Bath is an external stimulus for preterm infants. Currently, three methods are used for preterm infants to bath. It is important to choose the best way for them. The objective of this meta-analysis is to evaluate the effectiveness of different bath methods on physiological indexes and behavioral status of preterm infants.This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA] guidelines and was registered in PROSPERO(CRD42022377657). PubMed, Embase, Cochrane Library, Web of Science, CINAHL, Sino Med, China National Knowledge Internet (CNKI) and Wan-Fang database were systematically searched for randomized controlled trials on the effects of different bath methods for preterm infants. The retrieval time was from the establishment of the database to February 2023. According to the inclusion and exclusion criteria, the literature was screened, quality evaluated and the data was extracted. Reman Version 5.4 was used for meta-analysis and Stata 16.0 software for publication bias Egger’s test. 2 = 0; p < 0.01), , while the heart rates were higher than those in conventional tub bath group. Preterm infant’s body temperature and blood oxygen saturation of in swaddle bath group were higher than those in conventional tub bath group , , respiratory rates were more stable compared with infants in conventional tub bath group . The crying duration, stress and pain scores of preterm infants in swaddle bath group were lower than those in conventional tub bath group , , . Egger's test showed no publication bias in body temperature, respiratory rate, oxygen saturation, and crying duration.A total of 11 RCTs with 828 preterm infants were included. The results of meta-analysis showed that the body temperature and oxygen saturation of preterm infants in the sponge bath group were lower than those in conventional tub bath group (SMD = -0.34; 95%CI -0.56 to -0.12; ISwaddle bath is the best bathing method than conventional tub bath and sponge bath in maintaining the stability of preterm infant’s body temperature, blood oxygen saturation and respiratory rate. In addition, swaddle bath also plays a role in reducing cry duration, stress scores, and pain levels of preterm infant compared with conventional tub bath and sponge bath. However, due to the important heterogeneity in some outcomes, future studies with larger sample size and more appropriately design are needed to conduct before recommendation.Prospero CRD42022377657The online version contains supplementary material available at 10.1186/s12887-023-04280-y. According to the Global Action Agenda, 15 million preterm infants are born every year . It poseSeveral studies have shown –9 that cThe American Association for Women’s Health, Obstetrics, and Neonatal Nursing and the World Health Organization guidelines have specified the time for the first bath of newborns , 20, butThe primary objective of this systematic review and meta-analysis was to evaluate the effectiveness of different bathing methods on physiological indexes and behavioral status of preterm infants.Inclusion criteria: (a) Research type: randomized controlled trials (RCT) on bath methods of preterm infants published in Chinese or English; (b) Population: preterm infants born before 37 weeks of gestation; (c) Interventions: effects of different bathing methods on premature infants; (d) Comparator group: one of the three bath methods  in experimental group, the other of the three bathing methods in control group; (e) Outcomes: (1) the primary outcome was to assess the effectiveness of different bathing methods about physiological indexes including body temperature, blood oxygen saturation, heart rate, respiratory rate; (2) the second outcome was to evaluate the bathing methods on behavioral indicators including crying duration, pain scores and stress scores.Exclusion criteria: (a) Conference papers, abstracts and other documents that cannot obtain original data; (b) Duplicate publications.We conducted a comprehensive search including PubMed, The Cochrane Library, CINAHL, Embase, Web of Science, CNKI, Wan-Fang Database, Sino Med, which covered the period from establishment of the database to February 2023. The subject headings (Mesh) combined with free words, supplemented by manual retrieval and literature retrospective method to systematically retrieve literature. English search strategy as follows:  OR ("extremely premature infant*"[Title/Abstract] OR "extremely preterm infant*"[Title/Abstract])) AND ("bath*"[ Mesh Terms] OR "sponge bath*"[Title/Abstract] OR "swaddled bath*"[Title/Abstract] OR ("tube"[All Fields] AND "bath*"[Title/Abstract])).According to the tool of Cochrane Handbook for Systematic Reviews of Interventions, two researchers searched the databases independently, imported all retrieved literatures into Endnote X9 software for deduplication, and then conduct the first round of screening by reading the title and abstract and further read the full text for the second round of screening. In case of disagreement, a third researcher adjudicated. Two authors used a predesigned spreadsheet to extract literatures’ characteristics and outcome data independently and then compared for consistency after completion. Data extracted from the final included literatures including: authors, country, year of publication, type of study design, participant characteristics, sample size, intervention measures, and outcome indexes.According to the Cochrane Risk of Bias tool for randomized controlled trails (RoB 2) , two resp < 0.1 or I2 > 50%, it indicated that the heterogeneity among the included literature was obvious. The random effect model was used to analyze. The sensitivity analysis was carried out by excluding the literature one by one to judge the stability of Meta-analysis results. Subgroup analysis was performed on outcome indicators with large heterogeneity to find the source of heterogeneity; If p ≥ 0.1 and I2 ≤ 50%, it indicated that no significant heterogeneity among the included literatures, and the fixed effect model was used for analysis. All data in this study are measurement data and the mean Difference (MD) is used as the effect indicator. If the measurement units are inconsistent, the standardized mean difference (SMD) is used as the effect indicator. Each effect size estimated using a 95% confidence interval. p < 0.05 means the difference is statistically significant. Stata 16.0 software was used to conduct Egger's test on body temperature, respiratory rate, blood oxygen saturation and crying duration, and P < 0.05 was considered as publication bias.Reman Version 5.4 statistical software was used for Meta-analysis. First, the heterogeneity of the literature was tested. If Subgroup analysis was conducted by researchers to further explore the causes of the significant heterogeneity.The study selection process is illustrated by the PRISMA Study Flow Diagram see Fig. . A prelin = 7) comprehensively compared the conventional tub bath with swaddle bath [In this systematic review descriptive, detailed characteristics of the data are presented in Table dle bath , 31, 33.dle bath  compareddle bath , 29, 32 Body temperature was measured by different types of thermometers or skin heat probe, heart rate and respiratory rate were measured by stethoscope or multiparametric monitor sensor attached to infant’s foot, and blood oxygen saturation was also measured by multiparametric monitor sensor attached to infant’s foot too. Crying duration was the total crying time during the bath or the percentage of the bathing time and the data was obtained through video recording or on-site observation. One study  measuredA total of 11 RCTs were included in our study, one was grade A  and the 2 = 88%; p = 0.006). The result of random-effects model showed that body temperature in swaddle bath group was significantly higher than that in conventional tub bath group .Five studies , 31, 33 2 = 0; p < 0.01).Three studies , 30, 33 Four studies , 31, 33 2 = 86%; p = 0.04). with high heterogeneity .Four studies , 31, 33 2 = 91%, p < 0.01).Six studies , 30, 33 2 = 0%; p < 0.01).Two studies , 30 incl2 = 49%; p < 0.01).Only two studies , 33 invo2 = 0%; p = 0.003).Three studies , 29, 32 2 = 0%; p = 0.06).Only two studies , 29 invo2 = 39%; p = 0.04).Two studies , 29 incl2 = 61%; p = 0.03).Two studies , 29 inclp = 0.000). Infant’s stress and pain scores in sponge bath group were higher than that in swaddle bath group (p < 0.05).One crossover RCT  includinThe heterogeneity of body temperature, blood oxygen saturation and crying duration of preterm infants in swaddle bath and conventional tub bath group was relatively high. Due to limited studies, we didn’t find variables to subgroup the body temperature. As shown in Figs. p > 0.05)  and the sensitivity analysis showed stable results by removing study one by one. Due to the limited number of included studies, some original data could not be obtained because of privacy, copyright, and other issues, subgroup analysis for body temperature couldn’t be conducted. It might be related to multiple factors such as different modes of investigators’ operation, gestational age and weight distribution of study participants, age of study participants, and bathing frequency in different included studies. The heterogeneity of oxygen saturation was also high (I2 = 86%). The result of subgroup analysis showed that different ethnic groups and regions were one of the sources of high heterogeneity . Subgroup analysis showed that the crying duration of preterm infants was shorter in preterm infants within 5 min of swaddle bathing time  This study is based on published literatures, and not conducted in-depth retrospective of ongoing research or unpublished conference papers or special reports. (b) Some of outcomes in this study were heterogeneous, and no definite source of heterogeneity had been found because some of the original data could not be obtained. (c) The number of included studies in some outcomes are too small that it’s impossible to assess publication bias.The results of this meta-analysis indicate that swaddle bath is better than conventional tub bath and sponge baths in maintaining the stability of body temperature, blood oxygen saturation, and respiratory rate in premature infants. Furthermore, Swaddle bath is superior to conventional tub bath and sponge bath in reducing preterm infant’s crying duration, stress scores, and pain levels. These results may exert a positive impact on swaddle bath being recommended as the best bathing method for preterm infants. However, due to the important heterogeneity in some outcomes, further studies focusing on this issue needs to be generated in preterm infants. Randomized clinical trials concentrated on swaddle bath should be encouraged as well.Additional file 1:Fig. S1. Meta-analysis of body temperature in swaddle bath vs conventional tub bath. Fig. S2. Meta-analysis of body temperature in sponge bath vs conventional tub bath. Fig. S3. Meta-analysis of respiratory rate in sponge bath vs conventional tub bath. Fig. S4. Meta-analysis of respiratory rate in swaddle bath vs conventional tub bath. Fig. S5. Meta-analysis of blood oxygen saturation in swaddle bath vs conventional tub bath. Fig. S6. Meta-analysis of blood oxygen saturation in sponge bath vs conventional tub bath. Fig. S7. Meta-analysis of heart rate in swaddle bath vs conventional tub bath. Fig. S8. Meta-analysis of heart rate in sponge bath vs conventional tub bath. Fig. S9. Meta-analysis of crying duration in swaddle bath vs conventional tub bath. Fig. S10. Meta-analysis of stress score in swaddle bath vs conventional tub bath. Fig. S11. Meta-analysis of pain score in swaddle bath vs conventional tub bath.


Dyrk1a gene, a known candidate gene linked to intellectual disability and microcephaly in DS, we documented adverse effects on spine density, alterations in the molecular composition of synapses, and the presence of synaptic plasticity deficits within the PFC. The current study aimed to enrich our understanding of the roles of different genes in DS by studying Ts65Dn mice, which overexpress several genes including Dyrk1a, to compare with our previous work on mBACtgDyrk1a mice. Through ex-vivo electrophysiological experiments, including patch-clamp and extracellular field potential recordings, we identified alterations in the intrinsic properties of PFC layer V/VI pyramidal neurons in Ts65Dn male mice. Additionally, we observed changes in the synaptic plasticity range. Notably, long-term depression was absent in Ts65Dn mice, while synaptic or pharmacological long-term potentiation remained fully expressed in these mice. These findings provide valuable insights into the intricate synaptic mechanisms contributing to PFC dysfunction in DS, shedding light on potential therapeutic avenues for addressing the neurocognitive symptoms associated with this condition.Down syndrome (DS), the most prevalent cause of intellectual disability, stems from a chromosomal anomaly resulting in an entire or partial extra copy of chromosome 21. This leads to intellectual disability and a range of associated symptoms. While there has been considerable research focused on the Ts65Dn mouse model of DS, particularly in the context of the hippocampus, the synaptic underpinnings of prefrontal cortex (PFC) dysfunction in DS, including deficits in working memory, remain largely uncharted territory. In a previous study featuring mBACtgDyrk1a mice, which manifest overexpression of the  This additional copy introduces ~300 extra genes, resulting in a wide range of significant clinical phenotypes. The shared feature among all individuals with DS is intellectual disability, which manifests as specific deficits in learning and memory . The undDyrk1a gene has been proposed as a major contributor to the intellectual disability and microcephaly in DS , many of which are conserved between mice and humans . This trly in DS . Ts65Dn ly in DS . Much ofly in DS .The prefrontal cortex (PFC) is acknowledged as a key brain region controlling executive cognitive processes like planning, cognitive flexibility, working memory, and emotional behavior . DysfuncIn this study, we analyzed the intrinsic characteristics and glutamatergic synaptic plasticity of deep-layer pyramidal neurons in the PFC of adult male Ts65Dn mice. Our research focus was directed toward the synapses in the deep layers of the prefrontal cortex (PrPFC), specifically from layer II-III to V-VI. We targeted the deep-layer pyramidal neurons situated in layer V-VI, which serve as a central source of output from the prefrontal cortex. Notably, the downward projections from layers II/III to layers V/VI play a pivotal role in information processing, with the pyramidal cells in layer V projecting to subcortical regions.Dyrk1a in the cerebral cortex has been detected in males, but not females . The B6EiC3Sn.BLiA-Ts(1716)65Dn/DnJ [known as Ts65Dn] mice were obtained from Dr. Jean Delabar’s laboratory. Ts65Dn mice  were mai2.2.PFC slices were prepared as described . Mice we2.3.Whole-cell patch-clamp and field excitatory postsynaptic potential (fEPSP) were recorded from layer V/VI pyramidal cells in coronal slices of mouse prelimbic PFC . For recFor whole-cell patch-clamp experiments, pyramidal neurons were visualized using an infrared microscope . Experiments were performed with electrodes containing 128 mM potassium gluconate (KGlu), 20 mM NaCl, 1 mM MgCl2, 1 mM EGTA, 0.3 mM CaCl2, 2 mM Na2 + -ATP, 0.3 mM Na + -GTP, 10 mM glucose buffered with 10 mM HEPES, pH 7.3, osmolarity 290 mOsm. Electrode resistance was 4–6 MOhm. If access resistance  changed by >20%, the experiment was rejected . NeuronaFor fEPSP experiments –F, input2.4.Due to the strong phenotypes, the experimenters were not blind to the genotypes, but no data were excluded before statistical analysis . Data were recorded on a MultiClamp700B, filtered at 2 kHz, digitized , collected using Clampex 10.2 and analyzed using Clampfit 10.2 . Both amplitude and area of fEPSPs and EPSCs were computed, and only amplitude was display, the area giving the same results. The magnitude of LTD and LTP was calculated, respectively, 30–35 min and 35–40 min after induction as percentage of baseline responses. To perform current–voltage (I–V) curves and to test the excitability of pyramidal neurons, a series of 500 ms long hyperpolarizing and depolarizing current steps, from −400 to +400 pA with 50 pA increment, were applied immediately after breaking in the cell. The rheobase has been determined as the minimum current intensity required to induce a first action potential.2.5.Drugs were added at the final concentration to the ACSF. Picrotoxin was from Sigma . DNQX was from the National Institute of Mental Health’s Chemical Synthesis and Drug Supply Program . Forskolin was from Tocris .2.6.t-test. Multiple comparisons (genotype and current injection) were analyzed using repeated measure two-way ANOVA with post hoc Sidak’s test. Statistical significance was set at p < 0.05.The value n corresponds to the number of individual cells or slice per animal. All values are given as mean ± standard error to the mean (s.e.m). Statistical analysis was performed with Prism 7.0 . Two sample comparisons were made with the Mann–Whitney 3.3.1.Neuronal pathways are plastic, continually adapting in response to stimuli. These alterations can occur at synaptic locations (areas where neurons connect) as well as non-synaptic locations throughout the neuron. Non-synaptic, or intrinsic, plasticity can be defined as a change in the neuron’s inherent excitability that is independent of changes in synaptic transmission. To understand the impact of the segmental trisomy 16 of Ts65Dn mice on neuronal membrane properties, the basic intrinsic properties of prefrontal cortex (PFC) pyramidal neurons were first examined. Pyramidal neurons from layers V/VI of the PFC were recorded in the “current-clamp” mode to assess their membrane profile in response to a range of somatic current steps, from −400 to +400 pA in 50 pA increments . The ave3.2.The intrinsic properties of neurons, which dictate their spiking patterns and level of excitability, are critical for their computational capabilities. Changes in these non-synaptic properties, as well as in synaptic properties, can influence synaptic efficacy. Long-term modifications of synaptic efficacy, referred to as synaptic plasticity, are believed to play crucial roles in cognition, learning, and the formation of memory. Following our assessment of neuronal intrinsic properties, we next evaluated synaptic plasticity in the prefrontal cortex of Ts65Dn mice. We compared opposite forms of synaptic plasticity that rely on distinct mechanisms in our mouse groups. These forms included endocannabinoid-mediated long-term depression (eCB-LTD), presynaptic adenylyl cyclase/cyclic adenosine monophosphate signaling pathway-dependent facilitation (AC/cAMP-facilitation), and N-methyl-D-aspartate receptor-dependent long-term potentiation (NMDAR-LTP) .3.2.1.The endocannabinoid eCB) system plays a significant role in synaptic plasticity, and it might contribute to the development of mood disorders associated with prefrontal cortex (PFC) dysfunction . In resp system p3.2.2.To determine if the release probability was generally affected, we next investigated a presynaptic form of LTP, specifically Adenylyl cyclase (AC)/cAMP-facilitation. Adenylyl cyclase is an enzyme that transforms ATP into cAMP, which subsequently activates protein kinase A, thereby facilitating the release of the transmitter . We used3.2.3.NMDAR-dependent long-term potentiation (LTP) is arguably the most widely expressed and comprehensively studied form of synaptic potentiation . We eval4.In this study, we found altered intrinsic properties and some impaired synaptic plasticity in the PFC of Ts65Dn mice, a model of DS with overexpression of around 130 genes from the mouse analog of Hsa21, Mmu16, including Dyrk1a. Notably, our results contrast with those reported in mBACtgDyrk1a mice.4.1.Kcnj6 gene, one of the triplicated genes in the Ts65Dn mice  and the United States National Institutes of Health Guide for the care and use of laboratory animals. The French Ethical committee authorized this project (APAFIS#3279–2015121715284829 v5). The study was conducted in accordance with the local legislation and institutional requirements.AT and OM designed the research. AT and OL carried out the experiments. AT analyzed the data. AT and OM wrote the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by INSERM, CNRS, ANR “DsTher” (OM), Fondation Jérôme Lejeune (OM and AT) and Fondation pour la Recherche Médicale (OM and AT). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The objective of this study was to investigate the effects of N-carbamylglutamate (NCG) supplementation on the growth performance, hindgut microbiota composition, and short-chain fatty acid (SCFA) contents in Charollais and Small Tail Han crossbred sheep.A total of 16 female crossbred mutton sheep , aged 4 months, with an initial body weight of 30.03 ± 0.08 kg, were utilized in a 60 days experiment. The sheep were divided into two groups based on their initial body weight. Each group consisted of 8 replicates, with each individual sheep considered as a replicate. The dietary treatments comprised a basal diet supplemented with either 0.00% or 0.12% NCG.16S rRNA technique, we identified Lachnospiraceae_NK3A20_group and Parasutterella as biomarkers for the hindgut microbiota in mutton sheep fed a diet containing NCG. Further analysis of the microbiota composition revealed that NCG supplementation significantly increased the abundance of Lachnospiraceae_NK3A20_group and Parasutterella, while decreasing unclassified_f_Lachnospiraceae and Lachnoclostridium. Correlation analysis between hindgut SCFA contents and microbiota composition revealed that the abundance of Lachnoclostridium was positively correlated with the contents of acetic acid and hexanoic acid, but negatively correlated with propanoic acid. Additionally, the abundance of Lachnospiraceae_NK3A20_group and Parasutterella was positively correlated with the content of propanoic acid, while being negatively correlated with acetic acid and hexanoic acid. Based on these findings, we conclude that dietary supplementation of 0.12% NCG can modulate hindgut SCFA contents in mutton sheep by regulating the composition of the hindgut microbiota.Our findings indicate that NCG supplementation did not have a significant effect on the growth performance of mutton sheep. However, it did lead to changes in hindgut SCFA contents. Specifically, NCG supplementation increased the content of propanoic acid while decreasing acetic acid and hexanoic acid in the hindgut. Through microbiota analysis using the  In recent years, there has been a growing interest among animal nutritionists in studying the intestinal microbiota due to its close relationship with the growth and production performance of animals . The intGiven the significant impact of diet on the composition of the intestinal microbiota, animal nutritionists often explore strategies to modulate the intestinal microbiota by providing animals with different types of exogenous additives . The objWhile limited research has investigated the effects of NCG supplementation on hindgut SCFA contents and the intestinal microbiota in ruminants, some studies have provided promising insights. For instance, Buchon et al.  found thA total of 16 healthy female crossbred mutton sheep , aged 4 months, with similar initial body weight (30.03 ± 0.08 kg), were utilized in a 60 days experiment. The sheep were divided into two groups based on their initial body weight, with 8 replicates per group, and each sheep served as a replicate. The dietary treatments consisted of a basal diet supplemented with either 0.00% or 0.12% NCG. The dosage of NCG used in this study was determined based on previous research , and theThe sheep were housed in a cleaned and disinfected facility with natural ventilation and programmed lighting schedule. They were fed twice a day at 7 am and 6 pm, with free access to feed and water throughout the experimental period. The dietary ingredients and their chemical composition are presented in The individual body weights of the sheep were recorded weekly to calculate the average daily gain (ADG). The feed intake of each pen was measured weekly to calculate the average daily feed intake (ADFI). Feed efficiency was calculated as the ratio of ADG to ADFI (G:F).On the final day of the experiment, four sheep were randomly selected from each group to obtain fresh stool samples for hindgut SCFA analysis using an Agilent Technologies Inc. 7,890-5,977 GC/MS . Data were manually processed after exportation from the instrument. The SCFA content of each sample was calculated as μg/mg = /sample weight.® Soil DNA Kit  following the kit’s instructions. The quality of DNA extraction was assessed through 1% agarose gel electrophoresis, and the DNA density and purity were measured using the NanoDrop 2000 UV–vis spectrophotometer . The V3-V4 variable region of the 16S rRNA gene was amplified by PCR using primers 338F (5′-ACTCCTACGGGAGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). Sequencing was performed using the Illumina MiSeq PE300/Novaseq PE250 platform. The original sequencing sequences were subjected to quality control using Fastp software (version 0.20.0). Line joining was performed using FLASH software (version 1.2.7) and UPARSE software (version 7.1). The operational taxonomic units (OTUs) were clustered at a 97% similarity level, and chimeric sequences were removed. The RDP Classifier (version 2.2) was used to annotate the species classification of each sequence, with comparisons made in the SILVA 16S rRNA database (V138) using a comparison threshold of 70%. Alpha-diversity was estimated using the Chao1, Shannon, and Simpson indices, while beta-diversity was assessed using the p-value of Adonis analysis. The LEfSe analysis was performed using LEfSe software, with a linear discriminant analysis score threshold set at 3.5.Fresh stool samples obtained above were immediately placed in iceboxes and transported to the laboratory. Total DNA was extracted from the microbial community using the E.Z.N.A.t-test procedure in SAS software . The normality of the data was assessed using the Shapiro–Wilk test and QQ plots. Beta-diversity of the hindgut microbiota was analyzed using Adonis analysis. Spearman analysis was conducted to evaluate correlations among hindgut microbiota and hindgut SCFA contents. The results were presented as means ± standard deviation, with a probability value below 0.05 considered statistically significant.Data on growth performance, hindgut SCFA contents, alpha-diversity of hindgut microbiota, and differences in hindgut microbiota at the genus level were analyzed using the student’s Dietary supplementation of NCG had no significant effects on the growth performance of mutton sheep. The final body weight, ADG, ADFI, and feed efficiency did not differ among groups .p < 0.05) and hexanoic acid (p < 0.05) in the hindgut of mutton sheep fed with an NCG-containing diet were lower than those fed with a basal diet. However, those fed with an NCG-containing diet presented a higher content of propanoic acid in the hindgut (p < 0.05) (The contents of acetic acid ( < 0.05) .NCG supplementation did not affect the Shannon, Simpson, Ace, and Chao1 indexes of the hindgut microbiota .Lachnoclostridium was positively correlated with the contents of acetic acid (p < 0.05) and hexanoic acid (p < 0.05), but negatively correlated with propanoic acid (p < 0.01). Additionally, the abundance of Lachnospiraceae_NK3A20_group and Parasutterella were positively correlated with the content of propanoic acid (p < 0.05), while being negatively correlated with acetic acid (p < 0.05) and hexanoic acid (p < 0.05)  .The Venn diagram showed that 559 bacterial OTUs were shared among groups, while 108 bacterial OTUs were unique in the hindgut microbiota of mutton sheep fed with a basal diet; 95 bacterial OTUs were unique in the hindgut microbiota of mutton sheep fed with an NCG-containing diet .Beta-diversity, presented in a PCoA plot based on unweighted UniFrac distance, displayed that the samples from all groups did not separate, indicating a similar hindgut microbiota community composition between groups .unclassified_f_Lachnospiraceae, UCG-005, Parabacteroides, Treponema, Prevotellaceae_NK3B31_group, Phascolarctobacterium, Succinivibrio, Prevotella, norank_f_Muribaculaceae, and Bacteroides  with LDA scores <3.5 were identified as biomarkers for the hindgut of mutton sheep fed with a basal diet at the genus level. Additionally, two genera (Lachnospiraceae_NK3A20_group and Parasutterella) with LDA scores <3.5 were identified as biomarkers for the hindgut of mutton sheep fed with a basal diet supplemented with NCG at the genus level  and Parasutterella (p < 0.05), while decreasing unclassified_f_Lachnospiraceae (p < 0.05) and Lachnoclostridium (p < 0.05)  .Clostridium, Lactobacillus, and Streptococcus within the colonic mucosa of lambs beset by intrauterine growth restriction. Likewise, Li et al.  can be found at: The animal study was approved by the methods and procedures used in the present study were approved by the Ethics Committee of Jinzhou Medical University. The study was conducted in accordance with the local legislation and institutional requirements.WM and MY: conceptualization and methodology. SC: data collection. WM: writing—original draft preparation. CW: investigation, supervision, and writing—reviewing and editing. All authors contributed to the article and approved the submitted version.


This study aimed to investigate the effects of intensive psychological intervention care on adverse emotions and post-traumatic stress disorder (PTSD) symptoms in female teenage patients after induced abortion.n = 50) and the control group (n = 50). The intervention group received intensive psychological intervention care, while the control group received standard routine nursing. The scores of the PTSD checklist for DSM-5 (PCL-5), self-rating depression (SDS), and self-rating anxiety scale (SAS) were compared between the two groups at 1 month and 3 months after the operation.This prospective cohort study included 100 teenage female patients seeking induced abortion who were randomly divided into two groups: the intervention group (p < 0.05), SDS , and SAS  at 1 month and 3 months after induced abortion.The intervention group had lower risk of developing PTSD (24% vs. 44%), depression (10% vs. 32%), and anxiety (0% vs. 12%) symptoms at 1 month after the surgery. However, there were no significant differences observed between the two groups at 3 months after the surgery. Furthermore, the intervention group had significantly lower scores in PCL-5 (27.4 ± 5.4 vs. 31.8 ± 5.7; 20.5 ± 7.1 vs. 25.0 ± 7.5; These findings suggest that intensive psychological intervention care can reduce the incidence and severity of depression, anxiety, and PTSD symptoms in teenage patients who undergo induced abortion.https://www.chictr.org.cn/showproj.html?proj=185200, identifier ChiCTR2300067531. Globally, the high rates of induced abortion among young women are a significant public health concern . In the Psychological sequelae resulting from induced abortion have long been a topic of concern among researchers . PosttraMultiple studies have shown that anxiety and depression are risk factors for PTSD . AdditioPrevious research has primarily concentrated on the occurrence and risk factors of teenage mental health issues following induced abortion, with limited exploration on prevention or treatment. Teenagers who experience post-traumatic stress disorder (PTSD) after induced abortion exhibit distinct pathophysiological characteristics compared to adults, highlighting the need for enhanced psychological interventions.n = 50) and the intervention group (n = 50). Ethics approval (20201216) was obtained from the ethics committee of Shunde Hospital, Southern Medical University . Written informed consent was obtained from all patients.This prospective cohort study enrolled 100 female teenage patients who underwent induced abortion and were admitted to Shunde Hospital of Southern Medical University from June 2021 to September 2021. The patients were randomly divided into two groups: the control group  Severe underlying diseases such as diabetes, hypertension, and cancers; (2) mental health problems; (3) traumatic experiences in the past year ; and (4) inability to complete the follow-up.The control group patients received routine nursing care, which included medical services for complications of abortion, post-abortion family planning services (PAFPS), counseling services, community services, and comprehensive reproductive health services.Intervention group patients received intensive psychological intervention care through phone interviews. This included one-on-one stress support treatment, which was conducted four times . The treatment incorporated various cognitive behavioral therapies such as emotional expression, normalization, psychological education, and cognitive re-evaluation. Each session lasted approximately 30 min and was conducted by the same trained nurse. Throughout the treatment, patients in the intervention group were encouraged to utilize relaxation and recovery techniques, such as relaxation music and meditation exercises.Psychological conditions were assessed using the PTSD Checklist for DSM-5 (PCL-5), the self-rating anxiety scale (SAS), and the self-rating depression scale (SDS) at 1 month and 3 months after the induced abortion.For PCL-5, individuals assess the severity of 20 symptoms on a five-point scale , and a reasonable cut score is 33. Symptom severity of PTSD was generally higher with a higher score .The Self-rating Depression Scale (SDS) is composed of 20 items and has a cutoff value of 53 points. If the SDS score is ≤52, there are no signs of depression. A score of 53–62 indicates mild depression, 63–72 indicates moderate depression, and ≥73 indicates severe depression  were calculated, and an independent Intervention and control groups consisted of individuals aged between 15–20 years old. There were no significant differences in age, gestational weeks, education, and family structure between the two groups, as shown in p = 0.035), and lower PCL-5 scores at 1 month after the operation . There were no statistically significant differences in the incidence of PTSD symptoms between the two groups at 3 months after the operation, although the intervention group had a lower incidence of PTSD symptoms . However, the intervention group had lower PCL-5 scores 3 months after the operation   and 19% (19/100) respectively. The intervention group had significantly fewer cases with PTSD symptoms compared to the control group  .p < 0.001); but no significant differences were observed at 3 months after the procedure . Furthermore, the intervention group showed significantly lower SDS scores compared to the control group at both 1 month and 3 months after induced abortion   at 1 month and 8% (8/100) at 3 months after the procedure. The intervention group exhibited a significantly lower prevalence of depression symptoms at 1 month after induced abortion  .p = 0.027; 0% vs. 0%, NS). However, the intervention group displayed lower SAS scores than the control group at 1 month and 3 months after abortion   at 1 month and 0% (0/100) at 3 months. When comparing the incidence of anxiety between the two groups, no significant difference was observed at 1 month and 3 months after induced abortion  .Patients who undergo abortions may experience emotional distress, although research indicates that the abortion procedure itself typically does not lead to mental health issues. However, factors such as personal susceptibility and societal prejudice can contribute to negative emotions among these individuals. Consequently, many patients may experience intense negative emotions following an abortion, thereby increasing the likelihood of developing mental illness. Offering psychological guidance to patients can help alleviate their psychological burden and eliminate negative emotions. The aim of this study was to investigate the impact of intensive post-abortion care (PAC) psychological nursing on adverse emotions and post-traumatic stress disorder in female adolescent patients who have undergone induced abortion.The incidence of PTSD following induced abortion varies significantly across different studies. A study conducted by the University of California found that 40% of women who had undergone an abortion experienced one or more symptoms of PTSD, with 16% meeting the diagnostic, criteria for PTSD . AnotherAnxiety and depression are both risk factors for PTSD. In turn, individuals with PTSD often experience co-morbid symptoms of depression and anxiety . Among wThis study has certain limitations that should be considered. Firstly, we did not assess the baseline levels of PTSD, depression, and anxiety in the two groups of patients. However, randomization helps to guarantee that the two groups are similar in terms of characteristics such as age, gender, and incidence of PTSD, depression, and anxiety. Additionally, this study did not evaluate the likelihood of women developing lifelong PTSD, depression, and anxiety without a clinical diagnosis. Lastly, the specific source of trauma experienced by females in this study could not be determined.In summary, intensive psychological intervention care has been shown to reduce the incidence and severity of depression, anxiety, and PTSD in teenage adolescent patients who have undergone induced abortion. The implementation of these interventions can lead to significant health benefits for teenage patients, making them highly valuable for widespread clinical application.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving humans were approved by the ethics committee of Shunde Hospital, Southern Medical University . The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.MO designed the manuscript and enhanced the figures and language. HL, FW, GL, and SM conducted the clinical trial. HL prepared the figure and drafted this manuscript and edited and revised manuscript. All authors contributed to the article and approved the submitted version.


Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization. Hemispheric specialization is a fundamental aspect of human brain organization. Here, the authors demonstrate that language lateralization is heritable and evident throughout the broad functional architecture of cortex. Despite this fundamentally symmetrical plan, common to the vast clade of animals known as the bilateria6, the presence of functional asymmetries have been a leading principle of human evolution7 and, more broadly, the organization of the metazoan nervous system6. The hemispheric specialization of a range of specific functions has been well characterized. One of the most widely investigated is the left-lateralized high-order language network encompassing aspects of the anterior and posterior cortices8. However, while the lateralization of brain functions and associated behaviors has fascinated neuroscientists for over a century10, the origins, mechanisms, and consequences of hemispheric specialization are still largely unknown15. In this regard, the extent to which the asymmetrical organization of discrete processes may be evident throughout the macroscale functional organization of the cortical sheet remains an open question16.A primary architectural feature of the human brain is its homotopy, with each hemisphere exhibiting broadly comparable spatial organization in terms of cytoarchitecture, macroscopic anatomy, and associated large-scale functional systems17, including Broca’s area within the inferior frontal gyrus adjacent to the somato/motor network and Wernicke’s area within the posterior superior temporal cortex. The presence of this left lateralized system has been supported by converging evidence from in vivo imaging studies of language function in healthy populations18 and, more recently, data-driven algorithms that parcelate cortex into discrete functional networks across a variety of task contexts19. Critically, however, the left-hemispheric dominance of the language system is not fixed across development or ubiquitous in the general populations, where atypical organization has been observed22. Although some anatomical and functional hemispheric asymmetries appear early in human development23, language is distributed symmetrically in children, with lesions to either hemisphere resulting in an equal likelihood of associated deficits24. From early to late adolescence, there is a gradual transition to left-hemisphere dominance in the majority of the population14, with atypical language organization evident in ~10 percent of individuals26. This flipped profile of a right hemisphere language system is more likely to be observed in left-handed individuals27, although not specific to this group. In right-handed adults, 2% to 8% show a dominance reversal28. However, the exact mechanisms of brain lateralization are still largely unknown, as are the associated consequences on broader properties of brain organization.The detailed anatomical study of the brain systems supporting language began through the post-mortem examination of patients with acquired brain injuries and aphasias. These seminal studies revealed a set of interconnected regions in the anterior and posterior cortices of the left hemisphere that underpin healthy language functioning30. The topographic organization of this complex interdigitated architecture is evident in the presence of functional gradients that situate discrete networks along continuous spectra31. The spatial arrangement of areal parcels along these global gradients, for instance, along a principal gradient anchored on one end by the unimodal  regions and the other by the cortical association areas that underpin complex cognition32, reflect a fundamental property of brain organization34. Converging evidence for these macroscale gradients has been established through in vivo imaging measures of function, anatomy35, and areal allometric scaling36, as well as histology-derived assessments of cytoarchitecture38 and cortical gene transcription41 (for review see ref. 33). Intriguingly, there is a strong correspondence between the relative positions of parcels along these gradients and the extent to which they share common cortical microstructure, connectivity, and profiles of gene expression, while the organization of cortical gradients differs between the two hemispheres44. Building upon these discoveries, a core goal of the present work is to characterize the organization and lateralization of the language network in relation to the mosaic of functionally distinct large-scale networks and associated macroscale connectivity gradients that span the cortical sheet.The cerebral cortex is comprised of a dense tapestry of areal units embedded in corresponding processing streams and housed within associated large-scale functional networks8, we worked to determine the extent to which typical and atypical language lateralization is reflected across the functional architecture of the cerebral cortex. First, through a combination of resting-state functional MRI (fMRI) and task activation studies of language, we establish the presence of typical (92% of sample) and atypical (8% of sample) individuals within the Human Connectome Project (HCP) database45. Second, we provide evidence that atypical language lateralization is associated with global shifts in cortical organization. To do so, we applied the dimensionality reduction approach of diffusion map embedding31 to resting-state data to extract a global framework that accounts for the dominant connectome-level connectivity patterns within each hemisphere. Individuals with atypical language organization exhibited corresponding hemispheric differences in the macroscale functional gradients. This pattern was preferential to functional networks within association cortex. Third, twin-based heritability analyses revealed that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. In doing so, our analyses reveal evidence linking the lateralization of language with broad changes in the functional organization of the cortical sheet.Here, using a recently developed higher-order language atlasn = 995, 110 left-handers) as a part of the Human Connectome Project45. Demographics are available in the Methods section (HCP participants). Language lateralization of each participant was assessed using SENSAAS, a higher-order language atlas8. In brief, two task-induced functional asymmetries during a language task46 were obtained. First, at the network level, averaging across associated parcels, and second, within language network hubs, corresponding to Broca’s and Wernicke’s areas8. Three resting-state variables were also used to assess language lateralization. Two of which characterized the intra-hemispheric organization of the language network at rest, operationalized as the sum and the asymmetry of the average language network functional connectivity strength. The last metric characterized the homotopic inter-hemispheric connectivity of the language network. Taken together, these 5 functional metrics revealed the organization of the higher-order language network , a mild typical group with moderate leftward asymmetry , and atypical individuals showing a rightward asymmetry  and hubs level , as well as a more leftward lateralized language network in strong  than in mild typical participants  both at the network and hub level. Intrinsic functional connectivity strength asymmetry profiles revealed that atypical individuals possess a bilateral language network organization (μstrength asym = 9 × 10−3 ± 0.18), in contrast to strong  and mild typical  participants. Strong and mild individuals showed no differences (pstrength asym = 0.12). Finally, strength sum and inter-hemispheric connectivity displayed a similar profile across groups, with strong typical (μstrength sum = 12.16 ± 0.39 and μr = 0.61 ± 0.02) and atypical individuals  exhibiting a similar profile with significantly larger values than mild individuals .We next examined the extent to which language lateralization was reflected across each of the 5 features used to derive the higher-order language network Fig. . Analysi31. First, functional connectivity matrices (384 × 384 AICHA parcels48) across the full sample were decomposed into components that capture the maximum variance in connectivity. Consistent with prior work49, diffusion map embedding50 was used to reduce the dimensionality of the connectivity data through the nonlinear projection of the voxels into an embedding space. The resulting functional components or manifolds, here termed gradients, are ordered by the variance they explain in the initial functional connectivity matrix. The present analysis focused on the first three gradients, reflecting divergent spatial patterns of connectivity across the cortex and accounting for 57% of the total variance in cortical connectivity. The first 3 group-level gradients respectively explained 22%, 21%, and 14% of the total variance in the initial matrix of cortical connectivity  regions, while the other end encompassed broad swaths of the association cortex, including aspects of the ventral and dorsal medial prefrontal, posteromedial/retrosplenial, and inferior parietal cortices, representing a functional hierarchy that spans from primary visual and somato/motor areas through the default network34  = 1.11 to µL-R = 4.09). The somato/motor network was symmetrical  = 0.01, CI95% = 0.24). The control network was strongly right lateralized  = −6.21, CI95% = 0.59) which may align with previous results on attention60. Conversely, the second gradient displayed a more heterogeneous pattern. Here, the gradient values within the control network  = −2.93, CI95% = 0.36) were right lateralized, as well with the somato/motor  = −2.52, CI95% = 0.41), limbic  = −0.63, CI95% = 0.48), and default networks  = −0.54, CI95% = 0.26). The visual network was symmetrical  = −0.24, CI95% = 0.29), and the dorsal  = 0.88, CI95% = 0.54) and ventral =1.26, CI95% = 0.45) attention networks were left lateralized. Finally, the third gradient was primarily right lateralized or symmetrical, with the default  = −1.20, CI95% = 0.73), limbic  = −2.53, CI95% = 0.71) and salience/ventral attention networks  = −4.26, CI95% = 0.63) rightward dominant, and the control  = −0.77, CI95% = 0.90), dorsal attention  = −0.61, CI95% = 0.67) and somato/motor networks  = 0.34, CI95% = 0.34) symmetrical. The visual network was the only leftward lateralized network for the third gradient  = 0.53, CI95% = 0.28). See Supplementary Table For each participant, functional network gradient asymmetry values correspond to the difference between the normalized gradient values in the left hemisphere minus the gradient values in the right hemisphere, averaged across all network parcels. Broadly, within the mild and strong typical groups, the first gradient showed a leftward asymmetry for 5 of the 7 canonical networks  and next contrasted with the atypical participants . Broadly, with exception of the limbic network, analyses of covariance revealed a preferential association between language lateralization and the asymmetric organization of association cortex networks, relative to unimodal systems across each of the three gradients , of which 2 of them exhibited a shift in their lateralization from left to right dominant: the default network  = −1.62, CI95% = 1.00) and the salience/ventral-attention network  = −1.65, CI95% = 1.05). The dorsal-attention  = 1.56, CI95% = 1.11) and the visual network =0.67, CI95% = 0.53) showed a weakened dominance in the left hemisphere. The control network  = −9.21, CI95% = 1.21) was characterized by an increase in its dominance in favor of the right hemisphere. Those alterations in the hemispheric dominance mainly came from an increase of the gradient values in the right hemisphere for all the networks impacted by the phenotype, except the default network for which the change came from a decrease of the gradient values in the left hemisphere.Specifically, in the first gradient, five of the seven networks exhibited a significant main effect of language lateralization , the default  = −1.58, CI95% = 0.53) and control networks  = −4.26, CI95% = 0.74) exhibited an increase in their rightward dominance, both coming from a mixed effect of an increase of their gradient values in the right hemisphere and a decrease in the left hemisphere. The salience/ventral-attention network  = −0.17, CI95% = 0.92) showed a symmetrical pattern in atypical individuals instead of being leftward dominant, coming from a decrease in its gradient values in the left hemisphere. Of the four remaining networks, two showed rightward lateralization: somato/motor  = −1.28, CI95% = 1.28), and limbic  = −1.77, CI95% = 0.99), and the two last ones were symmetrical: dorsal-attention  = 0.52, CI95% = 1.10), and visual  = 0.29, CI95% = 0.61).Three networks showed a significant impact of language lateralization within the second gradient  showed an increase in their asymmetry in favor of the left hemisphere. The default  = 9.05, CI95% = 1.52), control  = 8.51, CI95% = 1.87), and limbic networks  = 1.57, CI95% = 1.47) became significantly left asymmetric through an increase of their gradient values in the left hemisphere and a decrease in the right. The salience/ventral-attention one showed a bilateralization  = 1.25, CI95% = 1.31) of its functional architecture coming from a decrease of its gradient values in the right hemisphere. The 3 remaining networks did not show significant differences compared to typical organization  and were all leftward symmetrical: dorsal-attention  = 1.50, CI95% = 1.39), somato/motor  = 0.84, CI95% = 0.71), and visual  = 1.12, CI95% = 0.58).Finally, four of the seven networks for the third gradient significantly impacted by the language lateralization phenotype , and the hemispheric asymmetries in gradient organization, reflecting the difference in gradient values between the left and right hemisphere , are under genetic control. Heritability of gradient asymmetry values for each network was estimated using sequential oligogenic linkage analysis routines (SOLAR70) and covaried for age, sex, age2, age × sex, age2 × sex, handedness, and FreeSurfer-derived intracranial volume. Prior work examining connectivity strengths and the network topographies indicates reduced heritability in the size63 and connectivity strength62 of heteromodal association networks, relative to unimodal sensory/motor cortex. In contrast, with the exception of the limbic network, the present analyses revealed the influence of genetic factors on the gradient asymmetries across each association cortex network. Notably, genetic factors did not significantly account for the lateralization of gradient values within somato/motor and visual territories and heritability was significantly greater  within heteromodal  association cortices than within unimodal networks . Overall, these data reveal the substantial influence of genetic factors on the lateralization of both specific cognitive functions and the broad functional organization of the cortex. These results are consistent with the hypothesis that neuronal asymmetries likely developed under phylogenetic pressure, and therefore possess a genetic basis71.Leveraging a twin-based estimate of heritability, our analyses suggest that both the lateralization of the language network, as assessed through the hierarchical classification approach  or a reading task, it still significantly activates and lateralizes the language network in the left hemisphere8. In line with this, asymmetries observed during language tasks, compared to a high reference condition, serve as a suitable marker for determining language dominance114. Furthermore, incorporating asymmetries at the hubs (Broca’s and Wernicke’s areas) increases the amplitude of asymmetries in the comprehension task. Finally, our prior work showed that combining resting and task metrics is essential to accurately identify atypical individuals26. Additionally, from a clinical perspective, the potential relationships linking aphasias with corresponding shifts in the global functional architecture of cortex have yet to be established and warrant further study116.Although the present results provide evidence that atypical language network organization is linked to widespread properties of cortical organization, there are several limitations with our approach. First, the causal pathways linking the lateralization of the putatively distinct cognitive processes with broad features of brain functioning remain to be established. We are unable, for instance, to examine atypicalities in the lateralization of attentional processes. Additionally, given the cross sectional nature of the study data, we are not able to establish the developmental course linking atypicality in language lateralization with the development of global brain architecture. As such, the manner through which lateralized functions impinge upon, and are in turn influenced by, other properties of brain organization across development remains an open question. From a methodological perspective, the HCP database contains only one language comprehension task117 as well as neuropsychiatric and neurological disorders with known alterations in brain laterality119.The extent to which the lateralization of specific cognitive functions may be evident across the macroscale organizational properties of the cortical sheet is a central question across the brain sciences. The present results demonstrate that asymmetric language network organization is carried throughout the association cortex. While the exact determinants of lateralization mechanisms are still unknown, both the hemispheric specialization of language and corresponding asymmetries across the sweeping functional gradients that span cerebral cortex were found to be heritable. Here, the lateralization of heteromodal association cortex networks under increased genetic control, relative unimodal networks. The further study of this entangled relationship between language lateralization and broader properties of functional network organization has the potential to shed light on the phenomenon of cerebral dominance thought to underpin sophisticated cognition in humans45. From 1206 healthy participants, participants with fully completed 3 T language and 3 T resting-state fMRI protocols were selected, resulting in a total of 995 participants (477 women). The mean educational level of participants was 14.97 years (SD = 1.77 years). The sample mean age was 28.70 years (SD = 3.71 years). Participants’ handedness was defined based on the manual preference strength assessed with the Edinburgh inventory:120 participants with a score below 30 were considered left-handers122, right-handers otherwise. The values for Edinburg Inventory (EHI) scores can be found in the HCP database’s restricted demographic file under the variable name “Handedness”, which is accessible only to authorized users. It is worth noting that the HCP’s EHI score includes one foot-related item among its ten items. As a result, it does not solely measure manual preference. Analyses using a corrected EHI score123 that excludes the foot-related item yield consistent results . The sample contained 110 left-handed participants (50 women), leading to a sample broadly representative of the general population124. Data collection was approved by a consortium of institutions institutional review boards (IRBs) in the United States and Europe, led by Washington University (St Louis) and the University of Minnesota (WU-Minn HCP Consortium). The current study was approved by the Yale University IRB.The study sample was part of the S1200 Release (updated April 2018) of the WU-Minn Human Connectome Project (HCP) database that has been fully described elsewhere125. (2) Task fMRI (t-fMRI) data were acquired using the identical multiband EPI sequence as the rs-fMRI session. Among the 7 contrasts, only the Story minus Math contrast was used. Details on the protocol are available elsewhere46. The language-related protocol was developed by Binder and colleagues126. Briefly, the contrast consisted of comparing comprehension of brief narratives (Story task) with a semantically shallow control task involving serial arithmetic (Math task). Two runs were performed each consisting of 4 blocks of a Story interleaved with 4 blocks of a Math task. Each run was 3.8 min long.HCP datasets used include two main imaging sessions. Data were acquired using multiband echo-planar imaging (EPI) on a customized Siemens 3 T MRI scanner (Skyra system). Structural data consisted of one 0.7 mm isotropic scan. (1) Two sessions (REST1 and REST2) of resting-state fMRI (rs-fMRI), where each session comprised two runs  of 14 min and 33 s each (repetition time (TR) = 720 ms, echo time (TE) = 33.1 ms, voxel dimension: 2 mm isotropic). Details on rs-fMRI can be found elsewhere127. The R library neurohcp128 was used to interface AWS S3 bucket (R package version: 0.9.0). The R library RNifti129 (R package version: 1.3.1) and oro.nifti130 (R package version: 0.11.4) were used to read and handle the fMRI data.Minimally preprocessed volumetric rs- and t-fMRI data were sourced from the online HCP repository through Amazon Web Services (AWS). Details of the minimal preprocessing pipeline can be found elsewhere131, since volume-smoothed level 2 t-fMRI analysis results are no longer being distributed. rs-fMRI data are represented in the MNI volumetric space.The 995 individuals have been coregistered using MSM-All pipeline. t-fMRI data are represented in the HCP 32k_LR MNI surface space26.Preprocessed data were analyzed to compute 5 functional features characterizing the high-order language network. These 5 features have been previously shown to accurately determine the language network typicality8. Briefly, 18 regions of interest corresponding to the core language network have been selected from the language atlas. The core language network corresponded to a set of heteromodal brain regions significantly involved, leftward asymmetrical across 3 language contrasts , and intrinsically connected. It should be noted that the language atlas was based on the AICHA atlas, a functional brain atlas optimized for the study of functional brain asymmetries48.The high-order language atlas (SENSAAS) has been fully described elsewhere132. The surface language atlas was then used as a binary mask to estimate the average BOLD signal variation of language networks in both hemispheres for the Story minus Math contrast. The average asymmetry of activations was then measured by computing the difference between the left and right hemispheres (left-right). The same process has been repeated to estimate the average asymmetry at the hub level. A description of language hubs can be found in Labache and colleagues8. Briefly, the language network hubs corresponded to the inferior frontal gyrus (Broca’s area) and to the posterior aspect of the superior temporal sulcus (corresponding to Wernicke’s area).First, two of the 5 features were computed from the t-fMRI data. For each individual, the native volumetric language atlas has been mapped to the closest mid-thickness surface vertex using tools from the HCP workbenchz-transformed prior to being averaged and r-transformed with a hyperbolic tangent function. The 4 scans were averaged to increase the signal-to-noise ratio and reliability for generating individual functional connectivity matrices133. For each individual and each region, the strength, or centrality degree, was computed in each hemisphere. The strength was calculated as the sum of the correlations existing between one region and all the 18 others. Strength values were then averaged across the 18 regions of the same hemisphere and the resulting left and right averaged strength values were summed. The left minus right differences were also computed. Finally, the inter-hemispheric connectivity strength was estimated in each individual by averaging across the 18 region pairs of the z-transformed intrinsic correlation coefficient between homotopic regions.Second, the 3 other features were computed from the rs-fMRI data. For each of 4 rs-fMRI scans, each individual and each of 18 language regions, an individual BOLD rs-fMRI time series was computed by averaging the BOLD fMRI time series of all voxels located within the region’s volume. An intrinsic connectivity matrix was then calculated for each of 995 individuals and scans. The intrinsic connectivity matrix off-diagonal elements were the Pearson correlation coefficients between the rs-fMRI time series of region pairs. For each individual, the 4 connectivity matrices were 31. Functional gradients reflect the topographical organization of cortex in terms of sensory integration flow as described by Mesulam134. Gradients were computed using Python135 (Python version: 3.8.10) and the BrainSpace library136 (Python library version: 0.1.3). Gradients computed at both the regional and vertex level showed similar performance136.For each participant, values were obtained for the first 3 functional gradients. The gradients reflect participant connectivity matrices, reduced in their dimensionality through the approach of Margulies and colleaguesi.e. 384 AICHA brain regions, same process as for the language connectivity matrices). Consistent with prior work, the top 10% connections of each region were retained, and other elements in the matrix were set to 0 to enforce sparsity49. The normalized angle distance between any two rows of a matrix was calculated to obtain a symmetrical similarity matrix. Diffusion map embedding138 was implemented on the similarity matrix to derive the first 3 gradients. Note that the individual-level gradients were aligned using Procrustes rotation (Niterations=10) to the corresponding group-level gradient. This alignment procedure was used to improve the similarity of the individual-level gradients to those from the prior literature. Min-max normalization (0-100) was performed at the individual level for the whole brain42.Average region-level functional connectivity matrices of the 4 scans were generated for each individual across the entire cortex . Data wrangling was performed using the R library dplyr141 (R package version: 1.0.10). Brain visualizations were realized using Surf Ice142.Statistical analysis was performed using RAn overview of our experimental workflow is shown in Supplementary Fig. 26, the 995 participants have been classified using agglomerative hierarchical clustering. Each participant was characterized according to their language network organization. Language network was described by 5 features: network- and hubs-level asymmetry during the language task, sum and asymmetry of strength, and homotopic inter-hemispheric connectivity value at rest. Hierarchical classification allowed for the identification of language lateralization for each individual. Briefly, hierarchical agglomerative clustering143 was performed using Euclidean distance as metric and Ward’s criterion as linkage criteria144. Each variable was standardized before classification.Using the same methodology as by Labache and colleaguesNbClust145 (R package version: 3.0.1) and pvclust146 (R package version: 2.2.0), we selected a 3-cluster solution , which was shown to reproduce our previous results26. pvclust showed that the 3-cluster solution was stable . Furthermore, among the 26 indices used by NbClust to evaluate the stability of different clustering schemes, the 3-cluster partition was the second most supported, with 5 indices in its favor. The most supported partition was a 4-cluster solution with 11 indices. This would have led to the partitioning of the strong typical group, which was deemed unnecessary as it would not have provided new insights to the aim of this study. The 3 clusters defined the language lateralization phenotype.We employed an unsupervised methodology to determine the optimal number of clusters. Combining results from the R package t-test for binary ones. The reported p-values in the corresponding Results section are corrected for multiple comparisons.Using analysis of covariance, the broader relationship between language lateralization and the 5 features was assessed. Each of the 5 models was specified as follows: the features were the dependant variable, language lateralization phenotype was the independent variable, age, intracranial volume (FreeSurfer-derived), gender, and handedness as covariate, as well as the interaction handedness × language lateralization phenotype. Post-hoc analyses were conducted using Tukey’s range test for multiple comparisons , or Student’s t-test. The reported p-values in the corresponding Results section are not corrected for multiple comparisons and are significant if less than 0.007.Analysis of covariance was used to assess the broader relationship between language lateralization and lateralization of large-scale cortical organization, modeled by gradient asymmetry. For each gradient and network, the model was specified as follows: gradient asymmetry for a given network and a given gradient was the dependant variable, language lateralization phenotype was the independent variable, age, intracranial volume (FreeSurfer-derived), gender, and handedness as covariate, as well as the interaction handedness × language lateralization phenotype. Bonferroni correction of significance thresholds was used to account for 7 independent tests of a given gradient. Post-hoc analyses were conducted using the Student’s 70 (version: 9.0.0) through the R package solarius147 (R package version: 0.3.2), covarying for age, sex, age2, age × sex, age2 × sex, handedness, and FreeSurfer-derived intracranial volume. Bonferroni correction of significance thresholds was used to account for 7 independent tests of heritability. Heritability of language lateralization phenotype  was also assessed using the same covariates.Heritability is a statistic indicating to what extent the variation in a phenotypic trait is accounted for by the combined effects of genetic variations over the genome of a population. Heritability estimates range from 0 to 1. The heritability of gradient network asymmetry was estimated using SOLARn = 260), 70 DZ twins (n = 140), non-twin siblings (n = 479), and unrelated singletons (n = 110).Heritability estimates were conducted on 989 HCP participants, composed of 130 MZ twins (Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Aspergillus section Flavi associated with the two crops, and (iii) assessed aflatoxin-producing potentials among the recovered fungi. A total of 120 groundnut and 380 maize samples were collected at harvest from eight and 16 provinces, respectively. Most of the groundnut (93%) and maize (87%) contained aflatoxin below the European Union threshold, 4 μg/kg. Morphological characterization of the recovered Aspergillus section Flavi fungi revealed that the L-morphotype of A. flavus was the predominant species. Aflatoxin production potentials of the L-morphotype isolates were evaluated in maize fermentations. Some isolates produced over 137,000 μg/kg aflatoxin B1. Thus, despite the relatively low aflatoxin levels at harvest, the association of both crops with highly toxigenic fungi poses significant risk of post-harvest aflatoxin contamination and suggests measures to mitigate aflatoxin contamination in Burundi should be developed. Over 55% of the L-morphotype A. flavus did not produce aflatoxins. These atoxigenic L-morphotype fungi were characterized using molecular markers. Several atoxigenic genotypes were detected across the country and could be used as biocontrol agents. The results from the current study hold promise for developing aflatoxin management strategies centered on biocontrol for use in Burundi to reduce aflatoxin contamination throughout the value chain.Aflatoxin contamination of the staples maize and groundnut is a concern for health and economic impacts across sub-Saharan Africa. The current study (i) determined aflatoxin levels in maize and groundnut collected at harvest in Burundi, (ii) characterized populations of  Aspergillus section Flavi fungi (Production of food crops including maize and groundnut in sub-Saharan Africa (SSA) faces a combination of challenges that reduce yields, including drought, pests, diseases, soil nutrient limitation, shortage of farm inputs and credit, climate change, low labor productivity, and high population pressure on farmland . Additiovi fungi . Crop covi fungi . Also, tvi fungi . Trade wvi fungi .1, B2, G1, and G2. Aflatoxin B1 is the most prevalent and toxic. Aspergillus flavus and A. parasiticus are the species most implicated in contamination events  and 37% samples (39% maize and 51% groundnut) exceeded the East African Community (EAC) standard . It is not known whether those levels were due to either pre- or post-harvest contamination, or a combination of both.Aflatoxin contamination can start in the field during crop development where it sometimes reaches dangerous levels . HoweverAspergillus section Flavi associated with the crops, (iii) quantify potentials of the recovered fungi to produce aflatoxins, and (iv) characterize molecularly the atoxigenic fungi. The obtained results provide knowledge on the extent of aflatoxin contamination in maize and groundnut in Burundi at harvest, as well as, the fungi responsible for aflatoxin contamination. A large number of atoxigenic fungi were detected, which can be put to use as components of aflatoxin management strategies across Burundi.To better design appropriate aflatoxin management strategies in Burundi, the current study sought to (i) quantify aflatoxin levels in maize and groundnut collected at harvest across Burundi, (ii) characterize populations of Burundi lies between latitudes 2.3°S to 4.5°S and longitudes 28.8°E to 31.0°E. The elevation across the country ranges between 770 and 2,670 m above sea level . The couSampling was conducted across the major maize and groundnut production areas of Burundi . Maize wA total of 120 groundnut and 380 maize samples were collected from farmers’ fields at harvest, in two batches. The first batch (250) was collected in the lowlands and midlands in March 2014, after the end of the short-rain season. The samples were transported to KALRO Regional Mycotoxin Laboratory in Katumani, Kenya for processing. The second batch of samples (250) were harvested in highland areas in July 2014 at the end of the long-rain season and sent to Katumani for processing and analysis. Up to 10 maize cobs (~1 kg of grains after shelling) were sampled per field while groundnut pods were collected from up to 10 points in each farm (approximately 500 g when shelled). All samples were collected by moving in a zigzag line across each farm.All cob/pod samples were sundried for 7 d, shelled manually and grain dried in a hot air oven  at 45°C for 48 h, to reach a moisture content of ≤ 13% for maize and ≤ 10% for groundnut. Moisture content was assessed using an Infratec™ 1241 Grain Analyzer . Then, maize grains were ground using a coffee mill  and groundnut grains were milled using a blender . Both the coffee mill and blender were washed with 70% ethanol between samples to prevent cross contamination. All samples were divided in two halves, one for microbial and the other for aflatoxin analyzes. Halves for microbial analyzes were stored in hermetic bags at 4°C while those for aflatoxin analyzes were stored at −20°C until analysis.® beaker. Thereafter, 500 μL sample diluent was transferred to a sample cup and 100 μL of sample filtrate was added and mixed by pipetting up and down seven times. A 100-μL of diluted sample extract was transferred into a new sample cup. A strip was placed into the sample cup and left for 6 min. Then, the strip was read in the Accuscan Pro Reader. The lower detection limit of the Reader was 2 μg/kg while the upper detection limit was 150 μg/kg. Samples with more than 150 μg/kg were serially diluted in 65% ethanol, re-analyzed and the dilution factor was considered during the interpretation of results.Aflatoxin levels in maize and groundnut were determined using Reveal Q+ for Aflatoxin kits and Accuscan Pro Reader  following the manufacturer’s instructions. After homogenizing the sub-samples, 10 g were taken, mixed with 50 ml 65% ethanol, and shaken for 3 min using an orbital shaker . The mixture was filtered through fluted Whatman No. 4 filter paper  into a Tri-PourAspergillus section Flavi were isolated and identified as in previous studies in our research group  was used for isolation while 5–2 agar  was used for both identifying Aspergillus section Flavi fungi as well as for saving sporulating cultures. Both media were autoclaved for 20 min at 121°C and cooled to <60°C. After cooling, 0.01 g dichloran and 0.05 g streptomycin sulfate were added to MRBA before pouring into Petri dishes.For microbiological analyzes, the sub-samples from batch 1 were sent to IITA Pathology and Mycotoxin Laboratory in Ibadan, Nigeria under appropriate import/export permits provided by phytosanitary authorities. The sub-samples from batch 2 were analyzed in Katumani. ch group . ModifieAspergillus section Flavi colonies were transferred to 5–2 plates using sterile toothpicks. When the number of putative section Flavi colonies per plate exceeded 10, the sub-sample was serially diluted and re-plated. When section Flavi colonies were not detected in a sample, the sub-sample weight or aliquot was increased accordingly. Colony forming units (CFU) of Aspergillus section Flavi per g of maize and groundnut were calculated as follows: CFU/g = (number of colonies × dilution factor) / weight of samples.Briefly, 1 g of each maize and groundnut sample was obtained from a thoroughly mixed sub-sample and suspended in 10 mL sterile distilled water. The suspension was homogenized by vortexing for 30 s and aliquots of 100 μL were inoculated on MRBA in a biosafety cabinet. Inoculated plates were incubated in the dark . Putative A. flavus L-morphotype. Isolates with numerous small sclerotia were classified as fungi with S-morphology. Colonies showing dark green color and large, rough dark-green spores were assigned as A. parasiticus. Colonies showing brown color were identified as A. tamarii. Pure cultures of 12 isolates per sample were stored in 4 mL vials containing 2 mL sterile water and stored at room temperature (23 ± 2°C) for short-term storage. For long-term storage, cultures were stored on silica gel at 4°C.Isolates with greenish-yellow colonies and no or large sclerotia were identified as 6 spores/mL) of an Aspergillus section Flavi isolate. Cultures were incubated at 31°C  for fermentation of maize grains by the inoculated isolates. Vials containing sterile grains inoculated with sterile water were used as controls.Aflatoxin-free maize grains were sourced in both Katumani and Ibadan. Maize samples were analyzed using Accuscan Pro as above and considered as aflatoxin-free when no aflatoxin was detected in five tests. Five grams of aflatoxin-free grains were weighed into 40 mL clear glass vials, washed with tap water, and soaked overnight in 20 mL distilled water to adjust moisture content to 25%. The grains were then washed thrice with tap water to remove any fermentation product and thereafter autoclaved . The sterile grains were independently inoculated with 500-μL spore suspension  with winCATS 1.4.2 software . The limit of quantification for all experiments was 2 μg/kg.In Ibadan, aflatoxin extracts were re-dissolved in 1 mL dichloromethane. Then, extracts and aflatoxin standards of known concentrations were spotted on thin-layer chromatography (TLC) plates. The plates were developed in diethylene:methanol:water (96:3:1) solution and then visualized under UV light (365 nm). The presence or absence of aflatoxin BA. flavus L-morphotype isolates that did not produce aflatoxins in maize fermentations  were characterized using simple sequence repeats (SSRs) developed for A. flavus  was determined in laboratory competition assays as described earlier (6 spores/mL) of individual atoxigenic isolate and the common toxigenic isolate (1 mL each) were combined and inoculated on 10 g autoclaved maize grain. Maize grains inoculated individually with each atoxigenic isolate, the toxigenic isolate, and water served as controls. There were four replications for each co-inoculation and control treatment. Following inoculation, protocols for maize fermentation and aflatoxin quantification process were similar as described in the previous sections.The ability of representative isolates of 11 selected atoxigenic SSR haplotypes to reduce aflatoxin when co-inoculated with a potent aflatoxin-producing  earlier . BrieflyAspergillus section Flavi species, and aflatoxins produced by the recovered fungi were analyzed using a negative binomial generalized linear model in R studio v3.5.3. Means were separated using Fisher’s protected least significance difference . Aspergillus section Flavi isolates were categorized into aflatoxigenic and atoxigenic based on their ability to produce aflatoxin in maize fermentations. Aflatoxin content in samples at harvest was categorized into four levels: (i) aflatoxin below LOD of the kits (no aflatoxin), (ii) aflatoxin below the EUC threshold (4 μg/kg), (iii) aflatoxin above 4 μg/kg but below the EAC threshold (10 μg/kg), and (iv) aflatoxin above the EAC threshold. A chi-square test of association between aflatoxin concentrations and sample type (maize or groundnut) was performed in SPSS v.22 . Correlation analysis among the population of Aspergillus section Flavi and levels of aflatoxins produced by selected isolates was performed in SPSS v.22.Data on CFU/g, frequency of Before analysis of SSR data, amplicon sizes were converted to repeat number by subtracting the size of the flanking region from the total amplicon size and then dividing by the size of the repeat. Allele frequencies and haplotypes were assessed with GenoDive . RelatioAlthough 76% of both maize and groundnut contaminated with aflatoxin met the EUC threshold ( < 4 μg/kg), and a few maize (3%) and groundnut (6%) samples contained aflatoxin above the EAC threshold  higher in maize  than in groundnut (mean = 266 CFU/g). For maize, there were significant (p < 0.001) differences in fungal densities among provinces (p < 0.005) differed among provinces  higher in maize (92%) than in groundnut  differed among provinces for both crops, with L-morphotype ranging from 85 to 98% in maize, and 45 to 85% in groundnut.The population of nut 60%; ,B. PropoAspergillus section Flavi isolates were toxigenic (A. flavus L-morphotype isolates (1 was significantly (p < 0.001) higher in isolates recovered from groundnut  than in isolates from maize . Fungi with S-morphology generally produced higher concentrations of each type of aflatoxin than the other isolates; A. parasiticus produced higher concentrations of B2 in groundnut and of G1 in maize. Overall, 93.5% of the fungi with S-morphology produced aflatoxins (31.9% produced only B aflatoxins); only two isolates of A. parasiticus did not produce aflatoxins. The recovered A. tamarii fungi did not produce aflatoxin, as expected . On the contrary, aflatoxin concentrations produced by selected fungi with S-morphology had a positive correlation with the population of this type of fungi in samples from which the isolates were recovered . These correlations were consistent for the types of aflatoxins produced by the two types of fungi. Moreover, there was a positive correlation between aflatoxin G1  and G2  produced by A. parasiticus with the population of the fungus in the samples from which the isolates were recovered.Concentrations of aflatoxins produced by selected A. flavus were highly diverse. There were 376 SSR haplotypes among the 1,335 atoxigenic isolates, representing 85 unique SSR haplotypes in the 168 groundnut isolates and 336 unique SSR haplotypes in 1,167 maize isolates. A. flavus found in Burundi. A Neighbor-Net visualization of the unique haplotypes , several genotypes associated with both maize and groundnut were detected across Burundi, including genotypes of active ingredients of the aflatoxin biocontrol product Aflasafe KE01already registered for use in Kenya. The results from the current study provide evidence of the extent of aflatoxin contamination of maize and groundnut at harvest in Burundi and revealed structures and compositions of fungal communities associated with the two crops, with some members of those communities posing a risk during the postharvest stage while others with potential for use in aflatoxin management. The identified fungi with potential for use as biocontrol agents in Burundi need to be tested across Burundi to determine their effectiveness in limiting aflatoxin contamination at pre- and post-harvest stages . Both crops were associated with various types of aflatoxin-producing fungi, including some with the capacity to contaminate crops with dangerous concentrations of aflatoxins. The fungal communities were dominated by the t stages .Overall, only a small fraction of the samples contained aflatoxins above 4 μg/kg, the EUC threshold . AflatoxA. flavus L-morphotype was the predominant species in both maize and groundnut  from a group with frequent occurrence, detected in many regions across Burundi, but with relatively less aflatoxin reduction in the competition experiments . We hypoiomorphs . Three oAspergillus from the crop environment, and this results in low aflatoxin levels in crops at harvest and during storage, even under sub-optimal conditions  indicates that the Aflasafe KE01 active ingredients may be broadly effective across East Africa. On-going field testing of a country specific Aflasafe product for use in Burundi, Aflasafe BU01 , and AflAspergillus section Flavi in both maize and groundnut was composed of a significant proportion of aflatoxigenic strains. Fungi with S-morphology were the most toxigenic while A. flavus L-morphotype isolates were mostly atoxigenic. While the observed and potential contamination can be attributed to the fungi with S-morphology, the high proportion of A. flavus L-morphotype provides hope for developing biocontrol products for use in Burundi. Indeed, among the L-morphotype isolates of A. flavus, 55% were atoxigenic within which a few genetic groups were widely distributed in Burundi. The active ingredients of the biocontrol product registered for use in Kenya (Aflasafe KE01) were also found in Burundi and could be evaluated in Burundi. In addition, another biocontrol product, Aflasafe BU01, was formulated with four different widely distributed genetic groups specific to Burundi. However, biocontrol must be supported by other interventions including awareness creation, timely harvesting, rapid grain drying, appropriate storage structures, sorting, and processing and insect control at pre-and post-harvest stages.Only a small proportion of samples  was contaminated with aflatoxins above the EAC threshold of 10 μg/kg. However, maize and groundnut were associated with highly toxigenic fungi, representing a risk of contamination during the post-harvest stages, which may last for more than 1 year. Further studies to assess contamination further up the value chain are necessary. The population of The original contributions presented in the study are included in the article/RB, PC, and CM designed the overall projects from which data are derived. GN, CM, JW, PN, JA, EN, PC, and RB contributed to the conception and design of the experiments. GN, PN, MN, and EN collected the grain samples. GN, CM, JW, AM, NN, JA, and AO-B conducted and analyzed the microbiology and aflatoxin studies. KC and PC collected and analyzed the molecular data. AO-B, KC, and RB performed distribution mapping of the genetic groups. CM, PC, AO-B, and RB provided guidance. GN, CM, and AO-B drafted the original manuscript followed by editing by other authors. RB and PC secured funds for the study. All authors contributed to the article and approved the submitted version.https://www.cgiar.org/research/).The study was supported by the United States Agency for International Development (USAID), through the Aflatoxin Policy and Program for the East Africa Region (APPEAR) project that was implemented by the International Institute of Tropical Agriculture (IITA), Institut des Science Agronomiques du Burundi (ISABU), Kenya Agricultural and Livestock Research Organization (KALRO) and the East African Community. We acknowledge partial support from the Bill & Melinda Gate Foundation (OPP1133356). Support was also provided by USDA Agricultural Research Project 5347-42000-02-00D. We also gratefully acknowledge additional funding support from the CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), and the CGIAR Plant Health Initiative by CGIAR Trust Fund contributors (The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.The use of trade, firm, or corporation names in these methods is for the information and convenience of the reader. 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