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Fulltext Student Behavior Recognition From Heterogeneous View Perception in Class Based on 3-D Multiscale Residual Dense Network for the Analysis of Case Teaching

Liu H, Liu Y, Zhang R, Wu X

Front Neurorobot, 2021;15:675827.
PMID: 34393749 DOI: 10.3389/fnbot.2021.675827

The study of student behavior analysis in class plays a key role in teaching and educational reforms that can help the university to find an effective way to improve students' learning efficiency and innovation ability. It is also one of the effective ways to cultivate innovative talents. The traditional behavior recognition methods have many disadvantages, such as poor robustness and low efficiency. From a heterogeneous view perception point of view, it introduces the students' behavior recognition. Therefore, we propose a 3-D multiscale residual dense network from heterogeneous view perception for analysis of student behavior recognition in class. First, the proposed method adopts 3-D multiscale residual dense blocks as the basic module of the network, and the module extracts the hierarchical features of students' behavior through the densely connected convolutional layer. Second, the local dense feature of student behavior is to learn adaptively. Third, the residual connection module is used to improve the training efficiency. Finally, experimental results show that the proposed algorithm has good robustness and transfer learning ability compared with the state-of-the-art behavior recognition algorithms, and it can effectively handle multiple video behavior recognition tasks. The design of an intelligent human behavior recognition algorithm has great practical significance to analyze the learning and teaching of students in the class.
Prediction model of transformer top oil temperature based on data quality enhancement

Dong N, Zhang R, Li Z, Cao B

Rev Sci Instrum, 2023 Jul 01;94(7).
PMID: 37493503 DOI: 10.1063/5.0159072

Top oil temperature (TOT) is an important parameter to evaluate the running state of a transformer. According to the variation trend of TOT, the internal thermal state of transformers can be predicted so as to arrange operation and maintenance reasonably and prevent the occurrence of accidents. However, due to the complex working environment in the field, there are often a large number of missing values in online monitoring data, which seriously affects the prediction of TOT. At the same time, it is affected by various factors such as load, ambient temperature, wind speed, and solar radiation, which cause the information of different time scales to be mixed in its monitoring data. Therefore, it is difficult to achieve the desired accuracy with a single model. In this article, a model for predicting TOT based on data quality enhancement is proposed. First, the Markov model is used to complete the online monitoring data containing missing values to obtain a complete and continuous time series. Then, using the ensemble empirical modal decomposition method, the time series of TOT is decomposed into multiple time series components to eliminate the interaction between different time scales of information, thus reducing the prediction difficulty. Finally, the sub-prediction model of the extreme learning machine is constructed, and the prediction results of all the sub-models are reconstructed to obtain the final prediction results of TOT. In order to verify the effectiveness of the model, the TOT of an operating transformer for the next two days is predicted in the article, and its mean absolute percentage error (MAPE) is 5.27% and its root mean square error (RMSE) is 2.46. Compared with the BP neural network model and the support vector machines (SVM) model, the MAPE is reduced by 69.56% and 61.92%, respectively, and the RMSE is reduced by 67.02% and 59.87%. The results of this study will provide important support for the fault diagnosis of the top oil temperature online monitoring system.
Fulltext Consensus models with aggregation operators for minimum quadratic cost in group decision making

Zhang R, Huang J, Xu Y, Herrera-Viedma E

Appl Intell (Dordr), 2023;53(2):1370-1390.
PMID: 35506044 DOI: 10.1007/s10489-021-02948-5

In group decision making (GDM), to facilitate an acceptable consensus among the experts from different fields, time and resources are paid for persuading experts to modify their opinions. Thus, consensus costs are important for the GDM process. Notwithstanding, the unit costs in the common linear cost functions are always fixed, yet experts will generally express more resistance if they have to make more compromises. In this study, we use the quadratic cost functions, the marginal costs of which increase with the opinion changes. Aggregation operators are also considered to expand the applications of the consensus methods. Moreover, this paper further analyzes the minimum cost consensus models under the weighted average (WA) operator and the ordered weighted average (OWA) operators, respectively. Corresponding approaches are developed based on strictly convex quadratic programming and some desirable properties are also provided. Finally, some examples and comparative analyses are furnished to illustrate the validity of the proposed models.
The association between neuropsychiatric effects of substance use and occurrence of endoplasmic reticulum and unfolded protein response: A systematic review

Yang B, Zhang R, Leong Bin Abdullah MFI

Toxicol Lett, 2024 Jan;391:71-85.
PMID: 38101493 DOI: 10.1016/j.toxlet.2023.12.008

INTRODUCTION: This systematic review aimed to assess the association between neuropsychiatric effects of substance use and occurrence of ER stress and unfolded protein response (UPR) through comprehensive electronic search of existing literature and review of their findings.
METHODS: A comprehensive electronic literature search was carried out on research articles published between 1950 to July 2023 through major databases, such as Scopus, Web of Science, Google Scholar, PubMed, PsycINFO, EMBASE, Medline and Cochrane Library.
RESULTS: A total of 21 research articles were selected for review, which were comprised of sixteen animal studies, four human studies and one study on postmortem human brain samples. The selected studies revealed that alcohol, methamphetamine, cocaine, opioid and kratom exposures contributed to neuropsychiatric effects: such as decline in learning and memory function, executive dysfunction, alcohol, methamphetamine, opioid, and kratom dependence. These effects were associated with activation and persistent of ER stress and UPR with elevation of BiP and CHOP expression and the direction of ER stress is progressing towards the PERK-eIF2α-ATF4-CHOP pathway and neuronal apoptosis and neurodegeneration at various regions of the brain. In addition, regular kratom use in humans also contributed to elevation of p-JNK expression, denoting progress of ER stress towards the IRE1-ASK1-JNK-p-JNK pathway which was linked to kratom use disorder. However, treatment with certain compounds or biological agents could reverse the activation of ER stress.
CONCLUSIONS: The neuropsychiatric effects of alcohol, methamphetamine, cocaine, opioid and kratom use may be associated with persistent ER stress and UPR.
Spatiotemporal dynamics of forest fires in the context of climate change: a review

Zhang Y, Lim HS, Hu C, Zhang R

Environ Sci Pollut Res Int, 2024 Apr 25.
PMID: 38662294 DOI: 10.1007/s11356-024-33305-x

Forest fires are sudden, destructive, hazardous, and challenging to manage and rescue, earning them a place on UNESCO's list of the world's eight major natural disasters. Currently, amid global warming, all countries worldwide have entered a period of high forest fire incidence. Due to global warming, the frequency of forest fires has accelerated, the likelihood of large fires has increased, and the spatial and temporal dynamics of forest fires have shown different trends. Therefore, the impact of climate change on the spatiotemporal dynamics of forest fires has become a hot issue in the field of forest fire research in recent years. Therefore, it is of great significance and necessity to conduct a review of the research in this area. This review delves into the interactions and impacts between climate change and the spatiotemporal dynamics of forest fires. To address this issue, scholars have mainly adopted the following research methods: first, statistical analysis methods, second, the establishment of spatiotemporal prediction models for meteorology and forest fires, and third, the coupling of climate models with forest fire risk forecasting models. The statistical analysis method relies on the analysis of historical meteorological and fire-related data to study the effects of climate change and meteorological factors on fire occurrence. Meanwhile, forest fire prediction models utilize technical tools such as remote sensing. These models synthesize historical meteorological and fire-related data, incorporating key meteorological factors such as temperature, rainfall, relative humidity, and wind. The models revealed the spatial and temporal distribution patterns of fires, identified key drivers, and explored the interactions between climate change and forest fire dynamics, culminating in the construction of predictive models. With the deepening of the study, the coupling of climate models and fire risk ranking systems became a trend in the prediction of forest fire risk trends. Moreover, as the climate warms, the increased frequency of extreme weather events like heatwaves, droughts, snow and ice storms, and El Niño-Southern Oscillation (ENSO) has accelerated forest fire occurrences and raised the risk of major fires. This review offers valuable technical insights by comprehensively analyzing the spatial and temporal characteristics of forest fires, elucidating key meteorological drivers, and exploring potential mechanisms. These insights serve as a scientific foundation for preventive measures and effective forest fire management. In the face of a changing climate, this synthesis contributes to the development of informed strategies to mitigate the escalating threat of forest fires.
Long term mesenchymal stem cell culture on a defined synthetic substrate with enzyme free passaging

Duffy CR, Zhang R, How SE, Lilienkampf A, De Sousa PA, Bradley M

Biomaterials, 2014 Jul;35(23):5998-6005.
PMID: 24780167 DOI: 10.1016/j.biomaterials.2014.04.013

Mesenchymal stems cells (MSCs) are currently the focus of numerous therapeutic approaches in tissue engineering/repair because of their wide multi-lineage potential and their ability to modulate the immune system response following transplantation. Culturing these cells, while maintaining their multipotency in vitro, currently relies on biological substrates such as gelatin, collagen and fibronectin. In addition, harvesting cells from these substrates requires enzymatic or chemical treatment, a process that will remove a multitude of cellular surface proteins, clearly an undesirable process if cells are to be used therapeutically. Herein, we applied a high-throughput 'hydrogel microarray' screening approach to identify thermo-modulatable substrates which can support hES-MP and ADMSC growth, permit gentle reagent free passaging, whilst maintaining multi-lineage potential. In summary, the hydrogel substrate identified, poly(AEtMA-Cl-co-DEAA) cross-linked with MBA, permitted MSCs to be maintained over 10 passages (each time via thermo-modulation), with the cells retaining expression of MSC associated markers and lineage potency. This chemically defined system allowed the passaging and maintenance of cellular phenotype of this clinically important cell type, in the absence of harsh passaging and the need for biological substrates.
Fulltext Biogeography of bacterioplankton in the tropical seawaters of Singapore

Lau SC, Zhang R, Brodie EL, Piceno YM, Andersen G, Liu WT

FEMS Microbiol Ecol, 2013 May;84(2):259-69.
PMID: 23237658 DOI: 10.1111/1574-6941.12057

Knowledge about the biogeography of marine bacterioplankton on the global scale in general and in Southeast Asia in particular has been scarce. This study investigated the biogeography of bacterioplankton community in Singapore seawaters. Twelve stations around Singapore island were sampled on different schedules over 1 year. Using PCR-DNA fingerprinting, DNA cloning and sequencing, and microarray hybridization of the 16S rRNA genes, we observed clear spatial variations of bacterioplankton diversity within the small area of the Singapore seas. Water samples collected from the Singapore Strait (south) throughout the year were dominated by DNA sequences affiliated with Cyanobacteria and Alphaproteobacteria that were believed to be associated with the influx of water from the open seas in Southeast Asia. On the contrary, water in the relatively polluted Johor Strait (north) were dominated by Betaproteobacteria, Gammaproteobacteria, and Bacteroidetes and that were presumably associated with river discharge and the relatively eutrophic conditions of the waterway. Bacterioplankton diversity was temporally stable, except for the episodic surge of Pseudoalteromonas, associated with algal blooms. Overall, these results provide valuable insights into the diversity of bacterioplankton communities in Singapore seas and the possible influences of hydrological conditions and anthropogenic activities on the dynamics of the communities.
RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI

Jing W, Tao H, Rahman MA, Kabir MN, Yafeng L, Zhang R, et al.

Work, 2021;68(3):923-934.
PMID: 33612534 DOI: 10.3233/WOR-203426

BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system.
OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.
RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.
CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate.
ADA-SR: Activity detection and analysis using security robots for reliable workplace safety

Zhang G, Jing W, Tao H, Rahman MA, Salih SQ, Al-Saffar A, et al.

Work, 2021;68(3):935-943.
PMID: 33612535 DOI: 10.3233/WOR-203427

BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
Interaction modeling and classification scheme for augmenting the response accuracy of human-robot interaction systems

Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.

Work, 2021;68(3):903-912.
PMID: 33720867 DOI: 10.3233/WOR-203424

BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.
OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.
RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.
CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.
Fulltext Protective effect of curcumin against ultraviolet A irradiation‑induced photoaging in human dermal fibroblasts

Liu X, Zhang R, Shi H, Li X, Li Y, Taha A, et al.

Mol Med Rep, 2018 05;17(5):7227-7237.
PMID: 29568864 DOI: 10.3892/mmr.2018.8791

Ultraviolet (UV) radiation induces DNA damage, oxidative stress, and inflammatory processes in skin, resulting in photoaging. Natural botanicals have gained considerable attention due to their beneficial protection against the harmful effects of UV irradiation. The present study aimed to evaluate the ability of curcumin (Cur) to protect human dermal fibroblasts (HDFs) against ultraviolet A (UVA)‑induced photoaging. HDFs were treated with 0‑10 µM Cur for 2 h and subsequently exposed to various intensities of UVA irradiation. The cell viability and apoptotic rate of HDFs were investigated by MTT and flow cytometry assays, respectively. The effect of UVA and Cur on the formation of reactive oxygen species (ROS), malondialdehyde levels, which are an indicator of ROS, and the levels/activity of antioxidative defense proteins, including glutathione, superoxide dismutase and catalase, were evaluated using 2',7'-dichlorofluorescin diacetate and commercial assay kits. Furthermore, western blotting was performed to determine the levels of proteins associated with endoplasmic reticulum (ER) stress, the apoptotic pathway, inflammation and the collagen synthesis pathway. The results demonstrated that Cur reduced the accumulation of ROS and restored the activity of antioxidant defense enzymes, indicating that Cur minimized the damage induced by UVA irradiation in HDFs. Furthermore, western blot analysis demonstrated that Cur may attenuate UVA‑induced ER stress, inflammation and apoptotic signaling by downregulating the protein expression of glucose‑regulated protein 78, C/EBP‑homologous protein, nuclear factor‑κB and cleaved caspase‑3, while upregulating the expression of Bcl‑2. Additionally, it was demonstrated that Cur may regulate collagen metabolism by decreasing the protein expression of matrix metalloproteinase (MMP)‑1 and MMP‑3, and may promote the repair of cells damaged as a result of UVA irradiation through increasing the protein expression of transforming growth factor‑β (TGF‑β) and Smad2/3, and decreasing the expression of the TGF‑β inhibitor, Smad7. In conclusion, the results of the present study indicate the potential benefits of Cur for the protection of HDFs against UVA‑induced photoaging and highlight the potential for the application of Cur in skin photoprotection.
(RS)-bambuterol and its enantiomers: Potential improvement of (R)-bambuterol in mice with colitis

Deng L, Wang S, Guo H, Liu X, Zou X, Zhang R, et al.

Int Immunopharmacol, 2022 Feb;103:108501.
PMID: 34974400 DOI: 10.1016/j.intimp.2021.108501

Bambuterol (BMB) has been used clinically to treat asthma due to its bronchodilation activity. However, the effect of BMB on ulcerative colitis (UC) has not been examined. The present work focused on the effects of enantiomeric BMB on UC. Acute UC was induced in mice by 3% dextran sulfate sodium (DSS), and (R)-, (S) and (RS)-BMB were orally administered. Body weight loss and the disease activity index (DAI) were measured once a day. Inflammatory factors were detected by ELISA and qRT-PCR. Histological evaluations of colon samples were performed. IL-6, STAT3, and RORγt pathway-related proteins were analyzed by western blotting. The results verified that colitis severity was dramatically ameliorated by (R)-BMB, which was significantlybetter than the effect of (RS)-BMB or (S)-BMB, as evidenced by body weight loss, DAI, colon length, spleen/body weight ratio and histopathological manifestations. Furthermore, (R)-BMB treatment significantly diminished the levels of inflammatory cytokines and macrophages infiltration in mice with colitis. Besides, treated with (R)-BMB obviously elevated the level of β2AR. In addition, (R)-BMB decreased the expression of IL-6, IL-17, retinoic acid receptor-related orphan receptor-gamma t (RORt), and phosphorylated STAT3 (p-STAT3) in a dose-dependent manner in the colon tissues. The efficacy of (R)-BMB was more notable than aminosalicylic acid (5-ASA). (R)-BMB is either butyrilcholinesterase inhibitor or β2AR agonist which offers new treatment of colitis.
Fulltext Sclerosing odontogenic carcinoma of maxilla: A case report

Soh HY, Zhang WB, Yu Y, Zhang R, Chen Y, Gao Y, et al.

World J Clin Cases, 2023 Mar 16;11(8):1878-1887.
PMID: 36970007 DOI: 10.12998/wjcc.v11.i8.1878

BACKGROUND: Sclerosing odontogenic carcinoma is a rare primary intraosseous neoplasm that was featured recently as a single entity in the World Health Organization classification of Head and Neck Tumors 2017, with only 14 cases published to date. The biological characteristics of sclerosing odontogenic carcinoma remain indistinct because of its rarity; however, it appears to be locally aggressive, with no regional or distant metastasis reported to date.
CASE SUMMARY: We reported a case of sclerosing odontogenic carcinoma of the maxilla in a 62-year-old woman, who presented with an indolent right palatal swelling, which progressively increased in size over 7 years. Right subtotal maxillectomy with surgical margins of approximately 1.5 cm was performed. The patient remained disease free for 4 years following the ablation surgery. Diagnostic workups, treatment, and therapeutic outcomes were discussed.
CONCLUSION: More cases are needed to further characterize this entity, understand its biological behavior, and justify the treatment protocols. Resection with wide margins of approximately 1.0 to 1.5 cm is proposed, while neck dissection, post-operative radiotherapy, or chemotherapy are deemed unnecessary.
Fulltext Kratom use disorder and unfolded protein response: Evaluating their relationship in a case control study

Yang B, Tan ML, Zhang R, Singh D, Leong Bin Abdullah MFI

PLoS One, 2023;18(6):e0287466.
PMID: 37352311 DOI: 10.1371/journal.pone.0287466

BACKGROUND AND AIMS: Kratom (Mitragyna speciosa Korth.) is widely use worldwide despite its addictive potential. Although psychostimulant use has been linked to occurrence of endoplasmic reticulum (ER) stress, data is lacking on how regular kratom use affects ER stress. This case-control study first determined differences in ER stress sensor protein expression (BiP, sXBP1, ATF4, CHOP, JNK, and p-JNK) between regular kratom users and healthy controls. Second, it evaluated the association between kratom use characteristics, targeted ER stress sensor protein expression, and "kratom use disorder" diagnosed with Diagnostic and Statistical Manual for Mental Disorders 5th Edition (DSM-5) among regular kratom users.
METHODS: In total, 60 regular kratom users and 50 healthy control-group participants were recruited and administered a sociodemographic and clinical characteristics questionnaire. While participants who used kratom were also administered a kratom use characteristics questionnaire. Blood samples were collected from all participants, and targeted ER stress sensor protein expression was determined via Western blot analysis.
RESULTS: The study's findings revealed first that kratom users registered significantly higher protein expression in all targeted ER stress sensors compared to the control group. Second, higher protein expression of CHOP (B = 5.061, standard error [SE] = 2.547, Wald = 3.948, adjusted odds ratio [AOR] = 5.382, 95% confidence interval [CI] = 1.071 to 9.656, p = 0.047) and p-JNK (B = 5.795, SE = 2.635, Wald = 4.544, AOR = 17.025, 95% CI = 1.395 to 24.123, p = 0.017) increased the odds of kratom use disorder occurrence. Kratom use characteristics and other ER stress sensor protein expression were not associated with kratom use disorder.
CONCLUSION: Regular kratom use may induce protracted ER stress, leading to the decompensation of the unfolded protein response to maintain ER homeostasis. This effect may be linked to kratom use disorder occurrence.
Fulltext Sustainable utilization of Sedum plumbizincicola as superior hydrochar for efficient nutrients recovery

Zhang R, Zhang Y, Goei R, Oh WD, Zhang Z, He C

J Environ Manage, 2023 Oct 15;344:118441.
PMID: 37379626 DOI: 10.1016/j.jenvman.2023.118441

To realize sound disposal of hyperaccumulator harvested from phytoremediation, hydrothermal carbonization (HTC) has been employed to obtain superior hydrochar adsorbents for removal of phosphate and ammonium from water body. A series of hydrochars have been prepared under tuned HTC conditions to tailor hydrochar with desired properties. Generally, increased temperature and prolonged reaction time facilitated acidic oxygen functional groups on hydrochars, thereby improving adsorption capacity of hydrochar. In single solute system, a superior hydrochar, derived from HTC under 260 °C for 2 h, achieved a maximum phosphate and ammonium adsorption capacity of 52.46 mg/g and 27.56 mg/g at 45 °C, respectively. In binary system, synergistic adsorption was observed only in lower solute concentration, whereas competitive adsorption occurred under higher solute concentration. Characterization and adsorption kinetics suggested chemisorption may dominate the adsorption process, thus the adsorption capacity could be improved by tuning pHpzc of hydrochar. This study firstly demonstrates the sustainable utilization of hyperaccumulators into nutrients-enriched hydrochar as fertilizer for in-situ phytoremediation of contaminated sites with minimized environmental risks towards circular economy.
Fulltext Validation of the Malay version of the Multidimensional Scale of Perceived Social Support (MSPSS-M) among patients with cancer in Malaysia

Song W, Mansor NS, Shari NI, Azman N, Zhang R, Leong Bin Abdullah MFI

PLoS One, 2023;18(11):e0293698.
PMID: 37988357 DOI: 10.1371/journal.pone.0293698

BACKGROUND: The well-being and adaptive functioning of patients with cancer depend on their perception of social support. To accurately assess and understand the impact of social support in a diverse population, validated measurement tools are essential. This study aimed to adapt and validate the Malay version of the Multidimensional Scale of Perceived Social Support (MSPSS-M) among patients with cancer in Malaysia.
METHODS: A total of 346 cancer patients with mixed disease types were recruited and completed the socio-demographic and clinical characteristics questionnaire and the MSPSS-M. The MSPSS-M was assessed for internal consistency, construct validity, face, content, convergent, discriminant validity, and confirmatory factor analyses.
RESULTS: The MSPSS-M and its three domains demonstrated good internal consistency with Cronbach's α ranging from 0.900 to 0.932. Confirmatory factor analysis (CFA) of the MSPSS-M supported the three-factor model of the original English version of the MSPSS. The MSPSS-M also exhibited good convergent validity and discriminant validity.
CONCLUSION: The MSPSS-M demonstrates favorable psychometric properties among patients with cancer in Malaysia. The validation of the MSPSS-M provides a culturally adapted and linguistically valid instrument to assess perceived social support among Malay-speaking patients with cancer in Malaysia.
Fabricating an adsorbent and micro-nano bubble catalyst through confining maghemite in the β cage of NaY zeolite

Duan Y, Zhang R, Han P, Wong NH, Sunarso J, Liu S, et al.

Chemosphere, 2024 Feb;350:141103.
PMID: 38184083 DOI: 10.1016/j.chemosphere.2023.141103

This work reports the ion exchange fabrication of maghemite (γ-Fe2O3) modified NaY zeolite (Fe2O3@Y) with bifunction of adsorption and catalysis. The Fe3+ successfully replaced the Na+ in the β cage of zeolite in the ion exchange process and coordinated with framework oxygens to form magnetic γ-Fe2O3. Therefore, most of the γ-Fe2O3 particles were confined in the β cages, which resulted in the high dispersal and stability of the catalyst. The Fe2O3@Y could remove methylene blue (MB) model pollutants up to 59.02 and 61.47% through the adsorption and catalysis process, respectively. The hydrogen bond between the OH- ions around the Fe2O3@Y surface and the N and O presented in the MB molecules enabled the chemical adsorption to MB, which accorded with the pseudo-second-order kinetic model. Further, the H+ existed in the solution and the β cage of zeolite promoted the collapse of micro-nano bubbles (MNBs). Then, the γ-Fe2O3 catalyst would be activated by high temperature and oxidated OH- to produce hydroxyl radicals for pollutant degradation. Thus, pollutant removal was attributed to the combined effects of adsorption and catalysis in the Fe2O3@Y + MNB system. In this work, the Fe2O3@Y was demonstrated as a potentially magnetic adsorbent or MNB catalyst for wastewater treatment.
MenSCs Transplantation Improve the Viability of Injured Endometrial Cells Through Activating PI3K/Akt Pathway

Zhang S, Zhang R, Yin X, Lu Y, Cheng H, Pan Y, et al.

Reprod Sci, 2023 Nov;30(11):3325-3338.
PMID: 37308799 DOI: 10.1007/s43032-023-01282-0

Endometrial injury is one of the leading causes of female infertility and is caused by intrauterine surgery, endometrial infection, repeated abortion, or genital tuberculosis. Currently, there is little effective treatment to restore the fertility of patients with severe intrauterine adhesions and thin endometrium. Recent studies have confirmed the promising therapeutic effects of mesenchymal stem cell transplantation on various diseases with definite tissue injury. The aim of this study is to investigate the improvements of menstrual blood-derived endometrial stem cells (MenSCs) transplantation on functional restoration in the endometrium of mouse model. Therefore, ethanol-induced endometrial injury mouse models were randomly divided into two groups: the PBS-treated group, and the MenSCs-treated group. As expected, the endometrial thickness and gland number in the endometrium of MenSCs-treated mice were significantly improved compared to those of PBS-treated mice (P
Psychometric properties of the Malay version of the Illness Cognition Questionnaire among cancer patients in Malaysia

Song W, Mansor NS, Shari NI, Zhang R, Abdullah MFILB

BMC Public Health, 2024 Jan 13;24(1):173.
PMID: 38218795 DOI: 10.1186/s12889-023-17060-1

OBJECTIVE: The Illness Cognition Questionnaire (ICQ) was translated from its original English version to the Malay version for this research, adapted the Malay language version of the ICQ (ICQ-M) for use in cancer patients, and assessed the internal consistency, content, face, construct, convergent, discriminant and concurrent validity of the ICQ-M among a cohort of cancer patients with mixed cancer types in Malaysia.
METHOD: Initially, the ICQ was translated into Malay and back-translated, and its content and face validity were evaluated. Then, 346 cancer patients with various cancer types received the ICQ-M, and its internal consistency, convergent, discriminant, construct, and concurrent validity were evaluated.
RESULTS: The ICQ-M and its domains had acceptable internal consistency with Cronbach's α ranging from 0.742 to 0.927. Construct validity assessment demonstrated that the ICQ-M consists of 17 items designated in two domains with good convergent and discriminant validity. The ICQ-M and its domains also had moderate correlations with the Acceptance and Action Questionnaire II, which denotes that the ICQ-M had acceptable concurrent validity.
CONCLUSION: The ICQ-M had good psychometric properties and is now available to measure the illness cognition of cancer patients in Malaysia.
Fulltext Research protocol of the efficacy of probiotics for the treatment of alcohol use disorder among adult males: A comparison with placebo and acceptance and commitment therapy in a randomized controlled trial

Zhang B, Zhang R, Deng H, Cui P, Li C, Yang F, et al.

PLoS One, 2023;18(12):e0294768.
PMID: 38051740 DOI: 10.1371/journal.pone.0294768

BACKGROUND AND AIM: Primarily, this study compares the efficacy of probiotic and acceptance and commitment therapy (ACT) in alleviating the severity of alcohol craving and alcohol use disorder (AUD) among patients who had undergo two weeks of in-patient detoxification. Secondarily, this study compares the efficacy of probiotic and ACT in mitigating the severity of comorbid depression and anxiety symptoms; decreasing serum level of pro-inflammatory cytokines, such as interleukin 1β (IL-1β), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); changing the event-related potential in electroencephalogram (EEG) and restoring microbiota flora in the gut of AUD patients.
METHODS AND ANALYSIS: Initially, during Phase I of the study, the serum level of IL-1β, IL-6 and TNF-α; ERP changes in the EEG and fecal microbiota content will be compared between 120 AUD patients and 120 healthy controls. Subsequently in Phase II of the study, 120 AUD patients will be randomized by stratified permuted block randomization into the probiotic, ACT and placebo groups in a 1:1:1 ratio. Participants in the probiotic and placebo groups will be administered one sachet per day of Lactobacillus spp. probiotic and placebo, respectively for 12 weeks. While those in the ACT group will receive one session per week of ACT for 8 weeks. Outcome measures will be administered at four timepoints, such as t0 = baseline assessment prior to intervention, t1 = 8 weeks after intervention began, t2 = 12 weeks after intervention and t3 = 24 weeks after intervention. Primary outcomes are the degrees of alcohol craving, alcohol withdrawal during abstinence and AUD. Secondary outcomes to be assessed are the severity of co-morbid depression and anxiety symptoms; the serum levels of IL-1β, IL-6 and TNF-α; changes in ERP and fecal microbiota content.
TRIAL REGISTRATION NUMBER: NCT05830708 (ClinicalTrials.gov). Registered on April 25, 2023.

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