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The issues of state estimations based on distributed observers for linear time-invariant (LTI) systems with multiple sensors are discussed in this paper. We deal with the scenario when the information exchange has known time delays, and aim at designing a distributed observer for each subsystem such that each distributed observer can estimate the system state asymptotically by rejecting the time delay. To begin with, by rewriting the target system in a connecting form, a subsystem which is affected by the time-delay states of other nodes is established. And then, for this subsystem, a distributed observer with time delay is constructed. Moreover, an equivalent state transformation is made for the observer error dynamic system based on the observable canonic decomposition theorem. Further, in order to ensure that the distributed observer error dynamic system is asymptotically stable even if there exists a time delay, a linear matrix inequality (LMI) which is relative to the Laplace matrix is elaborately set up, and a special Lyapunov function candidate based on the LMI is considered. Next, based on the Lyapunov function and Lyapunov stability theory, we prove that the error dynamic system of the distributed observer is asymptotically stable, and the observer gain is determined by a feasible solution of the LMI. Finally, a simulation example is given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Natural regeneration is deemed essential for maintaining biodiversity and ecosystem stability. Previous studies, however, have primarily concentrated on regions exhibiting limited environmental and climatic variability, overlooking the classification of natural regeneration based on age and source. Research conducted at the mesoscale, characterized by increased environmental variability and the incorporation of neighborhood competition and understory-associated vegetation, enhances our comprehension of the multifaceted influences on natural regeneration. To comprehend this issue, this study implemented 60 plots, each measuring 20 m × 20 m, across five distinct areas of Chongqing, China. Twenty explanatory variables were chosen from five diverse categories: understory vegetation, neighborhood competition, stand structure, climatic factors, and environmental factors. And the naturally regenerated species were classified into seedlings and saplings, as well as endogenous and exogenous species, based on their age and origin. We examined the response of the different categories of natural regeneration to various factors and constructed a structural equation model (SEM) for significant factors to investigate their direct and indirect effects on natural regeneration. A total of 61 regenerated tree species belonging to 29 families and 42 genera were found in the study area, and the naturally regenerating species with high importance values were Quercus fabri, Robinia pseudoacacia, Alangium chinense, Cunninghamia lanceolata, and Ligustrum lucidum. It was found that neighborhood competition and understory-associated vegetation explained the largest proportion (more than 50%) of the variation in the different categories of natural regeneration, and forests with clumped distribution (W), a high mingling index (M) and strong competition (H) had a reduced natural regeneration capacity. Understory-associated herbs significantly reduced natural regeneration and the crowdedness index (C) significantly inhibited the understory-associated herbs, thus indirectly promoting natural regeneration. The shrub cover is significantly and positively correlated with the number of naturally regenerated plants and can be used as an indicator of a forest community's regeneration potential. Understanding the differences in the importance of various factors at the mesoscale, as well as their direct and indirect impacts, can help us further comprehend the mechanisms of natural regeneration and provide a foundation for the sustainable development of forests. [ABSTRACT FROM AUTHOR]

Underground cable trench inspection robots work in narrow, variable friction coefficient, and complex road environments. The running trajectory easily deviates from the desired path and leads to a collision, or even the destruction of the robot or cable. Addressing this problem, a path-following control method for the dual-tracked chassis robot based on a self-coupling PID (SCPID) control algorithm was developed. The caterpillar robot dynamics were modelled and both the unknown dynamics and external bounded disturbances were defined as sum disturbances, thus mapping the nonlinear system into a linearly disturbed system, then the self-coupling PD (SCPD) controller was designed. The system proved to be a robust stability control system and only one parameter, the velocity factor, needed to be tuned to achieve parameter calibration. Meanwhile, to solve the problem that the error-based speed factor is not universal and to improve the adaptive ability of the SCPD controller, an iterative method was used for adaptive tuning. The simulation results showed that the SCPID can achieve better control. The field test results showed that the SCPD's maximum offset angle was 56.7% and 10.3% smaller than incremental PID and sliding mode control (SMC), respectively. The inspection time of the SCPD was 20% faster than other methods in the same environment. [ABSTRACT FROM AUTHOR]

Sepsis remains a critical concern in healthcare, and its management is complicated when patients have pre-existing diabetes and varying body mass indexes (BMIs). This retrospective multicenter observational study, encompassing data from 15,884 sepsis patients admitted between 2012 and 2017, investigates the relationship between peak glucose levels and peak glycemic gap in the first 3 days of ICU admission, and their impact on mortality. The study reveals that maintaining peak glucose levels between 141–220 mg/dL is associated with improved survival rates in sepsis patients with diabetes. Conversely, peak glycemic gaps exceeding 146 mg/dL are linked to poorer survival outcomes. Patients with peak glycemic gaps below −73 mg/dL also experience inferior survival rates. In terms of predicting mortality, modified Sequential Organ Failure Assessment–Peak Glycemic Gap (mSOFA-pgg) scores outperform traditional SOFA scores by 6.8% for 90-day mortality in overweight patients. Similarly, the modified SOFA-Peak Glucose (mSOFA-pg) score demonstrates a 17.2% improvement over the SOFA score for predicting 28-day mortality in underweight patients. Importantly, both mSOFA-pg and mSOFA-pgg scores exhibit superior predictive power compared to traditional SOFA scores for patients at high nutritional risk. These findings underscore the importance of glycemic control in sepsis management and highlight the potential utility of the mSOFA-pg and mSOFA-pgg scores in predicting mortality risk, especially in patients with diabetes and varying nutritional statuses. [ABSTRACT FROM AUTHOR]

The study aimed to determine whether using body composition data acquired through bio-electrical impedance analysis (BIA) to adjust diet formulas could improve outcomes in septic patients. There were 132 septic patients in medical intensive care units enrolled in the prospective, randomized, double-blind, interventional study. For the intervention group, dietitians had access to BIA data for adjusting diet formulas according to body composition variables on days 1, 3, and 8. The patients were also stratified based on nutritional risk using the modified Nutrition Risk in Critically ill (mNUTRIC) score. Patients with intervention were more likely to achieve caloric and protein intake goals compared to the control group, especially in the low-risk group. The intervention did not significantly affect mortality, but the survival curves suggested potential benefits. The high-risk group had longer ICU stays and mechanical ventilation duration, which were mitigated by the intervention. Certain body composition variables (e.g., extracellular water to total body water ratio and phase angle) showed differences between high-risk and low-risk groups and may be related to patient outcomes. Non-invasive body composition assessment using BIA can help dietitians adjust diet formulas for critically ill septic patients. Body composition variables may be associated with sepsis outcomes, but further research with larger patient numbers is needed to confirm these findings. [ABSTRACT FROM AUTHOR]

BACKGROUND: The B-type natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (pBNP) are predictors of cardiovascular morbidity and mortality. Since the artificial intelligence (AI)-enabled electrocardiogram (ECG) system is widely used in the management of many cardiovascular diseases (CVDs), patients requiring intensive monitoring may benefit from an AI-ECG with BNP/pBNP predictions. This study aimed to develop an AI-ECG to predict BNP/pBNP and compare their values for future mortality. METHODS: The development, tuning, internal validation, and external validation sets included 47,709, 16,249, 4001, and 6042 ECGs, respectively. Deep learning models (DLMs) were trained using a development set for estimating ECG-based BNP/pBNP (ECG-BNP/ECG-pBNP), and the tuning set was used to guide the training process. The ECGs in internal and external validation sets belonging to nonrepeating patients were used to validate the DLMs. We also followed-up all-cause mortality to explore the prognostic value. RESULTS: The DLMs accurately distinguished mild (≥500 pg/mL) and severe (≥1000 pg/mL) an abnormal BNP/pBNP with AUCs of ≥0.85 in the internal and external validation sets, which provided sensitivities of 68.0–85.0% and specificities of 77.9–86.2%. In continuous predictions, the Pearson correlation coefficient between ECG-BNP and ECG-pBNP was 0.93, and they were both associated with similar ECG features, such as the T wave axis and correct QT interval. ECG-pBNP provided a higher all-cause mortality predictive value than ECG-BNP. CONCLUSIONS: The AI-ECG can accurately estimate BNP/pBNP and may be useful for monitoring the risk of CVDs. Moreover, ECG-pBNP may be a better indicator to manage the risk of future mortality. [ABSTRACT FROM AUTHOR]

Given rapid global urban development, increases to impervious surfaces, urban population growth, building construction, and energy consumption result in the urban heat island (UHI) phenomenon. However, the spatial extent of UHIs is not clearly mapped in many UHI studies based on a remote sensing approach. Therefore, we developed a method to extract the spatial extent of the UHI during the period from 2000 to 2021 in Nanjing, China, and explored the impact of urban two- and three-dimensional expansion on UHI spatial extent and UHI intensity. After cropland effects (i.e., bare soil) were eliminated, our proposed method combines the Getis-Ord-Gi* and the standard deviation of the normalized difference vegetation index (NDVI STD) to extract the UHI area from Landsat 5 and Landsat 8 images using land surface temperature (LST) spatial autocorrelation characteristics and the seasonal variation of vegetation. Our results show the following: (1) Bare farmland has a large influence on the extraction results of UHI—combined with the seasonal variation characteristics of NDVI STD, the impact of bare soil on UHI extraction was highly reduced, strongly improving the accuracy of UHI extraction. (2) The dynamics of the UHI area are consistent with the changes in the built-up area in Nanjing at both spatial and temporal scales, but with the increase of the urban green ratio, the UHI area of mature urban areas trends to decrease due to the cooling effect of green space. (3) The accumulation of population and GDP promote the vertical expansion of urban buildings. When the two-dimensional expansion of the city reaches saturation, the UHI intensity is primarily affected by three-dimensional urban expansion. [ABSTRACT FROM AUTHOR]

Ductility-based structural design is currently the mainstream method. In order to analyze the ductility performance of concrete columns with high-strength steel reinforcements under eccentric compression, corresponding experimental studies have been performed. Numerical models were established, and their reliability was verified. Based on the numerical models, the parameter analysis was carried out, where eccentricity, concrete strength, and reinforcement ratio were considered to systematically discuss the ductility of the concrete column section with high-strength steel reinforcement. The results show that the ductility of the section under eccentric compression increases with the strength of the concrete and eccentricity, and decreases with the reinforcement ratio. Finally, a simplified calculation formula capable of quantitatively evaluating the section ductility was proposed. [ABSTRACT FROM AUTHOR]

For plate structures, their random parameters can be regarded as a two-dimensional random field in the plane. To solve the plate theory considering a two-dimensional random field, an efficient strategy for the stochastic finite element method was adopted. Firstly, the stochastic finite element method was used to establish the plate structural model, in which the random field characteristics of the parameter were considered, and the mathematical expression of its random field was obtained through the Karhunen–Loève expansion; secondly, the point estimate method was applied to calculate the statistics of random structures. The computational efficiency can be significantly improved through the reference point selection strategy. The accuracy and efficiency of the calculation strategy were verified, and the influences of correlation length and coefficient of variation of the parameter on the random response of plate structures under different plate types (including Kirchhoff plate and Mindlin plate) and boundary conditions (including simply supported and clamped supported) were discussed. The proposed method can provide some help in solving static problems of plate structures. [ABSTRACT FROM AUTHOR]

In essence, cultural and creative design features humanity and culture. The process of how to transform culture into creativity is an essential subject of design education, which, in turn, calls for a new design teaching system. In regard to combining traditional Chinese thinking with modern design experience, the question of how to apply traditional Chinese thinking to design concepts, methods, and education is systematically explored in this research. Firstly, the question of how to transform the philosophy of "Tao, Vessel, Change and Comprehensiveness" in the Book of Changes into "design thinking" in order to establish the learning process of creative design with added value—as well as to set up the teaching model of cultural and creative design under "Tao, Vessel, Change and Comprehensiveness"—is discussed. After this, two cases of the Aboriginal Harvest Festival's cultural creativity "Dancing Together" candlestick and the animation, cultural, and creative design of the "Wind Lion God" are used in order to examine the effectiveness of the specific design and to verify the feasibility of this teaching model in the development and application of cultural and creative products. The results demonstrate the feasibility of this teaching model, which provides a new systematic approach for the purposes of teaching and practice in the field of cultural and creative design. [ABSTRACT FROM AUTHOR]

The Chinese stock market exhibits many characteristics that deviate from the efficient market hypothesis and the trading volume contains a great deal of complexity information that the price cannot reflect. Do small or big orders drive trading volume? We studied the complex behavior of different orders from a microstructure perspective. We used ETF data of the CSI300, SSE50, and CSI500 indices and divided transactions into big and small orders. A multifractal detrended fluctuation analysis (MFDFA) method was used to study persistence. It was found that the persistence of small orders was stronger than that of big orders, which was caused by correlation with time. A multiscale composite complexity synchronization (MCCS) method was used to study the synchronization of orders and total volume. It was found that small orders drove selling-out transactions in the CSI300 market and that big orders drove selling-out transactions in the CSI500 market. Our findings are useful for understanding the microstructure of the trading volume in the Chinese market. [ABSTRACT FROM AUTHOR]

Magnetic Barkhausen noise (MBN), sensitive to the microstructure of materials, can be applied in the surface decarburization depth detection of ferromagnetic specimens. However, the effects of core microstructures on the determination results of decarburization depth have not been explored. In this study, MBN was employed to evaluate the magnetic properties of the decarburized 60Si2Mn spring steels with martensitic and pearlitic core microstructures. Spring steel samples were austenitized at different times to generate different decarburization depths. Seven magnetic features were extracted from the MBN butterfly profiles. We used the variation coefficient, linear correlation coefficient, and normalized sensitivity to discuss the influence of the core microstructures on these seven features. The different core microstructures led to a large difference in the ability of MBN features to characterize the decarburization layer depth. However, three features of MBN butterfly profiles demonstrated an approximately linear dependency (linear correlation coefficient > 94%) on surface decarburization depth and monotonically increased with the increase in depth in both core microstructures of spring steels. [ABSTRACT FROM AUTHOR]

Klotho is an anti-aging gene. Studies have revealed its association with insulin resistance. Visceral fat is related to insulin resistance, and the sagittal abdominal diameter (SAD) can serve as a biomarker for visceral fat (VF). This study investigated the association between SAD and serum Klotho concentration (SKC). We enrolled 2301 participants from the 2011–2012 National Health and Nutrition Examination Survey (NHANES) dataset, and 49.2% of the enrolled individuals were male. Qualified participants were separated into four quartiles according to the SAD value. SKC values were obtained by ELISA. Demographic characteristics, body mass index (BMI), systolic blood pressure, and biochemistry parameters with significance were analyzed using multivariate linear regression models. The mean age of the study participants was 57.22 ± 10.53 years. The fully adjusted regression model showed a negative association between SAD and SKC (p < 0.05), with a β-coefficient of −12.02. We also analyzed subgroups of participants according to age and BMI. Participants with an age ≥65 and <65 years old were each negatively associated with SKC, and this association was significant for participants with a BMI ≥ 30 kg/m2 (p = 0.001, β-coefficient: −18.83). We also found a concentration-dependent relationship between SAD and SKC. In conclusion, VF and SKC are associated, and SAD can serve as a surrogate of VF and an indicator of SKC. [ABSTRACT FROM AUTHOR]

Aerosols, through cloud condensation nuclei (CCN) or ice nuclei (IN), affect cloud microphysics. With increasing concentrations of aerosols, it is important to consider the impact of IN along with CCN on clouds and precipitation in numerical simulations; further, aerosols may also affect the weather-modification seeding effect. On the basis of the observation of natural IN concentration and cloud-drop number concentrations, numerical sensitivity experiments for a snowfall case were designed to study the effects of parameters of IN and cloud number concentrations at the cloud base to consider the CCN effects on clouds and precipitation as well as weather-modification seeding effects. Generally, with smaller cloud-drop number concentration, the mass contents were much lower. With more ice nuclei, more ice crystals were able to nucleate, and additional snow particles were generated through ice crystals. Cloud-drop number concentrations heavily affected the location and amount of snowfall. During the 1e9 test, 2.4 mm was the highest reduction in the amount of snowfall; additionally, the amount of snowfall from the combined impacts of increased IN and cloud-drop number decreased in wide areas, and its maximum precipitation reduction exceeded 2.7 mm as well as up to 15% of the daily amount of snowfall. More IN reduced the artificial seeding effect, lowered the increase in snowfall in the center of the seeding, and lowered the reduction of snowfall in the reduction center of the seeding. With more IN, the seeding effect was able to shift approximately 0.6% from the 3.9% seeding effect of the control simulation. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) causes progressive lung fibrosis with subsequent fatality and has limited treatment options. NICEFIT is the first Taiwan-based prospective, observational, and non-interventional registry for IPF progression under routine clinical practice in Taiwan. Data on 101 patients (aged 74.6 ± 9.1 years and 83.2% men) with IPF were collected over 2 years (2018−2020) from medical centers in Taiwan at baseline, 1 month, and subsequent 3-month intervals. Treated patients (n = 88) received the antifibrotics nintedanib or pirfenidone, compared with the untreated group (n = 13). The 2-year assessment revealed overall preserved lung functionality in the treated patients, with insignificant changes from baseline for percent predicted forced vital capacity or FVC (±1.7%). The presence of respiratory comorbidities significantly increased the risk of both AE and death (with or without AE) over the full study duration. Furthermore, the decline of predicted FVC significantly increased with the risk of acute exacerbations (AE) in the second year. Overall, antifibrotic medication was beneficial in stalling IPF progression, reducing AEs, and delaying mortality in the treated cohort, despite their lower baseline lung functions. Further, no new safety concerns over antifibrotic treatments were observed for the Taiwanese population. [ABSTRACT FROM AUTHOR]

Both hypernatremia and an abnormal immune response may increase hospital mortality in patients with sepsis. This study examined the association of hypernatremia with abnormal immune response and mortality in 520 adult patients with sepsis in an intensive care unit (ICU). We compared the mortality and ex vivo lipopolysaccharide (LPS)-induced inflammatory response differences among patients with hyponatremia, eunatremia, and hypernatremia, as well as between patients with acquired hypernatremia on ICU day 3 and those with sustained eunatremia over first three ICU days. Compared with eunatremia or hyponatremia, hypernatremia led to higher 7 day, 14 day, 28 day, and hospital mortality rates (p = 0.030, 0.009, 0.010, and 0.033, respectively). Compared with sustained eunatremia, acquired hypernatremia led to higher 7, 14, and 28 day mortality rates (p = 0.019, 0.042, and 0.028, respectively). The acquired hypernatremia group nonsignificantly trended toward increased hospital mortality (p = 0.056). Day 1 granulocyte colony-stimulating factor (G-CSF) and tumor necrosis factor (TNF) α levels were relatively low in patients with hypernatremia (p = 0.020 and 0.010, respectively) but relatively high in patients with acquired hypernatremia (p = 0.049 and 0.009, respectively). Thus, in ICU-admitted septic patients, hypernatremia on admission and in ICU-acquired hypernatremia were both associated with higher mortality. The higher mortality in patients with hypernatremia on admission was possibly related to the downregulation of G-CSF and TNF-α secretion after endotoxin stimulation. Compared to sustained eunatremia, acquired hypernatremia showed immunoparalysis at first and then hyperinflammation on day 3. [ABSTRACT FROM AUTHOR]

Reactive oxygen species (ROS) are highly reactive oxidant molecules that can kill cancer cells through irreversible damage to biomacromolecules. ROS-mediated cancer therapies, such as chemodynamic (CDT) and photodynamic therapy (PDT), are often limited by the hypoxia tumor microenvironment (TME) with high glutathione (GSH) level. This paper reported the preparation, characterization, in vitro and in vivo antitumor bioactivity of a meso-tetra(4-carboxyphenyl)porphine (TCPP)-based therapeutic nanoplatform (CMMFTP) to overcome the limitations of TME. Using Cu2+ as the central ion and TCPP as the ligand, the 2D metal-organic framework Cu-TCPP was synthesized by the solvothermal method, then CMMFTP was prepared by modifying MnO2, folic acid (FA), triphenylphosphine (TPP), and poly (allylamine hydrochloride) (PAH) on the surface of Cu-TCPP MOFs. CMMFTP was designed as a self-oxygenating ROS nanoreactor based on the PDT process of TCPP MOFs and the CDT process by Cu(II) and MnO2 components (mainly through Fenton-like reaction). The in vitro assay suggested CMMFTP caused a 96% lethality rate against Hela cells (MTT analysis) in specific response to TME stimulation. Moreover, the Cu(II) and MnO2 in CMMFTP efficiently depleted the glutathione (80%) in tumor cells and consequently amplified ROS levels to improve CDT/PDT effects. The FA-induced tumor targeting and TPP-induced mitochondria targeting further enhanced the antitumor activity. Therefore, the nanoreactor based on dual targeting and self-oxygenation-enhanced ROS mechanism provided a new strategy for cancer therapy. [ABSTRACT FROM AUTHOR]

As a typical complex system, the stock market has attracted the attention of scholars and investors to comprehensively understand its fractal characteristics and analyze its market efficiency. Firstly, this paper proposes an asymmetric, detrended fluctuation analysis based on overlapping sliding windows (OSW-A-MFDFA). It reduces the generation of fluctuation errors, and the calculation results are more robust and reliable. The advantage of the OSW-A-MFDFA is that it not only can reveal the multifractal characteristics of time series clearly, but also can further accurately analyze the asymmetry of fractal characteristics under different trends. Secondly, this paper focuses on the variation in the width difference and height difference of the multifractal spectrum under different trends. Finally, based on multifractality, this paper proposes a comprehensive indicator MED that can be used to measure market efficiency, which is characterized by traversing all fluctuation orders. The application revealed many interesting findings in style stock indices. Style stock indices have asymmetric multifractal characteristics, and there are significant differences in the fractal spectrum of different style assets. Moreover, the market efficiency of style stock indices is time-varying, which can be reasonably explained from the perspective of the adaptive market hypothesis. [ABSTRACT FROM AUTHOR]

In this work, we report the fabrication and functional demonstration of a kind of dually responsive nanoparticles (NPs) as a potential drug delivery vector. The pH value, corresponding to the acidic microenvironment at the tumor site, and mannitol, to the extracellular trigger agent, were employed as the dually responsive factors. The function of dual responses was achieved by breaking the dynamic covalent bonds between phenylboronic acid (PBA) groups and diols at low pH value (pH 5.0) and/or under the administration of mannitol, which triggered the decomposition of the complex NPs and the concomitant release of anticancer drug of doxorubicin (DOX) loaded inside the NPs. The NPs were composed of modified chitosan (PQCS) with quaternary ammonium and PBA groups on the side chains, heparin (Hep), and poly(vinyl alcohol) (PVA), in which quaternary ammonium groups offer the positive charge for the cell-internalization of NPs, PBA groups serve for the formation of dynamic bonds in responding to pH change and mannitol addition, PVA furnishes the NPs with diol groups for the interaction with PBA groups and the formation of dynamic NPS, and Hep plays the roles of reducing the cytotoxicity of highly positively-charged chitosan and forming of complex NPs for DOX up-loading. A three-step fabrication process of drug-loaded NPs was described, and the characterization results were comprehensively demonstrated. The sustained drug release from the drug-loaded NPs displayed obvious pH and mannitol dependence. More specifically, the cumulative DOX release was increased more than 1.5-fold at pH 5.0 with 20 mg mL−1 mannitol. Furthermore, the nanoparticles were manifested with effective antitumor efficient and apparently enhanced cytotoxicity in response to the acidic pH value and/or mannitol. [ABSTRACT FROM AUTHOR]

Although early life stress (ELS) can increase susceptibility to adulthood psychiatric disorders and produce a greater inflammatory response in a stressful event, targeted preventive and therapeutic drugs still remain scarce. Ganoderma lucidum triterpenoids (GLTs) can exert anti-inflammatory effects in the periphery and central nervous systems. This study employed a combined model of "childhood maternal separation + adulthood sub-stress" to explore whether GLTs may alleviate anxiety- and depression-like behaviors in male and female mice by mitigating inflammation. Male and female pups were separated from their mothers for four hours per day from postnatal day 1 (PND 1) to PND 21; starting from PND 56, GLTs were administered intraperitoneally once daily for three weeks and followed by three days of sub-stress. Results showed that maternal separation increased the anxiety- and depression-like behaviors in both male and female mice, which disappeared after the preemptive GLTs treatment (40 mg/kg) before adulthood sub-stress. Maternal separation up-regulated the pro-inflammatory markers in the periphery and brain, and activated microglia in the prefrontal cortex and hippocampus. All the abnormalities were reversed by GLTs administration, with no adverse effects on immune organ indices, liver, and renal function. Our findings suggest that GLTs can be a promising candidate in treating ELS-induced psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: We aimed to determine whether septic patients with liver cirrhosis (LC) had worse survival than septic patients without liver cirrhosis (WLC). We also investigated the survival of septic patients with compensated liver cirrhosis (CLC) and decompensated liver cirrhosis (DLC). Methods: This study enrolled 776 consecutive adult patients with sepsis admitted to the medical intensive care units of a tertiary referral hospital. Clinical factors and laboratory data were collected for analysis. Propensity scoring was also used for the control of selection bias. The variables included in the propensity model were age, sex, presence of diabetes mellitus, hypertension, cardiovascular accident, chronic kidney disease, malignancy, APCHE II (Acute Physiology and Chronic Health Evaluation) score, hemoglobin, and platelet data on the day when sepsis was confirmed. Seven-day, ICU, and hospital mortality were analyzed after correcting for these confounding factors. Results: Of the 776 septic patients, 64 (8.2%) septic patients presented with LC. Patients were divided into two groups—LC (n = 64) and WLC (n = 712)—which presented different rates of hospital mortality (LC: 62.5% vs. WLC: 41.0%, p = 0.001). We further separated septic patients with LC into two groups: patients with CLC (n = 24) and those with DLC (n = 40). After propensity score matching, the survival of septic patients with CLC (63.6%) was not inferior to patients WLC (54.5%) (p = 0.411). Patients with DLC had more hospital mortality, even after matching (p < 0.05). The Quick SOFA (qSOFA) score, SOFA score, and sub-SOFA score were also comparable between groups. SOFA scores were not significantly different between the CLC and WLC groups after matching. Poor SOFA scores were observed in the DLC group on days 3 and 7 after matching (p < 0.05). Conclusions: Septic patients with LC had higher mortality compared to patients WLC before matching. However, after propensity score matching, the survival of septic patients with CLC was non-inferior to patients WLC. [ABSTRACT FROM AUTHOR]

BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference < 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF (>50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD. [ABSTRACT FROM AUTHOR]

Targeting threonyl-tRNA synthetase (ThrRS) of Brucella abortus is a promising approach to developing small-molecule drugs against bovine brucellosis. Using the BLASTp algorithm, we identified ThrRS from Escherichia coli (EThrRS, PDB ID 1QF6), which is 51% identical to ThrRS from Brucella abortus (BaThrRS) at the amino acid sequence level. EThrRS was used as the template to construct a BaThrRS homology model which was optimized using molecular dynamics simulations. To determine the residues important for substrate ATP binding, we identified the ATP-binding regions of BaThrRS, docked ATP to the protein, and identified the residues whose side chains surrounded bound ATP. We then used the binding site of ATP to virtually screen for BaThrRS inhibitors and got seven leads. We further characterized the BaThrRS-binding site of the compound with the highest predicted inhibitory activity. Our results should facilitate future experimental effects to find novel drugs for use against bovine brucellosis. [ABSTRACT FROM AUTHOR]

(1) Background: Posterior circulation ischemic stroke has high mortality and disability rates and requires an early prediction prognosis to provide the basis for an interventional approach. Current quantitative measures are only able to accurately assess the prognosis of patients using magnetic resonance imaging (MRI). However, it is difficult to obtain MRI images in critically urgent cases. Therefore, the development of a noncontrast CT-based rapid-assist tool is needed to enhance the value of the clinical application. (2) Objective: This study aimed to develop an auxiliary-annotating noncontrast CT-efficient tool, which is based on a deep learning model, to provide a quantitative scale and the prognosis of posterior circulation ischemic stroke patients. (3) Methods: A total of 31 patients with posterior circulation ischemic stroke, diagnosed in the stroke registry at the Tri-Service General Hospital from November 2019 to July 2020, were included in the study, with a total of 578 CT images collected from noncontrast CT and MRI that were ≤ 3 days apart. A 5-fold cross validation was used to develop an image segmentation model to identify nine posterior circulation structures, and intersection over union (IoU) was used to assess the ability of the model to identify each structure. A quantitative score was integrated to assess the importance of the proportion of ischemic lesions in each posterior circulation structure, and the ROC curve was compared with the semiquantitative score for prognostic power. The prognoses of the patients were defined into two groups of 18 patients. An mRS score of 0–2 at discharge was defined as a good prognosis, while an mRS score of 3–6 was deemed to be a poor prognosis. (4) Results: The performance of the image segmentation model for identifying the nine posterior circulation structures in noncontrast CT images was evaluated. The IoU of the left cerebellum was 0.78, the IoU of the right cerebellum was 0.79, the IoU of the left occipital lobe was 0.74, the IoU of the right occipital lobe was 0.68, the IoU of the left thalamus was 0.73, the IoU of the right thalamus was 0.75, the IoU of the medulla oblongata was 0.82, and the IoU of the midbrain was 0.83. The prognostic AUC of posterior circulation patients predicted using a quantitative integrated score was 0.74, which was significantly higher than that of the pc-ASPECTS (AUC = 0.63, p = 0.035), with a sensitivity of 0.67 and a specificity of 0.72. (5) Conclusions: In this study, a deep learning model was used to develop a noncontrast CT-based quantitative integrated score tool, which is an effective tool for clinicians to assess the prognosis of posterior circulation ischemic stroke. [ABSTRACT FROM AUTHOR]

Background: Left atrium enlargement (LAE) can be used as a predictor of future cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical electrocardiogram (ECG) changes have been reported in patients with LAE. This study developed a deep learning model (DLM)-enabled ECG system to identify patients with LAE. Method: Patients who had ECG records with corresponding echocardiography (ECHO) were included. There were 101,077 ECGs, 20,510 ECGs, 7611 ECGs, and 11,753 ECGs in the development, tuning, internal validation, and external validation sets, respectively. We evaluated the performance of a DLM-enabled ECG for diagnosing LAE and explored the prognostic value of ECG-LAE for new-onset HTN, new-onset stroke (STK), new-onset mitral regurgitation (MR), and new-onset Afib. Results: The DLM-enabled ECG achieved AUCs of 0.8127/0.8176 for diagnosing mild LAE, 0.8587/0.8688 for diagnosing moderate LAE, and 0.8899/0.8990 for diagnosing severe LAE in the internal/external validation sets. Notably, ECG-LAE had higher prognostic value compared to ECHO-LAE, which had C-indices of 0.711/0.714 compared to 0.695/0.692 for new-onset HTN, 0.676/0.688 compared to 0.663/0.677 for new-onset STK, 0.696/0.695 compared to 0.676/0.673 for new-onset MR, and 0.800/0.806 compared to 0.786/0.760 for new-onset Afib in internal/external validation sets, respectively. Conclusions: A DLM-enabled ECG could be considered as a LAE screening tool and provide better prognostic information for related cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Klotho protein is an anti-aging protein and plays multiple roles in ion-regulation, anti-oxidative stress, and energy metabolism through various pathways. Metabolic syndrome is a combination of multiple conditions that compose of multiple risk factors of cardiovascular disease and type 2 diabetes. Gene regulation and protein expression are discovered associated with metabolic syndrome. We aimed to figure out the correlation between Klotho protein and metabolic syndrome in generally healthy adults. A cross-sectional study of 9976 respondents ≥ 18 years old from the US National Health and Nutrition Examination Survey (2007–2012) by utilizing their soluble Klotho protein concentrations. Multivariate linear regression models were used to analyze the effect of soluble Klotho protein on the prevalence of metabolic syndrome. Soluble Klotho protein concentration was inversely correlated with the presence of metabolic syndromes (p = 0.013) and numbers of components that met the definition of metabolic syndrome (p < 0.05). The concentration of Soluble Klotho protein was negatively associated with abdominal obesity and high triglyceride (TG) in the adjusted model (p < 0.05). Soluble Klotho protein is correlated with changing metabolic syndrome components in adults, especially central obesity and high TG levels. Despite conventional function as co-factor with fibroblast growth factor-23 (FGF23) that regulates phosphate and vitamin D homeostasis, FGF23-independent soluble Klotho protein may act on multiple signal pathways in different organs and tissue in roles of anti-aging and protection from metabolic syndrome. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunotherapy is approved in selected cases of gastric cancer, and durable responses have been observed in exceptional responders. Several potential predictive biomarkers have been identified in gastric cancer, such as microsatellite instability-high (MSI-H), Epstein–Barr virus (EBV), and programmed death ligand 1 (PD-L1). We explored the real-world evidence of these biomarkers and their outcomes. When only combined positive score (CPS) ≥ 1 was used as the biomarker, the overall response rate (ORR) and progression-free survival (PFS) were not statistically significant. CPS ≥ 1 was commonly combined with MSI-H (75%) and Epstein–Barr encoding region (EBER) (80%). MSI-H and CPS ≥ 5 were prognostic biomarkers associated with better ORR and PFS. In patients with EBER, better ORR and PFS were observed only in patients with CPS ≥ 1. These results could transform clinical practice and can be used to formulate more precise treatment suggestions for patients with gastric cancer. Immunotherapy benefits selected cases of gastric cancer (GC), but the correlation between biomarkers and prognosis is still unclear. Fifty-two patients with GC who underwent immunotherapy were enrolled from June 2016 to December 2020. Their clinical features and biomarkers—microsatellite instability-high (MSI-H), programmed cell death ligand 1 (PD-L1) combined positive score (CPS), and Epstein–Barr encoding region (EBER)—were analyzed. Eight patients had MSI-H, five patients had EBER, 29 patients had CPS ≥ 1, and 20 patients had no biomarker. The overall response rates (ORRs) of the MSI-H, EBER, PD-L1 CPS ≥ 1, and all-negative group were 75%, 60%, 44.8%, and 15%, respectively. Compared with that of the all-negative group, progression-free survival (PFS) was better in the MSI-H (p = 0.018), CPS ≥ 5 (p = 0.012), and CPS ≥ 10 (p = 0.006) groups, but not in the EBER (p = 0.2) and CPS ≥ 1 groups (p = 0.35). Ten patients had combined biomarkers, CPS ≥ 1 with either MSI-H or EBER. The ORRs were 66.7% for CPS ≥ 1 and MSI-H and 75% for CPS ≥ 1 and EBER. PFS was better in patients with combined biomarkers (p = 0.01). MSI-H, EBER, and CPS are useful biomarkers for predicting the efficacy of immunotherapy. [ABSTRACT FROM AUTHOR]

Nutritional status could affect clinical outcomes in critical patients. We aimed to determine the prognostic accuracy of the modified Nutrition Risk in Critically Ill (mNUTRIC) score for hospital mortality and treatment outcomes in patients with severe community-acquired pneumonia (SCAP) compared to other clinical prediction rules. We enrolled SCAP patients in a multi-center setting retrospectively. The mNUTRIC score and clinical prediction rules for pneumonia, as well as clinical factors, were calculated and recorded. Clinical outcomes, including mortality status and treatment outcome, were assessed after the patient was discharged. We used the receiver operating characteristic (ROC) curve method and multivariate logistic regression analysis to determine the prognostic accuracy of the mNUTRIC score for predicting clinical outcomes compared to clinical prediction rules, while 815 SCAP patients were enrolled. ROC curve analysis showed that the mNUTRIC score was the most effective at predicting each clinical outcome and had the highest area under the ROC curve value. The cut-off value for predicting clinical outcomes was 5.5. By multivariate logistic regression analysis, the mNUTRIC score was also an independent predictor of both clinical outcomes in SCAP patients. We concluded that the mNUTRIC score is a better prognostic factor for predicting clinical outcomes in SCAP patients compared to other clinical prediction rules. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) is one of the leading causes of cancer deaths in women worldwide. Ubiquitin-conjugating enzyme 9 (Ubc9), the sole conjugating enzyme for sumoylation, regulates protein function and plays an important role in sumoylation-mediated cellular pathways. Although sumoylation plays a key role in DNA repair and tumorgenesis, whether Ubc9 is involved in EOC progression remains unknown. In the present study, we constructed Ubc-9 expressed recombined plasmid pEGFP-N1-Ubc9. The mRNA levels of Ubc9 were confirmed in human ovarian cell lines before and after transfection with pEGFP-N1-Ubc9 or small interfering RNA (siRNA) targeted Ubc9 by real-time polymerase chain reaction (PCR). The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was used to observe the effect of Ubc9 on cell proliferation. The protein levels of Ubc9, and proliferation-related signals Akt and physphorylated Akt were determined by Western blot. Our results showed that proliferation of EOC cells increased significantly in Ubc9 overexpressing cells, but decreased in Ubc9 knockdown cells. The physphorylation of Akt showed similar trends. In addition, the inhibitor of PI3K/Akt signaling pathway, LY294002, dramatically inhibited the growth of Ubc9 overexpressing cells. Therefore, Ubc9 gene plays an important role in cell proliferation in EOC through PI3K/Akt signaling pathway. [ABSTRACT FROM AUTHOR]

A stripped no-core optical fiber with a 125 μm diameter was transformed into a symmetric and unbroken optical fiber that tapers slightly to a 45-μm-diameter waist. The laser light can be easily launched into the no-core optical fiber. The enhanced evanescent wave of the slightly tapered no-core optical fiber can attract nearby 5-μm-diameter polystyrene microparticles onto the surface of the tapered multimode optical fiber within fast flowing fluid and propel the trapped particles in the direction of the light propagation to longer delivery range than is possible using a slightly tapered telecom single-mode optical fiber. [ABSTRACT FROM AUTHOR]

Tumor-associated macrophages (TAMs) are correlated with poor prognosis in many human cancers; however, the mechanism by which TAMs facilitate ovarian cancer cell migration and invasion remains unknown. This study was aimed to examine the function of adrenomedullin (ADM) in macrophage polarization and their further effects on the migration of ovarian cancer cells. Exogenous ADM antagonist and small interfering RNA (siRNA) specific for ADM expression were treated to macrophages and EOC cell line HO8910, respectively. Then macrophages were cocultured with HO8910 cells without direct contact. Flow cytometry, Western blot and real-time PCR were used to detect macrophage phenotype and cytokine production. The migration ability and cytoskeleton rearrangement of ovarian cancer cells were determined by Transwell migration assay and phalloidin staining. Western blot was performed to evaluate the activity status of signaling molecules in the process of ovarian cancer cell migration. The results showed that ADM induced macrophage phenotype and cytokine production similar to TAMs. Macrophages polarized by ADM promoted the migration and cytoskeleton rearrangement of HO8910 cells. The expression of RhoA and its downstream effector, cofilin, were upregulated in macrophage-induced migration of HO8910 cells. In conclusion, ADM could polarize macrophages similar to TAMs, and then polarized macrophages promote the migration of ovarian cancer cells via activation of RhoA signaling pathway in vitro. [ABSTRACT FROM AUTHOR]

Simple Summary: Stomach cancer is a common malignancy and one of the leading causes of cancer death in Taiwan. Although tumor characteristics are the main determinants of oncological outcomes, modulation of the immune system may also play some role in cancer progression. Despite the hypothesis that perioperative blood transfusion may suppress the immune reactivity and promote tumor recurrence, the role of perioperative transfusion in the prognosis of stomach cancer remains controversial. To fill this gap, we designed this retrospective study using sound analytical approaches to investigate the impact of perioperative transfusion on oncologic outcomes after curative resection for stomach cancer. We demonstrated that perioperative transfusion was associated with inferior disease-free and overall survival after stomach cancer surgery and a dose-response relationship was also noted between the amount of transfusion and risk of cancer recurrence or mortality. Background: Whether perioperative packed red blood cell (pRBC) transfusion is associated with inferior long-term outcomes after stomach cancer surgery remains controversial. Methods: This research used a retrospective cohort study. Patients with stage I~III stomach cancer undergoing tumor resection were collected at a tertiary medical center. Patient characteristics, surgical features and pathologic findings were gathered from an electronic medical chart review. The associations of perioperative pRBC transfusion with postoperative disease-free and overall survivals were evaluated using Cox regression analysis with an inverse probability of treatment weighting (IPTW). Restricted cubic spline functions were employed to characterize dose-response relationships between the amount of transfusion and cancer outcomes after surgery. Results: Among the 569 patients, 160 (28.1%) received perioperative pRBC transfusion. Perioperative transfusion was associated with worse disease-free survival (IPTW adjusted HR: 1.42, 95% CI: 1.18–1.71, p < 0.001) and overall survival (IPTW adjusted HR: 1.27, 95% CI: 1.05–1.55, p = 0.014). A non-linear dose-response relationship was noted between the amount of transfusions and worse disease-free or overall survival. Conclusions: Perioperative pRBC transfusion was associated with worse disease-free and overall survival after stomach cancer surgery, and strategies aiming to minimize perioperative transfusion exposure should be further considered to reduce the potential risk. [ABSTRACT FROM AUTHOR]

Body mass index (BMI) influences the prognosis of patients with non-small cell lung cancer (NSCLC), including both early-stage and late-stage NSCLC patients that are undergoing chemotherapies. However, earlier research on the relationship between BMI and survival in patients taking epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) yielded contradictory results. These publications either had a limited number of patients or were getting TKIs in various lines of therapy, which might explain why the outcomes were contradictory. As a result, we undertook retrospective study to examine the effect of BMI on survival outcomes in patients with advanced EGFR mutant NSCLC receiving first-line EGFR-TKIs. We also compared the findings to those with wild-type EGFR. Between November 2010 and March 2014, 513 patients with advanced NSCLC were enrolled in the study. According to the adjusted BMI cut-off point for Asia, 35 out of 513 (6.8%) patients were underweight (BMI < 18.5 kg/m2), whereas 197 (38.4%) were overweight (BMI > 24 kg/m2). Overweight patients with wild-type EGFR exhibited longer progression-free survival (4.6 vs. 2.1 months, p = 0.003) and overall survival (OS) (8.9 vs. 4.3 months, p = 0.003) than underweight patients. Overweight patients with EGFR mutations had a longer OS than normal-weight patients (23.0 vs. 20.2 months, p = 0.025). Bodyweight reduction was related to a shorter OS in both the mutant EGFR patients (17.1 vs. 30.5 months, p < 0.001) and the wild-type EGFR patients (7.8 vs. 18.7 months, p < 0.001). In conclusion, advanced stages NSCLC patients with a lower BMI and early weight loss had a worse outcome that was independent of EGFR mutation status. [ABSTRACT FROM AUTHOR]

Medical records scoring is important in a health care system. Artificial intelligence (AI) with projection word embeddings has been validated in its performance disease coding tasks, which maintain the vocabulary diversity of open internet databases and the medical terminology understanding of electronic health records (EHRs). We considered that an AI-enhanced system might be also applied to automatically score medical records. This study aimed to develop a series of deep learning models (DLMs) and validated their performance in medical records scoring task. We also analyzed the practical value of the best model. We used the admission medical records from the Tri-Services General Hospital during January 2016 to May 2020, which were scored by our visiting staffs with different levels from different departments. The medical records were scored ranged 0 to 10. All samples were divided into a training set (n = 74,959) and testing set (n = 152,730) based on time, which were used to train and validate the DLMs, respectively. The mean absolute error (MAE) was used to evaluate each DLM performance. In original AI medical record scoring, the predicted score by BERT architecture is closer to the actual reviewer score than the projection word embedding and LSTM architecture. The original MAE is 0.84 ± 0.27 using the BERT model, and the MAE is 1.00 ± 0.32 using the LSTM model. Linear mixed model can be used to improve the model performance, and the adjusted predicted score was closer compared to the original score. However, the project word embedding with the LSTM model (0.66 ± 0.39) provided better performance compared to BERT (0.70 ± 0.33) after linear mixed model enhancement (p < 0.001). In addition to comparing different architectures to score the medical records, this study further uses a mixed linear model to successfully adjust the AI medical record score to make it closer to the actual physician's score. [ABSTRACT FROM AUTHOR]

Crustins are cysteine-rich cationic antimicrobial peptides with diverse biological functions including antimicrobial and proteinase inhibitory activities in crustaceans. Although a few crustins reportedly respond to white spot syndrome virus (WSSV) infection, the detailed antiviral mechanisms of crustins remain largely unknown. Our previous research has shown that SpCrus2, from mud crab Scylla paramamosain, is a type II crustin containing a glycine-rich region (GRR) and a cysteine-rich region (CRR). In the present study, we found that SpCrus2 was upregulated in gills after WSSV challenge. Knockdown of SpCrus2 by injecting double-stranded RNA (dsSpCrus2) resulted in remarkably increased virus copies in mud crabs after infection with WSSV. These results suggested that SpCrus2 played a critical role in the antiviral immunity of mud crab. A GST pull-down assay showed that recombinant SpCrus2 interacted specifically with WSSV structural protein VP26, and this result was further confirmed by a co-immunoprecipitation assay with Drosophila S2 cells. As the signature sequence of type II crustin, SpCrus2 GRR is a glycine-rich cationic polypeptide with amphipathic properties. Our study demonstrated that the GRR and CRR of SpCrus2 exhibited binding activities to VP26, with the former displaying more potent binding ability than the latter. Interestingly, pre-incubating WSSV particles with recombinant SpCrus2 (rSpCrus2), rGRR, or rCRR inhibited virus proliferation in vivo; moreover, rSpCrus2 and rGRR possessed similar antiviral abilities, which were much stronger than those of rCRR. These findings indicated that SpCrus2 GRR contributed largely to the antiviral ability of SpCrus2, and that the stronger antiviral ability of GRR might result from its stronger binding activity to the viral structural protein. Overall, this study provided new insights into the antiviral mechanism of SpCrus2 and the development of new antiviral drugs. [ABSTRACT FROM AUTHOR]

The effects of diabetes and glucose on the outcomes of patients with sepsis are somewhat conflicting. This retrospective study enrolled 1214 consecutive patients with sepsis, including a subpopulation of 148 patients with immune profiles. The septic patients were stratified according to their Diabetes mellitus (DM) status or peak glucose level (three-group tool; P1: ≤140 mg/dL, P2: 141–220 mg/dL, P3: >220 mg/dL) on day 1. Although the DM group had a lower hazard ratio (HR) for 90-day mortality compared to non-DM patients, the adjusted HRs were insignificant. The modified sequential organ failure assessment-glucose (mSOFA-g) score can predict 90-day survival in patients with and without diabetes (β = 1.098, p < 0.001; β = 1.202, p < 0.001). The goodness of fit of the mSOFA-g score was 5% higher than the SOFA score of the subgroup without diabetes. The SOFA score and human leukocyte antigen-D-related (HLA-DR) expression were comparable between the groups. The P3 group had lower HLA-DR expression on days 1 and 3 and a higher 90-day mortality. The three-group tool was useful for predicting 90-day mortality in patients with separate Kaplan-Meier survival curves and mortality HRs in the construction and validation cohorts. The peak glucose level, instead of diabetes status, can be used as an easy adjunctive tool for mortality risk stratification in critically ill septic patients. [ABSTRACT FROM AUTHOR]

We investigated the best timing for using the National Early Warning Score 2 (NEWS2) for predicting sepsis outcomes and whether combining the NEWS2 and the Sequential Organ Failure Assessment (SOFA) was applicable for mortality risk stratification in intensive care unit (ICU) patients with severe sepsis. All adult patients who met the Third International Consensus Definitions for Sepsis and Septic Shock criteria between August 2013 and January 2017 with complete clinical parameters and laboratory data were enrolled as a derivation cohort. The primary outcomes were the 7-, 14-, 21-, and 28-day mortalities. Furthermore, another group of patients under the same setting between January 2020 and March 2020 were also enrolled as a validation cohort. In the derivation cohort, we included 699 consecutive adult patients. The 72 h NEWS2 had good discrimination for predicting 7-, 14-, 21-, and 28-day mortalities (AUC: 0.780, 0.724, 0.700, and 0.667, respectively) and was not inferior to the SOFA (AUC: 0.740, 0.680, 0.684, and 0.677, respectively). With the new combined NESO tool, the hazard ratio was 1.854 (1.203–2.950) for the intermediate-risk group and 6.810 (3.927–11.811) for the high-risk group relative to the low-risk group. This finding was confirmed in the validation cohort using a separated survival curve for 28-day mortality. The 72 h NEWS2 alone was non-inferior to the admission SOFA or day 3 SOFA for predicting sepsis outcomes. The NESO tool was found to be useful for 7-, 14-, 21-, and 28-day mortality risk stratification in patients with severe sepsis. [ABSTRACT FROM AUTHOR]

The financial market is a complex system, which has become more complicated due to the sudden impact of the COVID-19 pandemic in 2020. As a result there may be much higher degree of uncertainty and volatility clustering in stock markets. How does this "black swan" event affect the fractal behaviors of the stock market? How to improve the forecasting accuracy after that? Here we study the multifractal behaviors of 5-min time series of CSI300 and S&P500, which represents the two stock markets of China and United States. Using the Overlapped Sliding Window-based Multifractal Detrended Fluctuation Analysis (OSW-MF-DFA) method, we found that the two markets always have multifractal characteristics, and the degree of fractal intensified during the first panic period of pandemic. Based on the long and short-term memory which are described by fractal test results, we use the Gated Recurrent Unit (GRU) neural network model to forecast these indices. We found that during the large volatility clustering period, the prediction accuracy of the time series can be significantly improved by adding the time-varying Hurst index to the GRU neural network. [ABSTRACT FROM AUTHOR]

(1) Background: Recent studies have reported that the glucose variability (GV), irrespective of glycosylated hemoglobin (HbA1c), could be an additional risk factor for the development of diabetic retinopathy (DR). However, measurements for GV, such as continuous glucose monitoring (CGM) and fasting plasma glucose (FPG) variability, are expensive and time consuming. (2) Methods: This present study aims to explore the correlation between the glycemic gap as a measurement of GV, and DR. In total, 2565 patients were included in this study. We evaluated the effect of the different types of glycemic gaps on DR progression. (3) Results: We found that the area under the curve (AUC) values of both the glycemic gap and negative glycemic gap showed an association with DR progression. (4) Conclusions: On eliminating the possible influences of chronic blood glucose controls, the results show that GV has deleterious effects that are associated with the progression of DR. The glycemic gap is a simple measurement of GV, and the predictive value of the negative glycemic gap in DR progression shows that GV and treatment-related hypoglycemia may cause the development of DR. Individual treatment goals with a reasonable HbA1c and minimal glucose fluctuations may help in preventing DR. [ABSTRACT FROM AUTHOR]

Background: glycated hemoglobin (HbA1c) provides information on diabetes mellitus (DM) management. Electrocardiography (ECG) is a noninvasive test of cardiac activity that has been determined to be related to DM and its complications. This study developed a deep learning model (DLM) to estimate HbA1c via ECG. Methods: there were 104,823 ECGs with corresponding HbA1c or fasting glucose which were utilized to train a DLM for calculating ECG-HbA1c. Next, 1539 cases from outpatient departments and health examination centers provided 2190 ECGs for initial validation, and another 3293 cases with their first ECGs were employed to analyze its contributions to DM management. The primary analysis was used to distinguish patients with and without mild to severe DM, and the secondary analysis was to explore the predictive value of ECG-HbA1c for future complications, which included all-cause mortality, new-onset chronic kidney disease (CKD), and new-onset heart failure (HF). Results: we used a gender/age-matching strategy to train a DLM to achieve the best AUCs of 0.8255 with a sensitivity of 71.9% and specificity of 77.7% in a follow-up cohort with correlation of 0.496 and mean absolute errors of 1.230. The stratified analysis shows that DM presented in patients with fewer comorbidities was significantly more likely to be detected by ECG-HbA1c. Patients with higher ECG-HbA1c under the same Lab-HbA1c exhibited worse physical conditions. Of interest, ECG-HbA1c may contribute to the mortality (gender/age adjusted hazard ratio (HR): 1.53, 95% conference interval (CI): 1.08–2.17), new-onset CKD (HR: 1.56, 95% CI: 1.30–1.87), and new-onset HF (HR: 1.51, 95% CI: 1.13–2.01) independently of Lab-HbA1c. An additional impact of ECG-HbA1c on the risk of all-cause mortality (C-index: 0.831 to 0.835, p < 0.05), new-onset CKD (C-index: 0.735 to 0.745, p < 0.01), and new-onset HF (C-index: 0.793 to 0.796, p < 0.05) were observed in full adjustment models. Conclusion: the ECG-HbA1c could be considered as a novel biomarker for screening DM and predicting the progression of DM and its complications. [ABSTRACT FROM AUTHOR]

Objective: Polycyclic aromatic hydrocarbons (PAHs) are not only natural but also anthropogenic contaminants that exist in many places in the environment. Human beings often accidentally ingest PAHs via smoking. Furthermore, smoking may increase the risk of bowel disorder, including diarrhea and other gastrointestinal problems. Therefore, PAH exposure is hypothesized to be related to diarrhea risk. This study discusses the association between diarrhea and PAH exposure in the United States adult population. Method: 10,537 participants from the National Health and Nutrition Examination Survey (NHANES 2001–2006) were involved in this cross-sectional analysis. Bowel disorders were assessed via examination of stool frequency and stool type. The concentrations of urinary PAH metabolites were used to evaluate PAH exposure. The association between bowel habits and PAH exposure was assessed using a multivariate logistic regression model with covariate assessment of gender, age, race, liver function, kidney function, and common chronic health diseases. Results: All PAH metabolites except 1-hydroxynaphthalene, 1-hydroxypyrene, and 9-hydroxyfluorene were substantially correlated with an increased risk of diarrhea (p < 0.05) after modification of relevant covariables. This study also revealed significant association in the group of females (p < 0.05). Furthermore, all PAH metabolites except 1-hydroxynaphthalene, 2-hydroxyphenanthrene, 1-hydroxypyrene, and 9-hydroxyfluorene show significantly positive association in the non-obesity group (BMI < 30, p < 0.05). Conclusions: PAH exposure is highly associated with risk of bowel disorders among the adult population in the United States, especially in female and non-obesity populations. More research is necessary to shed light on the pathophysiological mechanisms associated to PAH exposure and diarrhea. [ABSTRACT FROM AUTHOR]

Nutritional status affects the survival of patients with sepsis. This retrospective study analyzed the impact of body mass index (BMI) and modified nutrition risk in critically ill (mNUTRIC) scores on survival of these patients. Data of 1291 patients with sepsis admitted to the intensive care unit (ICU) were extracted. The outcomes were mortality, duration of stay, ICU stay, and survival curve for 90-day mortality. Logistic regression analysis was performed to examine the risk factors for mortality. Cytokine and biomarker levels were analyzed in 165 patients. The 90-day survival of underweight patients with low mNUTRIC scores was significantly better than that of normal-weight patients with low mNUTRIC scores (70.8% vs. 58.3%, respectively; p = 0.048). Regression model analysis revealed that underweight patients with low mNUTRIC scores had a lower risk of mortality (odds ratio = 0.557; p = 0.082). Moreover, normal-weight patients with low mNUTRIC scores had the lowest human leukocyte antigen DR (HLA-DR) level on days 1 (underweight vs. normal weight vs. overweight: 94.3 vs. 82.1 vs. 94.3, respectively; p = 0.007) and 3 (91.8 vs. 91.0 vs. 93.2, respectively; p = 0.047). Thus, being underweight may not always be harmful if patients have optimal clinical nutritional status. Additionally, HLA-DR levels were the lowest in patients with low survival. [ABSTRACT FROM AUTHOR]

Acute kidney injury (AKI) requiring renal replacement therapy (RRT) increases the mortality of acute respiratory distress syndrome (ARDS) patients. The aim of this study was to investigate the outcomes and predictors of RRT in patients with influenza pneumonia-related ARDS. This retrospective cohort study includes patients from eight tertiary referral centers in Taiwan between January and March 2016, and all 282 patients with influenza pneumonia-related ARDS were enrolled. Thirty-four patients suffered from AKI requiring RRT, while 16 patients had underlying end stage renal disease (ESRD). The 30- and 60-day mortality rates were significantly higher in patients with AKI requiring RRT compared with those not requiring RRT (50.0% vs. 19.8%, p value < 0.001; 58.8% vs. 27.2%, p value = 0.001, respectively), but the patients with ESRD had no significant difference in mortality (12.5% vs. 19.8%, p value = 0.744; 31.3% vs. 27.2%, p value = 0.773, respectively). The predictors for AKI requiring RRT included underlying chronic liver disease and C-reactive protein. The mortality predictors for patients with AKI requiring RRT included the pneumonia severity index, tidal volume, and continuous renal replacement therapy. In this study, patients with influenza pneumonia-related ARDS with AKI requiring RRT had significantly higher mortality compared with other patients. [ABSTRACT FROM AUTHOR]

The Kuroshio Current has its origin in the northwestern Pacific, flowing northward to the east of Taiwan and the northern part of Luzon Island. As the Kuroshio Current flows northward, it quasi-periodically intrudes (hereafter referred to as Kuroshio intrusion (KI)) into the northern South China Sea (SCS) basin through the Luzon Strait. Despite the complex generation mechanisms of KI, the purpose of this study is to improve our understanding of the effects of KI through the Luzon Strait on the regional atmospheric and weather variations. Long-term multiple satellite observations, including absolute dynamic topography, absolute geostrophic currents, sea surface winds by ASCAT, multi-scale ultra-high resolution sea surface temperature (MURSST) level-four analysis, and research-quality three-hourly TRMM multi-satellite precipitation analysis (TMPA), was used to systematically examine the aforementioned scientific problem. Analysis indicates that the KI is interlinked with the consequential anomalous precipitation off southwestern Taiwan. This anomalous precipitation would lead to ~560 million tons of freshwater influx during each KI event. Subsequently, independent moisture budget analysis suggests that moisture, mainly from vertical advection, is the possible source of the precipitation anomaly. Additionally, a bulk formula analysis was applied to understand how KI can trigger the precipitation anomaly through vertical advection of moisture without causing an evident change in the low-level flows. These new research findings might reconcile the divisiveness on why winds are not showing a synchronous response during the KI and consequential anomalous precipitation events. [ABSTRACT FROM AUTHOR]

(1) Background: The prevalence of knee osteoarthritis (OA) in women is significantly higher than in men. The estrogen receptor α (ERα) has been considered to play a key role due to a large gender difference in its expression. ERα is encoded by the gene estrogen receptor 1 (ESR1), which is widely studied to explore the gender difference in knee OA. Several polymorphisms in ESR1 [PvuII (rs2234693) and BtgI (rs2228480)] were confirmed as the risk factors of OA. However, the evidence of the last widely investigated polymorphism, ESR1 Xbal (rs9340799), is still insufficient for concluding its effect on knee OA. (2) Objective: This study proposed a case–control study to investigate the association between ESR1 Xbal and knee OA. Moreover, a meta-analysis and trial sequential analysis (TSA) were conducted to enlarge the sample size for obtaining a conclusive evidence. (3) Methods: In total, 497 knee OA cases and 473 healthy controls were recruited between March 2015 and July 2018. The Kellgren–Lawrence grading system was used to identify the knee OA cases. To improve the evidence level of our study, we conducted a meta-analysis including the related studies published up until December 2018 from PubMed, Embase, and previous meta-analysis. The results are expressed as odds ratios (ORs) with corresponding 95% confidence intervals (CI) for evaluating the effect of this polymorphism on knee OA risk. TSA was used to estimate the sample sizes required in this issue. (4) Results: We found non-significant association between the G allele and knee OA [Crude-OR: 0.97 (95% CI: 0.78–1.20) and adjusted-OR: 0.90 (95% CI: 0.71–1.15) in allele model] in the present case–control study, and the analysis of other genetic models showed a similar trend. After including six published studies and our case–control studies, the current evidence with 3174 Asians showed the conclusively null association between ESR1 XbaI and knee OA [OR: 0.78 (95% CI: 0.59–1.04)] with a high heterogeneity (I2: 78%). The result of Caucasians also concluded the null association [OR: 1.05 (95% CI: 0.56–1.95), I2: 87%]. (5) Conclusions: The association between ESR1 XbaI and knee OA was not similar with other polymorphisms in ESR1, which is not a causal relationship. This study integrated all current evidence to elaborate this conclusion for suggesting no necessity of future studies. [ABSTRACT FROM AUTHOR]

(1) Background: It has rarely been studied whether the severity of diabetic retinopathy (DR) could influence renal disease progression in end-stage renal disease (ESRD) and chronic kidney disease (CKD) in patients with type 2 diabetes. The aim of this study was to evaluate renal disease progression in ESRD and CKD according to DR severity in patients with type 2 diabetes. (2) Methods: We included 1329 patients and divided the cohort into two end-points. The first was to trace the incidence of ESRD in all enrolled participants and the other was to follow their progression to CKD. (3) Results: Significantly higher crude hazard ratios (HRs) of ESRD incidence in all enrolled participants were noted, and this ratio increased in a stepwise fashion. However, after adjustment, DR severity was not associated with ESRD events. Therefore, a subgroup of 841 patients without CKD was enrolled to track their progression to CKD. Compared with no diabetic retinopathy, the progression of CKD increased in a stepwise fashion, from mild nonproliferative diabetic retinopathy (NPDR) to moderate NPDR, to severe NPDR and to proliferative diabetic retinopathy (PDR), both in the crude and adjusted models. (4) Conclusions: The severity of retinopathy appeared to be associated with renal lesions and the development of CKD. Our findings suggest that the severity of DR is a risk factor for progression to CKD. Therefore, diabetic retinopathy is useful for prognosticating the clinical course of diabetic kidney disease. [ABSTRACT FROM AUTHOR]

Simple Summary: Mitochondrial stress responses play a key role in cancer progression. Tid1, a mitochondrial co-chaperone, has been investigated and may act as a tumor suppressor in several cancers. However, the role of Tid1 in gastric cancers has not been clearly identified. Herein, we uncovered the clinical effects of Tid1 expression in gastric cancer patients. Moreover, we dissected the possible regulatory mechanism of Tid1 for cancer progression in gastric cancer cells. Our results demonstrated that Tid1 might regulate cell migration and invasion of gastric cancers. Tid1 may also be a key player for mitochondrial DNA maintenance in gastric cancer cells. We also found that the Tid1-galectin-7-MMP-9 axis might be one of the malignant regulatory mechanisms for gastric cancer metastasis and provide a potential target for gastric cancer treatment. Background: Gastric cancer is a common health issue. Deregulated cellular energetics is regarded as a cancer hallmark and mitochondrial dysfunction might contribute to cancer progression. Tid1, a mitochondrial co-chaperone, may play a role as a tumor suppressor in various cancers, but the role of Tid1 in gastric cancers remains under investigated. Methods: The clinical TCGA online database and immunohistochemical staining for Tid1 expression in tumor samples of gastric cancer patients were analyzed. Tid1 knockdown by siRNA was applied to investigate the role of Tid1 in gastric cancer cells. Results: Low Tid1 protein-expressing gastric cancer patients had a poorer prognosis and higher lymph node invasion than high Tid1-expressing patients. Knockdown of Tid1 did not increase cell proliferation, colony/tumor sphere formation, or chemotherapy resistance in gastric cancer cells. However, Tid1 knockdown increased cell migration and invasion. Moreover, Tid1 knockdown reduced the mtDNA copy number of gastric cancer cells. In addition, the Tid1-galectin-7-MMP-9 axis might be associated with Tid1 knockdown–induced cell migration and invasion of gastric cancer cells. Conclusions: Tid1 is required for mtDNA maintenance and regulates migration and invasion of gastric cancer cells. Tid1 deletion may be a poor prognostic factor in gastric cancers and could be further investigated for development of gastric cancer treatments. [ABSTRACT FROM AUTHOR]