In Utero Exposure to Maternal COVID-19 Vaccination and Offspring Neurodevelopment at 12 and 18 Months.

Importance: Uptake of COVID-19 vaccines among pregnant individuals was hampered by safety concerns around potential risks to unborn children. Data clarifying early neurodevelopmental outcomes of offspring exposed to COVID-19 vaccination in utero are lacking. Objective: To determine whether in utero exposure to maternal COVID-19 vaccination was associated with differences in scores on the Ages and Stages Questionnaire, third edition (ASQ-3), at 12 and 18 months of age. Design, Setting, and Participants: This prospective cohort study, Assessing the Safety of Pregnancy During the Coronavirus Pandemic (ASPIRE), enrolled pregnant participants from May 2020 to August 2021; follow-up of children from these pregnancies is ongoing. Participants, which included pregnant individuals and their offspring from all 50 states, self-enrolled online. Study activities were performed remotely. Exposure: In utero exposure of the fetus to maternal COVID-19 vaccination during pregnancy was compared with those unexposed. Main Outcomes and Measures: Neurodevelopmental scores on validated ASQ-3, completed by birth mothers at 12 and 18 months. A score below the established cutoff in any of 5 subdomains (communication, gross motor, fine motor, problem solving, social skills) constituted an abnormal screen for developmental delay. Results: A total of 2487 pregnant individuals (mean [SD] age, 33.3 [4.2] years) enrolled at less than 10 weeks' gestation and completed research activities, yielding a total of 2261 and 1940 infants aged 12 and 18 months, respectively, with neurodevelopmental assessments. In crude analyses, 471 of 1541 exposed infants (30.6%) screened abnormally for developmental delay at 12 months vs 203 of 720 unexposed infants (28.2%; χ2 = 1.32; P = .25); the corresponding prevalences at 18 months were 262 of 1301 (20.1%) vs 148 of 639 (23.2%), respectively (χ2 = 2.35; P = .13). In multivariable mixed-effects logistic regression models adjusting for maternal age, race, ethnicity, education, income, maternal depression, and anxiety, no difference in risk for abnormal ASQ-3 screens was observed at either time point (12 months: adjusted risk ratio [aRR], 1.14; 95% CI, 0.97-1.33; 18 months: aRR, 0.88; 95% CI, 0.72-1.07). Further adjustment for preterm birth and infant sex did not affect results (12 months: aRR, 1.16; 95% CI, 0.98-1.36; 18 months: aRR, 0.87; 95% CI, 0.71-1.07). Conclusions and Relevance: Results of this cohort study suggest that COVID-19 vaccination was safe during pregnancy from the perspective of infant neurodevelopment to 18 months of age. Additional longer-term research should be conducted to corroborate these findings and buttress clinical guidance with a strong evidence base.

Machine learning identifies key metabolic reactions in bacterial growth on different carbon sources.

Carbon source-dependent control of bacterial growth is fundamental to bacterial physiology and survival. However, pinpointing the metabolic steps important for cell growth is challenging due to the complexity of cellular networks. Here, the elastic net model and multilayer perception model that integrated genome-wide gene-deletion data and simulated flux distributions were constructed to identify metabolic reactions beneficial or detrimental to Escherichia coli grown on 30 different carbon sources. Both models outperformed traditional in silico methods by identifying not just essential reactions but also nonessential ones that promote growth. They successfully predicted metabolic reactions beneficial to cell growth, with high convergence between the models. The models revealed that biosynthetic pathways generally promote growth across various carbon sources, whereas the impact of energy-generating pathways varies with the carbon source. Intriguing predictions were experimentally validated for findings beyond experimental training data and the impact of various carbon sources on the glyoxylate shunt, pyruvate dehydrogenase reaction, and redundant purine biosynthesis reactions. These highlight the practical significance and predictive power of the models for understanding and engineering microbial metabolism.

Genome-scale metabolic network model and phenome of solvent-tolerant Pseudomonas putida S12.

BACKGROUND: Pseudomonas putida S12 is a gram-negative bacterium renowned for its high tolerance to organic solvents and metabolic versatility, making it attractive for various applications, including bioremediation and the production of aromatic compounds, bioplastics, biofuels, and value-added compounds. However, a metabolic model of S12 has yet to be developed. RESULTS: In this study, we present a comprehensive and highly curated genome-scale metabolic network model of S12 (iSH1474), containing 1,474 genes, 1,436 unique metabolites, and 2,938 metabolic reactions. The model was constructed by leveraging existing metabolic models and conducting comparative analyses of genomes and phenomes. Approximately 2,000 different phenotypes were measured for S12 and its closely related KT2440 strain under various nutritional and environmental conditions. These phenotypic data, combined with the reported experimental data, were used to refine and validate the reconstruction. Model predictions quantitatively agreed well with in vivo flux measurements and the batch cultivation of S12, which demonstrated that iSH1474 accurately represents the metabolic capabilities of S12. Furthermore, the model was simulated to investigate the maximum theoretical metabolic capacity of S12 growing on toxic organic solvents. CONCLUSIONS: iSH1474 represents a significant advancement in our understanding of the cellular metabolism of P. putida S12. The combined results of metabolic simulation and comparative genome and phenome analyses identified the genetic and metabolic determinants of the characteristic phenotypes of S12. This study could accelerate the development of this versatile organism as an efficient cell factory for various biotechnological applications.

Experimental Investigation of the Peel Strength of Artificial Leather and Polypropylene Specimens.

This study investigates the surface properties and adhesive strength of polypropylene (PP) in order to enhance the bond between PP injection-molded specimens and polyvinyl chloride (PVC) synthetic artificial leather. Plasma, primer, and flame treatments were applied to the surface of each specimen prepared using the two types of injection molds. The surface morphology, surface roughness, and contact angle were analyzed, and peel-strength analyses and a morphological inspections of the peeled specimens were performed. The peeling strength of the PP injection molding was measured, followed by a morphological examination of the peeled specimens. The plasma and flame treatments improved the peel strength, and the plasma and flame treatments changed the rough exterior to a hydrophilic surface, improving the peel strength. In addition, the primer treatment exhibited a lower peel strength than did the other treatments. This confirmed the low adhesion of the primer to the hydrophobic PP surface. The outcomes of this study can be employed across a multitude of industries that require improved adhesion for PP injection molded products.

Effects of Annealing for Strength Enhancement of FDM 3D-Printed ABS Reinforced with Recycled Carbon Fiber.

This study investigates the effect of annealing on the mechanical properties of fused deposition modeling (FDM) 3D-printed recycled carbon fiber (rCF)-reinforced composites. In this study, filaments for FDM 3D printers are self-fabricated from pure acrylonitrile butadiene styrene (ABS) and ABS reinforced with fiber content of 10 wt% and 20 wt% rCF. This study explores the tensile and flexural properties as a function of the annealing temperature and time for the three different fiber content values. In addition, dimensional measurements of the shape changes are performed to determine the suitability of applying annealing in practical manufacturing processes. The results show that annealing improves the mechanical properties by narrowing the voids between the beads, which occur during the FDM process, and by reducing the gaps between the fibers and polymer. Following annealing, the largest tensile and flexural strength improvements are 12.64% and 42.33%, respectively, for the 20 wt% rCF content samples. Moreover, compared with the pure ABS samples, the annealing effect improves the mechanical properties of the rCF-reinforced samples more effectively, and they have higher dimensional stability, indicating their suitability for annealing. These results are expected to expand the application fields of rCF and greatly increase the potential use of FDM-printed parts.

Identification of a gene cluster for D-tagatose utilization in Escherichia coli B2 phylogroup.

D-Tagatose is a promising low-calorie sugar-substituting sweetener in the food industry. Most ingested D-tagatose is fermented by intestinal microorganisms. Until now, Escherichia coli has been considered incapable of growing on D-tagatose. Here, we discovered a gene cluster involved in D-tagatose utilization in E. coli. The chromosome of the intestinal probiotic E. coli Nissle 1917 contains a six-gene cluster encoding the ABC transporter, D-tagatose kinase, D-tagatose-bisphosphate aldolase, and putative aldose 1-epimerase. The functionality of the gene cluster was experimentally validated. Based on single-gene deletions, D-tagatose dissimilation occurs via D-tagatose 6-phosphate to D-tagatose 1,6-bisphosphate to D-glyceraldehyde 3-phosphate plus dihydroxyacetone phosphate. Remarkably, this gene cluster was located in 93% of the completely sequenced genomes of the E. coli B2 phylogroup, which contains the majority of extraintestinal pathogenic and adherent-invasive E. coli strains prevalent in patients with inflammatory bowel disease. This highlights the importance of understanding the clinical significance of D-tagatose in microbiota alterations.

Novel Dithienopyrrole-Based Conjugated Copolymers: Importance of Backbone Planarity in Achieving High Electrical Conductivity and Thermoelectric Performance.

The development of conjugated polymers with structures that are suitable for efficient molecular doping and charge transport is a key challenge in the construction of high-performance conjugated polymer-based thermoelectric devices. In this study, three novel conjugated polymers based on dithienopyrrole (DTP) are synthesized and their thermoelectric properties are compared. When doped with p-dopant, a donor-acceptor type copolymer, DPP-MeDTP, exhibits higher electrical conductivity and thermoelectric power factor compared to the other donor-donor type copolymers. The high electrical conductivity of DPP-MeDTP compared to the other polymers originates from the high degree of backbone planarity and molecular order, which contributes to its high charge carrier mobility. In addition, the highly crystalline structure of DPP-MeDTP is well maintained upon doping, while the crystalline order of the other polymers decreases significantly upon doping. The findings of this work not only provide insights into the design of DTP-based conjugated polymers for thermoelectric use but also demonstrate the significance of a high degree of molecular order and structural robustness upon doping to achieve high thermoelectric performance.

Association of the ubiquitin specific peptidase 9X -linked and Afadin expression patterns with sexual maturation in boar testis.

Closely correlated expression patterns between ubiquitin specific peptidase 9X-linked (USP9X) and adherens junction formation factor (Afadin) in mouse testis development suggests that Usp9x regulates the deubiquitination of Af-6 (also known as Afadin, AFDN), and subsequently, the cell adhesion dynamics during gametogenesis. However, this relationship has not yet been tested in other domestic animals. The study was examined the temporal and spatial expression patterns of porcine USP9X and AFDN from the pre-pubertal to adult stages using real time-PCR and immunohistochemistry. Furthermore, we detected the transcripts of USP9X and AFDN in the testis of 1-, 6- and 12-months old boar, respectively. USP9X and AFDN were found to have similar expressions patterns, with basal expression after 1 month followed by a significant up-regulation from 6 months (puberty) onwards. In addition, neither the AFDN or USP9X proteins were detected in spermatogenic cells but they were expressed in the leydig cells and sertoli cells. USP9X was detected around the basal lamina during pre-puberty, and predominantly expressed in the leydig cells at puberty. Finally, in adult testis, USP9X was increased at the sertoli cell-cell interface and the sertoli cell-spermatid interface. In summary, closely correlated expression patterns between USP9X and AFDN in boar testis supports the previous findings in mice. Furthermore, the junction connections between the sertoli cells may be regulated by the ubiquitination process mediated via USP9X.

Investigation of gene-environment interactions in relation to tic severity.

Tourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive-compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene-environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene-environment studies.

Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic Escherichia coli Strain Nissle 1917.

Escherichia coli Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studied probiotic. However, to date, its genome-wide metabolic network model has not been developed. Here, we developed a comprehensive and highly curated EcN metabolic model, referred to as iDK1463, based on genome comparison and phenome analysis. The model was improved and validated by comparing the simulation results with experimental results from phenotype microarray tests. iDK1463 comprises 1463 genes, 1313 unique metabolites, and 2984 metabolic reactions. Phenome data of EcN were compared with those of Escherichia coli intestinal commensal K-12 MG1655. iDK1463 was simulated to identify the genetic determinants responsible for the observed phenotypic differences between EcN and K-12. Further, the model was simulated for gene essentiality analysis and utilization of nutrient sources under anaerobic growth conditions. These analyses provided insights into the metabolic mechanisms by which EcN colonizes and persists in the gut. iDK1463 will contribute to the system-level understanding of the functional capacity of gut microbes and their interactions with microbiota and human hosts, as well as the development of live microbial therapeutics.