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Abstract Background To analyze multiple imaging modalities in patients with Bietti crystalline dystrophy (BCD) and to investigate which factors from these modalities are associated with best corrected visual acuity (BCVA). Methods In this retrospective study, 40 eyes from 22 patients with BCD were included and were separated into group 1 (BCVA ≤20/200) and group 2 (BCVA > 20/200). Data including BCVA and characteristic findings from near-infrared reflectance (NIR) imaging, fundus autofluorescence (FAF), and spectral domain-optic coherence tomography (SD-OCT) were analyzed and compared. The outcome measures of multimodal imaging were evaluated for correlation with BCVA. Results NIR is a good diagnostic tool for detecting either crystalline or sclerotic vessels in BCD. Patients in group 1 tended to have a thinner choroid (P = 0.047) with ellipsoid zone (EZ) disruption (P = 0.011). Calculation of the area under the curve indicated that EZ disruption detected on SD-OCT could be a good predictor of legal blindness in BCD. Conclusion For the diagnosis of BCD, NIR could be a good diagnostic tool. Of the studied imaging modalities, we found that EZ disruption at the fovea were strongly associated with legal blindness, which could be easily assessed by SD-OCT.

Abstract Background To evaluate the feasibility of a surgical technique using a sub-perfluoro-n-octane (PFO) injection of ocular viscoelastic device (OVD) to stabilize inverted internal limiting membrane (ILM) flap for the treatment of macular hole retinal detachment (MHRD). Methods This study was a retrospective, consecutive, interventional case series. Patients who underwent MHRD surgery with sub-PFO injection of OVD to stabilize inverted ILM flap onto the macular hole (MH) were reviewed. The color fundus and optical coherence tomography (OCT) images were collected and evaluated. The best-corrected visual acuity (BCVA) before and after surgery were compared as the functional outcome. Results The study included 8 eyes of 8 consecutive patients (mean age: 61.8 ± 7.1 years; mean follow-up period: 9.0 ± 2.5 months). All eyes (100%) achieved successful MH closure; 7 eyes (87.5%) demonstrated complete retinal reattachment, and 1 eye (12.5%) had minimal residual subretinal fluid parafoveally. Of the 8 patients, 7 patients (87.5%) had achieved improvement in BCVA after the primary surgery, whereas 1 eye remained stable. The average BCVA before and after the surgery at the last visit improved from 20/843 (1.63 ± 0.48 logMAR) to 20/200 (1.00 ± 0.39 logMAR) (P = 0.016). Anatomically, near-normal foveal contour was noted in five (62.5%) eyes at the final follow-up. Conclusions The use of sub-PFO injection of OVD in MHRD surgery could stabilize inverted ILM flaps, achieve good anatomical results and improve postoperative BCVA.

Abstract Background To evaluate the surgical technique using autologous retinal graft (ARG) and autologous blood clot (ABC) for the management of refractory macular holes (MHs). Methods This study was a retrospective, consecutive, interventional case series. Six eyes of 6 patients who underwent vitrectomy combined with ARG and ABC for the treatment of refractory MH were reviewed. Visual and anatomic outcomes were evaluated. Results The mean age was 59.0 ± 9.9 years. All cases had multiple vitreoretinal procedures including vitrectomy and gas fluid exchange before patient presentation. The average numbers of vitrectomies were 2.3 ± 0.5, and those of gas fluid exchange were 3 ± 1.7. Closure of the macular hole was achieved in four (66.7%) cases at last follow-up. The mean follow-up time was 25.2 ± 15.6 months. The averaged BCVA before and after 12 months of the surgery improved from 20/591 to 20/244. Conclusions This surgical technique using ARG and ABC provide an option for the treatment of refractory MHs.

We report a case with multiple recurrences of retinal detachment (RD) with severe proliferative vitreoretinopathy in a 12-year-old child who underwent vitrectomy using a heavy liquid perfluoro-n-octane (PFO) as a short-term postoperative tamponade. He had an encircling band and three vitrectomies with gas, followed by silicone oil tamponade for retinal redetachment prior to the use of PFO as a short-term tamponade. Short-term PFO tamponade was used in which inferior retinal reattachment was considered to be difficult with conventional gas or silicone oil tamponade, especially in regard to proper postoperative posturing. The PFO was left in the eye for 1 week, and the retina remained reattached after removal of the PFO which was replaced with silicone oil tamponade in this case. PFO appears feasible and tolerable as a short-term postoperative tamponade in the management of complex pediatric RD.

Abstract Background To present a case of conjunctival growth on the amniotic membrane and subsequent pathology revealing conjunctival squamous metaplasia in a patient with Stevens-Johnson syndrome. Case presentation A 21-year-old female presented with painful, blurred vision in both eyes for two weeks. She was diagnosed with Stevens-Johnson syndrome 5 weeks before. Due to bilateral corneal epithelial defects, ProKera®, an amniotic membrane corneal bandage with a polycarbonate ring, was placed in both eyes. However, three weeks later, a slit-lamp examination revealed vascularized tissue growth from the palpebral conjunctiva to the amniotic membrane, along with symblepharon formation in the left eye. The patient underwent conjunctival biopsy, amniotic membrane removal, and symblepharon release. Pathology report showed the growth of squamous epithelium on the acellular amniotic membrane. Immunohistochemistry further supported the diagnosis, revealing squamous markers through p40 staining and highlighting the presence of the amniotic membrane using trichrome stain. Three months later, the patient’s visual acuity had improved to 20/25 and no symblepharon was noted. Conclusions This is the first case of conjunctival squamous metaplasia on amniotic membrane associated with Stevens-Johnson syndrome. Our case indicates that, despite the anti-inflammatory properties of amniotic membrane, conjunctival squamous metaplasia may arise after amniotic membrane grafting due to intense inflammation in Stevens-Johnson syndrome. Clinicians should conduct regular monitoring before amniotic membrane dissolution to preclude the development of conjunctival squamous metaplasia on the membrane and potential invasion into the cornea.

Abstract Hepatocellular carcinoma (HCC) is the primary malignant tumor of the liver. c-Myc is one of the most common oncogenes in clinical settings, and amplified levels of c-Myc are frequently found in HCC. Histone deacetylase inhibitors (HDACi), such as Trichostatin A (TSA), hold enormous promise for the treatment of HCC. However, the potential and mechanism of TSA in the treatment of c-Myc-induced HCC are unclear. In this study, we investigated the effects of TSA treatment on a c-Myc-induced HCC model in mice. TSA treatment delayed the development of HCC, and liver function indicators such as ALT, AST, liver weight ratio, and spleen weight ratio demonstrated the effectiveness of TSA treatment. Oil red staining further demonstrated that TSA attenuated lipid accumulation in the HCC tissues of mice. Through mRNA sequencing, we identified that TSA mainly affected cell cycle and fatty acid degradation genes, with alcohol dehydrogenase 4 (ADH4) potentially being the core molecular downstream target. QPCR, immunohistochemistry, and western blot analysis revealed that ADH4 expression was repressed by c-Myc and restored after TSA treatment both in vitro and in vivo. Furthermore, we observed that the levels of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration increased after c-Myc transfection in liver cells but decreased after TSA intervention. The levels of phosphorylated protein kinase B (p-AKT) and p-mTOR were identified as targets regulated by TSA, and they governed the ADH4 expression and the downstream regulation of total NAD+ and NADH, NAD+, NAD+/NADH, and ATP concentration. Overall, our study suggests that TSA has a therapeutic effect on c-Myc-induced HCC through the AKT-mTOR-ADH4 pathway. These findings provide valuable insights into the potential treatment of HCC using TSA and shed light on the underlying molecular mechanisms involved.

Abstract Background Extreme precipitation events often cause sudden drops in salinity, leading to disease outbreaks in shrimp aquaculture. Evidence suggests that environmental stress increases animal host susceptibility to pathogens. However, the mechanisms of how low salinity stress induces disease susceptibility remain poorly understood. Methods We investigated the acute response of shrimp gut microbiota exposed to pathogens under low salinity stress. For comparison, shrimp were exposed to Vibrio infection under two salinity conditions: optimal salinity (Control group) and low salinity stress (Stress group). High throughput 16S rRNA sequencing and real-time PCR were employed to characterize the shrimp gut microbiota and quantify the severity level of Vibrio infection. Results The results showed that low salinity stress increased Vibrio infection levels, reduced gut microbiota species richness, and perturbed microbial functions in the shrimp gut, leading to significant changes in lipopolysaccharide biosynthesis that promoted the growth of pathogens. Gut microbiota of the bacterial genera Candidatus Bacilliplasma, Cellvibrio, and Photobacterium were identified as biomarkers of the Stress group. The functions of the gut microbiota in the Stress group were primarily associated with cellular processes and the metabolism of lipid-related compounds. Conclusions Our findings reveal how environmental stress, particularly low salinity, increases shrimp susceptibility to Vibrio infection by affecting the gut microbiota. This highlights the importance of avoiding low salinity stress and promoting gut microbiota resilience to maintain the health of shrimp.

Abstract Objective Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data sets. Methods We conducted our research using a data set consisting of 1656 patients, representing a diverse demographic, from the sleep center of China Medical University Hospital. To detect apnea ECG segments and extract apnea features, we utilized the EfficientNet and some of its layers, respectively. Furthermore, we compared various training and data preprocessing techniques to enhance the model’s prediction, such as setting class and sample weights or employing overlapping and regular slicing. Finally, we tested our approach against other literature on the Apnea-ECG database. Results Our research found that the EfficientNet model achieved the best apnea segment detection using overlapping slicing and sample-weight settings, with an AUC of 0.917 and an accuracy of 0.855. For patient screening with AHI > 30, we combined the trained model with XGBoost, leading to an AUC of 0.975 and an accuracy of 0.928. Additional tests using PhysioNet data showed that our model is comparable in performance to existing models regarding its ability to screen OSA levels. Conclusions Our suggested architecture, coupled with training and preprocessing techniques, showed admirable performance with a diverse demographic dataset, bringing us closer to practical implementation in OSA diagnosis. Trial registration The data for this study were collected retrospectively from the China Medical University Hospital in Taiwan with approval from the institutional review board CMUH109-REC3-018.

Study region: The southwestern coast of Taiwan. Study focus: By employing sea-level rise (SLR) projections from the Sixth Assessment Report, we assess the future high tide flooding (HTF) and the resulting inundation extents and evaluate the impacts on populations and economic losses. New hydrological insights for the region: Under the low-emissions scenario, SLR-induced minor HTF days, i.e., 0.55 m above the mean higher high water (MHHW) are projected to exceed 300 annually by 2100; moderate HTF (0.85 m above the MHHW) events are expected to occur daily in the high-emissions scenario by 2090; major HTF (1.2 m above the MHHW) events were projected to occur in 2070, regardless of the emission scenario considered; regarding the extent of inundation, the projected HTF events would lead to a flooded area ranging from 30 to 600 km2. The impact on the present population ranged from 41,000 to 490,000 individuals. The upper limit of total economic losses based on current land use resulting from HTF was anticipated to range from 3.25 million US dollars to 35.31 million US dollars across the low-, medium-, and high-emission scenarios. The at-risk population decreased from 520,000 in 2008–490,000 in 2022, representing a decline of 5.8 % over 15 years in this coastal region.

Abstract Automated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice.

In medical and healthcare application scenarios, data integrity and user privacy are often concerned the most. A sanitizable signature scheme is a common adopted approach since it admits an authorized person to sanitize partial sensitive information of signed messages while keeping the correctness of preserved message and signature pairs. A certificateless sanitizable signature scheme further enjoys the merits of certificateless public key systems. That is, it is unnecessary to maintain the public key certificates in traditional cryptosystems or deal with the key escrow problem in identity-based systems. However, the functionality of batch verification for retained message-signature pairs and the revocation mechanism are still lack in previous works. To resolve these issues, the authors propose a revocable certificateless sanitizable signature scheme with batch verification in this paper. The revocation mechanism is fulfilled by combining user’s private key with an updatable time key. Hence, a revoked user is unable to request the renewed time key. We also provide a formal proof that our proposed system satisfies the security requirement of existential unforgeability under adaptive chosen-message attacks (EUF-CMA) in the random oracle model. In comparison to related variants, our system demonstrates superior functionality and computational efficiency.

Understanding the feeding behavior of Portunidae crabs with different baits can improve bait selection and is crucial for improving the effectiveness of crab fishing gear. This study, conducted in indoor experimental tanks, used trajectory tracking software and two types of natural baits (mackerel (Scomber australasicus) and squid (Uroteuthis chinensis)) to understand the behavior of Portunus sanguinolentus and Charybdis natator. Spatial distribution results showed that P. sanguinolentus was frequently present in the starting area (S1) and bait area (S3) in the control and treatment groups. However, C. natator was frequently present and concentrated in the S1 area compared to the middle areas S2 and S3, and only in the mackerel treatments were they observed to move to the S3 areas. The spatial distribution results indicate that P. sanguinolentus shows a stronger willingness to explore its surroundings, while C. natator is generally in a stationary, wait-and-see state. The swimming speeds of P. sanguinolentus and C. natator showed different trends. P. sanguinolentus showed continuous movement with no fixed speed when no bait was present in the control groups. However, when treated with mackerel and squid, the average swimming speed of P. sanguinolentus was faster (>5 cm/s) in the first 10 min and showed a more stable movement speed when searching for the baits. C. natator showed a stationary or low movement speed when no bait was present in the control groups. However, when C. natator perceived the presence of the baits in the treatment groups, their movement speed increased in the first 10 min. In addition, there was no significant difference between male and female crabs of P. sanguinolentus and C. natator in movement speed in the control and treatment groups. Compared to C. natator, P. sanguinolentus might be more sensitive to natural baits, as shown by its movement from S1 to S3. The results indicate that the species of Portunidae crabs show different bait selections. Natural baits (mackerel and squid) are recommended for catching P. sanguinolentus in crab fisheries.

Vortex-induced vibration is a type of wind-induced vibration occurring frequently in large-span sea-crossing bridges under relatively low wind speeds, posing a threat to the structural fatigue performance and driving comfort. Identifying the instantaneous occurrence moments of vortex-induced vibration is a prerequisite for establishing a data-driven prediction model for vortex-induced vibration, and it is of great significance for the monitoring and early warning of vortex-induced vibration performance in bridges. To automatically detect the occurrence moments of vortex-induced vibration and establish a correlation model between vortex-induced vibration amplitude and environmental factors, this study proposes a fuzzy C-means clustering-based classification method. In order to detect the occurrence moments of vortex-induced vibration more finely, only short-term or even instantaneous structural vibration indicators were selected and transformed for distribution as clustering features. The entire detection process could be carried out unsupervised, reducing the manual cost of obtaining vortex-induced vibration information from massive monitoring data. Finally, actual vortex-induced vibration test data from a certain overseas bridge was utilized to verify the feasibility of this method. Based on the classification results, the correlation between vortex-induced vibration amplitude and environmental variables was determined, providing valuable guidance for predicting vortex-induced vibration amplitudes.

Abstract Large-artery atherosclerosis (LAA) is a leading cause of cerebrovascular disease. However, LAA diagnosis is costly and needs professional identification. Many metabolites have been identified as biomarkers of specific traits. However, there are inconsistent findings regarding suitable biomarkers for the prediction of LAA. In this study, we propose a new method integrates multiple machine learning algorithms and feature selection method to handle multidimensional data. Among the six machine learning models, logistic regression (LR) model exhibited the best prediction performance. The value of area under the receiver operating characteristic curve (AUC) was 0.92 when 62 features were incorporated in the external validation set for the LR model. In this model, LAA could be well predicted by clinical risk factors including body mass index, smoking, and medications for controlling diabetes, hypertension, and hyperlipidemia as well as metabolites involved in aminoacyl-tRNA biosynthesis and lipid metabolism. In addition, we found that 27 features were present among the five adopted models that could provide good results. If these 27 features were used in the LR model, an AUC value of 0.93 could be achieved. Our study has demonstrated the effectiveness of combining machine learning algorithms with recursive feature elimination and cross-validation methods for biomarker identification. Moreover, we have shown that using shared features can yield more reliable correlations than either model, which can be valuable for future identification of LAA.

Abstract Objective This study evaluated the association between serum albumin levels and preoperative deep vein thrombosis (DVT) in geriatric hip fractures. Methods Older adult patients with hip fractures were screened between January 2015 and September 2019. The demographic and clinical characteristics of the patients were collected. Multivariate binary logistic regression and generalized additive model were used to identify the linear and nonlinear association between albumin levels and preoperative DVT. Analyses were performed using EmpowerStats and the R software. Results A total of 1819 patients were included in this study. The average age was 79.37 ± 6.88 years. There were 550 males and 1269 females. The preoperative albumin was 38.19 ± 4.07 g/L. There were 580 (31.89%) preoperative DVTs. Multivariate binary logistic regression showed that albumin level was associated with preoperative DVT (odds ratio [OR] = 0.94, 95% confidence interval [CI]: 0.91–0.97, P = 0.0002) after adjusting for confounding factors. The fully adjusted model showed a DVT risk decrease of 6% when albumin concentration increased by one g/L after controlling for confounding factors. In addition, the trend test and propensity score matching also showed a stable linear correlation between albumin level and preoperative DVT. Conclusion Serum albumin is associated with preoperative DVT in geriatric patients with hip fractures, and it could be considered a predictor for the risk of DVT. Registration ID ChiCTR2200057323.

In this paper, we obtain the multiplicity of homoclinic solutions for a class of asymptotically autonomous Hamiltonian systems with indefinite sign potentials. The concentration-compactness principle is applied to show the compactness. As a byproduct, we obtain the uniqueness of the positive ground state solution for a class of autonomous Hamiltonian systems and the best constant for Sobolev inequality which are of independent interests.

This study detailed the course design principles and implementation of project-based learning (PBL) in a technology-themed graduate-level online course. Students were trained to develop knowledge and skills in instructional leadership, such as the capability to design, deliver, and evaluate educational technology professional development programs. Pre- and post- survey data were collected to examine any change in students' knowledge and skills in instructional leadership by completing this course (N = 18). Quantitative findings revealed positive learning outcomes, and there was statistical significance regarding student improvement in knowledge and skills of instructional leadership, rendering the PBL approach viable.

Research on Digital Game-Based learning (DGBL) indicated it is effective in inducing student motivation and learning outcomes. Teachers as gatekeepers of technology should maneuver DGBL as pedagogical approach to engage students. In this convergent mixed method study, the researcher surveyed 116 pre-service, internship, and in-service teachers about their attitudes, self-efficacy, teaching philosophy, and perceived barriers toward the implementation of DGBL. Qualitative and quantitative data were collected and corroborated. Results showed majority of teachers gravitated toward Edutainment Games and Educational Applications based on pre-existing familiarity, comfortableness, and ease of use. Findings revealed misalignment between teachers’ endorsed teaching philosophy and their preferred game genre for use in instruction. The implication is that teachers during internship and post-induction should become educated in digital games and corresponding learning theory inherent in its design, so they can leverage teaching philosophy, knowledge and strategies to instruct in tandem with a pedagogically sound and thoughtfully chosen game.

Objectives This study aimed to conduct a thorough analysis of fluid retention-associated adverse events (AEs) associated with BCR::ABL inhibitors.Design A retrospective pharmacovigilance study.Setting Food and Drug Administration Adverse Event Reporting System (FAERS) database for BCR::ABL inhibitors was searched from 1 January 2004 to 30 September 2021.Main outcome measures Reporting OR (ROR) and 95% CI were used to detect the signals. ROR was calculated by dividing the odds of fluid retention event reporting for the target drug by the odds of fluid retention event reporting for all other drugs. The signal was considered positive if the lower limit of 95% CI of ROR was >1. The analysis was run only considering coupled fluid retention events/BCR::ABL inhibitors with at least three cases.Results A total of 97 823 reports were identified in FAERS. Imatinib had the most fluid retention signals, followed by dasatinib and nilotinib, while bosutinib and ponatinib had fewer signals. Periorbital oedema (ROR=24.931, 95% CI 22.404 to 27.743), chylothorax (ROR=161.427, 95% CI 125.835 to 207.085), nipple swelling (ROR=48.796, 95% CI 26.270 to 90.636), chylothorax (ROR=35.798, 95% CI 14.791 to 86.642) and gallbladder oedema (ROR=77.996, 95% CI 38.286 to 158.893) were the strongest signals detected for imatinib, dasatinib, nilotinib, bosutinib and ponatinib, respectively. Pleural effusion, pericardial effusion and pulmonary oedema were detected for all BCR::ABL inhibitors, with dasatinib having the highest RORs for pleural effusion (ROR=37.424, 95% CI 35.715 to 39.216), pericardial effusion (ROR=14.146, 95% CI 12.649 to 15.819) and pulmonary oedema (ROR=11.217, 95% CI 10.303 to 12.213). Patients aged ≥65 years using dasatinib, imatinib, nilotinib or bosutinib had higher RORs for pleural effusion, pericardial effusion and pulmonary oedema. Patients aged ≥65 years and females using imatinib had higher RORs for periorbital oedema, generalised oedema and face oedema.Conclusions This pharmacovigilance study serves as a clinical reminder to physicians to be more vigilant for fluid retention-associated AEs with BCR::ABL inhibitors.

Background/Aim: Gout, characterized by acute inflammatory symptoms and monosodium urate crystal deposits in joints, is prevalent among males and the elderly. Total knee arthroplasty (TKA) is a common treatment for knee osteoarthritis (OA), but its impact on the risk of developing gout is unclear. This study examined the risk of gout in patients undergoing TKA. Patients and Methods: Utilizing the TriNetX research network, a retrospective cohort study was conducted on OA patients without prior gout. The TKA cohort was compared to a non-TKA control group using propensity score matching to balance covariates. The primary outcome was the incidence of gout over a five-year follow-up period. Results: The study included 38,834 matched pairs of TKA and non-TKA patients. TKA patients had a 15.6% higher risk of developing gout (HR=1.156; 95%CI=1.042-1.284) compared to controls. Sensitivity analyses confirmed the increased risk across various models and follow-up durations. Conclusion: TKA is associated with a higher risk of developing gout, particularly in females and older adults. Clinicians should monitor and manage gout risk in TKA patients, emphasizing preventive measures and early intervention. Further research is needed to understand the underlying mechanisms and improve patient care post-TKA. [ABSTRACT FROM AUTHOR]

In this study, a polyvinylidene fluoride (PVDF)/graphene nanoplatelet (GNP) micro-nanocomposite membrane was fabricated through electrospinning technology and was employed in the fabrication of a fiber-reinforced polymer composite laminate. Some glass fibers were replaced with carbon fibers to serve as electrodes in the sensing layer, and the PVDF/GNP micro-nanocomposite membrane was embedded in the laminate to confer multifunctional piezoelectric self-sensing ability. The self-sensing composite laminate has both favorable mechanical properties and sensing ability. The effects of different concentrations of modified multiwalled carbon nanotubes (CNTs) and GNPs on the morphology of PVDF fibers and the β-phase content of the membrane were investigated. PVDF fibers containing 0.05% GNPs were the most stable and had the highest relative β-phase content; these fibers were embedded in glass fiber fabric to prepare the piezoelectric self-sensing composite laminate. To test the laminate’s practical application, four-point bending and low-velocity impact tests were performed. The results revealed that when damage occurred during bending, the piezoelectric response changed, confirming that the piezoelectric self-sensing composite laminate has preliminary sensing performance. The low-velocity impact experiment revealed the effect of impact energy on sensing performance.

Three typhoons, Meranti, Malakas, and Megi, occurred successively in eastern Taiwanese waters in September 2016, causing extreme waves (significant wave height > 10.0 m), and these events were selected to investigate the effect of model grid resolution and wave–wave interaction on simulating typhoon-driven waves. The WAVEWATCH III (WW3) model, with 0.50 deg, 0.25 deg, 0.20 deg, 0.10 deg, and 0.05 deg grid resolutions, and two reanalysis wind fields were adopted to simulate ocean waves during these three typhoons. The results indicated that the exertion of the Climate Forecast System version 2 (CFSv2) winds over the WW3 model with 0.10 deg grid resolution yielded optimum simulations of typhoon waves in a compromise between accuracy and elapsed time. In the present study, the WW3 model modeled nonlinear wave–wave interactions using discrete interaction approximation (DIA). The numerical experiments revealed that the underestimations of typhoon waves were significant when the WW3 model excluded nonlinear wave–wave interactions, especially when employing a higher grid resolution. This study also found that the WW3 model is superior to the Wind Wave Model III (WWM-III) using the CFSv2 winds because the WWM-III tended to overestimate the extreme waves in all three of these eastern Taiwan typhoon events that occurred in September 2016.

Recently, miRNAs have become a promising biomarker for disease diagnostics. miRNA-145 is closely related to strokes. The accuracy determination of miRNA-145 (miR-145) in stroke patients still remains challenging due to its heterogeneity and low abundance, as well as the complexity of the blood matrix. In this work, we developed a novel electrochemical miRNA-145 biosensor via subtly coupling the cascade strand displacement reaction (CSDR), exonuclease III (Exo III), and magnetic nanoparticles (MNPs). The developed electrochemical biosensor can quantitatively detect miRNA-145 ranging from 1 × 102 to 1 × 106 aM with a detection limit as low down as 100 aM. This biosensor also exhibits excellent specificity to distinguish similar miRNA sequences even with single-base differences. It has been successfully applied to distinguish healthy people from stroke patients. The results of this biosensor are consistent with the results of the reverse transcription quantitative polymerase chain reaction (RT-qPCR). The proposed electrochemical biosensor has great potential applications for biomedical research on and clinical diagnosis of strokes.

Infectious keratitis (IK) represents a major cause of corneal blindness. This study aims to investigate the demographics, risk factors, microbiological characteristics and antibiotic susceptibility patterns of IK in Taiwan over the past 15 years. A retrospective population-based study was conducted using the Chang Gung Research Database. Patients with IK were identified by diagnostic codes for corneal ulcer from 2004 to 2019. Of 7807 included subjects, 45.2% of patients had positive corneal cultures. The proportion of contact lens-related IK declined, while that of IK related to systemic diseases grew. The percentage of isolated gram-positive bacteria surpassed that of gram-negative bacteria in the 15-year period. The prevalence of Pseudomonas aeruginosa showed a decreasing trend (p = 0.004), whereas coagulase-negative Staphylococcus (CNS) and Propionibacterium species were increasingly detected (p < 0.001). Overall, the trend of antibiotic susceptibility of both gram-positive and gram-negative bacteria did not change throughout the study period. The susceptibility to the test antibiotics maintained over 90% in gram-negative isolates over 15 years. Vancomycin preserved 100% susceptibility to all gram-positive isolates. Since most tested antibiotics exhibited stable susceptibility over decades, this study reinforced that fluoroquinolones and fortified vancomycin continue to be good empiric therapies for treating bacterial keratitis in Taiwan.

Exosomal MicroRNA-21 (miRNA-21, miR-21) is significantly up-regulated in blood samples of patients with lung cancer. Exosomal-derived miR-21 can be used as a promising biomarker for the early diagnosis of lung cancer. This paper develops a fluorescent biosensor based on the combination of magnetic nanoparticles (MNPs), cascade strand displacement reaction (CSDR) and CRISPR/Cas12a to detect the exosomal miR-21 from lung cancer. The powerful separation performance of MNPs can eliminate the potential interference of matrix and reduce the background signal, which is very beneficial for the improvement of specificity and sensitivity. The CSDR can specifically transform one miR-21 into plenty of DNA which can specifically trigger the trans-cleavage nuclease activity of Cas12a, resulting in the cleavage of ssDNA bi-labeled with fluorescent and a quencher. Under the optimized experimental conditions, the developed fluorescence biosensor exhibited high sensitivity and specificity towards the determination of exosomal-derived miR-21 with a linear range from 10 to 1 × 105 fM and a low detection limit of about 0.89 fM. Most importantly, this method can be successfully applied to distinguish the exosomal miR-21 from the lung cancer patients and the healthy people.

Coronavirus disease-2019 (COVID-19) causes severe pneumonia and acute respiratory distress syndrome. According to the current consensus, immunosuppressants, such as dexamethasone and anti-interleukin-6 receptor monoclonal antibodies, are therapeutic medications in the early stages of infection. However, in critically ill patients, viral, fungal, and bacterial coinfection results in higher mortality. We conducted a single-center, retrospective analysis of 29 mechanically ventilated patients with artificial airways. Patients were adults with confirmed COVID-19 infection and severe pneumonia. Acute respiratory distress syndrome was diagnosed according to the Kigali modification of the Berlin definition. Six patients had invasive pulmonary aspergillosis coinfection based on elevated serum galactomannan levels and/or bronchoalveolar lavage fluid. We present two cases with brief histories and available clinical data. We also conducted a literature review to determine whether immunosuppressants, such as tocilizumab, increase infection risk or invasive aspergillosis in patients with COVID-19. There is no conclusive evidence to suggest that tocilizumab increases coinfection risk. However, further studies are needed to determine the optimal dose, between-dose interval, and timing of tocilizumab administration in patients with COVID-19.

Objectives: Doxorubicin is commonly used in the treatment of superficial bladder cancer, but more side effects and shorter intracellular retention time hamper its clinical application. Since lipo-doxorubicin (Lipodox) has the advantages of longer half-life and lower clearance rate than doxorubicin, it should improve the efficacy of tumor therapy and reduce the normal tissue toxicity of doxorubicin. Materials and Methods: In this study, we compared the cytotoxicity of Lipodox and doxorubicin in different treatment durations on bladder cancer cells by 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. Drug distribution was tracked under fluorescence microscopy. The metabolic rate after treatment was measured by serial flow cytometry. Finally, an in vivo orthotopic MBT-2 bladder tumor model was established for comparing the differences of therapeutic efficacy, including tumor weight and survival rate. Results: The 50% inhibitory concentration (IC50) of doxorubicin and Lipodox for MBT-2 cells was 0.62 μg/mL and 130 μg/mL, respectively, after 48 hours treatment. Lipo-dox presented higher cytotoxicity than doxorubicin at 6 hours (93% vs 73%) and 12 hours (93% vs 80%) treatment. After drug treatment, Lipodox fluorescence distribution was observed mostly in the cell membrane, lysosomes, and nuclei of tumor cells, while doxorubicin was concentrated in the nuclei. Initial fluorescence intensity of doxorubicin was 27.3 times that of Lipodox (p

Super Typhoons Maria (2018) and Lekima (2019) were adopted for this case study, although they only passed the northern offshore waters of Taiwan without making landfall. A direct modification technique was employed to create the atmospheric conditions for a wave-circulation model to hindcast large typhoon-driven waves. The radius of the modified scale (Rtrs) for a hybrid typhoon wind plays an important role in the significant wave height (SWH) simulations during the passage of typhoons. The maximum increment in peak SWH reached 3.0 m and 5.0 m in the deep ocean for Super Typhoons Maria (2018) and Lekima (2019), respectively if the Rtrs was increased from 4 × Rmax (radius of the maximum wind) to 7 × Rmax. The SWHs induced by the typhoon winds in the surf zone were more sensitive to different wave-breaking formulations used in the wave-circulation model. The maximum difference in peak SWH reached 2.5 m and 1.2 m for Super Typhoons Maria (2018) and Lekima (2019), respectively, when the wave-breaking formulations of BJ78 (proposed by Battjes and Janssen in 1978) and CT93 (proposed by Church and Thornton in 1993) were introduced to the wave-circulation model. The SWH simulations in the surf zone were insensitive to the wave-breaking criterion (γ) during the passage of typhoons. In shallow nearshore waters, the utilization of a constant γ for the wave-circulation model always produces peak SWHs that are smaller than those using γ based on local steepness or peak steepness.

Artificial intelligence (AI) has been expeditiously developing and carrying a pivotal role in education to help establish an effective educational environment. AI in Education (AIED) is impactful on the practices and environment of teaching and learning. This study investigated instructional technology faculty's perspectives about the role and utility of AI in education. Semi-structured interviews were administered to collect in-depth feedback about using AI in teaching, learning, and assessment. The four participants were college professors who taught in the instructional technology program at a large Midwestern university. Findings showed that AI does not receive enough attention from professors in general. Participants expressed strong desire to integrate AI throughout the educational environment, but maturation of integration will take time. The implication of this study is that integrating AI tools into educational settings can benefit both teachers and learners by utilizing them as intellectual assistants. [ABSTRACT FROM AUTHOR]

In this study, long-term wind fields during 1991–2010 from the Climate Forecast System Reanalysis (CFSR) were dynamically downscaled over Taiwan and its offshore islands at a 5 km horizontal resolution using the Weather Research and Forecasting (WRF) model. Simulations of the 10 m (above sea level) dynamically downscaled winds served as the atmospheric forcing for driving a fully coupled wave-circulation model. The sea states of the waters surrounding Taiwan during 1991–2010 were hindcasted to evaluate the offshore wave energy resources and optimal wave energy hotspots. This study reveals that the southeastern offshore waters of Taiwan and the Central Taiwan Strait exhibited the highest mean wave power density (WPD), exceeding 20 kW/m. The annual mean WPD, incidence of the hourly WPD greater than or equal to 4 kW/m, monthly variability index and coefficient of variation of the WPD indicated that the sea areas located between Green Island and Orchid Island (OH_1), southeast of Orchid Island (OH_2), south of the Hengchun Peninsula (OH_3), and north of the Penghu Islands (OH_4) were the optimal hotspots for deploying wave energy converters. The most energetic months were October for OH_1 and OH_2 and November for OH_3 and OH_4, while the wave power was weak from March to June for OH_1, OH_2 and OH_3 and in May for OH_4. The wave direction is prevailingly east-northeast for OH_1, OH_2 and OH_3 and nearly northeast for OH_4. These phenomena reveal that wave power in the waters offshore Taiwan is induced primarily by the northeast (winter) monsoon. The exploitable annual WPD was estimated to be 158.06, 182.89, 196.39 and 101.33 MWh/m for OH_1, OH_2, OH_3 and OH_4, respectively.

The sensitivity of storm wave simulations to storm tides and tidal currents was investigated using a high-resolution, unstructured-grid, coupled circulation-wave model (Semi-implicit Cross-scale Hydroscience Integrated System Model Wind Wave Model version III (SCHISM-WWM-III)) driven by two typhoon events (Typhoons Soudelor and Megi) impacting the northeastern coast of Taiwan. Hourly wind fields were acquired from a fifth-generation global atmospheric reanalysis (ERA5) and were used as meteorological conditions for the circulation-wave model after direct modification (MERA5). The large typhoon-induced waves derived from SCHISM-WWM-III were significantly improved with the MERA5 winds, and the peak wave height was increased by 1.0–2.0 m. A series of numerical experiments were conducted with SCHISM-WWM-II and MERA5 to explore the responses of typhoon wave simulations to tidal elevation and current. The results demonstrate that the simulated significant wave height, mean wave period and wave direction for a wave buoy in the outer region of the typhoon are more sensitive to the tidal current but less sensitive to the tidal elevation than those for a wave buoy moored in the inner region of the typhoon. This study suggests that the inclusion of the tidal current and elevation could be more important for typhoon wave modeling in sea areas with larger tidal ranges and higher tidal currents. Additionally, the suitable modification of the typhoon winds from a global atmospheric reanalysis is necessary for the accurate simulation of storm waves over the entire region of a typhoon.

Despite numerous studies on the effect of a cold weather disaster on fisheries in 2008, no operational systems have been developed to monitor the threat of such an event to mariculturists in the Penghu Islands (PHI) region of Taiwan. The present study employed a suitable aquaculture site selection map of the inner bay of the PHI to reduce aquaculture losses and mortality rates of cobia (Rachycentron canadum) during extreme events. Daily marine environmental data, including sea surface temperature (SST), chlorophyll-a concentration (chl-a), and wind speed in the winter, were collected. An extreme event was defined as a period of over 11 days in a month of strong winds (>6 m/s). Four parameters in the PHI inner bay, including SST, cold-water intrusion days, chl-a, and offshore distance to the PHI coastline, were used to evaluate suitable aquaculture sites for cobia culture. The results indicated that La Niña events could not be used as a factor to detect cold-water intrusion events and select suitable aquaculture sites in the PHI. The evaluated suitable aquaculture site selection map, obtained using an arithmetic mean model and a geometric mean model, revealed that the avoidance sites during extreme events were concentrated in the northern and northwestern PHI. Suitable areas were concentrated in the southeastern areas. We further suggested that commercial cobia aquaculture operations in the PHI inner bay could be moved to the suitable sites in southeastern PHI during extreme events.

The protection of water resources is of paramount importance to human beings’ practical lives. Monitoring and improving water quality nowadays has become an important topic. In this study, a novel Bayesian probabilistic neural network (BPNN) improved from ordinary Bayesian probability methods has been developed to quantitatively predict water quality parameters including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a. The proposed method, based on conventional Bayesian probability methods, involves feature engineering and deep neural networks. Additionally, it extracts significant information for each endmember from combinations of spectra by feature extraction, with spectral unmixing based on mathematical and statistical analysis, and calculates each of the water quality parameters. The experimental results show the great performance of the proposed model with all coefficient of determination R 2 over 0.9 greater than the values (0.6–0.8) from conventional methods, which are greater than ordinary Bayesian probability analysis. The mean percent of absolute error (MPAE) is taken into account as an important statistical criterion to evaluate model performance, and our results show that MPAE ranges from 4% (nitrogen) to 10% (COD). The root mean squared errors (RMSEs) of phosphorus, nitrogen, COD, BOD, and chlorophyll-a (Chla) are 0.03 mg/L, 0.28 mg/L, 3.28 mg/L, 0.49 mg/L, and 0.75 μg/L, respectively. In comparison with other deep learning methods, this study takes a relatively small amount of data as training data to train the proposed model and the proposed model is then tested on the same amount of testing data, achieving a greater performance. Thus, the proposed method is time-saving and more effective. This study proposes a more compatible and effective method to assist with decomposing combinations of hyperspectral signatures in order to calculate the content level of each water quality parameter. Moreover, the proposed method is practically applied to hyperspectral image data on board an unmanned aerial vehicle in order to monitor the water quality on a large scale and trace the location of pollution sources in the Maozhou River, Guangdong Province of China, obtaining well-explained and significant results.

Traditional teaching approaches in research methods courses demotivate students, hindering their ability to learn and apply research concepts in practical settings. Instructors who are devoted to employing active learning pedagogy in teaching research courses have observed favorable outcomes. However, a dearth of literature has focused on students' perceptions and evaluation of active learning pedagogy. This study explores how students perceive active learning approaches via in-person and writtenresponse interviews. Eighteen participants volunteered and self-selected one of the interview forms. In addition to exploring students' perspectives on active learning pedagogy, we conducted a comparison of those interviewing modes. Our analysis revealed that regardless of interview type, participants provided similar results. In-person interviews generated more information segments; however, the segments from written-response interviews provided more informative meaning. Combining all data, we developed three themes and 29 codes about students' perceptions of active learning pedagogy. We found that students valued self-exploration as well as interactive activities that promoted deep learning and knowledge transfer. Based on the results, we provide practical recommendations for how instructors can design active learning-based research courses to facilitate students in active and self-regulated learning. [ABSTRACT FROM AUTHOR]