Point-of-care high-sensitivity cardiac troponin in suspected acute myocardial infarction assessed at baseline and 2†h.

BACKGROUND AND AIMS: Strategies to assess patients with suspected acute myocardial infarction (AMI) using a point-of-care (POC) high-sensitivity cardiac troponin I (hs-cTnI) assay may expedite emergency care. A 2-h POC hs-cTnI strategy for emergency patients with suspected AMI was derived and validated. METHODS: In two international, multi-centre, prospective, observational studies of adult emergency patients (1486 derivation cohort and 1796 validation cohort) with suspected AMI, hs-cTnI (Siemens Atellica® VTLi) was measured at admission and 2 h later. Adjudicated final diagnoses utilized the hs-cTn assay in clinical use. A risk stratification algorithm was derived and validated. The primary diagnostic outcome was index AMI (Types 1 and 2). The primary safety outcome was 30-day major adverse cardiac events incorporating AMI and cardiac death. RESULTS: Overall, 81 (5.5%) and 88 (4.9%) patients in the derivation and validation cohorts, respectively, had AMI. The 2-h algorithm defined 66.1% as low risk with a sensitivity of 98.8% [95% confidence interval (CI) 89.3%-99.9%] and a negative predictive value of 99.9 (95% CI 99.2%-100%) for index AMI in the derivation cohort. In the validation cohort, 53.3% were low risk with a sensitivity of 98.9% (95% CI 92.4%-99.8%) and a negative predictive value of 99.9% (95% CI 99.3%-100%) for index AMI. The high-risk metrics identified 5.4% of patients with a specificity of 98.5% (95% CI 96.6%-99.4%) and a positive predictive value of 74.5% (95% CI 62.7%-83.6%) for index AMI. CONCLUSIONS: A 2-h algorithm using a POC hs-cTnI concentration enables safe and efficient risk assessment of patients with suspected AMI. The short turnaround time of POC testing may support significant efficiencies in the management of the large proportion of emergency patients with suspected AMI.

Interlamellar-Spacing Engineering of Stable and Toxicity-Reduced 2D Perovskite Single Crystal for High-Resolution X-ray Imaging.

Two-dimensional (2D) lead halide perovskites are excellent candidates for X-ray detection due to their high resistivity, high ion migration barrier, and large X-ray absorption coefficients. However, the high toxicity and long interlamellar distance of the 2D perovskites limit their wide application in high sensitivity X-ray detection. Herein, we demonstrate stable and toxicity-reduced 2D perovskite single crystals (SCs) realized by interlamellar-spacing engineering via a distortion self-balancing strategy. The engineered low-toxicity 2D SC detectors achieve high stability, large mobility-lifetime product, and therefore high-performance X-ray detection. Specifically, the detectors exhibit a record high sensitivity of 13488 µC Gy1- cm-2, a low detection limit of 8.23 nGy s-1, as well as a high spatial resolution of 8.56 lp mm-1 in X-ray imaging, all of which are far better than those of the high-toxicity 2D lead-based perovskite detectors. These advances provide a new technical solution for the low-cost fabrication of low-toxicity, scalable X-ray detectors.

Ultrafast and Parts-per-Billion-Level MEMS Gas Sensors by Hetero-Interface Engineering of 2D/2D Cu-TCPP@ZnIn2S4 with Enriched Surface Sulfur Vacancies.

The primary challenge for resonant-gravimetric gas sensors is the synchronous improvement of the sensitivity and response time, which is restricted by low adsorption capacity and slow mass transfer in the sensing process and remains a great challenge. In this study, a novel 2D/2D Cu-TCPP@ZnIn2S4 composite is successfully constructed, in which Cu-TCPP MOF is used as a core substrate for the growth of 2D ultrathin ZnIn2S4 nanosheets with well-defined {0001} crystalline facets. The Cu-TCPP@ZnIn2S4 sensor exhibited high sensitivity (1.5 Hz@50 and 2.3 Hz@100 ppb), limit of detection (LOD: 50 ppb), and ultrafast (9 s @500 ppb) detection of triethylamine (TEA), which is the lowest LOD and the fastest sensor among the reported TEA sensors at room temperature, tackling the bottleneck for the ultrafast detection of the resonant-gravimetric sensor. These above results provide an innovative and easily achievable pathway for the synthesis of heterogeneous structure sensing materials.

Integrated MICROFASP Method with CZE-Based Fractionation Technique and NanoRPLC-ESI-MS/MS for a Comprehensive Proteomics Analysis of a Submicrogram Sample.

We report a loss-less two-dimensional (2D) separation platform that integrated capillary zone electrophoresis (CZE) fractionation and nanoRPLC-ESI-MS/MS for a comprehensive proteomics analysis of a submicrogram sample. Protein digest was injected into the linear polyacrylamide-coated capillary, followed by CZE separation. The schemes for collecting the fractions were carefully optimized to maximize the protein coverage. The peptide fractions were directly eluted into the autosampler insert vials, followed by the nanoRPLC-ESI-MS/MS analysis without lyophilization and redissolution, thus dramatically minimizing sample loss and potential contamination. The integrated platform generated 30,845 unique peptides and 5231 protein groups from 500 ng of a HeLa protein digest within 11.5 h (90 min CZE fractionation plus 10 h LC-MS analysis). Finally, the developed platform was used to analyze the protein digest prepared by the MICROFASP method with 1 µg of cell lysate as the starting material. Three thousand seven hundred ninety-six (N = 2, RSD = 4.95%) protein groups and 20,577 (N = 2, RSD = 7.89%) peptides were identified from only 200 ng of the resulted tryptic digest within 5.5 h. The results indicated that the combination of the MICROFASP method and the developed CZE/nanoRPLC-MS/MS 2D separation platform enabled comprehensive proteome profiling of a submicrogram biological sample. Data are available via ProteomeXchange with the identifier PXD052735.

Cardiac biomarker responses following high-intensity interval and continuous exercise: the influence of ACE-I/D gene polymorphism and training status in men.

This study aimed to investigate the relationship between pre- and postexercise cardiac biomarker release according to athletic status (trained vs. untrained) and to establish whether the I/D polymorphism in the angiotensin-converting enzyme (ACE) gene had an influence on cardiac biomarkers release with specific regard on the influence of the training state. We determined cardiac troponin I (cTnI) and N-terminal pro-brain natriuretic peptide (NT-proBNP) in 29 trained and 27 untrained male soccer players before and after moderate-intensity continuous exercise (MICE) and high-intensity interval exercise (HIIE) running tests. Trained soccer players had higher pre (trained: 0.014 ± 0.007 ng/mL; untrained: 0.010 ± 0.005 ng/mL) and post HIIE (trained: 0.031 ± 0.008 ng/mL; untrained: 0.0179 ± 0.007) and MICE (trained: 0.030 ± 0.007 ng/mL; untrained: 0.018 ± 0.007) cTnI values than untrained subjects, but the change with exercise (ΔcTnI) was similar between groups. There was no significant difference in baseline and postexercise NT-proBNP between groups. NT-proBNP levels were elevated after both HIIE and MICE. Considering three ACE genotypes, the mean pre exercise cTnI values of the trained group (DD: 0.015 ± 0.008 ng/mL, ID: 0.015 ± 0.007 ng/mL, and II: 0.014 ± 0.008 ng/mL) and their untrained counterparts (DD: 0.010 ± 0.004 ng/mL, ID: 0.011 ± 0.004 ng/mL, and II: 0.010 ± 0.006 ng/mL) did not show any significant difference. To sum up, noticeable difference in baseline cTnI was observed, which was related to athletic status but not ACE genotypes. Neither athletic status nor ACE genotypes seemed to affect the changes in cardiac biomarkers in response to HIIE and MICE, indicating that the ACE gene does not play a significant role in the release of exercise-induced cardiac biomarkers indicative of cardiac damage in Iranian soccer players.NEW & NOTEWORTHY Our study investigated the impact of athletic status and angiotensin-converting enzyme (ACE) gene I/D polymorphism on cardiac biomarkers in soccer players. Trained players showed higher baseline cardiac troponin I (cTnI) levels, whereas postexercise ΔcTnI remained consistent across groups. N-terminal pro-brain natriuretic peptide increased after exercise in both groups, staying within normal limits. ACE genotypes did not significantly affect pre-exercise cTnI. Overall, athletic status influences baseline cTnI, but neither it nor ACE genotypes significantly impact exercise-induced cardiac biomarker responses in this population.

Establishing optimal cutoff values for high-sensitivity cardiac troponin algorithms in risk stratification of acute myocardial infarction.

Acute myocardial infarction (AMI) is a leading cause of mortality globally, highlighting the need for timely and accurate diagnostic strategies. Cardiac troponin has been the biomarker of choice for detecting myocardial injury. A dynamic change in concentrations supports the diagnosis of AMI in the setting of evidence of acute myocardial ischemia. The new generation of high-sensitivity cardiac troponin (hs-cTn) assays has significantly improved analytical sensitivity but at the expense of decreased clinical specificity. As a result, sophisticated algorithms are required to differentiate AMI from non-AMI patients. Establishing optimal hs-cTn cutoffs for these algorithms to rule out and rule in AMI has been the subject of intensive investigations. These efforts have evolved from examining the utility of the hs-cTn 99th percentile upper reference limit, comparing the percentage versus absolute delta thresholds, and evaluating the performance of an early European Society of Cardiology-recommended 3 h algorithm, to the development of accelerated 1 h and 2 h algorithms that combine the admission hs-cTn concentrations and absolute delta cutoffs to rule out and rule in AMI. Specific cutoffs for individual confounding factors such as sex, age, and renal insufficiency have also been investigated. At the same time, concerns such as whether the small delta thresholds exceed the analytical and biological variations of hs-cTn assays and whether the algorithms developed in European study populations fit all other patient cohorts have been raised. In addition, the accelerated algorithms leave a substantial number of patients in a non-diagnostic observation zone. How to properly diagnose patients falling in this zone and those presenting with elevated baseline hs-cTn concentrations due to the presence of confounding factors or comorbidities remain open questions. Here we discuss the developments described above, focusing on criteria and underlying considerations for establishing optimal cutoffs. In-depth analyses are provided on the influence of biological variation, analytical imprecision, local AMI rate, and the timing of presentation on the performance metrics of the accelerated hs-cTn algorithms. Developing diagnostic strategies for patients who remain in the observation zone and those presenting with confounding factors are also reviewed.

Highly Sensitive Fiber Crossbar Sensors Enabled by Second-Order Synergistic Effect of Air Capacitance and Equipotential Body.

Fiber crossbars, an emerging electronic device, have become the most promising basic unit for advanced smart textiles. The demand for highly sensitive fiber crossbar sensors (FCSs) in wearable electronics is increased. However, the unique structure of FCSs presents challenges in replicating existing sensitivity enhancement strategies. Aiming at the sensitivity of fiber crossbar sensors, a second-order synergistic strategy is proposed that combines air capacitance and equipotential bodies, resulting in a remarkable sensitivity enhancement of over 20 times for FCSs. This strategy offers a promising avenue for the design and fabrication of FCSs that do not depend on intricate microstructures. Furthermore, the integrative structure of core-sheath fibers ensures a robust interface, leading to a low hysteresis of only 2.33% and exceptional stability. The outstanding capacitive response performance of FCSs allows them to effectively capture weak signals such as pulses and sounds. This capability opens up possibilities for the application of FCSs in personalized health management, as demonstrated by wireless monitoring systems based on pulse signals.

Highly Sensitive Soft Pressure Sensors for Wearable Applications Based on Composite Films with Curved 3D Carbon Nanotube Structures.

Soft pressure sensors based on 3D microstructures exhibit high sensitivity in the low-pressure range, which is crucial for various wearable and soft touch applications. However, it is still a challenge to manufacture soft pressure sensors with sufficient sensitivity under small mechanical stimuli for wearable applications. This work presents a novel strategy for extremely sensitive pressure sensors based on the composite film with local changes in curved 3D carbon nanotube (CNT) structure via expandable microspheres. The sensitivity is significantly enhanced by the synergetic effects of heterogeneous contact of the microdome structure and changes of percolation network within the curved 3D CNT structure. The finite-element method simulation is used to comprehend the relationships between the sensitivity and mechanical/electrical behavior of microdome structure under the applied pressure. The sensor shows an excellent sensitivity (571.64 kPa-1 ) with fast response time (85 ms), great repeatability, and long-term stability. Using the developed sensor, a wireless wearable health monitoring system to avoid carpel tunnel syndrome is built, and a multi-array pressure sensor for realizing a variety of movements in real-time is demonstrated.

Dion-Jacobson Type Lead-Free Double Perovskite with Ultra-Narrow Aromatic Interlayer Spacing for Highly Sensitive and Stable X-ray Detection.

The low-toxic and environmentally friendly 2D lead-free perovskite has made significant progress in the exploration of "green" X-ray detectors. However, the gap in detection performance between them and their lead-based analogues remains a matter of concern that cannot be ignored. To reduce this gap, shortening the interlayer spacing to accelerate the migration and collection of X-ray carriers is a promising strategy. Herein, a Dion-Jacobson (DJ) lead-free double perovskite (4-AP)2AgBiBr8 (1, 4-AP = 4-amidinopyridine) with an ultra-narrow interlayer spacing of 3.0 Å, is constructed by utilizing π-conjugated aromatic spacers. Strikingly, the subsequent enhanced carrier transport and increased crystal density lead to X-ray detectors based on bulk single crystals of 1 with a high sensitivity of 1117.3 µC Gy-1 cm-2, superior to the vast majority of similar double perovskites. In particular, the tight connection of the inorganic layers by the divalent cations enhances structural rigidity and stability, further endowing 1 detector with ultralow dark current drift (3.06 × 10-8 nA cm-1 s-1 V-1, 80 V), excellent multiple cycles switching X-ray irradiation stability, as well as long-term environmental stability (maintains over 94% photoresponse after 90 days). This work brings lead-free double perovskites one step closer to realizing efficient practical green applications.

Highly Sensitive, Degradable, and Rapid Self-Healing Hydrogel Sensor with Semi-Interpenetrating Network for Recognition of Micro-Expressions.

Flexible conductive hydrogels have revolutionized the lives and are widely applied in health monitoring and wearable electronics as a new generation of sensing materials. However, the inherent low mechanical strength, sensitivity, and lack of rapid self-healing capacity results in their short life, poor detection accuracy, and environmental pollution. Inspired by the molecular structure of bone and its chemical characteristics, a novel fully physically cross-linked conductive hydrogel is fabricated by the introduction of nanohydroxyapatite (HAp) as the dynamic junction points. In detail, the dynamically cross-linked network, including multiple physical interactions, provides it with rapid self-healing ability and excellent mechanical properties (elongation at break (>1200%), tensile strength (174kPa), and resilience (92.61%)). Besides, the ions (Cl-, Li+, Ca2+) that move freely within the system impart outstanding electrical conductivity (2.46 ± 0.15 S m-1), high sensitivity (gauge factor, GF>8), good antifreeze (-40.2 °C), and humidity properties. The assembled sensor can be employed to sensitively detect various large human motions and subtle changes in behavior (facial expressions, speech recognition). Meanwhile, the hydrogel sensor can also degrade in phosphate-buffered saline solution without causing any environmental pollution. Therefore, the designed hydrogels may become a promising candidate material in the future potential applications for smart wearable sensors and electronic skin.

Harsh Environment-Tolerant, High Performance Soft Pressure Sensors Enabled by Fiber-Segment Structure and Plasma Treatment.

As the demand for specialized and diversified pressure sensors continues to increase, excellent performance and multi-applicability have become necessary for pressure sensors. Currently, flexible pressure sensors are primarily utilized in fields such as health monitoring and human-computer interaction. However, numerous complex extreme environments in reality, including deep sea, corrosive conditions, extreme cold, and high temperatures, urgently require the services of flexible devices. Here, a piezoresistive flexible pressure sensor based on expanded polytetrafluoroethylene/functionalized carbon nanotubes (EPTFE/FCNT) is proposed. Benefiting from the unique fiber-segment architecture, chemical stability, and strong chemical binding force between EPTFE and FCNT, the fabricated sensor exhibits remarkable sensing capabilities and can be employed in multifarious extreme environments. It demonstrates a sensitivity of 862.28 kPa-1, a response time of 6-7 ms, and a detection limit below 1 Pa. Furthermore, it possesses a pressure resolution of 0.0018% under 111 kPa and can withstand over 10,000 loading and unloading cycles under 1 MPa. Additionally, the EPTFE/FCNT sensor retains its outstanding pressure response and work efficiency in extreme conditions such as an ultra-low temperature of -80 °C, high temperature (200 °C), acidic and alkaline corrosion, and underwater. These notable attributes enormously broaden the sensors' real-world application range.

Clonal Dynamics and Relapse Risk Revealed by High-Sensitivity FLT3-Internal Tandem Duplication Detection in Acute Myeloid Leukemia.

The ability to detect low-level disease is key to our understanding of clonal heterogeneity in acute myeloid leukemia (AML) and residual disease that elude conventional assays and seed relapse. We developed a high-sensitivity next-generation sequencing (HS-NGS) clinical assay, able to reliably detect low levels (1 × 10-5) of FLT3-ITD, a frequent, therapeutically targetable and prognostically relevant mutation in AML. By applying this assay to 289 longitudinal samples from 62 patients at initial diagnosis and/or clinical follow-up (mean follow-up of 22 months), we reveal the frequent occurrence of FLT3-ITD subclones at diagnosis and demonstrate a significantly decreased relapse risk when FLT3-ITD is cleared after induction or thereafter. We perform pairwise sequencing of diagnosis and relapse samples from 23 patients to uncover more detailed patterns of FLT3-ITD clonal evolution at relapse than is detectable by less-sensitive assays. Finally, we show that rising ITD level during consecutive biopsies is a harbinger of impending relapse. Our findings corroborate the emerging clinical utility of high-sensitivity FLT3-ITD testing and expands our understanding of clonal dynamics in FLT3-ITD-positive AML.

Sex-differences in Mediterranean diet: a key piece to explain sex-related cardiovascular risk in obesity? A cross-sectional study.

BACKGROUND: Mediterranean Diet (MD) has many health benefits, particularly in reducing cardiovascular risk (CVR). However, it is still little known if there are any sex differences in following this nutritional pattern and, thus, the potential sex-related repercussions on CVR in obesity. The study aimed to characterize sex-related adherence to MD and its association with CVR factors in subjects with obesity. METHODS: A total of 968 females (33.81 ± 11.06 years; BMI 34.14 ± 7.43 kg/m2) and 680 males (aged 34.77 ± 11.31years; BMI 33.77 ± 8.13 kg/m2) were included in a cross-sectional observational study. Lifestyle habits, anthropometric parameters, high sensitivity C-reactive protein (hs-CRP), and adherence to MD were evaluated. RESULTS: Females had significantly higher adherence to MD and lower hs-CRP levels than males (p < 0.001). Additionally, females consumed significantly more vegetables, fruits, legumes, fish/seafood, nuts, and sofrito sauce and less quantity of olive oil, butter, cream, margarine, red/processed meats, soda drinks (p = 0.001), red wine, and commercial sweets and confectionery than their counterparts. A PREDIMED score of ≤ 6 was associated with a significantly increased CVR in both sexes. CONCLUSIONS: Females had higher adherence to MD, lower CVR, and different food preferences than males. Although the same PREDIMED threshold has been identified as a spy of CVR, the sex-related preference of individual foods included in the MD could explain the different impact of this nutritional pattern on CVR in both sexes.

Distribution and prognostic value of high-sensitivity cardiac troponin T and I across glycemic status: a population-based study.

BACKGROUND: Whether distributions and prognostic values of high-sensitivity cardiac troponin (hs-cTn) T and I are different across normoglycemic, prediabetic, and diabetic populations is unknown. METHODS: 10127 adult participants from the National Health and Nutrition Examination Survey 1999-2004 with determined glycemic status and measurement of at least one of hs-cTn assays were included, from whom healthy participants and presumably healthy diabetic and prediabetic participants were selected to investigate pure impacts of glycemic status on distributions of hs-cTn. The nonparametric method and bootstrapping were used to derive the 99th upper reference limits of hs-cTn and 95% CI. Participants with available follow-up and hs-cTn concentrations of all 4 assays were included in prognostic analyses. Associations of hs-cTn with all-cause and cardiac-specific mortality were modeled by Cox proportional hazard regression under the complex survey design. The incremental value of hs-cTn to an established risk score in predicting cardiac-specific mortality was assessed by the 10-year area under time-dependent receiver operating characteristic curve (AUC) using the Fine-Grey competing risk model. RESULTS: Among 9714 participants included in prognostic analyses, 5946 (61.2%) were normoglycemic, 2172 (22.4%) prediabetic, and 1596 (16.4%) diabetic. Hyperglycemic populations were older than the normoglycemic population but sex and race/ethnicity were similar. During the median follow-up of 16.8 years, hs-cTnT and hs-cTnI were independently associated with all-cause and cardiac-specific mortality across glycemic status. In the diabetic population, adjusted hazard ratios per 1-standard deviation increase of log-transformed hs-cTnT and hs-cTnI (Abbott) concentrations were 1.77 (95% CI 1.48-2.12; P < .001) and 1.83 (95% CI 1.33-2.53; P < .001), respectively, regarding cardiac-specific mortality. In the diabetic but not the normoglycemic population, adding either hs-cTnT (difference in AUC: 0.062; 95% CI 0.038-0.086; P < 0.001) or hs-cTnI (Abbott) (difference in AUC: 0.071; 95% CI 0.046-0.097; P < 0.001) would significantly increase the discriminative ability of the risk score; AUC of the score combined with hs-cTnT would be further improved by incorporating hs-cTnI (0.018; 95%CI 0.006-0.029; P = 0.002). The 99th percentile of hs-cTnT of the presumably healthy diabetic population was higher than the healthy population and had no overlap in 95% CIs, however, for hs-cTnI 99th percentiles of the two populations were very close and 95% CIs extensively overlapped. CONCLUSIONS: Hs-cTnT and hs-cTnI demonstrated consistent prognostic associations across glycemic status but incremental predictive values in hyperglycemic populations only. The susceptibility of hs-cTnT 99th percentiles to diabetes plus the additive value of hs-cTnI to hs-cTnT in diabetic cardiovascular risk stratification suggested hs-cTnI and hs-cTnT may be differentially associated with glycemic status, but further research is needed to illustrate the interaction between hyperglycemia and hs-cTn.

Joint association of TyG index and high sensitivity C-reactive protein with cardiovascular disease: a national cohort study.

BACKGROUND: Both the triglyceride-glucose (TyG) index, as a surrogate marker of insulin resistance, and systemic inflammation are predictors of cardiovascular diseases; however, little is known about the coexposures and relative contributions of TyG index and inflammation to cardiovascular diseases. Using the nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we conducted longitudinal analyses to evaluate the joint and mutual associations of the TyG index and high-sensitivity C-reactive protein (hsCRP) with cardiovascular events in middle-aged and older Chinese population. METHODS: This study comprised 8 658 participants aged at least 45 years from the CHARLS 2011 who are free of cardiovascular diseases at baseline. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Cardiovascular events were defined as the presence of physician-diagnosed heart disease and/or stroke followed until 2018.We performed adjusted Cox proportional hazards regression and mediation analyses. RESULTS: The mean age of the participants was 58.6 ± 9.0 years, and 3988 (46.1%) were females. During a maximum follow-up of 7.0 years, 2606 (30.1%) people developed cardiovascular diseases, including 2012 (23.2%) cases of heart diseases and 848 (9.8%) cases of stroke. Compared with people with a lower TyG index (< 8.6 [median level]) and hsCRP < 1 mg/L, those concurrently with a higher TyG and hsCRP had the highest risk of overall cardiovascular disease (adjusted hazard ratio [aHR], 1.300; 95% CI 1.155-1.462), coronary heart disease (aHR, 1.294; 95% CI 1.130-1.481) and stroke (aHR, 1.333; 95% CI 1.093-1.628), which were predominant among those aged 70 years or below. High hsCRP significantly mediated 13.4% of the association between the TyG index and cardiovascular disease, while TyG simultaneously mediated 7.9% of the association between hsCRP and cardiovascular risk. CONCLUSIONS: The findings highlight the coexposure effects and mutual mediation between the TyG index and hsCRP on cardiovascular diseases. Joint assessments of the TyG index and hsCRP should be underlined for the residual risk stratification and primary prevention of cardiovascular diseases, especially for middle-aged adults.

Repeated dynamic [18F]FDG PET/CT imaging using a high-sensitivity PET/CT scanner for assessing non-small cell lung cancer patients undergoing induction immuno-chemotherapy followed by hypo-fractionated chemoradiotherapy and consolidative immunotherapy: report from a prospective observational study (GASTO-1067).

OBJECTIVE: The study aims to investigate the role of dynamic [18F]FDG PET/CT imaging by high-sensitivity PET/CT scanner for assessing patients with locally advanced non-small cell lung cancer (LA-NSCLC) who undergo induction immuno-chemotherapy, followed by concurrent hypo-fractionated chemoradiotherapy (hypo-CCRT) and consolidative immunotherapy. METHODS: Patients with unresectable LA-NSCLC are prospectively recruited. Dynamic [18F]FDG PET/CT scans are conducted at four timepoints: before treatment (Baseline), after induction immuno-chemotherapy (Post-IC), during hypo-CCRT (Mid-hypo-CCRT) and after hypo-CCRT (Post-hypo-CCRT). The primary lung tumors (PTs) are manually delineated, and the metabolic features, including the Patlak-Ki (Ki), maximum SUV (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) have been evaluated. The expressions of CD3, CD8, CD68, CD163, CD34 and Ki67 in primary lung tumors at baseline are assayed by immunohistochemistry. The levels of blood lymphocytes at four timepoints are analyzed with flow cytometry. RESULTS: Fifteen LA-NSCLC patients are enrolled between December 2020 and December 2022. Baseline Ki of primary tumor yields the highest AUC values of 0.722 and 0.796 for predicting disease progression and patient death, respectively. Patients are classified into the High FDG Ki group (n = 8, Ki > 2.779 ml/min/100 g) and the Low FDG Ki group (n = 7, Ki ≤ 2.779 ml/min/100 g). The High FDG Ki group presents better progression-free survival (P = 0.01) and overall survival (P = 0.025). The High FDG Ki group exhibits more significant reductions in Ki after hypo-CCRT compared to the Low FDG Ki group. Patients with a reduction in Ki > 73.1% exhibit better progression-free survival than those with a reduction ≤ 73.1% in Ki (median: not reached vs. 7.33 months, P = 0.12). The levels of CD3+ T cells (P = 0.003), CD8+ T cells (P = 0.002), CD68+ macrophages (P = 0.071) and CD163+ macrophages (P = 0.012) in primary tumor tissues are higher in the High FDG Ki group. The High FDG Ki group has higher CD3+CD8+ lymphocytes in blood at baseline (P = 0.108), post-IC (P = 0.023) and post-hypo-CCRT (P = 0.041) than the Low FDG Ki group. CONCLUSIONS: The metabolic features in the High FDG Ki group significantly decrease during the treatment, particularly after induction immuno-chemotherapy. The Ki value of primary tumor shows significant relationship with the treatment response and survival in LA-NSCLC patients by the combined immuno-chemoradiotherapy regimen. TRIAL REGISTRATION: ClinicalTrials.gov. NCT04654234. Registered 4 December 2020.

Development and performance of SIAT bPET: a high-resolution and high-sensitivity MR-compatible brain PET scanner using dual-ended readout detectors.

PURPOSE: Positron emission tomography/magnetic resonance imaging (PET/MRI) is a powerful tool for brain imaging, but the spatial resolution of the PET scanners currently used for brain imaging can be further improved to enhance the quantitative accuracy of brain PET imaging. The purpose of this study is to develop an MR-compatible brain PET scanner that can simultaneously achieve a uniform high spatial resolution and high sensitivity by using dual-ended readout depth encoding detectors. METHODS: The MR-compatible brain PET scanner, named SIAT bPET, consists of 224 dual-ended readout detectors. Each detector contains a 26 × 26 lutetium yttrium oxyorthosilicate (LYSO) crystal array of 1.4 × 1.4 × 20 mm3 crystal size read out by two 10 × 10 silicon photomultiplier (SiPM) arrays from both ends. The scanner has a detector ring diameter of 376.8 mm and an axial field of view (FOV) of 329 mm. The performance of the scanner including spatial resolution, sensitivity, count rate, scatter fraction, and image quality was measured. Imaging studies of phantoms and the brain of a volunteer were performed. The mutual interferences of the PET insert and the uMR790 3 T MRI scanner were measured, and simultaneous PET/MRI imaging of the brain of a volunteer was performed. RESULTS: A spatial resolution of better than 1.5 mm with an average of 1.2 mm within the whole FOV was obtained. A sensitivity of 11.0% was achieved at the center FOV for an energy window of 350-750 keV. Except for the dedicated RF coil, which caused a ~ 30% reduction of the sensitivity of the PET scanner, the MRI sequences running had a negligible effect on the performance of the PET scanner. The reduction of the SNR and homogeneity of the MRI images was less than 2% as the PET scanner was inserted to the MRI scanner and powered-on. High quality PET and MRI images of a human brain were obtained from simultaneous PET/MRI scans. CONCLUSION: The SIAT bPET scanner achieved a spatial resolution and sensitivity better than all MR-compatible brain PET scanners developed up to date. It can be used either as a standalone brain PET scanner or a PET insert placed inside a commercial whole-body MRI scanner to perform simultaneous PET/MRI imaging.

Socioeconomic adversity, maternal nutrition, and the prenatal programming of offspring cognition and language at two years of age through maternal inflammation.

Increasing rates of child neurodevelopmental vulnerability are a significant public health challenge. The adverse effect of socioeconomic adversity on offspring cognition may be mediated through elevated prenatal maternal systemic inflammation, but the role of modifiable antecedents such as maternal nutrition has not yet been clarified. This study aimed to examine (1) whether prenatal factors, with an emphasis on maternal nutrition, were associated with prenatal maternal systemic inflammation at 28 weeks' gestation, including the metabolomic marker glycoprotein acetyls (GlycA); (2) the extent to which the association between prenatal maternal nutrition and child cognition and language at age two years was mediated by elevated maternal inflammation in pregnancy; (3) the extent to which the associations between prenatal socioeconomic adversity and child neurodevelopment were mediated through prenatal maternal nutrition and GlycA levels. We used a prospective population-derived pre-birth longitudinal cohort study, the Barwon Infant Study (Barwon region of Victoria, Australia), where 1074 mother-child pairs were recruited by 28 weeks' gestation using an unselected sampling frame. Exposures included prenatal factors such as maternal diet measured by a validated food frequency questionnaire at 28 weeks' gestation and dietary patterns determined by principal component analysis. The main outcome measures were maternal inflammatory biomarkers (GlycA and hsCRP levels) at 28 weeks' gestation, and offspring Bayley-III cognition and language scores at age two years. Results showed that the 'modern wholefoods' and 'processed' maternal dietary patterns were independently associated with reduced and elevated maternal inflammation respectively (GlycA or hsCRP p < 0.001), and also with higher and reduced offspring Bayley-III scores respectively (cognition p ≤ 0.004, language p ≤ 0.009). Associations between dietary patterns and offspring cognition and language were partially mediated by higher maternal GlycA (indirect effect: cognition p ≤ 0.036, language p ≤ 0.05), but were less evident for hsCRP. The maternal dietary patterns mediated 22 % of the association between socioeconomic adversity (lower maternal education and/or lower household income vs otherwise) and poorer offspring cognition (indirect effect p = 0.001). Variation in prenatal GlycA levels that were independent of these dietary measures appeared less important. In conclusion, modifiable prenatal maternal dietary patterns were associated with adverse child neurocognitive outcomes through their effect on maternal inflammation (GlycA). Maternal diet may partially explain the association between socioeconomic adversity and child neurocognitive vulnerability. Maternal diet-by-inflammation pathways are an attractive target for future intervention studies.

Association of high-sensitivity C-reactive protein and hematologic-inflammatory indices with risk of cardiovascular diseases: a population-based study with partial least squares structural equation modeling approach.

Partial least squares structural equation modeling is a simple approach that may be used to determine the factors associated with diseases. In the current study, we aimed to explore the most associated high-sensitivity C-reactive protein (hs-CRP) as well as hematologic-inflammatory indices for the risk of cardiovascular disease (CVD). A total of 7362 healthy (non-CVD) participants aged 35-65 years old from baseline investigation were evaluated in the Phase 2 follow-up. Of these, 1022 individuals were found to have CVDs in the second phase (10-year follow-up) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. We used partial least squares structural equation modeling to develop a prediction model for association of CVD risk factors and hs-CRP as well as hematologic-inflammatory indices in the study population. According to the study, age had the most significant impact on the presence of CVD. Increasing in age by one unit raises the risk of CVD by 0.166. Also, serum hs-CRP was found to have the second-highest impact on CVD; increasing in age by one unit raises the risk of CVD by 0.042. The study also discovered a strong and significant correlation between red cell distribution width (RDW) and CVD. Moreover, the study found that several factors such as hemoglobin (HGB), neutrophil (NEUT), neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-to-lymphocyte ratio (PLR) have indirect effects on CVD that are mediated by hs-CRP while controlling for age, sex and social-economic factors. Generally, the results showed that age, hs-CRP, and RDW were the most important risk factors on CVD.

Prediction of metabolic syndrome following a first pregnancy.

BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome. OBJECTIVE: This study aimed to develop machine learning models to predict the development of metabolic syndrome using factors ascertained in nulliparous pregnant individuals. STUDY DESIGN: This was a secondary analysis of a prospective cohort study (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be Heart Health Study [nuMoM2b-HHS]). Data were collected from October 2010 to October 2020, and analyzed from July 2023 to October 2023. Participants had in-person visits 2 to 7 years after their first delivery. The primary outcome was metabolic syndrome, defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, which was measured within 2 to 7 years after delivery. A total of 127 variables that were obtained during pregnancy were evaluated. The data set was randomly split into a training set (70%) and a test set (30%). We developed a random forest model and a lasso regression model using variables obtained during pregnancy. We compared the area under the receiver operating characteristic curve for both models. Using the model with the better area under the receiver operating characteristic curve, we developed models that included fewer variables based on SHAP (SHapley Additive exPlanations) values and compared them with the original model. The final model chosen would have fewer variables and noninferior areas under the receiver operating characteristic curve. RESULTS: A total of 4225 individuals met the inclusion criteria; the mean (standard deviation) age was 27.0 (5.6) years. Of these, 754 (17.8%) developed metabolic syndrome. The area under the receiver operating characteristic curve of the random forest model was 0.878 (95% confidence interval, 0.846-0.909), which was higher than the 0.850 of the lasso model (95% confidence interval, 0.811-0.888; P<.001). Therefore, random forest models using fewer variables were developed. The random forest model with the top 3 variables (high-density lipoprotein, insulin, and high-sensitivity C-reactive protein) was chosen as the final model because it had the area under the receiver operating characteristic curve of 0.867 (95% confidence interval, 0.839-0.895), which was not inferior to the original model (P=.08). The area under the receiver operating characteristic curve of the final model in the test set was 0.847 (95% confidence interval, 0.821-0.873). An online application of the final model was developed (https://kawakita.shinyapps.io/metabolic/). CONCLUSION: We developed a model that can accurately predict the development of metabolic syndrome in 2 to 7 years after delivery.