The COSPAR international space weather action teams (ISWAT) initiative: a driving force for the COSPAR space weather roadmap - Maria M. Kuznetsova; Mario M. Bisi; Hermann J. Opgenoorth; Martin A. Reiss; M. Leila Mays; Lucilla Alfonsi; C. Nick Arge; David Barnes; Anna Belehaki; Thomas E. Berger; Amanda Brecht; Sean Bruinsma; et al. (Advances in Space Research, 2026)

Synergistic effect in ZIF-67/MoS2 entrenched MWCNT photo (electro) catalyst for degradation of tetracycline and alternative to Pt counter electrode in dye-sensitized solar cells - K. Aravinthkumar; Bhanupriya Das; Shiao-Shing Chen; C. Raja Mohan (Journal of Environmental Chemical Engineering, 2024)

Low Magnetic Fields Stimulates Cardiac Mitochondrial Bioenergetics with a Bell-Shaped Response, Possibly Through the Radical Pair Mechanism - Shey-Shing Sheu; Gisela Beutner; Huoy-Jen Yuh; Ilan Goldenberg; Douglas C. Wallace; George A. Porter; Arthur J. Moss (Biochimica et Biophysica Acta (BBA) - Bioenergetics, 2024)

Predicting ischemic stroke patients’ prognosis changes using machine learning in a nationwide stroke registry - Ching-Heng Lin; Yi-An Chen; Jiann-Shing Jeng; Yu Sun; Cheng-Yu Wei; Po-Yen Yeh; Wei-Lun Chang; Yang C. Fann; Kai-Cheng Hsu; Jiunn-Tay Lee (Medical & Biological Engineering & Computing, 2024)
Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although previous studies have demonstrated that machine learning (ML) shows reasonably accurate stroke outcome predictions with limited datasets, to identify specific clinical features associated with prognosis changes after stroke that could aid physicians and patients in devising improved recovery care plans have been challenging. This study aimed to overcome these gaps by utilizing a large national stroke registry database to assess various prediction models that estimate how patients’ prognosis changes over time with associated clinical factors. To properly evaluate the best predictive approaches currently available and avoid prejudice, this study employed three different prognosis prediction models including a statistical logistic regression model, commonly used clinical-based scores, and a latest high-performance ML-based XGBoost model. The study revealed that the XGBoost model outperformed other two traditional models, achieving an AUROC of 0.929 in predicting the prognosis changes of stroke patients followed for 3 months. In addition, the XGBoost model maintained remarkably high precision even when using only selected 20 most relevant clinical features compared to full clinical datasets used in the study. These selected features closely correlated with significant changes in clinical outcomes for stroke patients and showed to be effective for predicting prognosis changes after discharge, allowing physicians to make optimal decisions regarding their patients’ recovery. Graphical Abstract

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials - Mary Clare McKenna; Marlene Tahedl; Jasmin Lope; Rangariroyashe H. Chipika; Stacey Li Hi Shing; Mark A. Doherty; Jennifer C. Hengeveld; Alice Vajda; Russell L. McLaughlin; Orla Hardiman; Siobhan Hutchinson; Peter Bede (Brain Imaging and Behavior, 2022)
Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.

Chronic mild stress paradigm as a rat model of depression: facts, artifacts, and future perspectives - Tatyana Strekalova; Yanzhi Liu; Daniel Kiselev; Sharafuddin Khairuddin; Jennifer Lok Yu Chiu; Justin Lam; Ying-Shing Chan; Dmitrii Pavlov; Andrey Proshin; Klaus-Peter Lesch; Daniel C. Anthony; Lee Wei Lim (Psychopharmacology, 2022)
Rationale The chronic mild stress (CMS) paradigm was first described almost 40 years ago and has become a widely used model in the search for antidepressant drugs for major depression disorder (MDD). It has resulted in the publication of almost 1700 studies in rats alone. Under the original CMS procedure, the expression of an anhedonic response, a key symptom of depression, was seen as an essential feature of both the model and a depressive state. The prolonged exposure of rodents to unpredictable/uncontrollable mild stressors leads to a reduction in the intake of palatable liquids, behavioral despair, locomotor inhibition, anxiety-like changes, and vegetative (somatic) abnormalities. Many of the CMS studies do not report these patterns of behaviors, and they often fail to include consistent molecular, neuroanatomical, and physiological phenotypes of CMS-exposed animals. Objectives To critically review the CMS studies in rats so that conceptual and methodological flaws can be avoided in future studies. Results Analysis of the literature supports the validity of the CMS model and its impact on the field. However, further improvements could be achieved by (i) the stratification of animals into ‘resilient’ and ‘susceptible’ cohorts within the CMS animals, (ii) the use of more refined protocols in the sucrose test to mitigate physiological and physical artifacts, and (iii) the systematic evaluation of the non-specific effects of CMS and implementation of appropriate adjustments within the behavioral tests. Conclusions We propose methodological revisions and the use of more advanced behavioral tests to refine the rat CMS paradigm, which offers a valuable tool for developing new antidepressant medications.

Extra-motor cerebral changes and manifestations in primary lateral sclerosis - Eoin Finegan; Stacey Li Hi Shing; Rangariroyashe H. Chipika; Kai Ming Chang; Mary Clare McKenna; Mark A. Doherty; Jennifer C. Hengeveld; Alice Vajda; Niall Pender; Colette Donaghy; Siobhan Hutchinson; Russell L. McLaughlin; et al. (Brain Imaging and Behavior, 2021)

Public Perceptions of Mangrove Forests Matter for Their Conservation - Farid Dahdouh-Guebas; Gordon N. Ajonina; A. Aldrie Amir; Dominic A. Andradi-Brown; Irfan Aziz; Thorsten Balke; Edward B. Barbier; Stefano Cannicci; Simon M. Cragg; Marília Cunha-Lignon; David J. Curnick; Carlos M. Duarte; et al. (Frontiers in Marine Science, 2020)

Preparing for the coming transnational cancer crisis amid the COVID-19 pandemic - Eric C. Ip; Shing Fung Lee (Cancer Causes & Control, 2020)

UN Decade on Ecosystem Restoration 2021–2030—What Chance for Success in Restoring Coastal Ecosystems? - Nathan J. Waltham; Michael Elliott; Shing Yip Lee; Catherine Lovelock; Carlos M. Duarte; Christina Buelow; Charles Simenstad; Ivan Nagelkerken; Louw Claassens; Colin K-C Wen; Mario Barletta; Rod M. Connolly; et al. (Frontiers in Marine Science, 2020)

Unexpected dose response of HaCaT to UVB irradiation - Rong-Shing Chang; Chi-Shuo Chen; Ching-Lung Huang; Chiu-Ting Chang; Yujia Cui; Wei-Ju Chung; Wun-Yi Shu; Chi-Shiun Chiang; Chun-Yu Chuang; Ian C. Hsu (In Vitro Cellular & Developmental Biology - Animal, 2018)

Mechanistic relationships between hepatic genotoxicity and carcinogenicity in male B6C3F1 mice treated with polycyclic aromatic hydrocarbon mixtures - Tracie D. Phillips; Molly Richardson; Yi-Shing Lisa Cheng; Lingyu He; Thomas J. McDonald; Leslie H. Cizmas; Stephen H. Safe; Kirby C. Donnelly; Fen Wang; Bhagavatula Moorthy; Guo-Dong Zhou (Archives of Toxicology, 2015)

Topography of Inferior Olivary Neurons that Encode Canal and Otolith Inputs - Chun-Wai Ma; Chun-Hong Lai; Billy K. C. Chow; Daisy K. Y. Shum; Ying-Shing Chan (The Cerebellum, 2013)

A review of the pharmacobiotic regulation of gastrointestinal inflammation by probiotics, commensal bacteria and prebiotics - L. Vitetta; D. Briskey; E. Hayes; C. Shing; J. Peake (Inflammopharmacology, 2012)

A population-based, case–control study of green tea consumption and leukemia risk in southwestern Taiwan - Yau-Chang Kuo; Chu-Ling Yu; Chen-Yu Liu; Su-Fen Wang; Pi-Chen Pan; Ming-Tsang Wu; Chi-Kung Ho; Yu-Shing Lo; Yi Li; David C. Christiani (Cancer Causes & Control, 2009)

The role of secretin in the cerebellum - Wing-Ho Yung; Ying-Shing Chan; Billy K. C. Chow; Jian-Jun Wang (The Cerebellum, 2006)

On the Closing Sounds of a Mechanical Heart Valve - Changfu Wu; Bruce A. Herman; Stephen M. Retta; Laurence W. Grossman; Jia-Shing Liu; Ned H. C. Hwang (Annals of Biomedical Engineering, 2005)

Seasonal and Interannual Variability in the Distribution of Surface Nutrients and Dissolved Inorganic Carbon in the Northern North Pacific: Influence of El Niño - Chi Shing Wong; Nathalie A. D. Waser; Yukihiro Nojiri; Wm. Keith Johnson; Frank A. Whitney; John S. C. Page; Jiye Zeng (Journal of Oceanography, 2002)

Subtyping for TNFa microsatellite sequence variation - Arno R. van der Slik; Danielle C. Shing; Peter Eerligh; Marius J. Giphart (Immunogenetics, 2000)