Age-stratified comorbid and pharmacologic analysis of patients with glioblastoma.

Background: Increased age is a strong and unfavorable prognostic factor for patients with glioblastoma (GBM). However, the relationships between stratified patient age, comorbidities, and medications have yet to be explored in GBM patient survival analyses. Objective: To evaluate co-morbid conditions, tumor-related symptoms, medication prescriptions, and subject age for patients with GBM and to establish potential targets for prospective studies. Methods: Electronic health records for 565 patients with IDHwt GBM were evaluated at a single center between January 1, 2000 and August 9, 2021 were retrospectively assessed. Data were stratified by MGMT promoter methylation status when available and were used to construct multivariable time-dependent cox models and intra-cohort hazards. Results: Younger (<65 years of age) but not older (≥65 years) GBM patients demonstrated a worse prognosis with movement related disabilities (P < 0.0001), gait/balance difficulty (P = 0.04) and weakness (P = 0.007), as well as psychiatric conditions, mental health disorders (P = 0.002) and anxiety (P = 0.001). In contrast, older but not younger GBM patients demonstrated a worse prognosis with epilepsy (P = 0.039). Both groups had worse survival with confusion/altered mental status (P = 0.023 vs < 0.000) and an improved survival with a Temozolomide prescription. Older but not younger GBM patients experienced an improved hazard with a prescription of ace-inhibitor medications (P = 0.048). Conclusion: Age-dependent novel associations between clinical symptoms and medications prescribed for co-morbid conditions were demonstrated in patients with GBM. The results of the current work support future mechanistic studies that investigate the negative relationship(s) between increased age, comorbidities, and drug therapies for differential clinical decision-making across the lifespan of patients with GBM.

Implementation of single-port robotic urologic surgery: experience at a large academic center.

The Single-Port (SP) robotic system is increasingly being implemented in the United States, allowing for several minimally invasive urologic procedures to be performed. The present study aims to describe our single-center experience since the adoption of the SP platform. We retrospectively collected and analyzed consecutive SP cases performed at a major teaching hospital in the Midwest (Rush University Medical Center) from December 2020 to December 2023. Demographic variables were collected. Surgical and pathological outcomes were analyzed in the overall cohort and for each type of procedure. The study timeframe was divided into two periods to assess the evolution of SP technical features over time. In total, 160 procedures were performed, with robot-assisted radical prostatectomy (RARP) being the most common (49.4%). Overall, 54.4% of the procedures were extraperitoneal, with a significantly higher adoption of this approach in the second half of the study period (30% vs 74.3%, p < 0.001). A "plus one" assistant port was adopted in 38.1% of cases, with a shift towards a "pure" single-port surgery in the most recent procedures (21.1% vs 76.7%, p < 0.001). The median LOS was 33.5 h (30-48), with a rate of any grade and CD ≥ 3 postoperative complications of 9.4% and 2.5%, respectively, and a 30-day readmission rate of 1.9%. SP robotic surgery can be safely and effectively implemented for various urologic procedures. With increasing experience, the SP platform allows shifting away from transperitoneal procedures, potentially minimizing postoperative pain, and shortening hospital stay and postoperative recovery.

High-fidelity spin qubit operation and algorithmic initialization above 1 K.

The encoding of qubits in semiconductor spin carriers has been recognized as a promising approach to a commercial quantum computer that can be lithographically produced and integrated at scale1-10. However, the operation of the large number of qubits required for advantageous quantum applications11-13 will produce a thermal load exceeding the available cooling power of cryostats at millikelvin temperatures. As the scale-up accelerates, it becomes imperative to establish fault-tolerant operation above 1 K, at which the cooling power is orders of magnitude higher14-18. Here we tune up and operate spin qubits in silicon above 1 K, with fidelities in the range required for fault-tolerant operations at these temperatures19-21. We design an algorithmic initialization protocol to prepare a pure two-qubit state even when the thermal energy is substantially above the qubit energies and incorporate radiofrequency readout to achieve fidelities up to 99.34% for both readout and initialization. We also demonstrate single-qubit Clifford gate fidelities up to 99.85% and a two-qubit gate fidelity of 98.92%. These advances overcome the fundamental limitation that the thermal energy must be well below the qubit energies for the high-fidelity operation to be possible, surmounting a main obstacle in the pathway to scalable and fault-tolerant quantum computation.

Single-port vs multi-port robot-assisted partial nephrectomy: A single center propensity score-matched analysis.

INTRODUCTION AND OBJECTIVES: The aim of the study is to compare key outcomes of Single-Port (SP) and Multi-Port (MP) robot-assisted partial nephrectomy (RAPN). METHODS: A retrospective analysis was conducted on our prospectively collected database of patients who underwent SP-RAPN or MP-RAPN at our institution from January 2021 to August 2023. To adjust for potential baseline pre-operative confounders, a 1:1 propensity-score matching analysis (PSMa) was performed. The primary endpoint was to compare perioperative outcomes between the two groups. The secondary endpoint was to compare the achievement of the "Trifecta" outcome (defined as negative surgical margins, absence of high-grade complications and change in eGFR values (ΔeGFR) < 10% at 6 months follow-up) in the matched cohort. RESULTS: After PSMa, 30 SP cases were matched 1:1 to 30 MP cases. In the matched cohort, there were no significant differences between SP and MP approaches in operative time, estimated blood loss, ischemia time, transfusions rate, intraoperative complications, postoperative complications, and positive surgical margin rates. Patients who underwent SP-RAPN had a shorter median length of stay [25 (IQR:24.0-34.5) vs 34 (IQR:30.2-48.0) hours, p < 0.003]. The Trifecta outcome was achieved in 16 (57%) of SP patients and 17 (63%) of MP patients (p = 0.8). CONCLUSIONS: SP-RAPN can be safely implemented in a Center with an established MP-RAPN program. Despite being early in the SP-RAPN experience, key surgical outcomes are not compromised. While offering comparable perioperative and short-term functional outcomes, SP-RAPN can translate into faster recovery and shorter LOS, paving the way for outpatient robotic surgery.

Parental and child genetic burden of glycaemic dysregulation and early-life cognitive development: an Asian and European prospective cohort study.

Insulin resistance and glucose metabolism have been associated with neurodevelopmental disorders. However, in the metabolically more susceptible Asian populations, it is not clear whether the genetic burden of glycaemic dysregulation influences early-life neurodevelopment. In a multi-ethnic Asian prospective cohort study in Singapore (Growing Up in Singapore Towards healthy Outcomes (GUSTO)), we constructed child and parental polygenic risk scores (PRS) for glycaemic dysregulation based on the largest genome-wide association studies of type 2 diabetes and fasting glucose among Asians. We found that child PRS for HOMA-IR was associated with a lower perceptual reasoning score at ~7 years (ß = -0. 141, p-value = 0.024, 95% CI -0. 264 to -0. 018) and a lower WIAT-III mean score at ~9 years (ß = -0.222, p-value = 0.001, 95% CI -0.357 to -0.087). This association were consistent in direction among boys and girls. These inverse associations were not influenced by parental PRS and were likely mediated via insulin resistance rather than mediators such as birth weight and childhood body mass index. Higher paternal PRS for HOMA-IR was suggestively associated with lower child perceptual reasoning at ~7 years (ß = -0.172, p-value = 0.002, 95% CI -0.280 to -0.064). Replication analysis in a European cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, showed that higher child PRS for fasting glucose was associated with lower verbal IQ score while higher maternal PRS for insulin resistance was associated with lower performance IQ score in their children at ~8.5 years. In summary, our findings suggest that higher child PRS for HOMA-IR was associated with lower cognitive scores in both Asian and European replication cohorts. Differential findings between cohorts may be attributed to genetic and environmental factors. Further investigation of the functions of the genetic structure and ancestry-specific PRS and a more comprehensive investigation of behavioural mediators may help to understand these findings better.

Prediction and Detection of Glaucomatous Visual Field Progression Using Deep Learning on Macular Optical Coherence Tomography.

PRCIS: A deep learning model trained on macular OCT imaging studies detected clinically significant functional glaucoma progression and was also able to predict future progression. OBJECTIVE: To use macular optical coherence tomography (OCT) imaging to predict the future and detect concurrent visual field progression, respectively, using deep learning. DESIGN: A retrospective cohort study. SUBJECTS: A pretraining data set was comprised of 7,702,201 B-scan images from 151,389 macular OCT studies. The progression detection task included 3902 macular OCT imaging studies from 1534 eyes of 828 patients with glaucoma, and the progression prediction task included 1346 macular OCT studies from 1205 eyes of 784. METHODS: A novel deep learning method was developed to detect glaucoma progression and predict future progression using macular OCT, based on self-supervised pretraining of a vision transformer (ViT) model on a large, unlabeled data set of OCT images. Glaucoma progression was defined as a mean deviation (MD) rate of change of ≤ -0.5 dB/year over 5 consecutive Humphrey visual field tests, and rapid progression was defined as MD change ≤ -1 dB/year. MAIN OUTCOME MEASURES: Diagnostic performance of the ViT model for prediction of future visual field progression and detection of concurrent visual field progression using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. RESULTS: The model distinguished stable eyes from progressing eyes, achieving an AUC of 0.90 (95% CI, 0.88-0.91). Rapid progression was detected with an AUC of 0.92 (95% CI, 0.91-0.93). The model also demonstrated high predictive ability for forecasting future glaucoma progression, with an AUC of 0.85 (95% CI 0.83-0.87). Rapid progression was predicted with an AUC of 0.84 (95% CI 0.81-0.86). CONCLUSIONS: A deep learning model detected clinically significant functional glaucoma progression using macular OCT imaging studies and was also able to predict future progression. Early identification of patients undergoing glaucoma progression or at high risk for future progression may aid in clinical decision-making.

Patterns of Antiseizure Medication Use Following Meningioma Resection: A Single-Institution Experience.

OBJECTIVE: To investigate antiseizure medication (ASM) practice behavior for patients who present with seizures before meningioma resection and to review postoperative ASM management. METHODS: A retrospective study was performed of 112 consecutive patients with meningiomas who underwent resection at a single institution between October 2016 and January 2020. Data were collected through detailed chart review. RESULTS: Of 112 patients, 35 (31%) had a preoperative seizure, and 43 (38%) were prescribed a preoperative ASM. At discharge, 96 patients (86%) were prescribed an ASM, most often 1000 mg daily of levetiracetam (64%, 61/96) and less often higher doses of levetiracetam or other ASMs. By the 6-month postoperative visit, 55 patients (49%) were taking at least 1 ASM, most commonly levetiracetam monotherapy (65%) at 500 mg twice daily (47%). This number further decreased to 45 (40%) patients by 1-year follow-up and 36 (32%) patients by last-known follow-up. By last follow-up (median 27.3 months; range 5.4-57.4 months), 24 patients (21%) had experienced a postoperative seizure, and 36 patients (32%) were never able to discontinue ASMs. Of patients remaining on levetiracetam monotherapy, only 36% remained on levetiracetam 500 mg twice daily. CONCLUSIONS: Approximately two thirds (68%) of patients who underwent surgical resection of meningioma were eventually able to completely discontinue their postoperative ASM regimen. However, nearly one third (32%) of patients required long-term ASM management. Levetiracetam monotherapy was the most common ASM prescribed during the postoperative period, and the proportion of patients requiring either higher doses of levetiracetam or alternative ASMs increased over time.

Discovery of novel cMET-targeting antibody Fab drug conjugates as potential treatment for solid tumors with highly expressed cMET.

BACKGROUND: Solid tumors are becoming prevalent affecting both old and young populations. Numerous solid tumors are associated with high cMET expression. The complexity of solid tumors combined with the highly interconnected nature of the cMET/HGF pathway with other cellular pathways make the pursuit of finding an effective treatment extremely challenging. The current standard of care for these malignancies is mostly small molecule-based chemotherapy. Antibody-based therapeutics as well as antibody drug conjugates are promising emerging classes against cMET-overexpressing solid tumors. RESEARCH DESIGN AND METHODS: In this study, we described the design, synthesis, in vitro and in vivo characterization of cMET-targeting Fab drug conjugates (FDCs) as an alternative therapeutic strategy. The format is comprised of a Fab conjugated to a potent cytotoxic drug via a cleavable linker employing lysine-based and cysteine-based conjugation chemistries. RESULTS: We found that the FDCs have potent anti-tumor efficacies in cancer cells with elevated overexpression of cMET. Moreover, they demonstrated a remarkable anti-tumor effect in a human gastric xenograft mouse model. CONCLUSIONS: The FDC format has the potential to overcome some of the challenges presented by the other classes of therapeutics. This study highlights the promise of antibody fragment-based drug conjugate formats for the treatment of solid tumors.

Structural Characterization and Ligand-Induced Conformational Changes of SenB, a Se-Glycosyltransferase Involved in Selenoneine Biosynthesis.

Selenium (Se) is an essential micronutrient that is found naturally in proteins, nucleic acids, and natural products. Unlike selenoproteins and selenonucleic acids, little is known about the structures of biosynthetic enzymes that incorporate Se into small molecules. Here, we report the X-ray crystal structure of SenB, the first known Se-glycosyltransferase that was recently found to be involved in the biosynthesis of the Se-containing metabolite selenoneine. SenB catalyzes C-Se bond formation using selenophosphate and an activated uridine diphosphate sugar as a Se and glycosyl donor, respectively, making it the first known selenosugar synthase and one of only four bona fide C-Se bond-forming enzymes discovered to date. Our crystal structure, determined to 2.25 Å resolution, reveals that SenB is a type B glycosyltransferase, displaying the prototypical fold with two globular Rossmann-like domains and a catalytic interdomain cleft. By employing complementary structural biology techniques, we find that SenB undergoes both local and global substrate-induced conformational changes, demonstrating a significant increase in α-helicity and a transition to a more compact conformation. Our results provide the first structure of SenB and set the stage for further biochemical characterization in the future.

Long-term antiseizure medication use in patients after meningioma resection: identifying predictors for successful weaning and failures.

OBJECTIVE: To define risk factors for meningioma-related seizures and predictors of successful weaning of antiseizure medications following meningioma resection. METHODS: This is a retrospective study of 95 patients who underwent meningioma resection at a single institution. Primary outcome analyzed was ability to achieve seizure freedom without the use of anti-seizure medication at 6-months, 1-year, and last known follow up. Secondary outcome was postoperative seizure freedom. RESULTS: Preoperative seizures (OR: 11.63, 95% CI [3.64, 37.17], p < 0.0001), non-skull base tumor location (OR: 3.01, 95% CI [1.29, 7.02], p = 0.0128), and modified STAMPE score of 3-5 (OR: 5.42, 95% CI [2.18, 13.52], p = 0.0003) were associated with greater likelihood of remaining on antiseizure medication at 6-month follow up. Preoperative seizures (OR: 4.93, 95% CI: [2.00, 12.16 ], p = 0.0008), intratumoral calcifications (OR: 4.19, 95% CI: [1.61, 14.46], p = 0.0055), modified STAMPE score of 3-5 (OR: 5.42, CI [2.18, 13.52], p = 0.0003), and Ki67 greater than 7% (OR: 5.68, CI [1.61, 20.10], p = 0.0060) were significant risk factors for inability to discontinue ASMs by last follow up. Preoperative seizures (OR: 4.33, 95% CI [1.59, 11.85], p = 0.0050) and modified STAMPE score of 3-5 (OR: 6.09, 95% CI [2.16, 17.20], p = 0.0007) were significant risk factors for postoperative seizures. CONCLUSIONS: Preoperative seizures, modified STAMPE2 score of 3-5, non-skull base tumor location, intratumoral calcifications, and Ki67 > 7% were significant risk factors for inability to achieve seizure freedom without ASMs. In addition, the modified STAMPE2 score successfully predicted increased seizure risk following meningioma resection for patients with a score of 3 or higher.

Generative Artificial Intelligence for Chest Radiograph Interpretation in the Emergency Department.

Importance: Multimodal generative artificial intelligence (AI) methodologies have the potential to optimize emergency department care by producing draft radiology reports from input images. Objective: To evaluate the accuracy and quality of AI-generated chest radiograph interpretations in the emergency department setting. Design, Setting, and Participants: This was a retrospective diagnostic study of 500 randomly sampled emergency department encounters at a tertiary care institution including chest radiographs interpreted by both a teleradiology service and on-site attending radiologist from January 2022 to January 2023. An AI interpretation was generated for each radiograph. The 3 radiograph interpretations were each rated in duplicate by 6 emergency department physicians using a 5-point Likert scale. Main Outcomes and Measures: The primary outcome was any difference in Likert scores between radiologist, AI, and teleradiology reports, using a cumulative link mixed model. Secondary analyses compared the probability of each report type containing no clinically significant discrepancy with further stratification by finding presence, using a logistic mixed-effects model. Physician comments on discrepancies were recorded. Results: A total of 500 ED studies were included from 500 unique patients with a mean (SD) age of 53.3 (21.6) years; 282 patients (56.4%) were female. There was a significant association of report type with ratings, with post hoc tests revealing significantly greater scores for AI (mean [SE] score, 3.22 [0.34]; P < .001) and radiologist (mean [SE] score, 3.34 [0.34]; P < .001) reports compared with teleradiology (mean [SE] score, 2.74 [0.34]) reports. AI and radiologist reports were not significantly different. On secondary analysis, there was no difference in the probability of no clinically significant discrepancy between the 3 report types. Further stratification of reports by presence of cardiomegaly, pulmonary edema, pleural effusion, infiltrate, pneumothorax, and support devices also yielded no difference in the probability of containing no clinically significant discrepancy between the report types. Conclusions and Relevance: In a representative sample of emergency department chest radiographs, results suggest that the generative AI model produced reports of similar clinical accuracy and textual quality to radiologist reports while providing higher textual quality than teleradiologist reports. Implementation of the model in the clinical workflow could enable timely alerts to life-threatening pathology while aiding imaging interpretation and documentation.

Cross-Sectional Analysis of Neurosurgical Residency Websites During the Virtual Interview Cycle.

BACKGROUND: The loss of in-person interviews during the COVID-19 pandemic warrants an investigation into what information is provided to applicants through neurosurgery residency program websites (NRPWs). This study examines NRPWs across the United States and Canada to determine what details are provided to applicants through their respective websites. METHODS: Accreditation Council for Graduate Medical Education accredited neurologic surgery residency programs were identified through the American Association of Neurological Surgeons (AANS) website. NRPWs were searched for 48 criteria, including program overview, application requirements, and curriculum information. Small programs were defined as 1-2 residents per class, while large programs were classified as those with 3-4 residents per year. Content differences were analyzed between the top 20 and remaining programs per the Doximity Residency Navigator Rankings. RESULTS: The most prevalent information among 122 NRPWs was the neurosurgery residency overview (95%), names of faculty members (95%), and names of current residents (94%). Top-20 NRPWs were more likely to include post PGY-7 fellowships (90% vs. 61% P = 0.0108), operating room virtual reality experience (35% vs. 12% P = 0.0160), and faculty research (90% vs. 62% P = 0.0182) than the remainder of the programs. CONCLUSIONS: This study investigates NRPW content after the COVID-19 pandemic. We report broad variability in content provided by various neurosurgical training programs. Higher-ranked neurosurgery programs are more likely to include fellowship information, operating room virtual reality experience, and faculty research than lower-ranked programs.

Biomechanical stress distribution of medical inelastic fabrics with different porosity structures.

Clothing fit and pressure comfort play important role in clothing comfort, especially in medical body sculpting clothing (MBSC). In the present study, different body movements (forward bending, side bending, and twisting) were adopted to simulate and investigate the biomechanical stress distribution of the human body with three kinds of porosity inelastic MBSCs through the finite element analysis method. The elastic modulus of the investigated MBSCs was also measured by means of tensile testing. Analytical results showed that in the compression region during body movements, the investigated inelastic MBSCs endured less compression stress, and most of the stress was transmitted to the human body. Moreover, the stresses on the body surface were decreased with the porosity increasing. However, most of the von Mises stresses on the human body were in the desired pressure comfort range. Therefore, these results could provide potential information in the modification of MBSC for medical applications.

Rapid detection of nicotine and benzoic acid in e-liquids with surface-enhanced Raman scattering and artificial intelligence-assisted spectrum interpretation.

Electronic cigarettes have rapidly gained acceptance recently. Nicotine-containing electronic cigarette liquids (e-liquids) are prohibited in some countries, but are permitted and simply available online in others. A rapid detection method is therefore required for on-site inspection or screening of a large amount of samples. Our previous study demonstrated a surface-enhanced Raman scattering (SERS)-based approach to identify nicotine-containing e-liquids; without any pre-treatment, e-liquid can be directly tested on our solid-phase SERS substrates, made of silver nanoparticle arrays embedded in anodic aluminium oxide nanochannels (Ag/AAO). However, this approach required manual determination of spectral signatures and negative samples should be validated in the second round detection. Here, after examining 406 commercial e-liquids, we refined this approach by developing artificial intelligence (AI)-assisted spectrum interpretations. We also found that nicotine and benzoic acid can be simultaneously detected in our platform. This increased test sensitivity because benzoic acid is usually used in nicotine salts. Around 64% of nicotine-positive samples in this study showed both signatures. Using either cutoffs of nicotine and benzoic acid peak intensities or a machine learning model based on the CatBoost algorithm, over 90% of tested samples can be correctly discriminated with only one round of SERS measurement. False negative and false positive rates were 2.5-4.4% and 4.4-8.9%, respectively, depending on the interpretation method and thresholds applied. The new approach takes only 1 microliter of sample and can be performed in 1-2 min, suitable for on-site inspection with portable Raman detectors. It could also be a complementary platform to reduce samples that need to be analyzed in the central labs and has the potential to identify other prohibited additives.

Jellybean Quantum Dots in Silicon for Qubit Coupling and On-Chip Quantum Chemistry.

The small size and excellent integrability of silicon metal-oxide-semiconductor (SiMOS) quantum dot spin qubits make them an attractive system for mass-manufacturable, scaled-up quantum processors. Furthermore, classical control electronics can be integrated on-chip, in-between the qubits, if an architecture with sparse arrays of qubits is chosen. In such an architecture qubits are either transported across the chip via shuttling or coupled via mediating quantum systems over short-to-intermediate distances. This paper investigates the charge and spin characteristics of an elongated quantum dot-a so-called jellybean quantum dot-for the prospects of acting as a qubit-qubit coupler. Charge transport, charge sensing, and magneto-spectroscopy measurements are performed on a SiMOS quantum dot device at mK temperature and compared to Hartree-Fock multi-electron simulations. At low electron occupancies where disorder effects and strong electron-electron interaction dominate over the electrostatic confinement potential, the data reveals the formation of three coupled dots, akin to a tunable, artificial molecule. One dot is formed centrally under the gate and two are formed at the edges. At high electron occupancies, these dots merge into one large dot with well-defined spin states, verifying that jellybean dots have the potential to be used as qubit couplers in future quantum computing architectures.

Exposure to perfluoroalkyl substances and women's fertility outcomes in a Singaporean population-based preconception cohort.

OBJECTIVES: Experimental models have demonstrated a link between exposure to perfluoroalkyl substances (PFAS) and decreased fertility and fecundability; however, human studies are scarce. We assessed the associations between preconception plasma PFAS concentrations and fertility outcomes in women. METHODS: In a case-control study nested within the population-based Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO), we measured PFAS in plasma collected in 2015-2017 from 382 women of reproductive age trying to conceive. Using Cox proportional hazards regression (fecundability ratios [FRs]) and logistic regression (odds ratios [ORs]) models, we assessed the associations of individual PFAS with time-to-pregnancy (TTP), and the likelihoods of clinical pregnancy and live birth, respectively, over one year of follow-up, adjusting for analytical batch, age, education, ethnicity, and parity. We used Bayesian weighted quantile sum (BWQS) regression to assess the associations of the PFAS mixture with fertility outcomes. RESULTS: We found a 5-10 % reduction in fecundability per quartile increase of exposure to individual PFAS (FRs [95 % CIs] for clinical pregnancy = 0.90 [0.82, 0.98] for PFDA; 0.88 [0.79, 0.99] for PFOS; 0.95 [0.86, 1.06] for PFOA; 0.92 [0.84, 1.00] for PFHpA). We observed similar decreased odds of clinical pregnancy (ORs [95 % CIs] = 0.74 [0.56, 0.98] for PFDA; 0.76 [0.53, 1.09] for PFOS; 0.83 [0.59, 1.17] for PFOA; 0.92 [0.70, 1.22] for PFHpA) and live birth per quartile increases of individual PFAS and the PFAS mixture (ORs [95 % CIs] = 0.61 [0.37, 1.02] for clinical pregnancy, and 0.66 [0.40, 1.07] for live birth). Within the PFAS mixture, PFDA followed by PFOS, PFOA, and PFHpA were the biggest contributors to these associations. We found no evidence of association for PFHxS, PFNA, and PFHpS and the fertility outcomes examined. CONCLUSIONS: Higher PFAS exposures may be associated with decreased fertility in women. The potential impact of ubiquitous PFAS exposures on infertility mechanisms requires further investigation.

Maternal preconception circulating blood biomarker mixtures, child behavioural symptom scores and the potential mediating role of neonatal brain microstructure: the S-PRESTO cohort.

Human brain development starts in the embryonic period. Maternal preconception nutrition and nutrient availability to the embryo may influence brain development at this critical period following conception and early cellular differentiation, thereby affecting offspring neurodevelopmental and behavioural disorder risk. However, studying this is challenging due to difficulties in characterizing preconception nutritional status and few studies have objective neurodevelopmental imaging measures in children. We investigated the associations of maternal preconception circulating blood nutrient-related biomarker mixtures (~15 weeks before conception) with child behavioural symptoms (Child Behaviour Checklist (CBCL), aged 3 years) within the Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO) study. The CBCL preschool form evaluates child behaviours based on syndrome scales and Diagnostic and Statistical Manual of Mental Disorders (DSM) oriented scales. These scales consist of internalizing problems, externalizing problems, anxiety problems, pervasive developmental problems, oppositional defiant, etc. We applied data-driven clustering and a method for modelling mixtures (Bayesian kernel machine regression, BKMR) to account for complex, non-linear dependencies between 67 biomarkers. We used effect decomposition analyses to explore the potential mediating role of neonatal (week 1) brain microstructure, specifically orientation dispersion indices (ODI) of 49 cortical and subcortical grey matter regions. We found that higher levels of a nutrient cluster including thiamine, thiamine monophosphate (TMP), pyridoxal phosphate, pyridoxic acid, and pyridoxal were associated with a higher CBCL score for internalizing problems (posterior inclusion probability (PIP) = 0.768). Specifically, thiamine independently influenced CBCL (Conditional PIP = 0.775). Higher maternal preconception thiamine level was also associated with a lower right subthalamic nucleus ODI (P-value = 0.01) while a lower right subthalamic nucleus ODI was associated with higher CBCL scores for multiple domains (P-value < 0.05). One potential mechanism is the suboptimal metabolism of free thiamine to active vitamin B1, but additional follow-up and replication studies in other cohorts are needed.

Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis.

AIMS: To examine associations of assisted reproductive technology (ART) conception (vs. natural conception: NC) with offspring cardiometabolic health outcomes and whether these differ with age. METHODS AND RESULTS: Differences in systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), lipids, and hyperglycaemic/insulin resistance markers were examined using multiple linear regression models in 14 population-based birth cohorts in Europe, Australia, and Singapore, and results were combined using meta-analysis. Change in cardiometabolic outcomes from 2 to 26 years was examined using trajectory modelling of four cohorts with repeated measures. 35 938 (654 ART) offspring were included in the meta-analysis. Mean age ranged from 13 months to 27.4 years but was <10 years in 11/14 cohorts. Meta-analysis found no statistical difference (ART minus NC) in SBP (-0.53 mmHg; 95% CI:-1.59 to 0.53), DBP (-0.24 mmHg; -0.83 to 0.35), or HR (0.02 beat/min; -0.91 to 0.94). Total cholesterol (2.59%; 0.10-5.07), HDL cholesterol (4.16%; 2.52-5.81), LDL cholesterol (4.95%; 0.47-9.43) were statistically significantly higher in ART-conceived vs. NC offspring. No statistical difference was seen for triglycerides (TG), glucose, insulin, and glycated haemoglobin. Long-term follow-up of 17 244 (244 ART) births identified statistically significant associations between ART and lower predicted SBP/DBP in childhood, and subtle trajectories to higher SBP and TG in young adulthood; however, most differences were not statistically significant. CONCLUSION: These findings of small and statistically non-significant differences in offspring cardiometabolic outcomes should reassure people receiving ART. Longer-term follow-up is warranted to investigate changes over adulthood in the risks of hypertension, dyslipidaemia, and preclinical and clinical cardiovascular disease.