Browse publications by year: 2025

Fulltext A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning

Zhao YF, Chaw JK, Ang MC, Tew Y, Shi XY, Liu L, et al.

PLoS One, 2025;20(1):e0317662.
PMID: 39869550 DOI: 10.1371/journal.pone.0317662

Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enable adaptive insulin dosing control, they face numerous challenges, including safety and training efficiency, which have hindered their clinical application. This paper proposes a safe and efficient adaptive insulin delivery controller based on DRL. It employed ten tricks to enhance the proximal policy optimization (PPO) algorithm, improving training efficiency. Additionally, a dual safety mechanism of 'proactive guidance + reactive correction' was introduced to reduce the risks of hyperglycemia and hypoglycemia and to prevent emergencies. Performance evaluations in the Simglucose simulator demonstrate that the proposed controller achieved an 87.45% time in range (TIR) median, superior to baseline methods, with a lower incidence of hypoglycemia, notably eliminating severe hypoglycemia and treatment failures. These encouraging results indicate that the DRL-based fully closed-loop AP controller has taken an essential step toward clinical implementation.

MeSH terms: Algorithms*; Computer Simulation; Humans; Hypoglycemia/prevention & control; Hypoglycemic Agents/administration & dosage; Hypoglycemic Agents/therapeutic use; Insulin/administration & dosage; Insulin Infusion Systems; Pancreas, Artificial*
Fulltext A study of Chinese enterprises' business models to determine the impact of dynamic capabilities on innovation and performance

Jingwen Y, Rahman AA, Tong T, Kamarulzaman NH, Sidek SB

PLoS One, 2025;20(1):e0310854.
PMID: 39869571 DOI: 10.1371/journal.pone.0310854

Small and medium-sized enterprises (SMEs) can gain a competitive advantage by implementing business model innovation (BMI), which is characterized as irreversible changes to a company's business model. However, BMI is often associated with high risk, uncertainty, and ambiguity. In this study, the effectiveness of BMI on improving SME performance is examined using structural equation modeling (SEM) based on data collected from 330 Chinese SMEs. The purpose of this paper is to examine how enterprise risk management (ERM), organizational agility (OA), and entrepreneurial orientation (EO) affect SME performance. The results reveal that ERM, OA, and EO all have a positive impact on efficiency-centered BMI and SME performance; efficiency-centered BMI mediates this pathway. Building on dynamic capabilities theory, this paper combines ERM, OA, and EO into one framework to assess their impact on SME performance. Additionally, a case study is presented to provide suggestions for making decisions about BMI implementation.

MeSH terms: China; Commerce*; Humans; Organizational Innovation; Entrepreneurship; Models, Organizational
Fulltext Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP

Mehmood S, Amin R, Mustafa J, Hussain M, Alsubaei FS, Zakaria MD

PLoS One, 2025;20(1):e0312425.
PMID: 39869573 DOI: 10.1371/journal.pone.0312425

Software-Defined Networks (SDN) provides more control and network operation over a network infrastructure as an emerging and revolutionary paradigm in networking. Operating the many network applications and preserving the network services and functions, the SDN controller is regarded as the operating system of the SDN-based network architecture. The SDN has several security problems because of its intricate design, even with all its amazing features. Denial-of-service (DoS) attacks continuously impact users and Internet service providers (ISPs). Because of its centralized design, distributed denial of service (DDoS) attacks on SDN are frequent and may have a widespread effect on the network, particularly at the control layer. We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. We use the SHAP feature selection technique to improve the detection procedure. By assisting in the identification of which features are most essential to spot the incidents, the approach aids in the process of enhancing precision and flammability. Fine-tuning the hyperparameters with the help of Bayesian optimization to obtain the best model performance is another important thing that we do in our model. Two datasets, InSDN and CICDDoS-2019, are utilized to assess the effectiveness of the proposed method, 99.95% for the true positive (TP) of the CICDDoS-2019 dataset and 99.98% for the InSDN dataset, the results show that the model is highly accurate.

MeSH terms: Algorithms; Humans; Software; Computer Security*; Neural Networks (Computer)*; Internet
Fulltext Dual-hybrid intrusion detection system to detect False Data Injection in smart grids

Mohammed SH, Singh MSJ, Al-Jumaily A, Islam MT, Islam MS, Alenezi AM, et al.

PLoS One, 2025;20(1):e0316536.
PMID: 39869576 DOI: 10.1371/journal.pone.0316536

Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures. This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. The main objective is to enhance the accuracy and robustness of IDS in smart grids. The proposed methodology combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for hybrid feature selection, ensuring the selection of the most relevant features for detecting FDIAs. Additionally, the IDS employs a hybrid deep learning classifier that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to capture the smart grid data's spatial and temporal features. The dataset used for evaluation, the Industrial Control System (ICS) Cyber Attack Dataset (Power System Dataset) consists of various FDIA scenarios simulated in a smart grid environment. Experimental results demonstrate that the proposed IDS framework significantly outperforms traditional methods. The hybrid feature selection effectively reduces the dimensionality of the dataset, improving computational efficiency and detection performance. The hybrid deep learning classifier performs better in key metrics, including accuracy, recall, precision, and F-measure. Precisely, the proposed approach attains higher accuracy by accurately identifying true positives and minimizing false negatives, ensuring the reliable operation of smart grids. Recall is enhanced by capturing critical features relevant to all attack types, while precision is improved by reducing false positives, leading to fewer unnecessary interventions. The F-measure balances recall and precision, indicating a robust and reliable detection system. This study presents a practical dual-hybrid IDS framework for detecting FDIAs in smart grids, addressing the limitations of existing IDS techniques. Future research should focus on integrating real-world smart grid data for validation, developing adaptive learning mechanisms, exploring other bio-inspired optimization algorithms, and addressing real-time processing and scalability challenges in large-scale deployments.

MeSH terms: Algorithms; Humans; Computer Security*; Neural Networks (Computer)
Fulltext LoVE4MUM Mobile App to Prevent Postpartum Depression: Protocol for a Pilot Randomized Controlled Trial

Kamarudin SS, Idris IB, Sharip S, Ahmad N

JMIR Res Protoc, 2025 Jan 27;14:e63564.
PMID: 39869891 DOI: 10.2196/63564

BACKGROUND: Postpartum depression remains a significant concern, posing substantial challenges to maternal well-being, infant health, and the mother-infant bond, particularly in the face of barriers to traditional support and interventions. Previous studies have shown that mobile health (mHealth) interventions offer an accessible means to facilitate early detection and management of mental health issues while at the same time promoting preventive care.
OBJECTIVE: This study aims to evaluate the effectiveness of the Leveraging on Virtual Engagement for Maternal Understanding & Mood-enhancement (LoVE4MUM) mobile app, which was developed based on the principles of cognitive behavioral therapy and psychoeducation and serves as an intervention to prevent postpartum depression.
METHODS: This single-blinded, pilot randomized controlled trial includes 64 mothers recruited from the postnatal ward and randomized using a 1:1 ratio to receive either postpartum care (treatment as usual) or postpartum care (treatment as usual) plus the self-guided LoVE4MUM mobile app. The primary outcome is the effectiveness of the mobile app at improving postpartum depression. Secondary outcomes are changes in the mental health literacy score and negative automatic thoughts, which are collected using a self-reported questionnaire.
RESULTS: Patient recruitment began on September 1, 2024. As of January 1, 2025, recruitment was successfully completed, with a total of 72 participants enrolled: 36 in the intervention group and 36 in the control group . The final results are anticipated to be available by March 2025, and publication is expected by the end of 2025.
CONCLUSIONS: By examining the LoVE4MUM app alongside standard postpartum care, this pilot randomized controlled trial seeks to offer preliminary evidence on the potential of mHealth tools to improve maternal mental health as well as to reduce postpartum depression symptoms. The findings are expected to contribute to the future development of effective, accessible, and scalable interventions for mothers.
TRIAL REGISTRATION: ClinicalTrials.gov NCT06366035; https://clinicaltrials.gov/study/NCT06366035.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63564.

MeSH terms: Adult; Female; Humans; Pilot Projects; Cognitive Therapy/methods; Single-Blind Method; Telemedicine; Mobile Applications*
Investigating the Li2O-Al2O3-B2O3 matrix: A promising approach for immobilizing radioactive waste

Zulkeplee SA, Ahmad NE, Sanusi MSM, Hashim S

Appl Radiat Isot, 2025 Apr;218:111696.
PMID: 39869950 DOI: 10.1016/j.apradiso.2025.111696

Dealing with radioactive waste, particularly from various industrial processes, poses significant challenges. This paper explores the use of lithium aluminate borate (Li-Al-B) glass matrix as an alternative method for immobilizing radioactive waste, focusing specifically on waste generated in tin smelting industries, known as tin slag. The study primarily concentrates on transforming tin slag, a byproduct abundant in Natural Occurring Radioactive Material (NORM), into a stable and safe form for disposal. The experimental procedures involve blending different compositions of tin slag and Li-Al-B glass, followed by melting them at 1000 °C for 1 h and then rapidly cooling to room temperature. The resulting glass waste identifies an optimal weight percentage of waste loading (typically ranging from 25% to 45%), to minimize volume while effectively immobilizing radioactive material. Notably, the glass waste exhibited an amorphous phase during the product consistency test (PCT) process, demonstrating the fundamental relationship between waste composition and immobilization efficiency. Energy dispersive X-ray spectroscopy (EDX) analysis confirmed a uniform distribution of major elements within the glass waste, underscoring its structural integrity. Furthermore, the dissolution rate of key elements in the glass waste is analyzed, revealing a robust resistance to leaching under varying pH conditions. The normalized mass loss of Boron (B), Lithium (Li), and Aluminum (Al) consistently remain below established glass limits (<2 gm-2), indicative of the glass's exceptional durability. In conclusion, these findings highlight the potential effectiveness of Li-Al-B glass as a versatile host material for immobilizing solid radioactive waste, extending beyond its initial application with tin slag. By highlighting the positive qualities of this matrix, the study emphasizes its potential flexibility in accommodating various types of solid waste matrices.
Fulltext Development of nebulized inhalation delivery for fusion-inhibitory lipopeptides to protect non-human primates against Nipah-Bangladesh infection

Reynard O, Iampietro M, Dumont C, Le Guellec S, Durand S, Moroso M, et al.

Antiviral Res, 2025 Mar;235:106095.
PMID: 39870114 DOI: 10.1016/j.antiviral.2025.106095

Nipah virus (NiV) is a lethal zoonotic paramyxovirus that can be transmitted from person to person through the respiratory route. There are currently no licensed vaccines or therapeutics. A lipopeptide-based fusion inhibitor was developed and previously evaluated for efficacy against the NiV-Malaysia strain. Intraperitoneal administration in hamsters showed superb prophylactic activity and promising efficacy, however the intratracheal delivery mode in non-human primates proved intractable and spurred the development of an aerosolized delivery route that could be clinically applicable. We developed an aerosol delivery system in an artificial respiratory 3D model and optimized the combinations of flow rate and particle size for lung deposition. We characterized the nebulizer device and assessed the safety of lipopeptide nebulization in an African green monkey model that mimics human NiV infection. Three nebulized doses of fusion-inhibitory lipopeptide were administered every 24 h, resulting in peptide deposition across multiple regions of both lungs without causing toxicity or adverse hematological and biochemical effects. In peptide-treated monkeys challenged with a lethal dose of NiV-Bangladesh, animals retained robust levels of T and B-lymphocytes in the blood, infection-induced lethality was significantly delayed, and 2 out of 5 monkeys were protected from NiV infection. The present study establishes the safety and feasibility of the nebulizer delivery method for AGM studies. Future studies will compare delivery methods using next-generation fusion-inhibitory anti-NiV lipopeptides to evaluate the potential role of this aerosol delivery approach in achieving a rapid antiviral response.

MeSH terms: Administration, Inhalation; Aerosols; Animals; Antiviral Agents/administration & dosage; Antiviral Agents/pharmacology; Cercopithecus aethiops; Disease Models, Animal; Humans; Lung/virology; Nebulizers and Vaporizers*; Viral Fusion Protein Inhibitors/administration & dosage; Viral Fusion Protein Inhibitors/pharmacology
Optimizing thermal and thermal-alkaline pretreatments for polylactic acid biodegradation by Amycolatopsis orientalis and Amycolatopsis thailandensis

Yasin NM, Polanska M, Verbeken K, Van Impe JFM, Akkermans S

Bioresour Technol, 2025 Mar;420:132114.
PMID: 39870143 DOI: 10.1016/j.biortech.2025.132114

Environmental pollution from packaging, has led to a need for sustainable alternatives. This study investigates the biodegradation of polylactic acid (PLA) by Amycolatopsis orientalis and Amycolatopsis thailandensis after thermal and thermal-alkaline pretreatments. The biodegradation was assessed based on weight loss, CO2 evolution, carbon balance analysis and scanning electron microscopy (SEM). The analysis showed that pretreatment at 37 °C for 8 h provided effective enhancement of the biodegradation performance. Combining thermal pretreatment with alkaline conditions led to chemical degradation of PLA, but is less suitable as a pretreatment for biodegradation. It was also demonstrated that the mineralization rate over a two-week period was higher following thermal than thermal-alkaline pretreatment. SEM confirmed improved biodegradation as illustrated by increased surface roughness. These findings suggest that thermal pretreatment at 37 °C for 8 h is the most effective strategy for enhancing PLA biodegradation by Amycolatopsis spp., promoting a sustainable approach to plastic waste management.

MeSH terms: Alkalies/pharmacology; Biodegradation, Environmental*; Carbon Dioxide/metabolism; Hydrogen-Ion Concentration; Microscopy, Electron, Scanning; Polymers/chemistry; Temperature; Lactic Acid/metabolism
Prediction of the Serial Alignment Change after Opening-Wedge High Tibial Osteotomy Based on Coronal Plane Alignment of the Knee Using Machine Learning Algorithm

Cho JH, Nam HS, Park SY, Ho JPY, Lee YS

J Knee Surg, 2025 Jan 27.
PMID: 39870165 DOI: 10.1055/a-2525-4622

Categorization of alignment into phenotypes can be useful for predicting and analyzing postoperative alignment changes after opening-wedge high tibial osteotomy (OWHTO). The purposes of this study were (1) to develop a machine learning model for the predicting the Coronal Plane Alignment of the Knee (CPAK) phenotypes of final alignment after OWHTO, and (2) to analyze predictive factors for final alignment phenotypes. Data were retrospectively collected from 163 knees that underwent OWHTO between March 2014 and December 2019. Each data was assessed at three time points: preoperatively, at 3 months postoperatively, and the final follow-up. Constitutional alignment was also evaluated. Machine learning models were developed using two independent feature sets consisting of serial radiologic parameters and CPAK phenotypes. The area under the curve (AUC) was used as a primary metric to determine the best model. To evaluate the feature importance, Shapley additive explanation (SHAP) analysis was also performed on the best model. Multi-layer perceptron (MLP) was the best prediction model, with the highest AUC of 0.867 based on radiologic parameters and 0.783 based on CPAK phenotypes. Joint line obliquity (JLO) at 3 months postoperatively was the most important factor among the radiologic parameters for predicting the final CPAK phenotypes. The features of constitutional and preoperative alignments also contributed, although the features of alignments at 3 months postoperatively were the highest contributing predictors. In conclusion, the developed machine learning models of the MLP showed excellent performance in predicting the final CPAK phenotypes after OWHTO. Postoperative JLO was the most important radiologic parameter for predicting the final alignment. The combination of features of the constitutional, preoperative, and postoperative periods enabled high accuracy and performance in predicting the final alignment. Level of evidence: Retrospective cohort study; Level III Key words: Knee, High tibial osteotomy, CPAK classification, Machine learning, Prediction.
Evaluation of integrated polysaccharide, biopolymers and clay composite membranes for clarification process of citrus fruit (sweet lime) juice

Arthanareeswaran G, Sankar K, Parvin US, Taweepreda W, Ismail AF

Int J Biol Macromol, 2025 Jan 25;301:140266.
PMID: 39870274 DOI: 10.1016/j.ijbiomac.2025.140266

This study focuses on the development of an efficient membrane-based clarification process to enhance the performance of subsequent ultrafiltration and produce high-quality sweet lime juice. A range of casting solutions were prepared using a blend of pore-forming polymers, including polyvinylpyrrolidone (PVP), polyvinylidene fluoride (PVDF), and cellulose acetate (CA), dissolved in dimethylformamide (DMF) solvent through the phase inversion technique. To further enhance the membrane's performance, four biopolymers poly (lactic acid) (PLA), xanthan gum, chitosan, and gelatin were incorporated, with and without clay, to refine its structure, porosity, and surface properties. The resulting membranes were characterized by FT-IR, SEM, and AFM, and their flux behaviour and fouling profiles were evaluated. The quality of the clarified juice was assessed by measuring total suspended solids (TSS), clarity, color, and apparent alcohol insoluble solids (AIS). Despite a reduction in permeate flux, the Xanthan-clay-loaded membrane enhanced juice quality and clarity. For the PLA-based membrane and the xanthan-based membrane, the fouling coefficient was lower. This membrane-based clarification technique can be applied effectively in the juice processing industries to improve product quality.
Fulltext Multi scale multi attention network for blood vessel segmentation in fundus images

Kande GB, Nalluri MR, Manikandan R, Cho J, Veerappampalayam Easwaramoorthy S

Sci Rep, 2025 Jan 27;15(1):3438.
PMID: 39870673 DOI: 10.1038/s41598-024-84255-w

Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the complexity of vessel structures, and the potential for confusion with lesions. In this paper, we introduce a novel approach, the MSMA Net model, which overcomes these challenges by replacing traditional convolution blocks and skip connections with an improved multi-scale squeeze and excitation block (MSSE Block) and Bottleneck residual paths (B-Res paths) with spatial attention blocks (SAB). Our experimental findings on publicly available datasets of fundus images, specifically DRIVE, STARE, CHASE_DB1, HRF and DR HAGIS consistently demonstrate that our approach outperforms other segmentation techniques, achieving higher accuracy, sensitivity, Dice score, and area under the receiver operator characteristic (AUC) in the segmentation of blood vessels with different thicknesses, even in situations involving diverse contextual information, the presence of coexisting lesions, and intricate vessel morphologies.

MeSH terms: Algorithms; Fundus Oculi*; Humans; Image Processing, Computer-Assisted/methods; ROC Curve; Neural Networks (Computer)
Fulltext Construction of an evaluation indicator system for the integrated development of sports, culture and tourism based on tourist perceptions

Tang Y, Li J, Xing C

Sci Rep, 2025 Jan 27;15(1):3330.
PMID: 39870883 DOI: 10.1038/s41598-025-87526-2

Through a literature review, expert interviews, questionnaires, and statistical methods, this study constructs an evaluation index system and calculates the score for the integrated development of sports, culture, and tourism at sports event venues, specifically the Hemei Rural Football Super League ("Village Super League") in Rongjiang, Guizhou. First, we reviewed and analyzed the relevant literature, which led to the formation of an initial index consisting of 18 items. The index was optimized after the analysis to include three main dimensions and 13 specific measurement items. The refined index demonstrated good reliability and validity and may thus provide a valuable tool for evaluating the sustainable development of sports, culture, and tourism integration in specific regions.

MeSH terms: China; Culture; Humans; Perception; Surveys and Questionnaires; Sports*
Fulltext Perceptions of stigma associated with chronic knee pain: voices of selected women in Thailand and Malaysia

Danes-Daetz C, Wainwright JP, Goh SL, McGuire K, Sinsurin K, Richards J, et al.

Physiother Theory Pract, 2025 Feb;41(2):405-419.
PMID: 38481112 DOI: 10.1080/09593985.2024.2329942

INTRODUCTION: A higher prevalence of knee pain in Southeast Asian countries, compared with non-Asian countries, is an established fact. This article hypothesizes that this fact, combined with personal, cultural, and environmental factors, may influence attitudes toward illness and treatment-seeking behavior and adherence.
OBJECTIVE: This study aimed to determine current attitudes, stigma, and barriers of women to the management of chronic knee pain and treatment in two Southeast Asian countries.
METHODS: Fourteen semi-structured interviews explored female lived perceptions of chronic knee pain in Southeast Asia. Using a phenomenological reduction process, open-ended questions allowed participants to voice their perceptions of their experience of this knee condition. Particular foci were potential stigma associated with the perceptions of others, health-seeking attitudes, and attitudes toward exercise.
RESULTS: The shared experiences of managing chronic knee pain revealed the impact of their condition on participants' normality of life and their struggles with pain, limitations, and fear for the future. Key individual, interpersonal, organizational and community barriers and facilitators impacted the health seeking attitudes and engagement with conservative rehabilitation programmes.
CONCLUSION: Improved socio-cultural competency and consideration for an individuals' intersectional identity and interpersonal relationships are key to designing rehabilitation and conservative management solutions. Co-creating alternative pathways for rehabilitation for individuals that are more distant from health facilities may help reduce socio-cultural barriers at a community level.

MeSH terms: Adult; Aged; Female; Humans; Interviews as Topic; Knee Joint/physiopathology; Health Knowledge, Attitudes, Practice; Malaysia; Middle Aged; Patient Acceptance of Health Care; Thailand; Arthralgia/psychology; Qualitative Research; Social Stigma*
Fulltext Benefits of Remote-Based Mindfulness on Physical Symptom Outcomes in Cancer Survivors: Systematic Review and Meta-Analysis

Komariah M, Maulana S, Amirah S, Platini H, Rahayuwati L, Yusuf A, et al.

JMIR Cancer, 2025 Jan 16;11:e54154.
PMID: 39864092 DOI: 10.2196/54154

BACKGROUND: Many cancer survivors experience a wide range of symptoms closely linked to psychological problems, highlighting the need for psychological treatment, one of the most popular being mindfulness. The use of the internet has greatly increased in the last decade, and has encouraged the use of remote-based interventions to help people living with cancer access treatment remotely via devices.
OBJECTIVE: The primary aim of this study was to explore the efficacy of internet-based mindfulness interventions on the physical symptoms of people living with cancer, where physical symptoms are defined as distressing somatic experiences (eg fatigue, insomnia, and pain) regardless of the underlying cause. The secondary aim was to investigate interventions for the quality of life (QoL).
METHODS: This study followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. Relevant articles were systematically searched using electronic databases, namely Scopus, Medline through PubMed, Cumulated Index in Nursing and Allied Health Literature (CINAHL) through EBSCOhost, and Cochrane Central Database. Randomized controlled and pilot trials involving adults and/or older adults with cancer and using remote-based mindfulness interventions compared to usual care were included. The quality of the trials included in this study was assessed using the revised Cochrane risk of bias, version 2.0. This study estimated the standardized mean difference (SMD) and mean difference (MD) with 95% CI. The I2 test was used to identify potential causes of heterogeneity. Publication bias was assessed using contour-enhanced funnel plots and the Egger linear regression test to reveal a small study effect.
RESULTS: The initial search yielded 1985 records, of which 13 studies were ultimately included. After treatment, remote-based mindfulness significantly reduced fatigue (SMD -0.94; 95% CI: -1.56 to -0.33; P=.002), sleep disturbance (SMD -0.36; 95% CI: -0.60 to -0.12; P=.004), and improved physical function (SMD .25; 95% CI: 0.09 to 0.41; P=.002) compared to that observed before treatment. However, compared with usual care, remote-based mindfulness showed a statistically significant reduction only in sleep disturbance (SMD: -0.37; 95% CI: -0.58 to -0.16; P=.0006) after treatment. Moreover, remote-based mindfulness was not statistically significant in reducing pain both within and between groups.
CONCLUSIONS: Remote-based mindfulness shows promise in reducing sleep disturbances; however, its impact on fatigue, pain, and physical function may be limited.

MeSH terms: Fatigue/etiology; Fatigue/psychology; Fatigue/therapy; Humans; Neoplasms/complications; Neoplasms/psychology; Neoplasms/therapy; Quality of Life/psychology
Unravelling the moderating roles of environmental regulations on the impact of foreign direct investment on environmental sustainability

Ehigiamusoe KU, Chen D, Dogan E, Binsaeed RH

J Environ Manage, 2025 Feb;375:124175.
PMID: 39864151 DOI: 10.1016/j.jenvman.2025.124175

In the era of economic globalization, China attracts significant foreign direct investment (FDI) to accelerate economic prosperity. FDI inflows could have ramifications on environmental degradation (ED) despite the enactment of different environmental regulations (ERs) such as market-incentive, command-and-control as well as informal regulations. Though some studies have shown that FDI and ED have significant relationship, the moderating roles of different ERs on the environmental impact of FDI has not been empirically unraveled. This study fills this research gap by analyzing the direct impact of FDI on ED (i.e., carbon dioxide emissions, ecological footprint) using the provincial panel data. Second, it unravels the moderating roles of different ERs on the environmental impact of FDI in the provinces and regions. The results indicate that FDI directly mitigates ED, verifying the pollution halo hypothesis while ERs directly alleviate ED in China. However, the interaction between FDI and ERs do not alleviate ED in China albeit regional heterogeneity exist. The economic implication is that FDI is not a channel through which ERs enhance environmental sustainability in China. This study recommends some policy options arising from the findings.

MeSH terms: Carbon Dioxide/analysis; China; Conservation of Natural Resources*; Environment; Investments*; Internationality; Economic Development; Environmental Policy
Early-life antibiotic exposures: Paving the pathway for dysbiosis-induced disorders

Attiq A

Eur J Pharmacol, 2025 Jan 24;991:177298.
PMID: 39864578 DOI: 10.1016/j.ejphar.2025.177298

Microbiota encompasses a diverse array of microorganisms inhabiting specific ecological niches. Gut microbiota significantly influences physiological processes, including gastrointestinal motor function, neuroendocrine signalling, and immune regulation. They play a crucial role in modulating the central nervous system and bolstering body defence mechanisms by influencing the proliferation and differentiation of innate and adaptive immune cells. Given the potential consequences of antibiotic therapy on gut microbiota equilibrium, there is a need for prudent antibiotic use to mitigate associated risks. Observational studies have linked increased antibiotic usage to various pathogenic conditions, including obesity, inflammatory bowel disease, anxiety-like effects, asthma, and pulmonary carcinogenesis. Addressing dysbiosis incidence requires proactive measures, including prophylactic use of β-lactamase drugs (SYN-004, SYN-006, and SYN-007), hydrolysing the β-lactam in the proximal GIT for maintaining intestinal flora homeostasis. Prebiotic and probiotic supplementations are crucial in restoring intestinal flora equilibrium by competing with pathogenic bacteria for nutritional resources and adhesion sites, reducing luminal pH, neutralising toxins, and producing antimicrobial agents. Faecal microbiota transplantation (FMT) shows promise in restoring gut microbiota composition. Rational antibiotic use is essential to preserve microflora and improve patient compliance with antibiotic regimens by mitigating associated side effects. Given the significant implications on gut microbiota composition, concerted intervention strategies must be pursued to rectify and reverse the occurrence of antibiotic-induced dysbiosis. Here, antibiotics-induced microbiota dysbiosis mechanisms and their systemic implications are reviewed. Moreover, proposed interventions to mitigate the impact on gut microflora are also discussed herein.
Fulltext Occupational management of low back pain secondary to prolapsed intervertebral disc in a Malaysian healthcare worker: a case report emphasizing ergonomic intervention and risk reduction strategies

Yap JF, Supramanian RK, Lim YC

Ind Health, 2025 Jan 27.
PMID: 39864863 DOI: 10.2486/indhealth.2024-0170

Low back pain (LBP) is a commonly encountered medical disorder in Malaysia's primary care setting, though establishing a direct connection between LBP and the workplace environment in adults is challenging. This case presents a clinic nurse who developed LBP due to a prolapsed intervertebral disc and her clinical management from an Occupational Health Doctor perspective. Her occupational management involved a walk-through survey at an urban hospital, which identified bone marrow aspiration as her most physically demanding task. Detailed assessment revealed that during this procedure, the nurse maintained awkward postures and performed repetitive movements while standing for extended periods. A Rapid Entire Body Assessment score of 4 suggested a medium risk, meriting further investigation. To accommodate her condition, the nurse was placed on light duty, with job modifications recommended to limit standing to no more than four hours and to avoid lifting objects exceeding five kilograms. Although the criteria for an occupational disease are not met, it is classified as a work-aggravated condition, given that her LBP was likely worsened by her daily work activities. In conclusion, effective management of occupational LBP requires thorough risk assessments. Modifying tasks and supervisor intervention are essential when job duties could exacerbate pre-existing LBP.
Fulltext Corrigendum to "Pan-Asian adapted ESMO Clinical Practice Guidelines for the diagnosis, treatment and follow-up of patients with biliary tract cancer": [ESMO Open 9 (2024) 103647]

Chen LT, Vogel A, Hsu C, Chen MH, Fang W, Pangarsa EA, et al.

ESMO Open, 2025 Jan;10(1):104074.
PMID: 39864890 DOI: 10.1016/j.esmoop.2024.104074
Fulltext External Validation of an AI mHealth Tool for Gingivitis Detection among Older Adults at Daycare Centers: A Pilot Study

Chau RCW, Cheng ACC, Mao K, Thu KM, Ling Z, Tew IM, et al.

Int Dent J, 2025 Jan 25.
PMID: 39864975 DOI: 10.1016/j.identj.2025.01.008

OBJECTIVES: Periodontal disease is a significant public health concern among older adults due to its relationship with tooth loss and systemic health disease. However, there are numerous barriers that prevent older adults from receiving routine dental care, highlighting the need for innovative screening tools at the community level. This pilot study aimed first, to evaluate the accuracy of GumAI, a new mHealth tool that uses AI and smartphones to detect gingivitis, and the user acceptance of personalized oral hygiene instructions provided through the new tool, among older adults in day-care community centers.
METHODS: Participants were invited from 3 day-care community centers. Intraoral photographs were captured and assessed by both GumAI (test) and a panel consisting of 2 calibrated periodontists and a dentist (benchmark). Mean sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and F1 score were calculated to determine GumAI's diagnostic performance in comparison to the benchmark. User acceptance with this tool was assessed using 2 Rasch Theory-based 5-point Likert-type questions.
RESULTS: 44 participants were recruited out of 80 invited older adults. GumAI demonstrated a sensitivity of 0.93 and specificity of 0.50 compared to the panel's assessments, with a PPV of 0.90 and NPV of 0.56. The accuracy and F1 scores were 0.85 and 0.91, respectively. All participants expressed high acceptance of the process.
CONCLUSION: GumAI demonstrates high sensitivity, PPV, accuracy, and F1 score compared to the panel's assessments but falls relatively short in specificity and NPV. Despite this, the tool was highly accepted by older adults, indicating its potential to enhance gingivitis detection and oral hygiene management in community settings. Further refinements are necessary to improve specificity and validate usability measures.
CLINICAL RELEVANCE: This study may pave the way for broader applications of mHealth systems in community settings, enabling greater health coverage and addressing oral health disparities.
Fulltext Warming-driven migration of enterotypes mediates host health and disease statuses in ectotherm Litopenaeus vannamei

Zeng S, Huang Z, Kriengkrai S, Zhou R, Yuan D, Tuấn NV, et al.

Commun Biol, 2025 Jan 26;8(1):126.
PMID: 39865129 DOI: 10.1038/s42003-025-07558-2

Global warming has threatened all-rounded hierarchical biosphere by reconstructing eco-structure and bringing biodiversity variations. Pacific white shrimp, a successful model of worldwide utilizing marine ectothermic resources, is facing huge losses due to multiple diseases relevant to intestinal microbiota (IM) dysbiosis during temperature fluctuation. However, how warming mediates shrimp health remains poorly understood. Herein, a global shrimp IM catalogue was conducted via 1,369 shrimp IM data from nine countries, including 918 samples from previously published data and 451 generated in the study. Shrimp IMs were stratified into three enterotypes with distinctive compositions and functions, dominated by Vibrio, Shewanella and Candidatus Bacilloplasma, which showed an obvious distribution bias between enterotypes and diseases. The ratio of Vibrio and Candidatus Bacilloplasma was a crucial indicator for shrimp health. Moreover, temperature was the most driving factor for microbial composition, which potentially led to the migration of enterotypes, and high probability of white feces syndrome and low risk of hepatopancreas necrosis syndrome. Collectively, the warming-driven enterotypes mediated shrimp health, which exemplified the causal relationship between temperature rising and ectothermic animals' health. These findings enlarged the cognition of shrimp health culture management from a microecological perspective, and alerted the inevitable challenge of global warming to ectothermic animals.

MeSH terms: Gastrointestinal Microbiome*; Animals; Temperature; Global Warming*

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