Survival outcomes in a prospective randomized multicenter Phase III trial comparing patients undergoing anatomical segmentectomy versus standard lobectomy for non-small cell lung cancer up to 2 cm

OBJECTIVES The oncological equivalence of anatomical segmentectomy for early stage non-small cell lung cancer (NSCLC) is still controversial. Primary aim of this study was survival outcomes in combination with improved quality of life after segmentectomy compared with lobectomy in patients with pathological stage Ia NSCLC (up to 2 cm, 7th edition) MATERIALS AND METHODS: We conducted a prospective, randomized, multicenter phase III trial to confirm the non-inferiority of segmentectomy to lobectomy in regard to prognosis (trial No. DRKS00004897). Patients were randomized to undergo either segmentectomy or lobectomy and followed up for 5-years survival and tumor recurrence. The 5-year hazard ratio comparing lobectomy with segmentectomy was required to remain above 0.5. RESULTS Between October 2013 and June 2016, 108 patients with verified or suspected NSCLC up to 2 cm diameter were enrolled; 54 were assigned to lobectomy and 54 (1 drop-out) to segmentectomy. In-hospital and 90 days mortality was 0% in both groups. Overall survival at 5 years was 86.52% in the lobectomy compared to 78.21% in the segmentectomy group (HR = 0.61, (95% CI 0.23-1.66), p-value of non-inferiority test, p-ni = 0.687). Disease free survival was 77.29% for the lobectomy and 77.96% for the segmentectomy patients (HR = 1.50, (95% CI 0.60-3.76), p-ni = 0.019). At a median follow-up of 5 years, no differences were noted in either the locoregional or distant recurrent disease in both groups (9.4% vs 7.4%, p-ni = 0.506). CONCLUSION Overall survival, locoregional and distant recurrences was not significantly difference for patients undergoing either segmentectomy or lobectomy for stage Ia NSCLC. The targeted non-inferiority of segmentectomy to lobectomy could not be proven for primary endpoint overall survival, but was significant for the secondary endpoint of disease free survival

Successful Resuscitation in a Model of Asphyxia and Hemorrhage to Test Different Volume Resuscitation Strategies. A Study in Newborn Piglets After Transition

Background: Evidence for recommendations on the use of volume expansion during cardiopulmonary resuscitation in newborn infants is limited.Objectives: To develop a newborn piglet model with asphyxia, hemorrhage, and cardiac arrest to test different volume resuscitation on return of spontaneous circulation (ROSC). We hypothesized that immediate red cell transfusion reduces time to ROSC as compared to the use of an isotonic crystalloid fluid.Methods: Forty-four anaesthetized and intubated newborn piglets [age 32 h (12–44 h), weight 1,220 g (1,060–1,495g), Median (IQR)] were exposed to hypoxia and blood loss until asystole occurred. At this point they were randomized into two groups: (1) Crystalloid group: receiving isotonic sodium chloride (n = 22). (2) Early transfusion group: receiving blood transfusion (n = 22). In all other ways the piglets were resuscitated according to ILCOR 2015 guidelines [including respiratory support, chest compressions (CC) and epinephrine use]. One hour after ROSC piglets from the crystalloid group were randomized in two sub-groups: late blood transfusion and infusion of isotonic sodium chloride to investigate the effects of a late transfusion on hemodynamic parameters.Results: All animals achieved ROSC. Comparing the crystalloid to early blood transfusion group blood loss was 30.7 ml/kg (22.3–39.6 ml/kg) vs. 34.6 ml/kg (25.2–44.7 ml/kg), Median (IQR). Eleven subjects did not receive volume expansion as ROSC occurred rapidly. Thirty-three animals received volume expansion (16 vs. 17 in the crystalloid vs. early transfusion group). 14.1% vs. 10.5% of previously extracted blood volume in the crystalloid vs. early transfusion group was infused before ROSC. There was no significant difference in time to ROSC between groups [crystalloid group: 164 s (129–198 s), early transfusion group: 163 s (162–199 s), Median (IQR)] with no difference in epinephrine use.Conclusions: Early blood transfusion compared to crystalloid did not reduce time to ROSC, although our model included only a moderate degree of hemorrhage and ROSC occurred early in 11 subjects before any volume resuscitation occurred

Insights into the structure, function and evolution of the radical-SAM 23S rRNA methyltransferase Cfr that confers antibiotic resistance in bacteria

The Cfr methyltransferase confers combined resistance to five classes of antibiotics that bind to the peptidyl tranferase center of bacterial ribosomes by catalyzing methylation of the C-8 position of 23S rRNA nucleotide A2503. The same nucleotide is targeted by the housekeeping methyltransferase RlmN that methylates the C-2 position. Database searches with the Cfr sequence have revealed a large group of closely related sequences from all domains of life that contain the conserved CX3CX2C motif characteristic of radical S-adenosyl-l-methionine (SAM) enzymes. Phylogenetic analysis of the Cfr/RlmN family suggests that the RlmN subfamily is likely the ancestral form, whereas the Cfr subfamily arose via duplication and horizontal gene transfer. A structural model of Cfr has been calculated and used as a guide for alanine mutagenesis studies that corroborate the model-based predictions of a 4Fe–4S cluster, a SAM molecule coordinated to the iron–sulfur cluster (SAM1) and a SAM molecule that is the putative methyl group donor (SAM2). All mutations at predicted functional sites affect Cfr activity significantly as assayed by antibiotic susceptibility testing and primer extension analysis. The investigation has identified essential amino acids and Cfr variants with altered reaction mechanisms and represents a first step towards understanding the structural basis of Cfr activity

Testing theories of post-error slowing

People tend to slow down after they make an error. This phenomenon, generally referred to as post-error slowing, has been hypothesized to reflect perceptual distraction, time wasted on irrelevant processes, an a priori bias against the response made in error, increased variability in a priori bias, or an increase in response caution. Although the response caution interpretation has dominated the empirical literature, little research has attempted to test this interpretation in the context of a formal process model. Here, we used the drift diffusion model to isolate and identify the psychological processes responsible for post-error slowing. In a very large lexical decision data set, we found that post-error slowing was associated with an increase in response caution and—to a lesser extent—a change in response bias. In the present data set, we found no evidence that post-error slowing is caused by perceptual distraction or time wasted on irrelevant processes. These results support a response-monitoring account of post-error slowing

A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis

Funder: The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257Abstract: The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

FIT, a regulatory hub for iron deficiency and stress signaling in roots, and FIT-dependent and -independent gene signatures

Iron (Fe) is vital for plant growth. Plants balance the beneficial and toxic effects of this micronutrient, and tightly control Fe uptake and allocation. Here, we review the role of the basic helix-loop-helix (bHLH) transcription factor FIT (FER-LIKE FE DEFICIENCY-INDUCED TRANSCRIPTION FACTOR) in Fe acquisition. FIT is not only essential, it is also a central regulatory hub in root cells to steer and adjust the rate of Fe uptake by the root in a changing environment. FIT regulates a subset of root Fe deficiency (-Fe) response genes. Based on a combination of co-expression network and FIT-dependent transcriptome analyses, we defined a set of FIT-dependent and FIT-independent gene expression signatures and co-expression clusters that encode specific functions in Fe regulation and Fe homeostasis. These gene signatures serve as markers to integrate novel regulatory factors and signals into the -Fe response cascade. FIT forms a complex with bHLH subgroup Ib transcription factors. Furthermore, it interacts with key regulators from different signaling pathways that either activate or inhibit FIT function to adjust Fe acquisition to growth and environmental constraints. Co-expression clusters and FIT protein interactions suggest a connection of -Fe with ABA responses and root cell elongation processes that can be explored in future studies

Novel sequencing technologies and bioinformatic tools for deciphering the non-coding genome

High-throughput sequencing techniques have significantly increased the molecular diagnosis rate for patients with monogenic disorders. This is primarily due to a substantially increased identification rate of disease mutations in the coding sequence, primarily SNVs and indels. Further progress is hampered by difficulties in the detection of structural variants and the interpretation of variants outside the coding sequence. In this review, we provide an overview about how novel sequencing techniques and state-of-the-art algorithms can be used to discover small and structural variants across the whole genome and introduce bioinformatic tools for the prediction of effects variants may have in the non-coding part of the genome