Mapping the landscape: a bibliometric study of global chimeric antigen receptor T cell immunotherapy research.

The rise of immunotherapy provided new approaches to cancer treatment. We aimed to describe the contribution of chimeric antigen receptor T cell immunotherapy to future prospects. We analyzed 8035 articles from the Web of Science Core Collection with CiteSpace that covered with various aspects with countries, institutions, authors, co-cited authors, journals, keywords, and references. The USA was the most prolific country, with the University of Pennsylvania being the most published institution. Among individual authors, June Carl H published the most articles, while Maude SL was the most frequently co-cited author. "Blood" emerged as the most cited journal. Keyword clustering revealed six core themes: "Expression," "Chimeric Antigen Receptor," "Tumor Microenvironment," "Blinatumomab," "Multiple Myeloma," and "Cytokine Release Syndrome." In the process of researching the timeline chart of keywords and references, "Large B-cell lymphoma" was located on the right side of the timeline. In the keyword prominence analysis, we found that the keywords "biomarkers," "pd-1," "antibody drug conjugate," "BCMA," and "chimeric antigen" had high explosive intensity in the recent past. We found that in terms of related diseases, "large B-cell lymphoma" and "cytokine release syndrome" are still difficult problems in the future. In the study of therapeutic methods, "BCMA," "PD-1," "chimeric antigen," and "antibody drug conjugate" deserve more attention from researchers in the future.

The utilization of chitosan/Bletilla striata hydrogels to elevate anti-adhesion, anti-inflammatory and pro-angiogenesis properties of polypropylene mesh in abdominal wall repair.

Polypropylene (PP) mesh is commonly used in abdominal wall repair due to its ability to reduce the risk of organ damage, infections and other complications. However, the PP mesh often leads to adhesion formation and does not promote functional tissue repair. In this study, we synthesized one kind of aldehyde Bletilla striata polysaccharide (BSPA) modified chitosan (CS) hydrogel based on Schiff base reaction. The hydrogel exhibited a porous network structure, a highly hydrophilic surface and good biocompatibility. We wrapped the PP mesh inside the hydrogel and evaluated the performance of the resulting composites in a bilateral 1 × 1.5 cm abdominal wall defect model in rats. The results of gross observation, histological staining and immunohistochemical staining demonstrated the positive impact of the CS hydrogel on anti-adhesion and wound healing effects. Notably, the addition of BSPA to the CS hydrogel further improved the performance of the composites in vivo, promoting wound healing by enhancing collagen deposition and capillary rearrangement. This study suggested that the BSPA-modified CS hydrogel significantly promoted the anti-adhesion, anti-inflammatory and pro-angiogenesis properties of PP meshes during the healing process. Overall, this work offers a novel approach to the design of abdominal wall repair patches.

Functional Multivariable Logistic Regression With an Application to HIV Viral Suppression Prediction.

Motivated by improving the prediction of the human immunodeficiency virus (HIV) suppression status using electronic health records (EHR) data, we propose a functional multivariable logistic regression model, which accounts for the longitudinal binary process and continuous process simultaneously. Specifically, the longitudinal measurements for either binary or continuous variables are modeled by functional principal components analysis, and their corresponding functional principal component scores are used to build a logistic regression model for prediction. The longitudinal binary data are linked to underlying Gaussian processes. The estimation is done using penalized spline for the longitudinal continuous and binary data. Group-lasso is used to select longitudinal processes, and the multivariate functional principal components analysis is proposed to revise functional principal component scores with the correlation. The method is evaluated via comprehensive simulation studies and then applied to predict viral suppression using EHR data for people living with HIV in South Carolina.

Discovery of Monovalent Direct Degraders of BRD4 that Act via the Recruitment of DCAF11.

Targeted protein degradation (TPD) using the ubiquitin proteasome system (UPS) is a rapidly growing drug discovery modality to eliminate pathogenic proteins. Strategies for TPD have focused on heterobifunctional degraders that often suffer from poor drug-like properties, and molecular glues that rely on serendipitous discovery. Monovalent "direct" degraders represent an alternative approach, in which small molecules bind to a target protein and induce degradation of that protein through the recruitment of an E3 ligase complex. Using an ultra-high throughput cell-based screening platform, degraders of the bromodomain extraterminal protein BRD4 were identified and optimized to yield a lead compound, PLX-3618. In this paper, we demonstrate that PLX-3618 elicited UPS-mediated selective degradation of BRD4, resulting in potent antitumor activity in vitro and in vivo. Characterization of the degradation mechanism identified DCAF11 as the E3 ligase required for PLX-3618-mediated degradation of BRD4. Protein-protein interaction studies verified a BRD4:PLX-3618:DCAF11 ternary complex, and mutational studies provided further insights into the DCAF11-mediated degradation mechanism. Collectively, these results demonstrate the discovery and characterization of a novel small molecule that selectively degrades BRD4 through the recruitment of the E3 substrate receptor, DCAF11, and promotes potent antitumor activity in vivo.

Rural-urban and racial differences in cesarean deliveries before and during the COVID-19 pandemic in South Carolina.

PROBLEM: Unnecessary cesarean delivery increases the risk of complications for birthing people and infants. BACKGROUND: Examining the intersectionality of rural and racial disparities in low-risk cesarean delivery is necessary to improve equity in quality obstetrics care. AIM: To evaluate rural and racial/ethnic differences in Nulliparous, Term, Singleton, Vertex (NTSV) and primary cesarean delivery rates before and during the COVID-19 pandemic in South Carolina. METHODS: This retrospective cohort study used birth certificates linked to all-payer hospital discharge data for South Carolina childbirths from 2018 to 2021. Multilevel logistic regressions examined differences in cesarean outcomes by rural/urban hospital location and race/ethnicity of birthing people during pre-pandemic (January 2018-February 2020) and peri-pandemic periods (March 2020-December 2021), adjusting for maternal, infant, and hospital characteristics among two low-risk pregnancy cohorts: 1) Nulliparous, Term, Singleton, Vertex (NTSV, n = 65,974) and 2) those without prior cesarean (primary, n = 167,928). FINDINGS: Black vs. White disparities remained for NTSV cesarean in adjusted models (urban pre-pandemic aOR = 1.34, 95 %CI 1.23-1.46) but were not significantly different for primary cesarean, apart from rural settings peri-pandemic (aOR = 0.87, 95 %CI 0.79-0.96). Hispanic individuals had higher adjusted odds of NTSV cesarean only for rural settings pre-pandemic (aOR = 1.28, 95 %CI 1.05-1.56), but this disparity was not significant during the pandemic (aOR = 1.13, 95 %CI 0.93-1.37). DISCUSSION AND CONCLUSION: Observed rural and racial/ethnic disparities in cesarean delivery outcomes were present before and during the COVID-19 pandemic. Strategies effective in reducing racial disparities in primary cesarean may be useful in also reducing Black vs. White NTSV cesarean disparities.

Aggregation Behavior and Application Properties of Novel Glycosylamide Quaternary Ammonium Salts in Aqueous Solution.

Amidation of lactobionic acid with N,N-dimethylaminopropyltriamine was conducted to obtain N-(3'-dimethylaminopropyl)-lactamido-3-aminopropane (DDLPD), which was quaternized with bromoalkanes of different carbon chain lengths to synthesize double-stranded lactosylamide quaternary ammonium salt N-[N'[3-(lactosylamide)]propyl-N'-alkyl] propyl-N,N-dimethyl-N-alkylammonium bromide (CnDDLPB, n = 8, 10, 12, 14, 16). The surface activity and the adsorption and aggregation behaviors of the surfactants were investigated via equilibrium surface tension, dynamic light scattering, and cryo-electron microscopy measurements in an aqueous solution. The application properties of the products in terms of wettability, emulsification, foam properties, antistatic, salt resistance, and bacteriostatic properties were tested. CnDDLPB exhibited a low equilibrium surface tension of 27.82 mN/m. With an increase in the carbon chain length, the critical micellar concentration of CnDDLPBD decreased. Cryo-electron microscopy revealed that all products except C8DDLPB formed stable monolayer, multi-layer, and multi-compartmental vesicle structures in an aqueous solution. C14DDLPB has the best emulsification performance on soybean oil, with a time of 16.6 min; C14DDLPB has good wetting and spreading properties on polytetrafluoroethylene (PTFE) when the length of carbon chain is from 8 to 14, and the contact angle can be lowered to 33°~40°; CnDDLPB has low foam, which is typical of low-foaming products; C8DDLPB and C10DDLPB both show good antistatic properties. C8DDLPB and C14DDLPB have good salt resistance, and C12DDLPB has the best antimicrobial property, with the inhibition rate of 99.29% and 95.28% for E. coli and Gluconococcus aureus, respectively, at a concentration of 350 ppm.

Untargeted metabolomics revealed the mechanism of aucubin on glucocorticoid-induced osteoporosis in mice through modulating arachidonic acid metabolism.

Glucocorticoid-induced osteoporosis (GIOP) represents the most prevalent form of secondary osteoporosis. Aucubin (AU), a principal active component found in traditional herbal medicines such as Eucommia ulmoides, has been demonstrated to enhance osteoblast differentiation. Nonetheless, the precise therapeutic effects of AU on GIOP and the complex underlying regulatory mechanisms warrant further investigation. We first established a GIOP model in female mice and then assessed the therapeutic effects of AU using micro-CT analysis, biomechanical testing, measurements of serum calcium (Ca) and phosphorus (P) levels, and histological analyses using Hematoxylin and Eosin (HE) and Masson staining. Subsequently, non-targeted metabolomics was employed in order to study the effects of AU on serum metabolites in GIOP mice. The levels of the factors related to these metabolites were quantified using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) and western blot analyses. Finally, the effects of AU on osteoblastic and osteoclastic differentiation were examined. We found that AU significantly ameliorated bone microarchitecture and strength in GIOP mice. It mitigated pathological damages such as impairment of trabecular bone structure and reduction in collagen fibers, while concurrently elevating serum levels of Ca and P. Non-targeted metabolomics revealed that Arachidonic acid (AA) metabolism serves as a common pathway between the control and GIOP groups, as well as between the high-dose AU (AUH) and GIOP groups. AU notably upregulates prostaglandin-endoperoxide synthase 2 (PTGS2) and microsomal prostaglandin-E synthase 1 (PTGES) expression and downregulates prostaglandin-H2 D-isomerase (PTGDS) expression. Furthermore, AU treatment increased the expression of runt-related transcription factor 2 (Runx2) and transcription factor Sp7 (Osterix), enhanced serum alkaline phosphatase (ALP) activity, and reduced osteoclast expression. These results indicate that AU is a potential drug for treating GIOP, and its mechanism is related to regulating AA metabolism and promoting osteoblast differentiation. However, the key targets of AU in treating GIOP still need further exploration.

Travel Burden and Timely Linkage to Care Among People Newly Diagnosed with HIV Infection in South Carolina from 2005 to 2020.

This retrospective study explored the association between travel burden and timely linkage to care (LTC) among people with HIV (PWH) in South Carolina. HIV care data were derived from statewide all-payer electronic health records, and timely LTC was defined as having at least one viral load or CD4 count record within 90 days after HIV diagnosis before the year 2015 and 30 days after 2015. Travel burden was measured by average driving time (in minutes) to any healthcare facility visited within six months before and one month after the initial HIV diagnosis. Multivariable logistic regression models with the least absolute shrinkage and selection operator were employed. From 2005 to 2020, 81.2% (3,547 out of 4,366) of PWH had timely LTC. Persons who had longer driving time (adjusted Odds Ratio (aOR): 0.37, 95% CI: 0.14-0.99), were male versus female (aOR: 0.73, 95% CI: 0.58-0.91), had more comorbidities (aOR: 0.73, 95% CI: 0.57-0.94), and lived in counties with a higher percentage of unemployed labor force (aOR: 0.21, 95% CI: 0.06-0.71) were less likely to have timely LTC. However, compared to those aged between 18 and 24 years old, those aged between 45 and 59 (aOR:1.47, 95% CI: 1.14-1.90) or older than 60 (aOR:1.71, 95% CI: 1.14-2.56) were more likely to have timely LTC. Concentrated and sustained interventions targeting underserved communities and the associated travel burden among newly diagnosed PWH who are younger, male, and have more comorbidities are needed to improve LTC and reduce health disparities.

The Value of 3D SPACE MRI in Differentiating between Sequestrated Lumbar Disc Herniation and Tumors: Two Cases and Literature.

Background: Intervertebral disc herniation, defined as the protrusion or extrusion of the disc mass outside the disc space, is common and easy to diagnose on conventional Magnetic Resonance imaging (MRI) or Computed Tomography (CT) scans. However, the sequestrated disc fragments are challenging to detect, and intervertebral disc mass displacement into the dural sac, which can lead to serious neurological problems such as Cauda equina syndrome (CES). The sequestrated disc fragments do not have specific clinical or radiological characteristics that can differentiate an atypical disc mass from a tumor, making the diagnosis difficult preoperatively. Herein, we describe the use of Sampling Perfection with Application Optimized Contrast using different flip angle Evolution in Magnetic Resonance Imaging (3D SPACE MRI) in the diagnosis of the intervertebral disc fragment that mimicked a tumor. Case presentation: In this study, we report two cases of sequestered lumbar disc herniation. The first case was a 37-year-old patient with a 2-year history of intermittent left lower limb pain that aggravates with exercise and is relieved at rest, while the second case was a 42-year-old patient with a history of 40 days of numbness and pain in the left lower limb. Conclusion: 3D SPACE MRI is a beneficial diagnostic imaging tool for discriminating between disc mass that mimics a tumor and a tumor before surgery. If the disc fragment mimicking a tumor can be identified before the operation, open surgical treatment won't be necessary for all patients.

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study.

BACKGROUND: Sepsis remains a significant challenge in patients with major trauma in the ICU. Early detection and treatment are crucial for improving outcomes and reducing mortality rates. Nonetheless, clinical tools for predicting sepsis among patients with major trauma are limited. This study aimed to develop and validate an artificial intelligence (AI) platform for predicting the risk of sepsis among patients with major trauma. METHODS: This study involved 961 patients, with prospective analysis of data from 244 patients with major trauma at our hospital and retrospective analysis of data from 717 patients extracted from a database in the United States. The patients from our hospital constituted the model development cohort, and the patients from the database constituted the external validation cohort. The patients in the model development cohort were randomly divided into a training cohort and an internal validation cohort at a ratio of 8:2. The machine learning algorithms used to train models included logistic regression (LR), decision tree (DT), extreme gradient boosting machine (eXGBM), neural network (NN), random forest (RF), and light gradient boosting machine (LightGBM). RESULTS: The incidence of sepsis for the model development cohort was 43.44%. Twelve predictors, including gender, abdominal trauma, open trauma, red blood cell count, heart rate, respiratory rate, injury severity score, sequential organ failure assessment score, Glasgow coma scale, smoking, total protein concentrations, and hematocrit, were used as features in the final model. Internal validation showed that the NN model had the highest area under the curve (AUC) of 0.932 (95% CI: 0.917-0.948), followed by the LightGBM and eXGBM models with AUCs of 0.913 (95% CI: 0.883-0.930) and 0.912 (95% CI: 0.880-0.935), respectively. In the external validation cohort, the eXGBM model (AUC: 0.891, 95% CI: 0.866-0.914) had the highest AUC value, followed by the LightGBM model (AUC: 0.886, 95% CI: 0.860-0.906), and the AUC value of the NN model was only 0.787 (95% CI: 0.751-0.829). Considering the predictive performance for both the internal and external validation cohorts, the LightGBM model had the highest score of 82, followed by the eXGBM (81) and NN (76) models. Thus, the LightGBM was emerged as the optimal model, and it was deployed online as an AI application. CONCLUSIONS: This study develops and validates an AI application to effectively assess the susceptibility of patients with major trauma to sepsis. The AI application equips healthcare professionals with a valuable tool to promptly identify individuals at high risk of developing sepsis. This will facilitate clinical decision-making and enable early intervention.

Hierarchical Bilayer Polyelectrolyte Ion Paper Conductor for Moisture-Induced Power Generation.

Harvesting energy from air water (atmospheric moisture) promises a sustainable self-powered system without any restrictions from specific environmental requirements (e.g., solar cells, hydroelectric, or thermoelectric devices). However, the present moisture-induced power devices traditionally generate intermittent or bursts of energy, especially for much lower current outputs (generally keeping at nA or µA levels) from the ambient environment, typically suffering from inferior ionic conductivity and poor hierarchical structure design for manipulating sustained air water and ion-charge transport. Here, we demonstrate a universal strategy to design a high-performance bilayer polyelectrolyte ion paper conductor for generating continuous electric power from ambient humidity. The generator can produce a continuous voltage of up to 0.74 V and also an exceptional current of 5.63 mA across a single 1.0 mm-thick ion paper conductor. We discover that the sandwiched LiCl-nanocellulose-engineered paper promises an ion-transport junction between the negatively and positively charged bilayer polyelectrolytes for application in MEGs with both high voltage and high current outputs. Moreover, we demonstrated the universality of this bilayer sandwich nanocellulose-salt engineering strategy with other anions and cations, exhibiting similar power generation ability, indicating that it could be the next generation of sustainable MEGs with low cost, easier operation, and high performance.

PARP-1 dependent cell death pathway (Parthanatos) mediates early brain injury after subarachnoid hemorrhage.

Subarachnoid hemorrhage (SAH) is a neurological condition with high mortality and poor prognosis, and there are currently no effective therapeutic drugs available. Poly (ADP-ribose) polymerase 1 (PARP-1) dependent cell death pathway-parthanatos is closely associated with stroke. We investigated improvements in neurological function, oxidative stress, blood-brain barrier and parthanatos-related protein expression in rats with SAH after intraperitoneal administration of PARP-1 inhibitor (AG14361). Our study found that the expression of parthanatos-related proteins was significantly increased after SAH. Immunofluorescence staining showed increased expression of apoptosis-inducing factor (AIF) in the nucleus after SAH. Administration of PARP-1 inhibitor significantly reduced malondialdehyde (MDA) level and the expression of parthanatos-related proteins. Immunofluorescence staining showed that PARP-1 inhibitor reduced the expression of 8-hydroxy-2' -deoxyguanosine (8-OHdG) and thus reduced oxidative stress. Moreover, PARP-1 inhibitor could inhibit inflammation-associated proteins level and neuronal apoptosis, protect the blood-brain barrier and significantly improve neurological function after SAH. These results suggest that PARP-1 inhibitor can significantly improve SAH, and the underlying mechanism may be through inhibiting parthanatos pathway.

To explore the protective effect of gastrodin on PC12 cells against oxidative stress induced by lead acetate based on network pharmacology.

Objective: Screening and predicting potential targets for gastrodin antioxidant stress based on network pharmacology methods, and exploring the effect of gastrodin on lead acetate induced oxidative stress in PC12 cells through cell experiments. Methods: Through the Pharmaper database Predict the target of action of gastrodin. Through OMIM and GeneCards to collect oxidative stress targets from database, and intersect with drug targets to obtain drug disease intersection targets; Construct a PPI network diagram using the STRING database. Perform GO enrichment analysis and KEGG pathway enrichment analysis on intersection targets through the DAVID platform. Lead acetate (PbAc) exposure was used to establish a lead poisoning cell model, and intracellular ROS levels, ALB, AKT1, and Caspase-3 levels were measured. Results: A total of 288 targets of gastrodin action, 638 targets related to oxidative stress, and 62 drug disease intersection targets were obtained, among which core targets such as ALB, AKT1, CASP3 may be closely related to oxidative stress. KEGG pathway analysis showed that gastrodin antioxidant stress mainly involved in lipid, cancer pathway and other signaling pathways. The results of the cell experiment showed that 50 µM is the optimal effective concentration for PbAc induced ROS production in PC12 cells. Gastrodin significantly increased the ROS content of PC12 cells treated with PbAc, Upregulation of ALB expression and downregulation of AKT1 and CASP3 expression. Conclusions: Gastrodin may alleviate PbAc-induced ROS in PC12 cells, indicating potential protective effects against oxidative stress. Further studies are needed to confirm these findings and explore the underlying mechanisms.

SNR Enhancement for Comparator-Based Ultra-Low-Sampling Φ-OTDR System Using Compressed Sensing.

The large amount of sampled data in coherent phase-sensitive optical time-domain reflectometry (Φ-OTDR) brings heavy data transmission, processing, and storage burdens. By using the comparator combined with undersampling, we achieve simultaneous reduction of sampling rate and sampling resolution in hardware, thus greatly decreasing the sampled data volume. But this way will inevitably cause the deterioration of detection signal-to-noise ratio (SNR) due to the quantization noise's dramatic increase. To address this problem, denoising the demodulated phase signals using compressed sensing, which exploits the sparsity of spectrally sparse vibration, is proposed, thereby effectively enhancing the detection SNR. In experiments, the comparator with a sampling parameter of 62.5 MS/s and 1 bit successfully captures the 80 MHz beat signal, where the sampled data volume per second is only 7.45 MB. Then, when the piezoelectric transducer's driving voltage is 1 Vpp, 300 mVpp, and 100 mVpp respectively, the SNRs of the reconstructed 200 Hz sinusoidal signals are respectively enhanced by 23.7 dB, 26.1 dB, and 28.7 dB by using compressed sensing. Moreover, multi-frequency vibrations can also be accurately reconstructed with a high SNR. Therefore, the proposed technique can effectively enhance the system's performance while greatly reducing its hardware burden.

Discovery of Monovalent Direct Degraders of BRD4 That Act Via the Recruitment of DCAF11.

Targeted protein degradation (TPD) using the ubiquitin proteasome system (UPS) is a rapidly growing drug discovery modality to eliminate pathogenic proteins. Strategies for TPD have focused on heterobifunctional degraders that often suffer from poor drug-like properties, and molecular glues that rely on serendipitous discovery. Monovalent "direct" degraders represent an alternative approach, in which small molecules bind to a target protein and induce degradation of that protein through the recruitment of an E3 ligase complex. Using an ultra-high throughput cell-based screening platform, degraders of the bromodomain extra-terminal (BET) protein BRD4 were identified and optimized to yield a lead compound, PLX-3618. In this paper, we demonstrate that PLX-3618 elicited UPS-mediated selective degradation of BRD4, resulting in potent anti-tumor activity in vitro and in vivo. Characterization of the degradation mechanism identified DCAF11 as the E3 ligase required for PLX-3618-mediated degradation of BRD4. Protein-protein interaction studies verified a BRD4:PLX-3618:DCAF11 ternary complex, and mutational studies provided further insights into the DCAF11-mediated degradation mechanism. Collectively, these results demonstrate the discovery and characterization of a novel small molecule that selectively degrades BRD4 through the recruitment of the E3 substrate receptor, DCAF11, and promotes potent anti-tumor activity in vivo.

Vaccination status and disease severity of COVID-19 in different phases of the pandemic.

This study aimed to explore the clinical profile and the impact of vaccination status on various health outcomes among COVID-19 patients diagnosed in different phases of the pandemic, during which several variants of concern (VOCs) circulated in South Carolina (SC). The current study included 861,526 adult COVID-19 patients diagnosed between January 2021 and April 2022. We extracted their information about demographic characteristics, vaccination, and clinical outcomes from a statewide electronic health record database. Multiple logistic regression models were used to compare clinical outcomes by vaccination status in different pandemic phases, accounting for key covariates (e.g. historical comorbidities). A reduction in mortality was observed among COVID-19 patients during the whole study period, although there were fluctuations during the Delta and Omicron dominant periods. Compared to non-vaccinated patients, full-vaccinated COVID-19 patients had lower mortality in all dominant variants, including Pre-alpha (adjusted odds ratio [aOR]: 0.33; 95%CI: 0.15-0.72), Alpha (aOR: 0.58; 95%CI: 0.42-0.82), Delta (aOR: 0.28; 95%CI: 0.25-0.31), and Omicron (aOR: 0.29; 95%CI: 0.26-0.33) phases. Regarding hospitalization, full-vaccinated parties showed lower risk of hospitalization than non-vaccinated patients in Delta (aOR: 0.44; 95%CI: 0.41-0.47) and Omicron (aOR: 0.53; 95%CI: 0.50-0.57) dominant periods. The findings demonstrated the protection effect of the COVID-19 vaccines against all VOCs, although some of the full-vaccinated population still have symptoms to varying degrees from COVID-19 disease at different phases of the pandemic.

Expression of a single-chain monellin (MNEI) mutant with enhanced stability in transgenic mice milk.

Monellin is a sweet protein that may be used as a safe and healthy sweetener. However, due to its low stability, the application of monellin is currently very limited. Here, we describe a wild-type, a double-sites mutant (E2N/E23A) and a triple-sites mutant (N14A/E23Q/S76Y) of single-chain monellin (MNEI) expressed in transgenic mice milk. Based on enzyme-linked immunoassay (ELISA), Western blot, and sweetness intensity testing, their sweetness and stability were compared. After boiling for 2 min at different pH conditions (2.5, 5.1, 6.8, and 8.2), N14A/E23Q/S76Y-MNEI showed significantly higher sweetness and stability than the wild-type and E2N/E23A-MNEI. These results suggest that N14A/E23Q/S76Y-MNEI shows remarkable potential as a sweetener in the future.

Multi-sequence MRI-based radiomics: An objective method to diagnose early-stage osteonecrosis of the femoral head.

OBJECTIVES: This study investigated the use of radiomics for diagnosing early-stage osteonecrosis of the femoral head (ONFH) by extracting features from multiple MRI sequences and constructing predictive models. MATERIALS AND METHODS: We conducted a retrospective review, collected MR images of early-stage ONFH (102 from institution A and 20 from institution B) and healthy femoral heads (102 from institution A and 20 from institution B) from two institutions. We extracted radiomics features, handled batch effects using Combat, and normalized features using z-score. We employed the Least absolute shrinkage and selection operator (LASSO) algorithm, along with Max-Relevance and Min-Redundancy (mRMR), to select optimal features for constructing radiomics models based on single, double, and multi-sequence MRI data. We evaluated performance using receiver operating characteristic (ROC) and precision-recall (PR) curves, and compared area under curve of ROC (AUC-ROC) values with the DeLong test. Additionally, we studied the diagnostic performance of the multi-sequence radiomics model and radiologists, compared the diagnostic outcomes of the model and radiologists using the Fisher exact test. RESULTS: We studied 122 early-stage ONFH and 122 normal femoral heads. The multi-sequence model exhibited the best diagnostic performance among all models (AUC-ROC, PR-AUC for training set: 0.96, 0.961; validation set: 0.96, 0.97; test set: 0.94, 0.94), and it outperformed three resident radiologists on the external testing group with an accuracy of 87.5 %, sensitivity of 85.00 %, and specificity of 90.00 % (p < 0.01), highlighting the robustness of our findings. CONCLUSIONS: Our study underscored the novelty of the multi-sequence radiomics model in diagnosing early-stage ONFH. By leveraging features extracted from multiple imaging sequences, this approach demonstrated high efficacy, indicating its potential to advance early diagnosis for ONFH. These findings provided important guidance for enhancing early diagnosis of ONFH through radiomics methods, offering new avenues and possibilities for clinical practice and patient care.

Multi-level Factors Associated with HIV Late Presentation with Advanced Disease and Delay Time of Diagnosis in South Carolina, 2005-2019.

This study explored individual- and county-level risk factors of late presentation with advanced disease (LPAD) among people with HIV (PWH) and their longer delay time from infection to diagnosis in South Carolina (SC), using SC statewide Enhanced HIV/AIDS Reporting System (eHARS). LPAD was defined as having an AIDS diagnosis within three months of initial HIV diagnosis, and delay time from HIV infection to diagnosis was estimated using CD4 depletion model. 3,733 (41.88%) out of 8,913 adult PWH diagnosed from 2005 to 2019 in SC were LPAD, and the median delay time was 13.04 years. Based on the generalized estimating equations models, PWH who were male (adjusted prevalence ratio [aPR]: 1.22, 95% CI: 1.12 ∼ 1.33), aged 55+ (aPR: 1.76, 95% CI: 1.62 ∼ 1.92), were Black (aPR: 1.09, 95% CI: 1.03 ∼ 1.15) or Hispanic (aPR: 1.42, 95% CI: 1.26 ∼ 1.61), and living in counties with a larger proportion of unemployment individuals (aPR: 1.02, 95% CI: 1.01 ∼ 1.03) were more likely to be LPAD. Among PWH who were LPAD, Hispanic (adjusted beta: 1.17, 95% CI: 0.49 ∼ 1.85) instead of Black (adjusted beta: 0.11, 95% CI: -0.30 ∼ 0.52) individuals had significant longer delay time compared to White individuals. Targeted and sustained interventions are needed for older, male, Hispanic or Black individuals and those living in counties with a higher percentage of unemployment because of their higher risk of LPAD. Additionally, specific attention should be paid to Hispanic individuals due to their longer delay time to diagnosis.

Plasma proteomics analysis reveals potential biomarkers for intracranial aneurysm formation and rupture.

The aim of this study was to investigate the plasma proteome in individuals with intracranial aneurysms (IAs) and identify biomarkers associated with the formation and rupture of IAs. Proteomic profiles (N = 1069 proteins) were assayed in plasma (N = 120) collected from patients with ruptured and unruptured intracranial aneurysms (RIA and UIA), traumatic subarachnoid hemorrhage (tSAH), and healthy controls (HC) using tandem mass tag (TMT) labeling quantitative proteomics analysis. Gene ontology (GO) and pathway analysis revealed that these relevant proteins were involved in immune response and extracellular matrix organization pathways. Seven candidate biomarkers were verified by ELISA in a completely separate cohort for validation (N = 90). Among them, FN1, PON1, and SERPINA1 can be utilized as diagnosis biomarkers of IA, with a combined area under the ROC curve of 0.891. The sensitivity was 93.33%, specificity was 75.86%, and accuracy was 87.64%. PFN1, ApoA-1, and SERPINA1 can serve as independent risk factors for predicting aneurysm rupture. The combined prediction of aneurysm rupture yielded an area under the ROC curve of 0.954 with a sensitivity of 96.15%, specificity of 81.48%, and accuracy of 88.68%. This prediction model was more effective than PHASES score. In conclusion, high-throughput proteomics analysis with population validation was performed to assess blood-based protein expression characteristics. This revealed the potential mechanism of IA formation and rupture, facilitating the discovery of biomarkers. SIGNIFICANCE: Although the annual rupture rate of small unruptured aneurysms is believed to be minimal, studies have indicated that ruptured aneurysms typically have an average size of 6.28 mm, with 71.8% of them being <7 mm in diameter. Hence, evaluating the possibility of rupture in UIA and making a choice between aggressive treatment and conservative observation emerges as a significant challenge in the management of UIA. No biomarker or scoring system has been able to satisfactorily address this issue to date. It would be significant to develop biomarkers that could be used for early diagnosis of IA as well as for prediction of IA rupture. After TMT proteomics analysis and ELISA validation in independent populations, we found that FN1, PON1, and SERPINA1 can be utilized as diagnostic biomarkers for IA, and PFN1, ApoA-1, and SERPINA1 can serve as independent risk factors for predicting aneurysm rupture. Especially, when combined with ApoA-1, SERPINA1, and PFN1 for predicting IA rupture, the area under the curve (AUC) was 0.954 with a sensitivity of 96.15%, specificity of 81.48%, and accuracy of 88.68%. This prediction model was more effective than PHASES score.