Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition.

PURPOSE: To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method. METHODS: Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient. RESULTS: The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well. CONCLUSION: The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.

Genetically engineered bacteriophages as novel nanomaterials: applications beyond antimicrobial agents.

Bacteriophages, also known as phages, are viruses that replicate in bacteria and archaea. Phages were initially discovered as antimicrobial agents, and they have been used as therapeutic agents for bacterial infection in a process known as "phage therapy." Recently, phages have been investigated as functional nanomaterials in a variety of areas, as they can function not only as therapeutic agents but also as biosensors and tissue regenerative materials. Phages are nontoxic to humans, and they possess self-assembled nanostructures and functional properties. Additionally, phages can be easily genetically modified to display specific peptides or to screen for functional peptides via phage display. Here, we demonstrated the application of phage nanomaterials in the context of tissue engineering, sensing, and probing.

Compartmental anisotropy of filtered exchange imaging (FEXI) in human white matter: What is happening in FEXI?

PURPOSE: To investigate the effects of compartmental anisotropy on filtered exchange imaging (FEXI) in white matter (WM). THEORY AND METHODS: FEXI signals were measured using multiple combinations of diffusion filter and detection directions in five healthy volunteers. Additional filters, including a trace-weighted diffusion filter with trapezoidal gradients, a spherical b-tensor encoded diffusion filter, and a T2 filter, were tested with trace-weighted diffusion detection. RESULTS: A large range of apparent exchange rates (AXR) and both positive and negative filter efficiencies (σ) were found depending on the mutual orientation of the filter and detection gradients relative to WM fiber orientation. The data demonstrated that the fast-diffusion compartment suppressed by diffusional filtering is not exclusively extra-cellular, but also intra-cellular. While not comprehensive, a simple two-compartment diffusion tensor model with water exchange was able to account qualitatively for the trends in positive and negative filtering efficiencies, while standard model imaging (SMI) without exchange could not. This two-compartment diffusion tensor model also demonstrated smaller AXR variances across subjects. When employing trace-weighted diffusion detection, AXR values were on the order of the R1 (=1/T1) of water at 3T for crossing fibers, while being less than R1 for parallel fibers. CONCLUSION: Orientation-dependent AXR and σ values were observed when using multi-orientation filter and detection gradients in FEXI, indicating that WM FEXI models need to account for compartmental anisotropy. When using trace-weighted detection, AXR values were on the order of or less than R1, complicating the interpretation of FEXI results in WM in terms of biological exchange properties. These findings may contribute toward better understanding of FEXI results in WM.

A Study on the Application of Recombinant Factor C (rFC) Assay Using Biopharmaceuticals.

Gram-negative bacterial endotoxins can cause pathophysiological effects such as high fever when introduced into the bloodstream. Therefore, endotoxin testing is necessary when producing injectable pharmaceuticals. The pharmaceutical industry has widely used Limulus amebocyte lysate (LAL) to certify product quality. However, ethical concerns have been raised and the increasing scarcity of Limulus polyphemus necessitates the development of novel testing techniques. Recombinant factor C (rFC) was developed using genetic engineering techniques. The aim of this study was to investigate the validity of rFC testing and compare it with the LAL method. The specificity, linearity, accuracy, precision, and robustness of the rFC assay were evaluated. After validation, the rFC assay was found to be suitable for endotoxin detection. We compared the accuracy of the rFC and LAL assays using reference standard endotoxin. The rFC assay was as accurate as the LAL assay. We also compared the two assays using biopharmaceuticals. Greater interference occurred in some samples when the rFC assay was used than when the LAL assay was used. However, the rFC assay overcame the interference when the samples were diluted. Overall, we suggest that rFC can be applied to test biopharmaceuticals.

Skeletal muscle regeneration with 3D bioprinted hyaluronate/gelatin hydrogels incorporating MXene nanoparticles.

There has been significant progress in the field of three-dimensional (3D) bioprinting technology, leading to active research on creating bioinks capable of producing structurally and functionally tissue-mimetic constructs. Ti3C2Tx MXene nanoparticles (NPs), promising two-dimensional nanomaterials, are being investigated for their potential in muscle regeneration due to their unique physicochemical properties. In this study, we integrated MXene NPs into composite hydrogels made of gelatin methacryloyl (GelMA) and hyaluronic acid methacryloyl (HAMA) to develop bioinks (namely, GHM bioink) that promote myogenesis. The prepared GHM bioinks were found to offer excellent printability with structural integrity, cytocompatibility, and microporosity. Additionally, MXene NPs within the 3D bioprinted constructs encouraged the differentiation of C2C12 cells into skeletal muscle cells without additional support of myogenic agents. Genetic analysis indicated that representative myogenic markers both for early and late myogenesis were significantly up-regulated. Moreover, animal studies demonstrated that GHM bioinks contributed to enhanced regeneration of skeletal muscle while reducing immune responses in mice models with volumetric muscle loss (VML). Our results suggest that the GHM hydrogel can be exploited to craft a range of strategies for the development of a novel bioink to facilitate skeletal muscle regeneration because these MXene-incorporated composite materials have the potential to promote myogenesis.

The effectiveness of Kami Guibi-tang for cognitive impairment patients: A retrospective chart review.

Background: and Purpose: The number of patients with cognitive impairment is increasing worldwide. Therapeutic drugs that slow disease progression are being developed; however, further research is required. This study investigated the effects of Kami Guibi-tang on patients with various types of cognitive decline. Methods: This study was a single-center, retrospective chart review of patients who visited KyungHee University Hospital at Gangdong from January 2015 to March 2022. The study included participants who took Kami Guibi-tang for more than 90 days and were assessed on the Korean version Mini-Mental State Examination (MMSE-K) scores before and after treatment. Participants who received other liquid herbal medicines during the treatment were excluded. The outcome of interest was changed scores in MMSE-K and Short form of Geriatric Depression Scale (S-GDS). Results: A total of 31 participants were included. The total MMSE-K score significantly increased with time and showed a significant increase at 3 and 9 months compared with baseline. Among the MMSE-K subscores, the orientation subscore showed a significant increase at three months compared with baseline, and the attention and calculation subscore showed a significant increase with time. In addition, four participants with vascular dementia showed a significant increase in the total MMSE-K score over time and a significant increase after 9 months compared with baseline. The S-GDS score in 31 participants showed a significant decrease with time and at all time points compared with baseline. Conclusions: Kami Guibi-tang may improve cognitive function in patients with cognitive decline.

Deciphering head and neck cancer microenvironment: Single-cell and spatial transcriptomics reveals human papillomavirus-associated differences.

Human papillomavirus (HPV) is a major causative factor of head and neck squamous cell carcinoma (HNSCC), and the incidence of HPV- associated HNSCC is increasing. The role of tumor microenvironment in viral infection and metastasis needs to be explored further. We studied the molecular characteristics of primary tumors (PTs) and lymph node metastatic tumors (LNMTs) by stratifying them based on their HPV status. Eight samples for single-cell RNA profiling and six samples for spatial transcriptomics (ST), composed of matched primary tumors (PT) and lymph node metastases (LNMT), were collected from both HPV- negative (HPV- ) and HPV-positive (HPV+ ) patients. Using the 10x Genomics Visium platform, integrative analyses with single-cell RNA sequencing were performed. Intracellular and intercellular alterations were analyzed, and the findings were confirmed using experimental validation and publicly available data set. The HPV+ tissues were composed of a substantial amount of lymphoid cells regardless of the presence or absence of metastasis, whereas the HPV- tissue exhibited remarkable changes in the number of macrophages and plasma cells, particularly in the LNMT. From both single-cell RNA and ST data set, we discovered a central gene, pyruvate kinase muscle isoform 1/2 (PKM2), which is closely associated with the stemness of cancer stem cell-like populations in LNMT of HPV- tissue. The consistent expression was observed in HPV- HNSCC cell line and the knockdown of PKM2 weakened spheroid formation ability. Furthermore, we found an ectopic lymphoid structure morphology and clinical effects of the structure in ST slide of the HPV+ patients and verified their presence in tumor tissue using immunohistochemistry. Finally, the ephrin-A (EPHA2) pathway was detected as important signals in angiogenesis for HPV- patients from single-cell RNA and ST profiles, and knockdown of EPHA2 declined the cell migration. Our study described the distinct cellular composition and molecular alterations in primary and metastatic sites in HNSCC patients based on their HPV status. These results provide insights into HNSCC biology in the context of HPV infection and its potential clinical implications.

Highly Aligned Ternary Nanofiber Matrices Loaded with MXene Expedite Regeneration of Volumetric Muscle Loss.

Current therapeutic approaches for volumetric muscle loss (VML) face challenges due to limited graft availability and insufficient bioactivities. To overcome these limitations, tissue-engineered scaffolds have emerged as a promising alternative. In this study, we developed aligned ternary nanofibrous matrices comprised of poly(lactide-co-ε-caprolactone) integrated with collagen and Ti3C2Tx MXene nanoparticles (NPs) (PCM matrices), and explored their myogenic potential for skeletal muscle tissue regeneration. The PCM matrices demonstrated favorable physicochemical properties, including structural uniformity, alignment, microporosity, and hydrophilicity. In vitro assays revealed that the PCM matrices promoted cellular behaviors and myogenic differentiation of C2C12 myoblasts. Moreover, in vivo experiments demonstrated enhanced muscle remodeling and recovery in mice treated with PCM matrices following VML injury. Mechanistic insights from next-generation sequencing revealed that MXene NPs facilitated protein and ion availability within PCM matrices, leading to elevated intracellular Ca2+ levels in myoblasts through the activation of inducible nitric oxide synthase (iNOS) and serum/glucocorticoid regulated kinase 1 (SGK1), ultimately promoting myogenic differentiation via the mTOR-AKT pathway. Additionally, upregulated iNOS and increased NO- contributed to myoblast proliferation and fiber fusion, thereby facilitating overall myoblast maturation. These findings underscore the potential of MXene NPs loaded within highly aligned matrices as therapeutic agents to promote skeletal muscle tissue recovery.

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies.

PURPOSE: To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR. METHODS: A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics. RESULTS: The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 µT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema. CONCLUSION: The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.

Predictors of mTICI 2c/3 over 2b in patients successfully recanalized with mechanical thrombectomy.

OBJECTIVE: For patients presenting with acute ischemic stroke (AIS) caused by large vessel occlusions (LVO), mechanical thrombectomy (MT) is the treatment standard of care in eligible patients. Modified Thrombolysis in Cerebral Infarction (mTICI) grades of 2b, 2c, and 3 are all considered successful reperfusion; however, recent studies have shown achieving mTICI 2c/3 leads to better outcomes than mTICI 2b. This study aims to investigate whether any baseline preprocedural or periprocedural parameters are predictive of achieving mTICI 2c/3 in successfully recanalized LVO patients. METHODS: We conducted a retrospective multicenter cohort study of consecutive patients presenting with AIS caused by a LVO from 1 January 2017 to 1 January 2023. Baseline and procedural data were collected through chart review. Univariate and multivariate analysis were applied to determine significant predictors of mTICI 2c/3. RESULTS: A total of 216 patients were included in the study, with 159 (73.6%) achieving mTICI 2c/3 recanalization and 57 (26.4%) achieving mTICI 2b recanalization. We found that a higher groin puncture to first pass time (OR = 0.976, 95%CI: 0.960-0.992, p = 0.004), a higher first pass to recanalization time (OR = 0.985, 95%CI: 0.972-0.998, p = 0.029), a higher admission NIHSS (OR = 0.949, 95%CI: 0.904-0.995, p = 0.031), and a lower age (OR = 1.032, 95%CI: 1.01-1.055, p = 0.005) were associated with a decreased probability of achieving mTICI 2c/3. INTERPRETATION: A lower groin puncture to first pass time, a lower first pass to recanalization time, a lower admission NIHSS, and a higher age were independent predictors of mTICI 2c/3 recanalization.

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI.

PURPOSE: Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone to errors because of the unavoidable noise in vivo. A deep learning-based single Lorentzian Fitting Network (sLoFNet) is proposed to overcome these shortcomings. METHODS: A neural network architecture was constructed and its hyperparameters optimized. Training was conducted on a simulated and in vivo-paired data sets of discrete signal values and their corresponding Lorentzian shape parameters. The sLoFNet performance was compared with LS on several WASSR data sets (both simulated and in vivo 3T brain scans). Prediction errors, robustness against noise, effects of sampling density, and time consumption were compared. RESULTS: LS and sLoFNet performed comparably in terms of RMS error and mean absolute error on all in vivo data with no statistically significant difference. Although the LS method fitted well on samples with low noise, its error increased rapidly when increasing sample noise up to 4.5%, whereas the error of sLoFNet increased only marginally. With the reduction of Z-spectral sampling density, prediction errors increased for both methods, but the increase occurred earlier (at 25 vs. 15 frequency points) and was more pronounced for LS. Furthermore, sLoFNet performed, on average, 70 times faster than the LS-method. CONCLUSION: Comparisons between LS and sLoFNet on simulated and in vivo WASSR MRI Z-spectra in terms of robustness against noise and decreased sample resolution, as well as time consumption, showed significant advantages for sLoFNet.

Bloch simulator-driven deep recurrent neural network for magnetization transfer contrast MR fingerprinting and CEST imaging.

PURPOSE: To develop a unified deep-learning framework by combining an ultrafast Bloch simulator and a semisolid macromolecular magnetization transfer contrast (MTC) MR fingerprinting (MRF) reconstruction for estimation of MTC effects. METHODS: The Bloch simulator and MRF reconstruction architectures were designed with recurrent neural networks and convolutional neural networks, evaluated with numerical phantoms with known ground truths and cross-linked bovine serum albumin phantoms, and demonstrated in the brain of healthy volunteers at 3 T. In addition, the inherent magnetization-transfer ratio asymmetry effect was evaluated in MTC-MRF, CEST, and relayed nuclear Overhauser enhancement imaging. A test-retest study was performed to evaluate the repeatability of MTC parameters, CEST, and relayed nuclear Overhauser enhancement signals estimated by the unified deep-learning framework. RESULTS: Compared with a conventional Bloch simulation, the deep Bloch simulator for generation of the MTC-MRF dictionary or a training data set reduced the computation time by 181-fold, without compromising MRF profile accuracy. The recurrent neural network-based MRF reconstruction outperformed existing methods in terms of reconstruction accuracy and noise robustness. Using the proposed MTC-MRF framework for tissue-parameter quantification, the test-retest study showed a high degree of repeatability in which the coefficients of variance were less than 7% for all tissue parameters. CONCLUSION: Bloch simulator-driven, deep-learning MTC-MRF can provide robust and repeatable multiple-tissue parameter quantification in a clinically feasible scan time on a 3T scanner.

CEST2022: Amide proton transfer-weighted MRI improves the diagnostic performance of multiparametric non-contrast-enhanced MRI techniques in patients with post-treatment high-grade gliomas.

New or enlarged lesions in malignant gliomas after surgery and chemoradiation can be associated with tumor recurrence or treatment effect. Due to similar radiographic characteristics, conventional-and even some advanced MRI techniques-are limited in distinguishing these two pathologies. Amide proton transfer-weighted (APTw) MRI, a protein-based molecular imaging technique that does not require the administration of any exogenous contrast agent, was recently introduced into the clinical setting. In this study, we evaluated and compared the diagnostic performances of APTw MRI with several non-contrast-enhanced MRI sequences, such as diffusion-weighted imaging, susceptibility-weighted imaging, and pseudo-continuous arterial spin labeling. Thirty-nine scans from 28 glioma patients were obtained on a 3 T MRI scanner. A histogram analysis approach was employed to extract parameters from each tumor area. Statistically significant parameters (P < 0.05) were selected to train multivariate logistic regression models to evaluate the performance of MRI sequences. Multiple histogram parameters, particularly from APTw and pseudo-continuous arterial spin labeling images, demonstrated significant differences between treatment effect and recurrent tumor. The regression model trained on the combination of all significant histogram parameters achieved the best result (area under the curve = 0.89). We found that APTw images added value to other advanced MR images for the differentiation of treatment effect and tumor recurrence.

Exogenous 8-Hydroxydeoxyguanosine Attenuates PM2.5-Induced Inflammation in Human Bronchial Epithelial Cells by Decreasing NLRP3 Inflammasome Activation.

Particulate matter 2.5 (PM2.5) induces lung injury by increasing the generation of reactive oxygen species (ROS) and inflammation. ROS aggravates NLRP3 inflammasome activation, which activates caspase-1, IL-1ß, and IL-18 and induces pyroptosis; these factors propagate inflammation. In contrast, treatment with exogenous 8-hydroxydeoxyguanosine (8-OHdG) decreases RAC1 activity and eventually decreases dinucleotide phosphate oxidase (NOX) and ROS generation. To establish modalities that would mitigate PM2.5-induced lung injury, we evaluated whether 8-OHdG decreased PM2.5-induced ROS generation and NLRP3 inflammasome activation in BEAS-2B cells. CCK-8 and lactate dehydrogenase assays were used to determine the treatment concentration. Fluorescence intensity, Western blotting, enzyme-linked immunosorbent assay, and immunoblotting assays were also performed. Treatment with 80 µg/mL PM2.5 increased ROS generation, RAC1 activity, NOX1 expression, NLRP3 inflammasome (NLRP3, ASC, and caspase-1) activity, and IL-1ß and IL-18 levels in cells; treatment with 10 µg/mL 8-OHdG significantly attenuated these effects. Furthermore, similar results, such as reduced expression of NOX1, NLRP3, ASC, and caspase-1, were observed in PM2.5-treated BEAS-2B cells when treated with an RAC1 inhibitor. These results show that 8-OHdG mitigates ROS generation and NLRP3 inflammation by inhibiting RAC1 activity and NOX1 expression in respiratory cells exposed to PM2.5.

Pretreatment brain CT perfusion thresholds for predicting final infarct volume in distal medium vessel occlusions.

BACKGROUND AND PURPOSE: Quantitative CT perfusion (CTP) thresholds for assessing the extent of ischemia in patients with acute ischemic stroke (AIS) have been established; relative cerebral blood flow (rCBF) <30% is typically used for estimating estimated ischemic core volume and Tmax (time to maximum) >6 seconds for critical hypoperfused volume in AIS patients with large vessel occlusion (LVO). In this study, we aimed to identify the optimal threshold values for patients presenting with AIS secondary to distal medium vessel occlusions (DMVOs). METHODS: In this retrospective study, consecutive AIS patients with anterior circulation DMVO who underwent pretreatment CTP and follow-up MRI/CT were included. The CTP data were processed by RAPID (iSchemaView, Menlo Park, CA) to generate estimated ischemic core volumes using rCBF <20%, <30%, <34%, and <38% and critical hypoperfused volumes using Tmax (seconds) >4, >6, >8, and >10. Final infarct volumes (FIVs) were obtained from follow-up MRI/CT within 5 days of symptom onset. Diagnostic performance between CTP thresholds and FIV was assessed in the successfully and unsuccessfully recanalized groups. RESULTS: Fifty-five patients met our inclusion criteria (32 female [58.2%], 68.0 ± 12.1 years old [mean ± SD]). Recanalization was attempted with intravenous tissue-type plasminogen activator and mechanical thrombectomy in 27.7% and 38.1% of patients, respectively. Twenty-five patients (45.4%) were successfully recanalized. In the successfully recanalized patients, no CTP threshold significantly outperformed what is used in LVO setting (rCBF < 30%). All rCBF CTP thresholds demonstrated fair diagnostic performances for predicting FIV. In unsuccessfully recanalized patients, all Tmax CTP thresholds strongly predicted FIV with relative superiority of Tmax >10 seconds (area under the receiver operating characteristic curve = .875, p = .001). CONCLUSION: In AIS patients with DMVOs, longer Tmax delays than Tmax  > 6 seconds, most notably, Tmax  > 10 seconds, best predict FIV in unsuccessfully recanalized patients. No CTP threshold reliably predicts FIV in the successfully recanalized group nor significantly outperformed rCBF < 30%.

Only-train-once MR fingerprinting for B0 and B1 inhomogeneity correction in quantitative magnetization-transfer contrast.

PURPOSE: To develop a fast, deep-learning approach for quantitative magnetization-transfer contrast (MTC)-MR fingerprinting (MRF) that simultaneously estimates multiple tissue parameters and corrects the effects of B0 and B1 variations. METHODS: An only-train-once recurrent neural network was designed to perform the fast tissue-parameter quantification for a large range of different MRF acquisition schedules. It enabled a dynamic scan-wise linear calibration of the scan parameters using the measured B0 and B1 maps, which allowed accurate, multiple-tissue parameter mapping. MRF images were acquired from 8 healthy volunteers at 3 T. Estimated parameter maps from the MRF images were used to synthesize the MTC reference signal (Zref ) through Bloch equations at multiple saturation power levels. RESULTS: The B0 and B1 errors in MR fingerprints, if not corrected, would impair the tissue quantification and subsequently corrupt the synthesized MTC reference images. Bloch equation-based numerical phantom studies and synthetic MRI analysis demonstrated that the proposed approach could correctly estimate water and semisolid macromolecule parameters, even with severe B0 and B1 inhomogeneities. CONCLUSION: The only-train-once deep-learning framework can improve the reconstruction accuracy of brain-tissue parameter maps and be further combined with any conventional MRF or CEST-MRF method.

Chat Generative Pre-trained Transformer: why we should embrace this technology.

With the advent of artificial intelligence that not only can learn from us but also can communicate with us in plain language, humans are embarking on a brave new future. The interaction between humans and artificial intelligence has never been so widespread. Chat Generative Pre-trained Transformer is an artificial intelligence resource that has potential uses in the practice of medicine. As clinicians, we have the opportunity to help guide and develop new ways to use this powerful tool. Optimal use of any tool requires a certain level of comfort. This is best achieved by appreciating its power and limitations. Being part of the process is crucial in maximizing its use in our field. This clinical opinion demonstrates the potential uses of Chat Generative Pre-trained Transformer for obstetrician-gynecologists and encourages readers to serve as the driving force behind this resource.

Lateralization of temporal lobe epileptic foci with automated chemical exchange saturation transfer measurements at 3 Tesla.

BACKGROUND: Magnetic Resonance Imaging (MRI) is an indispensable tool for the diagnosis of temporal lobe epilepsy (TLE). However, about 30% of TLE patients show no lesion on structural MRI (sMRI-negative), posing a significant challenge for presurgical evaluation. This study aimed to investigate whether chemical exchange saturation transfer (CEST) MRI at 3 Tesla can lateralize the epileptic focus of TLE and study the metabolic contributors to the CEST signal measured. METHODS: Forty TLE subjects (16 males and 24 females) were included in this study. An automated data analysis pipeline was established, including segmentation of the hippocampus and amygdala (HA), calculation of four CEST metrics and quantitative relaxation times (T1 and T2), and construction of prediction models by logistic regression. Furthermore, a modified two-stage Bloch-McConnell fitting method was developed to investigate the molecular imaging mechanism of 3 T CEST in identifying epileptic foci of TLE. FINDINGS: The mean CEST ratio (CESTR) metric within 2.25-3.25 ppm in the HA was the most powerful index in predicting seizure laterality, with an area under the receiver-operating characteristic curve (AUC) of 0.84. And, the combination of T2 and CESTR further increased the AUC to 0.92. Amine and guanidinium moieties were the two leading contributors to the CEST contrast between the epileptogenic HA and the normal HA. INTERPRETATION: CEST at 3 Tesla is a powerful modality that can predict seizure laterality with high accuracy. This study can potentially facilitate the clinical translation of CEST MRI in identifying the epileptic foci of TLE or other localization-related epilepsies. FUNDING: National Natural Science Foundation of China, Science Technology Department of Zhejiang Province, and Zhejiang University.

Remote patient monitoring for management of diabetes mellitus in pregnancy is associated with improved maternal and neonatal outcomes.

BACKGROUND: Diabetes mellitus is a common medical complication of pregnancy, and its treatment is complex. Recent years have seen an increase in the application of mobile health tools and advanced technologies, such as remote patient monitoring, with the aim of improving care for diabetes mellitus in pregnancy. Previous studies of these technologies for the treatment of diabetes in pregnancy have been small and have not clearly shown clinical benefit with implementation. OBJECTIVE: Remote patient monitoring allows clinicians to monitor patients' health data (such as glucose values) in near real-time, between office visits, to make timely adjustments to care. Our objective was to determine if using remote patient monitoring for the management of diabetes in pregnancy leads to an improvement in maternal and neonatal outcomes. STUDY DESIGN: This was a retrospective cohort study of pregnant patients with diabetes mellitus managed by the maternal-fetal medicine practice at one academic institution between October 2019 and April 2021. This practice transitioned from paper-based blood glucose logs to remote patient monitoring in February 2020. Remote patient monitoring options included (1) device integration with Bluetooth glucometers that automatically uploaded measured glucose values to the patient's Epic MyChart application or (2) manual entry in which patients manually logged their glucose readings into their MyChart application. Values in the MyChart application directly transferred to the patient's electronic health record for review and management by clinicians. In total, 533 patients were studied. We compared 173 patients managed with paper logs to 360 patients managed with remote patient monitoring (176 device integration and 184 manual entry). Our primary outcomes were composite maternal morbidity (which included third- and fourth-degree lacerations, chorioamnionitis, postpartum hemorrhage requiring transfusion, postpartum hysterectomy, wound infection or separation, venous thromboembolism, and maternal admission to the intensive care unit) and composite neonatal morbidity (which included umbilical cord pH <7.00, 5 minute Apgar score <7, respiratory morbidity, hyperbilirubinemia, meconium aspiration, intraventricular hemorrhage, necrotizing enterocolitis, sepsis, pneumonia, seizures, hypoxic ischemic encephalopathy, shoulder dystocia, trauma, brain or body cooling, and neonatal intensive care unit admission). Secondary outcomes were measures of glycemic control and the individual components of the primary composite outcomes. We also performed a secondary analysis in which the patients who used the two different remote patient monitoring options (device integration vs manual entry) were compared. Chi-square, Fisher's exact, 2-sample t, and Mann-Whitney tests were used to compare the groups. A result was considered statistically significant at P<.05. RESULTS: Maternal baseline characteristics were not significantly different between the remote patient monitoring and paper groups aside from a slightly higher baseline rate of chronic hypertension in the remote patient monitoring group (6.1% vs 1.2%; P=.011). The primary outcomes of composite maternal and composite neonatal morbidity were not significantly different between the groups. However, remote patient monitoring patients submitted more glucose values (177 vs 146; P=.008), were more likely to achieve glycemic control in target range (79.2% vs 52.0%; P<.0001), and achieved the target range sooner (median, 3.3 vs 4.1 weeks; P=.025) than patients managed with paper logs. This was achieved without increasing in-person visits. Remote patient monitoring patients had lower rates of preeclampsia (5.8% vs 15.0%; P=.0006) and their infants had lower rates of neonatal hypoglycemia in the first 24 hours of life (29.8% vs 51.7%; P<.0001). CONCLUSION: Remote patient monitoring for the management of diabetes mellitus in pregnancy is superior to a traditional paper-based approach in achieving glycemic control and is associated with improved maternal and neonatal outcomes.