High abundance of solar wind-derived water in lunar soils from the middle latitude.

Remote sensing data revealed that the presence of water (OH/H2O) on the Moon is latitude-dependent and probably time-of-day variation, suggesting a solar wind (SW)-originated water with a high degassing loss rate on the lunar surface. However, it is unknown whether or not the SW-derived water in lunar soil grains can be preserved beneath the surface. We report ion microprobe analyses of hydrogen abundances, and deuterium/hydrogen ratios of the lunar soil grains returned by the Chang'e-5 mission from a higher latitude than previous missions. Most of the grain rims (topmost ~100 nm) show high abundances of hydrogen (1,116 to 2,516 ppm) with extremely low δD values (-908 to -992‰), implying nearly exclusively a SW origin. The hydrogen-content depth distribution in the grain rims is phase-dependent, either bell-shaped for glass or monotonic decrease for mineral grains. This reveals the dynamic equilibrium between implantation and outgassing of SW-hydrogen in soil grains on the lunar surface. Heating experiments on a subset of the grains further demonstrate that the SW-implanted hydrogen could be preserved after burial. By comparing with the Apollo data, both observations and simulations provide constraints on the governing role of temperature (latitude) on hydrogen implantation/migration in lunar soils. We predict an even higher abundance of hydrogen in the grain rims in the lunar polar regions (average ~9,500 ppm), which corresponds to an estimation of the bulk water content of ~560 ppm in the polar soils assuming the same grain size distribution as Apollo soils, consistent with the orbit remote sensing result.

PNA-Functionalized, Silica Nanowires-Filled Glass Microtube for Ultrasensitive and Label-Free Detection of miRNA-21.

MicroRNAs (miRNAs) are endogenous and noncoding single-stranded RNA molecules with a length of approximately 18-25 nucleotides, which play an undeniable role in early cancer screening. Therefore, it is very important to develop an ultrasensitive and highly specific method for detecting miRNAs. Here, we present a bottom-up assembly approach for modifying glass microtubes with silica nanowires (SiNWs) and develop a label-free sensing platform for miRNA-21 detection. The three-dimensional (3D) networks formed by SiNWs make them abundant and highly accessible sites for binding with peptide nucleic acid (PNA). As a receptor, PNA has no phosphate groups and exhibits an overall electrically neutral state, resulting in a relatively small repulsion between PNA and RNA, which can improve the hybridization efficiency. The SiNWs-filled glass microtube (SiNWs@GMT) sensor enables ultrasensitive, label-free detection of miRNA-21 with a detection limit as low as 1 aM at a detection range of 1 aM-100 nM. Noteworthy, the sensor can still detect miRNA-21 in the range of 102-108 fM in complex solutions containing 1000-fold homologous interference of miRNAs. The high anti-interference performance of the sensor enables it to specifically recognize target miRNA-21 in the presence of other miRNAs and distinguish 1-, 3-mismatch nucleotide sequences. Significantly, the sensor platform is able to detect miRNA-21 in the lysate of breast cancer cell lines (e.g., MCF-7 cells and MDA-MB-231 cells), indicating that it has good potential in the screening of early breast cancers.

Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.

BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage rates of human papillomavirus (HPV) vaccines and routine screening are low in most developing countries and even some developed countries. This study aimed to explore the benefit of an artificial intelligence-assisted cytology (AI) system in a screening program for a cervical cancer high-risk population in China. METHODS: A total of 1231 liquid-based cytology (LBC) slides from women who underwent colposcopy at the Chinese PLA General Hospital from 2018 to 2020 were collected. All women had received a histological diagnosis based on the results of colposcopy and biopsy. The sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), false-positive rate (FPR), false-negative rate (FNR), overall accuracy (OA), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and Youden index (YI) of the AI, LBC, HPV, LBC + HPV, AI + LBC, AI + HPV and HPV Seq LBC screening strategies at low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL) thresholds were calculated to assess their effectiveness. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic values of the different screening strategies. RESULTS: The Se and Sp of the primary AI-alone strategy at the LSIL and HSIL thresholds were superior to those of the LBC + HPV cotesting strategy. Among the screening strategies, the YIs of the AI strategy at the LSIL + threshold and HSIL + threshold were the highest. At the HSIL + threshold, the AI strategy achieved the best result, with an AUC value of 0.621 (95% CI, 0.587-0.654), whereas HPV testing achieved the worst result, with an AUC value of 0.521 (95% CI, 0.484-0.559). Similarly, at the LSIL + threshold, the LBC-based strategy achieved the best result, with an AUC of 0.637 (95% CI, 0.606-0.668), whereas HPV testing achieved the worst result, with an AUC of 0.524 (95% CI, 0.491-0.557). Moreover, the AUCs of the AI and LBC strategies at this threshold were similar (0.631 and 0.637, respectively). CONCLUSIONS: These results confirmed that AI-only screening was the most authoritative method for diagnosing HSILs and LSILs, improving the accuracy of colposcopy diagnosis, and was more beneficial for patients than traditional LBC + HPV cotesting.

Comparison of multiple linear regression and machine learning methods in predicting cognitive function in older Chinese type 2 diabetes patients.

INTRODUCTION: The prevalence of type 2 diabetes (T2D) has increased dramatically in recent decades, and there are increasing indications that dementia is related to T2D. Previous attempts to analyze such relationships principally relied on traditional multiple linear regression (MLR). However, recently developed machine learning methods (Mach-L) outperform MLR in capturing non-linear relationships. The present study applied four different Mach-L methods to analyze the relationships between risk factors and cognitive function in older T2D patients, seeking to compare the accuracy between MLR and Mach-L in predicting cognitive function and to rank the importance of risks factors for impaired cognitive function in T2D. METHODS: We recruited older T2D between 60-95 years old without other major comorbidities. Demographic factors and biochemistry data were used as independent variables and cognitive function assessment (CFA) was conducted using the Montreal Cognitive Assessment as an independent variable. In addition to traditional MLR, we applied random forest (RF), stochastic gradient boosting (SGB), Naïve Byer's classifier (NB) and eXtreme gradient boosting (XGBoost). RESULTS: Totally, the test cohort consisted of 197 T2D (98 men and 99 women). Results showed that all ML methods outperformed MLR, with symmetric mean absolute percentage errors for MLR, RF, SGB, NB and XGBoost respectively of 0.61, 0.599, 0.606, 0.599 and 0.2139. Education level, age, frailty score, fasting plasma glucose and body mass index were identified as key factors in descending order of importance. CONCLUSION: In conclusion, our study demonstrated that RF, SGB, NB and XGBoost are more accurate than MLR for predicting CFA score, and identify education level, age, frailty score, fasting plasma glucose, body fat and body mass index as important risk factors in an older Chinese T2D cohort.

STEAP3 Affects Ovarian Cancer Progression by Regulating Ferroptosis through the p53/SLC7A11 Pathway.

Ovarian cancer (OC) is a common malignant cancer in women with a low overall survival rate, and ferroptosis may be a potential new strategy for treatment. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a gene closely related to ferroptosis, yet the role of STEAP3 in OC has not yet been thoroughly investigated. Using biological information analysis, we first found that STEAP3 was highly expressed in OC, which was significantly associated with poor prognosis of patients and was an independent prognostic factor. Through cloning, scratch, and transwell experiments, we subsequently found that knockdown of STEAP3 significantly reduced the proliferation and migration ability of OC cells. Furthermore, we found that knockdown of STEAP3 induced ferroptosis in OC cells by detecting ferroptosis indicators. Mechanistically, we also found that knockdown of STEAP3 induced ferroptosis through the p53/SLC7A11 signaling pathway. Through tumorigenic experiments in nude mice, we finally verified that the knockdown of STEAP3 could inhibit tumor growth in vivo by promoting ferroptosis through the p53 pathway. Overall, our study identified a novel therapeutic target for ferroptosis in OC and explored its specific mechanism of action.

Serratus Anterior Fascia for Immediate Implant-Based Breast Reconstruction: A Case Series of 65 Patients With Breast Cancer.

OBJECTIVE: After immediate implant-based breast reconstruction (IIBR) after mastectomy, implant exposure or capsular contracture can occur. This study aimed to evaluate IIBR using serratus anterior fascia in patients with breast cancer. METHODS: This retrospective case series study enrolled patients with breast cancer underwent IIBR using the serratus anterior fascia after mastectomy in the Department of Breast Surgery of Fujian Cancer Hospital between January 2021 and December 2022. RESULTS: Sixty-five cases with breast cancer underwent IIBR using serratus anterior fascia were enrolled, with a median age of 39 years (range, 24-57 years) and body mass index of 21.32 kg/m 2 (range, 19-25 kg/m 2 ). The aesthetic outcomes of the reconstructed breasts showed good in 53 cases (81.6%), moderate in 11 cases (16.9%), and poor in 1 case (1.5%) due to offset position. Two cases showed poor wound healing, which improved after repeat suturing and 5 cases developed partial ischemic necrosis of the nipple, which scabbed and healed spontaneously. CONCLUSIONS: Implant-based breast reconstruction using serratus anterior fascia may provide good aesthetic outcomes with few complications.

Based ATP-gating mechanism for detection of alkaline phosphatase in single-glass micropipettes functionalized by three-dimensional DNA network.

The construction of gating system in artificial channels is a cutting-edge research direction in understanding biological process and application sensing. Here, by mimicking the gating system, we report a device that easily synthesized single-glass micropipettes functionalized by three-dimensional (3D) DNA network, which triggers the gating mechanism for the detection of biomolecules. Based on this strategy, the gating mechanism shows that single-glass micropipette assembled 3D DNA network is in the "OFF" state, and after collapsing in the presence of ATP, they are in the "ON" state, at which point they exhibit asymmetric response times. In the "ON" process of the gating mechanism, the ascorbic acid phosphate (AAP) can be encapsulated by a 3D DNA network and released in the presence of adenosine triphosphate (ATP), which initiates a catalyzed cascade reaction under the influence of alkaline phosphatase (ALP). Ultimately, the detection of ALP can be responded to form the fluorescence signal generated by terephthalic acid that has captured hydroxyl radicals, which has a detection range of 0-250 mU/mL and a limit of detection of 50 mU/mL. This work provides a brand-new way and application direction for research of gating mechanism.

Integrated metabolic and epigenetic mechanisms in cardiomyocyte proliferation.

Heart disease continues to be the leading cause of mortality worldwide, primarily attributed to the restricted regenerative potential of the adult human heart following injury. In contrast to their adult counterparts, many neonatal mammals can spontaneously regenerate their myocardium in the first few days of life via extensive proliferation of the pre-existing cardiomyocytes. Reasons for the decline in regenerative capacity during postnatal development, and how to control it, remain largely unexplored. Accumulated evidence suggests that the preservation of regenerative potential depends on a conducive metabolic state in the embryonic and neonatal heart. Along with the postnatal increase in oxygenation and workload, the mammalian heart undergoes a metabolic transition, shifting its primary metabolic substrate from glucose to fatty acids shortly after birth for energy advantage. This metabolic switch causes cardiomyocyte cell-cycle arrest, which is widely regarded as a key mechanism for the loss of regenerative capacity. Beyond energy provision, emerging studies have suggested a link between this intracellular metabolism dynamics and postnatal epigenetic remodeling of the mammalian heart that reshapes the expression of many genes important for cardiomyocyte proliferation and cardiac regeneration, since many epigenetic enzymes utilize kinds of metabolites as obligate cofactors or substrates. This review summarizes the current state of knowledge of metabolism and metabolite-mediated epigenetic modifications in cardiomyocyte proliferation, with a particular focus on highlighting the potential therapeutic targets that hold promise to treat human heart failure via metabolic and epigenetic regulations.

Establishment of a Prognostic Nomogram for Cancer-Specific Survival in Patients With Base-of-Tongue Squamous Cell Carcinoma: A Retrospective Study Based on the SEER Database.

BACKGROUND: The aim of this retrospective study was to construct and clinically apply a nomogram for cancer-specific survival (CSS) in patients diagnosed with base-of-tongue squamous cell carcinoma (BOTSCC) to predict their survival prognosis. METHODS: We collected 8448 patients diagnosed with BOTSCC during 2004-2015 from the Surveillance, Epidemiology, and End Results (SEER) database and divided 30% and 70% of them into validation and training cohorts, respectively. We utilized backward stepwise regression in the Cox model to select variables. Predictive variables were subsequently identified from the variables selected above by using multivariate Cox regression. The new survival model was compared with the American Joint Committee on Cancer (AJCC) prognosis model using the following variables: calibration curve, time-dependent area under the receiver operating characteristic curve (AUC), concordance index (C-index), integrated discrimination improvement (IDI), decision-curve analysis (DCA), and net reclassification improvement (NRI). RESULTS: A nomogram was established for predicting the CSS probability in patients with BOTSCC. Factors including sex, race, age at diagnosis, marital status, radiotherapy status, chemotherapy status, TNM AJCC stage, surgery status, tumor size, and months from diagnosis to treatment were selected through multivariate Cox regression as independent predictors of CSS. Calibration plots indicated that the model we established had satisfactory calibration ability. The AUC, C-index, IDI, DCA, and NRI results illustrated that the nomogram performed explicit prognoses more accurately than did the AJCC system alone. CONCLUSION: We identified the relevant factors affecting the survival of BOTSCC patients and analyzed the data on patients suffering from BOTSCC in the SEER database. These factors were used to construct a new nomogram to give clinical staff a more-visual prediction model for the 3-, 5-, and 8-year probabilities of CSS for patients newly diagnosed with BOTSCC, thereby aiding clinical decision making.

Ethical and legal considerations in social media research for health technology assessment: conclusions from a scoping review.

OBJECTIVES: The objective was to identify and describe the published guidance and current academic discourse of ethical issues and standards related to the use of Social Media Research for generating patient insights for the use by health technology assessment (HTA) or health policy decisions. METHODS: A scoping review of the literature was conducted in PubMed and Embase and identified 935 potential references published between January 2017 and June 2021. After title and abstract screening by three reviewers, 40 publications were included, the relevant information was extracted and data were collected in a mind map, which was then used to structure the output of the review. RESULTS: Social Media Research may reveal new insights of relevance to HTA or health policies into patient needs, patient experiences, or patient behaviors. However, the research approaches, methods, data use, interpretation, and communication may expose those who post the data in social media channels to risks and potential harms relating to privacy, anonymity/confidentiality, authenticity, context, and rapidly changing technologies. CONCLUSIONS: An actively engaged approach to ensuring ethical innocuousness is recommended that carefully follows best practices throughout planning, conduct, and communication of the research. Throughout the process and as a follow-up, there should be a discourse with the ethical experts to maximally protect the current and future users of social media, to support their trust in the research, and to advance the knowledge in parallel to the advancement of the media themselves, the technologies, and the research tools.

Using social media research in health technology assessment: stakeholder perspectives and scoping review.

OBJECTIVES: The aim of this initiative was to examine collaboratively, in a multi-stakeholder team (health technology assessment (HTA) practitioners with patient involvement expertise, health technology industry, patient advocates, health policy experts, patient engagement experts), whether evidence generated through social media research (SMR) fills current information gaps relating to insights on specific aspects of patient experiences, preferences, or patient needs and delivers additional value to HTA. METHODS: The framing of the project was done in a co-creative, deliberative multi-stakeholder process. Challenge and refinement happened through discussions with 25 independent stakeholders from HTA bodies, industry, academia, and patient advocacy. For critical themes identified during the framing phase, scoping literature reviews were performed including the state of methods and examples for the use of SMR in HTA. RESULTS: The framing and stakeholder discussions specified a set of expectations and requirements, and the scoping reviews revealed the current state of methods and usage of SMR in health-policy decision making. CONCLUSIONS: The project concluded that SMR can contribute new, relevant evidence to HTA. It is however recommended to evolve the science through defining best practices when planning, conducting, and using SMR and to conduct multi-stakeholder pilot SMR projects to address questions relevant to current HTAs and to validate and improve the proposed practices.

Two new halogenated metabolites from the red alga Laurencia sp.

Two new halogenated metabolites, laurenhalogens A (1) and B (2), along with four known ones (3-6), were isolated from the red alga Laurencia sp. The structures of 1 and 2 were determined by the means of UV, IR, MS, NMR and X-ray diffraction analysis. In addition, the antibacterial activities of 1-6 were also evaluated.

Mixed organic and inorganic amendments enhance soil microbial interactions and environmental stress resistance of Tibetan barley on plateau farmland.

Sufficient crop yield while maintaining soil health and sustainable agricultural development is a global objective, serving a special challenge to certain climate-sensitive plateau areas. Despite conducting trails on a variety of soil amendments in plateau areas, systematic research is lacking regarding the influences of organic and inorganic amendments on soil quality, particularly soil microbiome. To our knowledge, this was the first study that compared the effects of inorganic, organic, and mixed amendments on typical plateau crop hulless barley (Hordeum vulgare L. var. Nudum, also known as "Qingke" in Chinese) over the course of tillering, jointing, and ripening. Microbial communities and their responses to amendments, soil properties and Tibetan hulless barley growth, yield were investigated. Results indicated that mixed organic and inorganic amendments promoted the abundance of rhizosphere microorganisms, enhancing the rhizosphere root-microbes interactions and resistance to pathogenic bacteria and environmental stresses. The rhizosphere abundant and significantly different genera Arthrobacter, Rhodanobacter, Sphingomona, Nocardioides and so on demonstrated their unique adaptation to the plateau environment based on the results of metagenomic binning. The abundance of 23 genes about plant growth and environmental adaptations in the mixed amendment soil were significantly higher than other treatments. Findings from this study suggest that the mixed organic/inorganic amendments can help establish a healthy microbiome and increase soil quality while achieving sufficient hulless barley yields in Tibet and presumably other similar geographic areas of high altitude.

Determination of Multiple Neurotransmitters through LC-MS/MS to Confirm the Therapeutic Effects of Althaea rosea Flower on TTX-Intoxicated Rats.

Tetrodotoxin (TTX) inhibits neurotransmission in animals, and there is no specific antidote. In clinical practice in China, Althaea rosea (A. rosea flower) extract has been used to treat TTX poisoning. In this work, the efficacy of the ethyl acetate fraction extract of A. rosea flower in treating TTX poisoning in rats was investigated. A high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine nine neurotransmitters in rat brain tissue, including γ-aminobutyric acid (GABA), dopamine (DA), 5-hydroxytryptamine (5-HT), noradrenaline (NE), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxyindole-3-acetic acid (5-HIAA), epinephrine (E), and tyramine (Tyn). The detoxifying effect of A. rosea flower was verified by comparing the changes in neurotransmitters' content in brain tissue before and after poisoning in rats. The assay was performed in multiple reaction monitoring mode. The quantification method was performed by plotting an internal-standard working curve with good linearity (R2 > 0.9941) and sensitivity. Analyte recoveries were 94.04-107.53% (RSD < 4.21%). Results indicated that the levels of 5-HT, DA, E, and NE in the brains of TTX-intoxicated rats decreased, whereas the levels of GABA, Tyn, and 5-HIAA showed an opposite trend, and HVA and DOPAC were not detected. The levels of all seven neurotransmitters returned to normal after the gavage administration of ethyl acetate extract of A. rosea flower to prove that the ethyl acetate extract of A. rosea flower had a therapeutic effect on TTX poisoning. The work provided new ideas for studies on TTX detoxification.

Synthesis, biological evaluation, pharmacokinetic studies and molecular docking of 4'''-acetyl-delicaflavone as antitumor agents.

Structural modification of natural products is the effective option to improve their pharmacological effects and drug properties. DLF is a lead compound of antitumor drug, which is a broad-spectrum, low toxic and high-efficient component isolated from Selaginella doederleinii Hieron by our research group. Here, we report the structural modification method of this component, and find that the acetylated product of C4'''- OH (C4'''-acetyl-delicaflavone, 4'''ADLF) has better inhibitory effect on the selected cancer cell lines, including, lung, liver, colon and cervical cancer cell lines. Since the increased water solubility of 4'''ADLF may lead to higher absorption rate and activity, we evaluate the pharmacodynamics in vitro and in vivo, and the pharmacokinetic of 4'''ADLF. It shows that 4'''ADLF inhibit the proliferation and induce cycle arrest in tumor cells, and had better anticancer activity and bioavailability than DLF.

Influence of ambulatory blood pressure-related indicators within 24 h on in-hospital death in sepsis patients.

Background: Sepsis is a serious public health problem worldwide. Blood pressure is one of the indicators that is closely monitored in intensive-care units, and it reflects complex interactions between the internal cardiovascular control mechanism and the external environment. We aimed to determine the impact of indicators related to the ambulatory blood pressure on the prognosis of sepsis patients. Methods: This retrospective study was based on the Medical Information Mart for Intensive Care IV database. Relevant information about sepsis patients was extracted according to specific inclusion and exclusion criteria. Examined parameters included the average blood pressure, blood pressure variability (BPV), and circadian rhythm, and the study outcome was in-hospital death. We investigated the effects of these indicators on the risk of in-hospital death among sepsis patients using Cox proportional-hazards models, restricted cubic splines analysis, and subgroup analysis. Results: This study enrolled 10,316 sepsis patients, among whom 2,117 died during hospitalization. All parameters except the nighttime variation coefficient of the diastolic blood pressure (DBP) were associated with in-hospital death of sepsis patients. All parameters except for fluctuations in DBP exhibited nonlinear correlations with the outcome. The subgroup analysis revealed that some of the examined parameters were associated with in-hospital death only in certain subgroups. Conclusion: Indicators related to the ambulatory blood pressure within 24 h are related to the prognosis of sepsis patients. When treating sepsis, in addition to blood pressure, attention should also be paid to BPV and the circadian rhythm in order to improve the prognosis and the survival rate.

Deep transfer learning to quantify pleural effusion severity in chest X-rays.

PURPOSE: The detection of pleural effusion in chest radiography is crucial for doctors to make timely treatment decisions for patients with chronic obstructive pulmonary disease. We used the MIMIC-CXR database to develop a deep learning model to quantify pleural effusion severity in chest radiographs. METHODS: The Medical Information Mart for Intensive Care Chest X-ray (MIMIC-CXR) dataset was divided into patients 'with' or 'without' chronic obstructive pulmonary disease (COPD). The label of pleural effusion severity was obtained from the extracted COPD radiology reports and classified into four categories: no effusion, small effusion, moderate effusion, and large effusion. A total of 200 datasets were randomly sampled to manually check each item and determine whether the tags are correct. A professional doctor re-tagged these items as a verification cohort without knowing their previous tags. The learning models include eight common network structures including Resnet, DenseNet, and GoogleNET. Three data processing methods (no sampling, downsampling, and upsampling) and two loss algorithms (focal loss and cross-entropy loss) were used for unbalanced data. The Neural Network Intelligence tool was applied to train the model. Receiver operating characteristic curves, Area under the curve, and confusion matrix were employed to evaluate the model results. Grad-CAM was used for model interpretation. RESULTS: Among the 8533 patients, 15,620 chest X-rays with clearly marked pleural effusion severity were obtained (no effusion, 5685; small effusion, 4877; moderate effusion, 3657; and large effusion, 1401). The error rate of the manual check label was 6.5%, and the error rate of the doctor's relabeling was 11.0%. The highest accuracy rate of the optimized model was 73.07. The micro-average AUCs of the testing and validation cohorts was 0.89 and 0.90, respectively, and their macro-average AUCs were 0.86 and 0.89, respectively. The AUC of the distinguishing results of each class and the other three classes were 0.95 and 0.94, 0.76 and 0.83, 0.85 and 0.83, and 0.87 and 0.93. CONCLUSION: The deep transfer learning model can grade the severity of pleural effusion.

Disruptive technologies in health care disenchanted: a systematic review of concepts and examples.

OBJECTIVES: To clarify the concept of disruptive technologies in health care, provide examples and consider implications of potentially disruptive technologies for health technology assessment (HTA). METHODS: We conducted a systematic review of conceptual and empirical papers on healthcare technologies that are described as "disruptive." We searched MEDLINE and Embase from 2013 to April 2019 (updated in December 2021). Data extraction was done in duplicate by pairs of reviewers utilizing a data extraction form. A qualitative data analysis was undertaken based on an analytic framework for analysis of the concept and examples. Key arguments and a number of potential predictors of disruptive technologies were derived and implications for HTA organizations were discussed. RESULTS: Of 4,107 records, 28 were included in the review. Most of the papers included conceptual discussions and business models for disruptive technologies; only few papers presented empirical evidence. The majority of the evidence is related to the US healthcare system. Key arguments for describing a technology as disruptive include improvement of outcomes for patients, improved access to health care, reduction of costs and better affordability, shift in responsibilities between providers, and change in the organization of health care. A number of possible predictors for disruption were identified to distinguish these from "sustaining" innovations. CONCLUSIONS: Since truly disruptive technologies could radically change technology uptake and may modify provision of care patterns or treatment paths, they require a thorough evaluation of the consequences of using these technologies, including economic and organizational impact assessment and careful monitoring.

Study on Quality Control of Compound Anoectochilus roxburghii (Wall.) Lindl. by Liquid Chromatography-Tandem Mass Spectrometry.

Compound Anoectochilus roxburghii (Wall.) Lindl. (A. roxburghii) oral liquid (CAROL) is a hospital preparation of A. roxburghii and Ganoderma lucidum (G. lucidum), which have hepatoprotective effects. Eight active components (five nucleosides/nucleobases and three triterpenoid acids) in CAROL, A. roxburghii, and G. lucidum were simultaneously detected by high-performance liquid chromatography−tandem mass spectrometry (LC−MS/MS). The multiple reaction monitoring (MRM) mode was applied for the detection of analytes. These eight compounds were separated well within 12 min and quantified using the internal standard working curve method. The method showed good linearity (R2 > 0.9935) and high sensitivity (limit of detection = 0.29 ng/mL). The analyte recovery ranged from 85.07% to 97.50% (relative standard deviation < 3.31%). The content of the target analytes in four batches of CAROL, and the raw materials of G. lucidum and A. roxburghii from the five regions was determined using this method. The contents of guanosine and ganoderic acid A in four batches of oral liquid were high and stabilized and could be recommended as quality markers (Q-marker) for CAROL. Simultaneous qualitative and quantitative analysis of nucleosides and triterpenoid acids in CAROL, A. roxburghii, and G. lucidum by LC−MS/MS based on the MRM model was reported for the first time. The proposed method provides a sensitive, rapid, and reliable approach for the quality control of Chinese medicinal products.

Trityl Cation-Catalyzed Hosomi-Sakurai Reaction of Allylsilane with ß,γ-Unsaturated α-Ketoester to Form γ,γ-Disubstituted α-Ketoesters.

(Ph3C)[BPh(F)4]-catalyzed Hosomi-Sakurai allylation of allylsilanes with ß,γ-unsaturated α-ketoesters has been developed to give γ,γ-disubstituted α-ketoesters in high yields with excellent chemoselectivity. Preliminary mechanistic studies suggest that trityl cation dominates the catalysis, while the silyl cation plays a minor role.