Monogenic Diabetes with GATA6 Mutations: Characterization of a Novel Family and a Comprehensive Analysis of the GATA6 Clinical and Genetics Traits.

Monogenic diabetes caused by GATA6 mutations were almost described as neonatal diabetes, and the phenotypic spectrum has expanded since then. Our study underscores the broad phenotypic spectrum by reporting a de novo GATA6 mutation in a family. Furthermore, we reviewed related literature to summarize the clinical and genetic characteristics of monogenic diabetes with GATA6 mutations (n = 39) in order to improve clinicians' understanding of the disease. We conclude that the GATA6 missense mutation (c. 749G > T, p. Gly250Val) is not reported presently, characterized by adult-onset diabetes with pancreatic dysplasia and located in transcriptional activation region. Carries with GATA6 mutations (n = 55) have a variable spectrum of diabetes, ranging from neonatal (72.7%), childhood-onset (20%) to adults-onset (7.5%). 83.5% of patients with abnormal pancreatic development. Heart and hepatobillary defects are the most common abnormalities of extrapancreatic features. Most mutations with GATA6 are loss of function (LOF, 71.8%) and located in functional region. Functional studies mostly support loss-of-function as the pathophysiological mechanism. In conclusion, there are various types of diabetes with GATA6 mutations, which can also occur in adult diabetes. Phenotypic defects with GATA6 mutations are most frequently malformations of pancreas and heart. This highlights the importance of comprehensive clinical evaluation of identified carriers to evaluate their full phenotypic spectrum.

Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease.

Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD), commonly occurring in patients at middle and late stages of the disease. Automatic and accurate FoG detection and prediction have emerged as a promising tool for long-term monitoring of PD and implementation of gait assistance systems. This paper reviews the recent development of FoG detection and prediction using wearable sensors, with attention on identifying knowledge gaps that need to be filled in future research. This review searched the PubMed and Web of Science databases to collect studies that detect or predict FoG with wearable sensors. After screening, 89 of 270 articles were included. The data description, extracted features, detection/prediction methods, and classification performance were extracted from the articles. As the number of papers of this area is increasing, the performance has been steadily improved. However, small datasets and inconsistent evaluation processes still hinder the application of FoG detection and prediction with wearable sensors in clinical practice.

Association between geriatric nutritional risk index and 28 days mortality in elderly patients with sepsis: a retrospective cohort study.

Background: There is a significant controversy surrounding the impact of the geriatric nutritional risk index (GNRI) on mortality among elderly septic patients. This retrospective cohort study aimed to investigate the association between GNRI at admission and 28 days mortality in elderly septic patients. Methods: We retrospectively analyzed data collected from the MIMIC IV database between 2009 and 2019, which included 2,834 septic patients aged 65 years and above. The exposure variable was the GNRI, determined according to albumin levels, height, and weight. The primary outcome was 28 days mortality. We employed multivariable Cox regression analyses and Kaplan-Meier survival curves to examine the association between GNRI and 28 days mortality. We used restricted cubic splines to determine if there was a non-linear relationship between 28 days mortality and GNRI in elderly patients with sepsis and to examine the presence of a threshold saturation effect. In addition, interaction tests were conducted to identify subgroups that exhibited significant differences. Results: A total of 2,834 elderly patients with sepsis participated in the study. Following adjustment, multivariable Cox regression analyses demonstrated that the GNRI was related to 28 days mortality (HR = 0.97, p < 0.001, 95% CI: 0.97-0.98). An L-shaped connection between GNRI and 28 days mortality was discovered via restricted cubic spline analysis, with an inflection point of 98.1. On the left side of the inflection point, GNRI levels were significantly negatively linked with 28 days mortality (HR = 0.967, 95% CI: 0.959-0.974; p < 0.001), and on the right side, there was no significant correlation (HR = 1.043, 95% CI: 0.984-1.106; p = 0.1549). Conclusion: In this analysis of data from a large cohort of elderly septic patients, GNRI scores on admission were correlated with a 28 days risk of death from sepsis in the elderly suggesting that GNRI scores could serve as a valuable indicator for evaluating mortality rates among elderly septic patients in the intensive care unit (ICU).

Dihydrokaempferol attenuates CCl4-induced hepatic fibrosis by inhibiting PARP-1 to affect multiple downstream pathways and cytokines.

The pathophysiological mechanism of hepatic fibrosis (HF) is related to the excessive activation of the DNA repair enzyme poly ADP-ribose polymerase-1 (PARP-1). The drugs, targeting PARP-1, are scarce. Therefore, the lead compound, moderately inhibiting PARP-1, with anti-HF properties should be identified. This study screened dihydrokaempferol (DHK) from herbs based on preliminary studies to intervene in a CCl4-induced liver injury and HF model in mice. In vitro, the expression levels of PARP-1-regulated related proteins and phosphorylation were examined. The binding pattern of DHK and PARP-1 was analyzed using molecular docking and molecular dynamics platforms. The results showed that DHK could significantly attenuate CCl4-induced liver injury and HF in mice. Moreover, it could also attenuate the toxic effects of CCl4 on HepG2 and inhibit α-SMA and Collagen 1/3 synthesis of LX-2 cells in-vitro. Molecular docking revealed that DHK could competitively bind to the Glu-988 and His-862 residues of the upstream DNA repair enzyme PARP-1, moderately inhibiting its overactivation. This led to maintaining NAD+ levels and energy metabolism in hepatocytes and inhibiting the activation of PARP-1-regulated downstream signaling pathways (TGF-ß1, etc.), related proteins (p-Smd2/3, etc.), and inflammatory mediators while acting indirectly. Thus, DHK could attenuate CCl4-induced liver injury and HF in mice in a different mechanism from those of the existing reported flavonoids. It was associated with inhibiting the expression of downstream pathways and related cytokines by competitively binding to PARP-1. This study might provide a basis and direction for the design and exploration of anti-HF lead compounds.

The ability of critical care nurses to identify pressure injury and incontinence-associated dermatitis: A multicentre cross-sectional survey.

AIM: To investigate the ability of critical care nurses to identify pressure injury and incontinence-associated dermatitis and analyse the possible influencing factors. DESIGN: Cross-sectional survey. METHODS: This study was conducted at 24 hospitals across 12 provinces in China. A self-made electronic questionnaire was used. Nurses identified and judged injuries according to the information provided. RESULTS: The average identification score for pressure injury and incontinence-associated dermatitis was 9.00 ± 3.51 points, and only 2.16% of nurses scored ≥16 points. The average correct identification rate for pressure injury and incontinence-associated dermatitis was 45%. The correct identification rate for stage 1 pressure injury was the highest, while those for stage 3, stage 4, deep tissue pressure injury and unstageable pressure injury were all lower than 50%; incontinence-associated dermatitis was also easily misjudged. Nurses' educational backgrounds, professional titles, job positions, hospital levels and learning frequency were the factors that affected their ability to identify pressure injury and incontinence-associated dermatitis.

Multimodal Data for the Detection of Freezing of Gait in Parkinson's Disease.

Freezing of gaits (FOG) is a very disabling symptom of Parkinson's Disease (PD), affecting about 50% of PD patients and 80% of advanced PD patients. Studies have shown that FOG is related to a complex interplay between motor, cognitive and affective factors. A full characterization of FOG is crucial for FOG detection/prediction and prompt intervention. A protocol has been designed to acquire multimodal physical and physiological information during FOG, including gait acceleration (ACC), electroencephalogram (EEG), electromyogram (EMG), and skin conductance (SC). Two tasks were designed to trigger FOG, including gait initiation failure and FOG during walking. A total number of 12 PD patients completed the experiments and produced a length of 3 hours and 42 minutes of valid data including 2 hours and 14 minutes of normal gait and 1 hour and 28 minutes of freezing of gait. The FOG episodes were labeled by two qualified physicians. The multimodal data have been validated by a FOG detection task.

High-accuracy wearable detection of freezing of gait in Parkinson's disease based on pseudo-multimodal features.

OBJECTIVE: Freezing of gait (FoG) is a serious symptom of Parkinson's disease and prompt detection of FoG is crucial for fall prevention. Although multimodal data combining electroencephalography (EEG) benefit accurate FoG detection, the preparation, acquisition, and analysis of EEG signals are time-consuming and costly, which impedes the application of multimodal information in FoG detection. This work proposes a wearable FoG detection method that merges multimodal information from acceleration and EEG while avoiding the acquisition of real EEG data. METHODS: A proxy measurement (PM) model based on long-short-term-memory (LSTM) network was proposed to measure EEG features from accelerations, and pseudo-multimodal features, i.e., pseudo-EEG and acceleration, could be extracted using a highly wearable inertial sensor for FoG detection. RESULTS: Based on a self-collected FoG dataset, the performance of different feature combinations were compared in terms of subject-dependent and cross-subject settings. In both settings, pseudo-multimodal features achieved the most promising performance, with a geometric mean of 91.0 ± 5.0% in subject-dependent setting and 91.0 ± 3.5% in cross-subject setting. CONCLUSION: Our study suggests that wearable FoG detection can be enhanced through leveraging cross-modal information fusion. SIGNIFICANCE: The new method provides a promising path for multimodal information fusion and the long-term monitoring of FoG in living environments.

Effect of intensive care unit diary on incidence of posttraumatic stress disorder, anxiety, and depression of adult intensive care unit survivors: A systematic review and meta-analysis.

AIM: To systematically evaluate the effect of intensive care unit diary psychotherapy on the incidence of posttraumatic stress disorder, anxiety, and depression after discharge from intensive care unit. BACKGROUND: Many studies have reported the potential advantages and risks of intensive care unit diary psychotherapy in adult patients discharged from intensive care unit, but the results are divergent. DESIGN: Systematic review and meta-analysis of prospective randomized controlled or case-controlled studies. DATA SOURCE: Databases such as Cochran Library, Pubmed, Embase, CINAHL, and ProQuest databases, China national knowledge infrastructure (CNKI) were searched for literatures published from January 2000-March 2020. REVIEW METHODS: We use the Cochrane Risk of Bias Tool for quality assessment and audit manager 5.3 software for meta-analysis. The main result is the incidence of posttraumatic stress disorder, anxiety, and depression. RESULTS: Ten studies meeting the inclusion criteria were identified, including eight randomized controlled studies and two case-controlled studies, with a total of 1,210 patients. The pooled results of this meta-analysis indicated that the intensive care unit diary could reduce the incidence of posttraumatic stress disorder, anxiety, and depression. CONCLUSION: This study showed that an intensive care unit diary could improve the psychological symptoms of adult intensive care unit patients after discharge. However, due to limitations such as publication bias and case sample size, the results should be carefully considered. Researchers need to further clarify the multidisciplinary collaborative process of intensive care unit diary therapy, the real beneficiaries, and its impact on family members' psychological status by conducting large, robust studies in the future. IMPACT: This study's findings suggest that medical staff need to re-examine the role of intensive care unit diary therapy, its standardized implementation and provide effective intervention for reducing psychological stress-related symptoms of intensive care unit patients after discharge.

Protective effect of Epicatechin on APAP-induced acute liver injury of mice through anti-inflammation and apoptosis inhibition.

Epicatechin (EC) is the most effective compound in Euonymus alatus (Thunb.)Sieb, and possesses a series of benefits, including anti-inflammatory, antioxidant, antiobesity and anticancer effects. In this study, we investigated the protective effects of EC in Acetaminophen(N-acetyl-p-aminophenol, APAP)-induced acute liver injury in C57BL/6J mice and explored the possible mechanisms involved in these effects.[Formula: see text].

Using machine learning approaches to predict high-cost chronic obstructive pulmonary disease patients in China.

The accurate identification and prediction of high-cost Chronic obstructive pulmonary disease (COPD) patients is important for addressing the economic burden of COPD. The objectives of this study were to use machine learning approaches to identify and predict potential high-cost patients and explore the key variables of the forecasting model, by comparing differences in the predictive performance of different variable sets. Machine learning approaches were used to estimate the medical costs of COPD patients using the Medical Insurance Data of a large city in western China. The prediction models used were logistic regression, random forest (RF), and extreme gradient boosting (XGBoost). All three models had good predictive performance. The XGBoost model outperformed the others. The areas under the ROC curve for Logistic Regression, RF and XGBoost were 0.787, 0.792 and 0.801. The precision and accuracy metrics indicated that the methods achieved correct and reliable results. The results of this study can be used by healthcare data analysts, policy makers, insurers, and healthcare planners to improve the delivery of health services.

Euonymus alatus and its monomers alleviate liver fibrosis both in mice and LX2 cells by blocking TßR1-Smad2/3 and TNF-α-NF-κB pathways.

This study aimed to investigate the protective effects, effective constituents and preliminary mechanisms of Euonymus alatus on liver fibrosis and screen new high-efficacy drug for fibrosis. 112 male C57BL/6 mice were randomly divided into 14 groups: control group (CG), CCL4 group (CTG), low/medium/high dose of Euonymus alatus ethanol extracts (EAE), catechin (CA), dihydroquercetin (DHQ) and kaempferol (KA) groups. The study lasted for 30 days by injecting CCL4 in peritoneal cavity to make fibrosis model, all mice were sacrificed to observe morphological changes and collagenous fiber by HE and Masson staining, to test liver index, ALT, AST, to measure the expression of α-SMA and collagen I by immunohistochemistry and western blotting, to discuss the pathways of TßR1-Smad2/3 and TNF-α-NF-κB by WB and Elisa; after being evaluated the efficacy, anti-fibrosis drug of highest efficacy was chosen to repeat these indexes in human hepatic stellate cells-LX2. Results showed that EAE/CA/DHQ/KA prevented increases in liver index, ALT, AST, α-SMA, collagen I, TßR1, Smad2/3, TNF-α and p-NF-κB caused by CCL4 in dose-dependence, they also improved the liver morphology, decreased inflammatory cell infiltration and collagenous fiber in dose-dependence, CA' efficacy was best in mice; in LX-2, CA also decreased the expression of α-SMA, collagen I, TGF-ß, Smad2/3. All findings suggested that Euonymus alatus could alleviate liver inflammation and fibrosis by inhibiting TßR1-Smad2/3 and TNF-α-NF-κB pathways, flavonoid were effective constituents and catechin was screened as a new star for its best performance.

Decreased HCN2 channel expression attenuates neuropathic pain by inhibiting pro-inflammatory reactions and NF-κB activation in mice.

Hyperpolarization-activated cyclic nucleotide-gated 2 (HCN2) ion channel activity plays a crucial role in the progress of peripheral neuropathic pain (PNP). However, the mechanism of HCN2 channels on PNP remains unclear. Here, we investigated the effects of HCN2 channel expression on the mechanical allodynia and thermal hyperalgesia, the local inflammatory response, the activation of astrocytes, microglia and transcription factor NF-κB in mice with spared sciatic nerve injury (SNI). The present study showed that the expression of HCN2 channels was increased in L4-L5 ipsilateral spinal dorsal horns, accompanied by a decreased paw mechanical withdrawal threshold (MWT) and paw withdrawal latency (PWL) in SNI mice. After intrathecal injection of ZD-7288 and si-HCN2, both MWT and PWL were significantly increased, while the level of pro-inflammatory factors TNF-α, IL-1ß and MCP-1 were decreased in L4-L5 ipsilateral spinal dorsal horn. Furthermore, the inhibition of HCN2 channels reduces the activated astrocytes and microglia, and suppressed NF-κB p65 activation and nuclear translocation. In conclusion, the present study suggests that decreased HCN2 channel expression attenuates neuropathic pain by inhibiting pro-inflammatory reactions and NF-κB activation.

A Guide to Production, Crystallization, and Structure Determination of Human IKK1/α.

A class of extracellular stimuli requires activation of IKK1/α to induce generation of an NF-κB subunit, p52, through processing of its precursor p100. p52 functions as a homodimer or heterodimer with another NF-κB subunit, RelB. These dimers in turn regulate the expression of hundreds of genes involved in inflammation, cell survival, and cell cycle. IKK1/α primarily remains associated with IKK2/ß and NEMO as a ternary complex. However, a small pool of it is also observed as a low molecular weight complex(es). It is unknown if the p100 processing activity is triggered by activation of IKK1/α within the larger or the smaller complex pool. Constitutive activity of IKK1/α has been detected in several cancers and inflammatory diseases. To understand the mechanism of activation of IKK1/α, and enable its use as a drug target, we expressed recombinant IKK1/α in different host systems, such as E. coli, insect, and mammalian cells. We succeeded in expressing soluble IKK1/α in baculovirus infected insect cells, obtaining mg quantities of highly pure protein, crystallizing it in the presence of inhibitors, and determining its X-ray crystal structure. Here, we describe the detailed steps to produce the recombinant protein, its crystallization, and its X-ray crystal structure determination.

[Effects of Coriaria Sinica Maxim's extract on microcirculation and oxidative stress of wounds in rats with deep second-degree burn].

OBJECTIVE: To investigate the effects of Coriaria Sinica Maxim's extract(CSME) on microcirculation and oxidative stress of wounds in rats with deep second-degree burn. METHODS: One hundred and eighty rats were randomly divided into normal saline group(NS), white petroleum group(WPL), silver sulfadiazine group (SSD), Coriariasinica Maxim's extract group which were divided into low dose(CSME-L),middle dose(CSME-M) and high dose(CSME-H). After anesthesia with burn instrument to burn the hair removal area of rats, these wounds were confirmed by pathological results with deep second degree burns.And then,those drugs were applied respectively on the wounds,such as NS、WPL、SSD and different concentrations of CSME. After injury at 48 h, 7 d, 14 d and 21 d,the healing rate(HR) of wound was measured, and the microvessel density (MVD), tissue moisture (TM), vascular endothelial growth factor (VEGF), model driven architecture (MDA), superoxide dismutase(SOD) and hydroxyproline(HYP) were detected, too. All pathological sections of the wound tissue were observed. RESULTS: The HR of CSME groups were obviously increased with a dose-dependent manner, which was significantly higher than that of NS and WPL (P<0.05); On the 21st day, the diameter, number, distribution of the vessels and and the TM were less than other groups with a dose-dependent manner; On the 7th and 14th day after injury, CSME groups were significantly higher than the NS, WPL and SSD with a dose-dependent manner (P<0.05), but, on the 21st day after injury, they were lower than NS, WPL and SSD with a dose-dependent (P<0.05) manner. The levels of SOD, HYP, NO and ET in CSME groups were higher than those in other groups with dose-dependent on SOD activity, HYP, NO and ET content (P<0.05), while MDA activity was weaker than other groups (P<0.05). Similarly, pathological findings were also shown that CSME groups were better than other groups with a dose-dependent manner in decrease decreasing of wound repair time and hyperplasia of scar tissue. CONCLUSIONS: CSME can relieve tissue edema, promote wound contraction, speed up the formation of eschar and accelerate the proliferation of granulation tissue, which are beneficial to the wound healing in the early stages. But, it can inhibit the hyperplasia of granulation tissue to prevent the excessive scar hyperplasia of burn wound in the later stages. Its mechanism is related to regulation what microcirculation, oxidativestress, NO and VEGF.

Protein Cofactors Are Essential for High-Affinity DNA Binding by the Nuclear Factor κB RelA Subunit.

Transcription activator proteins typically contain two functional domains: a DNA binding domain (DBD) that binds to DNA with sequence specificity and an activation domain (AD) whose established function is to recruit RNA polymerase. In this report, we show that purified recombinant nuclear factor κB (NF-κB) RelA dimers bind specific κB DNA sites with an affinity significantly lower than that of the same dimers from nuclear extracts of activated cells, suggesting that additional nuclear cofactors might facilitate DNA binding by the RelA dimers. Additionally, recombinant RelA binds DNA with relatively low affinity at a physiological salt concentration in vitro. The addition of p53 or RPS3 (ribosomal protein S3) increases RelA:DNA binding affinity 2- to >50-fold depending on the protein and ionic conditions. These cofactor proteins do not form stable ternary complexes, suggesting that they stabilize the RelA:DNA complex through dynamic interactions. Surprisingly, the RelA-DBD alone fails to bind DNA under the same solution conditions even in the presence of cofactors, suggesting an important role of the RelA-AD in DNA binding. Reduced RelA:DNA binding at a physiological ionic strength suggests that multiple cofactors might be acting simultaneously to mitigate the electrolyte effect and stabilize the RelA:DNA complex in vivo. Overall, our observations suggest that the RelA-AD and multiple cofactor proteins function cooperatively to prime the RelA-DBD and stabilize the RelA:DNA complex in cells. Our study provides a mechanism for nuclear cofactor proteins in NF-κB-dependent gene regulation.

Applicability of internet search index for asthma admission forecast using machine learning.

OBJECTIVE: This study aimed to determine whether a search index could provide insight into trends in asthma admission in China. An Internet search index is a powerful tool to monitor and predict epidemic outbreaks. However, whether using an internet search index can significantly improve asthma admissions forecasts remains unknown. The long-term goal is to develop a surveillance system to help early detection and interventions for asthma and to avoid asthma health care resource shortages in advance. METHODS: In this study, we used a search index combined with air pollution data, weather data, and historical admissions data to forecast asthma admissions using machine learning. RESULTS: Results demonstrated that the best area under the curve in the test set that can be achieved is 0.832, using all predictors mentioned earlier. CONCLUSION: A search index is a powerful predictor in asthma admissions forecast, and a recent search index can reflect current asthma admissions with a lag-effect to a certain extent. The addition of a real-time, easily accessible search index improves forecasting capabilities and demonstrates the predictive potential of search index.

The effects of air pollution on length of hospital stay for adult patients with asthma.

Length of hospital stay (LOS) of asthma can be a reflection of the disease burden faced by patients, and it is also sensitive to air pollution. This study aims at estimating and validating the effects of air pollution and readmission on the LOS for those who have asthma, considering their readmission history, minimum temperature, and threshold effects of air pollutants. In addition, sex, age, and season were also constructed for stratification to achieve more precise and specific results. The results show that no significant effects of PM2.5 and NO2 on LOS were observed in any of the patients, but there were significant effects of PM2.5 and NO2 on LOS when a stratifying subgroup analysis was performed. The effect of PM10 on LOS was found to be lower than that of PM2.5 and higher than that of NO2 . SO2 did not have a significant effect on LOS for patients with asthma in our study. Our study confirmed that the adverse effects of air pollutants (such as PM10 ) on LOS for patients with asthma existed; in addition, these effects vary for different stratifications. We measured the effects of air pollutants on the LOS for patients with asthma, and this study offers policy makers quantitative evidence that can support relevant policies for health care resource management and ambient air pollutants control.

Markov Chain-Based Acute Effect Estimation of Air Pollution on Elder Asthma Hospitalization.

Background: Asthma caused substantial economic and health care burden and is susceptible to air pollution. Particularly, when it comes to elder asthma patient (older than 65), the phenomenon is more significant. The aim of this study is to investigate the Markov-based acute effects of air pollution on elder asthma hospitalizations, in forms of transition probabilities. Methods: A retrospective, population-based study design was used to assess temporal patterns in hospitalizations for asthma in a region of Sichuan province, China. Approximately 12 million residents were covered during this period. Relative risk analysis and Markov chain model were employed on daily hospitalization state estimation. Results: Among PM2.5, PM10, NO2, and SO2, only SO2 was significant. When air pollution is severe, the transition probability from a low-admission state (previous day) to high-admission state (next day) is 35.46%, while it is 20.08% when air pollution is mild. In particular, for female-cold subgroup, the counterparts are 30.06% and 0.01%, respectively. Conclusions: SO2 was a significant risk factor for elder asthma hospitalization. When air pollution worsened, the transition probabilities from each state to high admission states increase dramatically. This phenomenon appeared more evidently, especially in female-cold subgroup (which is in cold season for female admissions). Based on our work, admission amount forecast, asthma intervention, and corresponding healthcare allocation can be done.