A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) algorithms on the conventional enhanced and CE-boost (contrast-enhancement-boost) images of indirect computed tomography venography (CTV) of lower extremities. MATERIALS AND METHODS: In this retrospective study, seventy patients who underwent CTV from June 2021 to October 2022 to assess deep vein thrombosis and varicose veins were included. Unenhanced and enhanced images were reconstructed for AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images were obtained using subtraction software. Objective and subjective image qualities were assessed, and radiation doses were recorded. RESULTS: The CT values of the inferior vena cava (IVC), femoral vein ( FV), and popliteal vein (PV) in the CE-boost images were approximately 1.3 (1.31-1.36) times higher than in those of the enhanced images. There were no significant differences in mean CT values of IVC, FV, and PV between AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images. Noise in AiCE, AiCE-boost images was significantly lower than in AIDR 3D and AIDR 3D-boost images ( P < 0.05). The SNR (signal-to-noise ratio), CNR (contrast-to-noise ratio), and subjective scores of AiCE-boost images were the highest among 4 groups, surpassing AiCE, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: In indirect CTV of the lower extremities images, DLR with the CE-boost technique could decrease the image noise and improve the CT values, SNR, CNR, and subjective image scores. AiCE-boost images received the highest subjective image quality score and were more readily accepted by radiologists.

Evolution of Digital Health and Exploration of Patented Technologies (2017-2021): Bibliometric Analysis.

BACKGROUND: The significant impact of digital health emerged prominently during the COVID-19 pandemic. Despite this, there is a paucity of bibliometric analyses focusing on technologies within the field of digital health patents. Patents offer a wealth of insights into technologies, commercial prospects, and competitive landscapes, often undisclosed in other publications. Given the rapid evolution of the digital health industry, safeguarding algorithms, software, and advanced surgical devices through patent systems is imperative. The patent system simultaneously acts as a valuable repository of technological knowledge, accessible to researchers. This accessibility facilitates the enhancement of existing technologies and the advancement of medical equipment, ultimately contributing to public health improvement and meeting public demands. OBJECTIVE: The primary objective of this study is to gain a more profound understanding of technology hotspots and development trends within the field of digital health. METHODS: Using a bibliometric analysis methodology, we assessed the global technological output reflected in patents on digital health published between 2017 and 2021. Using Citespace5.1R8 and Excel 2016, we conducted bibliometric visualization and comparative analyses of key metrics, including national contributions, institutional affiliations, inventor profiles, and technology topics. RESULTS: A total of 15,763 digital health patents were identified as published between 2017 and 2021. The China National Intellectual Property Administration secured the top position with 7253 published patents, whereas Koninklijke Philips emerged as the leading institution with 329 patents. Notably, Assaf Govari emerged as the most prolific inventor. Technology hot spots encompassed categories such as "Medical Equipment and Information Systems," "Image Analysis," and "Electrical Diagnosis," classified by Derwent Manual Code. A patent related to the technique of receiving and transmitting data through microchips garnered the highest citation, attributed to the patentee Covidien LP. CONCLUSIONS: The trajectory of digital health patents has been growing since 2017, primarily propelled by China, the United States, and Japan. Applications in health interventions and enhancements in surgical devices represent the predominant scenarios for digital health technology. Algorithms emerged as the pivotal technologies protected by patents, whereas techniques related to data transfer, storage, and exchange in the digital health domain are anticipated to be focal points in forthcoming basic research.

An antiferromagnetic spin phase change memory.

The electrical outputs of single-layer antiferromagnetic memory devices relying on the anisotropic magnetoresistance effect are typically rather small at room temperature. Here we report a new type of antiferromagnetic memory based on the spin phase change in a Mn-Ir binary intermetallic thin film at a composition within the phase boundary between its collinear and noncollinear phases. Via a small piezoelectric strain, the spin structure of this composition-boundary metal is reversibly interconverted, leading to a large nonvolatile room-temperature resistance modulation that is two orders of magnitude greater than the anisotropic magnetoresistance effect for a metal, mimicking the well-established phase change memory from a quantum spin degree of freedom. In addition, this antiferromagnetic spin phase change memory exhibits remarkable time and temperature stabilities, and is robust in a magnetic field high up to 60 T.

Contribution of Cd passivating functional bacterium H27 to tobacco growth under Cd stress.

The cadmium (Cd) embedded in tobacco not only affects yield and quality but also harms human health. Microbial remediation has attracted widespread attention due to its low cost and minimal risk of secondary pollution. Therefore, researching microbes capable of inhibiting crop absorption of heavy metals or removing heavy metals from the environment has significant practical implications. This study screened a strain named H27 with a Cd immobilization efficiency of up to 76.60%. Static cultivation experiments showed that immobilization of Cd by H27 is achieved through intracellular absorption, hydroxyl, carboxyl, and phosphate group reactions on the cell wall. The bacterium can also secrete extracellular substances to adsorb Cd and increase the environmental pH, reducing the bioavailability of Cd. H27 reduced the accumulation of Cd in the stems of hydroponically grown tobacco by 55.23% and decreased the expression of three Cd transport genes, HAM2, IRT1, and NRAMP1, in the roots. Additionally, H27 increased the mineralization rate of organic matter, increased the content of humic acid in the soil, promoted the formation of smaller soil particles, and enhanced the adsorption and fixation of Cd by soil components while simultaneously raising the pH of rhizosphere and non-rhizosphere soils in tobacco growth environments. Both hydroponic and potted experiments showed that H27 alleviated the inhibitory effect of Cd on tobacco growth, significantly reducing Cd accumulation in various parts of tobacco and lowering the transfer coefficient of Cd within the tobacco plant. This study aims to effectively reduce the Cd content in tobacco using microbes, mitigate the harm of heavy metals in cigarettes to human health, and provide theoretical and practical basis for the application of microbial techniques to control heavy metal absorption in tobacco.

Inducing ferroptosis by traditional medicines: a novel approach to reverse chemoresistance in lung cancer.

Lung cancer is the leading cause of global cancer-related deaths. Platinum-based chemotherapy is the first-line treatment for the most common type of lung cancer, i.e., non-small-cell lung cancer (NSCLC), but its therapeutic efficiency is limited by chemotherapeutic resistance. Therefore, it is vital to develop effective therapeutic modalities that bypass the common molecular mechanisms associated with chemotherapeutic resistance. Ferroptosis is a form of non-apoptotic regulated cell death characterized by iron-dependent lipid peroxidation (LPO). Ferroptosis is crucial for the proper therapeutic efficacy of lung cancer-associated chemotherapies. If targeted as a novel therapeutic mechanism, ferroptosis modulators present new opportunities for increasing the therapeutic efficacy of lung cancer chemotherapy. Emerging studies have revealed that the pharmacological induction of ferroptosis using natural compounds boosts the efficacy of chemotherapy in lung cancer or drug-resistant cancer. In this review, we first discuss chemotherapeutic resistance (or chemoresistance) in lung cancer and introduce the core mechanisms behind ferroptosis. Then, we comprehensively summarize the small-molecule compounds sourced from traditional medicines that may boost the anti-tumor activity of current chemotherapeutic agents and overcome chemotherapeutic resistance in NSCLC. Cumulatively, we suggest that traditional medicines with ferroptosis-related anticancer activity could serve as a starting point to overcome chemotherapeutic resistance in NSCLC by inducing ferroptosis, highlighting new potential therapeutic regimens used to overcome chemoresistance in NSCLC.

Qualifying P-glycoprotein in drug-resistant ovarian cancer cells: a dual-mode aptamer probe approach.

Drug resistance presents a significant obstacle in treating human ovarian cancer. The development of effective methods for detecting drug-resistant cancer cells is pivotal for tailoring personalized therapies and prognostic assessments. In this investigation, we introduce a dual-mode detection technique employing a fluorogenic aptamer probe for the qualification of P-glycoprotein (P-gp) in drug-resistant ovarian cancer cells. The probe, initially in an "off" state due to the proximity of a quencher to the fluorophore, exhibits increased fluorescence intensity upon binding with the target. The fluorescence enhancement shows a linear correlation with both the concentration of P-gp and the presence of P-gp in drug-resistant ovarian cancer cells. This correlation is quantifiable, with detection limits of 1.56 nM and 110 cells per mL. In an alternate mode, the optimized fluorophores, attached to the aptamer, form larger complexes upon binding to the target protein, which diminishes the rotation speed, thereby augmenting fluorescence polarization. The alteration in fluorescence polarization enables the quantitative analysis of P-gp in the cells, ranging from 100 to 1500 cells per milliliter, with a detection limit of 40 cells per mL. Gene expression analyses, protein expression studies, and immunofluorescence imaging further validated the reliability of our aptamer-based probe for its specificity towards P-gp in drug-resistant cancer cells. Our findings underscore that the dual-mode detection approach promises to enhance the diagnosis and treatment of multidrug-resistant ovarian cancer.

Pharmacologically inducing anoikis offers novel therapeutic opportunities in hepatocellular carcinoma.

Tumor metastasis occurs in hepatocellular carcinoma (HCC), leading to tumor progression and therapeutic failure. Anoikis is a matrix detachment-induced apoptosis, also known as detachment-induced cell death, and mechanistically prevents tumor cells from escaping their native extracellular matrix to metastasize to new organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat HCC. Several natural and synthetic products induce anoikis in HCC cells and in vivo models. Here, we first briefly summarize the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in HCC metastasis. Then we discuss the therapeutic potential of pharmacological induction of anoikis as a potential treatment against HCC. Finally, we discuss the key limitations of this therapeutic paradigm and propose possible strategies to overcome them. Cumulatively this review suggests that the pharmacological induction of anoikis can be used a promising therapeutic modality against HCC.

Application of machine learning in the analysis of multiparametric MRI data for the differentiation of treatment responses in breast cancer: retrospective study.

OBJECTIVE: The objective of this study is to develop and validate a multiparametric MRI model employing machine learning to predict the effectiveness of treatment and the stage of breast cancer. METHODS: The study encompassed 400 female patients diagnosed with breast cancer, with 200 individuals allocated to both the control and experimental groups, undergoing examinations in Shenzhen, China, during the period 2017-2023. This study pertains to retrospective research. Multiparametric MRI was employed to extract data concerning tumor size, blood flow, and metabolism. RESULTS: The model achieved high accuracy, predicting treatment outcomes with an accuracy of 92%, sensitivity of 88%, and specificity of 95%. The model effectively classified breast cancer stages: stage I, 38% ( P = 0.027); stage II, 72% ( P = 0.014); stage III, 50% ( P = 0.032); and stage IV, 45% ( P = 0.041). CONCLUSIONS: The developed model, utilizing multiparametric MRI and machine learning, exhibits high accuracy in predicting the effectiveness of treatment and breast cancer staging. These findings affirm the model's potential to enhance treatment strategies and personalize approaches for patients diagnosed with breast cancer. Our study presents an innovative approach to the diagnosis and treatment of breast cancer, integrating MRI data with machine learning algorithms. We demonstrate that the developed model exhibits high accuracy in predicting treatment efficacy and differentiating cancer stages. This underscores the importance of utilizing MRI and machine learning algorithms to enhance the diagnosis and individualization of treatment for this disease.

Analysis of vasoactive and oxidative stress indicators for evaluating the efficacy of continuous positive airway pressure, and relation of vasoactive and oxidative stress indicators and cardiac function in obstructive sleep Apnea Syndrome patients.

Background: Obstructive Sleep Apnea Syndrome (OSAS) is a breathing disorder during sleep. The work was to evaluate the relationship between vasoactive and oxidative stress indicators and cardiac function in Obstructive Sleep Apnea Syndrome (OSAS) patients. Methods: OSAS patients (n=120) were treated with CPAP from May 2021 to June 2022. According to the clinical efficacy, the patients were divided into effective and ineffective groups. Vasoactive factors and oxidative stress indices were compared between the two groups to evaluate their clinical efficacy. The changes in cardiac function indices in the two groups were tested, and the correlation between vasoactive factors and oxidative stress indices and cardiac function was analysed. Results: The effective rate of CPAP was 63.33% (76/120). Ang II, ET-1, and MDA levels were lower, and the SOD level was higher in the effective group than in the ineffective group after treatment. The AUC of the four indicators was all greater than 0.75. LPWT and IVST values of the effective group were lower than the ineffective group. A positive correlation was identified between the levels of Ang II, ET-1, and MDA with LPWT, between levels of ET-1 and MDA with IVST, and a negative correlation between SOD with LPWT and IVST. Conclusions: CPAP treatment can effectively improve vascular activity and reduce the oxidative stress response in OSAS patients, and the combined detection of vasoactive factors and oxidative stress indicators is valuable for evaluating the efficacy of CPAP and is related to the cardiac function of patients.

Enhanced remediation of chlorpyrifos-contaminated soil by immobilized strain Bacillus H27.

Chlorpyrifos is a pesticide widely used in agricultural production with a relatively long residual half-life in soil. Addressing the problem of residual chlorpyrifos is of universal concern. In this study, rice hull biochar was used as an immobilized carrier to prepare the immobilized strain H27 for the remediation of chlorpyrifos-contamination soil. Soil microorganisms after remediation were investigated by ecotoxicological methods. The immobilized strain H27 had the highest removal rate of chlorpyrifos when 10% bacterial solution was added to the liquid medium containing 0.075-0.109 mm diameter biochar cultured for 22 hr. This study on the removal of chlorpyrifos by immobilized strain H27 showed that the initial concentration of chlorpyrifos in solution was 25 mg/L, and the removal rate reached 97.4% after 7 days of culture. In the soil, the removal rate of the immobilized bacteria group increased throughout the experiment, which was significantly higher than that of the free bacteria and biochar treatment groups. The Biolog-ECO test, T-RFLP and RT-RCR were used to study the effects of the soil microbial community and nitrogen cycling functional genes during chlorpyrifos degradation. It was found that ICP group had the highest diversity index among the four treatment groups. The microflora of segment containing 114 bp was the dominant bacterial community, and the dominant microflora of the immobilized bacteria group was more evenly distributed. The influence of each treatment group on ammonia-oxidizing bacteria (AOB) was greater than on ammonia-oxidizing archaea (AOA). This study offers a sound scientific basis for the practical application of immobilized bacteria to reduce residual soil pesticides.

Immune protection of three serine protease inhibitors vaccine in mice against Rhipicephalus sanguineus.

Bioactive molecules in tick saliva are considered to be key to successful feeding and further the transmission of tick-borne pathogens. Problems such as pathogen transmission and animal weight loss result in tick infestation can cause tremendous economic losses to the livestock industry. Therefore, the development of a universal tick vaccine is urgently needed. In this paper, three serine protease inhibitor (serpin) proteins RMS-3, L7LRK7 and L7LTU1 were analyzed with bioinformatics methods. Subsequently the proteins were expressed and purified, and inoculated into Kunming mice for immune protection analysis. The amino acid sequence similarities between RMS-3, L7LRK7 and L7LTU1 were up to 90% in Rhipicephalus sanguineus. The recombinant RMS-3 + L7LRK7 + L7LTU1 showed anticoagulant reaction function and could inhibit the activity of CD4+ lymphocytes, when inoculated into Kunming mice. Additionally, After the immunized mice were challenged with Rhipicephalus sanguineus, the percentage of larvae and nymphs that were fully engorged dropped to 40.87% (P < 0.05) and 87.68% (P > 0.05) in the RmS-3 + L7LRK7 immune group, 49.57% (P < 0.01) and 52.06% (P < 0.05) in the RmS-3 + L7LTU1 group, and 45.22% (P < 0.05) and 60.28% (P < 0.05) in the RmS-3 + L7LRK7 + L7LTU1 immune group, in comparison with the control group. These data indicate that RmS-3 + L7LRK7 + L7LTU1 has good immune protection and has the potential to be developed into a vaccine against the larvae and nymphs of R. sanguineus.

Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant.

Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors. Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination. Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

The dual HCK/BTK inhibitor KIN-8194 impairs growth and integrin-mediated adhesion of BTKi-resistant mantle cell lymphoma.

Although Bruton's tyrosine kinase (BTK) inhibitors (BTKi) have significantly improved patient prognosis, mantle cell lymphoma (MCL) is still considered incurable due to primary and acquired resistance. We have recently shown that aberrant expression of the Src-family tyrosine kinase hematopoietic cell kinase (HCK) in MCL correlates with poor prognosis, and that genetic HCK perturbation impairs growth and integrin-mediated adhesion of MCL cells. Here, we show that KIN-8194, a dual inhibitor of BTK and HCK with in vivo activity against Myd88-L265P-driven diffuse large B-cell lymphoma and Waldenström Macroglobulinemia, has a potent growth inhibitory effect in MCL cell lines and primary MCL cells, irrespective of their sensitivity to BTKi (ibrutinib and acalabrutinib). In BTKi-resistant cells this is mediated by inhibition of HCK, which results in repression of AKT-S6 signaling. In addition, KIN-8194 inhibits integrin-mediated adhesion of BTKi-sensitive and insensitive MCL cells to fibronectin and stromal cells in an HCK-dependent manner. Finally, we show that MCL cells with acquired BTKi resistance retain their sensitivity to KIN-8194. Taken together, our data demonstrate that KIN-8194 inhibits growth and integrin-mediated adhesion of BTKi-sensitive MCL cells, as well as MCL cells with primary or acquired BTKi resistance. This renders KIN-8194 a promising novel treatment for MCL patients.