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Temporal and spatial convergence: the major depressive disorder burden attributed to intimate partner violence against women

Guo P, Wang R, Li J, Qin Y, Meng N, Shan L, et al.

Eur J Psychotraumatol, 2024;15(1):2386226.
PMID: 39355978 DOI: 10.1080/20008066.2024.2386226

Background: There is a strong causal relationship between intimate partner violence and major depressive disorder, which partly endangers women's safety across the life course and potentially affects the development of future generations. The international community has placed a high priority on addressing the intimate partner violence and the resulting burden of mental illness. Data collection needs to be captured across the temporal trend and spatial distribution for major depressive disorder attributed to intimate partner violence, to reflect the priorities and expectations of survivors.Method: This research obtained raw disability-adjusted life years (DALYs) information for major depressive disorder attributed to intimate partner violence from the Global Burden of Disease 2019. Using estimated annual percentage change and two-way fixed effects models, a secondary spatio-temporal analysis of the age-standardized DALYs rate from 1990 to 2019 was performed.Results: In 2019, DALYs lost among women experiencing major depressive disorder (3.16 million) accounted for 37.18% of the DALYs lost worldwide due to intimate partner violence. The age-standardized DALYs rate of major depressive disorder attributed to intimate partner violence was 108.57 per 100,000. The highest was concentrated in the menopausal transition (45-55), with 133.61 per 100,000, and particularly distributed in Uganda (429.31 per 100,000). The early reproductive period (15-19) showed the increasing age-standardized DALYs rate from 1990 to 2019, which was mainly driven by Malaysia (3.73% per year). Furthermore, countries with higher initial levels of the age-standardized DALYs rate were growing faster than those with lower levels.Conclusions: The burden of major depressive disorder attributed to intimate partner violence showed biological and spatial inequality, prioritized intervention should be targeted at vulnerable stage women in their early reproductive period and menopausal transition. Combined political, socio-cultural as well as medical measures to prevent violence and treat major depressive disorder should be implemented and developed.
Fulltext Potential Roles of Selectins in Periodontal Diseases and Associated Systemic Diseases: Could They Be Targets for Immunotherapy?

Zhong M, Huang J, Wu Z, Chan KG, Wang L, Li J, et al.

Int J Mol Sci, 2022 Nov 18;23(22).
PMID: 36430760 DOI: 10.3390/ijms232214280

Periodontal diseases are predisposing factors to the development of many systemic disorders, which is often initiated via leukocyte infiltration and vascular inflammation. These diseases could significantly affect human health and quality of life. Hence, it is vital to explore effective therapies to prevent disease progression. Periodontitis, which is characterized by gingival bleeding, disruption of the gingival capillary's integrity, and irreversible destruction of the periodontal supporting bone, appears to be caused by overexpression of selectins in periodontal tissues. Selectins (P-, L-, and E-selectins) are vital members of adhesion molecules regulating inflammatory and immune responses. They are mainly located in platelets, leukocytes, and endothelial cells. Furthermore, selectins are involved in the immunopathogenesis of vascular inflammatory diseases, such as cardiovascular disease, diabetes, cancers, and so on, by mediating leukocyte recruitment, platelet activation, and alteration of endothelial barrier permeability. Therefore, selectins could be new immunotherapeutic targets for periodontal disorders and their associated systemic diseases since they play a crucial role in immune regulation and endothelium dysfunction. However, the research on selectins and their association with periodontal and systemic diseases remains limited. This review aims to discuss the critical roles of selectins in periodontitis and associated systemic disorders and highlights the potential of selectins as therapeutic targets.
Fortunefuroic Acid J from Keteleeria hainanensis and Its Dual Inhibitory Effects on ATP-Citrate Lyase and Acetyl-CoA Carboxylase

Zhao ZY, Zang Y, Li J, Choo YM, Xiong J, Hu J

Chem Biodivers, 2024 Sep 02.
PMID: 39221607 DOI: 10.1002/cbdv.202401520

A previously undescribed triterpenoid (fortunefuroic acid J, 1) was isolated from the endangered conifer Keteleeria hainanensis, along with 20 other known terpenoids. Compound 1 is characterized by an unusual 3,4-seco-9βH-lanost-3-oic acid motif, featuring a rare furoic acid moiety in its lateral chain. The structure elucidation of this compound was achieved through a combination of spectroscopic and computational methods. The C-15 epimers of 15-methoxypinusolidic acid (15R-8 and 15S-9) were successfully separated and identified for the first time. Compound 1 demonstrated dual inhibitory effects against ATP-citrate lyase (ACL, IC50: 0.92 μM) and acetyl-CoA carboxylase 1 (ACC1, IC50: 10.76 μM). Compounds 2 and 11 exclusively inhibited ACL, exhibiting IC50 values of 2.64 and 6.35 μM, respectively. Compound 1 is classified among the fortunefuroic acid-type compounds, previously isolated from K. fortunei, distinguished by the presence of a rare furoic acid moiety in their lateral chain. The chemotaxonomic significance of the 9βH-lanost-26-oic acids in Keteleeria was briefly discussed. These findings highlight the importance of conserving plant species diversity, thereby enhancing the exploration of structurally diverse compounds and potential avenues for developing new therapeutics targeting ACL/ACC1-associated diseases.
The development of a digital intelligence quotient scale: A new measuring instrument for primary school students in China

Li J, Ju SY, Zhu C, Yuan Y, Fu M, Kong LK, et al.

Heliyon, 2024 Aug 30;10(16):e36437.
PMID: 39253112 DOI: 10.1016/j.heliyon.2024.e36437

The development of a Digital Intelligence Quotient (DQ) scale for primary school students is the basis for research on the DQ of primary school students, which helps to scientifically diagnose the level and the current average DQ among Chinese primary school students. This study developed and validated a scale applicable to the assessment of DQ in Chinese primary school students where, the initial scale was first constructed; Then 1109 valid datasets were collected through purposive sampling and divided into Sample A and Sample B; Sample A was subjected to exploratory factor analysis and Sample B was tested by confirmatory factor analysis; The final validated scale consists of 22 items in 7 dimensions: digital identity, digital use, digital safety, digital security, digital emotional intelligence, digital literacy and digital rights. The scale has high reliability and validity and thus can be used as a reliable instrument for assessing DQ in Chinese primary school students.
Abundance of microplastics and its ecological risk assessment in coral reef regions of Peninsular Malaysia

Lim KP, Sun C, Yusoff S, Ding J, Loh KH, Li J, et al.

Mar Pollut Bull, 2024 Dec;209(Pt A):117112.
PMID: 39406069 DOI: 10.1016/j.marpolbul.2024.117112

Microplastic contamination is an emerging concern in marine ecosystems, with limited knowledge on its impact on coral reefs, particularly in Malaysia. Surface waters were collected from several coral reef regions in Peninsular Malaysia by towing a plankton net behind the boat. Microplastics were detected at all sites, with a mean abundance of 0.344 ± 0.457 MP/m3. Perhentian Islands (0.683 ± 0.647 MP/m3) had significantly higher microplastic levels than Tioman Island (0.108 ± 0.063 MP/m3), likely due to oceanographic differences. Over half of the microplastics (55.7 %) were small microplastics (<1 mm), with the 0.05-0.5 mm size class being most abundant (29.2 %). Fragments and fibres dominated, and black, blue, and green were the prevalent colours. Polyethylene (PE), rayon (RY), chlorinated polyethylene (CPE), and polypropylene (PP) were the most common polymers. This study reveals the abundance and characteristics of microplastics, provides important data for further research on microplastics in coral reef ecosystem.
Structural and gel property changes in chicken myofibrillar protein induced by argon cold plasma-activated water: With a molecular docking perspective

Li J, Rao W, Sun Y, Zhou C, Xia Q, He J, et al.

Food Res Int, 2024 Dec;197(Pt 1):115271.
PMID: 39593348 DOI: 10.1016/j.foodres.2024.115271

This study investigated the effects of plasma-activated water (PAW) generated with argon at discharge times of 0, 4, 8, 12, and 16 min on the gel properties and structures of chicken myofibrillar protein (MP). Under treatments of 8, 12, and 16 min, both the gel strength and water retention capacity of MP significantly improved, with the gel strength (0.53 N) peaking at 16 min and the lowest cooking loss（30.38 %）. As the treatment time increased from 0 to 16 min, the storage modulus also gradually increased. Results from low-field nuclear magnetic resonance indicated a slowing of water proton mobility, with the proportion of bound water rising from 0.26 % (0 min) to 0.52 % at 16 min. Fourier transform infrared spectroscopy, endogenous fluorescence spectroscopy and scanning electron microscopy confirmed PAW's alteration of MP's secondary and tertiary structures and gel microstructure. Additionally, this study explored the influence of argon PAW's primary active species on MP from a molecular docking perspective·H2O2 could form hydrogen bonds with MP, while O3 and NO2‾could interact via both hydrogen bonds and electrostatic interactions. Thus, PAW can alter protein structure and enhance MP's functional properties, providing insights for applying cold plasma in processing chicken gel products.
Fulltext An efficient personalized federated learning approach in heterogeneous environments: a reinforcement learning perspective

Yang H, Li J, Hao M, Zhang W, He H, Sangaiah AK

Sci Rep, 2024 Nov 21;14(1):28877.
PMID: 39572631 DOI: 10.1038/s41598-024-80048-3

In order to address the problem of data heterogeneity, in recent years, personalized federated learning has tailored models to individual user data to enhance model performance on clients with diverse data distributions. However, the existing personalized federated learning methods do not adequately address the problem of data heterogeneity, and lack the processing of system heterogeneity. Consequently, these issues lead to diminished training efficiency and suboptimal model performance of personalized federated learning in heterogeneous environments. In response to these challenges, we propose FedPRL, a novel approach to personalized federated learning designed specifically for heterogeneous environments. Our method tackles data heterogeneity by implementing a personalized strategy centered on local data storage, enabling the accurate extraction of features tailored to the data distribution of individual clients. This personalized approach enhances the performance of federated learning models when dealing with non-IID data. To overcome system heterogeneity, we design a client selection mechanism grounded in reinforcement learning and user quality evaluation. This mechanism optimizes the selection of clients based on data quality and training time, thereby boosting the efficiency of the training process and elevating the overall performance of personalized models. Moreover, we devise a local training method that utilizes global knowledge distillation of non-target classes, which combined with traditional federated learning can effectively address the issue of catastrophic forgetting during global model updates. This approach enhances the generalization capability of the global model and further improves the performance of personalized models. Extensive experiments on both standard and real-world datasets demonstrate that FedPRL effectively resolves the challenges of data and system heterogeneity, enhancing the efficiency and model performance of personalized federated learning methods in heterogeneous environments, and outperforming state-of-the-art methods in terms of model accuracy and training efficiency.
Polychlorinated biphenyls (PCBs) and hexachlorobenzene (HCB) in the equatorial Indian Ocean: temporal trend, continental outflow and air-water exchange

Huang Y, Li J, Xu Y, Xu W, Cheng Z, Liu J, et al.

Mar Pollut Bull, 2014 Mar 15;80(1-2):194-9.
PMID: 24462236 DOI: 10.1016/j.marpolbul.2014.01.007

Nineteen pairs of air and seawater samples collected from the equatorial Indian Ocean onboard the Shiyan I from 4/2011 to 5/2011 were analyzed for PCBs and HCB. Gaseous concentrations of ∑(ICES)PCBs (ICES: International Council for the Exploration of the Seas) and HCB were lower than previous data over the study area. Air samples collected near the coast had higher levels of PCBs relative to those collected in the open ocean, which may be influenced by proximity to source regions and air mass origins. Dissolved concentrations of ∑(ICES)PCBs and HCB were 1.4-14 pg L⁻¹ and 0.94-13 pg L⁻¹, with the highest concentrations in the sample collected from Strait of Malacca. Fugacity fractions suggest volatilization of PCBs and HCB from the seawater to air during the cruise, with fluxes of 0.45-34 ng m⁻² d⁻¹ and 0.36-18 ng m⁻² d⁻¹, respectively.
The role of the quality assessment in the determination of overall biosimilarity: a simulated case study exercise

Schiestl M, Li J, Abas A, Vallin A, Millband J, Gao K, et al.

Biologicals, 2014 Mar;42(2):128-32.
PMID: 24373974 DOI: 10.1016/j.biologicals.2013.11.009

A determination of biosimilarity is based on a thorough characterization and comparison of the quality profiles of a similar biotherapeutic product and its reference biotherapeutic product. Although the general principles on the role of the quality assessment in a biosimilar evaluation are widely understood and agreed, detailed discussions have not been published yet. We try to bridge this gap by presenting a case study exercise based on fictional but realistic data to highlight key principles of an evaluation to determine the degree of similarity at the quality level. The case study comprises three examples for biosimilar monoclonal antibody candidates. The first describes a highly similar quality profile whereas the second and third show greater differences to the reference biotherapeutic product. The aim is to discuss whether the presented examples can be qualified as similar and which additional studies may be helpful in enabling a final assessment. The case study exercise was performed at the WHO implementation workshop for the WHO guidelines on quality assessment of similar biotherapeutic products held in Xiamen, China, in May 2012. The goal was to illustrate the interpretation of the comparative results at the quality level, the role of the quality assessment in the entire biosimilarity exercise and its influence on the clinical evaluation. This paper reflects the outcome of the exercise and discussion from Xiamen.
Screening for microsatellite instability in colorectal carcinoma: Practical utility of immunohistochemistry and PCR with fragment analysis in a diagnostic histopathology setting

Cheah PL, Li J, Looi LM, Koh CC, Lau TP, Chang SW, et al.

Malays J Pathol, 2019 Aug;41(2):91-100.
PMID: 31427545

Since 2014, the National Comprehensive Cancer Network (NCCN) has recommended that colorectal carcinoma (CRC) be universally tested for high microsatellite instability (MSI-H) which is present in 15% of such cancers. Fidelity of resultant microsatellites during DNA replication is contingent upon an intact mismatch repair (MMR) system and lack of fidelity can result in tumourigenesis. Prior to commencing routine screening for MSI-H, we assessed two commonly used methods, immunohistochemical (IHC) determination of loss of MMR gene products viz MLH1, MSH2, MSH6 and PMS2 against PCR amplification and subsequent fragment analysis of microsatellite markers, BAT25, BAT26, D2S123, D5S346 and D17S250 (Bethesda markers) in 73 unselected primary CRC. 15.1% (11/73) were categorized as MSI-H while deficient MMR (dMMR) was detected in 16.4% (12/73). Of the dMMR, 66.7% (8/12) were classified MSI-H, while 33.3% (4/12) were microsatellite stable/low microsatellite instability (MSS/MSI-L). Of the proficient MMR (pMMR), 95.1% (58/61) were MSS/MSI-L and 4.9% (3/61) were MSI-H. The κ value of 0.639 (standard error =0.125; p = 0.000) indicated substantial agreement between detection of loss of DNA mismatch repair using immunohistochemistry and the detection of downstream microsatellite instability using PCR. After consideration of advantages and shortcomings of both methods, it is our opinion that the choice of preferred technique for MSI analysis would depend on the type of laboratory carrying out the testing.
Classification of ERP signal from amnestic mild cognitive impairment with type 2 diabetes mellitus using single-scale multi-input convolution neural network

Wen D, Cheng Z, Li J, Zheng X, Yao W, Dong X, et al.

J Neurosci Methods, 2021 Nov 01;363:109353.
PMID: 34492241 DOI: 10.1016/j.jneumeth.2021.109353

BACKGROUND: The application of deep learning models to electroencephalogram (EEG) signal classification has recently become a popular research topic. Several deep learning models have been proposed to classify EEG signals in patients with various neurological diseases. However, no effective deep learning model for event-related potential (ERP) signal classification is yet available for amnestic mild cognitive impairment (aMCI) with type 2 diabetes mellitus (T2DM).
METHOD: This study proposed a single-scale multi-input convolutional neural network (SSMICNN) method to classify ERP signals between aMCI patients with T2DM and the control group. Firstly, the 18-electrode ERP signal on alpha, beta, and theta frequency bands was extracted by using the fast Fourier transform, and then the mean, sum of squares, and absolute value feature of each frequency band were calculated. Finally, these three features are converted into multispectral images respectively and used as the input of the SSMICNN network to realize the classification task.
RESULTS: The results show that the SSMICNN can fuse MSI formed by different features, SSMICNN enriches the feature quantity of the neural network input layer and has excellent robustness, and the errors of SSMICNN can be simultaneously transmitted to the three convolution channels in the back-propagation phase. Comparison with Existing Method(s): SSMICNN could more effectively identify ERP signals from aMCI with T2DM from the control group compared to existing classification methods, including convolution neural network, support vector machine, and logistic regression.
CONCLUSIONS: The combination of SSMICNN and MSI can be used as an effective biological marker to distinguish aMCI patients with T2DM from the control group.
Synthesis and biological evaluation of indole core-based derivatives with potent antibacterial activity against resistant bacterial pathogens

Hong W, Li J, Chang Z, Tan X, Yang H, Ouyang Y, et al.

J Antibiot (Tokyo), 2017 Jul;70(7):832-844.
PMID: 28465626 DOI: 10.1038/ja.2017.55

The emergence of drug resistance in bacterial pathogens is a growing clinical problem that poses difficult challenges in patient management. To exacerbate this problem, there is currently a serious lack of antibacterial agents that are designed to target extremely drug-resistant bacterial strains. Here we describe the design, synthesis and antibacterial testing of a series of 40 novel indole core derivatives, which are predicated by molecular modeling to be potential glycosyltransferase inhibitors. Twenty of these derivatives were found to show in vitro inhibition of Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus. Four of these strains showed additional activity against Gram-negative bacteria, including extended-spectrum beta-lactamase producing Enterobacteriaceae, imipenem-resistant Klebsiella pneumoniae and multidrug-resistant Acinetobacter baumanii, and against Mycobacterium tuberculosis H37Ra. These four compounds are candidates for developing into broad-spectrum anti-infective agents.
Fulltext Hard rock landforms generate 130 km ice shelf channels through water focusing in basal corrugations

Jeofry H, Ross N, Le Brocq A, Graham AGC, Li J, Gogineni P, et al.

Nat Commun, 2018 11 01;9(1):4576.
PMID: 30385741 DOI: 10.1038/s41467-018-06679-z

Satellite imagery reveals flowstripes on Foundation Ice Stream parallel to ice flow, and meandering features on the ice-shelf that cross-cut ice flow and are thought to be formed by water exiting a well-organised subglacial system. Here, ice-penetrating radar data show flow-parallel hard-bed landforms beneath the grounded ice, and channels incised upwards into the ice shelf beneath meandering surface channels. As the ice transitions to flotation, the ice shelf incorporates a corrugation resulting from the landforms. Radar reveals the presence of subglacial water alongside the landforms, indicating a well-organised drainage system in which water exits the ice sheet as a point source, mixes with cavity water and incises upwards into a corrugation peak, accentuating the corrugation downstream. Hard-bedded landforms influence both subglacial hydrology and ice-shelf structure and, as they are known to be widespread on formerly glaciated terrain, their influence on the ice-sheet-shelf transition could be more widespread than thought previously.
Multi-dimensional conditional mutual information with application on the EEG signal analysis for spatial cognitive ability evaluation

Wen D, Li R, Jiang M, Li J, Liu Y, Dong X, et al.

Neural Netw, 2021 Dec 25;148:23-36.
PMID: 35051867 DOI: 10.1016/j.neunet.2021.12.010

This study aims to explore an effective method to evaluate spatial cognitive ability, which can effectively extract and classify the feature of EEG signals collected from subjects participating in the virtual reality (VR) environment; and evaluate the training effect objectively and quantitatively to ensure the objectivity and accuracy of spatial cognition evaluation, according to the classification results. Therefore, a multi-dimensional conditional mutual information (MCMI) method is proposed, which could calculate the coupling strength of two channels considering the influence of other channels. The coupled characteristics of the multi-frequency combination were transformed into multi-spectral images, and the image data were classified employing the convolutional neural networks (CNN) model. The experimental results showed that the multi-spectral image transform features based on MCMI are better in classification than other methods, and among the classification results of six band combinations, the best classification accuracy of Beta1-Beta2-Gamma combination is 98.3%. The MCMI characteristics on the Beta1-Beta2-Gamma band combination can be a biological marker for the evaluation of spatial cognition. The proposed feature extraction method based on MCMI provides a new perspective for spatial cognitive ability assessment and analysis.
Biochar-based solid acid accelerated carbon conversion by increasing the abundance of thermophilic bacteria in the cow manure composting process

Zhu P, Li J, Wen X, Huang Y, Yang H, Wang S, et al.

J Environ Manage, 2022 Feb 07;308:114682.
PMID: 35144065 DOI: 10.1016/j.jenvman.2022.114682

This study investigated the effects of biochar-based solid acids (SAs) on carbon conversion, alpha diversity and bacterial community succession during cow manure composting with the goal of providing a new strategy for rapid carbon conversion during composting. The addition of SA prolonged the thermophilic phase and accelerated the degradation of lignocellulose; in particular, the degradation time of cellulose was shortened by 50% and the humus content was increased by 22.56% compared with the control group (CK). In addition, high-throughput sequencing results showed that SA improved the alpha diversity and the relative abundance of thermophilic bacteria, mainly Actinobacteria, increased by 12.955% compared with CK. A redundancy analysis (RDA) showed that Actinobacteria was positively correlated with the transformation of carbon.
The Effective Cognitive Assessment and Training Methods for COVID-19 Patients With Cognitive Impairment

Wen D, Xu J, Wu Z, Liu Y, Zhou Y, Li J, et al.

Front Aging Neurosci, 2021;13:827273.
PMID: 35087399 DOI: 10.3389/fnagi.2021.827273
17β-estradiol suppresses H2O2-induced senescence in human umbilical vein endothelial cells by inducing autophagy through the PVT1/miR-31/SIRT3 axis

Xiang X, Wang Y, Huang G, Huang J, Gao M, Sun M, et al.

J Steroid Biochem Mol Biol, 2023 Mar;227:106244.
PMID: 36584773 DOI: 10.1016/j.jsbmb.2022.106244

OBJECTIVE: 17β-estradiol (17β-E2) has been implicated in activating autophagy by upregulating SIRT3 (Sirtuin 3) expression, thereby inhibiting the senescence of vascular endothelial cells. Herein, we further examined the molecular mechanisms that regulate SIRT3 expression in 17β-E2-induced autophagy.
METHODS: Reverse-transcription-polymerase chain reaction was employed to measure the expression of plasmacytoma variant translocation 1 (PVT1), microRNAs (miRNAs), and SIRT3, and the dual-luciferase assay was used to determine their interaction. Electron microscopy observes autophagosomes, green fluorescent protein-microtubule-associated protein 1 light chain 3 (GFP-LC3) staining, and immunoblot analysis with antibodies against LC3，beclin-1, and P62 were conducted to measure autophagy. Cellular senescence was determined using immunoblot analysis with anti-phosphorylated retinoblastoma and senescence-associated β-galactosidase staining.
RESULTS: Women with higher estrogen levels (during the 10-13th day of the menstrual cycle or premenopausal) exhibit markedly higher serum levels of PVT1 than women with lower estrogen levels (during the menstrual period or postmenopausal). The dual-luciferase assay showed that PVT1 acts as a sponge for miR-31, and miR-31 binds to its target gene, SIRT3. The 17β-E2 treatment increased the expression of PVT1 and SIRT3 and downregulated miR-31 expression in human umbilical vein endothelial cells (HUVECs). Consistently, PVT1 overexpression suppresses miR-31 expression, promotes 17β-E2-induced autophagy, and inhibits H2O2-induced senescence. miR-31 inhibitor increases SIRT3 expression and leads to activation of 17β-E2-induced autophagy and suppression of H2O2-induced senescence.
CONCLUSION: Our findings demonstrated that 17β-E2 upregulates PVT1 gene expression and PVT1 functions as a sponge to inhibit miR-31, resulting in the upregulation of SIRT3 expression and activation of autophagy and subsequent inhibition of H2O2-induced senescence in HUVECs.
Fulltext Performance of the CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equations in a multiethnic Asian population

Teo BW, Koh YY, Toh QC, Li J, Sinha AK, Shuter B, et al.

Singapore Med J, 2014 Dec;55(12):656-9.
PMID: 25630321

INTRODUCTION: Clinical practice guidelines recommend using creatinine-based equations to estimate glomerular filtration rates (GFRs). While these equations were formulated for Caucasian-American populations and have adjustment coefficients for African-American populations, they are not validated for other ethnicities. The Chronic Kidney Disease-Epidemiology Collaborative Group (CKD-EPI) recently developed a new equation that uses both creatinine and cystatin C. We aimed to assess the accuracy of this equation in estimating the GFRs of participants (healthy and with chronic kidney disease [CKD]) from a multiethnic Asian population.

METHODS: Serum samples from the Asian Kidney Disease Study and the Singapore Kidney Function Study were used. GFR was measured using plasma clearance of 99mTc-DTPA. GFR was estimated using the CKD-EPI equations. The performance of GFR estimation equations were examined using median and interquartile range values, and the percentage difference from the measured GFR.

RESULTS: The study comprised 335 participants (69.3% with CKD; 38.5% Chinese, 29.6% Malays, 23.6% Indians, 8.3% others), with a mean age of 53.5 ± 15.1 years. Mean standardised serum creatinine was 127 ± 86 μmol/L, while mean standardised serum cystatin C and mean measured GFR were 1.43 ± 0.74 mg/L and 67 ± 33 mL/min/1.73 m2, respectively. The creatinine-cystatin C CKD-EPI equation performed the best, with an estimated GFR of 67 ± 35 mL/min/1.73 m2.

CONCLUSION: The new creatinine-cystatin C equation estimated GFR with little bias, and had increased precision and accuracy in our multiethnic Asian population. This two-biomarker equation may increase the accuracy of population studies on CKD, without the need to consider ethnicity.
Corrigendum to "17β-estradiol suppresses H2O2-induced senescence in human umbilical vein endothelial cells by inducing autophagy through the PVT1/miR-31/SIRT3 axis" [J. Steroid Biochem. Mol. Biol. 227 (2023) 106244]

Xiang X, Wang Y, Huang G, Huang J, Gao M, Sun M, et al.

J Steroid Biochem Mol Biol, 2023 May;229:106277.
PMID: 36893556 DOI: 10.1016/j.jsbmb.2023.106277
An evaluation framework for quantifying vegetation loss and recovery in response to meteorological drought based on SPEI and NDVI

Wu C, Zhong L, Yeh PJ, Gong Z, Lv W, Chen B, et al.

Sci Total Environ, 2024 Jan 01;906:167632.
PMID: 37806579 DOI: 10.1016/j.scitotenv.2023.167632

Drought affects vegetation growth to a large extent. Understanding the dynamic changes of vegetation during drought is of great significance for agricultural and ecological management and climate change adaptation. The relations between vegetation and drought have been widely investigated, but how vegetation loss and restoration in response to drought remains unclear. Using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI) data, this study developed an evaluation framework for exploring the responses of vegetation loss and recovery to meteorological drought, and applied it to the humid subtropical Pearl River basin (PRB) in southern China for estimating the loss and recovery of three vegetation types (forest, grassland, cropland) during drought using the observed NDVI changes. Results indicate that vegetation is more sensitive to drought in high-elevation areas (lag time 8 months). Vegetation loss (especially in cropland) is found to be more sensitive to drought duration than drought severity and peak. No obvious linear relationship between drought intensity and the extent of vegetation loss is found. Regardless of the intensity, drought can cause the largest probability of mild loss of vegetation, followed by moderate loss, and the least probability of severe loss. Large spatial variability in the probability of vegetation loss and recovery time is found over the study domain, with a higher probability (up to 50 %) of drought-induced vegetation loss and a longer recovery time (>7 months) mostly in the high-elevation areas. Further analysis suggests that forest shows higher but cropland shows lower drought resistance than other vegetation types, and grassland requires a shorter recovery time (4.2-month) after loss than forest (5.1-month) and cropland (4.8-month).

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