Older Taiwanese Volunteers as Standardized Patients: Service Motivation, Identity Formation, and Internal Transformation.

INTRODUCTION: Most standardized patients (SPs) in Taiwan are middle-aged or older volunteers with a high retention rate and selflessly devote themselves to the service. This study explored the psychological process behind the continued altruistic behaviors of SPs to understand the formation of service motivation, professional identity, and internal transformation. METHODS: Sixteen volunteers, aged 50 to 70 years, who served as SPs for 3 to 11 years in a religious hospital were enrolled in this study. Individual semistructured interviews were conducted. Each person was interviewed for approximately 120 minutes. We used a thematic analysis to analyze the interview transcripts. RESULTS: We identified 3 major themes and 8 subthemes. The first theme, SPs' service motivation, included the following 3 subthemes: past medical experiences, acquisition of medical knowledge, and emotional connections. The second theme, SPs' identity formation, included the following 3 subthemes: role recognition, work ethic, and a sense of religious mission. The third theme, SPs' physical and psychological support, included 2 subthemes: internal transformation and personal well-being. CONCLUSIONS: The interview results showed doctor-patient or life experiences served as the impetus prompting SPs to engage in such altruistic behavior. In addition, identity formation endowed older SPs with a life purpose and a sense of fulfillment and self-actualization through fostering and training medical students. In addition, a clear recognition of the role of an SP and self-worth helped volunteers mitigate any physical and mental problems caused by negative life experiences. Standardized patients continued to complete their tasks with a positive attitude.

Postoperative Rehabilitation after Anterior Cruciate Ligament Reconstruction through Telerehabilitation with Artificial Intelligence Brace during COVID-19 Pandemic.

BACKGROUND: Due to the rapid spread of the coronavirus disease-19 (COVID-19), most of the patients expressed a reluctance to undergo postoperative rehabilitation at a rehabilitation clinic. Therefore, in this scenario it was necessary to reshape the crucial role of postoperative rehabilitation of these patients. We conducted a telerehabilitation program based on an artificial intelligence brace (AI brace) which can monitor the progress of rehabilitation through an app and an internet server. Our hypothesis was that home-based telerehabilitation might provide clinical outcomes comparable to face-to-face, hospital-based rehabilitation programs in terms of effectiveness. METHODS: A retrospective cohort study enrolled patients who received anterior cruciate ligament reconstruction (ACLR) between January and September 2020. Patients were divided into two groups: the tele-AI group received telerehabilitation with an AI brace while the FTF group had face-to-face, hospital-based rehabilitation. Clinical knee functional scores and Tegner Activity Scale (TAS) were assessed and analyzed until 12 months after the operation. RESULTS: The tele-AI group had higher IKDC scores at 3 months (p = 0.0443) and 6 months (p = 0.0052) after surgery and higher KOOS scores at 1 month (p = 0.0365) and 6 months (p = 0.0375) after surgery. However, no significant difference between the two groups was detected at the end of the follow-up. The tele-AI group had higher TAS than FTF group after 1 year. CONCLUSIONS: Telerehabilitation after ACLR seems to provide a superior short-term outcome compared to hospital-based rehabilitation during the COVID-19 pandemic.

Quality evaluation of ground improvement by deep cement mixing piles via ground-penetrating radar.

Deep cement mixing piles are a key technology for treating settlement distress of soft soil subgrade. However, it is very challenging to accurately evaluate the quality of pile construction due to the limitations of pile material, large number of piles and small pile spacing. Here, we propose the idea of transforming defect detection of piles into quality evaluation of ground improvement. Geological models of pile group reinforced subgrade are constructed and their ground-penetrating radar response characteristics are revealed. We have also developed ground-penetrating radar attribute analysis technology and established ground-penetrating radar technical system for evaluating the quality of ground improvement. We further prove that the ground-penetrating radar results integrating single-channel waveform, multi-channel section and attributes can effectively detect the defects and stratum structure after ground improvement. Our research results provide a rapid, efficient and economic technical solution for the quality evaluation of ground improvement in soft soil subgrade reinforcement engineering.

Anaerobic spondylodiscitis: a retrospective analysis.

BACKGROUND: This retrospective study analyzed the clinical characteristics and outcomes of patients with anaerobic spondylodiscitis. METHODS: From a total of 382 patients with infectious spondylodiscitis, nine patients (2.4%; two male and seven female with an average age of 67 years) with anaerobic spondylodiscitis between March 2003 and March 2017 were analyzed. RESULTS: Most of the patients (77.8%) initially presented with afebrile back pain. Hematogenous spread occurred in seven patients and postoperative infection in two patients. Bacteroid fragilis was the most common pathogen isolated from three patients. Atypical radiographic characteristics, including a vertebral fracture with the preservation of disk height or coexisting spondylolytic spondylolisthesis, occurred in four patients with hematogenous anaerobic spondylodiscitis. The eradication rate of anaerobic infection was significantly higher in the patients with hematogenous infection than in those with postoperative infection (100% vs. 0%, p = 0.0476). Anaerobic spondylodiscitis accounted for 2.4% of cases of infectious spondylodiscitis and predominantly affected the female patients. CONCLUSIONS: Diagnostic delay may occur because of atypical spinal radiographs if the patient reports only back pain but no fever. Anaerobic infection following elective spinal instrumentation has a higher recurrence rate.

Genetic relatedness among azole-resistant Candida tropicalis clinical strains in Taiwan from 2014 to 2018.

To monitor trends in the distribution of yeast species and the susceptibilities of these species to commonly prescribed antifungal drugs, we conduct the Taiwan Surveillance of Antimicrobial Resistance of Yeasts (TSARY) every 4 years. We found that 25 of 294 Candida tropicalis isolates from TSARY 2014 and 31 of 314 C. tropicalis isolates from TSARY 2018 were resistant to fluconazole. We determined the genetic relatedness among fluconazole-resistant C. tropicalis isolates by multilocus sequence typing (MLST). Among 174 C. tropicalis isolates, including all 56 fluconazole-resistant, all 26 susceptible-dose dependent and 92 selected fluconazole-susceptible isolates, 59 diploid sequence types (DSTs) were identified. We found that 22 of the 25 fluconazole-resistant C. tropicalis from TSARY 2014 and 29 of the 31 fluconazole-resistant C. tropicalis from TSARY 2018 were genetically related and belonged to the same cluster (clade 4). A combination of mutation and overexpression of ERG11, encoding the target of azole drugs, was the major mechanism contributing to drug resistance. Approximately two-thirds of reviewed patients infected or colonised by fluconazole-resistant C. tropicalis were azole-naïve. Furthermore, there was no evidence of patient-to-patient transmission. Because the clade 4 fluconazole-resistant C. tropicalis strain persists in Taiwan, it is important to identify the source of azole-resistant C. tropicalis to prevent the spread of this resistant strain.

Joint protection strategies for Saccharomyces boulardii: exogenous encapsulation and endogenous biofilm structure.

Biofilms are heterogeneous structures composed of microorganisms and the surrounding extracellular polymeric substances (EPS) that protect the microbial cells from harsh environments. Saccharomyces boulardii is the first yeast classified as a probiotic strain with unique properties. However, tolerance of S. boulardii biofilms to harsh environments especially during production and in the gastrointestine remains unknown. In this study, S. boulardii cells were encapsulated in alginate microcapsules and subsequently cultured to form biofilms, and their survival and tolerance were evaluated. Microencapsulation provided S. boulardii a confined space that enhanced biofilm formation. The thick alginate shell and the mature biofilm improved the ability of S. boulardii to survive under harsh conditions. The exogenous encapsulation and the endogenous biofilm structure together enhanced the gastrointestinal tolerance and thermotolerance of S. boulardii. Besides, as the alginate shell became thinner with an increase in the subsequent culture duration, the EPS of S. boulardii biofilms exerted an important protective effect in resisting high temperatures. The encapsulated biofilm of S. boulardii after 24-h culture exhibited 60 × higher thermotolerance at 60 °C (10 min), while those after 6-h and 24-h culture showed 1000 × to 550,000 × higher thermotolerance at 120 °C (1 min) compared with the planktonic cells without encapsulation. The present study's findings suggest that a combination of encapsulation and biofilm mode efficiently enhanced gastrointestinal tolerance and thermotolerance of S. boulardii. KEY POINTS: • Encapsulated S. boulardii in biofilm mode showed enhanced tolerance. • Exogenous shell and endogenous biofilm provided dual protection to S. boulardii.

[Sources Apportionment of Oxygenated Volatile Organic Compounds (OVOCs) in a Typical Southwestern Region in China During Summer].

Oxygenated volatile organic compounds (OVOCs) are important intermediates in the troposphere and the most important sources of ozone. Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) was used to measure VOCs in the Chengdu Plain, Southwestern China. The diurnal variations, photochemical reactivity, O3 formation potential, and sources were also investigated. The mixing ratios of ten kinds of VOCs (acetaldehyde, acetone, isoprene, Methyl ethyl ketone, Methyl vinyl ketone and Methacrolein, benzene, toluene, styrene, C8 aromatics, and C9 aromatics) were (10.97±4.69)×10-9. The concentrations of OVOCs, aromatic hydrocarbons, and biogenic VOCs were (8.54±3.44)×10-9, (1.53±0.93)×10-9, and (0.90±0.32)×10-9, respectively. Isoprene, acetaldehyde, and m-xylene were the top three photochemically active species with the greatest O3 formation potentials. The dominant three OVOCs species (acetaldehyde, acetone, and MEK) were mainly derived from local biogenic sources and anthropogenic secondary sources, and acetone had a strong regional background level, indicating that pollution in this area is significantly affected by regional transmission. This study deepens the understanding of regional O3 formation mechanisms in southwest China and provides a basis for the scientifically informed control of O3 pollution.

Late complication of cervical disc arthroplasty: heterotopic ossification causing myelopathy after 10 years. Illustrative case.

BACKGROUND: Heterotopic ossification (HO) is a well-documented complication of cervical disc arthroplasty (CDA), although it rarely causes adverse clinical effects. Despite high-grade HO possibly limiting segmental mobility, it is reportedly seldom associated with symptoms. OBSERVATIONS: The authors report a case of a 46-year-old male patient who underwent hybrid CDA and anterior cervical discectomy and fusion for 3-level cervical disc herniation that caused myeloradiculopathy. The surgery was successful; the patient experienced nearly complete recovery postoperatively. The follow-up images, including computed tomography and magnetic resonance imaging scans, showed satisfactory decompression at the indexed levels without residual osteophytes or ossification of the posterior longitudinal ligament. However, 10 years later, the patient presented with symptomatic compressive myelopathy caused by severe HO that prompted a secondary surgery. LESSONS: Although it is generally reported in the literature that HO is clinically innocuous, in this patient, it gradually and progressively developed and caused myelopathy, requiring a secondary surgery. Symptomatic HO can be expected over time, and patients with a high risk of HO deserve long-term follow-up after CDA. Further investigations are warranted to corroborate these risk factors, including multilevel calcified disc herniation, severe spondylosis, and suboptimal placement of the device during primary CDA surgery.

Novel, safe, and easy spinal osteotomy for regional kyphotic deformities.

OBJECTIVE: This study aimed to assess the efficacy and safety of a newly developed transpedicular, anterior open-wedge osteotomy procedure with lamina preservation to correct sagittal imbalance in regional kyphotic deformities following compression fractures. METHODS: All seven patients [four females and three males; mean (range) age, 67 (56-78) years] included in this study underwent surgery between May 2005 and May 2016 for symptomatic, rigid kyphosis secondary to compression fractures. Transpedicular, anterior open-wedge osteotomy with lamina preservation was performed in all patients using an osteotome to create a transverse fracture in the vertebral body through bilateral pedicles and an anterior open-wedge space filled with compacted bone graft to correct kyphosis. Pre- and post-operative kyphotic Cobb angles were evaluated, and the volume of intra-operative blood loss was measured. RESULTS: The pre- and post-operative kyphotic Cobb angle was 35.3° and 17.7°, respectively (p<0.01); mean angle correction was 17.6° (p<0.05). No patient developed any complication with neurologic injury. Mean blood loss was 771 mL. Callus formation viewed on plain film was evident in all patients and was accompanied by decreased thoracolumbar back pain. CONCLUSION: Transpedicular, anterior open-wedge osteotomy with lamina preservation is an easy and safe spinal osteotomy procedure for the correction of regional, fixed kyphotic deformities. LEVEL OF EVIDENCE: Level IV, Therapeutic study.

Ipsilateral femoral neck and shaft fractures fixation with proximal femoral nail antirotation II (PFNA II): technical note and cases series.

BACKGROUND: Combined ipsilateral femoral neck and shaft fractures are an uncommon type of fractures. A number of different implant options are available for the management of this injury. Two-device procedures were suggested because of the higher rate of malunion by single-device treatment. However, surgical treatment using a cephalomedullary nail is still an alternative option that provides better mechanical advantage and minimal invasion. This study details the technique of treating these pattern fractures with proximal femoral nail anti-rotation II (PFNA-II) to achieve an acceptable reduction in both fracture sites. METHODS: Ten cases of ipsilateral femoral neck and shaft fractures under reduction by PFNA II were included and reviewed. A saw-bone model was also utilized to perform the detailed technique of reduction and fixation of PFNA II. RESULTS: Under the special technique by using the PFNA II, all ten cases achieved optimal reduction and alignment of both fracture sites in intra-operative fluoroscopy. There was no intra-operative complication noted. After 6 months of follow-up, radiography revealed proper alignment and well union of the fractures. CONCLUSIONS: Fixation of ipsilateral femoral neck and shaft fractures with a single construct provides advantages of good biomechanical function, minimal invasion, reduced blood loss, and less operation time when comparing to two-device fixation. Thus, if acceptable reduction could be achieved, fixation by one PFNA II was a good alternative choice for this injury pattern.

A canonical correlation analysis based method for contamination event detection in water sources.

In this study, a general framework integrating a data-driven estimation model is employed for contamination event detection in water sources. Sequential canonical correlation coefficients are updated in the model using multivariate water quality time series. The proposed method utilizes canonical correlation analysis for studying the interplay between two sets of water quality parameters. The model is assessed by precision, recall and F-measure. The proposed method is tested using data from a laboratory contaminant injection experiment. The proposed method could detect a contamination event 1 minute after the introduction of 1.600 mg l(-1) acrylamide solution. With optimized parameter values, the proposed method can correctly detect 97.50% of all contamination events with no false alarms. The robustness of the proposed method can be explained using the Bauer-Fike theorem.

Why conventional detection methods fail in identifying the existence of contamination events.

Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading.

Performance evaluation for three pollution detection methods using data from a real contamination accident.

Early warning systems have been widely deployed to safeguard water security. Many contamination detection methods have been developed and evaluated in the past decades. Although encouraging detection performance has been obtained and reported, these evaluations mainly used artificial or laboratory data. The evaluation of detection performance with data from real contamination accidents has rarely been conducted. Implementation of contamination event methods without full assessment using field data might lead to failure of an early warning system. In this paper, the detection performance of three contamination detection methods, a Pearson correlation Euclidean distance (PE) based detection method, a multivariate Euclidean distance (MED) method and a linear prediction filter (LPF) method, was evaluated using data from a real contamination accident. Results improve understanding of the implementation of detection methods to field situations and show that all methods are prone to yielding worse detection performance when applied to data from a real contamination accident. They also revealed that the Pearson correlation Euclidean distance based method is more capable of differentiating between equipment noise and presence of contamination and has greater potential to be used in real field situations than the MED and LPF methods.

Establishment and Validation of SSCLIP Scoring System to Estimate Survival in Hepatocellular Carcinoma Patients Who Received Curative Liver Resection.

BACKGROUND AND AIMS: There is no prognostic model that is reliable and practical for patients who have received curative liver resection (CLR) for hepatocellular carcinoma (HCC). This study aimed to establish and validate a Surgery-Specific Cancer of the Liver Italian Program (SSCLIP) scoring system for those patients. METHODS: 668 eligible patients who underwent CLR for HCC from five separate tertiary hospitals were selected. The SSCLIP was constructed from a training cohort by adding independent predictors that were identified by Cox proportional hazards regression analyses to the original Cancer of the Liver Italian Program (CLIP). The prognostic performance of the SSCLIP at 12 and 36-months was compared with data from existing models. The patient survival distributions at different risk levels of the SSCLIP were also assessed. RESULTS: Four independent predictors were added to construct the SSCLIP, including age (HR = 1.075, 95%CI: 1.019-1.135, P = 0.009), albumin (HR = 0.804, 95%CI: 0.681-0.950, P = 0.011), prothrombin time activity (HR = 0.856, 95%CI: 0.751-0.975, P = 0.020) and microvascular invasion (HR = 19.852, 95%CI: 2.203-178.917, P = 0.008). In both training and validation cohorts, 12-month and 36-month prognostic performance of the SSCLIP were significantly better than those of the original CLIP, model of end-stage liver disease-based CLIP, Okuda and Child-Turcotte-Pugh score (all P < 0.05). The stratification of risk levels of the SSCLIP showed an enhanced ability to differentiate patients with different outcomes. CONCLUSIONS: A novel SSCLIP to predict survival of HCC patients who received CLR based on objective parameters may provide a refined, useful prognosis algorithm.

A multivariate based event detection method and performance comparison with two baseline methods.

Early warning systems have been widely deployed to protect water systems from accidental and intentional contamination events. Conventional detection algorithms are often criticized for having high false positive rates and low true positive rates. This mainly stems from the inability of these methods to determine whether variation in sensor measurements is caused by equipment noise or the presence of contamination. This paper presents a new detection method that identifies the existence of contamination by comparing Euclidean distances of correlation indicators, which are derived from the correlation coefficients of multiple water quality sensors. The performance of the proposed method was evaluated using data from a contaminant injection experiment and compared with two baseline detection methods. The results show that the proposed method can differentiate between fluctuations caused by equipment noise and those due to the presence of contamination. It yielded higher possibility of detection and a lower false alarm rate than the two baseline methods. With optimized parameter values, the proposed method can correctly detect 95% of all contamination events with a 2% false alarm rate.

A real time method of contaminant classification using conventional water quality sensors.

Early warning systems are often used to detect deliberate and accidental contamination events in a water source. After contamination detection, it is important to classify the type of contaminant quickly to provide support for implementation of remediation attempts. Conventional methods commonly rely on laboratory-based analysis or qualitative geometry analysis, which require long analysis time or suffer low true positive rate. This paper proposes a real time contaminant classification method, which discriminates contaminants based on quantitative analysis. The proposed method utilizes the Mahalanobis distance of feature vectors to classify the type of contaminant. The performance and robustness of the proposed method were evaluated using data from contaminant injection experiments and through an uncertainty analysis. An advantage of the proposed method is that it can classify the type of contaminant in minutes with no significant compromise on true positive rate. This will facilitate fast remediation response to contamination events in a water system.

Contaminant classification using cosine distances based on multiple conventional sensors.

Emergent contamination events have a significant impact on water systems. After contamination detection, it is important to classify the type of contaminant quickly to provide support for remediation attempts. Conventional methods generally either rely on laboratory-based analysis, which requires a long analysis time, or on multivariable-based geometry analysis and sequence analysis, which is prone to being affected by the contaminant concentration. This paper proposes a new contaminant classification method, which discriminates contaminants in a real time manner independent of the contaminant concentration. The proposed method quantifies the similarities or dissimilarities between sensors' responses to different types of contaminants. The performance of the proposed method was evaluated using data from contaminant injection experiments in a laboratory and compared with a Euclidean distance-based method. The robustness of the proposed method was evaluated using an uncertainty analysis. The results show that the proposed method performed better in identifying the type of contaminant than the Euclidean distance based method and that it could classify the type of contaminant in minutes without significantly compromising the correct classification rate (CCR).

A method of detecting contamination events using multiple conventional water quality sensors.

Early warning systems are often used for detecting contamination accidents. Traditional event detection methods suffer from high false negative and false positive errors. This paper proposes a detection method using multiple conventional water quality sensors and introduces a method to determine the values of parameters, which was configured as a multiple optimization problem and solved using a non-dominated sorting genetic algorithm (NSGA-II). The capability of the proposed method to detect contamination events caused by cadmium nitrate is demonstrated in this paper. The performance of the proposed method to detect events caused by different concentrations was also investigated. Results show that, after calibration, the proposed method can detect a contamination event 1 min after addition of cadmium nitrate at the concentration of 0.008 mg/l and has low false negative and positive rates.

Real-time human movement retrieval and assessment with Kinect sensor.

The difficulty of vision-based posture estimation is greatly decreased with the aid of commercial depth camera, such as Microsoft Kinect. However, there is still much to do to bridge the results of human posture estimation and the understanding of human movements. Human movement assessment is an important technique for exercise learning in the field of healthcare. In this paper, we propose an action tutor system which enables the user to interactively retrieve a learning exemplar of the target action movement and to immediately acquire motion instructions while learning it in front of the Kinect. The proposed system is composed of two stages. In the retrieval stage, nonlinear time warping algorithms are designed to retrieve video segments similar to the query movement roughly performed by the user. In the learning stage, the user learns according to the selected video exemplar, and the motion assessment including both static and dynamic differences is presented to the user in a more effective and organized way, helping him/her to perform the action movement correctly. The experiments are conducted on the videos of ten action types, and the results show that the proposed human action descriptor is representative for action video retrieval and the tutor system can effectively help the user while learning action movements.