Assessing economic investment required to scale up bariatric surgery capacity in England: a health economic modelling analysis.

OBJECTIVES: To quantify the economic investment required to increase bariatric surgery (BaS) capacity in National Health Service (NHS) England considering the growing obesity prevalence and low provision of BaS in England despite its high clinical effectiveness. DESIGN: Data were included for the patients with obesity who were eligible for BaS. We used a decision-tree approach including four distinct steps of the patient pathway to capture all associated resource use. We estimated total costs according to the current capacity (current scenario) and three BaS scaling up strategies over a time horizon of 20 years (projected scenario): maximising NHS capacity (strategy 1), maximising NHS and private sector capacity (strategy 2) and adding infrastructure to NHS capacity to cover the entire prevalent and incident obesity populations (strategy 3). SETTING: BaS centres based in NHS and private sector hospitals in England. MAIN OUTCOME MEASURES: Number of BaS procedures (including revision surgery), cost (GBP) and resource utilisation over 20 years. RESULTS: At current capacity, the number of BaS procedures and the total cost over 20 years were estimated to be 140 220 and £1.4 billion, respectively. For strategy 1, these values were projected to increase to 157 760 and £1.7 billion, respectively. For strategy 2, the values were projected to increase to 232 760 and £2.5 billion, respectively. Strategy 3 showed the highest increase to 564 784 and £6.4 billion, respectively, with an additional 4081 personnel and 49 facilities required over 20 years. CONCLUSIONS: The expansion of BaS capacity in England beyond a small proportion of the eligible population will likely be challenging given the significant upfront economic investment and additional requirement of personnel and infrastructure.

Regulating Local Electron Density of Cyano Sites in Graphitic Nitride Carbon by Giant Internal Electric Field for Efficient CO2 Photoreduction to Hydrocarbons.

Selective photocatalytic CO2 reduction to high-value hydrocarbons using graphitic carbon nitride (g-C3N4) polymer holds great practical significance. Herein, the cyano-functionalized g-C3N4 (CN-g-C3N4) with a high local electron density site is successfully constructed for selective CO2 photoreduction to CH4 and C2H4. Wherein the potent electron-withdrawing cyano group induces a giant internal electric field in CN-g-C3N4, significantly boosting the directional migration of photogenerated electrons and concentrating them nearby. Thereby, a high local electron density site around its cyano group is created. Moreover, this structure can also effectively promote the adsorption and activation of CO2 while firmly anchoring *CO intermediates, facilitating their subsequent hydrogenation and coupling reactions. Consequently, using H2O as a reducing agent, CN-g-C3N4 achieves efficient and selective photocatalytic CO2 reduction to CH4 and C2H4 activity, with maximum rates of 6.64 and 1.35 µmol g-1 h-1, respectively, 69.3 and 53.8 times higher than bulk g-C3N4 and g-C3N4 nanosheets. In short, this work illustrates the importance of constructing a reduction site with high local electron density for efficient and selective CO2 photoreduction to hydrocarbons.

The mediating role of perceived social support between work-family conflict and presenteeism among ICU nurses working shift work in Chinese public hospitals: A cross-sectional investigation.

OBJECTIVE: Relative to explicit absenteeism, nurses' presenteeism has a more lasting impact and is more harmful and costly. This study aimed to explore the relationship between work-family conflict, perceived social support, and presenteeism and whether perceived social support mediates the relationship between work-family conflict and presenteeism among ICU nurses working on shifts in Chinese public hospitals. MATERIALS AND METHODS: A cross-sectional research design was conducted from January to April 2023 in Sichuan Province, China. A total of 609 valid questionnaires were collected. The questionnaires contained information on demographic characteristics, the Work-Family Conflict (WFC) scale, the Perceived Social Support Scale (PSSS), and Stanford Presenteeism Scale-6 (SPS-6). Multiple stratified regression was used to explore the mediating role of perceived social support between work-family conflict and presenteeism. The mediating effect of perceived social support in work-family conflict and presenteeism was tested by Model 4 in the PROCESS 4.1 macro program in SPSS. RESULTS: A total of 609 nurses were included in this study, and the mean presenteeism score for ICU nurses working on shifts was 16.01 ± 4.293 (Mean ± SD), with high presenteeism accounting for 58.46%. After controlling for sociodemographic characteristic variables, work-family conflict was positively associated with presenteeism, explaining 7.7% of the variance. High perceived social support was related to low presenteeism, explaining 11.5% of the variance. Perceived social support mediated the association between work-family conflict and presenteeism among ICU nurses working on shifts. CONCLUSIONS: Chinese shift-work ICU nurses' high presenteeism scores deserve managers' attention. Work-family conflict is a significant predictor of nurses' presenteeism. Perceived social support is essential in improving nurses' work-family conflict and mediates the relationship between work-family conflict and presenteeism. Improving social support can reduce the impact of work-family conflict on presenteeism among nurses working shifts.

Mapping of dynamic quantitative trait loci for plant height in a RIL population of foxtail millet (Setaria italica L.).

Plant height (PH) is a crucial trait for strengthening lodging resistance and boosting yield in foxtail millet. To identify quantitative trait loci (QTL) and candidate genes associated with PH, we first developed a genetic map using a recombinant inbred line (RIL) population derived from a cross between Aininghuang and Jingu 21. Then, PH phenotyping data and four variations of best linear unbiased prediction (BLUP) were collected from nine environments and three development stages. Next, QTL mapping was conducted using both unconditional and conditional QTL methods. Subsequently, candidate genes were predicted via transcriptome analysis of parental samples at three developmental stages. The results revealed that the genetic map, based on re-sequencing, consisted of 4,360 bin markers spanning 1,016.06 cM with an average genetic distance of 0.23 cM. A total of 19 unconditional QTL, accounting for 5.23%-35.36% of the phenotypic variation explained (PVE), which included 7 major and 4 stable QTL, were identified. Meanwhile, 13 conditional QTL, explaining 5.88%-40.35% of PVE, including 5 major and 3 stable QTL, were discovered. Furthermore, four consistent and stable QTL were identified. Finally, eight candidate genes were predicted through RNA-seq and weighted gene co-expression network analysis (WGCNA). Those findings provide a crucial foundation for understanding the genetic mechanisms underlying PH development and facilitate molecular marker-assisted breeding of ideal plant types in foxtail millet.

IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models.

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich vision-language correlation from image-text pairs, like BLIP-2 and GPT-4, have been intensively investigated. However, despite these developments, the application of LLMs and VLMs in image quality assessment (IQA), particularly in medical imaging, remains unexplored. This is valuable for objective performance evaluation and potential supplement or even replacement of radiologists' opinions. To this end, this study introduces IQAGPT, an innovative computed tomography (CT) IQA system that integrates image-quality captioning VLM with ChatGPT to generate quality scores and textual reports. First, a CT-IQA dataset comprising 1,000 CT slices with diverse quality levels is professionally annotated and compiled for training and evaluation. To better leverage the capabilities of LLMs, the annotated quality scores are converted into semantically rich text descriptions using a prompt template. Second, the image-quality captioning VLM is fine-tuned on the CT-IQA dataset to generate quality descriptions. The captioning model fuses image and text features through cross-modal attention. Third, based on the quality descriptions, users verbally request ChatGPT to rate image-quality scores or produce radiological quality reports. Results demonstrate the feasibility of assessing image quality using LLMs. The proposed IQAGPT outperformed GPT-4 and CLIP-IQA, as well as multitask classification and regression models that solely rely on images.

Recurrent mitral regurgitation after repair of Barlow's disease in a single-center retrospective cohort study.

Background: Barlow's disease (BD) is a common etiology of degenerative mitral valve (MV) disease, often causing significant mitral regurgitation (MR). The pathology of BD is challenging for surgeons performing MV repair (MVR). However, most MVR effectiveness studies have been based on survival and risk of reoperation. The aim of this study was to analyze the safety, efficacy, and durability of MVR in patients with BD and to identify factors that influence recurrent MR. Methods: We retrospectively analyzed the clinical outcomes of 274 patients undergoing MVR for BD at a tertiary hospital (Guangdong People's Hospital, Guangzhou, China) between January 2010 and June 2022. To analyze the results of MVR and identify the risk factors for MR recurrence, we defined two groups: a total of 240 patients with MR grade <2+ (group A) and a total of 34 patients who had recurrent MR after MVR (group B; the patients with MR ≥2+). All patients were operated on using standard repair techniques. Recurrent MR was the primary outcome. Secondary outcomes were death and reoperation after MVR. Patients were followed up until March 2023. Patients were followed up by clinic visits, telephone calls, and postal or electronic questionnaires. Results: The median [range] patient age was 46.00 [16-75] years and 186 (67.9%) patients were male. Concomitant procedures were performed in 123 patients: tricuspid valve repair 71 (25.9%), maze or pulmonary vein isolation (PVI) 12 (4.4%), atrial septal defect (ASD) repair 3 (1.1%), and left atrial appendage (LAA) closure 28 (10.2%). Hospital mortality was 0.4%. Long-term complications included radiofrequency ablation in 7 patients (2.6%), pacemaker implantation in 1 patient (0.4%), and stroke in 3 patients (1.1%). The median follow-up was 3.28 (range, 0-12.39) years. Considering the competing risk of mortality, the cumulative incidence of MR progression 2+ or more grades was 2.6%, 5.9%, 14.5%, and 27.7% at 1 month, 1, 5, and 10 years, respectively. Overall survival at 1, 5, and 10 years was 99.3%, 98.6%, and 98.6%, respectively. The immediate postoperative MR area [hazard ratio (HR) =1.723; 95% confidence interval (CI): 1.051-2.824; P=0.031], postoperative left ventricular end-diastolic dimension (LVEDD) (HR =1.149; 95% CI: 1.016-1.300; P=0.027), and postoperative MR grade {HR = Exp[4.500 - 0.544 × ln(t + 20)]; P=0.008} were associated with an increased risk of MR recurrence, whereas a higher left ventricular ejection fraction (LVEF) (HR =0.931; 95% CI: 0.868-0.999; P=0.049) was associated with a decreased risk. Conclusions: MVR in patients with BD can be performed with low mortality and complications and is associated with superior long-term outcomes. However, MVR was associated with a certain risk of MR recurrence, especially in those with high postoperative LVEDD, residual MR >1+, and decreased postoperative LVEF. We recommend MVR for patients with BD, especially for those with early-stage disease. However, future randomized controlled trials are needed to confirm this.

Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment. PURPOSE: To develop and validate an MRI-based radiomics model and combine it with clinical factors to assess progression-free survival (PFS) and overall survival (OS) of patients with PCNSL. STUDY TYPE: Retrospective and prospective. POPULATION: Three hundred seventy-nine patients (179 female, 53 ± 7 years) from 2014 to 2022. FIELD STRENGTH/SEQUENCE: T2/fluid-attenuated inversion recovery, contrast-enhanced T1WI and diffusion-weighted echo-planar imaging sequences on 3.0 T. ASSESSMENT: Radiomics features were extracted from enhanced tumor regions on preoperative multi-sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance. STATISTICAL TESTS: Chi-squared, Mann-Whitney, Kaplan-Meier, log-rank, LASSO, Cox, decision curve analysis, time-dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P-value <0.05 was considered significant. RESULTS: Follow-up duration was 28.79 ± 22.59 months (median: 25). High-risk patients, determined by the median radiomics score, showed significantly lower survival rates than low-risk patients. Compared with NCCN-IPI, conventional imaging and clinical models, the combined model achieved the highest C-index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1-year, 3-year, and 5-year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1-year and 3-year survival in external validation. DATA CONCLUSION: Incorporating a multi-sequence MR-based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Sodium alginate-based coaxial fibers synergistically integrate moisture actuation, length tracing, humidity sensing, and electric heating.

The development of wearable electronics has driven the need for smart fibers with advanced multifunctional synergy. In this paper, we present a design of a multifunctional coaxial fiber that is composed of a biopolymer-derived core and an MXene/silver nanowire (AgNW) sheath by wet spinning. The fiber synergistically integrates moisture actuation, length tracing, humidity sensing, and electric heating, making it highly promising for portable devices and protective systems. The biopolymer-derived core provides deformation for moisture-sensitive actuation, while the MXene/AgNW sheath with good conductivity enables the fiber to perform electric heating, humidity sensing, and self-sensing actuation. The coaxial fiber can be programmed to rapidly desorb water molecules to shrink to its original length by using the MXene/AgNW sheath as an electrical heater. We demonstrate proof-of-concept applications based on the multifunctional fibers for thermal physiotherapy and wound healing/monitoring. The sodium alginate@MXene-based coaxial fiber presents a promising solution for the next-generation of smart wearable electronics.

Exploration of GmDof11-lncRNA13082 Module Regulating Oil Synthesis in Plants.

Soybean (Glycine max [Linn.] Merr.) is an important oilseed crop. Although transcription factors (TFs) can coordinate the expression of mRNA and lncRNA, their coordination in the soybean oil synthesis pathway remains unclear. This study examined the interaction between the TF GmDof11 and lncRNA13082 and found that overexpression of GmDof11 led to an increase in the number of Arabidopsis seeds, thousand seed weight, crude protein, hydrolysis amino acid, and soluble sugar. Additionally, it reduced the triglyceride and starch contents and affected the proportion of fatty acids, increasing the contents of palmitic acid, stearic acid, and linolenic acid. The yeast two-hybrid experiments revealed that GmDof11 interacts with GmBCCP1, GmLEC1b, and GmFAB2 proteins. In the RT-qPCR analysis of transgenic soybean roots, it was found that GmDof11 can activate the production of lncRNA13082 and work in conjunction with lncRNA13082 to oversee oil synthesis and nutrient storage. Our research provides robust theoretical evidence for a comprehensive resolution of TF-lncRNA regulation in the soybean oil synthesis network.

Application of Bovine Pericardium and Expanded Polytetrafluoroethylene Patches in Tricuspid Valvuloplasty after Cardiac Surgery.

Background: Leaflet augmentation is often required to correct an inadequate leaflet size due to leaflet thickening, contracture and junctional fusion in patients with tricuspid valve regurgitation (TR) after left-side valve surgery (LSVS). However, the ideal material for leaflet augmentation remains controversial. This article aims to compare the medium- and long-term results of tricuspid valve repair with bovine pericardium (BP) and expanded Polytetrafluoroethylene (ePTFE) patches for the augmentation of tricuspid leaflets and to compare the durability of the two materials. Methods: From January 2015 to April 2023, a total of 69 patients with severe isolated TR underwent tricuspid valvuloplasty (TVP) by leaflets augmentation with patches in our institute. According to the different types of patches, they were divided into the BP group (n = 44) and the ePTFE group (n = 25). Results: There were 3 perioperative deaths (4.3%), one case was due to low cardiac output syndrome in the BP group, and 2 cases were due to acute respiratory dysfunction syndrome and low cardiac output syndrome in the ePTFE group, respectively. Before discharge, the area of the TR jet on echocardiography decreased from 23.5 ± 9.1 to 4.2 ± 3.4 cm 2 . One case in each group was found to have increased blood flow velocity at the tricuspid orifice. After discharge, one patient in each group underwent repeat TVP, in the BP group because of shortened chordae and in the ePTFE group because of calcification of the patch. During the entire follow-up period, there were 7 cases of severe TR (10.1%), 5 in the BP group and 2 in the ePTFE group, a total of 5 cases of tricuspid stenosis (7.2%), 4 in the BP group and 1 in the ePTFE group, and a total of 6 deaths (8.7%), 5 in the BP group and 1 in the ePTFE group. Transthoracic ultrasound in a patient with tricuspid stenosis suggests stiff leaflet movement and poor motion. Conclusions: Leaflet patch enlargement can be safely used in tricuspid valve repair, but BP patches carry a risk of reduced flexibility and stiffness of movement, and ePTFE patches carries a risk of calcification.

Integrated Information for Pathogenicity and Treatment of Spiroplasma.

Spiroplasma, belonging to the class Mollicutes, is a small, helical, motile bacterium lacking a cell wall. Its host range includes insects, plants, and aquatic crustaceans. Recently, a few human cases of Spiroplasma infection have been reported. The diseases caused by Spiroplasma have brought about serious economic losses and hindered the healthy development of agriculture. The pathogenesis of Spiroplasma involves the ability to adhere, such as through the terminal structure of Spiroplasma, colonization, and invasive enzymes. However, the exact pathogenic mechanism of Spiroplasma remains a mystery. Therefore, we systematically summarize all the information about Spiroplasma in this review article. This provides a reference for future studies on virulence factors and treatment strategies of Spiroplasma.

EGaIn-Modified ePADs for Simultaneous Detection of Homocysteine and C-Reactive Protein in Saliva toward Early Diagnosis of Cardiovascular Disease.

Homocysteine (Hcy) and C-reactive protein (CRP) are critical biomarkers for numerous chronic diseases, with cardiovascular disease (CVD) being the most prevalent. The ability to simultaneously detect both biomarkers in point-of-care settings is in high demand for CVD early diagnosis and prevention. Herein, we prepared the eutectic gallium indium (EGaIn) nanoparticles decorated with p-phenylenediamine (PPD) on the surface to facilitate the subsequent attachment of gold nanoparticles (AuNPs) to achieve EGaIn-PPD@Au, which was modified on the screen-printed electrochemical paper-based analytical devices (ePADs). Aptamers that are specific to Hcy and CRP were then immobilized on the EGaIn-PPD@Au surface to achieve the sensing interface on ePADs. The presence of EGaIn-PPD@Au significantly enhanced the electrical conductivity, leading to amplified electrochemical signals. This aptasensor demonstrated high specificity, capable of detecting Hcy in a range of 1-50 µM with a detection limit of 0.22 µM, and the detection range for CRP was 1-100 ng/mL with a detection limit of 0.039 ng/mL. The aptasensor also effectively detected Hcy and CRP in clinical saliva samples, yielding an area under the curve (AUC) of about 0.80 when the individual biomarker was considered and 0.93 when both biomarkers were taken into account. The positive correlation observed between salivary and blood concentrations of Hcy and CRP, coupled with their association with cardiovascular disease (CVD), suggested the potential of this methodology as a noninvasive point-of-care strategy for the early diagnosis of CVD.

GABAergic imbalance in Parkinson's disease-related depression determined with MEGA-PRESS.

OBJECTIVE: The pathogenesis of depression in patients with Parkinson's disease (PD) is poorly understood. Therefore, this study aimed to explore the changes in γ-aminobutyric acid (GABA) and glutamate plus glutamine (Glx) levels in patients with PD with or without depression determined using MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS). MATERIALS AND METHODS: A total of 83 patients with primary PD and 24 healthy controls were included. Patients with PD were categorized into depressed PD (DPD, n = 19) and nondepressed PD (NDPD, n = 64) based on the 17-item Hamilton Depression Rating Scale. All participants underwent T1-weighted imaging and MEGA-PRESS sequence to acquire GABA+ and Glx values. The MEGA-PRESS sequence was conducted using 18.48 mL voxels in the left thalamus and medial frontal cortex. The GABA+, Glx, and creatine values were quantified using Gannet 3.1 software. RESULTS: The GABA+ and Glx values were not significantly disparate between patients with PD and controls in the thalamus and medial frontal cortex. However, the levels of N-acetyl aspartate/creatine and choline/creatine in the left thalamus were significantly lower in patients with PD than in controls (P = .031, P = .009). The GABA+/Water and GABA+/Creatine in the medial frontal cortex were higher in DPD than in NDPD (P = .001, P = .004). The effects of depression on Glx or other metabolite levels were not evident, and no significant difference in metabolite values was noted in the left thalamus among all groups (P > .05). CONCLUSIONS: GABA+ levels increased in the medial frontal cortex in DPD, which may be more closely related to depressive pathology. Thus, alterations in GABAergic function in special brain structures may be related to the clinical manifestations of PD symptoms, and hence mediating this function might help in treating depression in PD.

Metabolomic Applications in Gut Microbiota-Host Interactions in Human Diseases.

The human gut microbiota, consisting of trillions of microorganisms, encodes diverse metabolic pathways that impact numerous aspects of host physiology. One key way in which gut bacteria interact with the host is through the production of small metabolites. Several of these microbiota-dependent metabolites, such as short-chain fatty acids, have been shown to modulate host diseases. In this review, we examine how disease-associated metabolic signatures are identified using metabolomic platforms, and where metabolomics is applied in gut microbiota-disease interactions. We further explore how integration of metagenomic and metabolomic data in human studies can facilitate biomarkers discoveries in precision medicine.

Forms and Migration Mechanisms of Phosphorus in the Ice, Water, and Sediments of Cold and Arid Lakes.

Phosphorus (P) is a crucial nutrient in lake ecosystems and organic phosphorus (Po) is a significant component. However, the distribution characteristics and migration behaviour of Po in ice-water-sediment systems under freezing and thawing conditions in cold and arid regions remain unclear. This study aims to investigate the forms of Po and its contribution to endogenous P pollution. We selected three lakes (Dai, Hu, and Wu Lake) and employed phosphorus nuclear magnetic resonance (31P-NMR) techniques to analyse the following: (1) The total phosphorus (TP) content, which was the highest in the water from Dai Lake (0.16 mg/L), with substantial seasonal variation observed in Wu Lake, where P content was four times higher in summer than in winter because of farmland drainage. (2) Eutrophication analysis, which indicated that Dai Lake had significantly higher eutrophication levels than Wu Lake, with P being the controlling factor in Dai Lake and both N and P in Wu Lake. The proportion of Po in the TP content was 90%, 70%, and 55% for Wu, Dai, and Hu Lake, respectively, indicating that Po was the main component of eutrophic lakes. (3) 31P-NMR, which revealed that orthophosphate (Ortho-P) and monoester phosphate (Mon-P) were the main P components in the winter, with a higher P content in Dai Lake. Ortho-P has a higher content in ice, indicating that inorganic phosphorus (Pi) migration is the main factor in ice-water media. Mon-P showed multiple peaks in Dai Lake, indicating a complex composition of adenosine monophosphate and glucose-1-phosphate. (4) The ice-water phase change simulation experiments, which showed that phosphate was the least repelled in ice, while pyrophosphate (Pyro-P) and macromolecular P were more repelled. Adding sediment enhanced the migration of P but did not change the repulsion of macromolecular P, suggesting the molecular structure as the main influencing factor. These results provide important scientific evidence for the quantitative analysis of Po pollution in lake water environments, aiding in P load reduction and risk prevention and control.

MRI-based radiomics signatures for preoperative prediction of Ki-67 index in primary central nervous system lymphoma.

PURPOSE: The aim of this study was to develop and validate radiomics signatures based on MRI for preoperative prediction of Ki-67 proliferative index (PI) expression in primary central nervous system lymphoma (PCNSL). METHODS: A total of 341 patients with PCNSL were retrospectively analyzed, including 286 patients in one center as the training set and 55 patients in another two centers as the external validation set. Radiomics features were extracted and selected from preoperative contrast-enhanced T1-weighted images, fluid attenuation inversion recovery to build radiomics signatures according to the Ki-67 PI. The predictive performances of the radiomics model were evaluated using four classifiers including random forest, K-Nearest Neighbors, Neural Network and Decision Tree. A combined model was built by incorporating radiomics signature, clinical variables and MRI radiological characteristics using multivariate logistic regression analysis, and a nomogram was established to predict the expression of Ki-67 individually. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: Radiomics signatures were independent predictors of the expression level of Ki-67 (OR: 2.523, P < 0.001). RF radiomics models had the highest accuracy (0.934 in the training set and 0.811 in the external validation set) and F1 Score (0.920 in the training set and 0.836 in the external validation set). The clinic-radiologic-radiomics nomogram showed better predictive performance with AUCs of 0.877(95 % CI: 0.837-0.918) in the training set and 0.866(95 % CI: 0.774-0.957) in the external validation set. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. CONCLUSIONS: Nomograms integrating MRI-based radiomics and clinical-radiological characteristics could effectively predict Ki-67 PI in primary PCNSL.

Development and validation of a nomogram to predict poor efficacy of imatinib in the treatment of newly diagnosed chronic phase chronic myeloid leukemia patients.

Background: Imatinib is the most widely used tyrosine kinase inhibitor (TKI) in patients with newly diagnosed chronic-phase chronic myeloid leukemia(CML-CP). However, failure to achieve optimal response after imatinib administration, and subsequent switch to second-generation TKI therapy results in poor efficacy and induces drug resistance. In the present study, we developed and validated a nomogram to predict the efficacy of imatinib in the treatment of patients newly diagnosed with CML-CP in order to help clinicians truly select patients who need 2nd generation TKI during initial therapy and to supplement the risk score system. Methods: We retrospectively analyzed 156 patients newly diagnosed with CML-CP who met the inclusion criteria and were treated with imatinib at the Second Affiliated Hospital of Xi'an Jiao Tong University from January 2012 to June 2022. The patients were divided into a poor-response cohort (N = 60)and an optimal-response cohort (N = 43) based on whether they achieved major molecular remission (MMR) after 12 months of imatinib treatment. Using univariate and multivariate logistic regression analyses, we developed a chronic myeloid leukemia imatinib-poor treatment (CML-IMP) prognostic model using a nomogram considering characteristics like age, sex, HBG, splenic size, and ALP. The CML-IMP model was internally validated and compared with Sokal, Euro, EUTOS, and ELTS scores. Results: The area under the curve of the receiver operator characteristic curve (AUC)of 0.851 (95% CI 0.778-0.925) indicated satisfactory discriminatory ability of the nomogram. The calibration plot shows good consistency between the predicted and actual observations. The net reclassification index (NRI), continuous NRI value, and the integrated discrimination improvement (IDI) showed that the nomogram exhibited superior predictive performance compared to the Sokal, EUTOS, Euro, and ELTS scores (P < 0.05). In addition, the clinical decision curve analysis (DCA) showed that the nomogram was useful for clinical decision-making. In predicting treatment response, only Sokal and CML-IMP risk stratification can effectively predict the cumulative acquisition rates of CCyR, MMR, and DMR (P<0.05). Conclusion: We constructed a nomogram that can be effectively used to predict the efficacy of imatinib in patients with newly diagnosed CML-CP based on a single center, 10-year retrospective cohort study.

Coiled Carbon Nanotube Fibers Sheathed by a Reinforced Liquid Crystal Elastomer for Strong and Programmable Artificial Muscles.

Fibers of liquid crystal elastomers (LCEs) as promising artificial muscle show ultralarge and reversible contractile strokes. However, the contractile force is limited by the poor mechanical properties of the LCE fibers. Herein, we report high-strength LCE fibers by introducing a secondary network into the single-network LCE. The double-network LCE (DNLCE) shows considerable improvements in tensile strength (313.9%) and maximum actuation stress (342.8%) compared to pristine LCE. To facilitate the controllability and application, a coiled artificial muscle fiber consisting of DNLCE-coated carbon nanotube (CNT) fiber is prepared. When electrothermally driven, the artificial muscle fiber outputs a high actuation performance and programmable actuation. Furthermore, by knitting the artificial muscle fibers into origami structures, an intelligent gripper and crawling inchworm robot have been demonstrated. These demonstrations provide promising application scenarios for advanced intelligent systems in the future.

Glycoengineering in antigen-specific immunotherapies.

Advances in immunotherapy have revolutionized modern medical care paradigms. However, many patients respond poorly to the current FDA-approved treatment regimens that primarily target protein-based antigens or checkpoints. Current progress in developing therapeutic strategies that target disease-associated glycans has pinpointed a new class of glycoimmune checkpoints that function orthogonally to the established protein-immune checkpoints. Glycoengineering using chemical, enzymatic, and genetic methods is also increasingly recognized for its massive potential to improve biopharmaceuticals, such as tailoring therapies with antigen-targeting agents. Here, we review the recent development and applications of glycoengineering of antibodies and cells to suit therapeutic applications. We highlight living-cell glycoengineering strategies on cancer and immune cells for better therapeutic efficacy against specific antigens by leveraging the pre-existing immune machinery or instructing de novo creation of targeting agents. We also discuss glycoengineering strategies for studying basic immuno-oncology. Collectively, glycoengineering has a significant contribution to the design of antigen-specific immunotherapies.

Assessing causal relationships between gut microbiota and abortion: evidence from two sample Mendelian randomization analysis.

Background: While some studies have suggested a link between gut microbiota (GM) and abortion, the causal relationship remains unclear. Methods: To explore the causal relationship between GM and abortion, including spontaneous abortion (SA) and habitual abortion (HA), we performed a two-sample Mendelian randomization (MR) analysis. We used summary statistics data from MiBioGen and FinnGen for genome-wide association studies (GWAS), with GM data as the exposure variable and abortion data as the outcome variable. Results: In the absence of heterogeneity and horizontal pleiotropy, the inverse-variance weighted (IVW) method identified five genetically predicted GM genera linked to the risk of abortions. Lactococcus was negatively correlated with the risk of SA, whereas the Eubacterium fissicatena group was positively correlated with the risk of SA. Genetic predictions of Coprococcus3 and Odoribacter were linked to a reduced risk of HA, while the Eubacterium ruminantium group was associated with an increased risk of HA. Conclusion: Our study suggests a genetic causal relationship between specific GM and two types of abortions, improving our understanding of the pathological relationship between GM and abortion.