Identification of protein complexes by integrating multiple alignment of protein interaction networks.

MOTIVATION: Protein complexes are one of the keys to studying the behavior of a cell system. Many biological functions are carried out by protein complexes. During the past decade, the main strategy used to identify protein complexes from high-throughput network data has been to extract near-cliques or highly dense subgraphs from a single protein-protein interaction (PPI) network. Although experimental PPI data have increased significantly over recent years, most PPI networks still have many false positive interactions and false negative edge loss due to the limitations of high-throughput experiments. In particular, the false negative errors restrict the search space of such conventional protein complex identification approaches. Thus, it has become one of the most challenging tasks in systems biology to automatically identify protein complexes. RESULTS: In this study, we propose a new algorithm, NEOComplex ( NE CC- and O rtholog-based Complex identification by multiple network alignment), which integrates functional orthology information that can be obtained from different types of multiple network alignment (MNA) approaches to expand the search space of protein complex detection. As part of our approach, we also define a new edge clustering coefficient (NECC) to assign weights to interaction edges in PPI networks so that protein complexes can be identified more accurately. The NECC is based on the intuition that there is functional information captured in the common neighbors of the common neighbors as well. Our results show that our algorithm outperforms well-known protein complex identification tools in a balance between precision and recall on three eukaryotic species: human, yeast, and fly. As a result of MNAs of the species, the proposed approach can tolerate edge loss in PPI networks and even discover sparse protein complexes which have traditionally been a challenge to predict. AVAILABILITY AND IMPLEMENTATION: http://acolab.ie.nthu.edu.tw/bionetwork/NEOComplex. CONTACT: bab@csail.mit.edu or csliao@ie.nthu.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A High-Temperature MEMS Surface Fence for Wall-Shear-Stress Measurement in Scramjet Flow.

A new variant of MEMS surface fence is proposed for shear-stress estimation under high-speed, high-temperature flow conditions. Investigation of high-temperature resistance including heat-resistant mechanism and process, in conjunction with high-temperature packaging design, enable the sensor to be used in environment up to 400 °C. The packaged sensor is calibrated over a range of ~65 Pa and then used to examine the development of the transient flow of the scramjet ignition process (Mach 2 airflow, stagnation pressure, and a temperature of 0.8 MPa and 950 K, respectively). The results show that the sensor is able to detect the transient flow conditions of the scramjet ignition process including shock impact, flow correction, steady state, and hydrogen off.

Rheological behaviors of anaerobic granular sludge in a spiral symmetry stream anaerobic bioreactor.

The rheological behaviors of the anaerobic granular sludge (AGS) in a spiral symmetry stream anaerobic bioreactor (SSSAB) were investigated. Shear-thinning behavior, thixotropic behavior, concentration-viscosity behavior and temperature-viscosity behavior were evaluated based on the constitutive equation of the AGS. The results indicated that the Herschel-Bulkley model was able to adequately describe the constitutive relation of AGS in the SSSAB. The AGS also showed shear-thinning behavior as well as thixotropic behavior. The critical shear rate and network strength of the AGS were 61.8 s(-1) and 497.0 W m(-3), respectively. The relationship between the apparent viscosity and the sludge concentration was illustrated and explained by the Woodcock formula. The relationship between apparent viscosity of the AGS and temperature could be modeled using the Arrhenius equation. The AGS was significantly thermo-sensitive and its mean energy of activation was 14.640 kJ mol(-1). Notably, it was necessary to consider such behaviors in the hydrodynamic modeling of SSSAB in which shear condition, sludge concentration and temperature were in non-uniform distribution.

Optimizing a global alignment of protein interaction networks.

MOTIVATION: The global alignment of protein interaction networks is a widely studied problem. It is an important first step in understanding the relationship between the proteins in different species and identifying functional orthologs. Furthermore, it can provide useful insights into the species' evolution. RESULTS: We propose a novel algorithm, PISwap, for optimizing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other intractable problems. PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information. In practice, our algorithm efficiently refines other well-studied alignment techniques with almost no additional time cost. We also show the robustness of the algorithm to noise in protein interaction data. In addition, the flexible nature of this algorithm makes it suitable for different applications of network alignment. This algorithm can yield interesting insights into the evolutionary dynamics of related species. AVAILABILITY: Our software is freely available for non-commercial purposes from our Web site, http://piswap.csail.mit.edu/. CONTACT: bab@csail.mit.edu or csliao@ie.nthu.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sociodemographic factors and health digital divide among urban residents: Evidence from a population-based survey in China.

Background: The deep integration of digital technology and healthcare services has propelled the healthcare system into the era of digital health. However, vulnerable populations in the field of information technology, they face challenges in benefiting from the digital dividends brought by digital health, leading to the emerging phenomenon of the "health digital divide." Methods: This study utilized the sample of 3547 urban from the 2021 Chinese Social Survey data for analysis. Models were constructed with digital access divide, digital usage divide, and digital outcome divide for urban residents, and structural equation modeling was implemented for analysis. Results: The impact ß coefficients (95% CI) of urban residents' digital access on the frequency of digital use, internet healthcare utilization, and patient experience were (ß = 0.737, P < 0.001), (ß = 0.047, P < 0.05), and (ß = 0.079, P < 0.001), respectively. Urban elderly groups were at a disadvantage in digital access and usage (ß = -0.007, ß = -0.024, and ß = -0.004), as well as those with lower educational levels (ß = 0.109, ß = 0.162, and ß = 0.045). However, these two factors did not have a significant direct impact on the patient experience in urban areas. Conclusions: The health digital divide of urban residents exhibits a cascading effect, primarily manifested in the digital access and usage divide. To bridge health digital divide among urban residents, efforts must be made to improve digital access and usage among the elderly and those with lower educational levels.

Interpretable Machine Learning Models for Predicting Critical Outcomes in Patients with Suspected Urinary Tract Infection with Positive Urine Culture.

(1) Background: Urinary tract infection (UTI) is a leading cause of emergency department visits and hospital admissions. Despite many studies identifying UTI-related risk factors for bacteremia or sepsis, a significant gap remains in developing predictive models for in-hospital mortality or the necessity for emergent intensive care unit admission in the emergency department. This study aimed to construct interpretable machine learning models capable of identifying patients at high risk for critical outcomes. (2) Methods: This was a retrospective study of adult patients with urinary tract infection (UTI), extracted from the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database. The critical outcome is defined as either in-hospital mortality or transfer to an intensive care unit within 12 h. ED visits were randomly partitioned into a 70%/30% split for training and validation. The extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM) algorithms were constructed using variables selected from the stepwise logistic regression model. The XGBoost model was then compared to the traditional model and clinical decision rules (CDRs) on the validation data using the area under the curve (AUC). (3) Results: There were 3622 visits among 3235 unique patients diagnosed with UTI. Of the 2535 patients in the training group, 836 (33%) experienced critical outcomes, and of the 1087 patients in the validation group, 358 (32.9%) did. The AUCs for different machine learning models were as follows: XGBoost, 0.833; RF, 0.814; and SVM, 0.799. The XGBoost model performed better than others. (4) Conclusions: Machine learning models outperformed existing traditional CDRs for predicting critical outcomes of ED patients with UTI. Future research should prospectively evaluate the effectiveness of this approach and integrate it into clinical practice.

Complete genome sequence of aquaculture pond isolate, Bacillus velezensis M4019.

Bacillus velezensis is commonly found in soil and has various antibacterial activities against animal and plant pathogens. Here, we present the complete genome sequence of Bacillus velezensis strain M4019, isolated from a euryhaline aquaculture pond water in Yong-An, Kaohsiung City, Taiwan. This pond-water-derived isolate, unlike common soil-derived isolates, may provide potentially different adaptations and antimicrobial cues for future research.

Evaluation of the cushion effect in blunt abdominal trauma patients: A computerized analysis.

BACKGROUND: Obesity may serve as a protective factor in blunt abdominal trauma (BAT) patients due to a "cushion effect". In this study, we aim to use computed tomography (CT) scans to measure abdominal adiposity and its correlation with injury severity in BAT patients. METHODS: We conducted a retrospective analysis of male BAT patients who had undergone CT scans. Subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) were manually measured and height-normalized for analysis at lumbar levels L2 and L3. Statistical methods were used to compare differences in adiposity between patients with and without severe abdominal injuries. For controls, we also compared adipose tissue in patients with and without severe trauma to the chest, where less fat typically accumulates. RESULTS: We included 361 male participants and conducted a comparative analysis of their demographic and injury characteristics. Patients without severe abdominal injuries had significantly higher SAT and VAT indices at both L2 and L3 (p < 0.05). However, these measures showed no significant differences between patients with and without severe chest trauma. Solid organ injuries, particularly liver injuries, were associated with decreased SAT and VAT. CONCLUSION: Increase abdominal adiposity was linked to lower abdominal injury severity and solid organ injuries, particularly liver injuries. In addition to conventional BMI for evaluating obesity, either subcutaneous or visceral adipose tissue over lumbar levels L2 and L3 can be used to assess the "cushion effect."

Reconstruction of phyletic trees by global alignment of multiple metabolic networks.

BACKGROUND: In the last decade, a considerable amount of research has been devoted to investigating the phylogenetic properties of organisms from a systems-level perspective. Most studies have focused on the classification of organisms based on structural comparison and local alignment of metabolic pathways. In contrast, global alignment of multiple metabolic networks complements sequence-based phylogenetic analyses and provides more comprehensive information. RESULTS: We explored the phylogenetic relationships between microorganisms through global alignment of multiple metabolic networks. The proposed approach integrates sequence homology data with topological information of metabolic networks. In general, compared to recent studies, the resulting trees reflect the living style of organisms as well as classical taxa. Moreover, for phylogenetically closely related organisms, the classification results are consistent with specific metabolic characteristics, such as the light-harvesting systems, fermentation types, and sources of electrons in photosynthesis. CONCLUSIONS: We demonstrate the usefulness of global alignment of multiple metabolic networks to infer phylogenetic relationships between species. In addition, our exhaustive analysis of microbial metabolic pathways reveals differences in metabolic features between phylogenetically closely related organisms. With the ongoing increase in the number of genomic sequences and metabolic annotations, the proposed approach will help identify phenotypic variations that may not be apparent based solely on sequence-based classification.

How has the COVID-19 pandemic affected the utilisation of online consultation and face-to-face medical treatment? An interrupted time-series study in Beijing, China.

OBJECTIVE: The COVID-19 pandemic has had a major impact on healthcare utilisation. This study aimed to quantify how the online and face-to-face utilisation of healthcare services changed during this time and thus gain insights into the planning of future healthcare resources during the outbreak of infectious diseases. DESIGN: This work is an interrupted time-series study. SETTING: Monthly hospital-grade healthcare-service data from 22 tertiary first-class public hospitals managed by the Beijing Hospital Authority and online-consultation data from GoodDoctor were used in this study. METHODS: This is an interrupted time-series study about the change in face-to-face and online healthcare utilisation before and after the COVID-19 outbreak. We compared the impact of COVID-19 on the primary outcomes of both face-to-face healthcare utilisation (outpatient and emergency visits, discharge volume) and online healthcare utilisation (online consultation volume). And we also analysed the impact of COVID-19 on the healthcare utilisation of different types of diseases. RESULTS: The monthly average outpatient visits and discharges decreased by 36.33% and 35.75%, respectively, compared with those in 2019 in 22 public hospitals in Beijing. Moreover, the monthly average online consultations increased by 90.06%. A highly significant reduction occurred in the mean outpatients and inpatients, which dropped by 1 755 930 cases (p<0.01) and 5 920 000 cases (p<0.01), respectively. Online consultations rose by 3650 cases (p<0.05). We identified an immediate and significant drop in healthcare services for four major diseases, that is, acute myocardial infarction (-174, p<0.1), lung cancer (-2502, p<0.01), disk disease (-3756, p<0.01) and Parkinson's disease (-205, p<0.01). Otherwise, online consultations for disk disease (63, p<0.01) and Parkinson's disease (25, p<0.05) significantly increased. More than 1300 unique physicians provided online-consultation services per month in 2020, which was 35.3% higher than in 2019. CONCLUSIONS: Obvious complementary trends in online and face-to-face healthcare services existed during the COVID-19 pandemic. Different changes in healthcare utilisation were shown for different diseases. Non-critically ill patients chose online consultation immediately after the COVID-19 lockdown, but critically ill patients chose hospital healthcare services first. Additionally, the volume of online physician services significantly rose as a result of COVID-19.

Corrigendum: Patients' choice preferences for specialist outpatient online consultations: a discrete choice experiment.

[This corrects the article DOI: 10.3389/fpubh.2022.1075146.].

Angular super-resolution in X-ray projection radiography using deep neural network: Implementation on rotational angiography.

BACKGROUND: Rotational angiography acquires radiographs at multiple projection angles to demonstrate superimposed vasculature. However, this comes at the expense of the inherent risk of increased ionizing radiation. In this paper, building upon a successful deep learning model, we developed a novel technique to super-resolve the radiography at different projection angles to reduce the actual projections needed for a diagnosable radiographic procedure. METHODS: Ten models were trained for different levels of angular super-resolution (ASR), denoted as ASRN, where for every N+2 frames, the first and the last frames were submitted as inputs to super-resolve the intermediate N frames. RESULTS: The results show that large arterial structures were well preserved in all ASR levels. Small arteries were adequately visualized in lower ASR levels but progressively blurred out in higher ASR levels. Noninferiority of image quality was demonstrated in ASR1-4 (99.75% confidence intervals: -0.16-0.03, -0.19-0.04, -0.17-0.01, -0.15-0.05 respectively). CONCLUSIONS: ASR technique is capable of super-resolving rotational angiographic frames at intermediate projection angles.

Dietary L-Lysine Requirement of Coho Salmon (Oncorhynchus kisutch) Alevins.

The suitable dietary L-lysine concentration for coho salmon (Oncorhynchus kisutch) alevins was assessed by a dose response feeding trial. Six experimental diets were made with graded L-lysine concentrations of 2.29%, 2.81%, 3.32%, 3.80%, 4.27%, and 4.78% of the dry matter, respectively, each of which was fed to triplicate groups of 100 alevins (initial body weight: 0.30 ± 0.01 g) in 18 plastic baskets (water volume 240 L). The alevins were cultured in a flowing freshwater system and fed manually to apparent satiation four times a day for 12 weeks. The survival rate of alevins did not differ significantly among the dietary groups. The specific growth rate (SGR), protein efficiency ratio (PER), and body protein deposition (BPD) increased significantly (p < 0.05) with the increase in dietary lysine concentration up to 3.80% and then reduced as lysine level further increased. The feed conversion ratio (FCR) had an inverse trend to SGR. The whole-body crude protein content of the alevins increased significantly with increasing dietary lysine level, while crude lipid content showed the opposite trend. In comparison, the contents of morphological indices, whole-body moisture, and ash were not affected significantly (p > 0.05) by the different dietary lysine concentrations. The highest contents of lysine, arginine, and total essential amino acids (EAAs) were observed in the group with 4.27% dietary lysine concentration, which did not differ significantly from those in the 3.32%, 3.80%, and 4.78% groups but was significantly higher than those in the 2.29% and 2.81% groups. Similarly, valine had the highest content in the group with 4.78%. The variations in dietary lysine had no significant impacts on other EAA and non-EAA contents except glycine, which increased with increasing dietary lysine level. Second-order polynomial model analyses based on SGR, PER, BPD, and FCR evaluated the optimum L-lysine requirements of coho salmon alevins as 3.74%, 3.73%, 3.91%, and 3.77% of the diet or 6.80%, 6.78%, 7.11%, and 6.85% of dietary proteins, respectively.

Roles of doctor-patient relationship perception and job satisfaction in the impact of workplace violence on medical professionals' turnover intentions in the early phase of COVID-19: a cross-sectional study in China.

OBJECTIVE: This study aimed to explore the role of the doctor-patient relationship (DPR) perception from the perspective of medical professionals in the association between workplace violence (WPV), job satisfaction and turnover intention in the early stages of the COVID-19 pandemic based on the affective events theory (AET). DESIGN: A cross-sectional study. SETTING: Nine medical institutions in Beijing were enrolled in this study. PARTICIPANTS: In total, 792 medical professionals participated in the study, excluding administrators and logisticians. RESULTS: The structural equation model was well adapted (comparative fit index (CFI) = 0.933; root mean square error of approximation (RMSEA) = 0.060). DPR mediated the association between WPV and job satisfaction, with an indirect effect of 0.247 (p<0.001). DPR perception mediated the effect of WPV on turnover intention, with an indirect effect of 0.090 (p<0.001). It also played a chain-mediating role in job satisfaction between WPV and turnover intention, with a mediation value of 0.117 (p<0.001), accounting for 53.42% of the total effect. CONCLUSIONS: This study developed a stable model using AET. DPR perception plays an important role in the relationship between WPV and job satisfaction and turnover intention, suggesting the key impact of emotional factors. This has strong practical implications for maintaining the stability of medical teams. Therefore, medical institutions should improve the level of DPR perception from the perspective of medical professionals to effectively prevent mental health problems following WPV.

Patients' choice preferences for specialist outpatient online consultations: A discrete choice experiment.

Background: Internet hospitals are multiplying with solid support from the Chinese government. In internet hospitals, specialist outpatient online consultations (SOOC) are the primary services. However, the acceptance and utilization rates of this service are still low. Thus, the study of patients' choice preferences for SOOC is needed. Objective: To analyze the choice preference of patients' SOOC via a discrete choice experiment, understand the influence of each factor and promote the development of internet hospitals. Methods: Via a discrete selection experiment, a total of 162 patients from two general hospitals and three specialized hospitals in Beijing were selected for the questionnaire survey. The choice preferences were analyzed by conditional logit regression. Results: From high to low, patients' willingness to pay (WTP) for the attributes of SOOC is as follows: doctors' recommendation rate (ß highly recommend = 0.999), the convenience of applying SOOC services (ß Convenient = 0.760), the increasing ratio of medical insurance payment for online services compared to offline (ß Increase by 10% = 0.545), and the disease's severity (ß severe = -3.024). The results of the subgroup analysis showed differences in patient choice preference by age, whether the patients had chronic diseases, income, and medical insurance types. Conclusion: Both price and nonprice attributes influence the choice preference of SOOC for patients. Among them, patients are more inclined to choose SOOC when doctors highly recommend it, when it is convenient to apply, when medical insurance increases by 10%, and when disease severity is mild. The current findings show the government and medical institutions formulate auxiliary policies and welfare strategies by clarifying core attributes and adjusting the levels of different attributes to improve patients' acceptance of SOOC. The utility of SOOC and the further development of internet hospitals are radically promoted.

Complete Genome Sequence of a Suckermouth Catfish Outbreak Isolate, Aeromonas hydrophila Strain LP0103.

Aeromonas hydrophila is the most common opportunistic pathogen that plagues freshwater and euryhaline fishponds. Here, we present the complete genome sequence of A. hydrophila strain LP0103, which was isolated from a bacterial septicemia outbreak among suckermouth catfish (Pterygoplichthys pardalis) at Lotus Pond in Kaohsiung City, Taiwan.

Red room temperature phosphorescence of lead halide based coordination polymer showing efficient angle-dependent polarized emission and photoelectric performance.

The development of organic-inorganic hybrid materials with long-lived room temperature phosphorescence (RTP) has attracted tremendous attention owing to their promising applications in the optoelectronic and anti-counterfeiting fields. In this work, by the selection of lead halide and electron-poor heteroaromatic molecule 1,10-phenanthroline (phen), a coordination polymer [Pb(phen)Cl2] has been synthesized under hydrothermal conditions. This complex shows an alternating arrangement of a long-range order of phen π-conjugated systems and lead halide inorganic chains as revealed by X-ray single-crystal structural analysis. This structural character and special chemical components endow this hybrid material with a rare example of red room temperature phosphorescence. Its electronic structure and electronic transition behavior were further examined by theoretical calculations. Meanwhile, the film of the complex features remarkable angle-dependent polarized emission and photoelectric performance.

An anthracene based metal-organic framework showing efficient angle-dependent polarized emission, luminescence thermometry, and photoelectronic response.

The development of luminescent metal-organic frameworks (MOFs) has attracted extensive attention due to their applications in photoelectric devices, organic light-emitting diodes (OLEDs), anti-counterfeiting, biological imaging and so on. In this work, a novel anthracene based metal-organic framework, [Cd(DCPA)(DMF)]·(H2O) (1) (H2DCPA = 9,10-di(p-carboxyphenyl)anthracene), has been successfully synthesized under solvothermal conditions. The highly ordered arrangement and special spatial conformation of the anthracene chromophore play a significant role in the photophysical properties of 1. The combination of theoretical calculations and experiments shows that the molecular orbitals have good separation for inhibiting the recombination of electrons and holes. Furthermore, the fluorescence emission of 1 can be instantaneously and reversibly tuned between blue and green at different polarizing angles. Temperature-dependent fluorescence measurements indicate a good linear relationship between the maximum emission intensity/wavelength and the temperature for efficient thermochromism and luminescence thermometry. Photoelectric measurements reveal that 1 shows high performance of photocurrent generation under light illumination. Therefore, our research affords a new perspective to extend the application of luminescent MOFs in the fields of polarized emission, thermometry and photoelectronic response.

Anaerobic co-digestion of textile dyeing sludge: Digestion efficiency and heavy metal stability.

Anaerobic co-digestion (AcoD) has become an important mean for the stabilization and recycling of textile dyeing sludge (TDS). Using the soybean okara byproduct (SOB) as a co-digestion substrate, the effects on AcoD performance and heavy metal stability were studied. The results indicated that the optimal mixing ratio was 1:1 (calculated by total sloid). Under this condition, the SCOD removal efficiency was 64% (that of TDS alone and SOB alone were 47% and 48%, respectively) and the cumulative methane production field was 503 L CH4/kg VS (that of TDS alone and SOB alone were 435 L CH4/kg VS and 408 L CH4/kg VS, respectively). At the same time, the addition of SOB could also enhance the stability of heavy metals (Zn, Cu, Cr and Ni) in TDS. Remarkably, that could increase the steady state content nickel from 47.98% to 57.21%, while anaerobic digestion of TDS caused no increase but a decrease (only 42.13%). According to the risk assessment code analyses, the AcoD of TDS by SOB can significantly reduce the ecotoxicity risk caused by Ni, Zn and Cr.

A review of protein-protein interaction network alignment: From pathway comparison to global alignment.

Network alignment provides a comprehensive way to discover the similar parts between molecular systems of different species based on topological and biological similarity. With such a strong basis, one can do comparative studies at a systems level in the field of computational biology. In this survey paper, we focus on protein-protein interaction networks and review some representative algorithms for network alignment in the past two decades as well as the state-of-the-art aligners. We also introduce the most popular evaluation measures in the literature to benchmark the performance of these approaches. Finally, we address several future challenges and the possible ways to conquer the existing problems of biological network alignment.