Burning plasma achieved in inertial fusion.

Obtaining a burning plasma is a critical step towards self-sustaining fusion energy1. A burning plasma is one in which the fusion reactions themselves are the primary source of heating in the plasma, which is necessary to sustain and propagate the burn, enabling high energy gain. After decades of fusion research, here we achieve a burning-plasma state in the laboratory. These experiments were conducted at the US National Ignition Facility, a laser facility delivering up to 1.9 megajoules of energy in pulses with peak powers up to 500 terawatts. We use the lasers to generate X-rays in a radiation cavity to indirectly drive a fuel-containing capsule via the X-ray ablation pressure, which results in the implosion process compressing and heating the fuel via mechanical work. The burning-plasma state was created using a strategy to increase the spatial scale of the capsule2,3 through two different implosion concepts4-7. These experiments show fusion self-heating in excess of the mechanical work injected into the implosions, satisfying several burning-plasma metrics3,8. Additionally, we describe a subset of experiments that appear to have crossed the static self-heating boundary, where fusion heating surpasses the energy losses from radiation and conduction. These results provide an opportunity to study α-particle-dominated plasmas and burning-plasma physics in the laboratory.

Engineered exosomes for studies in tumor immunology.

Exosomes are a type of extracellular vesicle (EV) with diameters of 30-150 nm secreted by most of the cells into the extracellular spaces and can alter the microenvironment through cell-to-cell interactions by fusion with the plasma membrane and subsequent endocytosis and release of the cargo. Because of their biocompatibility, low toxicity and immunogenicity, permeability (even through the blood-brain barrier (BBB)), stability in biological fluids, and ability to accumulate in the lesions with higher specificity, investigators have started making designer's exosomes or engineered exosomes to carry biologically active protein on the surface or inside the exosomes as well as using exosomes to carry drugs, micro RNA, and other products to the site of interest. In this review, we have discussed biogenesis, markers, and contents of various exosomes including exosomes of immune cells. We have also discussed the current methods of making engineered and designer's exosomes as well as the use of engineered exosomes targeting different immune cells in the tumors, stroke, as well as at peripheral blood. Genetic engineering and customizing exosomes create an unlimited opportunity to use in diagnosis and treatment. Very little use has been discovered, and we are far away to reach its limits.

ZCCHC17 Modulates Neuronal RNA Splicing and Supports Cognitive Resilience in Alzheimer's Disease.

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis using data from human autopsy tissue (consisting of males and females) and female human cell lines. Co-immunoprecipitation (co-IP) of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA-splicing proteins. ZCCHC17 knockdown results in widespread RNA-splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4-dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find a significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that the maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Neuronal alterations in AKT isotype expression in schizophrenia.

Schizophrenia is characterized by substantial alterations in brain function, and previous studies suggest insulin signaling pathways, particularly involving AKT, are implicated in the pathophysiology of the disorder. This study demonstrates elevated mRNA expression of AKT1-3 in neurons from schizophrenia subjects, contrary to unchanged or diminished total AKT protein expression reported in previous postmortem studies, suggesting a potential decoupling of transcript and protein levels. Sex-specific differential AKT activity was observed, indicating divergent roles in males and females with schizophrenia. Alongside AKT, upregulation of PDPK1, a critical component of the insulin signaling pathway, and several protein phosphatases known to regulate AKT were detected. Moreover, enhanced expression of the transcription factor FOXO1, a regulator of glucose metabolism, hints at possible compensatory mechanisms related to insulin signaling dysregulation. Findings were largely independent of antipsychotic medication use, suggesting inherent alterations in schizophrenia. These results highlight the significance of AKT and related signaling pathways in schizophrenia, proposing that these changes might represent a compensatory response to a primary defect of canonical insulin signaling pathways. This research underscores the need for a detailed understanding of these signaling pathways for the development of effective therapeutic strategies.

MCell4 with BioNetGen: A Monte Carlo simulator of rule-based reaction-diffusion systems with Python interface.

Biochemical signaling pathways in living cells are often highly organized into spatially segregated volumes, membranes, scaffolds, subcellular compartments, and organelles comprising small numbers of interacting molecules. At this level of granularity stochastic behavior dominates, well-mixed continuum approximations based on concentrations break down and a particle-based approach is more accurate and more efficient. We describe and validate a new version of the open-source MCell simulation program (MCell4), which supports generalized 3D Monte Carlo modeling of diffusion and chemical reaction of discrete molecules and macromolecular complexes in solution, on surfaces representing membranes, and combinations thereof. The main improvements in MCell4 compared to the previous versions, MCell3 and MCell3-R, include a Python interface and native BioNetGen reaction language (BNGL) support. MCell4's Python interface opens up completely new possibilities for interfacing with external simulators to allow creation of sophisticated event-driven multiscale/multiphysics simulations. The native BNGL support, implemented through a new open-source library libBNG (also introduced in this paper), provides the capability to run a given BNGL model spatially resolved in MCell4 and, with appropriate simplifying assumptions, also in the BioNetGen simulation environment, greatly accelerating and simplifying model validation and comparison.

Change in Nfkb/Nrf2/Bax Levels by High Monomeric Polyphenols Berries Extract (HMPBE) in Acute and Chronic Secondary Brain Damage.

BACKGROUND/AIMS: High Monomeric Polyphenols Berries Extract (HMPBE) is a formula highly rich in polyphenols clinically proven to enhance learning and memory. It is currently used to enhances cognitive performance including accuracy, working memory and concentration. METHODS: Here, we investigated for the first time the beneficial effects of HMPBE in a mouse model of acute and chronic traumatic brain injury (TBI). RESULTS: HMPBE, at the dose of 15 mg/kg was able to reduce histological alteration as well as inflammation and lipid peroxidation. HMPBE ameliorate TBI by improving Nrf-2 pathway, reducing Nf-kb nuclear translocation and apoptosis, and ameliorating behavioral alteration such as anxiety and depression. Moreover, in the chronic model of TBI, HMPBE administration restored the decline of Tyrosine Hydroxylase (TH) and dopamine transporter (DAT) and the accumulation of a-synuclein into the midbrain region. This finding correlates the beneficial effect of HMPBE administration with the onset of parkinsonism related to traumatic brain damage. CONCLUSION: The data may open a window for developing new support strategies to limit the neuroinflammation event of acute and chronic TBI.

Design of a novel multi-epitope vaccine against Marburg virus using immunoinformatics studies.

Marburg virus (MARV) is a highly contagious and virulent agent belonging to Filoviridae family. MARV causes severe hemorrhagic fever in humans and non-human primates. Owing to its highly virulent nature, preventive approaches are promising for its control. There is currently no approved drug or vaccine against MARV, and management mainly involves supportive care to treat symptoms and prevent complications. Our aim was to design a novel multi-epitope vaccine (MEV) against MARV using immunoinformatics studies. In this study, various proteins (VP35, VP40 and glycoprotein precursor) were used and potential epitopes were selected. CTL and HTL epitopes covered 79.44% and 70.55% of the global population, respectively. The designed MEV construct was stable and expressed in Escherichia coli (E. coli) host. The physicochemical properties were also acceptable. MARV MEV candidate could predict comprehensive immune responses such as those of humoral and cellular in silico. Additionally, efficient interaction to toll-like receptor 3 (TLR3) and its agonist (ß-defensin) was predicted. There is a need for validation of these results using further in vitro and in vivo studies.

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom integrations creates a substantial operational and maintenance burden. These custom integrations also increase the likelihood of unanticipated problems. Standards-based interoperability facilitates AI integration with systems from different vendors into a single environment by enabling seamless exchange between information systems in the radiology workflow. Integrating the Healthcare Enterprise (IHE) is an initiative to improve how computer systems share information across health care domains, including radiology. IHE integrates existing standards-such as Digital Imaging and Communications in Medicine, Health Level Seven, and health care lexicons and ontologies (ie, LOINC, RadLex, SNOMED Clinical Terms)-by mapping data elements from one standard to another. IHE Radiology manages profiles (standards-based implementation guides) for departmental workflow and information sharing across care sites, including profiles for scaling AI processing traffic and integrating AI results. This review focuses on the need for standards-based interoperability to scale AI integration in radiology, including a brief review of recent IHE profiles that provide a framework for AI integration. This review also discusses challenges and additional considerations for AI integration, including technical, clinical, and policy perspectives.

Impact of Clinician Training Background and Stroke Location on Bedside Diagnostic Test Accuracy in the Acute Vestibular Syndrome - A Meta-Analysis.

OBJECTIVE: Acute dizziness/vertigo is usually due to benign inner-ear causes but is occasionally due to dangerous neurologic ones, particularly stroke. Because symptoms and signs overlap, misdiagnosis is frequent and overuse of neuroimaging is common. We assessed the accuracy of bedside findings to differentiate peripheral vestibular from central neurologic causes. METHODS: We performed a systematic search (MEDLINE and Embase) to identify studies reporting on diagnostic accuracy of physical examination in adults with acute, prolonged dizziness/vertigo ("acute vestibular syndrome" [AVS]). Diagnostic test properties were calculated for findings. Results were stratified by examiner type and stroke location. RESULTS: We identified 6,089 citations and included 14 articles representing 10 study cohorts (n = 800). The Head Impulse, Nystagmus, Test of Skew (HINTS) eye movement battery had high sensitivity 95.3% (95% confidence interval [CI] = 92.5-98.1) and specificity 92.6% (95% CI = 88.6-96.5). Sensitivity was similar by examiner type (subspecialists 94.3% [95% CI = 88.2-100.0] vs non-subspecialists 95.0% [95% CI = 91.2-98.9], p = 0.55), but specificity was higher among subspecialists (97.6% [95% CI = 94.9-100.0] vs 89.1% [95% CI = 83.0-95.2], p = 0.007). HINTS sensitivity was lower in anterior cerebellar artery (AICA) than posterior inferior cerebellar artery (PICA) strokes (84.0% [95% CI = 65.3-93.6] vs 97.7% [95% CI = 93.3-99.2], p = 0.014) but was "rescued" by the addition of bedside hearing tests (HINTS+). Severe (grade 3) gait/truncal instability had high specificity 99.2% (95% CI = 97.8-100.0) but low sensitivity 35.8% (95% CI = 5.2-66.5). Early magnetic resonance imaging (MRI)-diffusion-weighted imaging (DWI; within 24-48 hours) was falsely negative in 15% of strokes (sensitivity 85.1% [95% CI = 79.2-91.0]). INTERPRETATION: In AVS, HINTS examination by appropriately trained clinicians can differentiate peripheral from central causes and has higher diagnostic accuracy for stroke than MRI-DWI in the first 24-48 hours. These techniques should be disseminated to all clinicians evaluating dizziness/vertigo. ANN NEUROL 2023;94:295-308.

Enhanced XUV harmonics generated in mixed noble gases using three-color laser fields.

High repetition coherent extreme ultraviolet (XUV) harmonics offer a powerful tool for investigating electron dynamics and understanding the underlying physics in a wide range of systems. We demonstrate the utilization of combined three-color (ω+2ω+3ω) laser fields in the generation of coherent extreme ultraviolet radiation in mixed noble gases. The three-color field results from the combination of fundamental, second-, and third-order harmonics of the near-infrared laser pulses in the nonlinear crystals. Different noble gases were selected as gas targets based on their ionization potentials, which are important parameters for generating higher cut-offs and intensities for the XUV harmonics. Enhanced XUV harmonic intensities were observed in the mixture of He + Kr gases when using three-color laser fields, compared to harmonics generated in the He + Kr mixture under a single-color pump. On the other hand, suppression of XUV harmonic intensity was observed in the mixture of He + Xe under the three-color pump due to the highest ionization level for these two mixed gases at similar laser conditions. Strong harmonic yields in the range of 25 to 80 eV of photon energy were observed.

Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment.

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

Illuminating the dark kinome: utilizing multiplex peptide activity arrays to functionally annotate understudied kinases.

Protein kinases are critical components of a myriad biological processes and strongly associated with various diseases. While kinase research has been a point of focus in biomedical research for several decades, a large portion of the kinome is still considered understudied or "dark," because prior research is targeted towards a subset of kinases with well-established roles in cellular processes. We present an empirical and in-silico hybrid workflow to extend the functional knowledge of understudied kinases. Utilizing multiplex peptide activity arrays and robust in-silico analyses, we extended the functional knowledge of five dark tyrosine kinases (AATK, EPHA6, INSRR, LTK, TNK1) and explored their roles in schizophrenia, Alzheimer's dementia (AD), and major depressive disorder (MDD). Using this hybrid approach, we identified 195 novel kinase-substrate interactions with variable degrees of affinity and linked extended functional networks for these kinases to biological processes that are impaired in psychiatric and neurological disorders. Biochemical assays and mass spectrometry were used to confirm a putative substrate of EPHA6, an understudied dark tyrosine kinase. We examined the EPHA6 network and knowledgebase in schizophrenia using reporter peptides identified and validated from the multi-plex array with high affinity for phosphorylation by EPHA6. Identification and confirmation of putative substrates for understudied kinases provides a wealth of actionable information for the development of new drug treatments as well as exploration of the pathophysiology of disease states using signaling network approaches.

Valorization of Agriculture Residues into Value-Added Products: A Comprehensive Review of Recent Studies.

Global agricultural by-products usually go to waste, especially in developing countries where agricultural products are usually exported as raw products. Such waste streams, once converted to "value-added" products could be an additional source of revenue while simultaneously having positive impacts on the socio-economic well-being of local people. We highlight the utilization of thermochemical techniques to activate and convert agricultural waste streams such as rice and straw husk, coconut fiber, coffee wastes, and okara power wastes commonly found in the world into porous activated carbons and biofuels. Such activated carbons are suitable for various applications in environmental remediation, climate mitigation, energy storage, and conversions such as batteries and supercapacitors, in improving crop productivity and producing useful biofuels.

Financial Viability of the No Surprises Act Independent Dispute Resolution Process: Radiology and Other Hospital-Based Specialties.

BACKGROUND. The federal No Surprises Act (NSA), designed to eliminate surprise medical billing for out-of-network (OON) care for circumstances beyond patients' control, established the independent dispute resolution (IDR) process to settle clinician-payer payment disputes for OON care. OBJECTIVE. The purpose of our study was to assess the fraction of OON claims for which radiologists and other hospital-based specialists can expect to at least break even when challenging payer-determined payments through the NSA IDR process, as a measure of the process's financial viability. METHODS. This retrospective study extracted claims from a national commercial database (Optum's deidentified Clinformatics Data Mart) for hospital-based specialties occurring on the same day as in-network emergency department (ED) visits or inpatient stays from January 2017 to December 2021. OON claims were identified. OON claims batching was simulated using IDR rules. Maximum potential recovered payments from the IDR process were estimated as the difference between the charges and the allowed amount. The percentages of claims for which the maximum potential payment and one-quarter of this amount (a more realistic payment recovery estimate) would exceed IDR fees were determined, using US$150 and US$450 fee thresholds to approximate the range of final 2024 IDR fees. These values represented the percentage of OON claims that would be financially viable candidates for IDR submission. RESULTS. Among 76,221,264 claims for hospital-based specialties associated with in-network ED visits or inpatient stays, 1,482,973 (1.9%) were OON. The maximum potential payment exceeded fee thresholds of US$150 and US$450 for 55.0% and 32.1%, respectively, of batched OON claims for radiologists and 76.8% and 61.3% of batched OON claims for all other hospital-based specialties combined. At payment of one-quarter of that amount, these values were 26.9% and 10.6%, respectively, for radiologists and 56.6% and 38.4% for all other hospital-based specialties combined. CONCLUSION. The IDR process would be financially unviable for a substantial fraction of OON claims for hospital-based specialists (more so for radiology than for other such specialties). CLINICAL IMPACT. Although the NSA enacted important patient protections, IDR fees limit clinicians' opportunities to dispute payer-determined payments and potentially undermine their bargaining power in contract negotiations. Therefore, IDR rulemaking may negatively impact patient access to in-network care.

Risk of stillbirth after a previous caesarean delivery: A Swedish nationwide cohort study.

OBJECTIVES: To investigate the risk of stillbirth in relation to (1) a previous caesarean delivery (CD) compared with those following a vaginal birth (VB); and (2) vaginal birth after caesarean (VBAC) compared with a repeat CD. DESIGN: Population-based cohort study. SETTING: The Swedish Medical Birth registry. POPULATION: Women with their first and second singletons between 1982 and 2012. METHODS: Multivariable logistic regression models were performed to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CI) of the association between CD in the first pregnancy and stillbirth in the second pregnancy and the association between VBAC and stillbirth. Sub-group analyses were performed by types of CD and timing of stillbirth (antepartum and intrapartum). MAIN OUTCOME MEASURES: Stillbirth (antepartum and intrapartum fetal death). RESULTS: Of the 1 771 700 singleton births from 885 850 women, 117 114 (13.2%) women had a CD in the first pregnancy, and 51 755 had VBAC in the second pregnancy. We found a 37% increased odds of stillbirth (aOR 1.37; 95% CI 1.23-1.52) in women with a previous CD compared with VB. The odds of intrapartum stillbirth were higher in the previous pre-labour CD group (aOR 2.72; 95% CI 1.51-4.91) and in the previous in-labour CD group (aOR 1.35; 95% CI 0.76-2.40), although not statistically significant in the latter case. No increased odds were found for intrapartum stillbirth in women who had VBAC (aOR 0.99; 95% CI 0.48-2.06) compared with women who had a repeat CD. CONCLUSIONS: This study confirms that a CD is associated with an increased risk of subsequent stillbirth, with a greater risk among pre-labour CD. This association is not solely mediated by increases in intrapartum asphyxia, uterine rupture or attempted VBAC. Further research is needed to understand this association, but these findings might help healthcare providers to reach optimal decisions regarding mode of birth, particularly when CD is unnecessary.

Pregnancy and birth complications and long-term maternal mental health outcomes: A systematic review and meta-analysis.

BACKGROUND: Few studies have examined the associations between pregnancy and birth complications and long-term (>12 months) maternal mental health outcomes. OBJECTIVES: To review the published literature on pregnancy and birth complications and long-term maternal mental health outcomes. SEARCH STRATEGY: Systematic search of Cumulative Index to Nursing and Allied Health Literature (CINAHL), Excerpta Medica Database (Embase), PsycInfo®, PubMed® and Web of Science from inception until August 2022. SELECTION CRITERIA: Three reviewers independently reviewed titles, abstracts and full texts. DATA COLLECTION AND ANALYSIS: Two reviewers independently extracted data and appraised study quality. Random-effects meta-analyses were used to calculate pooled estimates. The Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines were followed. The protocol was prospectively registered on the International Prospective Register of Systematic Reviews (PROSPERO: CRD42022359017). MAIN RESULTS: Of the 16 310 articles identified, 33 studies were included (3 973 631 participants). Termination of pregnancy was associated with depression (pooled adjusted odds ratio, aOR 1.49, 95% CI 1.20-1.83) and anxiety disorder (pooled aOR 1.43, 95% CI 1.20-1.71). Miscarriage was associated with depression (pooled aOR 1.97, 95% CI 1.38-2.82) and anxiety disorder (pooled aOR 1.24, 95% CI 1.11-1.39). Sensitivity analyses excluding early pregnancy loss and termination reported similar results. Preterm birth was associated with depression (pooled aOR 1.37, 95% CI 1.32-1.42), anxiety disorder (pooled aOR 0.97, 95% CI 0.41-2.27) and post-traumatic stress disorder (PTSD) (pooled aOR 1.75, 95% CI 0.52-5.89). Caesarean section was not significantly associated with PTSD (pooled aOR 2.51, 95% CI 0.75-8.37). There were few studies on other mental disorders and therefore it was not possible to perform meta-analyses. CONCLUSIONS: Exposure to complications during pregnancy and birth increases the odds of long-term depression, anxiety disorder and PTSD.

Understanding and Mitigating Bias in Imaging Artificial Intelligence.

Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. Bias may refer to unequal preference to a person or group owing to preexisting attitudes or beliefs, either intentional or unintentional. However, cognitive bias refers to systematic deviation from objective judgment due to reliance on heuristics, and statistical bias refers to differences between true and expected values, commonly manifesting as systematic error in model prediction (ie, a model with output unrepresentative of real-world conditions). Clinical decisions informed by biased models may lead to patient harm due to action on inaccurate AI results or exacerbate health inequities due to differing performance among patient populations. However, while inequitable bias can harm patients in this context, a mindful approach leveraging equitable bias can address underrepresentation of minority groups or rare diseases. Radiologists should also be aware of bias after AI deployment such as automation bias, or a tendency to agree with automated decisions despite contrary evidence. Understanding common sources of imaging AI bias and the consequences of using biased models can guide preventive measures to mitigate its impact. Accordingly, the authors focus on sources of bias at stages along the imaging machine learning life cycle, attempting to simplify potentially intimidating technical terminology for general radiologists using AI tools in practice or collaborating with data scientists and engineers for AI tool development. The authors review definitions of bias in AI, describe common sources of bias, and present recommendations to guide quality control measures to mitigate the impact of bias in imaging AI. Understanding the terms featured in this article will enable a proactive approach to identifying and mitigating bias in imaging AI. Published under a CC BY 4.0 license. Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Rouzrokh and Erickson in this issue.

Cytoreductive surgery plus chemotherapy versus chemotherapy alone for recurrent epithelial ovarian cancer.

OBJECTIVES: This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To evaluate the benefits and harms of secondary CRS and chemotherapy in comparison to chemotherapy alone for women with platinum-sensitive recurrent epithelial ovarian cancer.

Risk of stillbirth and adverse pregnancy outcomes in a third pregnancy when an earlier pregnancy has ended in stillbirth.

INTRODUCTION: Our study evaluated how a history of stillbirth in either of the first two pregnancies affects the risk of having a stillbirth or other adverse pregnancy outcomes in the third subsequent pregnancy. MATERIAL AND METHODS: We used the Swedish Medical Birth Register to define a population-based cohort of women who had at least three singleton births from 1973 to 2012. The exposure of interest was a history of stillbirth in either of the first two pregnancies. The primary outcome was subsequent stillbirth in the third pregnancy. Secondary outcomes included: preterm birth, preeclampsia, placental abruption and small-for-gestational-age infant. Adjusted logistic regression was performed including maternal age, body mass index, smoking, diabetes and hypertension. A sensitivity analysis was performed excluding stillbirths associated with congenital anomalies, pregestational and gestational diabetes, hypertension and preterm stillbirths. RESULTS: The study contained data on 1 316 175 births, including 8911 stillbirths. Compared with women who had two live births, the highest odds of stillbirth in the third pregnancy were observed in women who had two stillbirths (adjusted odds ratio [aOR] 11.40, 95% confidence interval [95% CI] 2.75-47.70), followed by those who had stillbirth in the second birth (live birth-stillbirth) (aOR 3.59, 95% CI 2.58-4.98), but the odds were still elevated in those whose first birth ended in stillbirth (stillbirth-live birth) (aOR 2.35, 1.68, 3.28). Preterm birth, pre-eclampsia and placental abruption followed a similar pattern. The odds of having a small-for-gestational-age infant were highest in women whose first birth ended in stillbirth (aOR 1.93, 95% CI 1.66-2.24). The increased odds of having a stillbirth in a third pregnancy when either of the earlier births ended in stillbirth remained when stillbirths associated with congenital anomalies, pregestational and gestational diabetes, hypertension or preterm stillbirths were excluded. However, when preterm stillbirths were excluded, the strength of the association was reduced. CONCLUSIONS: Even when they have had a live-born infant, women with a history of stillbirth have an increased risk of adverse pregnancy outcomes; this cannot be solely accounted for by the recurrence of congenital anomalies or maternal medical disorders. This suggests that women with a history of stillbirth should be offered additional surveillance for subsequent pregnancies.

An ultra-fast green ultra-high-performance liquid chromatography-tandem mass spectrometry method for estimating the in vitro metabolic stability of zotizalkib in human liver microsomes.

Zotizalkib (ZTK, TPX-0131) is a fourth-generation highly effective inhibitor of wild-type anaplastic lymphoma kinase (ALK) and ALK-resistant mutations that can penetrate the central nervous system. It exhibited greater potency compared to all five officially approved ALK inhibitors. The aim of this study was to develop a rapid, accurate, eco-friendly, and highly sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for measuring the concentration of ZTK in human liver microsomes (HLMs). The validation aspects of the current UHPLC-MS/MS methodology in the HLMs were conducted in accordance with the bioanalytical method validation standards specified by the US Food and Drug Administration. ZTK and encorafenib were separated using an Agilent C8 column (Eclipse Plus) and an isocratic mobile phase. The calibration curve for the developed ZTK exhibited a linear relationship within the concentration range of 1-3000 ng/mL. The results from the Analytical Green-ness Metric Approach program (0.76) suggested that the created method demonstrated a significant degree of environmental sustainability. The in vitro half-life (t1/2) and intrinsic clearance (Clint) of ZTK were determined to be 15.79 min and 51.35 mL/min/kg, respectively that suggests the ZTK exhibits characteristics similar to those of a medication with a high extraction ratio. These approaches are crucial for the progress of novel pharmaceutical development, especially in improving metabolic stability.