Paternal age and perinatal outcomes: an observational study.

OBJECTIVES: The study's primary aim was to examine the relationship between paternal age and perinatal outcomes. METHODS: This study used data from two hospital birth registries to examine the association between paternal age and adverse perinatal outcomes. The sample included all live singleton births between 2010 and 2022. The primary exposure was paternal age, and the following perinatal outcomes were considered: mode of conception, mode of delivery, pregnancy complications, and neonatal outcomes. RESULTS: A total of 15,232 pregnant women were considered. Maternal and paternal ages were 31.9 ± 5.3 and 36.5 ± 6.5 years, respectively. Independent of maternal, paternal age was associated with lower odds of spontaneous conceptions (OR 0.930, 95 % CI 0.968/0.993; p=0.003) and higher odds of intracytoplasmatic sperm injection (OR 1.054, 95 % CI 1.045/1.062; p=0.0001), respectively. In contrast to maternal age, paternal age decreased the odds of any (OR 0.922, 95 % CI 0.985/0.999; p=0.032) and urgent/emergent (OR 0.984, 95 % CI 0.975/0.993; p=0.0001) cesarean delivery. Paternal age did not affect the gestation length, placental or neonatal weight, blood loss during delivery, and neonatal 5th-minute Apgar score. CONCLUSIONS: Paternal age is associated with perinatal outcomes. These findings suggest that advanced paternal age may have implications for reproductive counseling and prenatal care.

Exposure to Prolonged Rupture of Membranes at Term Increases the Risk for Ventilatory Support in Uninfected Neonates.

OBJECTIVE: The effects of prolonged rupture of membranes (ROMs) on perinatal outcomes are still unclear, and it remains controversial for the management of those labors. This study aims to evaluate how the exposure of pregnant women to a prolonged ROM (≥ 24 hours) affects maternal and neonatal outcomes. STUDY DESIGN: This retrospective cohort study included singleton pregnant women at term delivering between January 2019 and March 2020 in a tertiary hospital. All relevant sociodemographic, pregnancy, and perinatal variables (maternal age, prepregnancy body mass index, labor, and delivery outcomes) were collected anonymously. Data were compared between the "ROM < 24 hours" and "ROM ≥ 24 hours" study groups. RESULTS: A total of 2,689 dyads were included in the study and divided according to their ROM-delivery time: ROM <24 hours (2,369 women, 88.1%), and ROM ≥ 24 hours (320 women, 11.9%). Maternal baseline characteristics were comparable except for the rate of nulliparous women, which was significantly higher among patients with ROM ≥ 24 hours. No significant differences were found regarding infectious neonatal outcomes. However, mechanical ventilation and continuous positive airway pressure were more common among neonates born after ROM ≥ 24 hours. The greater likelihood of neonatal respiratory distress was also confirmed among infants born to Group-B Streptococcus-negative women with ROM ≥ 24 hours (15 out of 267 neonates, 5.6% vs. 52 out of 1,529 with ROM < 24 hours, 3.4%, p = 0.04). CONCLUSION: According to the actual expectant policy, prolonged ROM is associated with an increased risk of respiratory support in noninfected neonates. Further investigations are required to explain such an association. KEY POINTS: · The management of women with prolonged rupture of membranes is controversial.. · The exposure of pregnant women to a prolonged rupture of membranes affects neonatal outcomes.. · Prolonged rupture of membranes is associated with an increased risk of respiratory support, in group-B Streptococcus-negative neonates..

Prelabour rupture of the membranes at term: antibiotic overuse in Italy.

BACKGROUND: The proper management of women with premature rupture of membrane (PROM) and not spontaneously entering in labour remains controversial. The aim of this study was to identify the current management for women with PROM at term according to the Group B Streptococcus (GBS) status across different Italian hospitals. METHODS: Anonymous online survey evaluating: the current practice of women with PROM in terms of management (expectant management vs. induction of labour) and antibiotic prophylaxis according to GBS status. RESULTS: In case of negative GBS status, the 82.4% of respondents wait until 24 hours before labour induction. Antibiotics are administered for prophylaxis in 35.3%, 27.5% and 2% at 18, 12 and 24 hours respectively. The remaining 35.3% of respondents are divided between those using antibiotics only with signs of infections or according to different risk factors (i.e. meconium-stained amniotic fluid or suspected infection). Neonates born from a mother with negative GBS status almost never (90.2%) receive prophylactic antibiotics. In case of positive GBS status, induction is started as soon as possible by 49.1% of respondents; the remnants choose to wait 6 (15.7%), 12 (17.6%), 18 (3.9%) and 24 (13.7%) hours. Antibiotics are administered as soon as possible by 78.4% of clinicians. In the neonates, 51% of neonatologist administer antibiotics upon clinical indications (suspected sepsis); 15.7% use antibiotics routinely or with a short interval between maternal antibiotics and delivery (17.6%). CONCLUSIONS: The management after PROM is highly heterogeneous with an inappropriate extension of antibiotic prophylaxis in cases with negative GBS status.

Lipoprotein(a) Where Do We Stand? From the Physiopathology to Innovative Terapy.

A number of epidemiologic studies have demonstrated a strong association between increasing lipoprotein a [Lp(a)] and cardiovascular disease. This correlation was demonstrated independent of other known cardiovascular (CV) risk factors. Screening for Lp(a) in the general population is not recommended, although Lp(a) levels are predominantly genetically determined so a single assessment is needed to identify patients at risk. In 2019 ESC/EAS guidelines recommend Lp(a) measurement at least once a lifetime, fo subjects at very high and high CV risk and those with a family history of premature cardiovascular disease, to reclassify patients with borderline risk. As concerning medications, statins play a key role in lipid lowering therapy, but present poor efficacy on Lp(a) levels. Actually, treatment options for elevated serum levels of Lp(a) are very limited. Apheresis is the most effective and well tolerated treatment in patients with high levels of Lp(a). However, promising new therapies, in particular antisense oligonucleotides have showed to be able to significantly reduce Lp(a) in phase II RCT. This review provides an overview of the biology and epidemiology of Lp(a), with a view to future therapies.

Prevalence of uterine rupture among women with one prior low transverse cesarean and women with unscarred uterus undergoing labor induction with PGE2: A systematic review and meta-analysis.

BACKGROUND: As uterine rupture may affect as many as 11/1000 women with 1 prior cesarean birth and 5/10.000 women with unscarred uterus undergoing labor induction, we intended to estimate the prevalence of such rare outcome when PGE2 is used for cervical ripening and labor induction. METHODS: We searched MEDLINE, ClinicalTrials.gov and the Cochrane library up to September 1st 2020. Retrospective and prospective cohort studies, as well as randomized controlled trials (RCTs) on singleton viable pregnancies receiving PGE2 for cervical ripening and labor induction were reviewed. Prevalence of uterine rupture was meta-analyzed with Freeman-Tukey double arcsine transformation among women with 1 prior low transverse cesarean section and women with unscarred uterus. RESULTS: We reviewed 956 full text articles to include 69 studies. The pooled prevalence rate of uterine rupture is estimated to range between 2 and 9 out of 1000 women with 1 prior low transverse cesarean (5/1000; 95%CI 2-9/1000, 122/9000). The prevalence of uterine rupture among women with unscarred uterus is extremely low, reaching at most 0.7/100.000 (<1/100.000.000; 95%CI <1/100.000.000-0.7/100.000, 8/17.684). CONCLUSIONS: Uterine rupture is a rare event during cervical ripening and labor induction with PGE2.

Pregnant woman infected by Coronavirus disease (COVID-19) and calcifications of the fetal bowel and gallbladder.

COVID-19 was declared to be a pandemic due to the rapid increase of cases around the world, including the number of pregnant women. Data about vertical transmission of COVID-19 are still limited and controversial: in most cases, although a positive mother, the virus could not be isolated in amniotic fluid, cord blood, breast milk or neonatal throat swab in these patients. No data have been published about possible intrauterine sonographic signs of infection. A pregnant woman was diagnosed with SARS-CoV-2 at 35+5 weeks of gestation and managed conservatively at home. At transabdominal ultrasound at 38+3 weeks, fetal bowel and gallbladder calcifications were noted. CMV and other infectious agents were ruled out; an iterative caesarean section was performed at 38+5 weeks without complications. Placenta resulted negative for SARS-CoV-2; the umbilical cord blood sample was IgG positive and IgM negative as per maternal infection. The baby developed respiratory distress syndrome requiring endotracheal surfactant administration and nasal-CPAP for one day but nasopharyngeal swabs at birth and after 48 hours were SARS-CoV-2 negative. Neonatal abdominal ultrasound showed normal liver, acalculous gallbladder with mild parietal thickening. The baby was discharged in good conditions. Although gallbladder calcifications and echogenic bowel are highly suspicious of viral infection and were thought to be due to the vertical transmission of SARS-CoV-2, these findings were not corroborated by the results of our diagnostic tests; these sonographic findings might represent a false positive of fetal infection in mother affected by COVID-19 since vertical transmission appears to be rare.

Genome-wide RNA-seq analysis indicates that the DAG1 transcription factor promotes hypocotyl elongation acting on ABA, ethylene and auxin signaling.

Hypocotyl elongation is influenced by light and hormones, but the molecular mechanisms underlying this process are not yet fully elucidated. We had previously suggested that the Arabidopsis DOF transcription factor DAG1 may be a negative component of the mechanism of light-mediated inhibition of hypocotyl elongation, as light-grown dag1 knock-out mutant seedlings show significant shorter hypocotyls than the wild type. By using high-throughput RNA-seq, we compared the transcriptome profile of dag1 and wild type hypocotyls and seedlings. We identified more than 250 genes differentially expressed in dag1 hypocotyls, and their analysis suggests that DAG1 is involved in the promotion of hypocotyl elongation through the control of ABA, ethylene and auxin signaling. Consistently, ChIP-qPCR results show that DAG1 directly binds to the promoters of WRKY18 encoding a transcription factor involved in ABA signaling, of the ethylene- induced gene ETHYLENE RESPONSE FACTOR (ERF2), and of the SMALL AUXIN UP RNA 67 (SAUR67), an auxin-responding gene encoding a protein promoting hypocotyl cell expansion.

Assessment of model accuracy estimations in CASP12.

The record high 42 model accuracy estimation methods were tested in CASP12. The paper presents results of the assessment of these methods in the whole-model and per-residue accuracy modes. Scores from four different model evaluation packages were used as the "ground truth" for assessing accuracy of methods' estimates. They include a rigid-body score-GDT_TS, and three local-structure based scores-LDDT, CAD and SphereGrinder. The ability of methods to identify best models from among several available, predict model's absolute accuracy score, distinguish between good and bad models, predict accuracy of the coordinate error self-estimates, and discriminate between reliable and unreliable regions in the models was assessed. Single-model methods advanced to the point where they are better than clustering methods in picking the best models from decoy sets. On the other hand, consensus methods, taking advantage of the availability of large number of models for the same target protein, are still better in distinguishing between good and bad models and predicting local accuracy of models. The best accuracy estimation methods were shown to perform better with respect to the frozen in time reference clustering method and the results of the best method in the corresponding class of methods from the previous CASP. Top performing single-model methods were shown to do better than all but three CASP12 tertiary structure predictors when evaluated as model selectors.

Evaluation of the template-based modeling in CASP12.

The article describes results of numerical evaluation of CASP12 models submitted on targets for which structural templates could be identified and for which servers produced models of relatively high accuracy. The emphasis is on analysis of details of models, and how well the models compete with experimental structures. Performance of contributing research groups is measured in terms of backbone accuracy, all-atom local geometry, and the ability to estimate local errors in models. Separate analyses for all participating groups and automatic servers were carried out. Compared with the last CASP, two years ago, there have been significant improvements in a number of areas, particularly the accuracy of protein backbone atoms, accuracy of sequence alignment between models and available structures, increased accuracy over that which can be obtained from simple copying of a closest template, and accuracy of modeling of sub-structures not present in the closest template. These advancements are likely associated with more effective strategies to build non-template regions of the targets ab initio, better algorithms to combine information from multiple templates, enhanced refinement methods, and better methods for estimating model accuracy.

Critical assessment of methods of protein structure prediction (CASP)-Round XII.

This article reports the outcome of the 12th round of Critical Assessment of Structure Prediction (CASP12), held in 2016. CASP is a community experiment to determine the state of the art in modeling protein structure from amino acid sequence. Participants are provided sequence information and in turn provide protein structure models and related information. Analysis of the submitted structures by independent assessors provides a comprehensive picture of the capabilities of current methods, and allows progress to be identified. This was again an exciting round of CASP, with significant advances in 4 areas: (i) The use of new methods for predicting three-dimensional contacts led to a two-fold improvement in contact accuracy. (ii) As a consequence, model accuracy for proteins where no template was available improved dramatically. (iii) Models based on a structural template showed overall improvement in accuracy. (iv) Methods for estimating the accuracy of a model continued to improve. CASP continued to develop new areas: (i) Assessing methods for building quaternary structure models, including an expansion of the collaboration between CASP and CAPRI. (ii) Modeling with the aid of experimental data was extended to include SAXS data, as well as again using chemical cross-linking information. (iii) A team of assessors evaluated the suitability of models for a range of applications, including mutation interpretation, analysis of ligand binding properties, and identification of interfaces. This article describes the experiment and summarizes the results. The rest of this special issue of PROTEINS contains papers describing CASP12 results and assessments in more detail.

The computational prediction of protein assemblies.

The function of proteins in the cell is almost always mediated by their interaction with different partners, including other proteins, nucleic acids or small organic molecules. The ability of identifying all of them is an essential step in our quest for understanding life at the molecular level. The inference of the protein complex composition and of its molecular details can also provide relevant clues for the development and the design of drugs. In this short review, I will discuss the computational aspects of the analysis and prediction of protein-protein assemblies and discuss some of the most recent developments as seen in the last Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment.

Dynamics behind affinity maturation of an anti-HCMV antibody family influencing antigen binding.

The investigation of antibody affinity maturation and its effects on antigen binding is important with respect to understanding the regulation of the immune response. To shed light on this crucial process, we analyzed two Igs neutralizing the human cytomegalovirus: the primary germline antibody M2J1 and its related mature antibody 8F9. Both antibodies target the AD-2S1 epitope of the gB envelope protein and are considered to establish similar interactions with the cognate antigen. We used molecular dynamics simulations to understand the effect of mutations on the antibody-antigen interactions. The results provide a qualitative explanation for the increased 8F9 peptide affinity compared with that of M2J1. The emerging atomistic-detailed description of these complexes reveals the molecular effects of the somatic hypermutations occurring during affinity maturation.

PIGSPro: prediction of immunoGlobulin structures v2.

PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro.

A computational approach for the functional classification of the epigenome.

BACKGROUND: In the last decade, advanced functional genomics approaches and deep sequencing have allowed large-scale mapping of histone modifications and other epigenetic marks, highlighting functional relationships between chromatin organization and genome function. Here, we propose a novel approach to explore functional interactions between different epigenetic modifications and extract combinatorial profiles that can be used to annotate the chromatin in a finite number of functional classes. Our method is based on non-negative matrix factorization (NMF), an unsupervised learning technique originally employed to decompose high-dimensional data in a reduced number of meaningful patterns. We applied the NMF algorithm to a set of different epigenetic marks, consisting of ChIP-seq assays for multiple histone modifications, Pol II binding and chromatin accessibility assays from human H1 cells. RESULTS: We identified a number of chromatin profiles that contain functional information and are biologically interpretable. We also observe that epigenetic profiles are characterized by specific genomic contexts and show significant association with distinct genomic features. Moreover, analysis of RNA-seq data reveals that distinct chromatin signatures correlate with the level of gene expression. CONCLUSIONS: Overall, our study highlights the utility of NMF in studying functional relationships between different epigenetic modifications and may provide new biological insights for the interpretation of the chromatin dynamics.

Superposition-free comparison and clustering of antibody binding sites: implications for the prediction of the nature of their antigen.

We describe here a superposition free method for comparing the surfaces of antibody binding sites based on the Zernike moments and show that they can be used to quickly compare and cluster sets of antibodies. The clusters provide information about the nature of the bound antigen that, when combined with a method for predicting the number of direct antibody antigen contacts, allows the discrimination between protein and non-protein binding antibodies with an accuracy of 76%. This is of relevance in several aspects of antibody science, for example to select the framework to be used for a combinatorial antibody library.

Genome-wide identification of direct HBx genomic targets.

BACKGROUND: The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. RESULTS: ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR-33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. CONCLUSIONS: Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication.

PepComposer: computational design of peptides binding to a given protein surface.

There is a wide interest in designing peptides able to bind to a specific region of a protein with the aim of interfering with a known interaction or as starting point for the design of inhibitors. Here we describe PepComposer, a new pipeline for the computational design of peptides binding to a given protein surface. PepComposer only requires the target protein structure and an approximate definition of the binding site as input. We first retrieve a set of peptide backbone scaffolds from monomeric proteins that harbor the same backbone arrangement as the binding site of the protein of interest. Next, we design optimal sequences for the identified peptide scaffolds. The method is fully automatic and available as a web server at http://biocomputing.it/pepcomposer/webserver.

Critical assessment of methods of protein structure prediction: Progress and new directions in round XI.

Modeling of protein structure from amino acid sequence now plays a major role in structural biology. Here we report new developments and progress from the CASP11 community experiment, assessing the state of the art in structure modeling. Notable points include the following: (1) New methods for predicting three dimensional contacts resulted in a few spectacular template free models in this CASP, whereas models based on sequence homology to proteins with experimental structure continue to be the most accurate. (2) Refinement of initial protein models, primarily using molecular dynamics related approaches, has now advanced to the point where the best methods can consistently (though slightly) improve nearly all models. (3) The use of relatively sparse NMR constraints dramatically improves the accuracy of models, and another type of sparse data, chemical crosslinking, introduced in this CASP, also shows promise for producing better models. (4) A new emphasis on modeling protein complexes, in collaboration with CAPRI, has produced interesting results, but also shows the need for more focus on this area. (5) Methods for estimating the accuracy of models have advanced to the point where they are of considerable practical use. (6) A first assessment demonstrates that models can sometimes successfully address biological questions that motivate experimental structure determination. (7) There is continuing progress in accuracy of modeling regions of structure not directly available by comparative modeling, while there is marginal or no progress in some other areas. Proteins 2016; 84(Suppl 1):4-14. © 2016 Wiley Periodicals, Inc.

A structural view of microRNA-target recognition.

It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed by AGO, a miRNA and 22 nt of a target mRNA that putatively interacts with it. We show here that MiREN can be used to assess the likelihood that an RNA molecule is the target of a given miRNA and that this approach is more accurate than other existing methods, usually based on sequence or sequence-related features. Our results also suggest that AGO plays a relevant role in the selection of the miRNA targets. Our method can represent an additional step for refining predictions made by faster but less accurate classical methods for the identification of miRNA targets.