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The ocean is the largest active carbon reservoir on Earth. Organic carbon (OC), as the primary species of carbon sequestration in the ocean, plays an important role in the global carbon cycle through its deposition and burial. In this study, sedimentary OC data from 5796 stations, together with relevant geochemical and sedimentological parameters in the Bohai Sea, Yellow Sea, and East China Sea (BYES) were used to summarize and elucidate the distribution and burial patterns of sedimentary OC, and assess carbon sink effect of sedimentary OC burial. The results show that the OC content in the sediments of the BYES ranges from 0.00% to 2.12%, with an average content of 0.47%±0.26%. OC content is significantly correlated with finegrained sediments, with an average OC content in mud areas being 39% higher than that in non-mud areas. Modern OC buried in the BYES are mainly deposited in 7 major mud areas, with a total sedimentary OC burial flux of approximately 8.20 Mt C yr−1. Among them, the burial flux of biospheric OC is 6.92 Mt C yr−1, equivalent to the OC consumption amount of silicate weathering of the 9 major river basins in the eastern China. In its natural state, the annually sequestered OC in the sediments of the eastern China seas is equivalent to 25.37 Mt of atmospheric CO2, indicating a significant carbon sink effect. The distribution and burial of terrigenous OC in the BYES are mainly influenced by the large river inputs and complex marine hydrodynamic environment, while human activities such as dam construction have significantly altered the OC burial in these coastal mud areas. [ABSTRACT FROM AUTHOR]

Estimation of knee contact force (KCF) during gait provides essential information to evaluate knee joint function. Machine learning has been employed to estimate KCF because of the advantages of low computational cost and real-time. However, the existing machine learning models do not adequately consider gait-related data's temporal-dependent, multidimensional, and highly heterogeneous nature. This study is aimed at developing a multisource fusion recurrent neural network to predict the medial condyle KCF. First, a multisource fusion long short-term memory (MF-LSTM) model was established. Then, we developed a transfer learning strategy based on the MF-LSTM model for subject-specific medial KCF prediction. Four subjects with instrumented tibial prostheses were obtained from the literature. The results showed that the MF-LSTM model could predict medial KCF to a certain high level of accuracy (the mean of ρ = 0.970). The transfer learning model improved the prediction accuracy (the mean of ρ = 0.987). This study shows that the MF-LSTM model is a powerful and accurate computational tool for medial KCF prediction. Introducing transfer learning techniques could further improve the prediction performance for the target subject. This coupling strategy can help clinicians accurately estimate and track joint contact forces in real time. Gait-related data are temporal-dependent, multidimensional, and highly heterogeneous. Therefore, we designed a multisource fusion recurrent neural network (MF-LSTM) structure and introduced a transfer learning strategy to predict knee contact force (KCF) during gait. [ABSTRACT FROM AUTHOR]

The polar oceans play a vital role in regulating atmospheric CO2 concentrations (pCO2) during the Pleistocene glacial cycles. However, despite being the largest modern reservoir of respired carbon, the impact of the subarctic Pacific remains poorly understood due to limited records. Here, we present high-resolution, 230Th-normalized export productivity records from the subarctic northwestern Pacific covering the last five glacial cycles. Our records display pronounced, glacial-interglacial cyclicity superimposed with precessional-driven variability, with warm interglacial climate and high boreal summer insolation providing favorable conditions to sustain upwelling of nutrient-rich subsurface waters and hence increased export productivity. Our transient model simulations consistently show that ice sheets and to a lesser degree, precession are the main drivers that control the strength and latitudinal position of the westerlies. Enhanced upwelling of nutrient/carbon-rich water caused by the intensification and poleward migration of the northern westerlies during warmer climate intervals would have led to the release of previously sequestered CO2 from the subarctic Pacific to the atmosphere. Our results also highlight the significant role of the subarctic Pacific in modulating pCO2 changes during the Pleistocene climate cycles, especially on precession timescale (~ 20 kyr). Ice sheets and precession are shown to control westerly strength and position, impacting nutrient-rich water upwelling and productivity in the subarctic Pacific. This finding underscores the subarctic Pacific's significant contribution to Pleistocene CO2, particularly on a precession timescale. [ABSTRACT FROM AUTHOR]

Background: Despite endovascular coiling as a valid modality in treatment of aneurysmal subarachnoid hemorrhage (aSAH), there is a risk of poor prognosis. However, the clinical utility of previously proposed early prediction tools remains limited. We aimed to develop a clinically generalizable machine learning (ML) models for accurately predicting unfavorable outcomes in aSAH patients after endovascular coiling. Methods: Functional outcomes at 6 months after endovascular coiling were assessed via the modified Rankin Scale (mRS) and unfavorable outcomes were defined as mRS 3-6. Five ML algorithms (logistic regression, random forest, support vector machine, deep neural network, and extreme gradient boosting) were used for model development. The area under precision-recall curve (AUPRC) and receiver operating characteristic curve (AUROC) was used as main indices of model evaluation. SHapley Additive exPlanations (SHAP) method was applied to interpret the best-performing ML model. Results: A total of 371 patients were eventually included into this study, and 85.4% of them had favorable outcomes. Among the five models, the DNN model had a better performance with AUPRC of 0.645 (AUROC of 0.905). Postoperative GCS score, size of aneurysm, and age were the top three powerful predictors. The further analysis of five random cases presented the good interpretability of the DNN model. Conclusion: Interpretable clinical prediction models based on different ML algorithms have been successfully constructed and validated, which would serve as reliable tools in optimizing the treatment decision-making of aSAH. Our DNN model had better performance to predict the unfavorable outcomes at 6 months in aSAH patients compared with Yan's nomogram model. [ABSTRACT FROM AUTHOR]

Background: Early identification of elderly patients undergoing non-cardiac surgery who may be at high risk for postoperative cognitive dysfunction (POCD) can increase the chances of prevention for them, as extra attention and limited resources can be allocated more to these patients. Aim: We performed this analysis with the aim of developing a simple, clinically useful machine learning (ML) model to predict the probability of POCD at 3 months in elderly patients after non-cardiac surgery. Methods: We collected information on patients who received surgical treatment at Nanjing First Hospital from May 2020 to May 2021. We used LASSO regression to select key features and built 5 ML models to assess the risk of POCD at 3 months in elderly patients after non-cardiac surgery. The Shapley Additive exPlanations (SHAP) and methods were introduced to interpret the best model. Results: A total of 415 patients with non-cardiac surgery were included. The support vector machine (SVM) was the best-performing model of the five ML models. The model showed excellent performance compared to the other four models. The SHAP results showed that VAS score, age, intraoperative hypotension, and preoperative hemoglobin were the four most important features, indicating that the SVM model had good interpretability and reliability. The website of the web-based calculator was https://modricreagan-non-3-pocd-9w2q78.streamlit.app/. Conclusion: Based on six important perioperative variables, we successfully established a series of ML models for predicting POCD occurrence at 3 months after surgery in elderly non-cardiac patients, with SVM model being the best-performing model. Our models are expected to serve as decision aids for clinicians to monitor screened high-risk patients more closely or to consider further interventions. [ABSTRACT FROM AUTHOR]

Objective: Aneurysmal subarachnoid hemorrhage (aSAH) is an aggressive disease with higher mortality rate in the elderly population. Unfortunately, the previous models for predicting clinical prognosis are still not accurate enough. Therefore, we aimed to construct and validate a visualized nomogram model to predict online the 3-month mortality in elderly aSAH patients undergoing endovascular coiling. Method: We conducted a retrospective analysis of 209 elderly aSAH patients at People's Hospital of Hunan Province, China. A nomogram was developed based on multivariate logistic regression and forward stepwise regression analysis, then validated using the bootstrap validation method (n = 1000). In addition, the performance of the nomogram was evaluated by various indicators to prove its clinical value. Result: Morbid pupillary reflex, age, and using a breathing machine were independent predictors of 3-month mortality. The AUC of the nomogram was 0.901 (95% CI: 0.853–0.950), and the Hosmer–Lemeshow goodness-of-fit test showed good calibration of the nomogram (p = 0.4328). Besides, the bootstrap validation method internally validated the nomogram with an area under the curve of the receiver operator characteristic (AUROC) of 0.896 (95% CI: 0.846–0.945). Decision curve analysis (DCA) and clinical impact curve (CIC) indicated the nomogram's excellent clinical utility and applicability. Conclusion: An easily applied visualized nomogram model named MAC (morbid pupillary reflex-age-breathing machine) based on three accessible factors has been successfully developed. The MAC nomogram is an accurate and complementary tool to support individualized decision-making and emphasizes that patients with higher risk of mortality may require closer monitoring. Furthermore, a web-based online version of the risk calculator would greatly contribute to the spread of the model in this field. [ABSTRACT FROM AUTHOR]

Background: Medication safety among children represents an underrecognized public health concern worldwide, yet little evidence was found in China. This study aimed to examine trends in rates of pediatric adverse drug reaction (ADR) reports in Jiangsu Province of China with a catchment population of more than 11 million children. Methods: Data for children aged under 15 years were extracted from the spontaneous reporting system of ADR surveillance in Jiangsu Province. Suspected therapeutic agents for ADRs were coded using the Anatomical Therapeutic Chemical classification system. We used the Chinese modification of the International Classification of Diseases, Tenth Revision, to group primary diseases, and the Medical Dictionary for Regulatory Activities to classify the manifestation of ADRs. We used Joinpoint to estimate age-adjusted ADR rates stratified by sex from July 2010 to June 2019, and further by specific features, including patient characteristics, main suspected therapeutic medications, primary diseases, and ADRs. We used the percentage change annualized estimator to evaluate trends over time. Results: A total of 79,903 ADR reports were identified among children aged under 15 years, which accounted for 11.4% of all ADRs reported in Jiangsu Province during the same period. The age-adjusted ADR report rates increased significantly from 66.20 to 96.76 per 100,000 children during the period July 2010–June 2019, with an annual increase of 4.9% (95% confidence interval 1.3–8.5%; p value 0.014). Of all ADR reports, there were 47,774 (59.8%) boys and 32,129 (40.2%) girls. Children aged 0–4 years accounted for more than half of the ADR reports (n = 47,680, 59.7%). Skin and subcutaneous tissue disorders were the most frequently reported ADRs (45,773, 57.3%). Respiratory diseases were the most commonly observed medical conditions in relation to pediatric ADRs, accounting for 68.8% (n = 54,940) of all ADR reports, and anti-infectives for systemic use consistently represented over time the most common medication group, contributing to 69.8% of all reports. A reduction in ADR report rates was observed for vaccines, with an annual decrease of 19% in children. Conclusions: ADRs remain a public health challenge among the vulnerable pediatric populations. Findings from the present study call for continuing efforts in ADR prevention and medication safety improvement in children. [ABSTRACT FROM AUTHOR]

The study of natural archives, such as bottom sediments of lakes and seas, is promising for paleoreconstructions due to rapid environmental changes, human impacts, and insufficient instrumental measurement data. Based on the radioisotope dating using unsupported 210Pb, the modern sedimentation rates were estimated for the last 150 years in the southern part of the Tatar Strait. According to CIC and CRS models, the sedimentation rate was 0.20–0.22 сm/year. [ABSTRACT FROM AUTHOR]

White birch (Betula platyphylla) is precious material for pulpwood and widely distributed in 14 provinces of China. Previous study indicated that inhibited expression of a gene encoding an auxin amide synthase, BpGH3.5, in transgenic plants reduced the level of IAA–amino acid conjugation, resulting in more free IAA, thereby better growth of birch. Utilizing transgenic-BpGH3.5 lines to increase wood production in a wide range of environments is the goal for breeders. In three field trials here, we measured tree height, diameter at breast height, and volume of 16 BpGH3.5-transgenic 7-year-old white birch lines (including 12 antisense strand lines and 4 overexpression lines) and a wild-type white birch line from three sites that varied greatly in their environmental conditions. To select elite BpGH3.5-transgenic lines for each target environment, we used an additive main effects and multiplicative interaction model to analyze genotype by environment interaction, growth adaptability and stability. The selection criteria for elite transgenic lines were set as the average volume plus 0.75 times the standard deviation for the tested lines at each test site. Results showed that the effect of line and site for height was highly significant (P < 0.01), and the effect of line × site was significant (P < 0.05); selected as the elite lines were FG12, FG13 and FG27 at the Maoershan Experimental Forest Farm, FG13 and FG32 at the Shidaohe Forest Farm, and FG3 and FG31 at the Ecological Experiment Forest Farm. These seven high-yield, stable lines can now be tested in production trials or adjacent trial areas with similar environmental conditions, while the high-yield, unstable lines should be tested in production trials in areas deemed suitable for their growth. These results provide guidance on which released transgenic elite lines will grow best in a wide range of conditions. [ABSTRACT FROM AUTHOR]

Estimating whether to treat the rupture risk of small intracranial aneurysms (IAs) with size ≤ 7 mm in diameter is difficult but crucial. We aimed to construct and externally validate a convenient machine learning (ML) model for assessing the rupture risk of small IAs. One thousand four patients with small IAs recruited from two hospitals were included in our retrospective research. The patients at hospital 1 were stratified into training (70%) and internal validation set (30%) randomly, and the patients at hospital 2 were used for external validation. We selected predictive features using the least absolute shrinkage and selection operator (LASSO) method and constructed five ML models applying diverse algorithms including random forest classifier (RFC), categorical boosting (CatBoost), support vector machine (SVM) with linear kernel, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost). The Shapley Additive Explanations (SHAP) analysis provided interpretation for the best ML model. The training, internal, and external validation cohorts included 658, 282, and 64 IAs, respectively. The best performance was presented by SVM as AUC of 0.817 in the internal [95% confidence interval (CI), 0.769–0.866] and 0.893 in the external (95% CI, 0.808–0.979) validation cohorts, which overperformed compared with the PHASES score significantly (all P < 0.001). SHAP analysis showed maximum size, location, and irregular shape were the top three important features to predict rupture. Our SVM model based on readily accessible features presented satisfying ability of discrimination in predicting the rupture IAs with small size. Morphological parameters made important contributions to prediction result. [ABSTRACT FROM AUTHOR]

The prognostic value of myosteatosis has been widely investigated in lung cancer, yet conclusions remain controversial. The purpose of this meta-analysis was to illuminate this issue. Medline, Embase, Cochrane Library and Web of Science Core Collection online databases were systematically searched from inception to 24 September 2021. Newcastle–Ottawa Scale tool was applied to evaluate the quality of included studies. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS) were used to examine prognostic value of myosteatosis. Subgroup analysis and sensitivity analysis were conducted to assess heterogeneity and stability of results. A total of 484 articles were screened from which 9 eligible studies involving 1667 patients were enrolled in this meta-analysis. Lung cancer patients with myosteatosis had significantly worse OS than patients without myosteatosis (HR 1.10, 95% CI 1.05–1.16, P < 0.001), both in six multivariate analysis (HR 1.46, 95% CI 1.16–1.85, P = 0.001) and in three univariate analysis (HR 1.08, 95% CI 1.03–1.14, P = 0.003). Pooled data from five studies using multivariate survival analysis also showed that patients with myosteatosis had a statistically significant unfavorable PFS (HR = 1.27, 95% CI 1.00–1.62, P = 0.049). Sensitivity analysis showed the result for OS was stable. But for PFS, the result was not robust. Myosteatosis might serve as an independent indicator of unfavorable survival outcomes for OS and PFS in lung cancer patients. Further studies are needed to confirm our results. [ABSTRACT FROM AUTHOR]

Early prediction of unfavorable outcome after ischemic stroke is significant for clinical management. Machine learning as a novel computational modeling technique could help clinicians to address the challenge. We aim to investigate the applicability of machine learning models for individualized prediction in ischemic stroke patients and demonstrate the utility of various model-agnostic explanation techniques for machine learning predictions. A total of 499 consecutive patients with Unfavorable [modified Rankin Scale (mRS) score 3–6, n = 140] and favorable (mRS score 0–2, n = 359) outcome after 6-month from ischemic stroke were enrolled in this study. Four machine learning models, including Random Forest [RF], eXtreme Gradient Boosting [XGBoost], Adaptive Boosting [Adaboost] and Support Vector Machine [SVM] were performed with the area-under-the-curve (AUC): (90.20 ± 0.22)%, (86.91 ± 1.05)%, (86.49 ± 2.35)%, (81.89 ± 2.40)%, respectively. Three global interpretability techniques (Feature Importance shows the contribution of selected features, Partial Dependence Plot aims to visualize the average effect of a feature on the predicted probability of unfavorable outcome, Feature Interaction detects the change in the prediction that occurs by varying the features after considering the individual feature effects) and one local interpretability technique (Shapley Value indicates the probability of unfavorable outcome of different instances) have been applied to present the interpretability techniques via visualization. Thereby, the current study is important for better understanding intelligible healthcare analytics via explanations for the prediction of local and global levels, and potentially reduction of the mortality of patients with ischemic stroke by assisting clinicians in the decision-making process. [ABSTRACT FROM AUTHOR]

Background: This phase II study evaluated camrelizumab in different PD-L1 expression cohorts of patients with previously treated advanced/metastatic non-small cell lung cancer (NSCLC; NCT03085069, registered March 21, 2017). Methods: Patients who progressed during/after chemotherapy were enrolled and divided into four cohorts based on PD-L1 tumor proportion score (TPS). Patients with EGFR/ALK alterations and PD-L1 TPS ≥ 50% were also eligible. All enrolled patients received camrelizumab at 200 mg IV Q2W. The primary endpoint was objective response rate. Results: A total of 146 patients were enrolled. As of data cutoff on Aug 20, 2020, the median follow-up was 29.5 months (95% CI 27.4–30.8). Objective response rate was 17.8% (95% CI 12.0–25.0) and improved with the increasing PD-L1 TPS (TPS < 1%, 12.2% [95% CI 5.7–21.8]; ≥ 1–< 25%, 19.4% [95% CI 7.5–37.5]; ≥ 25–< 50%, 36.4% [95% CI 10.9–69.2]; ≥ 50%, 23.3% [95% CI 9.9–42.3]). No response was observed in the five patients harboring EGFR mutations. Median progression-free survival was 3.2 months (95% CI 2.0–3.4), and patients with positive PD-L1 TPS had longer progression-free survival. Median overall survival was 14.8 months (95% CI 10.2–18.7). Treatment-related adverse events (TRAEs) of any grade occurred in 87.7% of patients, and 21.2% had grade ≥ 3 TRAEs. Conclusion: Camrelizumab showed improved efficacy compared with historical data of the second-line chemotherapy in pre-treated advanced/metastatic NSCLC. Patients with positive PD-L1 expression derived greater benefit from camrelizumab. Camrelizumab has a manageable safety profile. [ABSTRACT FROM AUTHOR]

Intracranial aneurysms (IAs) remain a major public health concern and endovascular treatment (EVT) has become a major tool for managing IAs. However, the recurrence rate of IAs after EVT is relatively high, which may lead to the risk for aneurysm re-rupture and re-bleed. Thus, we aimed to develop and assess prediction models based on machine learning (ML) algorithms to predict recurrence risk among patients with IAs after EVT in 6 months. Patient population included patients with IAs after EVT between January 2016 and August 2019 in Hunan Provincial Peopleʼs Hospital, and an adaptive synthetic (ADASYN) sampling approach was applied for the entire imbalanced dataset. We developed five ML models and assessed the models. In addition, we used SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanation (LIME) algorithms to determine the importance of the selected features and interpret the ML models. A total of 425 IAs were enrolled into this study, and 66 (15.5%) of which recurred in 6 months. Among the five ML models, gradient boosting decision tree (GBDT) model performed best. The area under curve (AUC) of the GBDT model on the testing set was 0.842 (sensitivity: 81.2%; specificity: 70.4%). Our study firstly demonstrated that ML-based models can serve as a reliable tool for predicting recurrence risk in patients with IAs after EVT in 6 months, and the GBDT model showed the optimal prediction performance. [ABSTRACT FROM AUTHOR]

Purpose: The objectives of the study were to establish a dose–response model for warfarin based on the relationship between daily warfarin dose and international normalized ratio (INR) and to evaluate the stability and reliability of the established model using external data. Methods: Clinical data were recorded from 676 outpatients with a steady-state warfarin dosage. Demographic characteristics, concomitant medications, daily dosage of warfarin, CYP2C9 and VKORC1 genotypes, and INR were recorded. Data analysis based on the Michaelis–Menten equation to describe the relationship between daily warfarin dose and INR was performed using NONMEM. The reliability and stability of the final model were evaluated using goodness-of-fit plots, resampling techniques with a nonparametric bootstrap, and external data. Results: The daily warfarin dose and INR were described by a more pharmacologically expressive model than multivariate linear regression (MLR) model. The population standard value of Km was 3.56 mg, and the Hill coefficient was 0.512, with individual variabilities of 53.1% and 55.9%, respectively. CYP2C9 *1/*3, VKORC1 AA, concomitant amiodarone, and nonheart valve replacement reduced the warfarin Km by 30.4%, 74.3%, 34.5%, and 39.4%, respectively. The Km value decreased with age and increased with fat free mass (FFM). INR prediction error (73.0%) of the external datasets was within ± 20%. Conclusion: A dose–response model of warfarin was established based on the relationship between daily warfarin dose and INR. Expected genotype effects on Km and demographic characteristics were confirmed. The model has the potential to be a powerful tool for individualized warfarin therapy for Chinese outpatients. [ABSTRACT FROM AUTHOR]

B Correction to: Neurological Sciences (2023) b https://doi.org/10.1007/s10072-023-06777-x The Authors agreed to swap the order of JianJun Zou and XiaoMing Dai to ensure that the corresponding author list in the official publication matches the original manuscript submission. Correction to: A visualized MAC nomogram online predicts the risk of three-month mortality in Chinese elderly aneurysmal subarachnoid hemorrhage patients undergoing endovascular coiling The original article can be found online at https://doi.org/10.1007/s10072-023-06777-x. [Extracted from the article]

Two sediment cores, KCES1 and ODP797, which were recovered from the Sea of Japan (JS), were measured for alkenone-derived sea surface temperatures ( $$U^{{\text{K}}^{\prime}}_{37} {\text{-SSTs}}$$ ). Our results revealed that the SSTs closely follow the glacial-interglacial cycles during the last 170 ka, except in the last glacial maximum (LGM), during which the SST was higher than in the Holocene. The anomalous high temperature in the LGM is considered as an effect of the intrusion of a low salinity water mass into the JS when the sea level was almost below 130 m. On the glacial-interglacial to orbital timescale, the $$ U^{{\text{K}}^{\prime }}_{37} {\text{-SSTs}} $$ record in the JS correlated well with the benthic foraminiferal δO record and solar insolation, which suggests the dominant control of solar insolation and its related sea ice development on the SST in the JS. On the sub-orbital/millennial timescale, reduced SST corresponds to an enhanced east asian winter monsoon (EAWM) during the last glacial period (MIS3 and MIS4), indicating the dominant control of sea ice expansion due to the enhanced EAWM on the SST in the JS. In contrast, during the last interglacial period (MIS5), the SST in the JS was controlled by variations in the east Asian summer monsoon. These results highlight the key role of solar insolation and associated glacial-interglacial conditions in the variations of the SST in the JS since the last 170 ka. [ABSTRACT FROM AUTHOR]

A total of six δC minimum events, i.e., VI, V, IV, III, II, and I, were observed via a stable carbon and oxygen isotope analysis of infaunal benthic foraminifera Uvigerina spp. in gravity core OS03-1 in the southeastern Okhotsk Sea over the last 180 ka. These events occurred at 112-109, 102-90, 85-76, 57-54, 44-40, and 17-10 ka BP. The largest negative excursions reached 2.5 ‰ in event V and were greater than 1 ‰ in the other events. We proposed that all δC minimum events were caused by the increase in sea surface water productivity, the weakened formation of Okhotsk Sea intermediate water, and the enhancement of the oxygen minimum zone. The negative excursions were unaffected by methane hydrate destabilization and subsequent methane release based on the results obtained by using archaeal lipid markers. [ABSTRACT FROM AUTHOR]

Located at the collision boundary between the Philippine Sea Plate and the Eurasian Continental Plate, the island of Taiwan is generally recognized as an important example in the MARGINS Program Science Plan and 'source-to-sink' research because of its high tectonic activity, heavy rainfall and unique geography. Large suspended sediment loads are transported to the adjacent ocean by Taiwanese rivers every year, making Taiwan an important source of sediments into the adjacent seas and a natural laboratory for studying the systemic movement of fluvial sediments from source to sink. A detailed study on the clay mineral composition of surface sediments collected from the drainage basins of 12 Taiwanese rivers using X-ray diffraction methods was conducted. Our results indicated that the clay mineral assemblages consisted dominantly of illite (approximately 73%) and chlorite (approximately 24%), with lesser abundances of kaolinite (approximately 3%) and even lower levels of smectite from the Danshuei River sediments in northwestern Taiwan. The Jhuoshuei River sediments from western Taiwan contained clay mineral assemblages that consisted of illite (approximately 75%) and chlorite (approximately 25%), but they lacked kaolinite and smectite. In southwestern Taiwan, the clay mineral assemblages were dominated by illite (approximately 75%) and chlorite (approximately 23%), but had a low abundance of kaolinite (generally < 2%) and no smectite. The clay mineral assemblages in eastern Taiwan are obviously different from those in western parts of the island. The most noticeable difference is that the average abundance of chlorite in the Hualien River from eastern Taiwan was the highest (approximately 48%) of all the Taiwanese rivers. We concluded that, in general, the clay mineral assemblages in Taiwanese rivers were mainly composed of illite and chlorite with kaolinite and smectite being scarce, and these trends are different from those in China's mainland rivers. The clay mineral composition shown in this study was primarily determined by the properties of the bedrock, and the differential weathering intensities of the drainage area. The surface sediments in Taiwan's rivers showed a greater abundance of illite and chlorite because the outcropped rocks were mainly composed of Tertiary sedimentary rocks, especially sandstone, shale and slate, and show strong physical weathering. The relatively high relief and more abundant rainfall also caused the clay minerals in the fluvial sediments to be transported to the estuaries down rivers from the mountains and then delivered to the adjacent seas by currents and waves over a shorter time scale. [ABSTRACT FROM AUTHOR]

Anisotropy of magnetic susceptibility (AMS) from above and below 7.31 m in a core from the southern Ulleung Basin shows clear differences on an equal area projection of the lower hemisphere. Rather concentrated steep inclination of K and horizontal inclination of K and K ( K⩾ K⩾ K) are located within the upper part, and the latter two axes lie perpendicular to each other near the bedding plane. In contrast, random distribution of the three axes and extremely high value of shape parameters ( Q=( K− K)/[( K+ K)/2− K]) are evident in the lower part, indicating complete destruction of the original sedimentary structure. This result is consistent with data from X-radiographs, which show numerous conglomerates, distortions and cleavages in the lower part. According to age models by Liu et al. (2010) and Zou et al. (2010), the bottom age at 7.31 m is 48 cal ka BP, and the time domain is discussed below. The degree of AMS ( P) is low, 1-1.08, and linearly related to the foliation ( F) ( R=0.95, N=176). The relationship between F and linearity ( L) implies oblate aligning patterns that are typically sedimentary in origin. At least five redox couplets were found with the aid of S ratios and other rock magnetic parameters, and in most cases, the original signals of climate survived early diagenesis. The paleomagnetically reoriented AMS show corresponding changes with millennial events in the last 48 cal ka. Clearly tilted K directions and reduction of P and F occurred within DO1-BA warm events, when melt water pulse 1A nd the YD cold event took place. The turbulent conditions therein, synchronous with coarsening of sediments, provide evidence of strong bottom currents and possible directional changes, as evidenced by different K tilting directions. A NE current direction in the last 4.5 cal ka is consistent with in situ measurements of bottom currents. Responses of AMS, mainly to climatic modulation, show on the one hand, the limited influence of diagenesis on rock magnetic signals and, on the other hand, the dramatic change of hydrodynamic conditions and terrigenous inputs during rapid sea level rise during the last deglaciation. [ABSTRACT FROM AUTHOR]

An accurate LC method was developed and validated for simultaneous determination of irinotecan (CPT-11) and its active metabolite SN-38 in rat plasma. Plasma samples were pretreated with 0.4 g mL−1 sodium dodecyl sulfate to inactive the carboxylesterase and avoid the conversion of CPT-11 to SN-38. Chromatographic separation was achieved on a Diamaonsil C18 column using acetonitrile–50 mM phosphate buffered solution (30:70, v/v) at pH 4.0 as the mobile phase with the flow rate of 1 mL min−1. The linear quantitation ranges for CPT-11 and SN-38 were 5.05–3,030 and 3.15–315 ng mL−1 with r 2 > 0.99, respectively. The lower limit of quantification (LLOQ) was 2.33 ng mL−1 for CPT-11 and 0.26 ng mL−1 for SN-38 with intra- and inter-day relative standard deviation of <12% and the accuracy values of >90%. The method was proved to be accurate and sensitive enough and was successfully applied to a pharmacokinetic study of CPT-11 in rats. [ABSTRACT FROM AUTHOR]

A sensitive and specific liquid chromatography–electrospray ionization–tandem mass spectrometry method has been developed and validated for the quantification of huperzine A in human plasma. After the addition of trimetazidine, the internal standard (IS) and sodium hydroxide, plasma samples were extracted using 5 mL ethyl acetate. The compounds were separated on an Agilent Zorbax SB C18 column (100 mm × 2.1 mm ID, dp 3.5 μm) using an elution system of 10 mM ammonium acetate solution–methanol–formic acid (18:82:0.1, v/ v) as the mobile phase. The quantification of target compounds was obtained by using multiple reaction monitoring (MRM) transitions: m/ z 243.1, 210.1 and 267.2, 166.0 were measured in positive mode for huperzine A and IS. Linearity was established for the range of concentrations 0.01–4.0 ng mL−1 with a coefficient of correlation ( r) of 0.9991. The lower limit of quantification (LLOQ) was identifiable and reproducible at 0.01 ng mL−1. The method has been successfully applied to study the pharmacokinetics of huperzine A in healthy male Chinese volunteers. [ABSTRACT FROM AUTHOR]

A simple and sensitive liquid chromatographic method was developed for quantification of cefteram in human plasma. Amoxicillin was used as an internal standard. The present method used protein precipitation for extraction of cefteram from human plasma. Separation was carried out on a reversed-phase C18 column. The column effluent was monitored by UV detection at 262 nm. The mobile phase was a mixture of methanol and water containing 0.3% v/v triethylamine and 0.6% v/v glacial acetic acid (35:65:0.3:0.6 v/v) at a flow rate of 0.30 mL min−1. The column temperature was 20 °C. This method was linear over the range of 47.5–4,750.0 ng mL−1 with determination coefficient greater than 0.99. The mean extraction recovery of cefteram and IS was ≥76.82 and ≥76.49%, respectively, and the method was found to be precise, accurate, and specific during the study. The method was successfully applied for a pharmacokinetic study of cefteram in human. [ABSTRACT FROM AUTHOR]

Objective: To compare the effects and adverse reactions of dihydrocodeine tartrate and codeine phosphate in treating moderate cancer pain. Methods: Sixty-nine cases of cancer patients with moderate pain were treated with dihydrocodeine tartrate or codeine phosphate respectively by double-blind, controlled randomized methods and the effects and adverse reactions were observed. Results: After administration of dihydrocodeine tartrate or codeine phosphate, in treatment group or control group, the total effective rate was 86.6% and 93.6%, and common adverse symptoms included constipation (31.3%/12.9%), nausea (18.8%/19.7%), gastric trouble (18.8%/19.7%), skin pruritus (12.5%/10%), vomit (9.3% and 6.5%) with the difference being not significant. Conclusion: The effects of dihydrocodeine tartrate in treating moderate cancer pain are similar to codeine phosphate. Both them can be used to treat moderate cancer pain. [ABSTRACT FROM AUTHOR]