Search

Abstract Cutaneous squamous cell carcinoma (CSCC) is common among the elderly, typically treated with surgery. However, for surgery-ineligible patients or those with non-healing wounds progressing to malignant ulcers, non-surgical local treatments are viable. This case details an 80-year-old with recurrent back CSCC and intractable malignant ulcers post-radiotherapy and chemotherapy. Treatment involved Hematoporphyrin Derivative (HpD) Photodynamic Therapy (PDT) with low-dose cindilimab immunotherapy (intravenous and intralesional). Two cycles achieved lesion remission, altering peripheral immune cell counts. HpD-PDT combined with immunotherapy is promising for treating CSCC, particularly with malignant ulcers.

Heart failure (HF) represents the advanced stage of several cardiovascular disorders. This study aimed to build an alternative splicing regulatory network and identify potential splicing factors involved in HF utilizing RNA-seq data and machine learning algorithms. We performed bioinformatics analysis on RNA-seq datasets containing samples from HF patients and normal individuals to obtain gene expression matrices and identify differently regulated alternative splicing events in HF. By calculating percent spliced-in (PSI) value, we identified 4055 abnormal alternative splicing events of 3142 genes in HF. These genes were significantly enriched in PPAR signaling, regulation of actin cytoskeleton, and muscle contraction. Interestingly, based on abnormal alternative splicing events, two distinct clusters of HF patients with distinct molecular mechanisms and pathways were identified using unsupervised clustering. Additionally, we built a regulatory network consisting of heart failure-related alternative splicing and splicing factors. Subsequently, we identify 203 HF specific pairs between splicing factors and alternative splicing events. Four splicing factors (RBM5, ZRANB2, HnRNPF, and HnRNPA0) were found using LASSO and SVM-RFE algorithms, their expression patterns were confirmed in two other microarray datasets. Our study clarifies involvement of splicing factors and alternative splicing events in HF by thoroughly analyzing RNA-seq data with machine learning methods. The findings may advance our understanding of the regulatory systems underlying biological processes associated with heart failure by providing candidates for further investigation and markers for diagnostic and therapeutic purposes.

Sustainable development has become a strategic consensus in response to the global environmental problems. Green credit is a major policy innovation that promotes the transformation of economic development mode and industrial green transformation (IGT). Using provincial panel data from 2005 to 2020, we investigate the effect of green credit on IGT using a systematic GMM model, a dynamic threshold model, as well as the possible nonlinear relationship. Benchmark regression results show that green credit can encourage industrial green transformation. In addition, there is a single green credit threshold with a value of 0.2612. The trend is “negative to positive”. According to the moderating effect results, environmental regulation moderates in a negative manner. As environmental regulations become more stringent, the contribution of green credit to IGT will diminish. The intermediary mechanism test demonstrates that green technology innovation and marketization level play a partial intermediary role. Heterogeneity testing confirms that the function of green credit in promoting industrial green transformation is more significant in regions with a higher level of green finance development and a lower degree of government intervention. Therefore, the government should encourage financial institutions to provide green credit products and services to meet the financing needs of different green projects, thereby facilitating the industrial green transformation.

Backgrounds: Radiofrequency ablation (RFA) is known to destroy tumoral tissue and activate immune cells. This study aimed to investigate the impact of RFA on peripheral T-cell responses and its relationship with tumor origin and hepatitis status. Methods: A retrospective analysis was conducted on 62 patients with various types of tumors, including hepatocellular carcinoma, colorectal cancer, lung cancer, breast cancer, and others, who underwent RFA treatment between June 2017 and December 2018. Blood samples were collected before and one day after RFA treatment. The peripheral T-cell subsets were measured by flow cytometry, and their changes were analyzed. Results: The study found a decrease in the CD4+CD8-and CD4-CD8+ T-cell subsets after RFA, but no significant changes were observed in the populations of CD4+CD8+ and the CD4+CD8-/CD4-CD8+ ratio. Furthermore, no significant differences were observed in peripheral T-cell subsets concerning tumor type or hepatitis status. Conclusions: The study suggests that RFA treatment may have a short-term impact on peripheral T-cell responses, characterized by a decrease in certain T-cell subsets. However, these changes do not seem to be related to the tumor type or hepatitis status of the patients.

Congestive heart failure (CHF) is a multifaceted cardiovascular condition that imposes significant economic and social burdens on society, while also presenting a dearth of efficacious treatment modalities. Long non-coding RNAs (lncRNAs) possess the ability to influence the pathophysiological mechanisms underlying cardiac disease through their regulation of gene transcription, translation, and post-translational modifications. Additionally, certain lncRNAs can be encoded by the mitochondrial genome, hence impacting mitochondrial function. The heart relies heavily on mitochondrial oxidative phosphorylation for approximately 95 % of its ATP production. Consequently, the primary determinant linking mitochondrial dysfunction to heart failure is the impairment of cardiac energy supply resulting from mitochondrial injury. Cardiac dysfunction can arise as a result of various factors, including metabolic disease, disturbances in calcium homeostasis, oxidative stress, apoptosis, and mitochondrial phagocytosis, all of which are facilitated by mitochondrial damage. Currently, an increasing body of research indicates that lncRNA plays a significant role in the regulation of mitochondrial activity, hence impacting heart failure. As a result, the goal of this paper is to propose new ideas and targets for clinical research and therapy of heart failure by reviewing recent research on the regulatory mechanism of mitochondrial function by novel lncRNAs.

The insulin receptor (IR) plays a crucial role in the growth and metabolism of animals. However, there are still many questions regarding the IR in crustaceans, particularly their role in shrimp growth and glucose metabolism. In this study, we identified a novel insulin-like receptor gene in Litopenaeus vannamei and cloned its full length of 6439 bp. This gene exhibited a highly conserved sequence and structural characteristics. Phylogenetic analysis confirmed it as an unreported RTK2-type IR, namely, LvRTK2. Expression pattern analysis showed that LvRTK2 is primarily expressed in female reproductive and digestive organs. Through a series of in vivo and in vitro experiments, including glucose treatment, exogenous insulin treatment, and starvation treatment, LvRTK2 was confirmed to be involved in the endogenous glucose metabolic pathway of shrimp under different glucose variations. Moreover, long-term and short-term interference experiments with LvRTK2 revealed that the interference significantly reduced the shrimp growth rate and serum glucose clearance rate. Further studies indicated that LvRTK2 may regulate shrimp growth by modulating the downstream PI3K/AKT signaling pathway and a series of glucose metabolism events, such as glycolysis, gluconeogenesis, glycogen synthesis, and glycogenolysis. This report on the characteristics and functions of LvRTK2 confirms the important role of RTK2-type IRs in regulating shrimp growth and glucose metabolism.

Background Stroke patients with coexisting intracranial artery stenosis (ICAS) and white matter lesions (WML) usually have a poor outcome. However, how WML affects stroke prognosis has not been determined. Objective To investigate the quantitative forward flow at the middle cerebral artery in ICAS patients with different degrees of WML using 4D flow. Design Single-center cross-sectional cohort study. Methods Ischemic stroke patients with symptomatic middle cerebral artery (MCA) atherosclerosis were included, and they were divided into 2 groups based on Fazekas scale on Flair image (mild group = Fazekas 0-2, and severe group = Fazekas >2), TOF-MRA and 4D flow were performed to quantify the stenosis degree and forward flow at the proximal of stenosis. The flow parameters were compared between different white matter hyperintensity (WMH) groups, as well as in different MCA stenosis groups, logistic regression was used to validate the association between forward flow and WMH. Results A total of 66 patients were included in this study (mean age 56 years old, 68.2% male). 77.3% of them presented with WMH (Fazekas 1-5). Comparison of flow index between mild and severe WMH groups found a significantly lower forward flow (2.34 ± 1.09 vs 3.04 ± 1.35), higher PI (0.75 ± 0.43 vs 0.66 ± 0.32), and RI (0.49 ± 0.19 vs 0.46 ± 0.15) at ipsilateral infarction MCA in the severe WMH group, all P -values

IntroductionVehicle emissions have become an important source of urban air pollution, and the assessment of air pollution emission characteristics and health effects caused by specific pollution sources can provide scientific basis for air quality management.MethodsIn this paper, vehicle PM2.5 pollution in typical urban agglomerations of China (the Beijing-Tianjin-Hebei urban agglomeration (BTHUA), the triangle of the Central China urban agglomeration (TCCUA) and the Chengdu-Chongqing urban agglomeration (CCUA)) were used as research samples to evaluate the emission characteristics, health effects and economic losses of vehicle PM2.5 pollution based on the emission inventory, air quality model and exposure-response function from 2010 to 2020.ResultsThe results indicated that PM2.5 emissions from vehicles in the three urban agglomerations during 2010-2020 first showed an upward yearly trend and then showed a slow decrease in recent years. Heavy-duty trucks and buses are the main contribution vehicles of PM2.5, and the contribution rates of light-duty vehicles to PM2.5 is increasing year by year. The contribution rate of PM2.5 in Beijing decreased significantly. In addition to capital cities and municipalities directly under the central Government, the emission of pollutants in other cities cannot be ignored. The evaluation results of the impact of PM2.5 pollution from vehicles on population health show that: the number of each health endpoint caused by PM2.5 pollution from vehicles in the BTHUA and CCUA showed an overall upward trend, while the TCCUA showed a downward trend in recent years. Among them, PM2.5 pollution from vehicles in the three major urban agglomerations cause about 78,200 (95% CI: 20,500-138,800) premature deaths, 122,800 (95% CI: 25,600-220,500) inpatients, and 628,400 (95% CI: 307,400-930,400) outpatients and 1,332,400 (95% CI: 482,700-2,075,600) illness in 2020. The total health economic losses caused by PM2.5 pollution from vehicles in the three major urban agglomerations in 2010, 2015 and 2020 were 68.25 billion yuan (95% CI: 21.65-109.16), 206.33 billion yuan (95% CI: 66.20-326.20) and 300.73 billion yuan (95% CI: 96.79-473.16), accounting for 0.67% (95% CI: 0.21-1.07%), 1.19% (95% CI: 0.38%-1.88%) and 1.21% (95% CI: 0.39%-1.90%) of the total GDP of these cities.DiscussionDue to the differences in vehicle population, PM2.5 concentration, population number and economic value of health terminal units, there are differences in health effects and economic losses among different cities in different regions. Among them, the problems of health risks and economic losses were relatively prominent in Beijing, Chengdu, Chongqing, Tianjin and Wuhan.

AbstractThis viewpoint article, which represents the opinions of the authors, discusses the barriers to developing a patient-oriented frailty website and potential solutions. A patient-oriented frailty website is a health resource where community-dwelling older adults can navigate to and answer a series of health-related questions to receive a frailty score and health summary. This information could then be shared with health care professionals to help with the understanding of health status prior to acute illness, as well as to screen and identify older adult individuals for frailty. Our viewpoints were drawn from 2 discussion sessions that included caregivers and care providers, as well as community-dwelling older adults. We found that barriers to a patient-oriented frailty website include, but are not limited to, its inherent restrictiveness to frail persons, concerns over data privacy, time commitment worries, and the need for health and lifestyle resources in addition to an assessment summary. For each barrier, we discuss potential solutions and caveats to those solutions, including assistance from caregivers, hosting the website on a trusted source, reducing the number of health questions that need to be answered, and providing resources tailored to each users’ responses, respectively. In addition to screening and identifying frail older adults, a patient-oriented frailty website will help promote healthy aging in nonfrail adults, encourage aging in place, support real-time monitoring, and enable personalized and preventative care.

Introduction A significant proportion of individuals suffering from post COVID-19 condition (PCC, also known as long COVID) can present with persistent, disabling fatigue similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and post-viral fatigue syndromes. There remains no clear pharmacological therapy for patients with this subtype of PCC, which can be referred to as post-COVID fatigue syndrome (PCFS). A low dose of the opioid antagonist naltrexone (ie, low-dose naltrexone (LDN)) has emerged as an off-label treatment for treating fatigue and other symptoms in PCC. However, only small, non-controlled studies have assessed LDN in PCC, so randomised trials are urgently required.Methods and analysis A prospective, randomised, double-blind, parallel arm, placebo-controlled phase II trial will be performed to assess the efficacy of LDN for improving fatigue in PCFS. The trial will be decentralised and open to eligible individuals throughout the Canadian province of British Columbia (BC). Participants will be recruited through the province-wide Post-COVID-19 Interdisciplinary Clinical Care Network (PC-ICCN) and research volunteer platform (REACH BC). Eligible participants will be 19–69 years old, have had a confirmed or physician-suspected SARS-CoV-2 infection at least 3 months prior and meet clinical criteria for PCFS adapted from the Institute of Medicine ME/CFS criteria. Individuals who are taking opioid medications, have a history of ME/CFS prior to COVID-19 or history of significant liver disease will be excluded. Participants will be randomised to an LDN intervention arm (n=80) or placebo arm (n=80). Participants in each arm will be prescribed identical capsules starting at 1 mg daily and follow a prespecified schedule for up-titration to 4.5 mg daily or the maximum tolerated dose. The trial will be conducted over 16 weeks, with assessments at baseline, 6, 12 and 16 weeks. The primary outcome will be fatigue severity at 16 weeks evaluated by the Fatigue Severity Scale. Secondary outcomes will include pain Visual Analogue Scale score, overall symptom severity as measured by the Patient Phenotyping Questionnaire Short Form, 7-day step count and health-related quality of life measured by the EuroQol 5-Dimension questionnaire.Ethics and dissemination The trial has been authorised by Health Canada and approved by The University of British Columbia/Children’s and Women’s Health Centre of British Columbia Research Ethics Board. On completion, findings will be disseminated to patients, caregivers and clinicians through engagement activities within existing PCC and ME/CFS networks. Results will be published in academic journals and presented at conferences.Trial registration number NCT05430152.

Introduction: Managing cognitive function in care homes is a significant challenge. Individuals in care have a variety of scores across standard clinical assessments, such as the Mini-Mental Status Exam (MMSE), and many of them have scores that fall within the range associated with dementia. A recent methodological advance, brain vital sign monitoring through auditory event-related potentials, provides an objective and sensitive physiological measurement to track abnormalities, differences, or changes in cognitive function. Taking advantage of point-of-care accessibility, the current study evaluated the methodological feasibility, the assessment of whether a particular research method can be successfully implemented, of quantitatively measuring cognition of care home residents using brain vital signs. Secondarily, the current study examined the relationship between brain vital signs, specifically the cognitive processing associated N400 component, and MMSE scores in care home residents. Materials and methods: Brain vital signs used the established N100 (auditory sensation), P300 (basic attention), and N400 (cognitive processing) event-related potential (ERP) components. A total of 52 residents were enrolled, with all participants evaluated using the MMSE. Participants were assigned into homogeneous groups based on their MMSE scores, and were categorized into low (n = 14), medium (n = 17), and high (n = 13) MMSE groups. Both brain vital sign measures and underlying ERP waveforms were examined. Statistical analyses used partial least squares correlation (PLS) analyses in which both MMSE and age were included as factors, as well as jackknife approaches, to test for significant brain vital sign changes. Results: The current study successfully measured and analyzed standardized, quantifiable brain vital signs in a care home setting. ERP waveform data showed specific N400 changes between MMSE groups as a function of MMSE score. PLS analyses confirmed significant MMSE-related and age-related differences in the N400 amplitude (p

Background/Objectives: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a neurological disorder characterized by post-exertional malaise. Despite its clinical relevance, the disease mechanisms of ME/CFS are not fully understood. The previous studies targeting brain function or metabolites have been inconclusive in understanding ME/CFS complexity. We combined single-voxel magnetic resonance spectroscopy (SV-MRS) and functional magnetic resonance imaging (fMRI). Our objectives were to examine the feasibility of the multimodal MRI protocol, identify possible differences between ME/CFS and healthy controls (HCs), and relate MRI findings with clinical symptoms. Methods: We enrolled 18 female ME/CFS participants (mean age: 39.7 ± 12.0 years) and five HCs (mean age: 45.6 ± 14.5 years). SV-MRS spectra were acquired from three voxels of interest: the anterior cingulate gyrus (ACC), brainstem (BS), and left dorsolateral prefrontal cortex (L-DLPFC). Whole-brain fMRI used n-back task testing working memory and executive function. The feasibility was assessed as protocol completion rate and time. Group differences in brain metabolites and fMRI activation between ME/CFS and HCs were compared and correlated with behavioral and symptom severity measurements. Results: The completion rate was 100% regardless of participant group without causing immediate fatigue. ME/CFS appeared to show a higher N-Acetylaspartate in L-DLPFC compared to HCs (OR = 8.49, p = 0.040), correlating with poorer fatigue, pain, and sleep quality scores (p’s = 0.001–0.015). An increase in brain activation involving the frontal lobe and the brainstem was observed in ME/CFS compared to HCs (Z > 3.4, p’s < 0.010). Conclusions: The study demonstrates the feasibility of combining MRS and fMRI to capture neurochemical and neurophysiological features of ME/CFS in female participants. Further research with larger cohorts of more representative sampling and follow-ups is needed to validate these apparent differences between ME/CFS and HCs.

Abstract Background Pituitary dysfunction (PD) is a common complication after aneurysmal subarachnoid hemorrhage (aSAH). The prevalence of PD varies widely at a global level and no recent meta-analysis is available. Therefore, the aim of our systematic review and meta-analysis was to summarize the updated estimates of worldwide prevalence of PD after aSAH. Methods Scopus, Embase, Web of Science, and PubMed databases were used to comprehensively search the appropriate literature and a random-effects meta-analysis on the results of the available studies was performed. The heterogeneity in the prevalence estimates was evaluated by subgroup analysis in terms of types of PD, and acute and chronic phases of aSAH. The onset of PD within 6 months after aSAH was considered as acute, while that after 6 months was considered as chronic. Results Twenty-seven studies with 1848 patients were included in this analysis. The pooled prevalence of PD in the acute phase was 49.6% (95% CI, 32.4-66.8%), and 30.4% (95% CI, 21.4-39.4%) in the chronic phase. Among the hormonal deficiencies, growth hormone dysfunction was the most prevalent in the acute phase, being 36.0% (95% CI, 21.0-51.0%), while hypoadrenalism was the most prevalent in the chronic phase, being 21.0% (95% CI, 12.0-29.0%). Among the six World Health Organization regions, the South-East Asia Region has the highest prevalence of PD in the acute phase (81.0%, 95%CI, 77.0-86.0%, P

Abstract Background N7-methylguanosine (m7G) modification has been reported to regulate RNA expression in multiple pathophysiological processes. However, little is known about its role and association with immune microenvironment in heart failure (HF). Results One hundred twenty-four HF patients and 135 nonfailing donors (NFDs) from six microarray datasets in the gene expression omnibus (GEO) database were included to evaluate the expression profiles of m7G regulators. Results revealed that 14 m7G regulators were differentially expressed in heart tissues from HF patients and NFDs. Furthermore, a five-gene m7G regulator diagnostic signature, NUDT16, NUDT4, CYFIP1, LARP1, and DCP2, which can easily distinguish HF patients and NFDs, was established by cross-combination of three machine learning methods, including best subset regression, regularization techniques, and random forest algorithm. The diagnostic value of five-gene m7G regulator signature was further validated in human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, consensus clustering algorithms were used to categorize HF patients into distinct molecular subtypes. We identified two distinct m7G subtypes of HF with unique m7G modification pattern, functional enrichment, and immune characteristics. Additionally, two gene subgroups based on m7G subtype-related genes were further discovered. Single-sample gene-set enrichment analysis (ssGSEA) was utilized to assess the alterations of immune microenvironment. Finally, utilizing protein–protein interaction network and weighted gene co-expression network analysis (WGCNA), we identified UQCRC1, NDUFB6, and NDUFA13 as m7G methylation-associated hub genes with significant clinical relevance to cardiac functions. Conclusions Our study discovered for the first time that m7G RNA modification and immune microenvironment are closely correlated in HF development. A five-gene m7G regulator diagnostic signature for HF (NUDT16, NUDT4, CYFIP1, LARP1, and DCP2) and three m7G methylation-associated hub genes (UQCRC1, NDUFB6, and NDUFA13) were identified, providing new insights into the underlying mechanisms and effective treatments of HF.

Mass spectrometry imaging (MSI) has been shown to be a valuable tool through nearly every stage of the preclinical drug research and development (R&D) pipeline, and even to the early phase of clinical pharmaceutical evaluation. MSI can specifically resolve distributions of a parent drug and its metabolic products across dosed specimens without loss of spatial information, thus facilitating the direct observation of a drug’s pharmacokinetic processes, such as absorption, distribution, metabolism, and excretion. MSI can simultaneously visualize hundreds of phenotype molecules, including proteins, glycans, metabolites, and lipids, which have unique distribution patterns and biofunctions across different physiologic regions. This featured specificity in the chemical and physical spaces empowers MSI as an ideal analytical technique in exploring a drug’s pharmacodynamic properties, including in vitro/in vivo efficacy, safety, potential toxicity, and possible molecular mechanism. The application of MSI in pharmaceutical research has also been expanded from the conventional dosed tissue analysis to the front end of the preclinical drug R&D pipeline, such as investigating the structure-activity relationship, high-throughput in vitro screening, and ex vivo studies on single cells, organoids, or tumor spheroids. This review summarizes MSI application in pharmaceutical research accompanied by its technical and methodologic advances serving this central demand.

IntroductionAs one of the key areas for air pollution prevention and control in China, the Fenwei Plain is experiencing serious near-surface O3 pollution, which is a key issue that needs to be solved urgently.MethodsBased on pollutant concentration monitoring data and meteorological and health data over the same period, this study analyzed the temporal and spatial characteristics, the relationships with meteorological factors of O3 pollution, and the health effects and economic losses caused by exposure to O3 pollution using environmental health risk and environmental value assessment methods in 11 cities on the Fenwei Plain in China from 2014 to 2020.ResultsThe results showed that O3 pollution has become increasingly serious on the Fenwei Plain in recent years. The annual average concentration of O3_8h_max showed an overall upwards trend, with an increase of 32.39% in 2020 compared to 2014. The mean concentrations observed in summer were the highest, followed by spring and autumn, and the lowest was in winter. The O3 concentration had a significant positive correlation with air temperature and sunshine hours. The evaluation results of the impact of air pollution on population health showed that the number of premature deaths caused by O3 pollution fluctuated and increased during 2014–2020. In 2020, the numbers of total, cardiovascular and respiratory deaths attributable to O3 pollution on the Fenwei Plain were 6,867 (95% CI: 3,739–9,965), 3,652 (95% CI: 1,363–5,905), and 1,257 (95% CI: 747–2,365), respectively, and the total number of premature deaths related to O3 exposure increased by 48.05% compared with 2014. The health and economic losses attributed to O3 pollution on the Fenwei Plain during the study period were 44.22 (95% CI: 22.17–69.18), 47.16 (95% CI: 23.64–73.77), 68.28 (95% CI: 34.27–106.31), 114.44 (95% CI: 57.42–177.76), 110.85 (95% CI: 55.45–172.52), 116.41 (95% CI: 58.24–180.74), and 116.81 (95% CI: 58.00–180.88) billion yuan, respectively. In Linfen City, the increasing rate of the number of premature deaths reached 283.39% because the O3 concentration increased greatly.DiscussionDue to high O3 concentrations and obvious population growth in Xi’an, the problems of premature death and health and economic losses attributed to O3 concentrations exceeding the standard value are prominent.

Objective: To investigate the frailty, as estimated by accumulated health deficits, in association with the symptomatic carotid atherosclerosis and in relation to five-year cardiovascular (CVD) outcomes. Methods: This is a five-year prospective cohort study. Secondary analysis of data from the Beijing Longitudinal Study on Aging. Community-dwelling people aged 55+ years (n = 1257) have been followed between 2009 and 2014, and having carotid ultrasonography examinations with no CVD events at baseline. Frailty was quantified using the deficit accumulation-based frailty index (FI), constructed from 37 health deficits assessed at baseline. The association between the degree of frailty and carotid atherosclerosis was examined using odds ratios (OR) with multivariate logistic regression analyses. Effects of frailty on the probability of five-year cardiovascular events and mortality were evaluated using Cox proportional hazard ratios (HR). The analyses were adjusted for demographics, baseline carotid atherosclerosis status, and CVD risk factors. Results: The FI showed characteristic properties and was independently associated with the major carotid atherosclerosis symptoms, including carotid artery intima-media thickening (the most frail vs. the least frail: OR = 4.39: 1.98–7.82), carotid plaque (OR = 3.41: 1.28–6.54), and carotid plaque stability (OR = 1.19, 95 % CI: 1.01–3.59). Compared with the least frail, the most frail individuals were more likely to develop a cardiovascular event in five years, including myocardial infarction (HR = 3.38, 95 % CI = 1.84–6.19), stroke (HR = 1.26, 95 % CI = 1.00–5.87), CVD death (HR = 6.33, 95 % CI = 1.69–11.02), and all-cause death (HR = 5.95, 95 % CI = 2.74–8.95). Conclusion: Deficit accumulation was closely associated with carotid atherosclerosis risks and strongly predicted five-year CVD events. The frailty index can be used to help identify older adults at high risks of CVD for improved preventive healthcare.

Novel coronavirus pneumonia (COVID-19) is a new type of viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has spread rapidly and become a global pandemic. Heart failure (HF) is the ultimate period of the development of various cardiovascular diseases. There are several research have found that SARS-CoV-2 infection may induce cardiac complications including enhanced cardiac stress biomarkers and heart failure. Our research aims at identifying underlying biological processes and key targets in COVID-19-associated heart failure via bioinformatics analysis. A total of three heart failure datasets and three COVID-19 datasets were obtained using the Gene Expression Omnibus (GEO) database. Batch effects cross each sample were eliminated with surrogate variable analysis algorithm. Then, we identified key modules of COVID-19 datasets and heart failure datasets through weighted gene co-expression network analysis. HF-associated as well as COVID-19-associated key modules were intersected for determining the shared genes of COVID-19-associated heart failure. The pivotal genes associated with COVID-19-related heart failure were determined by intersecting the shared genes with the HF-associated hub genes selected through WGCNA. Furthermore, we conducted GO as well as KEGG enrichment analysis on shared genes of COVID-19-associated heart failure. Two COVID-19-associated key modules as well as three HF-associated key modules were determined. In addition, eleven shared genes for COVID-19-associated heart failure were determined. In conclusion, our work screened two critical genes, namely PYGM and BLM, which may be possible intervention targets for COVID-19-associated heart failure. According to functional enrichment results, the shared genes of COVID-19-associated heart failure showed high enrichment in starch and sucrose metabolism, homologous recombination, Fanconi anemia pathway, and insulin resistance indicate the probably biological processes linked to COVID-19-associated heart failure. These results provided further insights in possible interventional and therapeutic targets of COVID-19-associated heart failure.

Abstract Objective Named entity recognition (NER) is a key and fundamental part of many medical and clinical tasks, including the establishment of a medical knowledge graph, decision-making support, and question answering systems. When extracting entities from electronic health records (EHRs), NER models mostly apply long short-term memory (LSTM) and have surprising performance in clinical NER. However, increasing the depth of the network is often required by these LSTM-based models to capture long-distance dependencies. Therefore, these LSTM-based models that have achieved high accuracy generally require long training times and extensive training data, which has obstructed the adoption of LSTM-based models in clinical scenarios with limited training time. Method Inspired by Transformer, we combine Transformer with Soft Term Position Lattice to form soft lattice structure Transformer, which models long-distance dependencies similarly to LSTM. Our model consists of four components: the WordPiece module, the BERT module, the soft lattice structure Transformer module, and the CRF module. Result Our experiments demonstrated that this approach increased the F1 by 1–5% in the CCKS NER task compared to other models based on LSTM with CRF and consumed less training time. Additional evaluations showed that lattice structure transformer shows good performance for recognizing long medical terms, abbreviations, and numbers. The proposed model achieve 91.6% f-measure in recognizing long medical terms and 90.36% f-measure in abbreviations, and numbers. Conclusions By using soft lattice structure Transformer, the method proposed in this paper captured Chinese words to lattice information, making our model suitable for Chinese clinical medical records. Transformers with Mutilayer soft lattice Chinese word construction can capture potential interactions between Chinese characters and words.

New treatment strategies are required for ulcerative colitis. Here the authors show in mouse models that cholesterol sulfate, an endogenous active cholesterol derivative, contributes to the healing of the mucosal barrier by promoting cholesterol biosynthesis in colonic epithelial cells and exhibits therapeutic efficacy against ulcerative colitis.

Abstract Background The infant mortality rate (IMR) is considered a basic measure of public health for countries around the world. The specific aim of our study was to provide an updated description of infant mortality rate among different regions in rural China, and assess the trends and causes of the IMR geographical disparities. Methods Data were collected from China’s Under-5 Child Mortality Surveillance System(U5CMSS). The annual number of deaths and causes of death were adjusted using a 3-year moving average underreporting rate based on annual national data quality control results. The average annual decline rate (AADR) and the relative risk (RR) of the IMR and cause-specific infant mortality were calculated by Poisson regression and the Cochran–Mantel–Haenszel method. Data analysis was completed by SAS software. Results There was an apparent decrease in infant mortality in rural China from 2010 to 2018, at the AADR of 11.0% (95%CI 9.6–12.4), 11.2% (95%CI 10.3–12.1) and 6.6% (95%CI 6.0–7.3) in the eastern, central and western rural areas, respectively. The IMR was highest in the western rural area, followed by the central and eastern rural areas. Compared with the eastern rural area, the RR of infant mortality in the central rural area remained at 1.4–1.6 and increased from 2.4 (95%CI 2.3–2.6) in 2010–2012 to 3.1 (95% CI 2.9–3.4) in 2016–2018 in the western rural area. Pneumonia, preterm birth /LBW and birth asphyxia were the leading causes of infant deaths in the western rural area. Mortality rates of these three causes fell significantly in 2010–2018 but contributed to a higher proportion of deaths in the western rural area than in the central and western rural ares. Conclusions Our study indicated that the infant mortality rate dropped significantly from 2010 to 2018, however, geographical disparities of IMR in rural China are still persist. Therefore, there is an urgent need for public health programmes and policy interventions for infants in western rural China.

Abstract Introduction Frailty is a state of diminished physiological reserve and can be assessed using the frailty index. Early management of frailty is crucial for preventing adverse outcomes. Intended for assessing home‐living older adults, the initial release of the eFI‐CGA software was prior to the coronavirus disease 2019 (COVID‐19) pandemic. Methods In addressing the increased need of virtual assessment, the eFI‐CGA was upgraded to version 3.0. In this paper, we introduce the updated electronic frailty assessment tool, reporting the newly developed features and validating its use. Results End‐user experiences with the previous versions are discussed. The updated features include a search function to resume disrupted assessments. The improved user interface enabled clinicians to record care management details. Conclusion This study represents an example of software solutions in moving from disruption to transformation, benefiting healthcare for older adults during this challenging time.

Abstract Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer's disease (AD). However, the value of DL in detecting progressive structural MRI (sMRI) abnormalities linked to AD pathology has yet to be established. In this study, an interpretable DL algorithm named the Ensemble of 3‐dimensional convolutional neural network (Ensemble 3DCNN) with enhanced parsing techniques is proposed to investigate the longitudinal trajectories of whole‐brain sMRI changes denoting AD onset and progression. A set of 2369 T1‐weighted images from the multi‐centre Alzheimer's Disease Neuroimaging Initiative and Open Access Series of Imaging Studies cohorts are applied to model derivation, validation, testing, and pattern analysis. An Ensemble‐3DCNN‐based P‐score is generated, based on which multiple brain regions, including amygdala, insular, parahippocampal, and temporal gyrus, exhibit early and connected progressive neurodegeneration. Complex individual variability in the sMRI is also observed. This study combining non‐invasive sMRI and interpretable DL in detecting patterned sMRI changes confirmed AD pathological progression, shedding new light on predicting AD progression using whole‐brain sMRI.

Green innovation culture is essential to the Chinese 14th five-year plan aligned with sustainable development goal 9. This study examines the relationship between green innovation culture and market performance of Chinese small and medium-sized enterprises (SMEs). We evaluated hypothesis by taking a sample of 564 SMEs employees in China through an online survey. The structural equation modelling (SEM) method is used to analyze data. The findings showed that green innovation culture positively influence product and marketing innovation. Similarly, marketing innovation positively affects product innovation and market performance. In addition, product innovation has a substantial effect on market performance. The outcomes of this study imply that SMEs in emerging economies should concentrate on green innovation culture to improve their market performance. In addition, the identification of study limitations and suggestions for further research are also addressed for all stakeholders involved with SMEs.

Abstract Rib fracture detection is time-consuming and demanding work for radiologists. This study aimed to introduce a novel rib fracture detection system based on deep learning which can help radiologists to diagnose rib fractures in chest computer tomography (CT) images conveniently and accurately. A total of 1707 patients were included in this study from a single center. We developed a novel rib fracture detection system on chest CT using a three-step algorithm. According to the examination time, 1507, 100 and 100 patients were allocated to the training set, the validation set and the testing set, respectively. Free Response ROC analysis was performed to evaluate the sensitivity and false positivity of the deep learning algorithm. Precision, recall, F1-score, negative predictive value (NPV) and detection and diagnosis were selected as evaluation metrics to compare the diagnostic efficiency of this system with radiologists. The radiologist-only study was used as a benchmark and the radiologist-model collaboration study was evaluated to assess the model’s clinical applicability. A total of 50,170,399 blocks (fracture blocks, 91,574; normal blocks, 50,078,825) were labelled for training. The F1-score of the Rib Fracture Detection System was 0.890 and the precision, recall and NPV values were 0.869, 0.913 and 0.969, respectively. By interacting with this detection system, the F1-score of the junior and the experienced radiologists had improved from 0.796 to 0.925 and 0.889 to 0.970, respectively; the recall scores had increased from 0.693 to 0.920 and 0.853 to 0.972, respectively. On average, the diagnosis time of radiologist assisted with this detection system was reduced by 65.3 s. The constructed Rib Fracture Detection System has a comparable performance with the experienced radiologist and is readily available to automatically detect rib fracture in the clinical setting with high efficacy, which could reduce diagnosis time and radiologists’ workload in the clinical practice.

Abstract Background A crucial aspect of continued senior care is the early detection and management of frailty. Developing reliable and secure electronic frailty assessment tools can benefit virtual appointments, a need especially relevant in the context of the COVID-19 pandemic. An emerging effort has targeted web-based software applications to improve accessibility and usage. The objectives of this scoping review are to identify and evaluate web-based frailty assessment tools currently available and to identify challenges and opportunities for future development. Methods We conducted a review with literature (e.g., using MEDLINE databases) and Google searches (last updated on October 10, 2021). Each of the identified web applications were assessed based on eight featured categories and assigned a rating score accordingly. Results Twelve web-based frailty assessment applications were found, chiefly provided by the USA (50%) or European countries (41%) and focused on frailty grading and outcome prediction for specific patient groups (59%). Categories that scored well among the applications included the User Interface (2.8/3) and the Cost (2.7/3). Other categories had a mean score of 1.6/3 or lower. The least developed feature was Data Saving. Conclusions Web-based applications represent a viable option for remote frailty assessments and multidisciplinary integrated care of older adults. Despite the available web-based frailty assessments on the Internet, many missed certain needed features for professional use in healthcare settings. This situation calls for fully comprehensive web-based applications, taking into consideration a number of key functions linking graphical user interface and functionalities, and paying special attention to secure data management.

We present the use of conductive spray polymer ionization mass spectrometry (CPSI-MS) combined with machine learning (ML) to rapidly gain the metabolic fingerprint from 1 μl liquid extraction from the biopsied tissue of triple-negative breast cancer (TNBC) in China. The 76 discriminative metabolite markers are verified at the primary carcinoma site and can also be successfully tracked in the serum. The Lasso classifier featured with 15- and 22-metabolites detected by CPSI-MS achieve a sensitivity of 88.8% for rapid serum screening and a specificity of 91.1% for tissue diagnosis, respectively. Finally, the expression levels of their corresponding upstream enzymes and transporters have been initially confirmed. In general, CPSI-MS/ML serves as a cost-effective tool for the rapid screening, diagnosis, and precise characterization for the TNBC metabolism reprogramming in the clinical practice.

Herpes simplex encephalitis (HSE), a complication of herpes simplex virus type I (HSV-1) infection causes neurological disorder or even death in immunocompromised adults and newborns. However, the intrinsic factors controlling the HSE outcome remain unclear. Here, we show that HSE mice exhibit gut microbiota dysbiosis and altered metabolite configuration and tryptophan-nicotinamide metabolism. HSV-1 neurotropic infection activated microglia, with changed immune properties and cell numbers, to stimulate antiviral immune response and contribute substantially to HSE. In addition, depletion of gut microbiota by oral antibiotics (ABX)-treatment triggered the hyper-activation of microglia, which in turn enhanced inflammatory immune response, and cytokine production, resulting in aggregated viral burden and HSE pathology. Furthermore, exogenous administration of nicotinamide n-oxide (NAMO), an oxidative product of nicotinamide derived from gut microbiota, to ABX-treated or untreated HSE mice significantly diminished microglia-mediated proinflammatory response and limited HSV-1 infection in CNS. Mechanistic study revealed that HSV-1 activates microglia by increasing mitochondrial damage via defective mitophagy, whereas microbial metabolite NAMO restores NAD+-dependent mitophagy to inhibit microglia activation and HSE progression. NAMO also prevented neuronal cell death triggered by HSV-1 infection or microglia-mediated microenvironmental toxicity. Finally, we show that NAMO is mainly generated by neomycin-sensitive bacteria, especially Lactobacillus_gasseri and Lactobacillus_reuteri. Together, these data demonstrate that gut microbial metabolites act as intrinsic restrictive factors against HSE progression via regulating mitophagy in microglia, implying further exploration of bacterial or nutritional approaches for treating neurotropic virus-related neurodegenerative diseases.

White matter (WM) neuroplasticity in the human brain has been tracked non-invasively using advanced magnetic resonance imaging techniques, with increasing evidence for improved axonal transmission efficiency as a central mechanism. The current study is the culmination of a series of studies, which characterized the structure-function relationship of WM transmission efficiency in the cortico-spinal tract (CST) during motor learning. Here, we test the hypothesis that increased transmission efficiency is linked directly to increased myelination using myelin water imaging (MWI). MWI was used to evaluate neuroplasticity-related improvements in the CST. The MWI findings were then compared to diffusion tensor imaging (DTI) results, with the secondary hypothesis that radial diffusivity (RD) would have a stronger relationship than axial diffusivity (AD) if the changes were due to increased myelination. Both MWI and RD data showed the predicted pattern of significant results, strongly supporting that increased myelination plays a central role in WM neuroplasticity.

BackgroundHeart failure (HF) is the end stage of various cardiovascular diseases with a high mortality rate. Novel diagnostic and therapeutic biomarkers for HF are urgently required. Our research aims to identify HF-related hub genes and regulatory networks using bioinformatics and validation assays.MethodsUsing four RNA-seq datasets in the Gene Expression Omnibus (GEO) database, we screened differentially expressed genes (DEGs) of HF using Removal of Unwanted Variation from RNA-seq data (RUVSeq) and the robust rank aggregation (RRA) method. Then, hub genes were recognized using the STRING database and Cytoscape software with cytoHubba plug-in. Furthermore, reliable hub genes were validated by the GEO microarray datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR) using heart tissues from patients with HF and non-failing donors (NFDs). In addition, R packages “clusterProfiler” and “GSVA” were utilized for enrichment analysis. Moreover, the transcription factor (TF)–DEG regulatory network was constructed by Cytoscape and verified in a microarray dataset.ResultsA total of 201 robust DEGs were identified in patients with HF and NFDs. STRING and Cytoscape analysis recognized six hub genes, among which ASPN, COL1A1, and FMOD were confirmed as reliable hub genes through microarray datasets and qRT-PCR validation. Functional analysis showed that the DEGs and hub genes were enriched in T-cell-mediated immune response and myocardial glucose metabolism, which were closely associated with myocardial fibrosis. In addition, the TF–DEG regulatory network was constructed, and 13 significant TF–DEG pairs were finally identified.ConclusionOur study integrated different RNA-seq datasets using RUVSeq and the RRA method and identified ASPN, COL1A1, and FMOD as potential diagnostic biomarkers for HF. The results provide new insights into the underlying mechanisms and effective treatments of HF.

The strategic planning and decision making of the government in the combination of high-quality development and green development has had a far-reaching impact on the development of industrial enterprises. This paper grounded theory to build a theoretical framework model of the factors that influence the development of high-quality green industrial enterprises. The data are based on policy documents, policy interpretations, official public opinion, and other original text materials related to the high-quality green development of Chinese industrial enterprises. The research finds that the factors that influence the high-quality green development of industrial enterprises can be divided into three dimensions, including the environmental dimension, the enterprise dimension, and the process dimension. Among them, the enterprise dimension is the most core dimension and directly affects the high-quality green development of industrial enterprises. Different parts (six parts) in each dimension are connected together to form a circular chain of high-quality green development of industrial enterprises. There is also an interaction mechanism within each part.

Finance is significant support for the low-carbon transformation of the real economy, in which digital finance as a new direction of financial development exerts a significant influence on carbon emissions. Therefore, it is crucial to investigate the association between digital finance and carbon emissions in order to develop carbon reduction strategies from the financial side. For this purpose, using the sample set covering 30 provincial areas during 2011–2020, this paper investigates the direct, indirect, and non-linear effects of digital finance on carbon emissions by applying fixed effects, mediating effects, and threshold effects analysis techniques. The results indicate that: (1) digital finance can significantly mitigate carbon emissions at the national level. (2) Digital finance inhibits carbon emissions as it drives green technological innovation and industrial structure upgrading. (3) Significant regional heterogeneity is observed in the effect of digital finance on carbon emissions, i.e., the effects of digital finance on carbon emissions are higher in the east-central region than in the overall sample, while the opposite is true in the western region. (4) The dampening effect on carbon emissions steadily increases as digital finance levels cross the first and second thresholds, respectively. Based on the above considerations, policymakers shall not only develop differentiated digital finance initiatives, but shall also fully unleash carbon emission reduction potential by rationalizing and optimizing industrial layout and strengthening financial subsidies for green technology innovation.

Abstract Posttranslational modification (PTM) and regulation of protein stability are crucial to various biological processes. Histone deacetylase 6 (HDAC6), a unique histone deacetylase with two functional catalytic domains (DD1 and DD2) and a ZnF-UBP domain (ubiquitin binding domain, BUZ), regulates a number of biological processes, including gene expression, cell motility, immune response, and the degradation of misfolded proteins. In addition to the deacetylation of histones, other nonhistone proteins have been identified as substrates for HDAC6. Hsp90, a molecular chaperone that is a critical modulator of cell signaling, is one of the lysine deacetylase substrates of HDAC6. Intriguingly, as one of the best-characterized regulators of Hsp90 acetylation, HDAC6 is the client protein of Hsp90. In addition to regulating Hsp90 at the post-translational modification level, HDAC6 also regulates Hsp90 at the gene transcription level. HDAC6 mainly regulates the Hsp90-HSF1 complex through the ZnF-UBP domain, thereby promoting the HSF1 entry into the nucleus and activating gene transcription. The mutual interaction between HDAC6 and Hsp90 plays an important role in the regulation of protein stability, cell migration, apoptosis and other functions. Plenty of of studies have indicated that blocking HDAC6/Hsp90 has a vital regulatory role in multifarious diseases, mainly in cancers. Therefore, developing inhibitors or drugs against HDAC6/Hsp90 becomes a promising development direction. Herein, we review the current knowledge on molecular regulatory mechanisms based on the interaction of HDAC6 and Hsp90 and inhibition of HDAC6 and/or Hsp90 in oncogenesis and progression, antiviral and immune-related diseases and other vital biological processes.

The improvement of carbon emission efficiency and the realization of the goal of “carbon peaking and carbon neutrality” are the key issues that China needs to solve urgently at this stage. The green and low-carbon transformation of the economy requires sufficient financial support. Whether green finance is an opportunity to improve China’s carbon emission efficiency is worth studying. For the aim, based on the macro-panel data of 30 provinces in China from 2010 to 2019, this paper uses fixed effect model and spatial Durbin model to study the impact of green finance on regional carbon emission efficiency. The results show that: First, the development of green finance can improve the carbon emission efficiency; Second, in addition to the “local effect”, the influence of green finance on carbon emission efficiency has a “neighborhood effect”, that is, it has a spatial spillover effect on carbon emission efficiency in neighboring areas, and this effect only exists in a short time; Third, the impact of green finance on carbon emission efficiency is heterogeneous in different regions with different environmental regulations. This paper has reference significance for green finance development and the implementation of the goal of “carbon peaking and carbon neutrality” in China.

This study examines the impact of digital financing on the degree of financing constraints and discusses the mediating effect of investor confidence. The data are based on companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2010 to 2019. To investigate the impact of digital financing on the financing constraints of companies in different situations, the heterogeneity of internal control and equity characteristics of different organizations is analyzed. The results using fixed-effects models show that (i) the change in digital finance has a significant negative impact on the level of corporate financing constraints; (ii) investor confidence plays a mediating role between digital finance and financing constraints; and (iii) the level of internal control impacts the relationship between the digital finance and the corporate financing constraints. Specifically, for the organizations with better internal control, there is a significant negative relationship between digital finance and corporate financing constraints while for organizations with poor internal control, digital finance has no significant influence on the extent of financing constraints; and (iv) digital finance of private organizations is significantly negatively correlated with the extent of financing constraints, while for government organizations, a negative relationship is not evident.

Abstract Background Adopting a better understanding of how both older adults and health care providers view the community management of frailty is necessary for improving home health, especially facing the coronavirus disease 2019 (COVID‐19) pandemic. We conducted a qualitative focus group study to assess how both older adults and health care providers view frailty and virtual health care in home health. Methods Two focus groups enrolled home‐living older adults and health care professionals, respectively (n = 15). Questions targeting the use of virtual / telehealth technologies in‐home care for frail older adults were administered at audio‐recorded group interviews. Transcribed discussions were coded and analyzed using NVivo software. Results The older adult group emphasized the autonomy related to increasing frailty and social isolation and the need for transparent dissemination of health care planning. They were optimistic about remote technology‐based supports and suggested that telehealth / health‐monitoring/tracking were in high demand. Health care professionals emphasized the importance of a holistic biopsychosocial approach to frailty management. They highlighted the need for standardized early assessment and management of frailty. Conclusions The integrated perspectives provided an updated understanding of what older adults and practitioners value in home‐living supports. This knowledge is helpful to advancing virtual home care, providing better care for frail individuals with complex health care needs.

Under the new normal of economy, a series of active fiscal policies such as tax reduction and fee reduction and new infrastructure construction in China have reduced the source of local government revenue, while the expansion of fiscal expenditure and the widening gap between revenue and expenditure have further exacerbated the motivation of local governments to borrow. Using the spatial econometric model and based on the data of 30 provinces in China from 2006 to 2018, this article deeply studies the impact of local government debt on economic growth and its spatial spillover effect and discusses the regional location heterogeneity of this growth effect. The research shows that: (1) local government debt has significantly promoted regional economic growth; (2) the growth promoting effect of local government borrowing has significant spatial spillover; (3) borrowing debt has the greatest effect on promoting economic growth in the central region, followed by the east, and the west is almost unaffected. Therefore, the Chinese government needs to continue to implement an active fiscal policy, improve the promotion and assessment mechanism of local officials, and adhere to the goal of balanced regional development.

Climate change is one of the most serious threats facing the world today. Environmental pollution and depletion of natural resources have been highlighted by the United Nations Sustainable Development Goals (SDGs), paving the way for modern concepts such as sustainable growth to be introduced. Therefore, this research explores the relationship between green finance, energy efficiency, and CO2 emissions in the G7 countries. The study uses panel data model technique to examine the dependence structure of green finance, energy efficiency, and CO2 emissions. Moreover, we use DEA to construct an energy efficiency index of G7 countries. A specific interval exists between the values of the energy efficiency indexes. Japan, the United Kingdom, and the United States were named the most energy-efficient countries in the world, based on results obtained for five consecutive years in this category. However, according to the comparative rankings, France and Italy are the most successful of all the G7 members, followed by the United Kingdom and Germany. Our overall findings of the econometric model confirm the negative impact of green finance and energy efficiency on CO2 emissions; however, this relationship varies across the different quantiles of the two variables. The findings in the study confirm that green finance is the best financial strategy for reducing CO2 emissions.

Abstract Introduction Severe internal carotid stenosis, if left untreated, can pose serious risks for ischemic stroke and cognitive impairments. The effects of revascularization on any aspects of cognition, however, are not well understood, as conflicting results are reported, which have mainly been centered on paper‐based cognitive analyses. Here, we summarized and evaluated the publications to date of functional MRI (fMRI) studies that examined the mechanisms of functional brain activation and connectivity as a way to reflect cognitive effects of revascularization on patients with carotid stenosis. Methods A PubMed and Google Scholar (covering the relevant literature until November 1, 2021) search yielded eight original studies of the research line, including seven resting‐state and one task‐based fMRI reports. Results Findings demonstrated treatment‐related alterations in fMRI signal intensity and symmetry level, regional fMRI activation pattern, and functional brain network connectivity. The functional brain changes were associated largely with improvement in cognitive function assessed using standard cognitive test scores. Conclusions These findings support the contribution of fMRI to the understanding of brain functional activation and connectivity changes revealing cognitive effects of revascularization in the management of severe carotid stenosis. The review also highlighted the importance of reproducibility through enhancing experimental designs and cognitive task applications with future research for potential clinical translation.

Calcific aortic valve disease (CAVD) is a common heart valve disease in aging populations, and aberrant osteogenic differentiation of valvular interstitial cells (VICs) plays a critical role in the pathogenesis of ectopic ossification of the aortic valve. miR-214 has been validated to be involved in the osteogenesis process. Here, we aim to investigate the role and mechanism of miR-214 in CAVD progression. miR-214 expression was significantly downregulated in CAVD aortic valve leaflets, accompanied by upregulation of osteogenic markers. Overexpression of miR-214 suppressed osteogenic differentiation of VICs, while silencing the expression of miR-214 promoted this function. miR-214 directly targeted ATF4 and Sp7 to modulate osteoblastic differentiation of VICs, which was proved by dual luciferase reporter assay and rescue experiment. miR-214 knockout rats exhibited higher mean transvalvular velocity and gradient. The expression of osteogenic markers in aortic valve leaflets of miR-214 knockout rats was upregulated compared to that of the wild-type group. Taken together, our study showed that miR-214 inhibited aortic valve calcification via regulating osteogenic differentiation of VICs by directly targeting ATF4 and Sp7, indicating that miR-214 may act as a profound candidate of targeting therapy for CAVD.

5G can provide public network mode and private network mode for public users and vertical industries.Based on the requirements of service continuity and industry users,three deployment modes of 5G wireless private network for different scenarios and needs of industry users were studied,the standardization status,industrialization ability and supporting degree of 5G wireless private network was discussed,and the scenarios and applications that 5G wireless private network can achieve at present were analyzed.In the end,the future implementation of 5G wireless private network technology with ultra-low delay demand was prospected.

Abstract Background Herpes simplex virus 1, an enveloped DNA virus belonging to the Herpesviridae family, spreads to neurons and causes pathological changes in the central nervous system. The purpose of this study was to investigate the potency and mechanism of antiviral activity of Aspergillipeptide D, a cyclic pentapeptide isolated from a culture broth of marine gorgonian-derived fungus Aspergillus sp. SCSIO 41501, At present, there are many studies on the anti-tumor, anti-clotting, anti-oxidant and immunoinflammatory effects of Aspergillipeptide D, but little research has been done on the anti-HSV-1 activity of Aspergillipeptide D. Methods The anti-HSV-1 activity of Aspergillipeptide D was evaluated by plaque reduction assay. The mechanism of action against HSV-1 was determined from the effective stage. Then we assayed the viral DNA replication, viral RNA synthesis and protein expression, respectively. We also identified the proteins that interact with gB by mass spectrometry, and assayed the effect of Aspergillipeptide D on the interaction between the virus gB protein and cell proteins. Results Plaque reduction experiments showed that Aspergillipeptide D did not affect HSV-1 early infection events, including viral inactivation, attachment and penetration. Interestingly, Aspergillipeptide D dramatically reduced both the gene and protein levels of viral late protein gB, and suppressed its location in the endoplasmic reticulum and Golgi apparatus. In contrast, overexpression of gB restored viral production. Finally, proteomic analysis revealed that the numbers of cellular proteins that interacted with gB protein was largely decreased by Aspergillipeptide D. These results suggested that Aspergillipeptide D inhibited gB function to affect HSV-1 intercellular spread. Conclusions Our results indicated that Aspergillipeptide D might be a potential candidate for HSV-1 therapy, especially for ACV-resistant strains.

In this paper, we propose a novel girth measurement system based on multi-view stereo images for garment design. Our system is set in a fixed location to capture three pairs of stereo images for the subject by six calibrated and synchronously triggered cameras. An important feature of this system is the use of an optimized semantic segmentation network that can efficiently segment the girth region in the captured six-view stereo images. Another important feature of this system is the use of color subspace classification and coordinate clustering that can effectively constrain the stereo matching within the scope of markers. Then, the system performs only on the corresponding clusters to extract stereo matching point pairs of markers correctly. The space coordinates of 3D point corresponding to each stereo matching point pair are calculated in each coordinate system of stereo cameras. The unified coordinates of these 3D markers are transformed from three different coordinate systems into one unified coordinate system. Girth is measured by curve fitting of these markers and calculating the length of the fitting curve. Our proposed system performs passive and intelligent girth measurement in garment design, and overcomes the problem of too many invalid stereo matching point pairs in girth measurement. Experimental results demonstrate its accuracy. Our system has a maximum bust measurement error of 1.28cm for woman and 1.31cm for man and a maximum waist measurement error of 1.18cm for woman and 0.99cm for man, which are within the error limit regulated by China national standards GB/T 2664-2017, 2665-2017, 2666-2017 and textile industry standard FZ/T 81004-2012.

Herpes simplex virus type I (HSV-1) is a member of the Alphaherpesvirinae family, which could initiate labial herpes caused by the reactivation of HSV-1 primary infection, and secondary infection even causes herpes encephalitis. The study presented here demonstrates that Hsp90 inhibitors (AT-533 and 17-AAG) directly targeted the HSV-1 UL42-Hsp90 complex, and Hsp90 interacted with HSV-1 UL42 in silicon and experiment. Interestingly, Hsp90 inhibitors also reduced virus titers of ACV-resistant clinical HSV-1 strains (153 and blue strain), revealing that HSV-1 UL42 would be a new target against ACV-resistant HSV-1 strains. Altogether, this present study indicates that Hsp90 inhibitors prevent HSV-1 proliferation by regulating the interaction between Hsp90 and HSV-1 UL42, suggesting a promising target for anti-HSV-1 therapies in the replication.

Herpes simplex virus 1 (HSV-1) is a common neurotropic virus, the herpes simplex encephalitis (HSE) caused by which is considered to be the most common sporadic but fatal encephalitis. Traditional antiviral drugs against HSV-1 are limited to nucleoside analogs targeting viral factors. Inhibition of heat shock protein 90 (Hsp90) has potent anti-HSV-1 activities via numerous mechanisms, but the effects of Hsp90 inhibitors on HSV-1 infection in neuronal cells, especially in the phase of virus entry, are still unknown. In this study, we aimed to investigate the effects of the Hsp90 inhibitors on HSV-1 infection of neuronal cells. Interestingly, we found that Hsp90 inhibitors promoted viral adsorption but inhibited subsequent penetration in neuronal cell lines and primary neurons, which jointly confers the antiviral activity of the Hsp90 inhibitors. Mechanically, Hsp90 inhibitors mainly impaired the interaction between Hsp90 and cofilin, resulting in reduced cofilin membrane distribution, which led to F-actin polymerization to promote viral attachment. However, excessive polymerization of F-actin inhibited subsequent viral penetration. Consequently, unidirectional F-actin polymerization limits the entry of HSV-1 virions into neuron cells. Our research extended the molecular mechanism of Hsp90 in HSV-1 infection in neuron cells and provided a theoretical basis for developing antiviral drugs targeting Hsp90.

We introduce Nafion into the ambient ionization technique of spray mass spectrometry to serve for in situ desalting and direct analysis of biological fluids. Nafion was coated onto the surface of the triangular spray tip as the cation exchange material. Because the sulfonic group from the Nafion membrane effectively exchanges their carried protons with inorganic salt ions (e.g., Na+ and K+), the analyte’s ionization efficiency can be significantly enhanced by reducing ion suppression. The desalting efficiency can reach 90% and the maximum tolerance of the absolute salt amount reaches 100 μmol. The mass spectral profile can also be simplified by removing the multiple adducted ion types from small-molecule drugs and metabolites ([M + Na]+ and [M + K]+), or multiply charged ions formed by proteins ([M + nNa]n+ and [M + nK]n+). Thus, the Nafion coating makes less ambiguous data interpretation collected from spray mass spectrometry for qualitative profiling or quantitative measurement of a target analyte.

Abstract The survival rate of oral squamous cell carcinoma (OSCC) can be greatly improved if intervention could be initiated as early as possible. This poses a technical demand for developing a sensitive screening and specific in vitro diagnosis method for OSCC. Herewith, a large cohort consisting of 241 healthy contrast (HC) and 578 OSCC patients were recruited for conducting the rapid metabolic profiling of trace volume serum using conductive polymer spray ionization mass spectrometry (CPSI‐MS). Statistical analysis picked out 65 metabolite ions as potential characteristic markers for differentiating OSCC from HC. With the aid of a supporting vector machine (SVM), OSCC can be distinguished from HC with an accuracy of 98.0% by cross‐validation in the discovery cohort and 89.6% accuracy in the validation cohort. Furthermore, orthogonal partial least square‐discriminant analysis (OPLS‐DA) also initially showed the potential for OSCC staging, especially between T1/T2 and T3/T4 stages with an accuracy of 90.1%. CPSI‐MS combined with SVM or OPLS‐DA can not only quickly distinguish OSCC from HC but also predict the OSCC progression from T1/2 to T3/4 stages in a few minutes, making it a promising tool for both screening and diagnosing high‐risk population. Key points Sixty‐five characteristic metabolite ions significantly changed in OSCC serum metabolic profile compared to that in the HC group. CPSI‐MS combined with SVM achieved 89.6% accuracy on the validation cohort for OSCC prediction. CPSI‐MS/OPLS‐DA can distinguish T1/T2 from T3/T4 stages with an accuracy of 90.1% by cross‐validation.

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a multisystem medical condition with heterogeneous symptom expression. Currently, there is no effective cure or treatment for the standard care of patients. A variety of ME/CFS symptoms can be linked to the vital life functions of the brainstem, the lower extension of the brain best known as the hub relaying information back and forth between the cerebral cortex and various parts of the body.Objective/Methods: Over the past decade, Magnetic Resonance Imaging (MRI) studies have emerged to understand ME/CFS with interesting findings, but there has lacked a synthesized evaluation of what has been found thus far regarding the involvement of the brainstem. We conducted this study to review and evaluate the recent MRI findings via a literature search of the MEDLINE database, from which 11 studies met the eligibility criteria.Findings: Data showed that MRI studies frequently reported structural changes in the white and gray matter. Abnormalities of the functional connectivity within the brainstem and with other brain regions have also been found. The studies have suggested possible mechanisms including astrocyte dysfunction, cerebral perfusion impairment, impaired nerve conduction, and neuroinflammation involving the brainstem, which may at least partially explain a substantial portion of the ME/CFS symptoms and their heterogeneous presentations in individual patients.Conclusions: This review draws research attention to the role of the brainstem in ME/CFS, helping enlighten future work to uncover the pathologies and mechanisms of this complex medical condition, for improved management and patient care.

cGAS, a DNA sensor in mammalian cells, catalyzes the generation of 2’-3’-cyclic AMP-GMP (cGAMP) once activated by the binding of free DNA. cGAMP can bind to STING, activating downstream TBK1-IRF-3 signaling to initiate the expression of type I interferons. Although cGAS has been considered a traditional DNA-binding protein, several lines of evidence suggest that cGAS is a potential RNA-binding protein (RBP), which is mainly supported by its interactions with RNAs, RBP partners, RNA/cGAS-phase-separations as well as its structural similarity with the dsRNA recognition receptor 2’-5’ oligoadenylate synthase. Moreover, two influential studies reported that the cGAS-like receptors (cGLRs) of fly Drosophila melanogaster sense RNA and control 3′-2′-cGAMP signaling. In this review, we summarize and discuss in depth recent studies that identified or implied cGAS as an RBP. We also comprehensively summarized current experimental methods and computational tools that can identify or predict RNAs that bind to cGAS. Based on these discussions, we appeal that the RNA-binding activity of cGAS cannot be ignored in the cGAS-mediated innate antiviral response. It will be important to identify RNAs that can bind and regulate the activity of cGAS in cells with or without virus infection. Our review provides novel insight into the regulation of cGAS by its RNA-binding activity and extends beyond its DNA-binding activity. Our review would be significant for understanding the precise modulation of cGAS activity, providing the foundation for the future development of drugs against cGAS-triggering autoimmune diseases such as Aicardi-Gourtières syndrome.

Abstract Premature mothers present more anxiety and stress after delivery, which may be caused by mother–infant separation while hospitalised. Skin‐to‐skin contact (SSC), a mitigating factor for mother–infant separation, can benefit infants and mothers in many ways, but few studies focused on its efficacy on maternal anxiety and stress states. Therefore, this review aims to evaluate the effect of SSC on anxiety and stress. Comprehensive research was conducted in nine databases. Meta‐analysis was conducted to investigate the effect of SSC, and subgroup analyses were performed to explain the sources of heterogeneity. Eight randomised controlled trials with 728 participants were included, and SSC significantly reduced the level of anxiety ([standardised mean difference, SMD] −0.72; 95% CI −1.08 to −0.35) and stress state ([SMD] −0.84; 95% CI −1.59 to −0.09). One subgroup analysis revealed that SSC can relieve anxiety if performing SSC no less than 1 h per day ([SMD] −0.94; 95% CI −1.34 to −0.53). Another subgroup analysis suggested that applying SSC repeatedly and lasting less than 1 week ([SMD] −1.49; 95% CI −2.31 to −0.66) or for 1 week to 2 weeks ([SMD] −1.04; 95% CI −1.29 to −0.79) can significantly reduce maternal anxiety level but no significance if lasting over 2 weeks ([SMD] −0.33; 95% CI −0.67 to 0.01). SSC can effectively improve anxiety and stress states among premature mothers after delivery, and not definitive finding presents that only SSC that was performed no less than 60 min could improve postpartum anxiety states, while SSC alone was not as effective when carried out over 2 weeks.