Displaying publications 41 - 60 of 65 in total

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  1. Fulltext Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
    Nhu VH, Mohammadi A, Shahabi H, Ahmad BB, Al-Ansari N, Shirzadi A, et al.
    Int J Environ Res Public Health, 2020 07 08;17(14).
    PMID: 32650595 DOI: 10.3390/ijerph17144933
    We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled using Synthetic Aperture Radar Interferometry, Google Earth images, and field surveys, and 17 conditioning factors (slope, aspect, elevation, distance to road, distance to river, proximity to fault, road density, river density, normalized difference vegetation index, rainfall, land cover, lithology, soil types, curvature, profile curvature, stream power index, and topographic wetness index). We carried out the validation process using the area under the receiver operating characteristic curve (AUC) and several parametric and non-parametric performance metrics, including positive predictive value, negative predictive value, sensitivity, specificity, accuracy, root mean square error, and the Friedman and Wilcoxon sign rank tests. The AB model (AUC = 0.96) performed better than the ensemble AB-ADTree model (AUC = 0.94) and successfully outperformed the ADTree model (AUC = 0.59) in predicting landslide susceptibility. Our findings provide insights into the development of more efficient and accurate landslide predictive models that can be used by decision makers and land-use managers to mitigate landslide hazards.
  2. Fulltext Monitoring and Assessment of Water Level Fluctuations of the Lake Urmia and Its Environmental Consequences Using Multitemporal Landsat 7 ETM+ Images
    Nhu VH, Mohammadi A, Shahabi H, Shirzadi A, Al-Ansari N, Ahmad BB, et al.
    Int J Environ Res Public Health, 2020 06 12;17(12).
    PMID: 32545634 DOI: 10.3390/ijerph17124210
    The declining water level in Lake Urmia has become a significant issue for Iranian policy and decision makers. This lake has been experiencing an abrupt decrease in water level and is at real risk of becoming a complete saline land. Because of its position, assessment of changes in the Lake Urmia is essential. This study aims to evaluate changes in the water level of Lake Urmia using the space-borne remote sensing and GIS techniques. Therefore, multispectral Landsat 7 ETM+ images for the years 2000, 2010, and 2017 were acquired. In addition, precipitation and temperature data for 31 years between 1986 and 2017 were collected for further analysis. Results indicate that the increased temperature (by 19%), decreased rainfall of about 62%, and excessive damming in the Urmia Basin along with mismanagement of water resources are the key factors in the declining water level of Lake Urmia. Furthermore, the current research predicts the potential environmental crisis as the result of the lake shrinking and suggests a few possible alternatives. The insights provided by this study can be beneficial for environmentalists and related organizations working on this and similar topics.
  3. Fulltext Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
    Nhu VH, Shirzadi A, Shahabi H, Singh SK, Al-Ansari N, Clague JJ, et al.
    Int J Environ Res Public Health, 2020 04 16;17(8).
    PMID: 32316191 DOI: 10.3390/ijerph17082749
    Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susceptibility maps that can be used by land-use managers to reduce injury and damage. This paper contributes to this effort by comparing the power and effectiveness of five machine learning, benchmark algorithms-Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine-in creating a reliable shallow landslide susceptibility map for Bijar City in Kurdistan province, Iran. Twenty conditioning factors were applied to 111 shallow landslides and tested using the One-R attribute evaluation (ORAE) technique for modeling and validation processes. The performance of the models was assessed by statistical-based indexes including sensitivity, specificity, accuracy, mean absolute error (MAE), root mean square error (RMSE), and area under the receiver operatic characteristic curve (AUC). Results indicate that all the five machine learning models performed well for shallow landslide susceptibility assessment, but the Logistic Model Tree model (AUC = 0.932) had the highest goodness-of-fit and prediction accuracy, followed by the Logistic Regression (AUC = 0.932), Naïve Bayes Tree (AUC = 0.864), ANN (AUC = 0.860), and Support Vector Machine (AUC = 0.834) models. Therefore, we recommend the use of the Logistic Model Tree model in shallow landslide mapping programs in semi-arid regions to help decision makers, planners, land-use managers, and government agencies mitigate the hazard and risk.
  4. External validation of a modified trauma and injury severity score model in major trauma injury
    Chen WS, Tan JH, Mohamad Y, Imran R
    Injury, 2019 May;50(5):1118-1124.
    PMID: 30591225 DOI: 10.1016/j.injury.2018.12.031
    BACKGROUND: The establishment of an accurate prognostic model in major trauma patients is important mainly because this group of patients will benefit the most. Clinical prediction models must be validated internally and externally on a regular basis to ensure the prediction is accurate and current. This study aims to externally validate two prediction models, the Trauma and Injury Severity Score model developed using the Major Trauma Outcome Study in North America (MTOS-TRISS model), and the NTrD-TRISS model, which is a refined MTOS-TRISS model with coefficients derived from the Malaysian National Trauma Database (NTrD), by regarding mortality as the outcome measurement.

    METHOD: This retrospective study included patients with major trauma injuries reported to a trauma centre of Hospital Sultanah Aminah over a 6-year period from 2011 and 2017. Model validation was examined using the measures of discrimination and calibration. Discrimination was assessed using the area under the receiver operating characteristic curve (AUC) and 95% confidence interval (CI). The Hosmer-Lemeshow (H-L) goodness-of-fit test was used to examine calibration capabilities. The predictive validity of both MTOS-TRISS and NTrD-TRISS models were further evaluated by incorporating parameters such as the New Injury Severity Scale and the Injury Severity Score.

    RESULTS: Total patients of 3788 (3434 blunt and 354 penetrating injuries) with average age of 37 years (standard deviation of 16 years) were included in this study. All MTOS-TRISS and NTrD-TRISS models examined in this study showed adequate discriminative ability with AUCs ranged from 0.86 to 0.89 for patients with blunt trauma mechanism and 0.89 to 0.99 for patients with penetrating trauma mechanism. The H-L goodness-of-fit test indicated the NTrD-TRISS model calibrated as good as the MTOS-TRISS model for patients with blunt trauma mechanism.

    CONCLUSION: For patients with blunt trauma mechanism, both the MTOS-TRISS and NTrD-TRISS models showed good discrimination and calibration performances. Discrimination performance for the NTrD-TRISS model was revealed to be as good as the MTOS-TRISS model specifically for patients with penetrating trauma mechanism. Overall, this validation study has ascertained the discrimination and calibration performances of the NTrD-TRISS model to be as good as the MTOS-TRISS model particularly for patients with blunt trauma mechanism.

  5. Fulltext Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
    Zhang L, Marzuki A, Liao Z, Zhao K, Huang Z, Chen W
    Heliyon, 2023 Aug;9(8):e18570.
    PMID: 37520942 DOI: 10.1016/j.heliyon.2023.e18570
    This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, first, Zhuhai has the greatest potential for growth as the centre of the spatial and temporal evolution trend of the network structure of the tourism economy in Guangdong Province, ahead of Shenzhen, Huizhou, Zhaoqing, Zhongshan, Jiangmen and Dongguan. However, Guangzhou, the capital city of Guangdong Province, is experiencing a decline in such influence and development. Second, there is a counter-trend growth in the number of tourism-related economic links among the 21 cities. Although Guangdong's tourism economic network intensity is strong, there is still room for further optimisation. Third, the results of the overall network indicators show that there is a need for further improvement in network density, grade and efficiency to help reduce the relative development gap of the cities' tourism and effectively improve the overall development of Guangdong's tourism economy. Finally, based on the core-periphery structure, this study proposes relevant suggestions for the sustainable development of Guangdong's tourism industry.
  6. Erratum to "The histology of ovarian cancer: Worldwide distribution and implications for international survival comparisons (CONCORD-2)" [Gynecol. Oncol. 144 (2017) 405-413]
    Matz M, Coleman MP, Sant M, Chirlaque MD, Visser O, Gore M, et al.
    Gynecol Oncol, 2017 Jul 05.
    PMID: 28687170 DOI: 10.1016/j.ygyno.2017.06.032
  7. A New Perspective on Dry Eye Classification: Proposal by the Asia Dry Eye Society
    Tsubota K, Yokoi N, Watanabe H, Dogru M, Kojima T, Yamada M, et al.
    Eye Contact Lens, 2020 Jan;46 Suppl 1:S2-S13.
    PMID: 31425351 DOI: 10.1097/ICL.0000000000000643
    The 2017 consensus report of the Asia Dry Eye Society (ADES) on the definition and diagnosis of dry eyes described dry eye disease as "Dry eye is a multifactorial disease characterized by unstable tear film causing a variety of symptoms and/or visual impairment, potentially accompanied by ocular surface damage." The report emphasized the instability of tear film and the importance of visual dysfunction in association with dry eyes, highlighting the importance of the evaluation of tear film stability. This report also discussed the concept of tear film-oriented therapy, which stemmed from the definition, and which is centered on provision of insufficient components in each tear film layer and ocular surface epithelium. The current ADES report proposes a simple classification of dry eyes based on the concept of tear film-oriented diagnosis and suggests that there are three types of dry eye: aqueous-deficient, decreased wettability, and increased evaporation. It is suggested that these three types respectively coincide with the problems of each layer: aqueous, membrane-associated mucins, and lipid/secretory mucin. Although each component cannot be quantitatively evaluated with the current technology, a practical diagnosis based on the patterns of fluorescein breakup is recommended. The Asia Dry Eye Society classification report suggests that for a practical use of the definition, diagnostic criteria and classification system should be integrated and be simple to use. The classification system proposed by ADES is a straightforward tool and simple to use, only through use of fluorescein, which is available even to non-dry eye specialists, and which is believed to contribute to an effective diagnosis and treatment of dry eyes.
  8. Fulltext Efficacy of early initiation of ivabradine treatment in patients with acute heart failure: rationale and design of SHIFT-AHF trial
    Su Y, Ma T, Wang Z, Dong B, Tai C, Wang H, et al.
    ESC Heart Fail, 2020 Dec;7(6):4465-4471.
    PMID: 32945150 DOI: 10.1002/ehf2.12997
    AIMS: Elevated heart rate (HR) in heart failure (HF) is associated with worse outcomes, particularly in acute HF (AHF). HR reduction with ivabradine reduces cardiovascular events in HF patients with reduced ejection fraction. The present trial aimed to test the hypothesis that the early HR reduction using ivabradine improves clinical outcomes in patients with AHF.

    METHODS AND RESULTS: SHIFT-AHF is a prospective, multi-centre, double-blind, randomized, placebo-controlled trial to evaluate the efficacy and safety of ivabradine when adding to standard therapy in AHF patients (SHIFT-AHF). The trial will include 674 AHF patients with left ventricular ejection fraction 

  9. Luminescent polymorphic aggregates of trinuclear Cu(I)-pyrazolate tuned by intertrimeric CuNPy weak coordination bonds
    Zhan SZ, Chen W, Zheng J, Ng SW, Li D
    Dalton Trans, 2021 Jan 18.
    PMID: 33459321 DOI: 10.1039/d0dt03661g
    Five luminescent polymorphic aggregates of trinuclear Cu(i)-pyrazolate, namely [anti-Cu3L3]2 (1), [syn-Cu3L3·C2H5OH]2 (2), [anti-Cu3L3·C2H5OH]n (3), [anti-Cu3L3·0.5C7H8]n (4) and [syn-Cu3L3·C8H10]n (5) (HL = 4-(pyridin-4-ylthio)-3,5-dimethyl-1H-pyrazole), were reported. The trimeric Cu3L3 fragments present syn- and anti-conformations dependent on the dangled direction of 4-pyridyl groups on the two sides of the Cu3Pz3 plane (Pz = pyrazolate). Intertrimeric NPyCu weak coordination bonds associate these Cu3L3 fragments together to form dimeric or polymeric structures, which are further stabilized by crystallized solvent molecules or intertrimeric CuCu interactions. The solvated complexes (3-5) may be transformed into the unsolvated complex 1 by evacuation of the crystallized solvents upon heating. All these complexes emit from green to yellow under UV irradiation, which originated from the triplet excited states of metal to ligand charge transfer (3MLCT) mixed with intertrimeric CuCu interactions. This work provides a novel kind of supramolecular aggregate based on Cu3Pz3 beyond the classical π-acidbase adducts and metallophilicity-dependent dimers/oligomers.
  10. Fulltext Computer-assisted quantification of CD3+ T cells in follicular lymphoma
    Abas FS, Shana'ah A, Christian B, Hasserjian R, Louissaint A, Pennell M, et al.
    Cytometry A, 2017 06;91(6):609-621.
    PMID: 28110507 DOI: 10.1002/cyto.a.23049
    The advance of high resolution digital scans of pathology slides allowed development of computer based image analysis algorithms that may help pathologists in IHC stains quantification. While very promising, these methods require further refinement before they are implemented in routine clinical setting. Particularly critical is to evaluate algorithm performance in a setting similar to current clinical practice. In this article, we present a pilot study that evaluates the use of a computerized cell quantification method in the clinical estimation of CD3 positive (CD3+) T cells in follicular lymphoma (FL). Our goal is to demonstrate the degree to which computerized quantification is comparable to the practice of estimation by a panel of expert pathologists. The computerized quantification method uses entropy based histogram thresholding to separate brown (CD3+) and blue (CD3-) regions after a color space transformation. A panel of four board-certified hematopathologists evaluated a database of 20 FL images using two different reading methods: visual estimation and manual marking of each CD3+ cell in the images. These image data and the readings provided a reference standard and the range of variability among readers. Sensitivity and specificity measures of the computer's segmentation of CD3+ and CD- T cell are recorded. For all four pathologists, mean sensitivity and specificity measures are 90.97 and 88.38%, respectively. The computerized quantification method agrees more with the manual cell marking as compared to the visual estimations. Statistical comparison between the computerized quantification method and the pathologist readings demonstrated good agreement with correlation coefficient values of 0.81 and 0.96 in terms of Lin's concordance correlation and Spearman's correlation coefficient, respectively. These values are higher than most of those calculated among the pathologists. In the future, the computerized quantification method may be used to investigate the relationship between the overall architectural pattern (i.e., interfollicular vs. follicular) and outcome measures (e.g., overall survival, and time to treatment). © 2017 International Society for Advancement of Cytometry.
  11. Accurate wavelet thresholding method for ECG signals
    Yu K, Feng L, Chen Y, Wu M, Zhang Y, Zhu P, et al.
    Comput Biol Med, 2024 Feb;169:107835.
    PMID: 38096762 DOI: 10.1016/j.compbiomed.2023.107835
    Current wavelet thresholding methods for cardiogram signals captured by flexible wearable sensors face a challenge in achieving both accurate thresholding and real-time signal denoising. This paper proposes a real-time accurate thresholding method based on signal estimation, specifically the normalized ACF, as an alternative to traditional noise estimation without the need for parameter fine-tuning and extensive data training. This method is experimentally validated using a variety of electrocardiogram (ECG) signals from different databases, each containing specific types of noise such as additive white Gaussian (AWG) noise, baseline wander noise, electrode motion noise, and muscle artifact noise. Although this method only slightly outperforms other methods in removing AWG noise in ECG signals, it far outperforms conventional methods in removing other real noise. This is attributed to the method's ability to accurately distinguish not only AWG noise that is significantly different spectrum of the ECG signal, but also real noise with similar spectra. In contrast, the conventional methods are effective only for AWG noise. In additional, this method improves the denoising visualization of the measured ECG signals and can be used to optimize other parameters of other wavelet methods to enhancing the denoised periodic signals, thereby improving diagnostic accuracy.
  12. Fulltext Simulation via instant messaging - Birmingham advance (SIMBA): an innovative simulation-based learning model that helped to keep medical education continue during the COVID-19 pandemic
    Morgan G, Ooi E, Hanania T, Davitadze M, Zhou D, Blaggan P, et al.
    Clin Med (Lond), 2021 Mar;21(Suppl 2):34-35.
    PMID: 34078689 DOI: 10.7861/clinmed.21-2-s34
  13. Fulltext Simulation training using WhatsApp (Sim-thru-WhatsApp) improves doctors' confidence in endocrine and diabetes case management
    Chen W, Kempegowda P, Melson E, Davitadze M, Aftab M, Ooi E, et al.
    Clin Med (Lond), 2020 Mar;20(Suppl 2):s62-s63.
    PMID: 32409381 DOI: 10.7861/clinmed.20-2-s62
  14. Tetracycline removal in granulation: Influence of extracellular polymers substances, structure, and metabolic function of microbial community
    Yan L, Chen W, Wang C, Liu S, Liu C, Yu L, et al.
    Chemosphere, 2022 Feb;288(Pt 2):132510.
    PMID: 34627823 DOI: 10.1016/j.chemosphere.2021.132510
    Tetracycline is a potentially hazardous residual antibiotic detected in various sewages. High concentration (mg/L) of tetracycline is found in pharmaceutical/hospital wastewater and wastewater derived from livestock and poultry. So far, only antibiotics in μg/L level have been reported in granulation of aerobic sludge during wastewater treatment, but its effects in high concentration are rarely reported. In this study, the influence of tetracycline in high concentration (∼2 mg/L) on the formation of granular sludge, structure, and metabolic function of the microbial community during the granulation of aerobic sludge was investigated to improve the understanding of the aerobic granular sludge formation under high-level of tetracycline. The role of extracellular polymers substances (EPSs) derived from granular sludge in the granulation and tetracycline removal process was also investigated, showing that tetracycline improved the relative hydrophobicity, flocculability and protein/polysaccharide ratio of EPSs, accelerating the granulation of sludge. Succession of microbial communities occurred during the domestication of functional bacteria present in the sludge and was accompanied with regulation of metabolic function. The addition of tetracycline lead to an increase of tetracycline-degrading bacteria or antibiotic resistance genus. Those findings provide new perspectives of the influence of tetracycline on aerobic sludge granulation and the removal mechanism of tetracycline.
  15. Fulltext Electroacupuncture ameliorates chronic unpredictable mild stress-induced depression-like behavior and cognitive impairment through suppressing oxidative stress and neuroinflammation in rats
    Tong T, Hao C, Shen J, Liu S, Yan S, Aslam MS, et al.
    Brain Res Bull, 2024 Jan;206:110838.
    PMID: 38123022 DOI: 10.1016/j.brainresbull.2023.110838
    BACKGROUND: Depression is associated with lowered mood, anxiety, anhedonia, cognitive impairments, and even suicidal tendencies in severe cases. Yet few studies have directed acupuncture's mechanism toward enhancing axonal repair correlated with synaptic plasticity and anti-inflammatory effects related to oxidative stress in the hippocampus.

    METHODS: Male Sprague-Dawley (SD) rats were randomly divided into control group (CON), chronic unpredictable mild stress (CUMS) group, CUMS + electroacupuncture group (EA), and CUMS + fluoxetine group (FLX) (n = 10/group). Rats were given a 28-day treatment at the Shangxing (GV23) and Fengfu (GV16) acupoints with electroacupuncture or fluoxetine (2.1 mg/kg).

    RESULTS: Rats exposed to CUMS induced depression-like behaviors and spatial learning-memory impairment, changed the ionized calcium binding adaptor molecule 1 (IBA-1), Vglut1, myelin basic protein (MBP), and postsynaptic density protein 95 (PSD95) level of hippocampal, increased the Nod-like receptor protein 3 (NLRP3), atypical squamous cell (ASC), Caspase level and hippocampal reactive oxygen species (ROS), and prompted the activation of Epha4-mediated signaling and an inflammatory response. Conversely, electroacupuncture administration reduced these changes and prevented depression-like behaviors and cognitive impairment. Electroacupuncture also promoted hippocampal expression of Sirtuin1(SIRT1), Nuclear factor erythroid 2-like (Nrf2), Heme oxygenase-1 (HO-1); reduced the expression of interleukin-1β (IL-1β), interleukin-18 (IL-18), and tumor necrosis factor-alpha (TNF-α); and prevented neural damage, particularly the synaptic myelin sheath, and neuroinflammation by regulating Eph receptor A4 (EphA4) in the hippocampal.

    CONCLUSION: These results indicate that electroacupuncture prevents depression-like behaviors with cognitive impairment and synaptic and neuronal damage, probably by reducing EphA4, which mediates ROS hyperfunction and the inflammatory response.

  16. Fulltext Acupuncture alleviates CUMS-induced depression-like behaviors of rats by regulating oxidative stress, neuroinflammation and ferroptosis
    Shen J, Hao C, Yuan S, Chen W, Tong T, Chen Y, et al.
    Brain Res, 2024 Mar 01;1826:148715.
    PMID: 38142722 DOI: 10.1016/j.brainres.2023.148715
    BACKGROUND: The treatment of depression with acupuncture has been documented. The mechanism behind acupuncture's curative and preventative effects is still unknown.

    METHODS: The current study examined the effects of acupuncture on depression-like behaviors in a rat model of chronic unpredictable mild stress (CUMS), while also exploring its potential mechanisms. A total of six groups of rats were randomly assigned: control, CUMS, acupuncture, fluoxetine, acupoint catgut embedding and sham acupoint catgut embedding. Fluoxetine (2.1 mg/kg) and acupoint catgut embedding were used for comparative research to acupuncture. The modelling evaluation is measured by body weight and behavior tests. Western blotting and reverse transcription-polymerase chain reaction were used to detect the proteins and mRNA expression of Silent information regulator 1 (Sirt1)/ nuclear factor-erythroid 2-related factor 2 (Nrf2)/ heme oxygenase-1 (HO-1)/ Glutathione peroxidase 4 (GPX4) pathway in the hippocampus. The expression of oxidative stress (OS)-related proteins and inflammatory cytokines in the serum was detected with ELISA. Immunofluorescence showed microglia and astrocytes activity in the hippocampus.

    RESULTS: Acupuncture and fluoxetine could alleviate CUMS-induced depression-like behaviors. Acupuncture was also found to effectively reverse the levels of MDA, SOD, GSH, GSH-PX and T-AOC, IL-1β, IL-6 and TNF-α in the serum of CUMS-induced rats. Rats with CUMS showed decreased levels of Sirt1, Nrf2, HO-1 and GPX4 in the hippocampus, while acupuncture treatment could partly reverse the diminished effects. In addition, acupuncture treatment significantly reduced the activation of hippocampal microglia and astrocytes in CUMS-induced rats.

    CONCLUSION: The study's findings indicate that acupuncture has the potential to mitigate depression-like behaviors in rats induced with CUMS by mitigating OS and reducing neuroinflammation.

  17. The effect of acupuncture on lateral habenular nucleus and intestinal microflora in depression model rats
    Chen W, Chen Y, Aslam MS, Shen J, Tong T, Yan S, et al.
    Behav Brain Res, 2023 Oct 18;455:114627.
    PMID: 37619770 DOI: 10.1016/j.bbr.2023.114627
    BACKGROUND: Depression is a severe emotional condition that significantly affects the quality of life. Acupuncture exerts preventive effects on depression in rats with post-chronic unpredictable mild stress (CUMS). Methods The study involved chronic unpredictable mild stress (CUMS) depression model mice to administer acupuncture as a preventative measure to investigate the mechanism of acupuncture's antidepressant and observe the effect of acupuncture on impact via the Lateral Habenula (LHb) and Gut-Liver-Brain Axis. The researcher investigated molecules correlating with a nitric oxide/cyclic guanosine monophosphate (NO/cGMP) pathway and assessed inflammation in the LHb and liver. In addition, 16 S rDNA bioinformatics study revealed the quantity and variety of gut microbiota. Rats were randomly divided into five groups: control (CON), CUMS, CUMS + acupuncture (AP), CUMS + fluoxetine (FX) and CUMS + N(G) -nitro -L- arginine methyl ester (LNAME) group. Except for the CON group, other rats were exposed to CUMS condition for 28 days. Simultaneously, manual acupuncture (at Fengfu and Shangxing acupoints, once every other day) and fluoxetine gavage (2.1 mg/kg, 0.21 mg/mL, daily) were conducted to the groups of AP and FX, respectively, after stressors. Rats in LNAME group were treated with LNAME normal saline (10 mg/kg, 1 mg/mL, i.p.) solution. Behavioural tests and biological detection methods were conducted sequentially to evaluate depressionlike phenotype in rats.

    RESULTS: The results showed CUMS induced depression-like behaviours, hyper-activation of NO/cGMP signaling pathway, inflammation in serum, LHb and liver, and dysbiosis of the gut microbiota. These changes could be prevented and ameliorated by acupuncture to varying extents.

    CONCLUSION: Acupuncture prevented and attenuated depression-like phenotype induced by CUMS, possibly via regulating the NO/cGMP signaling pathway and thus improving inflammation in serum, LHb and liver, and gut microbiota dysbiosis. In addition, these can be evidence of the existence of the gut-liver-brain axis.

  18. Fulltext Distribution of axial length, anterior chamber depth, and corneal curvature in an aged population in South China
    Chen H, Lin H, Lin Z, Chen J, Chen W
    BMC Ophthalmol, 2016 May 01;16(1):47.
    PMID: 27138378 DOI: 10.1186/s12886-016-0221-5
    BACKGROUND: Ocular biometry is important for preoperative assessment in cataract and anterior segment surgery. The purpose of this study was to investigate normative ocular biometric parameters and their associations in an older Chinese population.

    METHODS: This was a cross-sectional observational study. From 2013 to 2014, we recruited inhabitants aged 50 years or older in Guangzhou, China. Among 1,117 participants in the study, data from 1,015 phakic right eyes were used for analyses. Ocular parameters including axial length (AL), anterior chamber depth (ACD), and corneal curvature (K) were measured using an IOL Master.

    RESULTS: The mean AL, ACD, and K were 23.48 mm [95 % confidence interval (CI), 23.40-23.55], 3.03 mm (CI, 3.01-3.05), and 44.20 mm (CI, 44.11-44.29), respectively. A mean reduction in ACD with age was observed (P = 0.002) in male subjects but not in female subjects (P = 0.558). Male subjects had significantly longer ALs (23.68 mm versus 23.23 mm, P 

  19. Fulltext Classification of follicular lymphoma: the effect of computer aid on pathologists grading
    Fauzi MF, Pennell M, Sahiner B, Chen W, Shana'ah A, Hemminger J, et al.
    BMC Med Inform Decis Mak, 2015;15:115.
    PMID: 26715518 DOI: 10.1186/s12911-015-0235-6
    Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL cases are stratified into three histological grades based on the average centroblast count per high power field (HPF). The centroblast count is performed manually by the pathologist using an optical microscope and hematoxylin and eosin (H&E) stained tissue section. Although this is the current clinical practice, it suffers from high inter- and intra-observer variability and is vulnerable to sampling bias.
  20. Fulltext Simulation via instant messaging-Birmingham advance (SIMBA) model helped improve clinicians' confidence to manage cases in diabetes and endocrinology
    Melson E, Davitadze M, Aftab M, Ng CY, Ooi E, Blaggan P, et al.
    BMC Med Educ, 2020 Aug 18;20(1):274.
    PMID: 32811488 DOI: 10.1186/s12909-020-02190-6
    BACKGROUND: Simulation-based learning (SBL) has been increasingly used in both undergraduate and postgraduate medical training curricula. The aim of Simulation via Instant Messaging-Birmingham Advance (SIMBA) is to create a simple virtual learning environment to improve trainees' self-reported confidence in diabetes and Endocrinology.

    METHODS: This study was done as part of the continuous professional development for Health Education England West Midlands speciality trainees in diabetes and Endocrinology. Standardized transcripts of anonymized real-life endocrinology (endocrine session) and diabetes cases (diabetes session) were used in the simulation model. Trainees interacted with moderators through WhatsApp® in this model. All cases were then discussed in detail by a consultant endocrinologist with reference to local, national and international guidelines. Trainee acceptance rate and improvement in their self-reported confidence levels post-simulation were assessed.

    RESULTS: 70.8% (n = 17/24) and 75% (n = 18/24) strongly agreed the simulation session accommodated their personal learning style and the session was engaging. 66.7% (n = 16/24) strongly felt that the simulation was worth their time. In the endocrine session, there was a significant improvement in trainees' confidence in the management of craniopharyngioma (p = 0.0179) and acromegaly (p = 0.0025). There was a trend towards improved confidence levels to manage Cushing's disease and macroprolactinoma. In diabetes session, there was a significant improvement in trainees' confidence to interpret continuous glucose monitor readings (p = 0.01). There was a trend towards improvement for managing monogenic diabetes, hypoglycaemic unawareness and interpreting Libre readings. Overall, there was a significant improvement in trainees' confidence in managing cases that were discussed post-simulation.

    CONCLUSION: SIMBA is an effective learning model to improve trainees' confidence to manage various diabetes and endocrine case scenarios. More sessions with a variety of other speciality case scenarios are needed to further assess SIMBA's effectiveness and application in other areas of medical training.

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