Chance of healthy versus adverse outcome in subsequent pregnancy after previous loss beyond 16 weeks: data from a specialized follow-up clinic

PURPOSE: Women with a previous fetal demise have a 2-20 fold increased risk of another stillbirth in a subsequent pregnancy when compared to those who have had a live birth. Despite this, there is limited research regarding the management and outcomes of subsequent pregnancies. This study was conducted to accurately quantify the chances of a woman having a healthy subsequent pregnancy after a pregnancy loss. METHODS: A retrospective study was conducted at a tertiary-level unit between March 2019 and April 2021. We collected data on all women with a history of previous fetal demise attending a specialized perinatal history clinic and compared the risk of subsequent stillbirth to those with a normal pregnancy outcome. Outcome data included birth outcome, obstetric and medical complications, gestational age and birth weight and mode of delivery. Those who had healthy subsequent pregnancies were compared with those who experienced adverse outcomes. RESULTS: A total of 101 cases were reviewed. Ninety-six women with subsequent pregnancies after a history of fetal demise from 16 weeks were included. Seventy-nine percent of women (n = 76) delivered a baby at term, without complications. Overall, 2.1% had repeat pregnancy losses (n = 2) and 2.1% delivered babies with fetal growth restriction (n = 2). There were no cases of abruption in a subsequent pregnancy. Eighteen neonates were delivered prematurely (18.4%), 15 of these (83.3%) were due to iatrogenic causes and three (16.7%) were spontaneous. In univariable logistic regression analyses, those with adverse outcomes in subsequent pregnancies had greater odds of pre-eclampsia (Odds ratio *(OR) = 3.89, 95% CI = 1.05-14.43, p = .042) and fetal growth restriction (OR = 4.58, 95% CI = 1.41-14.82, p = 0.011) in previous pregnancies compared to those with healthy outcomes. However, in multivariable logistic regression analyses, neither variable had a significant odds ratio (OR = 2.03, 95% CI = 0.44-9.39, p = .366 and OR = 3.42, 95% CI = 0.90 - 13.09, p = .072 for pre-eclampsia and FGR, respectively). CONCLUSION: Four in five women had a healthy subsequent pregnancy. This is a reassuring figure for women when contemplating another pregnancy, particularly if cared for in a specialist clinic

Identifying allosteric fluctuation transitions between different protein conformational states as applied to Cyclin Dependent Kinase 2

BACKGROUND: The mechanisms underlying protein function and associated conformational change are dominated by a series of local entropy fluctuations affecting the global structure yet are mediated by only a few key residues. Transitional Dynamic Analysis (TDA) is a new method to detect these changes in local protein flexibility between different conformations arising from, for example, ligand binding. Additionally, Positional Impact Vertex for Entropy Transfer (PIVET) uses TDA to identify important residue contact changes that have a large impact on global fluctuation. We demonstrate the utility of these methods for Cyclin-dependent kinase 2 (CDK2), a system with crystal structures of this protein in multiple functionally relevant conformations and experimental data revealing the importance of local fluctuation changes for protein function. RESULTS: TDA and PIVET successfully identified select residues that are responsible for conformation specific regional fluctuation in the activation cycle of Cyclin Dependent Kinase 2 (CDK2). The detected local changes in protein flexibility have been experimentally confirmed to be essential for the regulation and function of the kinase. The methodologies also highlighted possible errors in previous molecular dynamic simulations that need to be resolved in order to understand this key player in cell cycle regulation. Finally, the use of entropy compensation as a possible allosteric mechanism for protein function is reported for CDK2. CONCLUSION: The methodologies embodied in TDA and PIVET provide a quick approach to identify local fluctuation change important for protein function and residue contacts that contributes to these changes. Further, these approaches can be used to check for possible errors in protein dynamic simulations and have the potential to facilitate a better understanding of the contribution of entropy to protein allostery and function

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Abbreviations used: IP 3 R, inositol 1,4

⁎ Cytoplasmic Ca 2+ signals are highly regulated by various ion transporters, including the inositol 1,4,5-trisphosphate (IP 3 ) receptor (IP 3 R), which functions as a Ca 2+ release channel on the endoplasmic reticulum membrane. Crystal structures of the two N-terminal regulatory regions from type 1 IP 3 R have been reported; those of the IP 3 -binding core (IP 3 R CORE ) with bound IP 3 , and the suppressor domain. This study examines the structural effects of ligand binding on an IP 3 R construct, designated IP 3 R N , that contains both the IP 3 -binding core and the suppressor domain. Our circular dichroism results reveal that the IP 3 -bound and IP 3 -free states have similar secondary structure content, consistent with preservation of the overall fold within the individual domains. Thermal denaturation data show that, while IP 3 has a large effect on the stability of IP 3 R CORE , it has little effect on IP 3 R N , indicating that the suppressor domain is critical to the stability of IP 3 R N . The NMR data for IP 3 R N provide evidence for chemical exchange, which may be due to protein conformational dynamics in both apo and IP 3 -bound states: a conclusion supported by the small-angle X-ray scattering data. Further, the scattering data show that IP 3 R N undergoes a change in average conformation in response to IP 3 binding and the presence of Ca 2+ in the solution. Taken together, these data lead us to propose that there are two flexible linkers in the N-terminal region of IP 3 R that join stably folded domains and give rise to an equilibrium mixture of conformational sub-states containing compact and more extended structures. IP 3 binding drives the conformational equilibrium toward more compact structures, while the presence of Ca 2+ drives it to a more extended set

Ligand-induced conformational changes via flexible linkers in the amino-terminal region of the inositol 1,4,5-trisphosphate receptor

Cytoplasmic Ca2+ signals are highly regulated by various ion transporters, including the inositol 1,4,5-trisphosphate (IP3) receptor (IP3), which functions as a Ca2+ release channel on the endoplasmic reticulum membrane. Crystal structures of the two N-terminal regulatory regions from type 1 IP3R have been reported; those of the IP3-binding core (IP3RCORE) with bound IP3, and the suppressor domain. This study examines the structural effects of ligand binding on an IP3R construct, designated IP3RN, that contains both the IP3-binding core and the suppressor domain. Our circular dichroism results reveal that the IP3- bound and IP3-free states have similar secondary structure content, consistent with preservation of the overall fold within the individual domains. Thermal denaturation data show that, while IP3 has a large effect on the stability of IP3RCORE, it has little effect on IP3RN, indicating that the suppressor domain is critical to the stability of IP3RN. The NMR data for IP3RN provide evidence for chemical exchange, which may be due to protein conformational dynamics in both apo and IP3-bound states: a conclusion supported by the small-angle X-ray scattering data. Further, the scattering data show that IP3RN undergoes a change m average conformation in response to IP3-binding and the presence of Ca2+, in the solution. Taken together, these data lead us to propose that there are two flexible linkers in the N-terminal region of lP(3)R that join stably folded domains and give rise to an equilibrium mixture of conformational sub-states containing compact and more extended structures. IP3 binding drives the conformational equilibrium toward more compact structures, while the presence of Ca2+ drives it to a more extended set. © 2007, Elsevier Ltd

Intensive Versus Non-Intensive Induction Therapy for Patients (Pts) with Newly Diagnosed Acute Myeloid Leukemia (AML) Using Two Different Novel Prognostic Models

Abstract Background: Induction therapy for newly diagnosed AML pts can be classified as intensive or non-intensive. Non-intensive therapies are increasingly used in pts aged >65 years due to concerns about their ability to tolerate intensive chemotherapy. However, the relative benefit-risk ratios associated with intensive versus non-intensive therapies in AML pts is likely affected by age, comorbidities, and disease-related characteristics, such as cytogenetic and molecular features. Here, we examine these relationships. Methods: Data from 1295 newly diagnosed AML patients, given induction therapy between 2008 and 2012 at six participating academic centers, were retrospectively collected. We used two previously validated models to define distinct prognostic groups, and within each, compared 2-year mortality rates according to whether pts received intensive or non-intensive therapy. Non-intensive therapy principally included azacitidine, decitabine, or low-dose cytarabine, while intensive therapies primarily included the standard 7+3 regimen or "high-dose" cytarabine combinations with anthracyclines or purine analogs. The first model (Blood 2015; 126:532) was a composite of the prognostic effects of age, comorbidity index, and cytogenetic/genetics risks per European Leukemia Net (ELN) classification. The second (JCO 2011; 29(33): 4417) was a treatment related mortality (TRM) index including 8 pt- and AML-specific risk factors. Results: Age distribution of the pts were ≤49 (23%), 50-59 (20%), 60-69 (33%), and ≥70 (24%) years old. Median follow-up for currently alive pts was 41 (range, 0-99) months. Cytogenetic-molecular risks per ELN classification were favorable (18%), intermediate I and II (39%), or unfavorable (43%). Induction treatments were intensive in 77% and non-intensive in 23% of pts. The proportion of patients receiving non-intensive therapy increased with increasing age (Table 1). Almost all pts (99%) with the lowest composite scores (1-3) received intensive therapies and were therefore omitted from the comparisons with either model. Per the composite model grouping, pts had better survival rates if they received intensive therapy, although the differences were not statistically significant in pts with composite scores ≥10 (Table 2). Pts with TRM scores of 0-4 and ≥5, with a score of 5 corresponding to the median score, statistically significantly benefitted from intensive therapies (Table 2). Among all pts aged 70-79 years old (n=242), 41% received intensive therapy, while 59% received non-intensive therapy. The intensively treated pts in this age range had statistically significantly higher survival rates at 2 years (26% versus 13%, HR: 0.73, 95% CI: 0.54-0.98, P=0.04, Figure). Conclusion: After accounting for underlying prognosis using 2 validated models, we found pts with newly diagnosed AML generally had better survival if they received intensive therapy. This survival benefit was not statistically proven for pts with the highest composite scores (≥10). Early mortality was not increased in older pts given intensive versus non-intensive therapy (Figure), likely due to improvements in supportive care which allowed the greater anti AML effect of intensive therapy to become manifest over time. While we cannot exclude the effects of selection bias, absent a randomized trial our results suggest intensive therapy could be considered for most pts, up to the age of 80 years, regardless of their comorbidity burden. Although results seem better with intensive therapy, less than 50% of patients with composite scores >3 given such therapies were predicted to be alive at 2 years, suggesting the need for randomized clinical trials between novel intensive and non-intensive therapies to achieve better survival. Table 1 Regimen intensity per pt age groups Table 1. Regimen intensity per pt age groups Table 2 Comparisons of hazard ratios (HR) and 2-year rates of survival between intensive and non-intensive initial therapies Table 2. Comparisons of hazard ratios (HR) and 2-year rates of survival between intensive and non-intensive initial therapies Figure. Intensive versus non-intensive therapies among pts aged 70-79 years with AML Figure. Intensive versus non-intensive therapies among pts aged 70-79 years with AML Disclosures Fathi: Bexalata: Other: Advisory Board participation; Celgene: Consultancy, Research Funding; Merck: Other: Advisory Board participation; Agios Pharmaceuticals: Other: Advisory Board participation; Seattle Genetics: Consultancy, Other: Advisory Board participation, Research Funding. Sekeres:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Mukherjee:Novartis: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Wang:Incyte: Speakers Bureau; Immunogen: Research Funding. Shami:JSK Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Research Funding