Immune-mediated diseases after vaccinations with AZD1222, BNT-162b2, &/or mRNA-1273: An observational investigation of 78 patients.

BACKGROUND: Immune-mediated diseases (IMDs) after nucleic acid-based vaccines have been sporadically reported since their introduction during the worldwide COVID-19 crisis. Confirming their cause-effect association remains challenging. We analysed the effects of AZD1222 (ChAdOx1 nCoV-19), BNT-162b2, and/or mRNA-1273 on the development &/or deterioration of IMDs in terms of the time of clinical onsets of IMDs after exposure to these vaccines. METHODS: We retrospectively reviewed 78 in-patients in Taipei Veterans General Hospital, who presented with IMDs within 120 days after receiving AZD1222, BNT-162b2, &/or mRNA-1273 vaccinations in Taiwan from May 2021 to April 2022. The duration from inoculation to development of IMD was analysed by two-tailed Kolmogorov-Smirnov (K-S) test for goodness of fit. RESULTS: The average time to new IMDs or flare-up of the diseases following vaccinations was 36 ± 26 days for all 91 events in these 78 patients. The onset time of IMDs after vaccinations was not haphazard as analysed by two-tailed K-S test for overall 91 events (40 new and 51 deteriorating episodes, p < 0.001). The IMDs presenting as non-connective tissue diseases (non-CTDs) have a shorter duration of incubation after vaccinations than those of CTDs (<14.7 days, 95 % confidence interval [CI], 3.0 to 26.4, p = 0.014). Furthermore, systemic vasculitis and type 2 inflammatory diseases were observed exclusively in those receiving AZD1222. CONCLUSION: AZD1222, BNT-162b2, or mRNA-1273 influence the activities of IMDs in ways yet to be explored. High index of suspicion to IMDs after nucleic acid-based vaccine inoculation against COVID-19 may be important for primary care physicians.

Modelling of Gyratory Crusher Liner Wear Using a Digital Wireless Sensor.

A gyratory crusher is a key mineral processing asset in a comminution circuit. Monitoring and predicting the crusher liner wear is essential to ensure the throughput and product quality are maintained during production. This study developed a digital sensor and a discrete element modelling (DEM)-coupled methodology to monitor and reconstruct the gyratory crusher concave liner wear pattern. The developed digital sensor was able to track and report the live thickness of the specific installation point on a concave liner during operation. A wear reconstruction model was then developed based on the wear intensity obtained using the DEM and digital sensor results. The wear reconstruction model predictive results were subsequently compared with site measurements after 95 days of operation. The results indicated that the wear reconstruction model showed good agreement with measured results in terms of wear zone distribution as well as quantitative wear rate prediction. The outcome of this study can be potentially utilised in the mineral processing industry for plant monitoring and automation.

Anti-VEGF Therapy Possibly Extends Survival in Patients With Colorectal Brain Metastasis by Protecting Patients From Neurologic Disability.

BACKGROUND: Colorectal brain metastases (CBMs) are rare with poor prognosis. There is still no standard systemic treatment for multiple or unresectable CBM. our study aimed to explore the impact of anti-VEGF therapy on overall survival, brain-specific disease control, and neurologic symptom burden in patients with CBM. METHODS: A total of 65 patients with CBM under treatment were retrospectively enrolled and divided into anti-VEGF based systemic therapy or non-anti-VEGF based therapy. A total of 25 patients who received at least 3 cycles of anti-VEGF agent and 40 patients without anti-VEGF therapy were analyzed by endpoints of overall survival (OS), progression-free survival (PFS), intracranial PFS (iPFS) and neurogenic event-free survival (nEFS). Gene expression in paired primary metastatic colorectal cancer (mCRC), liver, lung and brain metastasis from NCBI data was analyzed using top Gene Ontology (GO) and cBioPortal. RESULTS: Patients who treated with anti-VEGF therapy had significantly longer OS (19.5 vs. 5.5 months, P = .009), iPFS (14.6 vs. 4.1 months, P < .001) and nEFS (17.6 vs. 4.4 months, P < .001). Patients who received anti-VEGF therapy beyond any disease progression presented with superior OS (19.7 vs. 9.4 months, P = .039). Top GO and cBioPortal analysis revealed a stronger molecular function of angiogenesis in intracranial metastasis. CONCLUSIONS: Anti-VEGF based systemic therapy showed favorable efficacy that was reflected in longer overall survival, iPFS and NEFS in patients with CBM.

Highly selective adsorption and lattice process of cesium by cubic cyanide-based functional materials.

Cesium (Cs) is a byproduct of nuclear bombs, nuclear weapons testing, and nuclear fission in nuclear reactors. Cs can enter the human body through food or air and cause lasting damage. Highly efficient and selective removal of 137Cs from low-level radioactive effluents (LLREs), which contain many radionuclides and dissolved heavy metal species, is imperative for minimizing LLRE volume, and facilitating their final disposal. Prussian blue analogs (PBAs) have received much attention as materials for the removal of radioactive Cs because of their affinity for adsorbing Cs+. In this study, an inexpensive and readily available cyanide-based functional material (PBACu) exhibiting high efficiency and excellent selectivity toward Cs capture was designed through a facile low-temperature co-precipitation process. Nano-PBACu, crystallizing in the cubic space group (Fm-3m (225)), has an average pore size of 6.53 nm; consequently, PBACu can offer abundant atomic occupation sites for capturing and incorporating Cs. Here, the pseudo-second-order kinetic model and Langmuir model fitted well with the adsorption of Cs + on PBACu, with a maximum capture capacity of 95.75 mg/g within 5 min, confirming that PBACu could rapidly capture Cs ions. PBACu strongly and selectively interacted with Cs even in a simulant containing large Na+, NH4+, Ca2+, and Mg2+ ion concentrations in an aqueous solution. The process of Cs + adsorption by cyanide-based functional crystals was confirmed to involve the entry of Cs+ into cyanide-based functional crystals to replace K+ and finally achieve the lattice incorporation of Cs. The current results broaden the lattice theory of radionuclide Cs removal and provide a promising alternative for the immobilization of Cs from radioactive wastewater.

Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings.

The pathological identification of lymph node (LN) metastasis is demanding and tedious. Although convolutional neural networks (CNNs) possess considerable potential in improving the process, the ultrahigh-resolution of whole slide images hinders the development of a clinically applicable solution. We design an artificial-intelligence-assisted LN assessment workflow to facilitate the routine counting of metastatic LNs. Unlike previous patch-based approaches, our proposed method trains CNNs by using 5-gigapixel images, obviating the need for lesion-level annotations. Trained on 5907 LN images, our algorithm identifies metastatic LNs in gastric cancer with a slide-level area under the receiver operating characteristic curve (AUC) of 0.9936. Clinical experiments reveal that the workflow significantly improves the sensitivity of micrometastasis identification (81.94% to 95.83%, P < .001) and isolated tumor cells (67.95% to 96.15%, P < .001) in a significantly shorter review time (-31.5%, P < .001). Cross-site evaluation indicates that the algorithm is highly robust (AUC = 0.9829).

Synthesis of thickness-controllable polydopamine modified halloysite nanotubes (HNTs@PDA) for uranium (VI) removal.

Halloysite nanotubes (HNTs) are considered structurally promising adsorption materials, but their application is limited due to their poor native adsorption properties. Improving the adsorption capacity of HNTs for radioactive U(VI) is of great significance. By controlling the mass ratio of HNTs and dopamine (DA), composite adsorbents (HNTs@PDA) with different polydopamine (PDA) layer thicknesses were synthesized. Characterization of HNTs@PDA demonstrated that the original structure of the HNTs was maintained. Adsorption experiments verified that the adsorption capacity of HNTs@PDA for U(VI) was significantly improved. The effects of solution pH, temperature, and coexisting ions on the adsorption process were investigated. The removal efficiency was observed to be 75% after five repeated uses. The adsorption mechanism of U(VI) by HNTs@PDA can be explained by considering electrostatic interactions and the complexation of C-O, -NH- and C-N/CN in the PDA layer. This study provides some basic information for the application of HNTs for U(VI) removal.

Graphene oxide functionalized with nano hydroxyapatite for the efficient removal of U(VI) from aqueous solution.

Water contamination caused by radionuclides is a major environmental issue. Uranium (U) belongs to the actinide group of elements. Hexavalent uranium (U(VI)) is radioactively and chemically harmful and highly mobile in the environment and wastewater stream. Therefore, developing highly efficient materials for minimizing the environmental impact of U(VI) is essential. To achieve this goal, we successfully synthesized a novel material, namely graphene oxide (GO)/hydroxyapatite (HAP), by directly assembling GO and HAP through a facile hydrothermal method, which exhibits effective U(VI) removal and immobilization. The GO/HAP composite has an outstanding sorption capacity for U(VI) (i.e., 373.00 mg/g) within 5 min at a pH of 3.0. The parameters from thermodynamic analysis indicated that the GO/HAP composite absorbed U(VI) through a process of spontaneous and exothermic adsorption. XPS, XRD, and FT-IR results revealed that the composite's phosphate group was mainly responsible for U(VI) retention and incorporation. The GO/HAP composite's enhanced U(VI) sorption capacity is most likely ascribed to the synergistic effect after functionalizing with nano HAP. The current findings may greatly facilitate the creation of rational design strategies to develop highly efficient materials that can treat radioactive wastewater.

The influence of particle size and natural organic matter on U(VI) retention by natural sand: Parameterization and mechanism study.

Contamination caused by radionuclides such as uranium (U) has become an increasingly serious environmental problem. The unique and diverse features of uranyl ions (U(VI)) remarkably dominate their mobility and environmental impact on the ecosystem. Understanding the sorption behavior and fate of aqueous U(VI) ions on natural mineral(s) such as quartz sand (a typical type of crystalline silica (SiO2)) particles is essential for unraveling many environmental issues. In this work, the sorption of uranyl ions by various particle size quartz sands under different reaction conditions was thoroughly investigated. The quartz sand with an average particle size of 3.588 µm exhibited an excellent sorption performance for the removal of aqueous U(VI) ions at pH 5.0. The sorption rate increased as the dosage of sorbent increased. The sorption rate descends with the rise of the initial U(VI) concentration while its sorption amount is reversed. The elevation of temperature impeded the U(VI) sorption. Humic acid (a typical natural organic matter) showed significant impacts on U(VI) removal. Ions of Ca2+, CO32- and K+ remarkably inhibited the U(VI) sorption, while PO43- ions significantly promoted the U(VI) sorption. The pseudo second-order kinetic model could fit well with the experimental sorption data. The U(VI) sorption is mainly chemisorption and it is an exothermic process. After sorption, the surface of used quartz sand became much smooth and XPS signals of U(VI) were detected, evidencing the success of the removal of aqueous U(VI). The outcomes of this study highlighted both solution pH and natural organic matters played critical roles on U(VI) removal by sand particles. This study further enhances our comprehension from the molecular-scale process manipulating U(VI) sorption behavior at the mineral-aqueous interface.

Study on anti-hyperlipidemia mechanism of high frequency herb pairs by molecular docking method / 中国中药杂志

Traditional Chinese medicine (TCM) has definitely clinical effect in treating hyperlipidemia, but the action mechanism still need to be explored. Based on consulting Chinese Pharmacopoeia (2010), all the lipid-lowering Chinese patent medicines were analyzed by associated rules data mining method to explore high frequency herb pairs. The top three couplet medicines with high support degree were Puerariae Lobatae Radix-Crataegi Fructus, Salviae Miltiorrhizae Radix et Rhizoma-Crataegi Fructus, and Polygoni Multiflori Radix-Crataegi Fructus. The 20 main ingredients were selected from the herb pairs and docked with 3 key hyperlipidemia targets, namely 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA reductase), peroxisome proliferator activated receptor-α (PPAR-α ) and niemann-pick C1 like 1 (NPC1L1) to further discuss the molecular mechanism of the high frequency herb pairs, by using the docking program, LibDock. To construct evaluation rules for the ingredients of herb pairs, the root-mean-square deviation (RMSD) value between computed and initial complexes was first calculated to validate the fitness of LibDock models. Then, the key residues were also confirmed by analyzing the interactions of those 3 proteins and corresponding marketed drugs. The docking results showed that hyperin, puerarin, salvianolic acid A and polydatin can interact with two targets, and the other five compounds may be potent for at least one of the three targets. In this study, the multi-target effect of high frequency herb pairs for lipid-lowering was discussed on the molecular level, which can help further researching new multi-target anti-hyperlipidemia drug.

Construction of automatic elucidation platform for mechanism of traditional Chinese medicine / 中国中药杂志

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

Quality and quantity classification models of Fructus Amomi applying electronic nose with multiple mathematical statistics methods / 国际药学研究杂志

Objective Fructus Amomi(Sharen) is derived from the dry ripe fruit of Amomum villosum Lour., A.villosum Lour. var. xanthioides T.L. Wu et Senjen and A.longiligulate T.L.Wu, which is widely utilized for its clinic effects on digestive system. However, Fructus Amomi from different species and habitats, possessing different quality, is difficult to identify. In this study, we aim to develop a simple, rapid and reliable method for authentication of Fructus Amomi. Methods Twenty-five batches of samples of Fructus Amomi were collected and electronic nose was introduced into analyzing their odor with multiple mathematical statistics methods. Na?ve bayes network (NBN), radical basis function (RBF) and random forest (RF) were applied to establish different classifiers while BestFirst+CfsSubsetEval (BC) was used to screen the attributes for searching sensor array with higher contributions. Results Firstly, after attribute-screening via BC, the established discriminative models via NBN, RBF and RF could successfully identify genuine and non-genuine samples, presenting correct judging ratios of 78% and 84% through ten-fold cross validation and external test set validation, respectively. Besides, quantity predictive models were constructed as well. In case of content of bornyl acetate, one of the effective components in Fructus Amomi, values were higher than 3.5 mg/g and lower than 1.8 mg/g with sensor response of 0.04 and 0.03, respectively. Conclusion In this paper, quality discriminative model and quantity predictive model of Fructus Amomi were established via electronic nose and multiple mathematical statistics methods. It indicates that electronic nose could be a promising method for quality evaluation of Chinese material medica.

SIMPP analysis on learning interest of students / 中华医学教育探索杂志

Interest in learning can not only stimulate students' enthusiasm for learning, but also directly affect the quality of higher education. In this paper, the questionnaire of the related factors of college students' interest was designed to carry out micro-system engineering research. The factors as-sociated with college students' interest in learning and their complex relationships were investigated by using methods of systems science and systems engineering. The results shows that the students who can actively participate in after-school learning discussions , feel good in lectures and have clear learning objectives, are interested in learning. And at the same time, the teacher's influence and his active guidance in classroom teaching will raise students' interest in learning. This study provides a more comprehensive basis and clues to improve students' interest in learning and education reform.

SIMPP analysis on teacher's impact on students / 中华医学教育探索杂志

The influence extent of students from teachers is related to the teaching effect , which means whether it can successfully promote the study of students and reach the expected teach-ing goal during the teaching process. To have a good teaching effect, guided by the micro-system en-gineering of teaching reform, we used SIMPP to analyze the related factors of the influence of students extent from teachers during the teaching process in TCM colleges and universities. The result shows that the influence extent from teachers is related to not only teachers themselves but students and their self-condition and family backgrounds as well. Going further in researching these factors and the related behavior patterns of influence extent of students from teachers is helpful to making the teach-ing more effective and more targeted.

SIMPP analysis on learning purpose of students / 中华医学教育探索杂志

The clear learning objective is one of the important factors to determine the learning effect of college students. In order to analyze the factors affecting the formation process of college stu-dents' learning objectives, to explore the teaching mode that can be helpful for college students' clear learning objective, under the guidance of the concept of the reform of the teaching system, the SIMPP analysis of the students learning objective in the TCM colleges was carried out. Results showed that the related factors that affected student learning objectives included family factors, school principals and students' subjective factors. Teachers' observing students' learning status carefully, their understanding students' background, income and other social factors, mastering the degree of students' learning spe-cific goals and behavior model, and conducting the targeted and effective inventiveness are to help students clear learning objectives. The results provide the technology and method of operation for col-lege teachers to correctly guide different types of students to establish a clear learning objective.

SIMPP analysis on learning diligence level of students / 中华医学教育探索杂志

Academic diligence level can not only directly affect the academic performance of students, but also affect the individual's emotional and physical health. In this study, through a question-naire survey of university students, with the method of SIMPP and the concept of the micro system engi-neering in higher education teaching reform, the related factors of diligence and the college students' behavior mode with respect to diligence are systematically analyzed. Analysis shows that, students' diligence level is affected not only by inherent factors such as clear learning objectives, learning state and after-school learning time, but also by the school ethos, the influence factors of the curriculum and parents' re-quirements.

SIMPP analysis on self-recognized learning effectiveness of students / 中华医学教育探索杂志

College students' self cognition of the learning effectiveness influences their learning behavior greatly. Focusing on college students' self cognition of their learning effectiveness, and then standardizing their learning behavior is one of the important work of educators in colleges. Therefore this paper has designed the questionnaire of the influencing factors of learning effectiveness self cog-nition, used SIMPP analysis method to analyze it, and set up the relation model. The analysis shows that college students' self cognition of learning effectiveness is influenced not only by students' dili-gence level and the recognition degree of specialized subject, but also by the factors such as the attitude when you get the bad results. The result provides data basis and scientific basis for future practice and relevant research for educators in colleges.

SIMPP analysis on self-study ability of students / 中华医学教育探索杂志

According to the theory of microscopic system reform in higher education, a total of 927 college students of different majors from Beijing University of Chinese Medicine were investigated by using SIMPP method. It indicated that through promoting the study of self-prepared, learning state and learning effect, students can enhance their learning ability of the admission acceptance. From the perspective of teachers, the students' self-study ability can be fully mobilized using individual person-alized teaching method. Then, the initiative of university education in the teaching and learning can be improved. Ultimately, the efficiency of student learning can be improved.

SIMPP analysis on class attendance of students / 中华医学教育探索杂志

In recent years, lower and lower class attendance has plagued the quality of uni-versity teaching. To solve this problem, this study conducted a questionnaire survey in accordance with the concepts of the Education Reform microscopic systems engineering and the method of SIMPP. The results showed that factors affecting student classroom attendance included two aspects: the sub-jective and objective factors. Indicators related to the subjective factors were: the personal attitude when faced with failure exams, the personal learning interest and personal grasp of the main source of knowledge. Indicators related to the objective factors were: school and teachers. Also, this study gave some suggestions on how to improve students' classroom attendance to provide data basis and refer-ence for further study on class attendance.

SIMPP analysis on curriculum satisfaction of students / 中华医学教育探索杂志

The degree of satisfaction of the curriculum is related not only to the degree of the curriculum but also to the degree of the students' development. With the concept of teaching reform micro system engineering, using the SIMPP analysis of the degree of satisfaction of the curriculum, the relevant factors of the students are studied. The results show that, the learning state, learning objec-tives, and the education level of mother affect the students more easily on the curriculum satisfaction. Research shows, in the present curriculum condition, educators should guide the students to study hard, establish a clear and reasonable learning goal, give the students the introduction and analysis of the curriculum, can effectively improve the students on the curriculum satisfaction, enhance the enthusiasm of the study.