Affiliated Hospital of Hangzhou Normal University

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Ferroptosis is a newly discovered type of cell death triggered by intracellular phospholipid peroxidation that is morphologically, biologically and genetically distinct from other types of cell death. Ferroptosis is classified as regulated necrosis and is more immunogenic than apoptosis. To date, compelling evidence indicates that ferroptosis plays an important role in inflammation, and several antioxidants functioning as ferroptosis inhibitors have been shown to exert anti-inflammatory effects in experimental models of certain diseases. Our review provides an overview of the link between ferroptosis and inflammation; a better understanding of the mechanisms underlying ferroptosis and inflammation may hasten the development of promising therapeutic strategies involving ferroptosis inhibitors to address inflammation.

Ferroptosis is an iron-dependent, oxidative cell death, and is characterized by iron-dependent accumulation of reactive oxygen species (ROS) within the cell. It has been implicated in various human diseases, including cancer. Recently, ferroptosis as a non-apoptotic form of cell death induced by small molecules is emerging in specific cancer types, however, its relevance in colorectal cancer (CRC) is unexplored and remains unclear. Here, we showed that ferroptosis inducer RSL3 initiated cell death and ROS accumulation in HCT116, LoVo and HT29 CRC cells over a 24 h time course. Furthermore, we determined that ROS levels and transferrin expression were elevated in CRC cells treated with RSL3 accompanied by a decrease in the expression of glutathione peroxidase 4 (GPX4), indicating an iron-dependent cell death, ferroptosis. Overexpression GPX4 resulted in decreased cell death after RSL3 treatment. Taken together, our results suggest that the induction of ferroptosis contributed to RSL3-induced cell death in CRC cells and ferroptosis may be a pervasive and dynamic form of cell death for cancer treatment.

Obesity is associated with impaired intestinal barrier function and dysbiosis of the gut microbiota. Spermidine, a polyamine that acts as an autophagy inducer, has important benefits in patients with aging-associated diseases and metabolic dysfunction. However, the mechanism of spermidine on obesity remains unclear. Here, we show that spermidine intake is negatively correlated with obesity in both humans and mice. Spermidine supplementation causes a significant loss of weight and improves insulin resistance in diet-induced obese (DIO) mice. These effects are associated with the alleviation of metabolic endotoxemia and enhancement of intestinal barrier function, which might be mediated through autophagy pathway and TLR4-mediated microbial signaling transduction. Moreover, spermidine causes the significant alteration of microbiota composition and function. Microbiota depletion compromises function, while transplantation of spermidine-altered microbiota confers protection against obesity. These changes might partly be driven by an SCFA-producing bacterium, Lachnospiraceae NK4A136 group, which was decreased in obese subjects and subsequently increased by spermidine. Notably, the change of Lachnospiraceae NK4A136 group is significantly correlated with enhanced gut barrier function induced by spermidine. Our results indicate that spermidine supplementation may serve as a viable therapy for obesity.

BACKGROUND: Severe traumatic brain injury (TBI) has been increasing with greater incidence of injuries from traffic or sporting accidents. Although there are a number of animal models of TBI using progesterone for head injury, the effects of progesterone on neurologic outcome of acute TBI patients remain unclear. The aim of the present clinical study was to assess the longer-term efficacy of progesterone on the improvement in neurologic outcome of patients with acute severe TBI. METHODS: A total of 159 patients who arrived within 8 hours of injury with a Glasgow Coma Score </= 8 were enrolled in the study. A prospective, randomized, placebo-controlled trial of progesterone was conducted in the Neurotrauma Center of our teaching hospital. The patients were randomized to receive either progesterone or placebo. The primary endpoint was the Glasgow Outcome Scale score 3 months after brain injury. Secondary efficacy endpoints included the modified Functional Independence Measure score and mortality. In a follow-up protocol at 6 months, the Glasgow Outcome Scale and the modified Functional Independence Measure scores were again determined. RESULTS: Of the 159 patients randomized, 82 received progesterone and 77 received placebo. The demographic characteristics, the mechanism of injury, and the time of treatment were compared for the two groups. After 3 months and 6 months of treatment, the dichotomized Glasgow Outcome Scale score analysis exhibited more favorable outcomes among the patients who were given progesterone compared with the control individuals (P = 0.034 and P = 0.048, respectively). The modified Functional Independence Measure scores in the progesterone group were higher than those in the placebo group at both 3-month and 6-month follow-up (P < 0.05 and P < 0.01). The mortality rate of the progesterone group was significantly lower than that of the placebo group at 6-month follow-up (P < 0.05). The mean intracranial pressure values 72 hours and 7 days after injury were lower in the progesterone group than in the placebo group, but there was no statistical significance between the two groups (P > 0.05). Instances of complications and adverse events associated with the administration of progesterone were not found. CONCLUSION: Our data suggest that acute severe TBI patients with administration of progesterone hold improved neurologic outcomes for up to 6 months. These results provide information important for further large and multicenter clinical trials on progesterone as a promising neuroprotective drug. TRIAL REGISTRATION: ACTRN12607000545460.

BACKGROUND: The coronavirus disease (COVID-19) epidemic has not been completely controlled. Although great achievements have been made in COVID-19 research and many antiviral drugs have shown good therapeutic effects against COVID-19, a simple oral antiviral drug for COVID-19 has not yet been developed. We conducted a meta-analysis to investigate the improvement in mortality or hospitalization rates and adverse events among COVID-19 patients with three new oral antivirals (including molnupiravir, fluvoxamine and Paxlovid). METHODS: We searched scientific and medical databases, such as PubMed, Web of Science, Embase and Cochrane Library for relevant articles and screened the references of retrieved studies on COVID-19. RESULTS: A total of eight studies were included in this study. The drug group included 2440 COVID-19 patients, including 54 patients who died or were hospitalized. The control group included a total of 2348 COVID-19 patients, including 118 patients who died or were hospitalized. The overall odds ratio (OR) of mortality or hospitalization was 0.33 (95% confidence interval [CI], 0.22-0.49) for COVID-19 patients in the drug group and placebo group, indicating that oral antiviral drugs were effective for COVID-19 patients and reduced the mortality or hospitalization by approximately 67%. CONCLUSIONS: This study showed that three novel oral antivirals (molnupiravir, fluvoxamine and Paxlovid) are effective in reducing the mortality and hospitalization rates in patients with COVID-19. In addition, the three oral drugs did not increase the occurrence of adverse events, thus exhibiting good overall safety. These three oral antiviral drugs are still being studied, and the available data suggest that they will bring new hope for COVID-19 recovery and have the potential to be a breakthrough and very promising treatment for COVID-19.KEY MESSAGESMany antiviral drugs have shown good therapeutic effects, and there is no simple oral antiviral drug for COVID-19 patients.Meta-analysis was conducted for three new oral antivirals to evaluate the improvement in mortality or hospitalization rates and adverse events among COVID-19 patients.We focussed on three new oral Coronavirus agents (molnupiravir, fluvoxamine and Paxlovid) and hope to provide guidance for the roll-out of oral antivirals.

Abstract Ferroptosis, a novel form of programmed cell death, is characterized by iron-dependent lipid peroxidation and has been shown to be involved in multiple diseases, including cancer. Stimulating ferroptosis in cancer cells may be a potential strategy for cancer therapy. Therefore, ferroptosis-inducing drugs are attracting more attention for cancer treatment. Here, we showed that erianin, a natural product isolated from Dendrobium chrysotoxum Lindl , exerted its anticancer activity by inducing cell death and inhibiting cell migration in lung cancer cells. Subsequently, we demonstrated for the first time that erianin induced ferroptotic cell death in lung cancer cells, which was accompanied by ROS accumulation, lipid peroxidation, and GSH depletion. The ferroptosis inhibitors Fer-1 and Lip-1 but not Z-VAD-FMK, CQ, or necrostatin-1 rescued erianin-induced cell death, indicating that ferroptosis contributed to erianin-induced cell death. Furthermore, we demonstrated that Ca 2+ /CaM signaling was a critical mediator of erianin-induced ferroptosis and that blockade of this signaling significantly rescued cell death induced by erianin treatment by suppressing ferroptosis. Taken together, our data suggest that the natural product erianin exerts its anticancer effects by inducing Ca 2+ /CaM-dependent ferroptosis and inhibiting cell migration, and erianin will hopefully serve as a prospective compound for lung cancer treatment.

: Our data for the first time suggest that the natural product β-elemene is a new ferroptosis inducer and combinative treatment of β-elemene and cetuximab is sensitive to KRAS mutant CRC cells by inducing ferroptosis and inhibiting EMT, which will hopefully provide a prospective strategy for CRC patients with RAS mutations.

OBJECTIVE: To investigate the diagnostic value of serological testing and dynamic variance of serum antibody in coronavirus disease 2019 (COVID-19). METHODS: This study retrospectively included 43 patients with a laboratory-confirmed infection and 33 patients with a suspected infection, in whom the disease was eventually excluded. The IgM/IgG titer of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was measured by chemiluminescence immunoassay analysis. RESULTS: Compared to molecular detection, the sensitivities of serum IgM and IgG antibodies to diagnose COVID-19 were 48.1% and 88.9%, and the specificities were 100% and 90.9%, respectively.In the COVID-19 group, the IgM-positive rate increased slightly at first and then decreased over time; in contrast, the IgG-positive rate increased to 100% and was higher than IgM at all times. The IgM-positive rate and titer were not significantly different before and after conversion to virus-negative. The IgG-positive rate was up to 90% and not significantly different before and after conversion to virus-negative. However, the median IgG titer after conversion to virus-negative was double that before, and the difference was significant. CONCLUSIONS: Viral serological testing is an effective means of diagnosis for SARS-CoV-2 infection. The positive rate and titer variance of IgG are higher than those of IgM in COVID-19.

The brain connectome collects the complex network architectures, looking at both static and dynamic functional connectivity. The former normally requires stationary signals and connections. However, the human brain activity and connections are most likely time dependent and dynamic, and related to ongoing rhythmic activity. We developed an open-source MATLAB toolbox DynamicBC with user-friendly graphical user interfaces, implementing both dynamic functional and effective connectivity for tracking brain dynamics from functional MRI. We provided two strategies for dynamic analysis: (1) the commonly utilized sliding-window analysis and (2) the flexible least squares based time-varying parameter regression strategy. The toolbox also implements multiple functional measures including seed-to-voxel analysis, region of interest (ROI)-to-ROI analysis, and voxel-to-voxel analysis. We describe the principles of the implemented algorithms, and then present representative results from simulations and empirical data applications. We believe that this toolbox will help neuroscientists and neurologists to easily map dynamic brain connectomics.

Lactate is an end product of glycolysis. As a critical energy source for mitochondrial respiration, lactate also acts as a precursor of gluconeogenesis and a signaling molecule. We briefly summarize emerging concepts regarding lactate metabolism, such as the lactate shuttle, lactate homeostasis, and lactate-microenvironment interaction. Accumulating evidence indicates that lactate-mediated reprogramming of immune cells and enhancement of cellular plasticity contribute to establishing disease-specific immunity status. However, the mechanisms by which changes in lactate states influence the establishment of diverse functional adaptive states are largely uncharacterized. Posttranslational histone modifications create a code that functions as a key sensor of metabolism and are responsible for transducing metabolic changes into stable gene expression patterns. In this review, we describe the recent advances in a novel lactate-induced histone modification, histone lysine lactylation. These observations support the idea that epigenetic reprogramming-linked lactate input is related to disease state outputs, such as cancer progression and drug resistance.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets.

Ferroptosis is a non-apoptotic regulated cell death caused by iron accumulation and subsequent lipid peroxidation. Currently, the therapeutic role of ferroptosis on cancer is gaining increasing interest. Baicalin an active component in Scutellaria baicalensis Georgi with anticancer potential various cancer types; however, the effects of baicalein on bladder cancer and the underlying molecular mechanisms remain largely unknown. In the study, we investigated the effect of baicalin on bladder cancer cells 5637 and KU-19-19. As a result, we show baicalin exerted its anticancer activity by inducing apoptosis and cell death in bladder cancer cells. Subsequently, we for the first time demonstrate baicalin-induced ferroptotic cell death in vitro and in vivo, accompanied by reactive oxygen species (ROS) accumulation and intracellular chelate iron enrichment. The ferroptosis inhibitor deferoxamine but not necrostatin-1, chloroquine (CQ), N-acetyl-l-cysteine, l-glutathione reduced, or carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]-fluoromethylketone (Z-VAD-FMK) rescued baicalin-induced cell death, indicating ferroptosis contributed to baicalin-induced cell death. Mechanistically, we show that ferritin heavy chain 1 (FTH1) was a key determinant for baicalin-induced ferroptosis. Overexpression of FTH1 abrogated the anticancer effects of baicalin in both 5637 and KU19-19 cells. Taken together, our data for the first time suggest that the natural product baicalin exerts its anticancer activity by inducing FTH1-dependent ferroptosis, which will hopefully provide a prospective compound for bladder cancer treatment.

OBJECTIVES: To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk. DESIGN: Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach. SETTING: 25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data. PARTICIPANTS: A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor. RESULTS: ). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture. CONCLUSIONS: This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk.

The COVID-19 pandemic has had a negative psychological effect on college students, and the prevalence of anxiety, depression, and stress among Chinese college students is lower than among non-Chinese college students.

Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at the clinical level. We identify TRAF2- and NCK-interacting kinase (TNIK) as an anti-fibrotic target using a predictive artificial intelligence (AI) approach. Using AI-driven methodology, we generated INS018_055, a small-molecule TNIK inhibitor, which exhibits desirable drug-like properties and anti-fibrotic activity across different organs in vivo through oral, inhaled or topical administration. INS018_055 possesses anti-inflammatory effects in addition to its anti-fibrotic profile, validated in multiple in vivo studies. Its safety and tolerability as well as pharmacokinetics were validated in a randomized, double-blinded, placebo-controlled phase I clinical trial (NCT05154240) involving 78 healthy participants. A separate phase I trial in China, CTR20221542, also demonstrated comparable safety and pharmacokinetic profiles. This work was completed in roughly 18 months from target discovery to preclinical candidate nomination and demonstrates the capabilities of our generative AI-driven drug-discovery pipeline.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

BACKGROUND: Cuff-based blood pressure measurement lacks comfort and convenience. Here, we examined whether blood pressure can be determined in a contactless manner using a novel smartphone-based technology called transdermal optical imaging. This technology processes imperceptible facial blood flow changes from videos captured with a smartphone camera and uses advanced machine learning to determine blood pressure from the captured signal. METHODS: We enrolled 1328 normotensive adults in our study. We used an advanced machine learning algorithm to create computational models that predict reference systolic, diastolic, and pulse pressure from facial blood flow data. We used 70% of our data set to train these models and 15% of our data set to test them. The remaining 15% of the sample was used to validate model performance. RESULTS: We found that our models predicted blood pressure with a measurement bias±SD of 0.39±7.30 mm Hg for systolic pressure, -0.20±6.00 mm Hg for diastolic pressure, and 0.52±6.42 mm Hg for pulse pressure, respectively. CONCLUSIONS: Our results in normotensive adults fall within 5±8 mm Hg of reference measurements. Future work will determine whether these models meet the clinically accepted accuracy threshold of 5±8 mm Hg when tested on a full range of blood pressures according to international accuracy standards.