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2 months ago | 
nature.com | Yu Cao |Han Zheng |Fang Hu |Wei Zhang |Yangfang Gu
To explore relationships among low back pain knowledge, fall fear, exercise self-efficacy and kinesiophobia in pregnant women with pregnancy-related low back pain (PLBP) through a chain mediating model. This study used a cross-sectional survey and utilized convenience sampling from August to December 2023 at a third-class hospital in Wuxi, China. A total of 325 PLBP pregnant women were chosen as the subjects of this study. Sociodemographics and information about low back pain knowledge, low back pain knowledge, fall fear, exercise self-efficacy, and kinesiophobia were collected. Path analysis was used to analyze the cross-sectional data. The results of this study found that low back pain knowledge can directly affect kinesiophobia (β = −0.489, p < 0.001). Fall fear and exercise self-efficacy play a significant mediating role between low back pain knowledge and kinesiophobia, with an overall mediating effect value of 0.202. After including fall fear and exercise self-efficacy, the direct effect value of low back pain knowledge on kinesiophobia was − 0.287. Low back pain knowledge in PLBP pregnant women can significantly and negatively predict their kinesiophobia. Between low back pain knowledge and kinesiophobia, there was not only an independent mediating effect of fall fear and exercise self-efficacy but also a chain mediating effect.
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Jan 31, 2025 | 
nature.com | Shuhao Yang |Jiaying Lin |Wei Zhang |Jian Qiao Zhang |Yaling Lu |Enxian Fu | +3 more
Efforts on climate change have demonstrated tangible impacts through various actions and policies. However, a significant knowledge gap remains: comparing the stringency of climate change policies over time or across jurisdictions is challenging due to ambiguous definitions, the lack of a unified assessment framework, complex causal effects, and the difficulty in achieving effective measurement. Furthermore, China’s climate governance is expected to address multiple objectives by integrating main effects and side effects, to achieve synergies that encompass environmental, economic, and social impacts. This paper employs an integrated framework comprising lexicon, text analysis, machine learning, and large-language model applied to multi-source data to quantify China’s policy stringency on climate change (PSCC) from 1954 to 2022. To achieve effective, robust, and explainable measurement, Chain-of-Thought and SHAP analysis are integrated into the framework. By framing the PSCC on varied sub-dimensions covering mitigation, adaptation, implementation, and spatial difference, this dataset maps the government’s varied stringency on climate change and can be used as a robust variable to support a series of downstream causal analysis.
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Jan 21, 2025 | 
nature.com | Yongzhi Lu |Qi Yang |Ting Ran |Wei Zhang |Deyin Guo |Xinwen Chen | +1 more
Correction to: Nature Communications https://doi.org/10.1038/s41467-024-54462-0, published online 23 November 2024In this article there is an error in Figure 1 where the residue labelling incorrectly read E164 and should be D164. The original article has been corrected.
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Jan 16, 2025 | 
pubs.acs.org | Wei Zhang |Yadong Lv |Guangxian Li |Yueshuang Wang
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Jan 16, 2025 | 
onlinelibrary.wiley.com | Jie Liu |Weiming Zeng |Wei Zhang |Ru bo Zhang
Conflicts of Interest The authors declare no conflicts of interest. References 1, , , et al., “Advanced Diffusion Magnetic Resonance Imaging in Patients With Alzheimer's and Parkinson's Diseases,” Neural Regeneration Research 15, no. 9 (2020): 1590–1600. 2 and , “The Neuropathological Diagnosis of Alzheimer's Disease,” Molecular Neurodegeneration 14, no. 1 (2019): 32.
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Jan 16, 2025 | 
dx.doi.org | Wei Zhang |Yueshuang Wang |Yadong Lv |Guangxian Li
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Jan 13, 2025 | 
onlinelibrary.wiley.com | Jiaming Zhang |Linlin Duan |Wei Zhang |Bing Ma
Supporting Information As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.
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Jan 10, 2025 | 
onlinelibrary.wiley.com | Dong Sun |Gang Wu |Wei Zhang |Nadeer M. Gharaibeh
References 1, , , , , . Osteoarthritis year in review 2023: Epidemiology & therapy. Osteoarthr Cartil 2024; 32(2): 159-165. 2, , , et al. Knee osteoarthritis: A review of pathogenesis and state-of-the-art non-operative therapeutic considerations. Genes (Basel) 2020; 11(8): 854. 3, , , , . MRI-based semiquantitative scoring of joint pathology in osteoarthritis. Nat Rev Rheumatol 2013; 9(4): 236-251. 4, , , , , .
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Jan 6, 2025 | 
chemistry-europe.onlinelibrary.wiley.com | Ruoran Wang |Yu Wang |Biao Lu |Wei Zhang
Supporting Information As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.
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Dec 24, 2024 | 
nature.com | Ting Zhu |Yao Hu |Yang Cao |Jia Xu |Heng-Qing Ye |Wei Zhang | +1 more
Depression is a heterogeneous and complex psychological syndrome with highly variable manifestations, which poses difficulties for treatment and prognosis. Depression patients are prone to developing various comorbidities, which stem from different pathophysiological mechanisms, remaining largely understudied. The current study focused on identifying comorbidity-specific phenotypes, and whether these clustered phenotypes are associated with different treatment patterns, clinical manifestations, physiological characteristics, and prognosis. We have conducted a 10-year retrospective observational cohort study using electronic medical records (EMR) for 11,818 patients diagnosed with depression and hospitalized at a large academic medical center in Chengdu, China. K-means clustering and visualization methods were performed to identify phenotypic categories. The association between phenotypic categories and clinical outcomes was evaluated using adjusted Cox proportional hazards model. We classified patients with depression into five stable phenotypic categories, including 15 statistically driven clusters in the discovery cohort (n = 9925) and the validation cohort (n = 1893), respectively. The categories include: (Category A) the lowest incidence of comorbidity, with prominent suicide, psychotic, and somatic symptoms (n = 3493/9925); (Category B) moderate comorbidity rate, with prominent anhedonia and anxious symptoms (n = 1795/9925); (Category C) the highest incidence of comorbidity of endocrine/metabolic and digestive system diseases (n = 1702/9925); (Category D) the highest incidence of comorbidity of neurological, mental and behavioral diseases (n = 881/9925); (Category E) other diseases comorbid with depression (n = 2054/9925). Patients in Category E had the lowest risk of psychiatric rehospitalization within 60-day follow-up, followed by Category C (HR, 1.57; 95% CI, 1.07–2.30), Category B (HR, 1.61; 95% CI, 1.10–2.40), Category A (HR, 1.82; 95% CI, 1.28–2.60), and Category D (HR, 2.38; 95% CI, 1.59–3.60) with P < 0.05, after adjustment for comorbidities, medications, and age. Regarding other longer observation windows (90-day, 180-day and 365-day), patients in Category D showed the highest rehospitalization risk all the time while there were notable shifts in rankings observed for Categories A, B and C over time. The results indicate that the higher the severity of mental illness in patients with five phenotypic categories, the greater the risk of rehospitalization. These phenotypes are associated with various pathways, including the cardiometabolic system, chronic inflammation, digestive system, neurological system, and mental and behavioral disorders. These pathways play a crucial role in connecting depression with other psychiatric and somatic diseases. The identified phenotypes exhibit notable distinctions in terms of comorbidity patterns, symptomology, biological characteristics, treatment approaches, and clinical outcomes.
