Aniba rosiodora has been exploited since the end of the nineteenth century for its essential oil, a valuable ingredient in the perfumery industry. This species occurs mainly in Northern South America, and the morphological similarity among different Aniba species often leads to misidentification, which impacts the consistency of products obtained from these plants. Hence, we compared the profiles of volatile organic compounds  and non-volatile organic compounds (methanolic extracts) of two populations of A. rosiodora from the RESEX and FLONA conservation units, which are separated by the Tapajós River in Western Pará State. The phytochemical profile indicated a substantial difference between the two populations: samples from RESEX present α-phellandrene (22.8%) and linalool (39.6%) in their essential oil composition, while samples from FLONA contain mainly linalool (83.7%). The comparison between phytochemical profiles and phylogenetic data indicates a clear difference, implying genetic distinction between these populations. Aniba rosiodora Ducke , which is frequently spelled incorrectly as A. rosaeodora  Mez, which are similar morphologically, but are not economically important as sources of essential oils + 330.1700 corresponding to reticuline . The fragmentations indicated the initial loss of methylamine, forming an ion of m/z 299.1272, followed by fragmentation of the benzyl moiety (m/z 137.0590). The stable naphthalene ion (m/z 175.0741) was formed from the rearrangement of the ion m/z 299. The benzylisoquinoline ion (m/z 192.1012) was formed directly from the quasi-molecular ion [M + H]+, and it was the diagnostic ion for this type of alkaloid  and A. rosiodora from Presidente Figueiredo (Amazonas) were also analyzed for comparison with the Aniba samples from FLONA and RESEX using 1H-NMR data. The NMR spectra of FLONA, RESEX, and other samples are in the A. rosiodora samples from RESEX were clustered apart from samples of A. parviflora, A. rosiodora from Presidente Figueiredo, and FLONA, which were all arranged in a distinct cluster  characters were variable, and 20 (0.5%) were parsimony informative. All 20 of the parsimony informative characters came from psbA–trnH.To explore further the relationships among the samples of Aniba rosiodora was resolved as monophyletic with strong support in the Bayesian analysis, but only had moderate support from maximum parsimony. Within A. rosiodora, the two accessions from RESEX were supported as a clade that is sister to a moderately supported clade of accessions from FLONA, Presidente Figueiredo, and Manaus. In the analysis, A. rosiodora was sister to a clade formed by A. cinnamomiflora and A. hypoglauca. In all analyses, the samples from RESEX formed a lineage separate from all other A. rosiodora specimens (datasets available at Scholar@UC: http://dx.doi.org/doi:10.7945/C21H64).The topologies of the Bayesian majority rule consensus tree and the maximum parsimony strict consensus of the two most parsimonious trees were not in conflict and differed in only one instances of resolution . Aniba rAniba rosiodora is widespread in the Amazonian basin, but data describing the phytochemical and genetic variation among populations are scarce and most of them focus on Amazonas State specimen variability. In this article, we analyzed two populations from Pará State located in the opposite banks of Tapajós River. This species has long been exploited because the essential oil has a high content of the terpenoid linalool, a compound appreciated by the perfumery industry. The presence of this compound at high concentrations (>30%) is one of the characters that has facilitated the identification of this species [Aniba [A. terminalis, A. riparia, and A. parviflora; [ species , since ts [Aniba  and is pviflora; ,22,23). A. duckei Kosterm. (synon. A. rosiodora) [Aniba species [A. parviflora [A. rosiodora from Emílio Goeldi Museum campus (city of Belém), the flavonoid pinocembrin was the major compound identified in the leaves, using mass spectra [A. rosiodora collected in the Ducke Forest Reserve  indicated the benzophenones cotoin and hydroxycotoin as key compounds for these seedlings [A. rosiodora woods [A. rosiodora populations diverge considerably from one another, not only for samples from opposite banks of the Tapajós river, but also for A. rosiodora from different locations in the Amazon forest.The evaluation of the non-volatile compound composition of the leaves, bark, and stems of the samples from FLONA and RESEX indicated a clear distinction between the two populations. The PCA analyses of the mass spectra data pinpointed the pyrone anibine, formerly isolated from siodora) , as the  species . The prerviflora ,17. It i spectra . Analysieedlings . Cotoin ra woods , but is Aniba presented here  and Reserva Extrativista Tapajós-Arapiuns—RESEX (S 02°30′6.1″/W 055°06′30.6″) . All colA. rosiodora by Dr João B. Baitello  and the vouchers  were deposited in Herbário Dom Bento Pickel (Herbarium SPSF) in the Instituto Florestal do Estado de São Paulo, Brazil. Additional samples and species from other locations were analyzed to compare chemical profiles: A. rosiodora (voucher Kato 1193) from Presidente Figueiredo, AM (S 2°02’46.2”/W 59°58’05.8”), and A. parviflora from Fazenda Curauá, Santarém, PA (S 02°34’15”/W 54°37’08”). These were deposited in the herbarium of the Empresa Brasileira de Pesquisa Agropecuária  (voucher IAN 84897).The plants from conservation units were identified as w/v). The essential oil percentage was calculated based on the dry weight of the plant material [m/z with 1.56 scans/s. Retention indexes were calculated relative to C8-C24 n-alkanes, and the identification of essential oil components was based on NIST MS data library version 2.0, followed by comparisons with published literature [One hundred grams of fresh cut aerial parts (leaves and thin branches approximately 6 mm in diameter) of specimens from FLONA  and RESEX  were extracted in triplicate , by hydrodistillation for 3 h using a Clevenger apparatus in proportion 1:10 , stems (S), and bark (B) were dried in an oven at 40 °C for 24 h and then ground. Powdered samples of each part (200 mg) were extracted with MeOH (HPLC grade) (2 mL) using a crushing disperser ) for 1 min at 6500 rpm. The extracts were centrifuged at 10,000 rpm for 10 min, and the supernatants were collected for analyses .2O as the mobile phase in a gradient of 0 min 20% of MeOH held until 5 min, from 5 to 30 min 20 to 100% MeOH. The mass spectrometer was operating in electrospray positive mode, with nebulization and drying gas at 4 Bar and 8 L/min, respectively. The capillary voltage was set to 4500 V, and the drying temperature was set to 200 °C. The collision cell and quadrupole energy were set to 12 eV and 6 eV, respectively. Samples were prepared by dissolving 50 µL of the supernatant collected directly from the extracts in 950 µL of MeOH, and filtered ; 10 µL of this sample was injected into the equipment. The HPLC-MS raw data were analyzed by XCMS online software 21, and multivariate analyses were performed using Unscrambler software version 10 .The analyses of ElectroSpray Ionization High-Resolution Mass Spectrometry (ESI-HRMS) were performed in a MicrOTOFQ-II Bruker Daltonics mass spectrometer  coupled to a Shimadzu HPLC  system consisting of two pumps LC-20AD, automatic injector SIL-20A, column oven CTO-20A and controller CBM-10A. A Phenomenex Luna 5 µm  column was used. The column oven was kept at 30 °C, and chromatography was performed with a flow of 500 µL/min using MeOH:H3 (99.8% Cambridge Isotopes Laboratories TM) containing 0.05% TMS (tetramethylsilane). The 1H-NMR (Bruker DPX 200 MHz) spectra were obtained operating at a hydrogen NMR frequency of 200.13 MHz with a 5 mm probe. The spectra consisted of 256 scans and 300 k data points, with a pulse width of 8.0 µs (30°) and a relaxation delay of 1.0 s. The processing of the spectra was performed in the MestReNova (version 6.0.2-5475) program by automatic Fourier transformation using a line broadening of 0.3 Hz. TMS was used as an internal standard, and the residual hydrogen signal of CDCl3 was referenced at 7.26 ppm. The integration of the spectra signals was carried out into regions of equal width (0.05 ppm) of the region δ 3.00–9.50 ppm. The region containing residues of chloroform (7.0 to 7.4 ppm) was excluded from each spectrum. The multivariate analysis was performed using Unscrambler software version 10 .Nuclear magnetic resonance (NMR) analyses were performed using 10 mg of MeOH extract dissolved in 800 µL of CDClA. rosiodora, including two from RESEX, one from FLONA, one from Presidente Figueiredo, and one from Manaus, as well as A. hypoglauca Sandwith and A. cinnamomiflora C.K. Allen were included in the phylogenetic analysis. Ocotea quixos (Lam.) Kosterm. was included as an outgroup. Voucher information and GenBank accession numbers are listed in Five accessions of psbA–trhH [psbD–trnT [trnC–rpoB [trnS–trnG [https://www.geneious.com).Total genomic DNA was isolated from silica gel-dried leaf material using the DNeasy Plant Mini Kit . PCR amplification was carried out using GoTaq Green Master Mix following the manufacturer’s protocol . The four molecular markers from the chloroplast genome used were sbA–trhH , psbD–trsbD–trnT , trnC–rprnC–rpoB , and trnrnS–trnG . After cBayesian inference analysis was performed using MrBayes 3.2.2 ,35. The


Combination therapy of tegafur/uracil (UFT) and leucovorin (LV) is widely used to treat colorectal cancers. Although this therapy has a significant therapeutic effect, severe adverse effects occur frequently. Therapeutic drug monitoring (TDM) may help to prevent adverse effects. A useful assay that can quantitate plasma levels of 5-FU, uracil, and tegafur simultaneously for TDM has been desired, but such a method is not currently available. In this study, we aimed to develop a sensitive method for simultaneous quantification of 5-FU, uracil, and tegafur in human plasma using ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). After preparing plasma samples by protein precipitation and liquid extraction, 5-FU, uracil, and tegafur were analyzed by UPLC-MS/MS in negative electrospray ionization mode. Validation was performed according to US Food and Drugs Administration guidance. The calibration curves were linear over concentration ranges of 2–500 ng/mL for 5-FU, 20–5000 ng/mL for uracil, and 200–50,000 ng/mL for tegafur. The corresponding average recovery rates were 79.9, 80.9, and 87.8%. The method provides accuracy within 11.6% and precision below 13.3% for all three analytes. Matrix effects of 5-FU, uracil, and tegafur were higher than 43.5, 84.9, and 100.2%, respectively. This assay was successfully applied to assess the time courses of plasma 5-FU, uracil, and tegafur concentrations in two patients with colorectal liver metastasis who received UFT/LV therapy after hepatectomy. In conclusion, we succeeded to develop a sensitive and robust UPLC-MS/MS method for simultaneous quantification of 5-FU, uracil, and tegafur in human plasma. This method is potentially useful for TDM in patients receiving UFT/LV combination therapy. Surgical excision is the gold standard treatment, and the prognosis of CRC has improved even in patients with locally advanced lesions2. However, the 5-year relative survival in patients with distant metastases or stage IV CRC remains only slightly higher than 10%3. The liver is the most common metastatic site of CRC, and hepatectomy is considered the most effective treatment for colorectal liver metastasis (CRLM), with reported 5-year post-hepatectomy survival rates of 35–58%7. However, hepatectomy alone does not necessarily lead to a complete cure, and the recurrence rate after hepatectomy is approximately 70%9. To reduce the recurrence, postoperative adjuvant chemotherapy for resectable CRLM is clinically essential. Nevertheless, there is a clinical obstacle to overcome: patients who receive postoperative adjuvant chemotherapy tend to develop adverse events. Severe adverse drug reaction is most likely due to impaired drug metabolism after hepatectomy.Colorectal cancer (CRC) is the leading cause of cancer death in Japan11. UFT contains tegafur and uracil in a 1:4 molar ratio. Tegafur is a prodrug that is converted to 5-fluorouracil (5-FU) in the liver, and uracil and LV enhance the activity of 5-FU based on biochemical modulation. Although this regimen has excellent efficacy, severe adverse effects frequently appear, including myelosuppression, fulminant hepatitis, and diarrhea14. Moreover, the incidence and grade of these adverse effects are expected to be higher in patients after hepatectomy. Thus, preventing these adverse effects is important clinically.Combination therapy of tegafur/uracil (UFT) and leucovorin (LV) is currently considered a tolerable and safe adjuvant chemotherapy regimen for CRLM after hepatectomy15. However, many anticancer drugs including UFT are now available to treat patients with cancers. Reports on the development of quantification methods of anticancer drugs for TDM have been published in recent decades. Several methods for UFT and 5-FU measurements have been reported, but there are problems in terms of run time, complicated procedure, specificity, and sensitivity18.Therapeutic drug monitoring (TDM) is a useful method that aims to maximize therapeutic effects and minimize the adverse effects of drugs. Among anticancer drugs, methotrexate has been measured in clinical practice for a long time22. UPLC provides higher efficiency with wider ranges of linear velocity, flow rate, and backpressure. Higher backpressure and increased throughput result in superior resolution and sensitivity. UPLC reduces time and cost per sample, thereby improving productivity. In this study, we developed a specific and sensitive UPLC-MS/MS assay for simultaneous quantification of 5-FU, uracil, and tegafur in human plasma. To our knowledge, there is no report to date which describes a method of simultaneous determination of 5-FU, uracil, and tegafur concentrations in human plasma. This method can be applied to TDM in patients receiving UFT/LV combination therapy after hepatectomy.Ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS) allows sensitive and selective quantification of drugs or endogenous biomarkers in biological matrices13C,15N2 and tegafur-13C,15N2, respectively, were synthesized by Toronto Research Chemicals  and that for uracil; uracil-15N2, was synthesized by Cambridge Isotope Laboratories Inc. . Ammonium formate used for preparing working solution was purchased from Wako Pure Chemical Ind. Ltd. . All solvents  used in chromatography, mass spectrometry, liquid extraction, and sample preparation were of the highest analytical quality (HPLC or LC/MS grade).The standards of 5-FU and uracil were purchased from Wako Pure Chemical Ind. Ltd. , and the standard of tegafur was purchased from Tokyo Chemical Industry Co. Ltd. . The stable isotope-labeled internal standards (IS) for 5-FU and tegafur; 5-FU-The clinical study protocol was approved by the Institutional Review Board (IRB) of Oita University Hospital  and performed according to the Declaration of Helsinki as amended in Somerset West (1996). After informed consent was obtained from two CRLM patients after undergoing partial hepatectomy, the patients started to take oral tegafur/uracil  plus leucovorin . The patients took UFT (400 mg/day for patient 1 and 500 mg/day for patient 2) and 75 mg/day of UZEL every 8 h on an empty stomach for 28 days. Blood samples were collected before administration  and after administration . After centrifugation, plasma samples were separated and frozen at − 40 °C until assay.13C,15N2 at 100 and 20 µg/mL, respectively, and tegafur and tegafur-13C,15N2 at 1 mg/mL and 20 µg/mL, respectively, in 100% methanol were prepared in 50-mL volumetric flasks, and were dispensed into 2 mL polypropylene tubes. Stock solutions of uracil and uracil-15N2 at 100 and 20 µg/mL, respectively, in 50% methanol were prepared in 50-mL volumetric flasks and dispensed as for 5-FU and tegafur. Stock solutions for quality control (QC) were prepared separately from standard solutions for the calibration curves. All stock solutions were stored at − 40 °C until use. Calibrating solutions were prepared by diluting the calibration stock solutions in 50% acetonitrile aqueous solution containing 2 mM ammonium formate to the following concentrations: 5-FU , uracil  and tegafur . Lower limit of quantification (LLOQ) and three QC  solutions were prepared by diluting the QC stock solutions to the following concentration: 5-FU , uracil  and tegafur .Stock solutions of 5-FU and 5-FU-13C,15N2; 200 ng/mL, uracil-15N2; 2000 ng/mL, and tegafur-13C,15N2; 5000 ng/mL). The patient sample (200 µL) was also vortexed with 100 µL of the IS mixture and 100 µL of 50% acetonitrile aqueous solution containing 2 mM ammonium formate for volume adjustment. After adding 500 µL of methanol for protein precipitation, all samples were vortexed for 1 min. After centrifugation at 15,000 rpm at 10 °C for 10 min, 750 µL of the supernatant was carefully transferred to a new polypropylene tube and evaporated with nitrogen (N2) gas. After evaporation, 1800 µL of ethyl acetate was added and liquid–liquid extraction was performed for 10 min. After centrifugation at 15,000 rpm at 10 °C for 10 min, 1440 µL of the supernatant was transferred to a new polypropylene tube and evaporated with N2 gas. The residue was redissolved with 100 µL of 27.5% acetonitrile aqueous solution containing 2 mM ammonium formate.Two hundred µL of blank plasma was added to 100 µL of each calibration or QC solution and vortexed with 100 µL of the internal standard (IS) mixture . For chromatographic separation of the analytes, a Waters Acquity HSS T3 column  preceded by a Waters Acquity HSS T3 Van-Guard pre-column  was used. The mobile phase used for chromatographic separation consisted of water (solvent A) and acetonitrile (solvent B). The total analysis time was 12 min per injection. The flow rate was 0.2 mL/min, and the gradient was started at 90% solvent A with 10% solvent B (1.0 min). Within 2.0 min, the ratio was changed linearly to 70% solvent A and 30% solvent B. Within the next 2.5 min, the ratio was changed linearly to 10% solvent A and 90% solvent B, and kept stable for 2.0 min. Finally, the gradient returned to the starting conditions for the last 4.5 min. The column temperature was kept at 30 °C during all measurements, while the sample temperature was kept at 5 °C. The injection volume into UPLC-MS/NS was 15 µL.The conditions for liquid chromatography were as described previously by Tanaka et al.21. Samples were ionized using the following parameters: electrospray voltage was 0.5 kV, cone voltage was 20 V, source temperature was 150 °C, cone gas (N2) flow rate was 150 L/hour, desolvation gas (N2) flow rate was 1000 L/hour, and desolvation temperature was 500 °C. The mass spectrometer was optimized automatically to 5-FU, uracil, tegafur, and each internal standard, using the MassLynx V4.1 system software package (Waters) and IntelliStart standard optimization procedures (Waters). Multiple reaction monitoring (MRM) analysis was carried out using argon as collision gas for collision-induced dissociation (CID). The transitions from precursor ions to product ions monitored in the negative ion mode for 5-FU, uracil, tegafur, and the corresponding internal standards were m/z 128.91 →  m/z 41.85 at 28 V, m/z 110.92 →  m/z 41.84 at 26 V, m/z 198.98 →  m/z 41.84 at 28 V, m/z 131.90 →  m/z 43.68 at 28 V, m/z 112.91 →  m/z 42.82 at 28 V and m/z 201.99 →  m/z 43.41 at 30 V, respectively, with a dwell time of 52 ms for each transition.The conditions for mass spectrometry were as described previously by Tanaka et al.23. All analytical parameters concerning validation were determined according to previous reports22. Three validation batches, each containing eight calibration samples and 24 QC samples at different concentrations , were analyzed. Accuracy was determined as the ratio of mean measured concentration to the nominal concentration. Precision was defined by the ratio of the standard deviation to the mean concentration measured. Accuracy and precision were calculated for each analytical batch (within-batch) and for three validation batches (batch-to-batch). Selectivity was evaluated by comparing chromatograms of blank plasma samples obtained from six healthy volunteers without the addition of the internal standard mixture. The baseline signals at the expected analyte retention times were evaluated for interfering peaks. The recovery rate from plasma was determined by comparing the peak areas obtained from QC samples A, B or C with the respective peak area obtained from blank plasma spiked at the corresponding QC level after extraction  in triplicate determination. The potential matrix effect of plasma components affecting the measurement of analytes was calculated by comparing the peak area of blank plasma spiked at QC levels A, B or C after extraction with the respective peak area of matrix-free LC eluent containing the same amount of analyte in triplicate determination. The freeze–thaw stability of analytes was tested using QC samples B and C after undergoing three freeze-and-thaw cycles, and accuracy was calculated. Stability in the autosampler was tested by performing repeated analysis on QC samples B and C after being placed in the autosampler at 5 °C for 24 h. Long-term stability has already been reported25.Analytical validation was performed according to the guidelines published by the US Food and Drug Administration (FDA)23, the percentage difference of the results between the original measurement and the reanalyzed measurement was determined with the following equation: % Difference = /Mean × 100%.Incurred sample reanalysis (ISR) was conducted to verify the reliability of the patient sample measurements. All the patient samples were reanalyzed. According to the FDA guidanceCalibration curves were obtained using the standard samples and analyte-specific MRM quantifier transitions. Peak area ratios of 5-FU, uracil and tegafur to the corresponding internal standards were calculated, and weighted linear regression (1/x) was carried out for each analytical batch using the TargetLynx V4.1 software package (Waters). Method linearity was validated by performing simple linear regression between the nominal concentrations and back-calculated concentrations of the calibration samples using the corresponding calibration curve.m/z 41.85 and 43.68, respectively, which differed by approximately m/z 2 due to isotopic labeling. The identical fragment ions of uracil and IS of uracil were m/z 41.84 and 42.82, respectively, with a difference of approximately m/z 1. The similar fragment ions of tegafur and IS of tegafur were m/z 41.84 and 43.41, respectively, and differed by approximately m/z 2. The chromatographic conditions were optimized for rapid and efficient separation of these three compounds and the ISs from other substances in plasma. Figure Figure 2) was ≥ 0.9952 for 5-FU (2 to 500 ng/mL), ≥ 0.9937 for uracil (20 to 5000 ng/mL), and ≥ 0.9916 for tegafur . Linearity of each calibration curve was confirmed with eight calibrating solutions. For assessment of method linearity, the regression coefficient (r2) was 0.9963 for 5-FU, 0.9946 for uracil, and 0.9941 for tegafur, which validated method linearity for the three analytes. Within-batch and batch-to-batch accuracy and precision data are presented in Table As shown in Fig. The time courses of plasma concentrations in two patients receiving UFT/LV combination therapy measured by the UPLC-MS/MS method developed in this study are shown in Fig. 17. However, this method cannot be used to measure uracil together with 5-FU and tegafur simultaneously. Uracil inhibits the degradation of 5-FU by dihydropyrimidine dehydrogenase (DPD) in a competitive manner. High uracil levels are associated with higher toxicity as well as efficacy. To maintain an optimal balance between effectiveness and toxicity, tegafur and uracil are combined in a molar ratio of 1:4 in the preparation of UFT26. Besides, it is known that hepatectomy causes a reduction in DPD activity, leading to elevation of not only plasma 5-FU but also uracil level28. In other words, it is critically important to monitor these three compounds to accurately assess the therapeutic and adverse effects of this combination therapy. For these reasons, we developed a novel method to quantify 5-FU, uracil, and tegafur simultaneously in this study.To the best of our knowledge, it is the first report of a method for simultaneous quantification of 5-FU, uracil, and tegafur. A method for simultaneous determination of tegafur and 5-FU was reported previously17. Despite using conditions favorable for measuring tegafur, our method has a more extensive calibration range and superior LLOQ for 5-FU compared to the previous method.We used a combination of protein precipitation and liquid extraction for sample preparation. Indeed, protein precipitation is a speedy and straightforward method for sample preparation. However, protein precipitation alone is insufficient to remove matrices that interfere with ionization. Moreover, considering routine use of the MS system, using a combination of sample preparation procedures significantly reduces the wear of the MS system. A combination of protein precipitation and liquid extraction is expected to improve the recovery rate and reduce the matrix effect. Furthermore, simultaneous and more selective detection of 5-FU and uracil was achieved by using tandem mass spectrometry instead of a UV detector system. However, in order to quantify 5-FU, uracil, and tegafur simultaneously, the conditions for sample preparation, MS system, and LC system in our method were set in favor of tegafur. As a result, the recovery rates of the highly polar compounds; 5-FU and uracil, were lower than that of tegafur. In a previously reported combined LC-UV and LC–MS/MS method for simultaneous determination of 5-FU and tegafur, the calibration range of 5-FU was 8–200 ng/mL, and that of tegafur was 800–20,000 ng/mL27. The changes in drug metabolism after hepatectomy observed in the rat model probably also apply to humans. UFT/LV combination therapy is considered more tolerable and safer than oxaliplatin or irinotecan-based regimen. Although we consider UFT/LV the most recommended regimen for CRLM patients after hepatectomy, the impact of hepatectomy on the pharmacokinetics of UFT/LV remains unclear. Therefore, the optimal dose of UFT in this regimen cannot be determined. To provide more reliable therapy, TDM is a useful approach.Severe adverse effects tend to occur during adjuvant chemotherapy given after liver resection compared to without liver resection. We previously reported that major hepatectomy enhanced the toxicity of 5-FU in a rat modelAfter our novel method was developed and validated, we examined the clinical application of this method to TDM for patients receiving UFT/LV therapy. Although several data points of each compound at day 1 were lower than LLOQ, all data points at day 8, when steady state was assumed to have reached, were within the calibration ranges. These results demonstrate that the method is clinically applicable for TDM of patients undergoing UFT/LV therapy.Currently, the department of gastroenterological and pediatric surgery and the department of clinical pharmacy in Oita University Hospital are jointly conducting phase I clinical study  designed to elucidate the effect of major hepatectomy, as reflected by the efficacy and toxicity of UFT/LV combination therapy. In the future, we shall evaluate the impact of major hepatectomy on drug metabolism in patients on UFT/LV combination therapy.We have succeeded to develop a method for simultaneous quantification of 5-FU, uracil, and tegafur using UPLC-MS/MS. Subsequently, we verified the clinical application of this method. Our novel method is potentially useful for TDM in CRLM patients receiving UFT/LV therapy after hepatectomy.


To determine whether anemia is an independent risk factor for ischemic stroke and major bleeding in patients with non‐valvular atrial fibrillation (NVAF).Anemia in patients with NVAF increase risk of clinical complications related to atrial fibrillation.We conducted a prospective multicenter registry of patients with NVAF in Thailand. Demographic data, medical history, comorbid conditions, laboratory data, and medications were collected and recorded, and patients were followed‐up every 6 months. The outcome measurements were ischemic stroke or transient ischemic attack (TIA), major bleeding, heart failure (HF), and death. All events were adjudicated by the study team. We analyzed whether anemia is a risk factor for clinical outcomes with and without adjusting for confounders.There were a total of 1562 patients. The average age of subjects was 68.3 ± 11.5 years, and 57.7% were male. The mean hemoglobin level was 13.2 ± 1.8 g/dL. Anemia was demonstrated in 518 (33.16%) patients. The average follow‐up duration was 25.8 ± 10.5 months. The rate of ischemic stroke/TIA, major bleeding, HF, and death was 2.9%, 4.9%, 1.8%, 8.6%, and 9.2%, respectively. Anemia significantly increased the risk of these outcomes with a hazard ratio of 2.2, 3.2, 2.9, 1.9, and 2.8, respectively. Oral anticoagulants (OAC) was prescribed in 74.8%; warfarin accounts for 89.9% of OAC. After adjusting for potential confounders, anemia remained a significant predictor of major bleeding, heart failure, and death, but not for ischemic stroke/TIA.Anemia was found to be an independent risk factor for major bleeding, heart failure, and death in patients with NVAF. The exclusion criteria were: (1) ischemic stroke within 3 months; (2) hematologic diseases that increase risk of bleeding, such as thrombocytopenia or myeloproliferative disorders; (3) rheumatic valvular disease; (4) mechanical heart valve or valve repair; (5) atrial fibrillation from transient reversible cause; (6) life expectancy less than 3 years; (7) inability to attend scheduled follow‐up; (8) refusal to participate; (9) current participation in a clinical trial; and, (10) no baseline hemoglobin data. The study protocol was mentioned earlier.This study was approved by the Institutional Review Board (IRB) of each participating hospital, and the IRB of the Thailand Ministry of Public Health (MOPH). All patients signed written informed consent prior to participation. The subjects were enrolled from 27 hospitals in Thailand during June 2014 to October 2017.2.2After informed consent was obtained, baseline data were recorded onto a case record form (CRF) using data from both the medical record and patient interview. All data in the CRF were then uploaded into the web system. All CRFs were sent to the data management site for centralized data management, including double entry, and validation of data. All questions concerning the correctness of data were sent to the site staff for confirmation. Follow‐up data were recorded in a similar manner every 6 months until 3 years. Site monitoring was performed at every site to ensure site staff compliance with the study protocol.2.32DS2‐VASc and HAS‐BLED scores; (6) vital signs; (7) medications including, OAC and antiplatelet; (8) twelve‐lead electrocardiogram (ECG); and, (9) laboratory data within 6 months, including hemoglobin and INR. Anemia was defined by World Heart Organization (WHO) criteria as a hemoglobin level < 13 g/dl for male, and < 12 g/dl for female.The following data were collected at baseline: (1) demographic data; (2) medical history and comorbid conditions ; (3) history of ischemic stroke/TIA and history of bleeding; (4) type and duration of atrial fibrillation; (5) components of CHA2DS2‐VASc and HAS‐BLED scoring, medications, and laboratory data were recorded at each 6‐month follow‐up visit. Patients needed at least 6 months of follow‐up data to be included in the analysis.Clinical outcomes, components of CHA2.4The main outcome measurements were ischemic stroke/TIA, major bleeding, heart failure, and death. Investigators were instructed to upload medical documentation and reports that supported any of these primary outcome events into the registry's web‐based system. All supporting documents were reviewed by the adjudication committee to confirm the reported events. Ischemic stroke was defined as a sudden onset of neurological deficit lasting more than 24 h. TIA was defined in a similar manner, but the deficit lasted less than 24 hours. Major bleeding was defined according to International Society of Thrombosis and Hemostasis (ISTH) criteria.2.5t test for unpaired data, whereas categorical data were compared by chi‐square test or Fisher's exact test. Cox proportional hazards model was used to test the effect of anemia on clinical outcomes, and the results are shown as hazard ratio (HR) and 95% confidence interval (CI). The effects were adjusted for potential confounders using multivariable analysis with Cox proportional model with the adjustment for age, gender, comorbid conditions , and OAC and antiplatelet. Sensitivity analysis was performed by categorizing anemia into 3 groups , and by using anemia as continuous data and analyze the effect of anemia on clinical outcomes. Mild anemia was defined as a hemoglobin level < 13 g/dl for male, and < 12 g/dl for female but ≥11 g/dl. Moderate to severe anemia was defined as a hemoglobin level < 11 g/dl.p‐value less than .05 was considered statistically significant. The data were analyzed by SPSS Statistics version 23  and R version 3.6.3.Data are described as mean ± SD for continuous data, and as number and percentage for categorical data. Continuous data were compared by Student's 32DS2‐VASc and HAS‐BLED scores, and more use of antiplatelet.A total of 1562 patients were enrolled. The mean age was 68.3 ± 11.5 years, and 661 (42.3%) were female. The average hemoglobin level was 13.2 ± 1.8 g/dl. Anemia was demonstrated in 518 (33.16%) patients. Table 3.1The average follow‐up duration was 25.8 ± 10.5 months. Rate of ischemic stroke/TIA, major bleeding, heart failure, and death was 1.39%, 2.33%, 0.85%, 4.08%, and 4.32%, respectively. Figure 3.2After adjusting for baseline and time varying covariates, anemia remained a significant predictor of major bleeding, heart failure, and death, but not for ischemic stroke/TIA . Benefit was demonstrated only in patients without anemia. The risk of major bleeding significantly increased in patients with anemia, especially in those taking OAC. However, in our study population, warfarin was used in 88.9% of those who were on OAC. The average TTR was 52.1 ± 26.1. TTR was 49.0 ± 25.8% in patients with anemia compared to 53.7 ± 26.1% in those without anemia (p = .009). TTR ≥65% was observed in 28.4% of patients with anemia, and in 36.4% of patients without anemia (p = .012); 50.7 ± 25.4 in mild anemia and 45.4 ± 26.4 in moderate to severe anemia. Non‐vitamin K antagonist oral anticoagulants (NOACs) were used in 130 patients (11.1% of patients who were on OAC). The discontinuation rate was 89 (5.7%); 97(6.2%) for warfarin and 6(0.4%) for NOACs. OAC discontinuation was 38 (9.9%) in anemia and 51 (6.5%) in no anemia (p = .041), (24 [9.0%] in mild anemia and 14 [12.0%] in moderate to severe anemia). Among patients with anemia, the rate of ischemic stroke/TIA was 5.1% among those taking warfarin, and 0% among those taking NOACs (p = .176). The rate of major bleeding was 10.8% among warfarin users, and 5.9% among NOAC users (p = .367) in anemia group . Among patients with history of major bleeding, the bleeding sites were as follows: Intracranial 6 (16.2%), intra‐ocular 1 (2.7%), intra‐muscular 3 (8.1%), upper gastrointestinal 16 (43.2%), lower gastrointestinal 6 (16.2%), hematuria 4 (10.8%), and others 2 (5.4%). Lastly, we did not collect data on the impact on outcome of the correction of anemia during follow‐up.This study has some limitations. First, we used only anemia at the baseline visit as the criterion for including a patient in the anemia group. However, the laboratory result at the baseline visit may not reflect the hemoglobin level before clinical events. Second, the participating hospitals were mainly large community and university hospitals. Therefore, the results of this study may not be generalizable to other levels of care. However, the study sites are distributed all across Thailand. Third, warfarin was used in a majority of patients with OAC. Therefore, the results of our study may not be applied to population that receive NOAC in the majority. Fourth, we do not have the data on the etiology of anemia and cannot correlate the results of this study to patients with correctable and uncorrectable cause of anemia. However, we had data on history of major bleeding. Thirty‐seven patients (2.4%) had a history of major bleeding. History of major bleeding was presence in 22 (4.2%) of anemia group, and 15 (1.4%) in no anemia group (The major strength of this study is its prospective registry design. More specifically, the study was designed before the enrollment of patients and data collection. Another important strength is that all primary outcome events were adjudicated by the study team before they were included for analysis.5More studies are needed to confirm the benefit of OAC especially NOAC in stroke prevention in patients with anemia. Future studies are needed to focus on the safely of OAC in patients with anemia. Net clinical benefit should be demonstrated for warfarin and NOAC in patients with anemia. For warfarin, more data are needed to look at the relation of TTR and risk of stroke and major bleeding. These future data should also include significant proportion of Asian population since Asian patients may behave differently from Western population.6Anemia was identified as an independent risk factor for major bleeding, heart failure, and death in patients with NVAF. OAC may not prevent ischemic stroke in patients with anemia, but it increases the risk of major bleeding. TTR was lower in patients with anemia compared to those without.The authors hereby declare no personal or professional conflicts of interest relating to any aspect of this study.Rungroj Krittayaphong: concept and design, data acquisition, interpretation of data, manuscript preparation, manuscript revision, and manuscript review; Satchana Pumprueg, Tomon Thongsri, Weerapan Wiwatworapan, Thaworn Choochunklin: data acquisition, manuscript revision, and manuscript review; Pontawee Kaewkumdee: data acquisition, interpretation of data, manuscript preparation, manuscript revision, and manuscript review and, Ahthit Yindeengam: data analysis, manuscript revision, and manuscript review. All authors read and approved the final manuscript, and approved the submission of this manuscript for journal publication.AppendixS1: Supporting informationClick here for additional data file.


The present study examined the relationship between body mass index (BMI) and the risk for fragility fractures in postmenopausal Korean women.2, underweight; 18.5 ≤ to < 25 kg/m2, normal weight; and ≥ 25 kg/m2, obese. Subjects were also divided into three groups according to the location of fragility fracture: spine, hip, or wrist.Among subjects who participated in the 4th Korea National Health and Nutrition Examination Survey (2008–2009), 2114 women ≥ 40 years of age were included. BMI was based on standards set by the Korean Society for the Study of Obesity, as follows: < 18.5 kg/mp = 0.001). After correcting for age, family history, and treatment history of osteoporosis and rheumatoid arthritis, smoking and drinking status, and level of exercise, multivariable regression analysis revealed that the odds ratio for fragility fracture in the underweight group was 5.48 [95% confidence interval (CI) 1.80–16.73] and 3.33 (95% CI 1.61–6.87) in the obese group. After subdividing fragility fractures into vertebral and non-vertebral, the odds ratio for vertebral fracture in the underweight group was 5.49 (95% CI 1.31–23.09) times higher than that in the normal weight group; in the obese group, the non-vertebral fracture odds ratio was 3.87 (95% CI 1.45–10.33) times higher. Analysis of non-vertebral fractures in the obese group revealed an odds ratio for fracture 22.05 (95% CI 1.33–365.31) times higher for hip fracture and 3.85 (95% CI 1.35–10.93) times higher for wrist fracture.The mean (± SD) rate of fragility fracture was significantly different among the three groups: 5.9 ± 2.9% (underweight), 1.1 ± 0.3% , and 3.0 ± 0.7% (obese) (Obesity and underweight increased the risk for fragility fractures in postmenopausal Korean women. Osteoporosis is a musculoskeletal disorder characterized by a decrease in bone density and abnormal changes in bone microstructure . It is o2 [One of the most common changes experienced by postmenopausal women is weight gain. Compared with premenopausal women, postmenopausal women exhibit a 20% increase in fat mass, especially in central adiposity . In gene2 . As suchAlthough several studies have investigated the relationship between obesity and osteoporosis in Koreans, only a few have examined the impact of obesity on fragility fractures. Accordingly, this study aimed to investigate the relationship between BMI—an index of obesity—and fragility fractures in postmenopausal Korean women.https://www.knhanes.cdc.go.kr) [The Korean National Health and Nutrition Examination Survey is a statutory survey addressing the health behavior, prevalence of chronic disease, and food and nutrition intake of Korean by the Korea Centers for Disease Control and Prevention and is a government-designated statistic based on Article 17 of the Statistics Act . It corresponds to research conducted by the government for public welfare in accordance with the Bioethics Act. The original survey data are freely accessible without any administrative permission as open-access resources through the website of the Korea Centers for Disease Control and Prevention (c.go.kr) .A total of 11,604 women registered in the 4th National Health and Nutrition Examination Survey (2008–2009) were selected as primary participant group. Of these, 3023 were postmenopausal, ≥ 40 years of age, and had available bone density test data, and were selected as the secondary participant group. After exclusion of 909 women with uncertain examination records, 2114 were ultimately included as the final participant group . Based on the WHO standards for the Western Pacific region and Korean Society for the Study of Obesity standards, BMI < 18.5 kg/m2 was defined as underweight, 18.5 ≤ to < 25 kg/m2 as normal weight, and ≥ 25 kg/m2 as obese [2, were allocated to the normal weight group according to the National Health and Nutrition Examination Survey questionnaire.BMI was determined by dividing body weight (kg) by height , and the lumbar spine and left femur were measured. The units of bone density were area density, g/cmoporosis .In the smoking questionnaire, current smokers refer to those who have smoked 100 or more cigarettes in a lifetime and continue to smoke at the time of the survey. Former smokers refer to those who smoked 100 or more cigarettes in the past and have not continued to smoke at the time of the survey. Non-smokers refer to those who have never smoked at least 100 cigarettes in their lifetime . For alcWaist circumference was measured to the nearest under 0.1 cm using SECA 200, a measuring tape, during whole exhalation at the horizontal plane midway between the lower end of the rib and the iliac crest, at the mid-axillary line .During the analysis of data from the National Health and Nutrition Examination Survey, the following errors were corrected through the complex sample design: inclusion errors due to differences in the number of households and populations between the sample design period and the survey period; unequal selection probabilities; and nonresponse error of those who did not participate in the survey. For this, the primary sampling unit, k-strata, and weight were specified .Participants were divided into three groups according to BMI: underweight, normal weight, and obese. The complex samples general linear model was used for continuous variables such as age, height, waist circumference, age at menopause, and bone density  for mean comparison. For categorical variables, such as fragility fracture rate, treatment history and family history of osteoporosis, history of rheumatoid arthritis, smoking status, drinking status, and moderate exercise, Rao–Scott chi-square test was used.Complex samples logistic regression was used to analyze the relationship between BMI and fragility fracture rate. During analysis, variables that could affect fragility fractures such as age, treatment history and family history of osteoporosis, history of rheumatoid arthritis, smoking status, drinking  status, and moderate exercise, were corrected.All statistical analyses in this study were performed using SPSS version 22 .p = 0.001). Among body composition items, mean height was not different among the three groups; however, weight, BMI, and waist circumference were different from the normal weight group. The mean weight of the normal, underweight, and obese groups was 53.62 ± 0.21 kg, 41.43 ± 1.05 kg, and 64.65 ± 0.28 kg, respectively; the differences were statistically significant . The mean BMI of the normal, underweight, and obese groups was 22.49 ± 0.06 kg/m2, 17.55 ± 0.20 kg/m2, and 27.31 ± 0.09 kg/m2, respectively . The mean waist circumferences of the normal, underweight, and obese groups were 76.96 ± 0.29 cm, 65.30 ± 0.86 cm, and 89.47 ± 0.37 cm, respectively, which was significantly different from the normal weight group . The average age at menopause was not different among the groups . The average weight-corrected appendicular skeletal muscle mass was 34.29 ± 0.37 for normal weight group, 49.43 ± 3.35 for underweight group, and 28.52 ± 0.33 for the obese group, with the underweight group and the obese group showing statistically significant difference compared to the normal weight group (each p < 0.001). In case of bone density (g/cm2), the average bone density of the femoral neck (0.79 ± 0.03) and the entire femur (0.94 ± 0.03) in the underweight group was significantly higher than that of the normal weight group   In the case of T-score, only the average T-score of the femoral neck in the underweight group (− 0.35 ± 0.24) was significantly different from that of the normal weight group (− 0.87 ± 0.06) (p = 0.032). Regarding fragility fracture rate, there were differences among the three groups: underweight, 5.9% ± 2.9; normal, 1.1 ± 0.3%; and obese, 3.0 ± 0.7% (p = 0.001). In the smoking status, there was a difference in the proportion of non-smoker, former smoker and current smoker in the three groups . There were no statistical differences in treatment history and family history of osteoporosis, history of rheumatoid arthritis, drinking status, and moderate exercise among the three groups (Table The mean (± SD) age of the normal weight group was 59.01 ± 0.42 years, which was not statistically different from the mean age of the underweight group (61.43 ± 3.00 years) but was significantly different from that of the obese group (60.98 ± 0.44 years) . When fracture rates were compared between the vertebral and non-vertebral fracture rates, vertebral fracture rate for the underweight group (4.5 ± 2.6%) was significantly higher compared with the normal weight group (0.6 ± 0.2%) and obese group (0.9 ± 0.4%) . In the case of non-vertebral fracture rate, that of the obese group (2.3 ± 0.6%) was relatively higher than that of the normal weight group (0.7 ± 0.3%) and underweight group (1.4 ± 1.4%), with a statistically significant difference among the three groups   and 2.72 (95% CI 1.38–5.37) in the obese group. In model 2, which was corrected for age and family history and treatment history of osteoporosis, odds ratio for the underweight group was 5.14 (95% CI 1.77–14.93) and 3.12 (95% CI 1.50–6.48) in the obese group. In model 3, which was corrected for age, family history and treatment history of osteoporosis, history of rheumatoid arthritis, smoking status, drinking status, and moderate exercise, the odds ratio for the underweight group was 5.48 (95% CI 1.80–16.73) and 3.33 (95% CI 1.61–6.87) for the obese group  times higher than that of the normal weight group. In the obese group, there was no statistically significant difference in the odds ratio for vertebral fracture, while the non-vertebral fracture odds ratio was observed to be 3.87 (95% CI 1.45–10.33) times higher. When non-vertebral fractures were compared after dividing them into hip and wrist, the obese group had an odds ratio for hip fracture 22.05 (95% CI 1.33–365.31) times higher and 3.85 (95% CI 1.35–10.93) times higher for wrist fracture (Table 1–23.09 tThe purpose of this study was to investigate the relationship between BMI and fragility fracture(s) in postmenopausal Korean women. In both the underweight and obese groups, the fragility fracture rates were 5.48 and 3.33 times higher, respectively, compared with the normal weight group. In particular, the underweight group exhibited an odds ratio for vertebral fracture that was 5.49 times higher, and the obese group exhibited an odds ratio for non-vertebral fracture that was 3.87 times higher. As such, the most significant finding of the present study was that postmenopausal women who were underweight or obese exhibited higher rates of fragility fracture(s).2 demonstrated a hip fracture rate twice as high as those with a BMI of 25 kg/m2 [2, the non-vertebral fracture rate was 2.45 times higher [2 compared to those with BMI > 24 kg/m2 [The findings of high fragility fracture rate in the underweight group were consistent with previous studies; however, there were slight differences in fracture sites for each study. According to one study, underweight individuals with a BMI < 20 kg/m25 kg/m2 . Anothers higher . The reas higher . Other s24 kg/m2 . Studies24 kg/m2 . AlthougIn this study, there was no statistical difference in the rate of lumbar spine fractures in the obese group, which was similar to other previous studies. One study that examined changes in lumbar spine bone density in individuals with weight changes showed that individuals with weight gain had increased lumbar spine bone density compared to those with weight loss . As a reRecently, it was reported that obesity is related to the site of fragility fractures. One study found that obesity led to lower risk of lumbar and femur fractures ; howeverThe non-vertebral fracture rate was higher in the obese group, unlike the underweight group, which could be explained by the fact that the obese group exhibited significantly lower weight-corrected appendicular skeletal muscle mass compared with the normal weight group. Appendicular skeletal muscle mass is used as one metric to define sarcopenia , and it Generalizing the results of the present investigation would be difficult given some following points. First, it was a cross-sectional study limited to postmenopausal women. Second, it was unclear when the BMD test performed and when the fracture occurred. Third, the BMI might have been calculated relatively high due to a decrease in height if there were a single or multiple vertebral fractures in the past. Further studies are required to consider the association between fragility fractures and other obesity indices such as waist circumference or waist to hip ratio as well as BMI. Fourth, the overweight group was inevitably included in the normal weight group for analysis because accurate analysis was difficult due to data limitations. Fifth, the percentage of underweight was only 2% of the total study population. As a relatively small number of people were classified as underweight, the general bone density characteristics of the group did not appear, and it is thought that the individual subjects' bone density characteristics were more reflected. This should be studied further through future researches.In conclusion, despite the various limitations, the most significant finding of this study was that underweight and obesity increased the rate of fragility fractures in postmenopausal women. In the end, there are various factors that affect fragility fractures, so further research will be needed, but the this study showed the impact of the body mass index.


LW,A (dB)) at 20–200 Hz, which are not provided by manufacturers but essential for estimating LFN exposure (LAeq) of nearby residents.Low-frequency (20–200 Hz) noise (LFN) from wind turbines has received much public attention due to potential health concerns. This work tries to estimate the sound power level of wind turbines  were estimated using propagation model ISO 9613-2 under different weather conditions  and validated with LFN monitoring data. The feasibility of using validated LW,A as inputs for ISO 9613-2 to simulate residents’ exposure (LAeq) to LFN were assessed considering interferences from rain, wind speed and wind directions.LW,A at 20–200 Hz ranged between 93.2 and 100.4 dB, 97.8 and 107.2 dB, and 96.5 and 110.4 dB for turbines of Brands A, B, and C, respectively, operating under wind speeds from 2 to 12 m/s. The LW,A at wind speed of 2–8 m/s increased on average by 1.4, 1.9 and 1.7 dB per 1 m/s increase for Brands A, B and C, respectively. The differences in modeled Leq obtained through the input of LW,A into the ISO 9613-2 model and the measured LAeq for the three studied wind farms all fall within 1.5 dB.The average LW,A of wind turbines of three brands, and subsequent residents’ LFN exposure (with 1.5 dB difference) at three wind farms. Accurately obtaining LFN exposure will serve as the basis for assessing LFN exposure-health relationship. As wind power widely use worldwide, health impact should be assessed based on validated LFN exposure assessment.This study successfully determined and validated the The online version of this article (10.1007/s40201-020-00478-9) contains supplementary material, which is available to authorized users. Wind power is used around the world as a source of clean energy. However, wind turbines generate a broad spectrum of low-frequency noise (LFN) in the range of 20–200 Hz , 2, whicStudies have widely affirmed that exposure to LFN can have adverse health effects on humans, including annoyance, stress, sleep disturbance, headache, tinnitus, irritation, exhaustion, anxiety, as well as hearing loss, impaired concentration, and in some cases chronic fatigue , 9–15. LLW,A), is neither provided by wind turbine manufacturers, nor found in other documentation. Only LW,A in the full audio spectrum (audio frequency range of 20–20 kHz) or in certain frequency spectra under 63–8 kHz and 50–10 kHz were provided in some references .LW: 1/3 octave source noise of wind turbine (dB).1: distance from turbine hub to receptor (m).dgr: frequency-specific ground attenuation (dB).Aatm: atmospheric attenuation (dB/km).A2: distance from turbine hub to receptor (km).dgr can be obtained directly from the frequency-specific ground attenuation table , is used instead of Lp in Eq. , a research-grade, web-enabled and data logging moveable weather station suitable for operation even in harsh outdoor climates. The HOBO weather station comprises a wind speed sensor (S-WSB-M003), temperature/relative humidity sensor (S-THB-M00x), and multi-channel data logger. Five-min meteorological data were analyzed in this study.For continuous measurement of LFN, a hand-held analyzer type NL-62 , which complies with IEC 61672–1, 2002 Class 1 and ISO 7196: 1995 applicable standards, was used. The frequency analysis program NX-62RT, with the options of 1/1 octave, 1/3 octave, and broadband sound measurements, was employed to analyze the measurements. In this study, the 1/3 octave noise spectrum with band central frequencies of 20, 25, 31.5, 40, 50, 63, 80, 100, 125, 160, and 200 Hz was used. Fig. SLAeq) in our dataset were from wind turbines rather than from other sources.The starting operational wind speeds of wind turbines are specified as 4 m/s, 3 m/s and 2 m/s for Brands A, B and C, respectively –45. HoweLW,A of turbine LFN input for Eq.  in October 2018 were input into Eq. LAeq,5min, which was compared with the actual measurements  in October 2018 to validate the original estimated LW,A at different wind speeds exceeding 2 m/s.This study first estimated  for Eq.  to simulLAeq,5min measurements into the ISO 9613-2 model, the difference in height between the turbine hub and the monitoring station was taken into account to calculate the linear distance between the two (d1 and d2). The difference in height was 45–5 = 40 at NT, 65–6 = 59 m at TY, and 64–12 = 52 m at HC.When inputting the actual 1 and d2) of different turbines (n) into the model produces a system of n equations, the sum of which is the measured LAeq. The system of n equations is then solved to obtain the estimated LW,A.In addition, LFN noise from multiple turbines at different distances from the receptor were considered at the same time. Inputting meteorological parameters (temperature and relative humidity) and distance parameters  into the ISO 9613-2 model to estimated LW,A and that comparing LW,A between days with and without rain over four months from September through December 2018 was made. From the differences of LW,A between days with and without rain to clarify effects of rain on LAeq. Moreover, the effects of wind speed were examined using monitoring data collected at the three studied wind farms in September 2018, while the effects of different wind directions on LAeq were assessed through comparing data gathered in May  with those in September of 2018  at HC. Furthermore, the effect of wind directions on noise propagation was evaluated in May and September.To investigate the effects of rain on LAeq,5min measured at the wind farms and estimated LW,A for the three different brands of wind turbines. Taiwan Environmental Protection Administration (EPA) designated different noise standards for different time of the day such as daytime (7 am to 7 pm), evening (7 pm to 10 pm) and nighttime (10 pm to 7 am) [ at all three wind farms compared to those at evening and nighttime. The LAeq,5min difference between daytime and nighttime were about 1.3–2.9 dB at the three wind farms. Moreover, observed LAeq,5min mainly came from the wind turbines. Nevertheless, there were other possible background noise sources at daytime, resulting in higher LAeq,5min. It is obvious that different brands of wind turbines generate different levels of LW,A, with Brand C producing the highest LW,A, implying that the LFN exposure  in the vicinity of HC would also be the greatest.Table to 7 am) . Our obsLW,A from monitoring data (LAeq) at different wind speeds between days with and without rain. As can be seen, LW,A is higher when it rains. Indeed, sound is produced when rain hits against any object, be they buildings, land, water, flowers, trees, including the turbines. Moreover, larger difference in LW,A of wind turbines is observed at low wind speeds of 2–4 m/s, with the difference becoming smaller at higher wind speeds of 5–9 m/s.Figure n < 30). Overall, the effect of rain on LAeq at different wind speeds is significant in most cases.Results of the two-sample t-test, shown in Fig. The above analysis implies that beside noise from turbines, wind farm on rainy days will have other sources of environmental LFN. It has been reported that in the presence of rain, rain-generated sound replaces wind-generated noise as the major noise source in the frequency range of 1–50 kHz . In otheIn northern Taiwan where all three wind farms are located, the prevailing wind comes mainly from northeast (NE) during September to March, and from southwest (SW) during April to August. The measurements for comparison were collected in the same month of September and hence, under the same prevailing NE wind. Only data on days without rain were analyzed.LW,A and sample size at wind speeds ranging between 2 and 12 m/s. Sound power levels estimated and number of measurements recorded at different wind speeds are listed in Table SLW,A) under three conditions, included 24 h period, Day time and Night time. As shown, the sample size (n) totaled 2473, 3521 and 5012 for NT, TY and HC, respectively. Note that measurements recorded under wind speed of 2 m/s were not included in the analysis. As can be seen, the majority of data collected were within the wind speed range of 2–8 m/s. The total number of measurements collected is in the order of HC > TY > NT, which also implies the frequency of wind speed above 2 m/s recorded during the study period is in the order of HC > TY > NT. Indeed, according to the observation data archived at the Central Weather Bureau,  during September 2018, our study period, the average daily wind speed was 1.1, 2.0 and 2.0 m/s at New Taipei, Taoyuan and Hsinchu area, respectively. Moreover, the highest wind speed recorded was 8 m/s at both NT and TY but 12 m/s at HC. Actual record at CWB of the study period also showed maximum wind speed of 7.4, 8 and 9.2 m/s at New Taipei, Taoyuan and Hsinchu area, respectively. Variations in observations made at the wind farms could be attributed to their geographical locations. NT is more sheltered in the hilly upland in the north; while both TY and HC are along the western shore subject to stronger wind over the sea. Moreover, Hsinchu, where HC wind farm is located, is popularly nicknamed as the ‘Windy City’ for its windy climate with average wind speed over the year 2.4 m/s (CODiS).Figure LW,A and wind speed; that is, LW,A increases with increasing wind speeds. In other words, sound power or noise level at turbine is higher at higher wind speed. Although Brand C has the highest LW,A of 110.4 dB at wind speed of 12 m/s, for the same range of wind speeds, 2–8 m/s, LW,A generated is in the order of Brand B > Brand C > Brand A. While Brands B and C have similar noise level generated, LW,A of Brand A is significantly lower, which can be attributed to the smaller wind turbine electric power (≤ 660 kW) of its wind turbine  at wind speed of 2–8 m/s increased on average by 1.4, 1.9 and 1.7 dB per 1 m/s increase for Brands A, B and C, respectively. The daytime LW,A were 93.3–100.4 dB, 97.8–107.3 dB and 95.7–105.0 dB for Brands A, B and C, respectively, at wind speed of 2–8 m/s. Compared with those at evening and nighttime, the daytime had the highest LW,A at most wind speed range. In addition, the LW,A (nighttime) increased on average by 1.4, 1.7 and 1.6 dB per 1 m/s increase for Brands A, B and C, respectively . Again, the average increase in noise level per 1 m/s increase in wind speed is also in the order of Brand B > Brand C > Brand A, for the same reason of difference in electric power generation. The present findings are consistent with previous results on positive correlation between wind speed and turbine noise emission [Results shown in Fig. emission , 31. Comemission .LW,A at different wind speeds are essential inputs for LFN propagation model for estimating LFN exposures (LAeq) of residents under different weather conditions. Furthermore, calculating the R-squared value of LW,A versus wind speed yielded 0.999, 0.995, and 0.978 for NT, TY and HC, respectively, indicating good correlation between wind turbine noise and wind speed.Data collected in this study do not allow comparison to be made on noise generation at wind speed exceeding 8 m/s as NT and TY did not record such high wind speed during the study period. Nevertheless, Among the three wind farms studied, HC had the monitoring station installed in April; hence, measurements obtained there included turbine-generated noise under both NE and SW winds. Moreover, regardless whether the prevailing wind is NE or SW, there are turbines at HC lying upwind and downwind in relation to the monitoring station. As illustrated in Fig. SLW,A of wind turbines under different wind directions at HC. Wind from different directions may affect noise propagation, thus affecting LAeq monitored at our monitoring station. Based on these observed LAeq, LW,A values were estimated based on Eq.  reported that the average noise levels measured at 120 m from the turbine did not vary by more than 4 dB (LAeq) across all wind directions and the difference in noise propagation between upwind and downwind condition reached 6–7 dB (LAeq) at a distance of 1000 m [LAeq) at a house 500 m away with the wind blowing in opposite directions [LAeq) obtained in this study at HC from turbines within 1-km radius is much lower than previous findings. Compare with previous study results that small variation in average noise propagation under different wind directions renders the present approach better suited for simulating LFN exposure (LAeq) by the estimated LW,A from wind turbines of residents in the vicinity of wind farms.At wind speeds of 2–12 m/s, the difference in estimated f 1000 m . Measurerections . In compLW,A values are higher under prevailing NE than SW wind, which can account for more reports from local residents of louder noise from wind turbines during periods with prevailing NE wind. Therefore, the estimated LW,A under prevailing NE wind in September of 2018 is served as a basis for future simulations for exposure of residents to LFN from wind turbines.Results of the two-sample t-test, shown in Fig. LAeq.Difference in measurements obtained between turbine LFN source situated downwind and upwind in relation to the monitoring station can be attributed to the Doppler effect, which indicates an apparent change in sound frequency when a source or receptor of sound is moving relative to the medium. This study focused on monitoring sound within the 20–200 Hz frequency range, and the upwind-downwind difference in turbine LFN sources experienced by the receptors under different wind directions can cause a shift in sound frequency from outside the frequency range into the 20–200 Hz range, resulting in differences in LAeq (20–200 Hz) in October 2018 from wind turbines at different wind speeds. Both modeled and measured results were obtained under similar meteorological conditions including temperature, relative humidity and wind speed. As can be seen, the two results obtained are very close with insignificant differences. The difference between measured and modeled LAeq ranged between 0.6–1.7 dB at NT (2–8 m/s), 0.6–1.6 dB at TY (2–8 m/s), and 0.4–2.4 dB at HC (2–10 m/s). Overall, the difference between modeled LAeq and actual measurement is mostly less than 1.5 dB for LFN propagation at the three wind farms. Our results are consistent with previous studies. Zagubien´ and Ingielewicz (2017) presented consistent results between measurements and computer simulations (by ISO 9613-2 norm). For all wind farms in north and central Poland, the discrepancy between measurements and calculations did not exceed 1.3 dB [Figure d 1.3 dB . In addid 1.3 dB .Fig. 4MeLAeq and actual measurement was 2.4 dB at HC under wind speed 3–4 m/s, which was smaller than ±3 dB stated in the manual. The smaller difference obtained in this study support the validity and accuracy of the present approach in LW,A estimation. The accuracy of modeled results can be attributed to the environmental setting of the monitoring stations. The absence of buildings or barriers in the open space surrounding the monitoring station allowed uniform propagation of turbine LFN and avoided echo caused by LFN reflecting off barriers.Manual of ISO 9613-2 states a prediction accuracy of ±3 dB for sources of heights up to 30 m above ground and for distances of up to 1000 m from the source , 40. TheLAeq) were estimated with LW,A (dB) as inputs into the ISO 9613-2 model under difference distances. Compare to long distances, receptors at the short distances had higher LFN level (LAeq), consistent with a previous study [LAeq) in addition to other surrounding obstacles. It should be also noted that ISO 9613-2 model is valid only within 1 km.Residential exposure levels to LFN  and the sea  are noise sources. Similarly, HC is located close to roads (around 130 m) and the sea (around 162 m) with overhead flight paths. Noises from road, sea and air traffic influence LFN. Previous studies indicated that there are a variety of LFN sources including road vehicles, aircraft, and sea traffic [LAeq. Disturbance to residents comes mainly from higher LFN level at higher wind speed. Accurate estimation of LFN level (LAeq) at different distances would serve as a basis for assessing the residents related health impacts.Moreover, the difference between measured and modeled  traffic , 35, 36.LW,A at 20–200 Hz from wind turbines of three manufacturers  in order to provide required inputs for ISO 9613-2 to simulate LFN level (LAeq) at different distances. Additionally, the effects of weather conditions  on LAeq were assessed. Our results showed that significant positive effect of rain on noise generated in low-wind-speed environments, with the effect decreasing at higher wind speeds. Average LW,A at 20–200 Hz ranged between 93.2 and 100.4 dB, 97.8 and 107.2 dB, and 96.5 and 110.4 dB for Brands A, B and C, respectively, at wind speeds of 2–12 m/s. On average, LW,A at wind speed of 2–8 m/s increased by 1.4, 1.9 and 1.7 dB per 1 m/s increase for Brands A, B and C, respectively. Overall speaking, differences between modeled LAeq and actual measurements are mostly less than 1.5 dB for LFN propagation at the three wind farms. This study successfully determined and validated the LW,A of wind turbines of three brands, which can serve as a basis for further estimation of residents’ exposure to wind turbine LFN. As wind power widely use worldwide, health impact should be assessed based on validated LFN exposure assessment.This study estimated the ESM 1(DOCX 6051 kb)


Flemingia macrophylla silage (FMS) supplementation at 0, 0.2, 0.4 and 0.6 kg dry matter (DM)/day in a 4 × 4 Latin square design. Feed DM intakes were measured during the 14 days and sample of feeds, feces, urine, as well as rumen fluid and blood were collected during the 7 days while the animals were on metabolism crates.Good quality protein as an on-farm feed resource has been in great demand to support the productivity of ruminants. A digestion trial using beef cattle crossbreds was conducted to assess the four dietary treatments of P < 0.05) nutrients digestibility  enhanced rumen total volatile fatty acid production especially propionic acid (C3), C2:C3 ratio while, remarkably promoted the microbial protein synthesis (MPS) by increasing N-balance and retention of purine derivatives.Based on this experiment strategic supplementation of FMS increased (Under this experiment, the results revealed the potential use of FMS as a good-quality feed to improve nutrients digestibility, rumen fermentation, microbial protein synthesis, and to mitigate methane production. FMS supplementation at 0.6 kg DM/day exhibited the best result. Flemingia is a multipurpose legume shrub that yields fresh biomass of about 55 tons/ha/year and thrives well in diverse conditions [4) production [Flemingia at 125 g of dry matter intake in goats did not affect adversely the feed intake and milk production. In addition [Flemingia hay meal at 150 g/head/day increased digestibility of nutrients, rumen fermentation and microbial protein synthesis. Moreover, Kang et al. [Flemingia leaves supplementation improved rumen fermentation and reduced the CH4 production. Conservation of feed in the form of silage has been a good practice especially for dry season feeding [Feed resources for ruminants are important in the livestock feeding systems for small-scale tropical farmers; particularly in the dry season . Flemingnditions . It contnditions –5. The poduction . Fagundeoduction  also repaddition , it was  feeding . Silage  feeding –12.Flemingia macrophylla silage on rumen fermentation. Hence, the aim of this experiment was to investigate the impact of Flemingia macrophylla silage on nutrient digestibility, rumen fermentation and microbial protein synthesis in beef cattle.However, there is limited information about the utilization of Concentrate supplement was formulated using cassava chip and agricultural by-products, namely rice bran, palm kernel meal, molasses etc., as shown in Table P > 0.05), however nutrients digestibilities of DM, OM, CP, NDF, and ADF were significantly increased (P < 0.001)  Table . In addi3) (P < 0.001), among treatments , butyric acid (C4), acetic acid to propionic acid (C2 to C3), CH4 production, and protozoal population were decreased (P < 0.001) among treatments, respectively. However, ruminal pH and BUN were not changed.FMS supplementation increased total VFA and propionic acid C (P < 0.0P < 0.001), while N excretion was similar among treatments (P > 0.05). However, N absorbed and N retained were increased (P < 0.001), respectively. The FMS supplementation affected on allantoin, uric acid, PD, purine absorb, microbial nitrogen supply and EMNS (P < 0.001). Moreover, FMS affected on percent of MNS and EMNS were increased significantly among treatments (P < 0.001), respectively.Table Flemingia is the shrub which can produce biomass for ruminant feeding. It contains high level of crude protein, CT and SP. The feed can be ensiled as silage for long time feeding, details are shown in Table P < 0.05), but enhanced the digestibilities of OM, CP, NDF and ADF. Higher level of CP of the silage could have attributed the degradation activity of the rumen microbiomes. Phesatcha et al. [As shown in Table a et al.  found sia et al. . Tannin-Flemingia leaf supplementation did not change ruminal pH and BUN. The normal rumen pH was reported to be 6.3–6.8 which can support cellulolytic bacteria’s normal activity [3-N and enhance the protein availability in lower-gut [3-N concentration was a key factor (15–30 mg/ml) for efficient microbial protein synthesis [3-N values (16.91 ± 0.08 to 19.31 ± 0.12 mg/ml) were found and could improve for rumen ecology in cattle crossbreds. With increased levels of FMS supplementation, the total VFA and C3 were remarkably increased (P < 0.05), and the highest impact was found in the group fed with of 0.6 kg/day, while C2, C2 to C3 ratio were reduced. Under the work of Phesatcha et al. [2 was reduced, which C3 was increased (P < 0.05). Makkar et al. [2 concentration. It was additionally reported that CT can impact on methanogenesis by reducing protozoa and methanogens, when C2 was reduced but C3 was greatly enhanced [4 depression could be influenced by the suppression of protozoal population by FMS supplementation. This may be attributed to CT in FMS which could interfere the cell membrane of protozoa, thus interfering with ion exchanges [Fibrobacter succinogenes, while the other two fibrolytic bacteria; Ruminococcus albus and Ruminococcus flavefaciens were decreased, but the actual mode of action needs to be further elucidated [Ruminal pH and BUN were not significantly shifted differently among treatments. This result was similar to the findings of Phesatcha et al.  who repoactivity . The tanower-gut , 22. Rumynthesis . In thisr et al.  further enhanced . Anotherxchanges . Poungchxchanges  earlier xchanges . Earlierxchanges –31. Howeucidated .3-N concentration has been shown to support the microbial protein synthesis, as it was well-utilized by cellulolytic bacteria as an important source of nitrogen [FMS supplementation affected N-balance as shown in Table nitrogen . In adeqnitrogen  or CT [3nitrogen  in the dFlemingia macrophylla silage as a good-quality feed to improve nutrients digestibility, rumen fermentation, microbial protein synthesis, and to mitigate methane production. Flemingia macrophylla silage supplementation at 0.6 kg DM/day exhibited the best result. Making Flemingia macrophylla silage should be encouraged to prepare for on-farm use especially during the long dry season. Furthermore, in vivo feeding trials should be conducted in both beef cattle and dairy cattle in order to obtain more relevant data.Under this experiment, the results revealed the potential use of This experiment approval was granted by the Institutional Animal Care and Use Committee of Khon Kaen University, Thailand (Record no. IACUC-KKU-94/61 and reference no. 0201.2. 11/73).Flemingia macrophylla was planted by stems on the experimental plots of Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Thailand with close supervision of the advisory Professor. All plant parts were kept and stored at TROFREC. Flemingia macrophylla (FM) whole top plant was harvested from the shrub after three months of regrowth. Silage of Flemingia was prepared by using young-whole leaf and stem, chopped (3 cm) and mixed with solution. Chopped fresh Flemingia (100 kg) was well-mixed with solution containing molasses, urea and water at 2:1:10, respectively. The mixture was ensiled in a plastic barrel for 21 days before feeding. Samples of FMS was randomly collected and later was analyzed for chemical compositions [ositions , 39, conositions , 41. Apaositions .The sample size calculation was based on experimental design according to in a 4 × 4 Latin square design with 4 replicates, which provided a total of 16 experimental units.Neither inclusion nor exclusion was used, since the four beef cattle were similar in age, weight and pre-fed under similar feeding condition.No blinding was performed, as the four treatments were already randomized statistically.ad libitum with supplementation of FMS at 0, 0.2, 0.4 and 0.6 kg DM/head/day. The trial was conducted for four periods each was consisted of 21 days, during the first 14 days was for matter feed intake measurement, while during the last 7 days for sample collection using total collection method. Each animal was in individual pens, where clean water and mineral-salt blocks were available at all times. The diet was offered to the animals twice dairy in the morning (07:00a.m.) and afternoon (04.00p.m.). The liveweight of each cattle was weighed at the beginning and the end of each period to calculate feed intake. Feed provided and refusals were measured daily throughout the experimental period. Feed samples were collected twice a week for DM analysis. Samples of feeds including concentrate, FMS, rice straw, feces were collected randomly daily during the last 7 days of each period. A daily sample of feces of each animal (about 100 g) was collected to be analyses [4) production [These experimental beef crossbreds belonged to Tropical Feed Resource Research and Development center (TROFREC), Khon Kaen University and were provided as experimental animals for Ph.D. students. The animals were well-maintained for their health with good feeding and other management. After the experiment all animals were kept and maintained well with all aspects; health, nutrition, feeding and would be used later for other experiments. Four, beef cattle about two year old with 172 ± 43 kg liveweight, were randomly assigned to in a 4 × 4 Latin square design. Concentrate was offered at 0.5 kg of body weight (BW)/day and rice straw offered analyses . Urinaryanalyses , and totanalyses . Detailsanalyses , protozoanalyses , and estoduction  are presoduction . Blood soduction .The samples were estimated according to the statistical design used 4 × 4 Latin Square Design.P < 0.05 was accepted as statistical differences while 0.05 < P < 0.10 was accepted as a tendency. Treatment means were statistically compared by Duncan’s New Multiple Range Test [All data were included in all analysis subjected to ANOVA according to a 4 × 4 Latin square design using the General Linear Models (GLM) procedures . The resnge Test .


Atlantoaxial subluxation (AAS) is a not rare abnormality between the atlas (C1) and axis (C2). For AAS patients with persistent neck pain and neurologic symptoms, surgical intervention is a good choice. Nevertheless, there were still few reports about the use of intraoperative skull traction and different fixation methods in treatment of AAS.From January 2012 to December 2018, a total of 86 cases were admitted to our hospital and diagnosed as AAS. All the patients received atlantoaxial reduction with the help of intraoperative skull traction and C1-C2 fixation. Clinical and radiological parameters were collected through chart review.There were 86 cases included in this study. The mean operative time was 153.9 ± 73.9 min, and the mean amount of intraoperative blood loss was 219.1 ± 195.6 ml. 81 patients underwent posterior reduction, internal fixation and fusion. 5 patients underwent anterior release, followed by posterior internal fixation and fusion. 82 patients got satisfactory postoperative outcomes while complications occurred in 4 patients. Significant neurologic improvement was observed in these patients. Bone fusion was achieved on the midline sagittal reconstructed CT images at the latest follow-up in all these patients except 1 case. All the patients were followed up for 34.84 ± 15.86 months at average (range 12–60 months). The mean ADI value was 7.55 ± 1.67 mm at average preoperatively, and improved to 4.03 ± 1.21 mm postoperatively, and to 4.21 ± 0.99 mm at the latest follow-up. The mean A-A angle was 15.48 ± 9.82 degrees at average preoperatively, and improved to 21.61 ± 10.43 degrees postoperatively, and to 19.73 ± 8.13 degrees at the latest follow-up. The mean A-A height was 35.61 ± 7.66 mm at average preoperatively, and improved to 40.08 ± 8.5 mm postoperatively, and to 38.83 ± 6.97 mm at the latest follow-up. There were complications in 4 patients, including pedicle misplacement, pedicle screw fracture, infection and one death.Intraoperative skull traction can effectively facilitate the surgical procedures for ASS caused by different etiologies. Further research will be needed to investigate the safety and effectiveness of this method in the future. Atlantoaxial subluxation (AAS) is a not rare abnormality between the atlas C1) and axis C2). Several diseases have been reported to be associated with the occurrence and development of AAS, including inflammatory, congenital, traumatic, and neoplastic processes [ and axis. SeveralFor AAS patients with persistent neck pain and neurologic symptoms, surgical intervention is a good choice. Multiple procedures have been used to stabilize the atlantoaxial joints and achieve spinal cord decompression. These procedures were performed by fixation between C1 and C2 at either a lateral mass , a pedicThis study was approved by our hospital’s ethics committee. From January 2012 to December 2018, a total of 86 cases were admitted to our hospital and diagnosed as AAS. Among them, 53 cases were males and 33 cases were females, with the average age of 52.8 ± 14.3 years (17–83 years). All the patients met the following criteria: 1) complaint of neck pain and varying degrees of neurological defects; 2) radiological findings confirm the presence of AAS and spinal cord compression; 3) all the patients received intraoperative skull traction and atlantoaxial reduction and fixation; 4) all the patients got at least 1- year regular follow-up. Patients without intact follow-up data or follow-up time < 1 year or with atlantoaxial tumor or infection were excluded.All the patients received cervical posteroanterior and lateral radiography, dynamic lateral radiography, three-dimensional CT, computed tomography angiography (CTA) of cervical arteries, and magnetic resonance imaging (MRI) of the cervical spine. The sex, age, pathology, operative time, blood loss, follow-up time and complications were collected in Table After general anesthesia, all the patients were placed in the supine position. Gardner–Wells tongs traction was performed to observe the reduction of AAS Fig. . The ini81 cases achieved satisfactory reduction of AAS, and posterior-only C1-C2 internal fixation and fusion were performed  for at least 2–3 months. For patients with transoral anterior release combined with posterior reduction and fusion, they were needed to be monitored in the intensive care unit for 2–3 days until they were extubated and then transferred to the in-patient ward.Postoperative cervical X-ray and CT scan were performed to evaluate the fixation and reduction at 1 week after the operation and every follow-up. Follow-up were needed at 3-month, 6-month, 1-year after the surgery and then at yearly intervals. Bony fusion was evaluated at the latest follow-up by cervical CT scan. Radiographic parameters preoperatively, postoperatively and at the latest follow-up, including atlas-dens interval (ADI), atlantoaxial height (A-A height), and atlantoaxial angle  . ADI, A-A height, and A-A angle preoperatively and postoperatively, postoperatively and at the latest follow-up were compared using the student’s paired t test. The t-test was used for the comparison and analysis of JOA scores preoperatively and at the latest follow-up. There were 86 cases included in this study. With respect to the etiology, there were 9 cases with rheumatoid arthritis, 3 cases with basilar invagination (BI), 5 cases with old odontoid fractures, 11 cases with os odontoideum, 27 cases with acute cervical trauma, and 33 cases with no specific reasons. Preoperative cervical three-dimensional CT revealed occiput (C0)–C1 fusion in 6 case and Os odontoideum in 11 cases. In these cases, high-riding vertebral artery (HRVA) were found in 3 patients, and 1 patient had bilateral HRVA.Eighty one patients underwent posterior reduction, internal fixation and fusion. 5 patients underwent anterior release, followed by posterior internal fixation and fusion. The mean operative time was 153.9 ± 73.9 min (range 60–385 min), and the mean amount of intraoperative blood loss was 219.1 ± 195.6 mL (range 100-1000 mL). 82 patients got satisfactory postoperative outcomes. Significant neurologic improvement was observed in these patients. Bone fusion was achieved on the midline sagittal reconstructed CT images at the latest follow-up in all these patients except 1 case. All the patients were followed up for 34.84 ± 15.86 months at average (range 12–60 months). The mean ADI value was 7.55 ± 1.67 mm at average preoperatively, and improved to 4.03 ± 1.21 mm postoperatively, and to 4.21 ± 0.99 mm at the latest follow-up. The mean A-A angle was 15.48 ± 9.82 degrees at average preoperatively, and improved to 21.61 ± 10.43 degrees postoperatively, and to 19.73 ± 8.13 degrees at the latest follow-up. The mean A-A height was 35.61 ± 7.66 mm at average preoperatively, and improved to 40.08 ± 8.5 mm postoperatively, and to 38.83 ± 6.97 mm at the latest follow-up. What’s more, the JOA score were 9.6 ± 3.8 preoperatively, and improved to 13.4 ± 3.5 at the latest follow-up, with significant statistical differences. There were significant differences between preoperative and postoperative in the ADI, A-A angle, and A-A height, no significant differences between postoperative and the latest follow-up (Table There were complications in 4 patients. In one patient, C2 pedicle screw misplacement was found on postoperative cervical CT. However, no abnormal symptoms were observed and no revision surgery was done during long-term follow-ups. One patient had breakage of pedicle screw at 4-month after surgery, which needed revision surgery. One patient developed infection after anterior release surgery, and needed repeated wound debridement. One patient died of acute brainstem infarction at two days after surgery.In our study, we retrospectively investigated clinical outcomes of AAS using different fixation methods with the help of intraoperative skull traction. Skull traction has been widely used for cervical bone fracture, scoliosis correction, the reduction of AAS and et al. Skull traction under general anesthesia, in which the utility of neuromuscular blockade can remove the tension of cervical muscle and ligaments and make the reduction easier. Wang et al. reported the utility of skull traction under general anesthesia in the reduction of AAS. 904 cases were included in their study . Among tFor AAS without good reduction with the utility of skull traction under general anesthesia, sufficient release of the dislocated atlantoaxial joint is of key importance for successful treatment. In order to achieve good reduction, various methods had been used for IAAD patients, including transoral odontoidectomy and posterior fixation , transorThe association between the fixation of atlanto-axis and the effect on the alignment of the subaxial cervical spine have attracted people’s attention recently. Yoshimoto H et al. found that when the A-A angle was fixed in an overextended position, the subaxial alignment would correspond to the overextended A-A angle and become kyphotic . Wang etThis study had several limitations. First, this study was a retrospective investigation and was not a randomized case-control study, which may not achieve a strong conclusion. Second, the sample size included in this study was small and this was a single center retrospective study. Third, the etiologies of patients included were multiple. Most of cases included were caused by odontoid fractures, which might attract more attention and limited the results applied to other cases. What’s more, the follow-up time was limited. A longer follow-up, randomized case-control and multi-center study will be needed in the future.AAS can cause neck pain and spinal cord compression, even irreversible neurological deficits. Early diagnosis and appropriate treatment should be performed for this kind of abnormity. Intraoperative skull traction can effectively facilitate the surgical procedures for ASS caused by different etiologies. It can not only effectively facilitate the reduction of ASS, but also make the C1 and C2 stable and easy to be implanted during the operation. Satisfactory clinical outcomes can be achieved for patients with satisfactory reduction with the help of intraoperative skull traction under general anesthesia. Multi-center research and longer follow-up are needed in the future to investigate the safety and effectiveness of this method.