 0.2 mL of 4% (w/v) 2,2'-dipyridyl, and 0.1 mL of 3% (w/v) FeCl3 were added to the previous solution. The mixture was incubated in a water bath for 40 min at 42°C. The absorption of solution was measured at 525 nm in a spectrophotometer . Ascorbic acid was expressed as mg AsA 100 g−1 FW.Ascorbic acid content was spectrophotometrically determined according to Kampfenkel et al. . The sam−1 FW:The carotenoid concentration was determined spectrophotometrically as reported by Porra et al. . The samWhere Chl a and Chl b were the chlorophyll a and b contents, respectively, and were calculated by Equations (2) and (3); Abs is the absorption of samples at a specific wavelength (nm):−1 FW.Soluble sugar content was spectrophotometrically determined according to Calatayud et al.  with sevp ≤ 0.05).The results obtained from the evaluated parameters underwent a one-way ANOVA analysis in Statgraphics Centurion XVII  using the selected landraces as the factor of analyses. The results were expressed as the mean ± standard deviation (SD). The means were accepted as being significantly different at a 95% confidence interval  was run for the standardised values using pairwise Euclidean distances among accession means to determinate any relations between genotypes. The extracted eigenvalues, and the relative and cumulative proportions of the total variance explained by the first three components, were calculated. Two-dimensional (2D) scatter plots  were prepared based on a distance matrix for the principal components to visualise the relation that explained traits. For the PCA analysis, the phenotypic data pertaining to the 31 landraces was considered together.n = 31); (2) dry weight, pulp colour and antioxidant traits of the selected landraces .Furthermore, two correlation analyses, in which the individual samples of each accession were subjected to linear regression and the correlation coefficients (r), were completed among the: (1) selected phenotypic quantitative traits of each landrace  were characterised by an erect plant growth habit, medium relative internode length, weak stem anthocyanin pigmentation, strong leaf pilosity and bright violet flowers. The fruits themselves stand out for their oval, pear or deck shape, and were much longer than they were wide, with a rounded or depressed apex, no curvature, white to greenish pulp and their long, but not very prickly calyx.The landraces grouped for their striped fruit-skin (G2) were mostly characterised by an intermediate prostrate growth habit, medium relative internode length, large hairy leaves and pale flowers. Their fruits were elongated, non-curved with a depressed apex, white pulp, many prickles on the calyx and they were considerably heavy. Dark yellow and purple colours predominated on their skin, along with a striped or compensated colour distribution.Three of the landraces in this study had white skin fruits (G3) and generally presented short internodes, prostrate growth habit, weak stem pilosity, absence of anthocyanins on the stem and many bright violet flowers. The aforementioned fruits had white pulp, many prickles, an oval-ovoidal shape and no curvature.Only two accessions that produced reddish-purple fruit were detected (G4). These plants presented erect-intermediate growth habit, dense branching, short internodes, weak stem pilosity, and bright violet flowers. Their fruits were elongated, ellipsoid-shaped and curved, and they presented a rounded apex, white pulp and a few prickles on the calyx.Landraces B7, B20, and B24 were not included in any of the groups because of their distinctive fruit typology. Variety B7 had globular fruits that were equally green and purple in colour, and were very light and small in size. This landrace was also notable for its high anthocyanin content on its hairy stem. The B20 entry had very elongated ellipsoid fruits that were green in colour with no prickles on the calyx. Finally, landrace B24 had mostly green and globular-shaped fruits, but with yellow stripes on the lower part. They also characterised for their white pulp and elevated weight.Correlation analyses were carried out to estimate the relation between the most important quantitative traits . The paip < 0.05 or p < 0.001) were found among the average values in the selected eggplant landraces for all the analysed nutraceutical compounds, but not in the DW percentage  were characterised to establish fruit quality. Significant differences , −2.38 to 1.6 (a*) and 15.11–22.87 (b*) for the studied landraces. Focusing on colour parameter L*, significant differences were found between landraces, turning B17 to own a lighter pulp colour . When analysing colour parameter a*, it was observed that landrace B14 had a greener pulp tonality . Also, in accordance with b* parameter data, landrace B14, showed a much more yellowish pulp , what differentiated this variety from B16 and B17.The ter cut,  ranged f−1 FW) compared to B16 and B17, with no differences found between them. Antioxidant capacity was 17.56% higher (1.8-fold) in B14.Antioxidant capacity was determined by the DPPH assay  and its −1 FW. B14 obtained a significantly higher mean value for phenolic content (4.47 mg g−1 FW), with no differences between B16 and B17 . Phenolic concentration was 1.7-fold higher in landrace B14, which was 42% higher than for the other varieties.The total phenolic content  for the −1 FW among the three landraces. Significant differences were found in the three landraces in relation to the total flavonoid content. Landraces B16 and B17 did not show any significant differences in the flavonoid concentration, and their mean values were 27.25 and 26.1 mg 100 g−1 FW, respectively. B14 stood out for its high flavonoid content . The flavonoid concentration was 59.4% higher in B14, which was 2.5-fold higher than B16 and B17.The total flavonoid content  ranged b−1 FW for the three landraces. Significant differences were found in the three landraces. Landrace B16 had a statistically lower ascorbic acid content  compared to B14 and B17 , with not differences between them. The ascorbic acid concentration was 60% lower in B16, which is 2.5-fold lower than B14 and B17.The ascorbic acid content  range wa−1 FW for the three landraces. The ANOVA analysis showed that landrace B14 had the highest carotenoid content . Accessions B16 and B17 did not show significant differences between them and, respectively, presented 1.65 and 1.78 μg g−1 of FW carotenoids as the mean value. The carotenoid concentration was 55.6% (2.27-fold) lower in B16 and B17 compared to B14.The total carotenoid content  range wa−1 FW, which is a 1.57-fold increase in content. Considerable differences were found in the studied landraces. B17 had a significantly higher mean value for sugar content (6.48 g 100 g−1 FW), and no differences were reported between B14 and B16 . Sugar content was 20.64% higher in B17, which is 1.25-fold increase compared to B14 and B16.The sugar content  for the b* value and four of the five nutraceutical compounds . By contrast, a strong but negative correlation was observed between a* and carotenoids content (r = −0.9771) while it was moderate and positive between L* and sugar content (r = 0.6226). When comparing nutraceutical compounds, four strong significant and positive correlations were recorded between the combinations of DPPH vs. phenolics, DPPH vs. flavonoids, DPPH vs. carotenoids, and phenolics and flavonoids, where the coefficient r ranged from 0.7955 to 0.8322. Phenols vs. carotenoidsalso showed moderate and positive correlation (r = 0.6898). Related to sugar content, it was positively correlated with carotenoids content (r = 0.6302).In order to estimate the contribution of the quality traits in the pulp of the fruits, several correlation analyses were carried between the different combinations of the percentage of DW, colour, nutraceutical compounds and sugar data . The paiThe morphological diversity of eggplant landraces has been the subject of many studies  and width (r = 0.359 and r = 0.3974). A larger foliar area can offer better accumulation of photosynthates in plants, to ultimately produce heavier and larger fruits  and width (r = 0.4208), while the absence of calyx prickles is desirable for harvest processes or consumer handling. On the contrary, a negative, but statistically significant, correlation occurred between the calyx length ratio and fruit length (r = −0.6542). Owning a short calyx (~20%) is a desirable attribute from the phytosanitary point of view since it helps to prevent eggplants from white mites, Botrytis cinerea and several fungal diseases, whose presence is favoured by relative high humidity as petals are adhered between the calyx and fruit , while showing a negative tendency toward a relation with big and heavy fruit. Altogether would mean that plants with great number of flowers, which are also able to develop many eggplants per plant, would develop small calibre fruits. This tendency has also been described by other authors in eggplants , which was 42% higher than in B16 (2.53 mg g−1 FW) and in B17 (2.61 mg g−1 FW). These results are higher than the values reported by several authors   and red onion (2.53–3.11 mg g−1 FW) reached similar levels. Moreover, even if the phenolic content in eggplant is comparable to that found in many types of fruits, such as in strawberry (3.64 mg g−1 FW) , blueberry (4.25 mg g−1 FW), and blackberry (2.47 mg g−1 FW) , significantly exceeds the phenolic content of many others as apples (around 1 mg g−1 FW), sweet cherries (7.88 mg g−1 FW), raspberries (1.79 mg g−1 FW) or black grapes (2.13 mg g−1 FW) , while it came close to 26 mg 100 g−1 FW in landraces B16 and B17. However, other studies performed in different eggplant landraces unseat our candidates because they had much higher flavonoid concentrations; 1.733 mg 100 g−1 FW , red onion (36–56 mg 100 g−1 FW)     , dogwood berry (91.4 mg 100 g−1 FW)      , but not between ascorbic acid and phenols. Andarwulan et al. (r = 0.6302). This same relationship was detected by Ramaiya et al.  produce many flowers and somewhat elongated fruits of an attractive colour for consumers, while the reddish fruit entries (G4) produce elongated but not too heavy fruits, with a few thorns on the calyx, which could be interesting options. As the nutritional profile is helpful for promoting the commercialisation and consumption of local varieties, and according to the nutritional quality part of this study, variety B14 could be promising for human consumption, mainly for its antioxidant properties. Taken together, this information could be relevant for future plant breeding programmes to obtain easily manageable and harvestable eggplant varieties.The original contributions presented in the study are included in the article/ÁC, M-RM-C, and EM-I: conceptualization, validation, and investigation. ÁC, EM-I, M-RM-C, JM, and RM-F: methodology. EM-I and M-RM-C: formal analysis and writing—original draught preparation. ÁC and M-RM-C: data curation. ÁC, SS, MD, and JV: resources, writing—review and editing, supervision, and funding acquisition. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Low birthweight (LBW) is associated with metabolic complications, such as glucose and lipid metabolism disturbances in early life. The objective of this study was to assess: (1) the effect of dietary tryptophan (Trp) on glucose and fat metabolism in an LBW piglet model, and (2) the role peripheral 5-hydroxytryptamine type 3 (5HT3) receptors in regulating the feeding behavior in LBW piglets fed with Trp-supplemented diets. Seven-day-old piglets were assigned to 4 treatments: normal birthweight-0%Trp (NBW-T0), LBW-0%Trp (LBW-T0), LBW-0.4%Trp (LBW-T0.4), and LBW-0.8%Trp (LBW-T0.8) for 3 weeks. Compared to LBW-T0, the blood glucose was decreased in LBW-T0.8 at 60 min following the meal test, and the triglycerides were lower in LBW-T0.4 and LBW-T0.8. Relative to LBW-T0, LBW-T0.8 had a lower transcript and protein abundance of hepatic glucose transporter-2, a higher mRNA abundance of glucokinase, and a lower transcript of phosphoenolpyruvate carboxykinase. LBW-T0.4 tended to have a lower protein abundance of sodium-glucose co-transporter 1 in the jejunum. In comparison with LBW-T0, LBW-T0.4 and LBW-T0.8 had a lower transcript of hepatic acetyl-CoA carboxylase, and LBW-T0.4 had a higher transcript of 3-hydroxyacyl-CoA dehydrogenase. Blocking 5-HT3 receptors with ondansetron reduced the feed intake in all groups, with a transient effect on LBW-T0, but more persistent effect on LBW-T0.8 and NBW-T0. In conclusion, Trp supplementation reduced the hepatic lipogenesis and gluconeogenesis, but increased the glycolysis in LBW piglets. Peripheral serotonin is likely involved in the regulation of feeding behavior, particularly in LBW piglets fed diets supplemented with a higher dose of Trp. Newborns who fail to reach an estimated fetal biometric by a certain gestational age  are considered small for gestational age ,3,4. TheNutrition is one of the important factors that can influence the glucose and lipid metabolism during the fetal and postnatal periods . In partTryptophan (Trp) is a neutral essential amino acid, which, due to its role in the regulation of various physiological functions, may potentially be used for developing therapeutics for preventing and treating chronic diseases . DietaryThe experimental procedures used in this study were in accordance with the FASS Guide for the Care and Use of Agricultural Animals in Research and Teaching  and wereThe body weight (BW) at day 7 postpartum was used as a criterion for considering pigs as LBW or normal birthweight (NBW). Seven-day-old piglets with a BW < 2 kg were considered as LBW, and piglets with a BW ≥ 2 kg were considered as NBW, in accordance with previous studies ,35. NBW ad-libitum access to their diets during each meal and were provided a minimum 60 g dry matter/kg BW/day of milk replacer, as previously suggested [Milk replacer powder was formulated for piglets , accordiuggested ,40.The milk replacer intake for each offering was measured by recording the volume of added milk to feeders and the leftover milk in the feeders, prior to the next feeding. Body weight and growth measurements, including heart girth, body length, and wither size, were recorded biweekly. The average daily gain , average dry matter intake , average daily protein intake /experimental days), gain:feed ratio , and gain:protein ratio  were calculated.Individual thermal images were captured biweekly using a FLIR C2 compact thermal camera, with focal length of 1.54 mm and thermal accuracy of ±2 °C . The camera was positioned roughly 1 m above of each pig. The emissivity coefficient was set at 0.96. To measure the piglets’ core body temperature, the rectal temperatures (RT) were measured biweekly for all piglets using an electronic thermometer.The role of 5HT3 receptors in mediating the effect of experimental diets on the DMI of the pigs was evaluated by the administration of ondansetron hydrochloride , a selective 5-HT3 receptor antagonist, and vehicle . Following an overnight fast, ondansetron   and saliDuring the diet preparations, the feed samples (~50 g) were collected from each feed bag and combined for each diet. Afterwards, they were stored at −20 °C, until feed composition analysis.®, Franklin Lakes, NJ, USA). The blood samples were centrifuged at 3000× g for 15 min at 4 °C, and the serum and plasma were separated and stored at −80 °C for further analysis. Following the blood collection at 120 min after the meal test, all pigs were euthanized using the CO2 asphyxiation method. As previously described [After an overnight fast (8 h) at week 3, the pigs were allowed to consume their respective diets for 1 h. Blood samples were collected at baseline and then at 60 and 120 min after the meal test from the jugular vein in the supine position into 10 mL serum tubes and 3 mL heparin containing plasma tubes  were analyzed by Servi-Tech laboratory  , as prev2) was determined using the following equation: σε (Ts4 − Tα4), where σ is the Stefan Boltzmann Constant (5.67 × 10−8 W/m2K4), ε is the thermodynamic emissivity (0.95), Ts is the body surface temperature (kelvin), and Tα is the ambient temperature (kelvin) [Using a free drawing tool of the FLIR camera software (FLIR Research Studio software), a region of interest was drawn in a rectangular shape on the entire back of the piglets, roughly from shoulders to the rump of the animal , to obta(kelvin) ,47.The plasma glucose, triglycerides, and cholesterol concentration were determined by a chemistry analyzer system , following calibration with a calibrator , using reagents  for glucose , cholesterol , and triglycerides , and recording the absorbance at 340 nm for glucose and at 505 nm for triglycerides and cholesterol.https://imagej.nih.gov/ij/download.html).Duodenum and jejunum segments were fixed in 10% formaldehyde, coated in paraffin, cut into 5 μm thick sections, and stained with hematoxyl and eosin. Ten well-oriented villi and crypt in each section were used to measure the villus height, villus width, crypt depth, crypt width, and muscle thickness  using a −∆∆CT method.RNA isolation and RT-qPCR were performed for glucose transporter 1 (GLUT1), glucokinase (GCK), liver-type phosphofructokinase (PFKL), liver-type pyruvate kinase (PKLR), pyruvate carboxylase (PC), phosphoenolpyruvate carboxykinase (PEPCK), glucose-6-phosphatase (G6PC), glucose transporter 2 (GLUT2), lipoprotein lipase (LPL), cluster of differentiation 36 molecule (CD36), fatty acid synthase (FAS), acetyl-CoA carboxylase (ACC), hydroxyacyl-CoA dehydrogenase (HADH), sterol regulatory element binding transcription factor 1 (SREBP-1), peroxisome proliferator activated receptor alpha (PPARα), and PPARG coactivator 1 alpha (PGC1α) in the liver, following our published procedures ,49,50. TWestern blot was conducted in hypothalamus for tryptophan hydroxylase 2 (TPH2), jejunum for TPH2, sodium/glucose cotransporter 1 (SGLT1), and glucose transporter 2 (GLUT2), duodenum for SGLT1 and GLUT2, liver for carnitine palmitoyltransferase I α (CPT1α) and GLUT2, and white adipose tissues for CPT1α , as prev® Instruments, Inc. Highland Park, VT). The intra-assay coefficient of variation (CV) was 4.8%. The insulin resistance indicator, HOMA-IR, was calculated, as previously described [The plasma insulin concentration was determined using a porcine ELISA kit, according to the manufacturer’s instructions . The optical density was read at a 450 nm wavelength using an Epoch microplate spectrophotometer , followed by a post hoc Dunnett’s test . The plasma glucose concentration distribution was not normal at 60 min after the meal. Therefore, an inverse distribution function  was used to normalize the data at this time point. The mixed procedure was used for the analysis of blood glucose, DMI, BW, rectal temperature, and thermal radiation, with diet, time, and the interaction of diet and time as fixed variables and pigs as a random variable. As previously described ,43,50, tOverall, except for the G:F ratio, the effect of diet on the initial BW, final BW, ADG, ADMI, ADPI, G:P ratio, heart girth, wither height, and body length was significant . NBW-T0 p < 0.05), but no differences in DMI were seen among the other groups. The effect of diet on BW was significant, with 9310, 6838, 6687, and 6787 g for NBW-T0, LBW-T0, LBW-T0.4, and LBW-T0.8, respectively  for thermal radiation, and the rectal temperature were detected among the treatments C–F.The histomorphometry data showed a tendency toward a greater villus height to crypt depth ratio in NBW-T0, compared to LBW-T0 in duodenum . Comparep < 0.01; p = 0.083; Overall, the effect of the drug on DMI was significant (No differences in blood glucose were observed among the treatments at 0 and 120 min following the meal test A. HoweveCompared to LBW-T0, the mRNA abundance of GLUT1 was higher in NBW-T0 A. Relatip < 0.05, The effect of diet on the mRNA abundance of liver ACC and HADH was significant (The protein abundance of SGLT1 tended to be lower in LBW-T0.4, compared to LBW-T0, in the jejunum D. MoreovLBW is not only associated with health complications in the long term ,6,7,8, bTo our knowledge, this is the first report on the effect of dietary Trp on glucose metabolism in LBW neonates. The plasma glucose concentration was decreased at 60 min after a meal test in LBW-T0.8. Similarly, others showed that dietary supplementation of Trp reduced hyperglycemia  and its Little is understood about the effect of Trp on biochemical pathways involved in glucose metabolism in LBW neonates. To our knowledge, the intestinal absorption of glucose and the dynamics of glucose metabolism in liver, particularly glycolysis and gluconeogenesis, have not been elucidated in LBW neonates receiving Trp-enriched diets. For the first time, here we show an increased hepatic mRNA abundance of GCK, decreased PEPCK transcript in the liver, and reduced hepatic GLUT2 gene and protein abundance in the LBW-T0.8 group. Further, the protein expression of SGLT1 in the jejunum and GLUT2 in the liver was decreased in the LBW-T0.4 group. Unlike our study, where we showed an increased mRNA abundance of GCK in LBW-T0.8, others have either failed to detect a change in the hepatic GCK mRNA expression in rats fed with diets supplemented with Trp  or showeIn the current study, for the first time, we show a decreased plasma triglyceride concentration in LBW-T0.4 and LBW-T0.8 piglets. In agreement with our data, dietary Trp supplementation reduced the serum lipids in rats  and the While the role of brain serotonin, as an anorexigenic hormone in the regulation of feeding behavior, is documented ,29,30,84To our knowledge, this is the first study assessing the effect of dietary Trp on glucose and lipid metabolism in LBW neonates. We demonstrated that supplemental Trp improves the glucose and lipid metabolism in an LBW piglet model through reducing hepatic lipogenesis, gluconeogenesis, and glucose efflux and increasing lipolysis and glycolysis. Further, we provided evidence of the role of peripheral serotonin in the regulation of feeding behavior and a lower serotonergic signaling in LBW piglets receiving no Trp supplement. Further research on the endocrine regulation of metabolic pathways involved in glucose and lipid metabolism following the administration of Trp in LBW neonates is required.


Dialister and Megamonas and lower abundance of Anaerotaenia and Gracilibacter at the genus level. All four selected genera explained 15% of the variance of ADHD, and this microbial signature achieved an overall sensitivity of 74% and a specificity of 71% for distinguishing between ADHD patients and healthy controls. We also tested whether the selected genera correlate with age, body mass index (BMI), or scores of the ADHD rating scale but found no evidence of correlation between genera relative abundance and any of the selected traits. These results are in line with recent studies supporting gut microbiome alterations in neurodevelopment disorders, but further studies are needed to elucidate the role of the gut microbiota on the ADHD across the lifespan and its contribution to the persistence of the disorder from childhood to adulthood.Compelling evidence supports alterations in gut microbial diversity, bacterial composition, and/or relative abundance of several bacterial taxa in attention-deficit/hyperactivity disorder (ADHD). However, findings for ADHD are inconsistent among studies, and specific gut microbiome signatures for the disorder remain unknown. Given that previous studies have mainly focused on the pediatric form of the disorder and involved small sample sizes, we conducted the largest study to date to compare the gastrointestinal microbiome composition in 100 medication-naïve adults with ADHD and 100 sex-matched healthy controls. We found evidence that ADHD subjects have differences in the relative abundance of several microbial taxa. At the family level, our data support a lower relative abundance of Gracilibacteraceae and higher levels of Selenomonadaceae and Veillonellaceae in adults with ADHD. In addition, the ADHD group showed higher levels of  Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a persistent pattern of symptoms of inattention, hyperactivity, and impulsivity, resulting in dysfunction in two or more areas of an individual’s life ,2,. ADHDThe prevalence of ADHD in children is approximately 5.3%, and of these, 50−70% will still show symptoms in adulthood . The etiThe gut microbiome is essential for health and plays a role in the bidirectional regulation of the brain-gut axis. Microorganisms influence the brain through their ability to produce and modify many metabolic, immunological, and neurochemical factors in the gut that ultimately impact the central nervous system –10; in tBifidobacterium in individuals with ADHD, changes that were associated with a significantly enhanced predicted synthesis of the dopamine precursor phenylalanine [Dialister, Lachnoclostridium, Sutterella, and Faecalibacterium in treatment-naïve children with ADHD compared with healthy controls and a negative association between the abundance of the last taxonomic group and parental reports of ADHD symptoms [Faecalibacterium, as well as higher amounts of Odoribacter and Enterococcus, in ADHD patients [Neisseria and decreased Prevotella and Parabacteroides in ADHD subjects [Fusobacterium genus as a marker for ADHD as well as enrichment of Lactobacillus in the control group [Ruminococcaceae _UCG_004 genus and ADHD inattention symptoms [Consistently, an increasing number of studies have shown gut microbiome alterations in neurodevelopmental disorders –19. For lalanine . Similarsymptoms . These rpatients . Moreovesubjects . Wang etol group . Finallysymptoms . All theAdditionally, clinical evidence shows that probiotic intervention in early life may improve later outcomes and reduce the risk of neuropsychiatric disorders , and micConsidering this background, we performed the largest characterization of the gastrointestinal microbiome composition in 100 medication-naïve adults with ADHD and 100 sex-matched healthy controls and assessed differences in the microbiota composition between both groups and whether such differences were associated with ADHD clinical symptoms.The clinical sample consisted of 100 adult medication-naïve ADHD subjects (DSM-5 criteria) who were referred to an ADHD program from primary care centers and adult community mental health services. All subjects were evaluated and recruited prospectively from a restricted geographic area of Catalonia (Spain) in a specialized outpatient program for adult ADHD and by a single clinical group at Hospital Universitari Vall d’Hebron of Barcelona (Spain). A description of the sample is provided in Supplementary Table The clinical assessment consisted of structured interviews and self-report questionnaires in two different steps: (i) ADHD diagnosis was based on the results of the Structured Diagnostic Interview for Adult ADHD (DIVA 2.0)  by a psyThe control sample consisted of 100 unrelated healthy donors matched by sex and ethnicity with the clinical group. The exclusion criteria were ADHD symptomatology according to the Adult Self-Report Scale A.S.R. S v1.1. and any prior or current psychiatric comorbidity.All subjects reported European ancestry, which was confirmed through principal component analysis (PCA) using genetic data. Exclusion criteria for all participants included treatment with antibiotics or probiotics up to before stool collection.The study was approved by the Clinical Research Ethics Committee (CREC) of Hospital Universitari Vall d’Hebron. All methods were performed in accordance with the relevant guidelines and regulations, and written informed consent was obtained from all subjects before inclusion. None of the participants received any financial compensation.® PowerFecal® DNA extraction kit . The isolated DNA was quantified using PicoGreen™ dsDNA Assay Kit [Human fecal samples were collected at home, stabilized with the OMNIgene·GUT (OM-200) (DNA Genotek Inc.) kit, and then transported to the laboratory. The samples were aliquoted into 1.5-ml tubes and stored at −80 °C. Microbial DNA was purified from 200 mg of each homogenized fecal sample using the QIAampssay Kit .The V3−V4 hypervariable region of the bacterial 16S rRNA gene was amplified for microbiome composition profiling. DNA library construction was performed following the manufacturer’s instructions (Illumina). We used the same workflow as described elsewhere  to perfohttps://github.com/vegandevs/vegan). Beta diversity (between-sample diversity) was calculated by weighted and unweighted UniFrac and Bray Curtis distances, as represented by two-dimensional principal coordinates analysis (PCoA) plots, and compared between groups by permutation multivariate analysis of variance (PERMANOVA) using the phyloseq R package [https://github.com/sdray/adespatial). Canonical correspondence analysis (CCA), a multivariate constrained ordination method, on rarefied OTUs was performed and significance regarding the microbial community composition between groups was assessed by permutational multivariate analysis of variance (ADONIS) using the vegan R package (https://github.com/vegandevs/vegan).Alpha diversity (within-sample diversity) was calculated on rarefied data with the Richness, Simpson and Shannon diversity indices and compared between individuals with ADHD and controls using the vegan R package  > 10 using the DESeq2 and randomForest R packages for the classification, rfUtilities to estimate the significance of the classification and rfPermute to evaluate the significance of specific taxa, with 1000 permutations. All comparisons were performed at the phylum, family, and genus levels. Any unknown taxonomic level was assigned to the next highest known taxonomic rank.https://github.com/AndriSignorell/DescTools); sensitivity and specificity were calculated with the caret R package (https://github.com/topepo/caret/). A likelihood ratio test with the lmtest R package (https://cran.r-project.org/web/packages/lmtest/) was employed to assess whether the inclusion of selected genera in the multiple logistic regression model fits the data significantly better than the model including only age, sex, and BMI. In the first model, we considered affectation status as dependent variable and age, sex and BMI as independent variables (ADHD 〜 age + sex + BMI); in the second model, we included selected taxa as independent variables . Spearman correlation tests were used to assess correlations between selected genera, age, BMI, and inattention and hyperactive/impulsivity subscale scores or total scores of the ADHD rating scale.Genera showing significant differences in relative abundance between ADHD cases and controls after multiple comparison corrections in DeSeq2 and the random forest comparisons were considered for downstream analyses. Multiple logistic regression models were applied to test the association between ADHD and all selected genera while adjusting for age, sex, and body mass index (BMI). Adjusted Pseudo-R2 was calculated with the McFaddenAdj method and the DescTools R package  were found between ADHD cases and controls when measured by three different indices  . When we assessed whether they correlated with each other, we found a moderate correlation between Anaerotaenia and Gracilibacter , a weak correlation between Anaerotaenia and Megamonas , and no correlation between the others , which explained 5.9% of the variance  patients [Megamonas, have previously been associated with other psychiatric conditions that often coexist with ADHD, such as ASD or depression [These results are in line with recent studies supporting gut microbiome differences in neurodevelopmental disorders. Although the mechanistic explanation for these associations remains unknown, a positive correlation between toddlers . Additiopatients ,46, or ipatients  comparedpatients . Furtherpression , 47–51. Although previous gut microbiome analyses on ADHD have mainly focused on pediatric samples , 26–28 aWe did not detect substantial changes in alpha or beta diversity between ADHD cases and controls. The high heterogeneity in terms of age, sample size, sex, clinical characteristics, and type of controls may explain nonreplicable results and discrepancies between studies. We sex-matched ADHD cases and controls and restricted the clinical sample to ADHD medication-naïve adult subjects, which is a major strength of our study design that may allow us to identify an imbalance in the gut microbiome composition that might be neglected by broader study designs. In addition, the sample sizes of previous studies on ADHD, were relatively small; although our study may also have limited statistical power to estimate the magnitude of the differences identified in microbial relative abundance, we assessed the largest sample size considered thus far. The results, however, need to be interpreted with caution given that we selected genera of interest and estimated the variance in ADHD explained by these taxa as well as the sensitivity and specificity of the regression model using the same dataset, which may have led to overfitting and further support the use of independent datasets to obtain more accurate estimates.Microbiome composition is strongly influenced by environmental factors such as diet, overall health status, and medication use , 54–56. SupplementaryTablesSupplementaryTable_S2. Raw and clean number of sequences, mean length, total mega bases sequenced, and mean quality per sample.Supplementary_figure1. Boxplots depicting alpha diversity at the genus level between ADHD cases and controls with (a) the Shannon, (b) Chao1 and (c) Simpson indices.Supplementary_figure2. Beta-diversity of gut microbial communities in ADHD cases and healthy controls. Principal component analysis (PCoA) plot based on weighted and unweighted UniFrac and Bray Curtis distances for 100 ADHD cases and 100 healthy controls. Two first principal components are show.Supplementary_figure3. Comparison of the microbiota between ADHD cases and controls with canonical correspondence analysis (CCA).Supplementary_figure4.Volcano plot showing differential microbiome composition between 100 ADHD cases and 100 controls found with the DESeq2 method. Red dots represent significant differential abundances of species (PFDR<0.05). A positive log2-fold change determined the genera overrepresented in ADHD, and a negative log2-fold change corresponded to the genera overrepresented in the control sample.


Genes encoding endocannabinoid and sphingolipid metabolism pathways were suggested to contribute to the genetic risk towards attention deficit hyperactivity disorder (ADHD). The present pilot study assessed plasma concentrations of candidate endocannabinoids, sphingolipids and ceramides in individuals with adult ADHD in comparison with healthy controls and patients with affective disorders. Targeted lipid analyses of 23 different lipid species were performed in 71 mental disorder patients and 98 healthy controls (HC). The patients were diagnosed with adult ADHD (n = 12), affective disorder  or adult ADHD with comorbid affective disorders (n = 37). Canonical discriminant analysis and CHAID analyses were used to identify major components that predicted the diagnostic group. ADHD patients had increased plasma concentrations of sphingosine-1-phosphate (S1P d18:1) and sphinganine-1-phosphate (S1P d18:0). In addition, the endocannabinoids, anandamide (AEA) and arachidonoylglycerol were increased. MD/BD patients had increased long chain ceramides, most prominently Cer22:0, but low endocannabinoids in contrast to ADHD patients. Patients with ADHD and comorbid affective disorders displayed increased S1P d18:1 and increased Cer22:0, but the individual lipid levels were lower than in the non-comorbid disorders. Sphingolipid profiles differ between patients suffering from ADHD and affective disorders, with overlapping patterns in comorbid patients. The S1P d18:1 to Cer22:0 ratio may constitute a diagnostic or prognostic tool. Attention deficit hyperactivity disorder (ADHD) is characterized by persistent inappropriate levels of inattention, hyperactivity and impulsiveness . It is aFADS3 and elongase ELOVL5 [FAAH) [Cnr1) have been associated with ADHD [Recently, whole-genome sequencing studies identified genetic variations in genes involved in fatty acid metabolism in association with ADHD, including fatty acid desaturase e ELOVL5  and fatt5 [FAAH) . FAAH ca5 [FAAH) ,13,14, s5 [FAAH) . CB1 is 5 [FAAH) ,19,20,21ith ADHD , and ADHith ADHD ,23, but ith ADHD . Interesith ADHD .LASS6/Cers6) and LASS2/Cers2 [In addition to fatty acid metabolism, ADHD genetics pointed to alteration of sphingolipid metabolism originating from variants of ceramide synthases 6 , kept on ice, and centrifuged in a tabletop centrifuge (Eppendorf) at 3000 rcf and 4 °C for 10 min within 15 min of blood collection. Plasma aliquots were stored immediately at −80 °C until analysis. Informed written consent was obtained from all participants. Sampling and data analyses adhered to the Declaration of Helsinki and were approved by the Ethics Committee of the Medical Faculty of the Goethe University . Demographic data, comorbidities, and treatments are summarized in Patients with adult attention deficit hyperactivity disorder  and patients with major depression  or bipolar disorder (BD) (n = 6) and healthy controls (n = 98)  were conThe severity of depression was assessed with the Beck Depression Inventory (BDI), which is a 21-question multiple-choice self-report inventory for measuring the severity of depression. Patients with bipolar disorder were additionally queried with the Young Mania Rating Scale (YMRS) to assess the severity of manic symptoms. The psychometric assessment encompasses 11 major clinical symptoms characterizing the last 48 h . The ADHBioactive lipids, including sphingolipids and ceramides, and endocannabinoids, were analyzed in plasma by liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) as described in recent previous publications ,39,46.v/v) after adding the internal standard. The organic phase was removed and evaporated. The sample was reconstituted in acetonitrile and injected into the LC-MS/MS system. The LC-MS/MS system consisted of a triple quadrupole mass spectrometer QTRAP 6500+  equipped with a Turbo Ion Spray source and an Agilent 1290 Infinity LC-system with binary HPLC pump, column oven, and autosampler . It operated in positive electrospray ionization mode. The chromatographic separation was performed on an Acquity UPLC BEH C18 2.1 × 100 mm column .Briefly, the determination of endocannabinoids, arachidonoyl ethanolamide (AEA), 2-arachidonoyl glycerol (2-AG), 1-arachidonoyl glycerol (1-AG), oleoyl ethanolamide (OEA), and palmitoylethanolamide (PEA) was performed as described in detail in Reference . Analytev/v/v). The extract was divided into two aliquots, one for the determination of ceramides and one for the determination of sphingoid bases. The extracts were evaporated at 45 °C under a slight stream of nitrogen and reconstituted in 50 µL solvent. For ceramides, tetrahydrofuran/water  with 0.2% formic acid and 10 mM ammonium formate were used. For sphingoid bases, methanol containing 5% formic acid was used. The LC-MS/MS system consisted of a triple quadrupole mass spectrometer QTRAP 5500  equipped with a Turbo Ion Spray source and Agilent 1290 Infinity LC-system as above. It was operated in positive electrospray ionization mode. The chromatographic separation of ceramides was done on a Zorbax RRHD Eclipse Plus C18 column (1.8 µm 50 × 2.1 mm ID), and sphingoid bases were separated on a Zorbax Eclipse Plus C8 UHPLC column .The determination of sphingoid bases and ceramides was performed as described in detail in Reference . The ana2 weighting. Acceptance criteria and quality assurance measures were as described in [After measuring the calibration standards, quality control samples of three different concentrations  were run as initial and final. The concentrations of calibration standards, quality controls, and samples were evaluated by Analyst software 1.7.1 and MultiQuant Software 3.0.3  using the internal standard method. Calibration curves were calculated by linear or quadratic regression with 1/x weighting or 1/xribed in .Lipid concentrations are presented as scatter plots with mean ± standard deviation (SD) or box-scatter plots, where the box is the interquartile range, and the whiskers show minimum to maximum. Lipid profiles are presented as mean ± SD or sem as specified in the figure legends. Data were analyzed with SPSS 25, Origin Pro 2020, and GraphPad Prism 8.4 and 9.0. According to Schapiro Wilk and Anderson Darling, the data distributions were assessed according to goodness of fit criteria for normal distribution and log normal distribution. Lipids were log-normally distributed and therefore log2 transformed for further analyses. Partial least square analysis (PLS) was used to reduce dimensionality and identify the factors, which contributed most to the variance, and discriminated best between groups. Groups , gender, age class, and BMI class were considered as independent factors. ADHD+ refers to patients with a primary diagnosis of ADHD who suffered from a mood disorder as comorbidity. In addition, linear canonical discriminant analysis (CanDisc) was used to assess the predictability of group membership based on CanDisc scores. Chi-square automatic interaction detection (CHAID) was used to generate decision trees based on Bonferroni adjusted significance testing. Lipids were introduced as independent variables and gender as an influencing variable.t-tests according to the data subgroup structure and distribution for between-group comparison. For multivariate analyses, the factors were “group” by “gender,” either with four groups  or three groups, where ADHD patients were summarized to gain power. For univariate analyses of “group”, age and body mass index were introduced as covariates. To address the younger ages of ADHD patients, a subset of young age-matched HC ≤ 40 years of age was compared with ADHD patients. For cluster analyses, PLS, and lipid profiles, lipid concentrations were normalized to the 75% quantile of the HC to allow for a combined analysis because the concentrations differ by several orders of magnitude.We used univariate or multivariate analyses of variance , or 2 statistics, paired t-tests of candidate two lipids, and linear regression analyses to address age and BMI and interrelationships of two lipids. In case of significant results of ANOVAs, groups were mutually compared using t-tests, and p-values were adjusted according to the procedures of Dunnett (versus one control group) or Šidák. The alpha level was set at 0.05 for all comparisons, and asterisks in the figures refer to adjusted p-values.Further analyses consisted of χWe first used canonical discriminant analysis to assess whether patients suffering from ADHD could be separated from healthy controls and patients suffering from mood disorders (MD/BD) based on their lipid profiles. The CanDisc score plots A show thConsidering group differences, overall abundance and variability, the ceramide importance ranking was Cer22:0 > Cer24:1 > Cer20:0 > Cer18:0 > Cer16:0 > Cer24:0 > Cer14:0 . CHAID analysis revealed that patients could be separated from HC based on Cer22:0 only E. AddingAll ceramides linearly increase with age, and Cer18:0 increases with BMI . Since AFurther CHAID analyses revealed that males could be separated from females based on 1-AG. The significant separation disappeared when ADHD+ patients were excluded. Hence, the sex difference originated from ADHD+ males. Because of the impact of sex on endocannabinoids , statistTo assess putative influences of drug treatments, we compared patients receiving or not receiving drugs of the key drug classes, which were “ADHD-drugs” , antidepressants , and antipsychotics  . A detaiKey candidate lipids were selected based on the CanDisc structure, and case profiles of the three top lipids were further compared. Paired analyses of the individual’s Cer22:0 and S1Pd18:1 levels show that MD/BD patients “always” had higher Cer22:0 than S1Pd18:1, except for one patient A. This pThe present pilot study shows that ADHD patients have elevated levels of plasma anandamide (AEA) and sphingosine-1-phosphate (S1Pd18:1). In contrast, MD/BD patients have increased ceramides, the latter in agreement with our previous data from an independent cohort of MD/BD patients . InteresFAAH; rs2295633) has been associated with ADHD [FAAH rs2295633 polymorphism also has been associated with posttraumatic stress disorder [FAAH variants were genetically linked with addiction, anxiety, eating disorders, depression, and obesity [FAAH variant reduces or increases reuptake or degradation of AEA. Both, loss and gain of function of FAAH variants have been discussed [As some patients report beneficial effects of cannabis , the finith ADHD . FAAH isith ADHD ,54,55,56disorder . Other F obesity ,61,62,63iscussed ,64,65. IThe finding of increased ceramides in MD/BP replicates the results of our previous observational study in an independent cohort of MD/BP patients . It exteDifferences in ages might also have affected the continuous shift of the S1P d18:1/Cer22 profiles in patients without or with MD/BP comorbidities because ADHD patients without comorbidities were about 10 years younger . The conDue to the heterogeneity of drug treatments relative to the low sample size, discriminant analyses did not reveal associations with drug treatments. The change of the lipid profiles from ADHD-only to comorbid-ADHD could not be assigned to a change of drugs or additional drugs. However, the comparisons of drug effects were limited because of the diversity of the patients, diversity of drugs and drug combinations, and the relatively small sample size. Further limitations are the confounding factors of age, metabolic status, and sex. For ceramides, very high BMI (>35) is associated with high ceramides, which may explain why one of the ADHD-only patients did not fit the ADHD scheme of “high S1Pd18:1/low Cer22:0”. The other patient who had a “non-ADHD-only” lipid profile had had an accident leading to amputation of both legs and chronic pain. In addition, these two patients were taking methylphenidate (MPH) for more than 3 years. In contrast, the other patients of the ADHD-only group were newly diagnosed and had just started MPH or lisdexamfetamine. In the “MD/BD-only group,” only one of the patients did not show high long-chain ceramides. In contrast to the other MD/BP patients, this patient did not receive any drugs and had a normal body weight.The present study suggests that ADHD patients have increased anandamide and S1P d18:1 plasma levels, whereas MD/BP patients display increased ceramides. Plasma S1P d18:1, Cer22:0 thus might be useful for differential diagnosis or to define subgroups of the disease, pending replication of our findings in larger samples.


Low Birth Weight (LBW) is considered as a major public health issue and leading cause of neonatal death. Almost one in four newborns are reported as underweight in Pakistan. Children born with low birth weight are highly vulnerable to develop diseases and death and/or remain undernourished . This study determines the LBW newborns are more prone to develop stunting and wasting in province of Sindh, Pakistan. Moreover, regression-based estimation of the impact of LBW on the child health outcomes of under five years of age, may be prone to selection bias because of the nature of non-experimental data set, thus, propensity score matching methods are used in this study. Data for this study was used from Multiple Indicators Cluster Survey (MICS-2014). MICS is a two-stage, stratified cluster sampling household level data covering urban and rural areas and consists of 19,500 households from five administrative divisions and 28 districts of Sindh province of Pakistan. The total sample size of children less than five years of age after cleaning the data are 7781, of which 2095 are LBW having birth weight categorized as “smaller than average and very small” and 5686 are normal birth weight (NBW) having birth weight very large, larger than average, and average. This study employed propensity score matching (PSM) regression methods to understand whether the children born as low birth weight are more prone to stunting and wasting and/or both. In province of Sindh, moderate wasting children under five years were 21%, severe wasting 6% and both wasting and stunting 10%. The propensity score results are shown significant in all groups. Specifically, all four types of PSM methods confirm a significant difference in the potential outcome variables—meaning that a child born with LBW has a significant adverse effect on the potential child health outcome variables . Thus, the propensity score matching findings confirm a significant and adverse effect of LBW on potential health outcomes of under five children. Similarly, low birth weight children are significantly more likely to be moderately wasted  and severely wasted  and both  as compared to children with normal birth weight. Male children, if born with low birth weight, are significantly more likely to be moderately wasted  and both  than girls. This large data analysis finding proved that the LBW newborns are on higher risk to develop wasting and stunting in Pakistan. Above 80% neonatal deaths were reported in LBW newborns including preterm and term small for gestational age2. About half of childhood deaths occur due to malnutrition and around 144 million children below five years of age were reported stunted and 47 million are reported as wasting globally3. Furthermore, it has been reported about 6 million children were stunted and wasted4. LBW is highly prevalent in particularly south Asian countries like, India, Pakistan and Bangladesh6.About 20 million of babies are born with low birth weight (LBW) worldwide7. Hence, LBW is considered as a major public health issue and leading cause of neonatal death with multiple health related adverse effects. LBW is an important health indicator for survival of babies born with weight less than 2500 g7. The children are on higher risk of developing diseases and deaths due to their low birth weight during childhood period8.LBW and preterm births are main causes of infant mortality that accounts for 30% child deaths during their first 28 days of life13. Other environmental factors like good personal hygiene and improved sanitation could reduce LBW incidence and decrease child mortality by 14–31%14. LBW has long term consequences on postnatal development, increased risk of respiratory distress, hypoglycemia, polycythemia, mental disabilities, cerebral palsy, food intake issues, sensory and vision dysfunction and later in life this can develop cardiovascular diseases and diabetes18.Past research has revealed that the factors like length of gestation, parity, perinatal care, parent’s education level, low socio-economic status, maternal anemia, short stature of the mother, birth spacing and infections are strongly associated with LBW19. The prevalence of stunting has dropped by 11% and wasting has declined, from 45 to 38%, during last 5 years20. Sindh province has reported highest prevalence of stunting and wasting among all the province of Pakistan19. Data shows four out of ten children below five-year age are underweight (42%) and almost half (48%) are stunted and (15%) children reported wasted in Sindh province21.According to Pakistan demographic health survey, (23%) of children under five year of age were reported as underweight22, is extensively used in economic policy intervention and in medical trial23.LBW and its immediate consequences on child health outcomes particularly stunting and wasting are not well documented empirically in Pakistan. Hence, the current study tries to fill this gap. Moreover, the study will come up with the empirical results, providing guidelines to the policy makers. The impact evaluation of LBW forms the foundation of public policy analysis. During the last two decades, impact evaluation through PSM has gained tremendous attention in applied econometrics. The current study utilizes the propensity score matching method to estimate the impact of LBW on the malnourished under five years of children for the case of Sindh, Pakistan. The data comes from the observational studies, which are none, randomize. The presence of such none randomize studies confronts with the problem of selection bias. To ward off or reduces the chances of such bias, a proposed PSM method21.The Multiple Indicator Cluster Survey (MICS) is an international household survey programme developed by the United Nations Children’s Fund (UNICEF). In Sindh, between January and August 2014, MICS collected household-level data to analyse the health of women and children, while also employing anthropometric (nutrition) measures and education measures among other key indicators. The two-stage stratified cluster sampling MICS data covered rural and urban areas of all 5 divisions and 28 districts of the province. Enumeration Blocks (EB) in urban areas and villages in rural areas were the primary sampling units (PSU). Households were considered as secondary sampling units, and from each PSU, 20 households were selected with a random start. The total sample consisted of 19,500 households with a response rate of 94%normal birth weight (NBW)” and smaller than average and very small as “low birth weight (LBW)”. The total sample size after cleaning the data are 7781, out of which 2095 under five years of age are LBW (treated/LBW group) and 5686 (untreated/NBW group) are normal birth weight children. Many important covariates: that’s child specific characteristic-age, birth order, sex and health condition related variables ; mother specific characteristics-age, education, health condition and household characteristics-sanitation, wealth are also included in the analysis.The analysis incorporates moderate wasting, severe wasting and combination of both wasting and stunting as outcome variables; whereas, the main explanatory variable is the weight of the child at birth. The birth indicator is generated as a binary variable by categorizing the original question (size of child at birth) such as very large, larger than average, average as “24. Matching of children is done based on the covariates of both treated (LBW) and controlled (NBW) groups. These matching estimates indicate that conditional on a set of individual characteristics of the treatment or assignment is independent of potential outcomes. The PSM usually involves three steps. First, estimating the propensity score . Second, matching the propensity score through four widely used methods used in the current study and third, making the impact analysis through match samples. A plethora of literature exists to matching the propensity score. However, widely used methods are, Nearest Neighbor Matching (NNM), Radius Matching (RM), Kernel Matching (KM), and Stratification Matching (SM)25.This study employs propensity score matching (PSM) regression methods. Because, the multivariate regression analysis relies on the modelling assumptions of linearity between the confounders and the odds of the outcome variables. However, the PSM eliminates the linearity assumptions and exhibits more empirical power than logistic regression26. All cases in the comparison group with estimated propensity scores falling within radius are matched to the treated case. Another matching method is the KM that uses the weighted averages of all individuals in the control group (NBW) to construct the counterfactual outcome28. The weights are inversely proportional to the distance between the propensity scores of the treated and comparison group. All treated units are matched with a weighted average of all comparison units. Finally, the SM divides the observations into five equal intervals based on the propensity scores, and then the difference between the average outcomes of the treated (LBW) and controlled group (NBW) is obtained. Weights are applied across intervals to calculate the average treatment effect. It excludes observations in blocks where either treated or controlled units are absent.In the NNM each treated unit is matched with controlled unit with the nearest propensity score. With replacement each treated unit is compared with the nearest controlled group (NBW), hence minimizing the propensity score distance, leading to reduce the bias between the two groups. However, if the comparison group is small, the nearest neighbor matching suffers from the risk of bad matches. In this case, the RM comes to the rescue30. Once the propensity score matching is performed, the balancing test is used for the purpose of balancing property. Balancing property is commonly tested by three methods. (1) checking standard bias estimation, (2) before and after treatment, (3) testing the significance difference between the treated (LBW) and controlled group (NBW) by t test. In this study, we used two sample t test. The estimated model having low t values satisfies the balancing property29. Second, re-calculation for the matched sample of propensity score calculation for the treated (LBW) and controlled group (NBW), and comparing pseudo R2 before and after matching. Low value indicates fulfillment of balancing property. Finally, through stratification method, in which sample are divided into blocks. The balancing property is satisfied if the difference between the two groups is insignificant using t test26. The region of common support is to be defined after the balancing property fulfillment. In this common support region, the propensity score for both groups should be overlapped. Minima and maxima standard approach are utilized for the common support region. Higher than the maxima and lower than the minima value, the observations are dropped from the sample31. The greater overlap between the groups, the lesser the chance of the bias28. After the satisfaction of the above mentioned properties, next task is to perform matching through estimated propensity score and for matching this study employed PSM methodology.The primary objective of the propensity score is not to analyze only the statistical properties of the parameters estimated, but also concern with the balancing properties of the covariatesBefore, we delve into the PSM estimation, we will first check if there is a significant difference between the means of normal birth weight child and low birth weight child to set the stage for PSM between the treated (LBW) and comparison groups (NBW). To this end, we will compare the two groups via t-test. Mathematically, the t-test takes a sample from each of the two sets and establishes the problem statement by assuming a null hypothesis that the two means are equal.This study is based on an analysis of cross sectional data available freely and publicly with all identifier information removed, no ethics approvals were required.(treated/LBW group) and normal birth weight (NBW) 5,686 (untreated/NBW group) were included in this study. Moderate wasting children were (21%), severe wasting (6%) and both wasting and stunting (10%) found under five years of age. More than half (55%) children were male and (19%) had their birth order more than one child. One-third (34%) of children were suffering from Diarrhoea and nearly half (46%) were reported ill with fever. About (77%) families were visited by lady health workers at their homes and received antenatal care during pregnancy. Less than half (43%) were delivered at hospital and (54%) mothers get tetanus toxoid injection. More than half (57%) children were living in the houses with good sanitation. The descriptive statistics of the variables are given in  The two-sample test of proportions results confirm a significant mean difference between the treated group (LBW) and control group ((NBW)). The mean difference findings are shown in Table . This diBefore we start analyzing the data, we compared all of the confounders between the treated (LBW) and untreated (NBW). Listing shows how we can get the mean and standard deviation for each variable in the treated (LBW) and untreated (NBW). The output shows us that the LBW and NBW groups differ by about less than 1 standard deviation (SD). So, the LBW and NBW groups are more similar. The balancing property is satisfied for both groups male and female. The low level of t test indicates that the distribution of conditioning covariates does not differ between the treated (LBW) and controlled groups (NBW) (Appendix A).We can now look at the distributions of the propensity score in the treated (LBW) and the untreated (NBW) groups. The result is shown in Fig. The result of average treatment effect (ATE) using PSM methods is given in Table Table Mothers’ education is a significant covariate of moderate wasting. Compared to no education reference category, children of highly educated mother are significantly less likely to be moderately wasted  and severely wasted  and both  as compared to no education. Whereas children of Primary  and Middle school completed mothers  are significantly less likely than no educated mothers to be severely wasted. Those children living in houses with improved sanitation are significantly less likely to be moderately wasted  as compared to those who don’t have improved sanitation at their houses. Parents of children with middle  and rich  wealth index are significantly less likely to be both stunted and wasted as compared to those who were poor. Families of children with speaking Sindhi , Saraiki  and others  are significantly less likely to be moderately wasted as compared to those who speak Urdu language.32. National Nutrition Survey of Pakistan data shows that two fifth of children below five years are stunted and one fifth is wasted in Pakistan and government needs to prioritise this public health problem and special interventions are also required33. PSM approach could provide reliable and efficient methods to control for covariates or potential confounding variables. Data from demographic and health survey and Multi-indicator Cluster Surveys datasets from 84 countries findings are consistent with our analysis and shows the prevalence for being wasted, stunted, and concurrently wasted and stunted among children less than five years4. Similar survey findings revealed that child age, birth order, education of parents, poor sanitation facilities and poverty are associated significantly with the likelihood of moderate and severe stunting in one of the province of Pakistan33. Study supported our findings that the families with choice of male babies could results malnourished and underweight babies in their families34. Another research has also similar with our results that the multiple factors like; babies living with large family size with sharing common room and illiteracy are on higher risk to develop LBW35. Local research has proved that the boys are more stunted as compare to girls and diarrhoea was also associated with LBW36. Research also found that a birth spacing less than two years was a major cause of stunting in the similar population where this study analysis was done37. Furthermore, recent multicounty analysis suggested that a quality antenatal care services could prevent LBW among their babies significantly38. Evidence shows that exclusive breastfeeding up to six months, complementary feeding for two years of age and early initiation of breast milk within hour of birth results in adequate growth among low birth weight babies and lower the risk of newborn deaths40. Environmental factors as good personal hygiene and improved sanitation could reduce LBW incidence and decrease child mortality by 14–31%14. Study also proved that the LBW, with premature birth (< 37 week), intrauterine growth restriction (IUGR) and other genetic factors may develop cardiovascular and renal diseases41. Premature birth and LBW infants are on higher risk of developing genetic congenital outcome42.This study analysed the impact of LBW on the child health outcomes including stunting, wasting and combination of both using matched pairs from the MICS data among children less than five years of age while adjusting for other confounders. This data also provided an ideal opportunity to control a large set of confounding factors when using the PSM approach. Moreover, LBW newborns are on high risk to develop wasting and stunting in Pakistan. This research has highlighted that the socioeconomic, demographic and personal factors are accountable for LBW likewise, those who had birth order more than one, with diarrhoea, male child and delivered at home were on high risk to develop LBW. PSM analysis can only be as good as the quality and the completeness of potential confounding variables that are at the disposal of the researcher. Study supports our finding with strong association of LBW children with family size, income and number of children in their family43. Data suggest that the infections in LBW are considered as serious condition that might increase the rate of morbidity and mortality among children37.Children with no diarrhea are significantly less likely to be stunted and wasted both as compared to those having an episode of diarrhea and children with fever are significantly more likely to be moderately and severely wasted as compared to those having no fever. Longitudinal study has supported that the LBW newborns are more susceptible to develop fever and Diarrhoea among children under five years of age44. Literature also confined with our findings and proved that females are three times more likely to be stunted as compare to male child because of multiple reasons34. In other study LBW prevalence in female neonates were observed (8.9%) as compared to male (5.3%) and was statistically significantly (p = 0.0002)45. Similar findings were seen in a hospital based study shows a majority of female (18%) babies were born with low gestational weight as compare to male (13%), which is matching our study results46. Low birth females are on high risk to get diseases later in her life and proved by study that LBW is strongly associated with diabetes in women as compare to men47.This analysis shows that female children are more affected with LBW as compared to males. Our findings were consistent with research explored that there was a higher chances of LBW among female children (OR = 1.39) as compare to male48. Study show that the LBW is associated with long-term health consequences has been shown with significant correlation between LBW and malnutrition and child mortality49.Strong correlation was found between LBW and malnutrition in this study among the children under five in Pakistan and moderate wasting group was found (26%) of LBW as with normal birth weights even after controlling for other factors. Hence, this shows that LBW newborns have a tendency to remain underweight in their childhood life. These findings are consistent with similar studies conducted in other parts of the worldThe study limitations include MICS Sindh 2014 data is provincially representative data although the findings of study should be interpreted with cautions and cannot be generalizable to Pakistan as a whole. Furthermore, we did not have the data for mother height and weight hence this study remains silent on mother’s health and its role in determining the persistence of wasting and stunting in children. Of note, this study is important as recently Sindh has got a World Bank funding for Accelerated Action plan for reduction of stunting and malnutrition (AAP) and hence provide an input to this process of understanding the prevalence of stunting, wasting and their relation with low birth weight in Sindh province of Pakistan. The MICS uses mother recall regarding size of birth for determination of birth weight because many infants are not weighed at birth and those who are weighed may be a biased sample of all births, the reported birth weights usually cannot be used to estimate the prevalence of low birth weight among all children. Therefore, the percentage of births weighing below 2500 g is estimated from two items in the questionnaire: the mother’s assessment of the child’s size at birth  and the mother’s recall of the child’s weight or the weight as recorded on a health card if the child was weighed at birth. Hence it may affect the correlation of LBW with other factors.In conclusion, PSM methods used for estimating treatment effects from observational data found reliable evidence. The current study investigates the impact of LBW on the child health outcomes particularly stunting and wasting using PSM method. The PSM is preferred over the conventional regression analysis because, conventional regression-based estimation, may be prone to selection bias because of the nature of non-experimental data set. Moreover, the PSM eliminates the linearity assumptions and exhibits more empirical power than conventional regression models. This study has concluded that the children with LBW are more prone to develop moderate wasting, severe wasting and both wasting and stunting among children under five years of age in Sindh Province of Pakistan. It is therefore mandatory that mother care before and during pregnancy as well as in the first 1000 days are important time for intervention to achieve the goal of undernutrition reduction in children.Supplementary Information.


Children with ADHD were more likely to undertake activity under the pressure of external stimuli and exhibited attention deficits regarding vigilance, visual search and divided attention. Differences between groups regarding attention decreased in conditions of increased motivation, indicating that motivation can reduce cognitive deficits in children with ADHD.Earlier reports showed the co-occurrence of a motivation deficit in children with ADHD. The purpose of this study was to assess the impact of extrinsic motivation on selected aspects of attention in children with ADHD, as well as to measure cortical activity and dimensions of motivation as per the self-determination theory. The study included 30 children with ADHD and 30 typically developing (TD) children aged 9–13 years. Children with ADHD exhibited a higher theta/beta power ratio (TBR) in the midline and a lower regional cerebral blood oxygenation (rCBO Attention Deficit Hyperactivity Disorder (ADHD) is the most common neurobehavioral childhood disorder. Its incidence is estimated at 3–8% in the age population of < 18 . ADHD maStudies using functional magnetic resonance imaging (fMRI) have shown that reduced activation in the prefrontal cortex is associated with attention deficit in children with ADHD . AttentiApart form neuronal ADHD correlates, researchers are trying to establish how behavior patterns of children with deficits are linked to motivation. Motivation helps to explain human behavior, its direction and duration . Deci anThe purpose of this study was to assess the impact of extrinsic motivation on selected aspects of attention in children with ADHD, as well as to measure cortical activity and dimensions of motivation as per the self-determination theory.Based on the aforementioned articles, we assumed that: (H1) children with ADHD may exhibit lower levels of cortical activity as measured using (a) TBR in the midline and the (b) HEG ratio in prefrontal areas than TD children; (H2) children with ADHD may display lower levels of (a) intrinsic motivation and (b) identified regulation as well as higher levels of (c) external regulation, (d) introjected regulation and (e) amotivation to learning compared to TD children; (H3) children with ADHD may exhibit deficits regarding: (a) vigilance, (b) visual search and (c) divided attention; (H4) increasing the motivation may reduce attention deficits in children with ADHD with regard to: (a) vigilance, (b) visual search and (c) divided attention. The obtained data will enable a better understanding of ADHD issues.The study was conducted in the fall of 2019. The participation in the study was voluntary. Consent was required of the patient and their parent or legal guardian. This study was approved by The Committee for Ethics in Scientific Research of The Institute of Psychology, Polish Academy of Science .The measurement of cortical activity, fluid intelligence and motivation to learning was conducted at the beginning of the study. The assessment of the impact of motivation on selected aspects of attention was carried out in a quasi-experiment model with repeated measurement. The manipulative technique consisted in increasing the motivation in all of the examined participants. For a correct result as part of each of the tasks (gain), participants received a sweet reward (chocolate). In addition, a named record board for the top 10 results was introduced—competition effect. The manipulative technique corresponds with previous studies by McInerney and Kerns , as wellThe study involved 30 children (24 boys and 6 girls) aged 9–13 years, diagnosed with ADHD by a specialist in pediatric psychiatry or neurology. Moreover, the diagnosis was confirmed by a structured diagnostic interview for psychomotor hyperactivity as per DSM-V , conductAs part of the study, cortical activity was measured using:TBR EEG was recorded using a 10-channel FlexComp Infiniti encoder (up to 2048 samples/s) with impedance control (less than 5 kΩ). Two additional reference electrodes were placed on the earlobes. Recording was conducted in resting state with eyes open for 3 min. Data were processed in Biograph Infiniti 6.2. The signal was filtered in the 0.50–30 Hz band. Artifacts were corrected by automatic elimination. Amplitudes above 70 µV were removed along with the artifacts. The results were subjected to the Fast Fourier Transform (FFT) analysis. TBR was calculated from the ratio of theta power (4–7 Hz waves) to beta power (13–30 Hz waves) based on the mean value registered using electrodes placed in central areas: C3, Cz, C4, according to the 10:20 placement.HEG Ratio The HEG system (32 samples/s) using near infrared spectroscopy (NIRS) was employed for recording regional cerebral blood oxygenation (rCBO2). The measurement method uses different optical properties of hemoglobin (Hb) and oxyhemoglobin (oxy-Hb). It was described in detail by Toomim et al. [m et al. . ReflectMoreover, the study used psychological tools to determine the level of intelligence, motivation and attention:Raven’s colored progressive matrices (CPM) in Polish standardization [dization  for measSituational motivation scale (SMS-15) [(SMS-15)  for meas(SMS-15) , 48. TheShortened version of the Mackworth clock task [ock task  for measVisual search task for assessing a conjunctive search, i.e. with a specific combination of two stimulus characteristics (color and angle of rotation). The role of the examined person is to scan the perception field in order to detect (by pressing a button) the red T letter among inverted red T letters and blue T letters. The probability of occurrence of an element complying with the criterion is 40%. The task consists of 48 boards with 5–20 elements on the screen. Recording takes place of the average reaction time (RT) and RT slope, which reflects the average RT increase at the moment of each additional element appearing on the screen.Multitasking test for measuring divided attention. The role of the examined person is to observe a screen divided into 2 parts and to react according to the location of the stimulus. If a figure appears in the upper part of the screen, the test taker should react (the appropriate button) according to the shape of the figure (square or rhombus), and if the figure is placed in the lower part, they should react accordingly to the number of dots in the middle of the figure (two or three dots). The task consists of 48 items. 24 boards for single-tasking (reaction according to one stimulus feature) and 24 boards for multi-tasking (reaction according to two stimulus features interlaced with one another).The tests we selected are popular among neuropsychologists and are often used to assess brain performance. The measurement of selected attention aspects was carried out using computer applications in the Java environment. The tasks were presented on a 19-inch screen. The distance of the examined person from the screen was about 70 cm. Each test was preceded by a short training session.p < 0.05. The effect size was assessed on the basis of a partial eta square (η²) or the r coefficient.Statistical data analysis was conducted in IBM SPSS Statistics 26. The normality distribution was verified using the Kolgomorov–Smirnov test. Levene’s test was used to assess the homogeneity of variance. In most cases, the obtained results allowed for the use of parametric tests . In order to determine the significance of differences, the Student’s t-test, Mann–Whitney’s U test and the repeated measures multivariate analysis of variance ANOVA were used. The repeated measures ANOVA did not include the sphericity test due to two levels of independent variable within each effect. The level of significance was set at The study did not contain statistically significant differences between children with ADHD and TD children in terms of age and intellectual capacity measured using CPM (each participant scored above the 50th centile).The Student’s t-test confirmed the occurrence of statistically significant differences between children with ADHD and TD children regarding: TBR, HEG ratio and motivation dimensions. Detailed analysis results are presented in Table children with ADHD versus TD children) × 2 . The factor measured between individuals was membership to one of the research groups, whereas motivation was the factor measured internally. Dependent variables included selected aspects of attention. As a result of the analyses, a multidimensional interaction effect was obtained regarding group membership and motivation, F = 8.13, p < 0.001, η² = 0.48. Due to the formulated research questions, main effects were not analyzed. Univariate F tests confirmed the interaction effects for the following dependent variables: omission errors, F = 19.58, p < 0.001, η² = 0.25; RT in visual search of 5–20 elements, F = 17.59, p = 0.001, η² = 0.23; RT slope in visual search, F = 7.84, p = 0.007, η² = 0.12; RT in single-tasking, F = 18.76, p < 0.001, η² = 0.24; as well as RT in multi-tasking, F = 7.94, p = 0.007, η² = 0.12. No significant interaction effect was obtained for the commission errors dependent variable, F = 0.09, p = 0.760, η² < 0.01.Next, a mixed design two-way MANOVA was conducted: 2 , commission errors , RT in visual search of 5–20 elements , RT slope in visual search , RT in single-tasking  and RT in multi-tasking .The group membership factor differentiated all of the controlled attention indicators under normal conditions: omission errors  and RT in multi-tasking . No significant differences were observed between ADHD and TD children in conditions of increased motivation for the following dependent variables: omission errors , RT in visual search of 5–20 elements , RT slope in visual search  and RT in single-tasking .The group membership factor differentiated the indicators of selected attention aspects in conditions of increased motivation: commission errors , RT in visual search of 5–20 elements , RT slope in visual search , RT in single-tasking  and RT in multi-tasking . In the case of commission errors, no significant differences in normal and increased motivation conditions were observed .The motivation factor significantly differentiated the indicators of selected attention aspects in children with ADHD: omission errors , commission errors , RT in visual search of 5–20 elements , RT slope in visual search , RT in single-tasking  and RT in multi-tasking .In the case of TD children, all of the controlled attention indicators were similar in normal and increased motivation conditions: omission errors . In our study we did not correct individual alpha peaks. Some children with ADHD may display slow alpha peak frequencies instead of increased theta activity. Lack of this correction may overstate the TBR value. Langberg et al. [Elevated TBR in children with ADHD has been well studied and described in the literature and has proven to be an effective aid in diagnosing attention deficits , 23, 24.g et al.  comparedg et al. . Howeverg et al. . On the g et al. , 27.r ∈ 〈0.70, 0.75〉) turned out to be larger than in the case of TBR differences.HEG/NIRS is a method of visualizing cerebral perfusion and, consequently, brain activity. So far, few measurements have been performed using this technology. In our study, children with ADHD showed significantly lower levels of hemoglobin saturation with oxygen within each controlled location in the prefrontal areas, i.e.: Fp1, Fpz, Fp2 (Hypothesis 1b). The obtained data are in line with the limited literature in this respect , 29, 57.r = 0.29), while the biggest one was noted in external regulation (r = 0.59). Our findings are consistent with the behavioral model of motivation in children with ADHD [Previous studies on motivation focused primarily on the lower achievement needs of children with ADHD and their biological conditioning, i.e. the limited availability of dopamine receptors in the reward system , 55. In ith ADHD .r = 0.45 for omission errors, r = 0.33 for commission errors). Omission errors may indicate distraction, while commission errors may be a sign of impulsivity. It should be noted that some researchers reported greater difference effects compared to TD children [Reports thus far have shown deficits in children with ADHD regarding vigilance , 41, 67.children . Howeverr = 0.56, as well as a bigger RT slope—medium effect: r = 0.44 (Hypothesis 3b). Our results are consistent with many earlier studies using the conjunctive search method, which requires intensive selective visual attention [Children with ADHD displayed longer RT in the visual search task—large effect: ttention , 40, 68.ttention , 69, 70.r = 0.41) and in multi-tasking (large effect: r = 0.50), which is consistent with many previous reports in this respect [In the multitasking test for divided attention (Hypothesis 3c), children with ADHD showed longer RT in single-tasking  and in commission errors, where no motivational impact was noted. Therefore, it seems that motivation, especially in simple cognitive tasks, can increase perceptual sensitivity in children with ADHD, increase the quality of information obtained from a stimulus, as well as the rate of collecting this information. However, motivation is not able to eliminate the limitations of complex tasks which require the integration of many cognitive processes, especially those more closely related to inhibitory control.Our study confirmed the positive impact of extrinsic motivation on selected aspects of attention in children with ADHD, who have improved their capacity regarding most controlled aspects of attention. This impact did not apply to TD children who, in conditions of increased motivation, achieved the same results in normal conditions. Motivated, children with ADHD exhibited comparable performance to TD children regarding most tasks. Differences between groups were maintained only in multitasking complex tasks . Two motivational techniques were applied in the study in parallel: the reward effect and the competition effect. We are not able to determine which of them proved to be more effective. Taking these variables into account may serve as an inspiration for further research. Despite the aforementioned limitations, our report introduced new data regarding cortical activity, motivation and attention deficits in children with ADHD.Our study is affected by certain limitations. It was conducted on a small number of participants. Further research is needed to generalize conclusions. In the study, we did not control the ADHD types of presentation or the co-occurrence of other disorders  that could differentiate the results. The structure of the group (age and sex) did not allow for assessing the demographic differences with respect to the controlled dependent variables. However, studies to date have indicated a statistically insignificant or small impact of age and sex on the TBR and HEG ratio values –75. At tThe study was conducted in the Fall of 2019 in Kraków (Poland). It included 30 children with ADHD as well as 30 TD children. The study confirmed significant differences between children with ADHD and TD children in terms of TBR and HEG ratio, which indicate different patterns of cortical activity in prefrontal and central areas. The study also confirmed the occurrence of attention deficits in children with ADHD. Moreover, for the first time we have displayed differences in motivation dimensions between ADHD and TD children as per the self-determination theory. We have also confirmed the positive impact of extrinsic motivation on cognitive capacity in children with ADHD—this is the first study to assess the impact of extrinsic motivation on vigilance and divided attention. The obtained data allow for a better understanding of the issues and for defining the clinical picture of ADHD. Cognitive deficits in children with ADHD are not permanent neuropsychological impairments. Cognitive capacity may be modulated by means of motivation. Evoking interest and more frequent strengthening help reduce cognitive deficits in children with ADHD. The data have an application value. They may be used in the diagnosis of ADHD, in the development of pedagogical programs and in therapeutic work.