Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.

A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.

Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.

The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.

The outbreak of major epidemics, such as COVID-19, has had a significant impact on supply chains. This study aimed to explore knowledge innovation in the field of emergency supply chain during pandemics with a systematic quantitative analysis.

Based on the Web of Science (WOS) Core Collection, proposing a 3-stage systematic analysis framework, and utilizing bibliometrics, Dynamic Topic Models (DTM), and regression analysis to comprehensively examine supply chain innovations triggered by pandemics.

A total of 888 literature were obtained from the WOS database. There was a surge in the number of publications in recent years, indicating a new field of research on Pandemic Triggered Emergency Supply Chain (PTESC) is gradually forming. Through a 3-stage analysis, this study identifies the literature knowledge base and distribution of research hotspots in this field and predicts future research hotspots and trends mainly boil down to 3 aspects: pandemic-triggered emergency supply chain innovations in key industries, management, and technologies.

COVID-19 strengthened academic exchange and cooperation and promoted knowledge output in this field. This study provides an in-depth perspective on emergency supply chain research and helps researchers understand the overall landscape of the field, identifying future research directions.

Patients with chronic insomnia are characterized by alterations in default mode network and alpha oscillations, for which the medial parietal cortex (MPC) is a key node and thus a potential target for interventions.

Fifty-six adults with chronic insomnia were randomly assigned to 2 mA, alpha-frequency (10 Hz), 30 min active or sham transcranial alternating current stimulation (tACS) applied over the MPC for 10 sessions completed within two weeks, followed by 4- and 6-week visits. The connectivity of the dorsal and ventral posterior cingulate cortex (vPCC) was calculated based on resting functional MRI.

For the primary outcome, the active group showed a higher response rate (≥ 50% reduction in Pittsburgh Sleep Quality Index (PSQI)) at week 6 than that of the sham group (71.4% versus 3.6%) (risk ratio 20.0, 95% confidence interval 2.9 to 139.0, p = 0.0025). For the secondary outcomes, the active therapy induced greater and sustained improvements (versus sham) in the PSQI, depression (17-item Hamilton Depression Rating Scale), anxiety (Hamilton Anxiety Rating Scale), and cognitive deficits (Perceived Deficits Questionnaire-Depression) scores. The response rates in the active group decreased at weeks 8–14 (42.9%–57.1%). Improvement in sleep was associated with connectivity between the vPCC and the superior frontal gyrus and the inferior parietal lobe, whereas vPCC-to-middle frontal gyrus connectivity was associated with cognitive benefits and vPCC-to-ventromedial prefrontal cortex connectivity was associated with alleviation in rumination.

Targeting the MPC with alpha-tACS appears to be an effective treatment for chronic insomnia, and vPCC connectivity represents a prognostic marker of treatment outcome.

To summarise the characteristics and postoperative outcomes in paediatric patients with coronary sinus septal defect.

This retrospective study recruited paediatric patients diagnosed with coronary sinus septal defect from the Guangdong Cardiovascular Institute between 2011 and 2023. Clinical characteristics, echocardiographic parameters, surgical procedures, and postoperative outcomes were collected from electronic health records.

Among the 68 patients, 50% were male, with a median age of 1.0 years. Four cases (5.9%) were diagnosed during the prenatal period. The proportions of patients with type I, II, III, and IV coronary sinus septal defect were 51.5%, 5.9%, 16.1%, and 26.5%, respectively. The most common coexisting cardiac anomalies were persistent left superior caval vein. Twenty-seven cases were either missed or misdiagnosed by echocardiogram, accounting for 39.7% of the overall cases, with type I being the most frequently missed diagnosis. Fifty-four patients underwent surgery, two patients received transcutaneous intervention, while the remaining patients did not undergo any surgery or intervention. At follow-up, two patients with type I coronary sinus septal defect died from multiorgan dysfunction, and one patient underwent reoperation due to narrowing of the extracardiac tunnel. The remaining patients did not experience any major events and recovered well.

Paediatric patients with coronary sinus septal defect often do not exhibit specific clinical manifestations. Enhancing our understanding of the anatomic and haemodynamic characteristics of coronary sinus septal defect can improve the diagnostic accuracy of echocardiography. If diagnosis is suspected, confirmation can be obtained by cardiac CT and cardiac magnetic resonance. Accurate preoperative and intraoperative diagnosis of coronary sinus septal defect contributes to high surgical success rates and favourable treatment outcomes.

Previous research has shown abnormal functional network gradients in Alzheimer’s disease (AD). Structural network gradient is capable of capturing continuous changes in brain morphology and has the ability to elucidate the underlying processes of neurodevelopment. However, it remains unclear whether structural network gradients are altered in AD and what associations exist between these changes and cognitive function, and gene expression profiles.

By constructing an individualized structural network gradient decomposition framework, we calculated the morphological similarity network (MSN) gradients for 404 subjects (186 AD patients and 218 normal controls). We investigated AD-related alterations in MSN gradients, along with the associations between MSN gradients and cognitive function, MSN topological properties, and gene expression profiles.

Our findings indicated that the principal MSN gradient alterations in AD were primarily characterized by an increase in the primary and secondary sensory cortices and a decrease in the association cortex 1. The primary and higher-order cortices exhibited opposite associations with cognition, including executive function, language skills, and memory processes. Moreover, the principal MSN gradients were found to significantly predict cognitive function in AD. The altered gradient pattern was 14.8% attributable to gene expression profiles, and the genes demonstrating the highest correlation are involved in metabolic activity and synaptic signaling.

Our results offered novel insights into the underlying mechanisms of structural brain network impairment in AD patients, enhancing our understanding of the neurobiological processes responsible for impaired cognition in patients with AD, and offering a new dimensional structural biomarker for AD.

Suicidal ideation (SI) is very common in patients with major depressive disorder (MDD). However, its neural mechanisms remain unclear. The anterior cingulate cortex (ACC) region may be associated with SI in MDD patients. This study aimed to elucidate the neural mechanisms of SI in MDD patients by analyzing changes in gray matter volume (GMV) in brain structures in the ACC region, which has not been adequately studied to date.

According to the REST-meta-MDD project, this study subjects consisted of 235 healthy controls and 246 MDD patients, including 123 MDD patients with and 123 without SI, and their structural magnetic resonance imaging data were analyzed. The 17-item Hamilton Depression Rating Scale (HAMD) was used to assess depressive symptoms. Correlation analysis and logistic regression analysis were used to determine whether there was a correlation between GMV of ACC and SI in MDD patients.

MDD patients with SI had higher HAMD scores and greater GMV in bilateral ACC compared to MDD patients without SI (all p < 0.001). GMV of bilateral ACC was positively correlated with SI in MDD patients and entered the regression equation in the subsequent logistic regression analysis.

Our findings suggest that GMV of ACC may be associated with SI in patients with MDD and is a sensitive biomarker of SI.

The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.

A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.

Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.

These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.

Congenital heart disease (CHD), the most common congenital malformation affecting fetuses and infants, poses a significant and rapidly emerging global challenge in children’s health. Prenatal and newborn screening are very important for preventing CHD. Therefore, this study aimed to analyze the status and corresponding foci of articles on CHD screening in the Chinese or English language using bibliometric methods.

Publications on prenatal or newborn screening for CHD were included. The Web of Science Core Collection (WoS) and China National Knowledge Infrastructure (CNKI) databases were searched to identify literature published from inception to 31 March 2023. CiteSpace was used to perform bibliometric analysis on the number of publications, institutions, authors, and keywords to generate corresponding knowledge maps.

A total of 582 publications were retrieved from the WoS and 233 from the CNKI databases. There was an increasing trend in the number of English and Chinese articles published, with the trend beginning in 2010 for Chinese language articles and in 2007 for English language articles. In English language publications, GR Martin was the most influential author, and the top five institutions were from high-income countries. Among the Chinese language publications, Wenhong Ding was the most influential author and the Hunan Province Maternal and Child Health Care Hospital was the most commonly reported institution. Keyword analysis revealed that the most frequently occurring terms in both language publications were as follows: antenatal diagnosis, cardiac auscultation, and fetal echocardiography in English language articles and screening, prenatal screening, and fetal in Chinese language publications.

Increasingly, articles on CHD screening have been listed in the WoS and CNKI databases. This bibliometric study provides the status and trends in the research on screening for CHD and may help researchers identify hot topics and explore new research directions in this field.

This research seeks to ascertain the prevalence and determinants of mirror-image dextrocardia in fetuses

With December 2022 as the reference point, we compiled colleted data on pregnant women who carried fetuses with mirror-image dextrocardia in Xi’an, Shaanxi Province: September–October 2022, November 2022, and December 2022–January 2023. An online questionnaire was distributed to 209 pregnant across China who had contracted COVID-19. The case group comprised women whose final menstrual cycle occurred in November 2022 and who had a fetus with mirror-image dextrocardia. Women with a November 2022 final menstrual period and a fetus without this condition made up the control group. To identify the risk factors associated with fetal mirror-image dextrocardia, both univariate and multivariate logistic regression analyses were employed.

A significant difference was noted in the gestational age at COVID-19 infection women with a September to October 2022 and December 2022 to January 2023 final menstrual period who did not bear a fetus with mirror-image dextrocardia, and those with a November 2022 final menstrual period whose fetus exhibited this condition. The univariate and multivariate analyses conducted on pregnant women with a final menstrual period in November 2022 who had contracted COVID-19 revealed significant differences in the presence and duration of fever between those bearing fetuses with mirror-image dextrocardia and those without (P = 0.000).

The findings suggest two critical factors to the increased prevalence of fetal mirror-image dextrocardia: 1) the infection timing which occurs between the 4th and 6th week of pregnancy and 2) the presence of fever and its prolonged duration.

Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD.

This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5–10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model.

During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09–1.23), NO2 (HR: 1.12, 95% CI: 1.05–1.19), and NO (HR: 1.10, 95% CI: 1.03–1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46–1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5.

Our findings highlight the importance of air pollution control in alleviating the burden of MD.