Photoinduced Radical Approach for Desulfurative Alkylation of Cysteine Derivatives to Make Unnatural Amino Acids.

Unnatural amino acids (UAAs) are highly valuable molecules in organic synthesis, pharmaceutical sciences, and material science. Herein, we present a photocatalytic radical approach for desulfurative alkylation of cysteine derivatives with arenethiol as the hydrogen atom transfer catalyst for making UAAs and peptides. The formate salt, acting as the hydrogen atom donor, in situ generates the highly reductive CO2 radical anion species, which is the key to unlocking the C-S bond cleavage process with a simple benzoyl protecting group. No photocatalyst is required for the radical initiation and propagation, which makes such a visible-light-induced process mild, efficient, and sustainable.

A feasibility study on utilizing machine learning technology to reduce the costs of gastric cancer screening in Taizhou, China.

Aim: To optimize gastric cancer screening score and reduce screening costs using machine learning models. Methods: This study included 228,634 patients from the Taizhou Gastric Cancer Screening Program. We used three machine learning models to optimize Li's gastric cancer screening score: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), and Deep Learning (DL). The performance of the binary classification models was evaluated using the area under the curve (AUC) and area under the precision-recall curve (AUCPR). Results: In the binary classification model used to distinguish low-risk and moderate- to high-risk patients, the AUC in the GBM, DRF, and DL full models were 0.9994, 0.9982, and 0.9974, respectively, and the AUCPR was 0.9982, 0.9949, and 0.9918, respectively. Excluding Helicobacter pylori IgG antibody, pepsinogen I, and pepsinogen II, the AUC in the GBM, DRF, and DL models were 0.9932, 0.9879, and 0.9900, respectively, and the AUCPR was 0.9835, 0.9716, and 0.9752, respectively. Remodel after removing variables IgG, PGI, PGII, and G-17, the AUC in GBM, DRF, and DL was 0.8524, 0.8482, 0.8477, and AUCPR was 0.6068, 0.6008, and 0.5890, respectively. When constructing a tri-classification model, we discovered that none of the three machine learning models could effectively distinguish between patients at intermediate and high risk for gastric cancer (F1 scores in the GBM model for the low, medium and high risk: 0.9750, 0.9193, 0.5334, respectively; F1 scores in the DRF model for low, medium, and high risks: 0.9888, 0.9479, 0.6694, respectively; F1 scores in the DL model for low, medium, and high risks: 0.9812, 0.9216, 0.6394, respectively). Conclusion: We concluded that gastric cancer screening indicators could be optimized when distinguishing low-risk and moderate to high-risk populations, and detecting gastrin-17 alone can achieve a good discriminative effect, thus saving huge expenditures.

Guidance of development, validation, and evaluation of algorithms for populating health status in observational studies of routinely collected data (DEVELOP-RCD).

BACKGROUND: In recent years, there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data (RCD). These studies rely on algorithms to identify specific health conditions (e.g. diabetes or sepsis) for statistical analyses. However, there has been substantial variation in the algorithm development and validation, leading to frequently suboptimal performance and posing a significant threat to the validity of study findings. Unfortunately, these issues are often overlooked. METHODS: We systematically developed guidance for the development, validation, and evaluation of algorithms designed to identify health status (DEVELOP-RCD). Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development, validation, and evaluation. Subsequently, we conducted an empirical study on an algorithm for identifying sepsis. Based on these findings, we formulated specific workflow and recommendations for algorithm development, validation, and evaluation within the guidance. Finally, the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it. RESULTS: A standardized workflow for algorithm development, validation, and evaluation was established. Guided by specific health status considerations, the workflow comprises four integrated steps: assessing an existing algorithm's suitability for the target health status; developing a new algorithm using recommended methods; validating the algorithm using prescribed performance measures; and evaluating the impact of the algorithm on study results. Additionally, 13 good practice recommendations were formulated with detailed explanations. Furthermore, a practical study on sepsis identification was included to demonstrate the application of this guidance. CONCLUSIONS: The establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD. This guidance has the potential to enhance the credibility of findings from observational studies involving RCD.

Altitude and prognosis after PCI: A propensity score-matched analysis.

Background: The impact of altitude on the prognosis of patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI) deserves further discussion and research. Methods: We conducted a post hoc analysis of a prospective observational study involving 5453 patients post-PCI, divided into medium-altitude and low-altitude groups. To control for confounding factors, propensity score matching was employed to pair patients with similar baseline characteristics between the two groups. The impact of altitude factors on patients' prognosis post-PCI was examined through endpoint events over a 2-year follow-up period. Results: During the 2-year follow-up, patients at medium altitude exhibited a lower risk of MACE (including cardiovascular mortality, myocardial infarction, revascularization, and stroke) compared to those at low altitude (1196 versus 1196 patients [medium-altitude versus low-altitude, respectively]; hazard ratio [HR], 0.781 [95 % CI, 0.629-0.969]; P = 0.025) during 2-year follow-up. Even after excluding stroke, a significant difference in heart-related adverse events (HRAE) persisted between the two groups (HR, 0.794; 95 % CI, 0.636-0.991; P = 0.042). The incidences of individual MACE components were not significantly different between the two groups. Conclusions: Patients post-PCI residing at medium altitude exhibited a lower risk of 2-year MACE compared to those at low altitude. Further research is necessary to provide more robust evidence.

Effects of Hypertension on Alzheimer's Disease: Updates in Pathophysiological and Neuroimaging Findings.

Alzheimer's disease (AD) is recognized as the leading cause of dementia, imposing a significant economic toll on society. Despite the emergence of novel therapeutic approaches for AD, their efficacy and safety mandates further validation through rigorous clinical trials. In this context, hypertension (HTN) has garnered considerable attention as an amendable risk factor for AD. Research indicates that hypertension during midlife is associated with an elevated risk of AD in later years, influencing both the onset and progression of the disease. Nevertheless, the relationship between AD and hypertension in the later stages of life remains a subject of debate. Moreover, the consequences of blood pressure reduction on cognitive function, along with the optimal pharmacological interventions and therapeutic thresholds for hypertension, have emerged as pivotal areas of inquiry. This review synthesizes findings on epidemiology, neuroimaging, and biomarkers, and the effects of antihypertensive medications to elucidate the link between hypertension and cognitive performance. We particularly investigate how hypertension and AD are related by plasma sulfide dysregulation, offering possible indicators for future diagnosis and therapy.

PROTAC technology: From drug development to probe technology for target deconvolution.

Drug development remains a critical focus within the global pharmaceutical industry. To date, more than 80 % of disease targets are considered difficult to target. The emergence of PROTAC technology has, to some extent, alleviated this challenge. Since introduction, PROTAC technology has evolved through the peptide E3 ligase ligand phase and the small molecule E3 ligase ligand phase. Currently, multiple PROTAC molecules are in the clinical research phase, showing promising potential for addressing drug resistance, disease recurrence, and intractable targets. Target deconvolution is a crucial step in the drug discovery and development process. Due to the exceptional targeting ability and specificity of PROTAC, it is widely used and promoted as an innovative technology for discovering new drug targets, leading to significant breakthroughs. The use of PROTAC probe requires only a catalytic dose and weak interaction with the target protein to achieve target degradation. Thus, it offers substantial advantages over traditional probes, particularly in identifying new targets that are low-abundance or difficult to target. This review provides a comprehensive overview of the advancements made by PROTAC technology in drug development and drug target discovery, while also systematically reviewing the workflow of PROTAC probe. With the ongoing development of PROTAC technology, PROTAC probe is poised to become a key research area in future drug target deconvolution.

Cardiovascular health metrics and diabetic nephropathy: a nationally representative cross-sectional study.

BACKGROUND: The pathogenesis of diabetic nephropathy is well-documented to be multifactorial. However, research available on the association between cardiovascular health and diabetic nephropathy is limited. Thus, this study aimed to investigate these potential associations and provide guidance for disease prevention. METHODS: We applied Life's Essential 8 (LE8) identified by the American Heart Association, which integrates multiple health behaviors and health factors to measure cardiovascular health. This study covered 4207 adults with diabetes from the National Health and Nutrition Examination Survey spanning 2007-2018. Weighted regression models assessed the estimated effect of LE8 score on the prevalence of diabetic nephropathy as well as their corresponding clinical indicators. Weighted restricted cubic spline models discussed the possible nonlinear dose-response relationships further. Subgroup analyses clarified the effects of other covariates on correlations. RESULTS: After adjusting for all covariates, participants with moderate or high cardiovascular health showed a decreased prevalence of diabetic nephropathy (odds ratio [OR]:0.52; 95% confidence interval [CI]:0.42-0.63), and also a decrease in the urinary albumin-to-creatinine ratio [UACR] (ß: - 0.83; 95% CI:- 1.00 to - 0.65). The prevalence of diabetic nephropathy and the level of UACR tended to decrease linearly as the total LE8 score increased (P for nonlinear > 0.05). Subgroup analyses showed that the effects of increased overall LE8 score and the specific cardiovascular health construct varied across age and obesity strata. CONCLUSION: Elevated overall LE8 score was significantly associated with a lower prevalence of diabetic nephropathy in U.S. adults, and the effects of the specific cardiovascular health construct on diabetic nephropathy and their corresponding clinical indicators varied. In all, maintaining good cardiovascular health by refining LE8 metrics may help reduce the adverse effects.

Retraction of "Effect of C-phycocyanin on HDAC3 and miRNA-335 in Alzheimer's disease".

[This retracts the article DOI: 10.1515/tnsci-2020-0101.].

Effectiveness of simulation-based clinical research curriculum for undergraduate medical students - a pre-post intervention study with external control.

BACKGROUND: Simulation is widely utilized in medical education. Exploring the effectiveness of high-fidelity simulation of clinical research within medical education may inform its integration into clinical research training curricula, finally cultivating physician-scientist development. METHODS: Standard teaching scripts for both clinical trial and cross-sectional study simulation were designed. We recruited undergraduates majoring in clinical medicine at 3th grade into a pre-post intervention study. Additionally, a cross-sectional survey randomly selected medical undergraduates at 4th or 5th grade, medical students in master and doctor degree as external controls. Self-assessment scores of knowledge and practice were collected using a 5-point Likert scale. Changes in scores were tested by Wilcoxon signed-rank test and group comparisons were conducted by Dunn's tests with multiple corrections. Multivariable quantile regressions were used to explore factors influencing the changes from baseline. RESULTS: Seventy-eight undergraduates involved the clinical trial simulation and reported improvement of 1.60 (95% CI, 1.48, 1.80, P < 0.001) in knowledge and 1.82 (95% CI, 1.64, 2.00, P < 0.001) in practice score. 83 undergraduates involved in the observational study simulation and reported improvement of 0.96 (95% CI, 0.79, 1.18, P < 0.001) in knowledge and 1.00 (95% CI, 0.79, 1.21, P < 0.001) in practice. All post-intervention scores were significantly higher than those of the three external control groups, P < 0.001. Higher agreement on the importance of clinical research were correlated with greater improvements in scores. Undergraduates in pre-post study showed high confidence in doing a future clinical research. CONCLUSION: Our study provides evidence supporting the integration of simulation into clinical research curriculum for medical students. The importance of clinical research can be emphasized during training to enhance learning effect.

Effectiveness of WeChat-assisted preoperative education to reduce perioperative anxiety in breast cancer patients: a prospective randomized controlled study protocol.

BACKGROUND: Breast cancer is the most prevalent cancer among women globally, and surgical procedures continue to be the primary treatment. However, over 50% of patients experience preoperative anxiety due to the unknown and fear associated with surgery. Although drug therapy is commonly used to address this anxiety, its side effects have led to a heated debate regarding its effectiveness. Consequently, non-pharmacological therapies, such as preoperative education, have emerged as an alternative approach to alleviate anxiety. WeChat, a widely popular social media platform, offers a public platform that can potentially be utilized for effective preoperative education. This study aims to evaluate the use of WeChat public platform as a tool for preoperative education in patients undergoing breast surgery. METHODS: This is a prospective, randomized, and controlled trial will involve 392 adult women scheduled for breast cancer resection. Participants will be randomly assigned to either the WeChat education group or the regular group. In addition to regular preoperative visits, the WeChat education group will also watch science videos through the WeChat public platform. The regular group will only receive education from ward nurses during preoperative visits. The primary outcome measure will be the incidence of preoperative anxiety, defined by scores of the State Anxiety Inventory (SAI) exceeding 40 points. Secondary outcome measures include the incidence of severe anxiety (SAI > 44) on the day before surgery, incidence of anxiety 72 h after surgery, incidence of severe anxiety 72 h after surgery, NRS scores for pain at rest and during activity 24, 48, and 72 h after surgery, incidence of nausea and vomiting within 24 h after surgery, subjective sleep score at 1 week postoperatively, quality of life QoR-15 scores at 1 and 3 months postoperatively, incidence of chronic pain at 3 months postoperatively, bowel function recovery, length of hospital stay, and hospitalization expenses. DISCUSSION: This is the first clinical trial to investigate the use of WeChat public platform for delivering preoperative education on perioperative anxiety in breast cancer patients. By utilizing the renowned WeChat public platform, our study aims to improve patient outcomes by providing video education that explains the disease, surgery, and anesthesia in a more accessible manner, thereby reducing the incidence of perioperative anxiety. If our hypothesis is confirmed, this non-pharmacological approach can be universally acknowledged as a cost-effective and practical method in clinical care. Its application can also be extended to other medical fields beyond breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05291494. Registered on 29 December 2021.

Instant duodenal decompression after endoscopic retrograde cholangiopancreatography can effectively reduce the incidence of post-ERCP pancreatitis and hyperamylasemia.

Background: Post-ERCP pancreatitis (PEP) is significantly influenced by the reflux of duodenal fluid. While gastrointestinal decompression represents a fundamental approach in acute pancreatitis management, the effectiveness of immediate duodenal decompression following ERCP to prevent PEP remains uncertain. This study aimed to investigate the impact of immediate duodenal decompression after ERCP on reducing the incidence of hyperamylasemia and PEP. Methods: This retrospective study encompassed patients with native papilla who underwent therapeutic ERCP for choledocholithiasis at the Department of Gastroenterology, Chun'an Branch of Zhejiang Provincial People's Hospital (Zhejiang, China) between January 2020 and June 2023. Based on the immediate placement of a duodenal decompression tube post-ERCP, patients were categorized into two groups: the duodenal decompression group and the conventional procedure group. Primary outcomes included the incidence of PEP and hyperamylasemia. Results: A total of 195 patients were enrolled (94 in the duodenal decompression group and 101 in the conventional procedure group). Baseline clinical and procedural characteristics exhibited no significant differences between the two groups. PEP occurred in 2 patients (2.1%) in the duodenal decompression group, in contrast to 11 patients (10.9%) in the conventional procedure group (Risk difference [RD] 8.8%; 95% confidence interval [CI] 1.7%-16.5%, P = 0.014). Hyperamylasemia was observed in 8 patients (8.5%) in the duodenal decompression group, compared to 20 patients (19.8%) in the conventional procedure group (RD 11.3%; 95% CI 1.4%-21.0%; P = 0.025). Patients with PEP in both groups showed improvement after receiving active treatment. No severe cases of PEP occurred in either group, and no serious adverse events related to duodenal catheter decompression were reported. Conclusion: Immediate duodenal decompression following ERCP demonstrates an effective reduction in the incidence of hyperamylasemia and PEP.

Walking forward or on hold: Could the ChatGPT be applied for seeking health information in neurosurgical settings?

Self-management is important for patients suffering from cerebrovascular events after neurosurgical procedures. An increasing number of artificial intelligence (AI)-assisted tools have been used in postoperative health management. ChatGPT is a new trend dialog-based chatbot that could be used as a supplemental tool for seeking health information. Responses from ChatGPT version 3.5 and 4.0 toward 13 questions raised by experienced neurosurgeons were evaluated in this exploratory study for their consistency and appropriateness blindly by the other three neurosurgeons. The readability of response text was investigated quantitively by word count and the Gunning Fog and Flesch-Kincaid indices. Results showed that the chatbot could provide relatively stable output between the two versions on consistency and appropriateness (χ² = 0.348). As for readability, there was a higher demand for readers to comprehend the output text in the 4.0 version (more counts of words; lower Flesch-Kincaid reading ease score; and higher Flesch-Kincaid grade level). In general, the capacity of ChatGPT to deliver effective health information is still under debate.

Marine-Derived Bisindoles for Potent Selective Cancer Drug Discovery and Development.

Marine-derived bisindoles exhibit structural diversity and exert anti-cancer influence through multiple mechanisms. Comprehensive research has shown that the development success rate of drugs derived from marine natural products is four times higher than that of other natural derivatives. Currently, there are 20 marine-derived drugs used in clinical practice, with 11 of them demonstrating anti-tumor effects. This article provides a thorough review of recent advancements in anti-tumor exploration involving 167 natural marine bisindole products and their derivatives. Not only has enzastaurin entered clinical practice, but there is also a successfully marketed marine-derived bisindole compound called midostaurin that is used for the treatment of acute myeloid leukemia. In summary, investigations into the biological activity and clinical progress of marine-derived bisindoles have revealed their remarkable selectivity, minimal toxicity, and efficacy against various cancer cells. Consequently, they exhibit immense potential in the field of anti-tumor drug development, especially in the field of anti-tumor drug resistance. In the future, these compounds may serve as promising leads in the discovery and development of novel cancer therapeutics.

MiR-142-3p Regulates ILC1s by Targeting HMGB1 via the NF-κB Pathway in a Mouse Model of Early Pregnancy Loss.

OBJECTIVE: Innate lymphoid cells (ILCs) are a class of newly discovered immunocytes. Group 1 ILCs (ILC1s) are identified in the decidua of humans and mice. High mobility group box 1 (HMGB1) is predicted to be one of the target genes of miR-142-3p, which is closely related to pregnancy-related diseases. Furthermore, miR-142-3p and HMGB1 are involved in regulating the NF-κB signaling pathway. This study aimed to examine the regulatory effect of miR-142-3p on ILC1s and the underlying mechanism involving HMGB1 and the NF-κB signaling pathway. METHODS: Mouse models of normal pregnancy and abortion were constructed, and the alterations of ILC1s, miR-142-3p, ILC1 transcription factor (T-bet), and pro-inflammatory cytokines of ILC1s (TNF-α, IFN-γ and IL-2) were detected in mice from different groups. The targeting regulation of HMGB1 by miR-142-3p in ILC1s, and the expression of HMGB1 in normal pregnant mice and abortive mice were investigated. In addition, the regulatory effects of miR-142-3p and HMGB1 on ILC1s were detected in vitro by CCK-8, Annexin-V/PI, ELISA, and RT-PCR, respectively. Furthermore, changes of the NF-κB signaling pathway in ILC1s were examined in the different groups. For the in vivo studies, miR-142-3p-Agomir was injected in the uterus of abortive mice to evaluate the abortion rate and alterations of ILC1s at the maternal-fetal interface, and further detect the expression of HMGB1, pro-inflammatory cytokines, and the NF-κB signaling pathway. RESULTS: The number of ILC1s was significantly increased, the level of HMGB1 was significantly upregulated, and that of miR-142-3p was considerably downregulated in the abortive mice as compared with the normal pregnant mice (all P<0.05). In addition, miR-142-3p was found to drastically inhibit the activation of the NF-κB signaling pathway (P<0.05). The number of ILC1s and the levels of pro-inflammatory cytokines were significantly downregulated and the activation of the NF-κB signaling pathway was inhibited in the miR-142-3p Agomir group (all P<0.05). CONCLUSION: miR-142-3p can regulate ILC1s by targeting HMGB1 via the NF-κB signaling pathway, and attenuate the inflammation at the maternal-fetal interface in abortive mice.

Predicion of initial recurrence risk in papillary thyroid carcinoma based on the multi-parametric analysis from dual-layer detector spectral CT / 中华放射学杂志

Objective:To investigate the value of multi-parametric analysis based on dual-layer detector spectral CT (DLCT) in predicting the initial recurrence risk for papillary thyroid carcinoma (PTC).Methods:From November 2021 to October 2022, 102 PTC patients confirmed by pathology were retrospectively collected at the First Affiliated Hospital of Nanjing Medical University in this cross-sectional study. There were 25 males and 77 females, with an age of (42±13) years old. The initial recurrence risk assessment for PTC patients was categorized into a low-risk group (75 cases) and an intermediate-high-risk group (27 cases). Clinical data, including age, gender, body mass index, history of nodular goiter, history of Hashimoto thyroiditis, and preoperative thyroid function, were collected. Tumor morphological features, including size, location, shape, aspect ratio, the degree of thyroid capsule contact, calcification, and cystic change, were evaluated. Quantitative DLCT parameters, including iodine concentration (IC), standardized iodine concentration (NIC), effective atomic number (Z eff), standardized effective atomic number (NZ eff), electronic density (ED), CT values under different energy levels (40-200 keV, 30 keV intervals) and slope of energy spectrum curve (λ HU) both in the arterial and venous phase were measured. The differences in clinical, morphological features, and spectral CT quantitative parameters between the two groups were compared using independent sample ttest, Mann-Whitney U test, or χ2 test. Multivariate logistic regression analyses were used to construct three models based on clinical and morphological features, quantitative DLCT parameters and their combination, respectively. The receiver operating characteristic curve was used to evaluate the predictive performance of these models for the initial recurrence risk of PTC patients, and the area under the curve (AUC) was compared using the DeLong test. Results:Significant differences were found in gender, lesion long diameter, lesion short diameter and calcification between the low-risk group and intermediate-high-risk groups ( P<0.05). The arterial phase IC, arterial phase Z eff, arterial phase λ HU, arterial phase CT 40 keV, venous phase NIC and venous phase NZ eff in intermediate-high-risk group were significantly lower than those in the low-risk group ( P<0.05). The logistic regression analysis revealed that the clinical model included gender ( OR=2.895, 95% CI 1.047-8.002, P=0.040) and lesion long diameter ( OR=1.142, 95% CI 1.042-1.251, P=0.004), with an AUC of 0.720, sensitivity of 63.0%, and specificity of 78.7% in predicting the initial recurrence risk of PTC patients. The DLCT quantitative parameter model included arterial phase IC ( OR=0.580, 95% CI 0.370-0.908, P=0.017), venous phase NIC ( OR=0.077, 95% CI 0.011-0.536, P=0.010), and venous phase NZ eff ( OR=0.002, 95% CI 0.001-0.103, P=0.009), with an AUC of 0.774, sensitivity of 71.9%, and specificity of 70.0%. The AUC of the combined model was 0.857, with a sensitivity of 74.1%, and specificity of 88.0%, outperforming the clinical model ( Z=2.92, P=0.004) and the DLCT quantitative parameter model ( Z=2.07, P=0.046). Conclusion:Multi-parametric analysis based on DLCT can help predict the initial recurrence risk for PTC, and combining it with clinical and morphological features, the predictive accuracy can be improved.

The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review.

Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), has been explored to promote the CPG implementation. This study has reviewed the main domains where computer technology and AI has been applied to CPG implementation. PubMed, Embase, Web of science, the Cochrane Library, China National Knowledge Infrastructure database, WanFang DATA, VIP database, and China Biology Medicine disc database were searched from inception to December 2021. Studies involving the utilization of computer technology and AI to promote the implementation of CPGs were eligible for review. A total of 10429 published articles were identified, 117 met the inclusion criteria. 21 (17.9%) focused on the utilization of AI techniques to classify or extract the relative content of CPGs, such as recommendation sentence, condition-action sentences. 47 (40.2%) focused on the utilization of computer technology to represent guideline knowledge to make it understandable by computer. 15 (12.8%) focused on the utilization of AI techniques to verify the relative content of CPGs, such as conciliation of multiple single-disease guidelines for comorbid patients. 34 (29.1%) focused on the utilization of AI techniques to integrate guideline knowledge into different resources, such as clinical decision support systems. We conclude that the application of computer technology and AI to CPG implementation mainly concentrated on the guideline content classification and extraction, guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration. The AI methods used for guideline content classification and extraction were pattern-based algorithm and machine learning. In guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration, computer techniques of knowledge representation were the most used.

Research on the development methodology for clinical practice guidelines for organic integration of traditional Chinese and Western medicine.

Integrated traditional Chinese medicine (TCM) and Western medicine (WM) is a new medical science grounded in the knowledge bases of both TCM and WM, which then forms a unique modern medical system in China. Integrated TCM and WM has a long history in China, and has made important achievements in the process of clinical diagnosis and treatment. However, the methodological defects in currently published clinical practice guidelines limit its development. The organic integration of TCM and WM is a deeper integration of TCM and WM. To realize the progression of "integration" to "organic integration", a targeted and standardized guideline development methodology is needed. Therefore, the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.

Enhanced sequestration of CO2 from simulated electrolytic aluminum flue gas by modified red mud.

The aluminum industry is facing severe economic and environmental problems due to increasing carbon emissions and growing stockpiles of red mud (RM). RM is a strongly alkaline, high-emission solid waste from the alumina industry with potential for CO2 sequestration. However, the effectiveness of RM carbon sequestration is poor, and the mechanism behind it is not well understood. In this study, the effect of microwave and tube furnace activation of RM on CO2 sequestration in alumina was first investigated at different temperatures. The result showed that the CO2 sequestration capacity of unmodified RM (URM) was only 14.35 mg/g at ambient temperature and pressure, and the CO2 sequestration capacity could be increased to 52.89 mg/g after high-temperature activation and modification. Besides, high-temperature activation and modification will effectively improve the carbon sequestration capacity of RM. The carbonized RM was characterized by FT-IR, SEM, XRD, laser particle size, TG-DSC, and pH measurements. In addition, the mechanism of RM capturing CO2 was also proposed, which shows that CO2 was finally sequestered in the RM as CaCO3. The change in particle size distribution and the mineral phase in the RM indicated that high-temperature activation modification positively affects the application of RM to the sequestration of CO2. This study can provide a promising technology for the low-carbon and green development of the aluminum industry, as well as achieving the waste treatment and utilization objective.