Metal-Organic Framework-Based Hetero-Phase Nanostructure Photocatalysts with Molecular-Scale Tunable Energy Levels.

As an effective method to modulate the physicochemical properties of materials, crystal phase engineering, especially hetero-phase, plays an important role in developing high-performance photocatalysts. However, it is still a huge challenge but significant to construct porous hetero-phase nanostructures with adjustable band structures. As a kind of unique porous crystalline materials, metal-organic frameworks (MOFs) might be the appropriate candidate, but the MOF-based hetero-phase is rarely reported. Herein, we developed a secondary building unit (SBU) regulating strategy to prepare two crystal phases of Ti-MOFs constructed by titanium and 1,4-dicarboxybenzene, i.e., COK and MIL-125. Besides, COK/MIL-125 hetero-phase was further constructed. In the photocatalytic hydrogen evolution reaction, COK/MIL-125 possessed the highest H2 yield compared to COK and MIL-125, ascribing to the Z-Scheme homojunction at hetero-phase interface. Furthermore, by decorating with amino groups (i.e., NH2-COK/NH2-MIL-125), the light absorbing capacity was broadened to visible-light region, and the visible-light-driven H2 yield was greatly improved. Briefly, the MOF-based hetero-phase possesses periodic channel structures and molecularly adjustable band structures, which is scarce in traditional organic or inorganic materials. As a proof of concept, our work not only highlights the development of MOF-based hetero-phase nanostructures, but also paves a novel avenue for designing high-performance photocatalysts.

Large-Area Conductive MOF Ultrathin Film Controllably Integrating Dinuclear-Metal Sites and Photosensitizers to Boost Photocatalytic CO2 Reduction with H2O as an Electron Donor.

Owing to the electrical conductivity and periodic porosity, conductive metal-organic framework (cMOF) ultrathin films open new perspectives to photocatalysis. The space-selective assembly of catalytic sites and photosensitizers in/on cMOF is favorable for promoting the separation of photogenerated carriers and mass transfer. However, the controllable integration of functional units into the cMOF film is rarely reported. Herein, via the synergistic effect of steric hindrance and an electrostatic-driven strategy, the dinuclear-metal molecular catalysts (DMC) and perovskite (PVK) quantum dot photosensitizers were immobilized into channels and onto the surface of cMOF ultrathin films, respectively, affording [DMC@cMOF]-PVK film photocatalysts. In this unique heterostructure, cMOF not only facilitated the charge transfer from PVK to DMC but also guaranteed mass transfer. Using H2O as an electron donor, [DMC@cMOF]-PVK realized a 133.36 µmol·g-1·h-1 CO yield in photocatalytic CO2 reduction, much higher than PVK and DMC-PVK. Owing to the excellent light transmission of films, multilayers of [DMC@cMOF]-PVK were integrated to increase the CO yield per unit area, and the 10-layer device realized a 1115.92 µmol·m-2 CO yield in 4 h, which was 8-fold higher than that of powder counterpart. This work not only lightens the development of cMOF-based composite films but also paves a novel avenue for an ultrathin film photocatalyst.

Comparative prevalence of oral bacteria and protozoa in patients with periodontitis in Taiwan.

OBJECTIVES: Periodontitis is an inflammatory disease caused by bacteria present in the dental biofilm. However, the presence of two oral protozoans, Entamoeba gingivalis and Trichomonas tenax, in patients with the periodontal disease remains largely unknown in Taiwan. Therefore, we investigated the prevalence of oral microbial infections between the sites with mild gingivitis and chronic periodontitis in patients. MATERIALS AND METHODS: We collected 60 dental biofilm samples from sites with mild gingivitis (probing depth <5 mm) and chronic periodontitis (probing depth ≥5 mm) from 30 patients at the National Cheng Kung University Hospital. The samples were analyzed via polymerase chain reaction and gel electrophoresis. RESULTS: Among oral protozoans, E. gingivalis and T. tenax were detected in 44 (74.07%) and 14 (23.33%) of all samples, respectively. Among oral bacteria, Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia were detected in 50 (83.33%), 47 (78.33%), and 48 (80.0%) samples, respectively. CONCLUSIONS: This study, which is the first to analyze E. gingivalis and T. tenax presence among patients with periodontitis in Taiwan, revealed an association between periodontitis and oral microbes.

Interdisciplinary treatment with implant-supported two-unit cantilever prosthesis for a patient with hypodontia: A clinical report.

A 21-year-old woman with multiple congenitally missing maxillary anterior teeth received interdisciplinary treatment to restore function and esthetics. The treatment was initiated with orthodontic treatment, followed by implant placement, bone and soft-tissue augmentation, and prosthetic treatment including a screw-retained implant-supported 2-unit cantilever fixed dental prosthesis.

Score-based prediction model for severe vitamin D deficiency in patients with critical illness: development and validation.

BACKGROUND: Severe vitamin D deficiency (SVDD) dramatically increases the risks of mortality, infections, and many other diseases. Studies have reported higher prevalence of vitamin D deficiency in patients with critical illness than general population. This multicenter retrospective cohort study develops and validates a score-based model for predicting SVDD in patients with critical illness. METHODS: A total of 662 patients with critical illness were enrolled between October 2017 and July 2020. SVDD was defined as a serum 25(OH)D level of < 12 ng/mL (or 30 nmol/L). The data were divided into a derivation cohort and a validation cohort on the basis of date of enrollment. Multivariable logistic regression (MLR) was performed on the derivation cohort to generate a predictive model for SVDD. Additionally, a score-based calculator (the SVDD score) was designed on the basis of the MLR model. The model's performance and calibration were tested using the validation cohort. RESULTS: The prevalence of SVDD was 16.3% and 21.7% in the derivation and validation cohorts, respectively. The MLR model consisted of eight predictors that were then included in the SVDD score. The SVDD score had an area under the receiver operating characteristic curve of 0.848 [95% confidence interval (CI) 0.781-0.914] and an area under the precision recall curve of 0.619 (95% CI 0.577-0.669) in the validation cohort. CONCLUSIONS: This study developed a simple score-based model for predicting SVDD in patients with critical illness. TRIAL REGISTRATION: ClinicalTrials.gov protocol registration ID: NCT03639584. Date of registration: May 12, 2022.

How Do Employees Understand Negative Leadership? The Non-linear Relationship Between Abusive Supervision and Employee Innovation Behavior: Job Performance as a Moderator.

This study aims to investigate the non-linear relationship between abusive supervision and employee innovation behavior and further examine how job performance moderates this relationship. Two hundred and seventy-six employees across three industries (restaurant service, tourism, and financial service) in China participated in this study and completed the survey at two time points. The results of curve regression show as follows: (1) There exists a non-linear relationship between abusive supervision and innovation behavior, and (2) job performance moderates the non-linear relationship between abusive supervision and employee innovation behavior. For employees who perform well at work, there exists a U-shaped relationship between abusive supervision and innovative behavior. Whereas, for employees with poor job performance, when abusive supervision reaches a certain level, it will promote employee innovation behavior; and the excess of abusive supervision will inhibit employee innovation behavior, showing an inverted U-shaped curve relationship. The finding suggests it is important for managers to understand the stakes arising from abusive supervision. That is, managers should manipulate the right level of abuse supervision to promote employee innovation behavior.

Determining Carina and Clavicular Distance-Dependent Positioning of Endotracheal Tube in Critically Ill Patients: An Artificial Intelligence-Based Approach.

Early and accurate prediction of endotracheal tube (ETT) location is pivotal for critically ill patients. Automatic and timely detection of faulty ETT locations from chest X-ray images may avert patients' morbidity and mortality. Therefore, we designed convolutional neural network (CNN)-based algorithms to evaluate ETT position appropriateness relative to four detected key points, including tracheal tube end, carina, and left/right clavicular heads on chest radiographs. We estimated distances from the tube end to tracheal carina and the midpoint of clavicular heads. A DenseNet121 encoder transformed images into embedding features, and a CNN-based decoder generated the probability distributions. Based on four sets of tube-to-carina distance-dependent parameters (i.e., (i) 30-70 mm, (ii) 30-60 mm, (iii) 20-60 mm, and (iv) 20-55 mm), corresponding models were generated, and their accuracy was evaluated through the predicted L1 distance to ground-truth coordinates. Based on tube-to-carina and tube-to-clavicle distances, the highest sensitivity, and specificity of 92.85% and 84.62% respectively, were revealed for 20-55 mm. This implies that tube-to-carina distance between 20 and 55 mm is optimal for an AI-based key point appropriateness detection system and is empirically comparable to physicians' consensus.

Prevalence of Vitamin D Deficiency and Associated Factors in Critically Ill Patients: A Multicenter Observational Study.

Background: Vitamin D deficiency is common in the general population worldwide, and the prevalence and severity of vitamin D deficiency increase in critically ill patients. The prevalence of vitamin D deficiency in a community-based cohort in Northern Taiwan was 22.4%. This multicenter cohort study investigated the prevalence of vitamin D deficiency and associated factors in critically ill patients in Northern Taiwan. Methods: Critically ill patients were enrolled and divided into five groups according to their length of stay at intensive care units (ICUs) during enrolment as follows: group 1, <2 days with expected short ICU stay; group 2, <2 days with expected long ICU stay; group 3, 3-7 days; group 4, 8-14 days; and group 5, 15-28 days. Vitamin D deficiency was defined as a serum 25-hydroxyvitamin D (25(OH)D) level < 20 ng/ml, and severe vitamin D deficiency was defined as a 25(OH)D level < 12 ng/ml. The primary analysis was the prevalence of vitamin D deficiency. The exploratory analyses were serial follow-up vitamin D levels in group 2, associated factors for vitamin D deficiency, and the effect of vitamin D deficiency on clinical outcomes in critically ill patients. Results: The prevalence of vitamin D deficiency was 59% [95% confidence interval (CI) 55-62%], and the prevalence of severe vitamin D deficiency was 18% (95% CI 15-21%). The median vitamin D level for all enrolled critically ill patients was 18.3 (13.7-23.9) ng/ml. In group 2, the median vitamin D levels were <20 ng/ml during the serial follow-up. According to the multivariable analysis, young age, female gender, low albumin level, high parathyroid hormone (PTH) level, and high sequential organ failure assessment (SOFA) score were significantly associated risk factors for vitamin D deficiency. Patients with vitamin D deficiency had longer ventilator use duration and length of ICU stay. However, the 28- and 90-day mortality rate were not associated with vitamin D deficiency. Conclusions: This study demonstrated that the prevalence of vitamin D deficiency is high in critically ill patients. Age, gender, albumin level, PTH level, and SOFA score were significantly associated with vitamin D deficiency in these patients.

Polymer-Assisted Space-Confined Strategy for the Foot-Scale Synthesis of Flexible Metal-Organic Framework-Based Composite Films.

At the gas-liquid interface, the confined synthesis of metal-organic framework (MOF) films has been extensively developed by spreading an ultrathin oil layer on the aqueous surface as a reactor. However, this interface is susceptible to various disturbances and incapable of synthesizing large-area crystalline MOF films. Herein, we developed a polymer-assisted space-confined strategy to synthesize large-area films by blending poly(methyl methacrylate) (PMMA) into the oil layer, which improved the stability of the gas-liquid interface and the self-shrinkage of the oil layer on the water surface. Meanwhile, the as-synthesized MOFs as a quasi-solid substrate immobilized the edge of the oil layer, which maintained a large spreading area. Thanks to this synergistic effect, we synthesized the freestanding MOF-based film with a foot-level (0.66 ft) lateral dimension, which is the largest size reported so far. Besides, due to the phase separation of the two components, the MOF-PMMA composite film combined the conductivity of MOFs (1.13 S/m) with the flexibility of PMMA and exhibited excellent mechanical properties. More importantly, this strategy could be extended to the preparation of other MOFs, coordination polymers (CPs), and even inorganic material composite films, bringing light to the design and large-scale synthesis of various composite films for practical applications.

Using Transfer Learning Method to Develop an Artificial Intelligence Assisted Triaging for Endotracheal Tube Position on Chest X-ray.

Endotracheal tubes (ETTs) provide a vital connection between the ventilator and patient; however, improper placement can hinder ventilation efficiency or injure the patient. Chest X-ray (CXR) is the most common approach to confirming ETT placement; however, technicians require considerable expertise in the interpretation of CXRs, and formal reports are often delayed. In this study, we developed an artificial intelligence-based triage system to enable the automated assessment of ETT placement in CXRs. Three intensivists performed a review of 4293 CXRs obtained from 2568 ICU patients. The CXRs were labeled "CORRECT" or "INCORRECT" in accordance with ETT placement. A region of interest (ROI) was also cropped out, including the bilateral head of the clavicle, the carina, and the tip of the ETT. Transfer learning was used to train four pre-trained models (VGG16, INCEPTION_V3, RESNET, and DENSENET169) and two models developed in the current study (VGG16_Tensor Projection Layer and CNN_Tensor Projection Layer) with the aim of differentiating the placement of ETTs. Only VGG16 based on ROI images presented acceptable performance (AUROC = 92%, F1 score = 0.87). The results obtained in this study demonstrate the feasibility of using the transfer learning method in the development of AI models by which to assess the placement of ETTs in CXRs.

Self-correction of pathologic tooth migration after nonsurgical periodontal treatment in a metabolic syndrome patient with severe periodontitis and drug-influenced gingival enlargement.

Drug-influenced gingival enlargement (DIGE) and reduced bone support caused by periodontitis are two of the etiologic factors for pathologic tooth migration (PTM). Comprehensive management, including surgical, orthodontic, and prosthodontic treatment, is usually required for recovery from severe DIGE and PTM. An 85-year-old Taiwanese male with a history of hypertension and uncontrolled diabetes mellitus (DM) visited our dental department for severe gingival enlargement and spontaneous bleeding. He was diagnosed as having advanced periodontitis and DIGE. Remarkable PTM occurred on the front sextants of his dentition. The patient's DM was gradually controlled, and his calcium channel blocker treatment was substituted with a new regimen for 7 months. One year after nonsurgical periodontal treatment and reinforcing the patient's oral care, both DIGE and PTM were spontaneously resolved without any surgical or orthodontic intervention. We advocate the value of early diagnosis, improving patient's oral hygiene, and meticulous nonsurgical treatment for both DIGE and PTM.

Recommendations for treating stage I-III periodontitis in the Taiwanese population: A consensus report from the Taiwan Academy of Periodontology.

BACKGROUND/PURPOSE: Based on the fundamental of the S3-level clinical practice guideline (CPG) for treating stage I-III periodontitis developed by the European Federation of Periodontology (EFP), this consensus report aimed to develop treatment recommendations for treating periodontitis in the Taiwanese population. METHODS: The report was constructed by experts from the Taiwan Academy of Periodontology. The following topics were reviewed: (a) the prevalence of periodontitis in Asia and current status of treatment in Taiwan; (b) specific anatomical considerations for treating periodontitis in Asians; (d) educational and preventive interventions and supragingival plaque control; (d) subgingival instrumentation and adjunctive treatment; (e) surgical periodontal therapy; and (f) maintenance and supportive periodontal care. Recommendations were made according to the evidences from the EFP CPG, the published literature and clinical studies in Asians, and the expert opinions. RESULTS: The treatment recommendations for the Taiwanese population were generally in parallel with the EFP CPG, and extra cautions during treatment and maintenance phases were advised due to the anatomical variations, such as shorter root trunk, higher prevalence of supernumerary distolingual root and lingual bony concavity in mandibular posteriors, and thinner anterior labial plate, of the Asian population. CONCLUSION: The EFP CPG could be adopted for treating periodontitis and maintaining periodontal health of the Taiwanese population, and anatomical variations should be cautious when the treatment is delivered.

Environmental stressors and well-being on middle-aged and elderly people: the mediating role of outdoor leisure behaviour and place attachment.

This study develops a relational model of how environmental stressors, place attachment and outdoor leisure are related to urban green zones and, accordingly, Fujian Province in China is studied as our case problem. The research is participated by primarily middle-aged and elderly residents. In total, 871 valid questionnaires are retrieved. Structural equation modelling and path analysis are used to verify the model's fitness. The results indicate that environmental stressors and outdoor leisure are significantly negatively correlated. In addition, the outdoor leisure and place attachment are significantly positively correlated. As such, the place attachment and well-being are significantly positively correlated. However, the place attachment and outdoor leisure mediated the relationship between environmental stressors and well-being. The mediating path indicated that middle-aged and elderly residents face severe environmental stressors and will engage in a few outdoor leisure activities, resulting in low well-being. Furthermore, when middle-aged and elderly residents face severe environmental stressors, they have increased place attachment, thereby increasing their well-being. The findings can serve as a reference for environmental management agencies and future researchers.

Incidence and management of metabolic acidosis with sodium bicarbonate in the ICU: An international observational study.

BACKGROUND: Metabolic acidosis is a major complication of critical illness. However, its current epidemiology and its treatment with sodium bicarbonate given to correct metabolic acidosis in the ICU are poorly understood. METHOD: This was an international retrospective observational study in 18 ICUs in Australia, Japan, and Taiwan. Adult patients were consecutively screened, and those with early metabolic acidosis (pH < 7.3 and a Base Excess < -4 mEq/L, within 24-h of ICU admission) were included. Screening continued until 10 patients who received and 10 patients who did not receive sodium bicarbonate in the first 24 h (early bicarbonate therapy) were included at each site. The primary outcome was ICU mortality, and the association between sodium bicarbonate and the clinical outcomes were assessed using regression analysis with generalized linear mixed model. RESULTS: We screened 9437 patients. Of these, 1292 had early metabolic acidosis (14.0%). Early sodium bicarbonate was given to 18.0% (233/1292) of these patients. Dosing, physiological, and clinical outcome data were assessed in 360 patients. The median dose of sodium bicarbonate in the first 24 h was 110 mmol, which was not correlated with bodyweight or the severity of metabolic acidosis. Patients who received early sodium bicarbonate had higher APACHE III scores, lower pH, lower base excess, lower PaCO2, and a higher lactate and received higher doses of vasopressors. After adjusting for confounders, the early administration of sodium bicarbonate was associated with an adjusted odds ratio (aOR) of 0.85 (95% CI, 0.44 to 1.62) for ICU mortality. In patients with vasopressor dependency, early sodium bicarbonate was associated with higher mean arterial pressure at 6 h and an aOR of 0.52 (95% CI, 0.22 to 1.19) for ICU mortality. CONCLUSIONS: Early metabolic acidosis is common in critically ill patients. Early sodium bicarbonate is administered by clinicians to more severely ill patients but without correction for weight or acidosis severity. Bicarbonate therapy in acidotic vasopressor-dependent patients may be beneficial and warrants further investigation.

The first study to detect co-infection of Entamoeba gingivalis and periodontitis-associated bacteria in dental patients in Taiwan.

Periodontitis, an inflammatory disease of the oral cavity, was caused by microbes from bacteria to protozoa. In this study, we detected protozoa, Entamoeba gingivalis and other three common pathogenic bacteria, Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia by the Polymerase chain reaction (PCR) on patients.

Differences of liver CT perfusion of blunt trauma treated with therapeutic embolization and observation management.

Massive hepatic necrosis after therapeutic embolization has been reported. We employed a 320-detector CT scanner to compare liver perfusion differences between blunt liver trauma patients treated with embolization and observation. This prospective study with informed consent was approved by institution review board. From January 2013 to December 2016, we enrolled 16 major liver trauma patients (6 women, 10 men; mean age 34.9 ± 12.8 years) who fulfilled inclusion criteria. Liver CT perfusion parameters were calculated by a two-input maximum slope model. Of 16 patients, 9 received embolization and 7 received observation. Among 9 patients of embolization group, their arterial perfusion (78.1 ± 69.3 versus 163.1 ± 134.3 mL/min/100 mL, p = 0.011) and portal venous perfusion (74.4 ± 53.0 versus 160.9 ± 140.8 mL/min/100 mL, p = 0.008) were significantly lower at traumatic parenchyma than at non-traumatic parenchyma. Among 7 patients of observation group, only portal venous perfusion was significantly lower at traumatic parenchyma than non-traumatic parenchyma (132.1 ± 127.1 vs. 231.1 ± 174.4 mL/min/100 mL, p = 0.018). The perfusion index between groups did not differ. None had massive hepatic necrosis. They were not different in age, injury severity score and injury grades. Therefore, reduction of both arterial and portal venous perfusion can occur when therapeutic embolization was performed in preexisting major liver trauma, but hepatic perfusion index may not be compromised.

The development an artificial intelligence algorithm for early sepsis diagnosis in the intensive care unit.

BACKGROUND: Severe sepsis and septic shock are still the leading causes of death in Intensive Care Units (ICUs), and timely diagnosis is crucial for treatment outcomes. The progression of electronic medical records (EMR) offers the possibility of storing a large quantity of clinical data that can facilitate the development of artificial intelligence (AI) in medicine. However, several difficulties, such as poor structure and heterogenicity of the raw EMR data, are encountered when introducing AI with ICU data. Labor-intensive work, including manual data entry, personal medical records sorting, and laboratory results interpretation may hinder the progress of AI. In this article, we introduce the developing of an AI algorithm designed for sepsis diagnosis using pre-selected features; and compare the performance of the AI algorithm with SOFA score based diagnostic method. MATERIALS AND METHODS: This is a prospective open-label cohort study. A specialized EMR, named TED_ICU, was implemented for continuous data recording. One hundred six clinical features relevant to sepsis diagnosis were selected prospectively. A labeling work to allocate SEPSIS or NON_SEPSIS status for each ICU patient was performed by the in-charge intensivist according to SEPSIS-3 criteria, along with the automatic recording of selected features every day by TED_ICU. Afterward, we use de-identified data to develop the AI algorithm. Several machine learning methods were evaluated using 5-fold cross-validation, and XGBoost, a decision-tree based algorithm was adopted for our AI algorithm development due to best performance. RESULTS: The study was conducted between August 2018 and December 2018 for the first stage of analysis. We collected 1588 instances, including 444 SEPSIS and 1144 NON-SEPSIS, from 434 patients. The 434 patients included 259 (59.6%) male patients and 175 female patients. The mean age was 67.6-year-old, and the mean APACHE II score was 13.8. The SEPSIS cohort had a higher SOFA score and increased use of organ support treatment. The AI algorithm was developed with a shuffle method using 80% of the instances for training and 20% for testing. The established AI algorithm achieved the following: accuracy = 82% ± 1%; sensitivity = 65% ± 5%; specificity = 88% ± 2%; precision = 67% ± 3%; and F1 = 0.66 ± 0.02. The area under the receiver operating characteristic curve (AUROC) was approximately 0.89. The SOFA score was used on the same 1588 instances for sepsis diagnosis, and the result was inferior to our AI algorithm (AUROC = 0.596). CONCLUSION: Using real-time data, collected by EMR, from the ICU daily practice, our AI algorithm established with pre-selected features and XGBoost can provide a timely diagnosis of sepsis with an accuracy greater than 80%. AI algorithm also outperforms the SOFA score in sepsis diagnosis and exhibits practicality as clinicians can deploy appropriate treatment earlier. The early and precise response of this AI algorithm will result in cost reduction, outcome improvement, and benefit for healthcare systems, medical staff, and patients as well.

Exploring Links between Polychronicity and Job Performance from the Person-Environment Fit Perspective-The Mediating Role of Well-Being.

Polychronicity refers to the preference of some individuals to structure their time in order to deal with multiple tasks simultaneously in a short period of time. Past research regarding the correlation between individual polychronicity and performance presented distinct arguments. Although most studies supported a positive correlation with performance, empirical findings showed inconsistent results, indicating the presence of other influencing factors. According to the person-environment fit theory and self-determination theory, the effect of polychronicity on job performance was verified and the mediation effect of well-being was tested in this study. Dual-mode questionnaires were collected from 532 subordinators and their direct supervisors in 98 chain restaurants and hierarchical regression analysis was performed to test the research hypotheses. The results showed that polychronicity positively affected well-being, that is, well-being was a full mediator between polychronicity and job performance. This study provides valuable insight for managers to understand employee polychronicity and, in turn, improve their well-being, which could help improve job performance.