BACKGROUND

Stroke is a leading cause of morbidity and mortality in the Philippines. Telestroke systems have been introduced to improve timely recognition and referral; however, their effectiveness depends on utilization at the community level.

OBJECTIVE

To assess stroke and telestroke knowledge, attitudes, practices, and barriers among barangay health workers (BHWs), and to determine factors associated with telestroke utilization.

METHODS

A cross-sectional study was conducted among 202 BHWs. Data were collected using a structured questionnaire assessing knowledge, attitudes, practices, and perceived barriers. Descriptive statistics were used to summarize responses. Associations between variables were analyzed using appropriate statistical tests, with significance set at p < 0.05.

RESULTS

Respondents had high stroke knowledge (75.5%, SD = 17.45) and telestroke knowledge (85.5%, SD = 18.82), as well as favorable attitudes (mean = 4.37). However, only 31.1% reported telestroke utilization. The most commonly reported barriers were lack of training (61.4%) and poor internet connectivity (15.8%). Telestroke familiarity was significantly associated with higher knowledge (p = 0.005) and more favorable attitudes (p = 0.001). Stroke-related training (p = 0.001) and years of experience (p = 0.001) were significantly associated with higher utilization.

CONCLUSION

Despite high knowledge and favorable attitudes, telestroke utilization among BHWs remains low. Training, familiarity, and infrastructure appear to play key roles in bridging the gap between knowledge and practice. Strengthening these factors may improve the effectiveness of community-based telestroke systems.

Human ; Occupational Groups ; Knowledge ; Attitude ; Stroke ; Technology

BACKGROUND AND OBJECTIVES

Telerehabilitation is the remote delivery of rehabilitation services using telecommunication technologies. Its local adoption was catalyzed by the COVID-19 pandemic, prompting the need to assess user acceptance. This study aimed to determine the acceptance of stroke telerehabilitation among patients, carers, and rehabilitation providers in the Department of Physical Medicine and Rehabilitation at St. Luke’s Medical Center – Global City and Quezon City.

METHODS

This descriptive cross-sectional study used purposive sampling to recruit 73 rehabilitation providers and 10 consumers. Data were collected using a self-administered survey based on the Technology Acceptance Model, covering perceived ease of use, usefulness, and behavioral intent. Descriptive and inferential statistics were used for analysis.

RESULTS

Most providers (94.4%) were familiar with telerehabilitation, while only half of the consumers were aware of it. Acceptance was moderate among providers (mean score: 35.75 ± 8.67) and high among consumers (mean score: 31.6 ± 7.52). Female providers were less likely to accept telerehabilitation (p=0.049). Consumers identified financial constraints and lack of a companion as key barriers, while providers cited internet issues and technology use. Both groups viewed telerehabilitation positively for teleconsultation, teletherapy, and telemonitoring. Smartphones were the preferred device; Viber and Facebook Messenger were the most commonly chosen platforms.

CONCLUSION

Stroke telerehabilitation was moderately to highly accepted by rehabilitation stakeholders in two tertiary private hospitals in Manila. Findings may guide institutional planning for telerehabilitation services. Training, infrastructure support, and awareness campaigns can help address implementation barriers.

Human ; Male ; Female ; Adult: 25-44 Yrs Old ; Middle Aged: 45-64 Yrs Old ; Remote Consultation ; Physical And Rehabilitation Medicine ; Tertiary Care Centers ; Telecommunications ; Telerehabilitation ; Cross-sectional Studies ; Technology ; Stroke ; Covid-19

BACKGROUND AND OBJECTIVES

Telerehabilitation is the remote delivery of rehabilitation services using telecommunication technologies. Its local adoption was catalyzed by the COVID-19 pandemic, prompting the need to assess user acceptance. This study aimed to determine the acceptance of stroke telerehabilitation among patients, carers, and rehabilitation providers in the Department of Physical Medicine and Rehabilitation at St. Luke’s Medical Center – Global City and Quezon City.

METHODS

This descriptive cross-sectional study used purposive sampling to recruit 73 rehabilitation providers and 10 consumers. Data were collected using a self-administered survey based on the Technology Acceptance Model, covering perceived ease of use, usefulness, and behavioral intent. Descriptive and inferential statistics were used for analysis.

RESULTS

Most providers (94.4%) were familiar with telerehabilitation, while only half of the consumers were aware of it. Acceptance was moderate among providers (mean score: 35.75 ± 8.67) and high among consumers (mean score: 31.6 ± 7.52). Female providers were less likely to accept telerehabilitation (p=0.049). Consumers identified financial constraints and lack of a companion as key barriers, while providers cited internet issues and technology use. Both groups viewed telerehabilitation positively for teleconsultation, teletherapy, and telemonitoring. Smartphones were the preferred device; Viber and Facebook Messenger were the most commonly chosen platforms.

CONCLUSION

Stroke telerehabilitation was moderately to highly accepted by rehabilitation stakeholders in two tertiary private hospitals in Manila. Findings may guide institutional planning for telerehabilitation services. Training, infrastructure support, and awareness campaigns can help address implementation barriers.

Human ; Male ; Female ; Adult: 25-44 Yrs Old ; Middle Aged: 45-64 Yrs Old ; Remote Consultation ; Physical And Rehabilitation Medicine ; Tertiary Care Centers ; Telecommunications ; Telerehabilitation ; Cross-sectional Studies ; Technology ; Stroke ; Covid-19

BACKGROUND

Occupational burnout is a growing concern in healthcare, which affects professionals across various disciplines. Radiographers working in non-traditional practice settings may face unique stressors that contribute to burnout, yet this population remains understudied, particularly in the Philippines.

OBJECTIVES

This study aimed to (1) assess and compare burnout levels among Filipino radiographers in non-traditional roles, (2) investigate the relationship between demographic variables and burnout, and (3) assess burnout severity by imaging role.

METHODS

A cross-sectional, quantitative survey design was employed. Participants (n = 188) completed an online survey including demographic questions and the Maslach Burnout Inventory (MBI). Data analysis was performed using SPSS 23. Non-parametric tests were used to assess relationships between demographic variables and MBI scores.

RESULTS

Significant differences in burnout scores were found across imaging roles (p = .000). Mobile imaging professionals reported the highest emotional exhaustion (M = 48.4, SD = 4.7) and depersonalization (M = 21.5, SD = 4.7), and the lowest personal accomplishment (M = 18.1, SD = 7.2). Forensic imaging professionals reported the lowest overall burnout (M = 58.9, SD = 13.8) and depersonalization (M = 7.7, SD = 4.3), and the highest personal accomplishment (M = 29.4, SD = 8.3). Sex differences were observed for depersonalization (p = .045), with males scoring higher. Participants with graduate degrees reported lower personal accomplishment (p = .036). Severe burnout was the dominant category, especially in mobile, military, and veterinary imaging.

CONCLUSION

Burnout levels vary significantly among Filipino radiographers in non-traditional roles, with mobile imaging professionals at particularly high risk. These findings highlight the need for targeted interventions to mitigate burnout and promote wellbeing in this population.

Human ; Burnout, Professional ; Technology, Radiologic ; Philippines ; Cross-sectional Studies

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

As a strategic emerging industry, biomanufacturing faces core challenges in achieving precise optimization and efficient scale-up of fermentation processes. This review focuses on two critical aspects of fermentation-real-time sensing and intelligent control-and systematically summarizes the advancements in online monitoring technologies, artificial intelligence (AI)-driven optimization strategies, and digital twin applications. First, online monitoring technologies, ranging from conventional parameters (e.g., temperature, pH, and dissolved oxygen) to advanced sensing systems (e.g., online viable cell sensors, spectroscopy, and exhaust gas analysis), provide a data foundation for real-time microbial metabolic state characterization. Second, conventional static control relying on expert experience is evolving toward AI-driven dynamic optimization. The integration of machine learning technologies (e.g., artificial neural networks and support vector machines) and genetic algorithms significantly enhances the regulation efficiency of feeding strategies and process parameters. Finally, digital twin technology, integrating real-time sensing data with multi-scale models (e.g., cellular metabolic kinetics and reactor hydrodynamics), offers a novel paradigm for lifecycle optimization and rational scale-up of fermentation. Future advancements in closed-loop control systems based on intelligent sensing and digital twin are expected to accelerate the industrialization of innovative achievements in synthetic biology and drive biomanufacturing toward higher efficiency, intelligence, and sustainability.
Artificial Intelligence ; Fermentation ; Bioreactors/microbiology* ; Neural Networks, Computer ; Algorithms ; Biotechnology/methods*

Echinocandin B (ECB) is a key precursor of the antifungal drug anidulafungin. It is a secondary metabolite of Aspergillus nidulans, and its titer in fermentation is significantly affected by the ECB synthesis pathway and cell morphology. In this study, the key genes related to the transcription activation, hydroxylation, and cell morphology during ECB biosynthesis were investigated to increase the fermentation titer of ECB and to change the cell morphology of Aspergillus nidulans to reduce the viscosity of the fermentation broth. The results indicated that after overexpression of ecdB and ecdK, the ECB titer increased by 25.8% and 23.7%, respectively, compared with that of the wild-type strain, reaching (2 030.5±99.2) mg/L and (1 996.4±151.4) mg/L. However, the deletion of fksA associated with cell wall synthesis resulted in damage to the cell wall, affecting strain growth and product synthesis. The engineered strain overexpressing ecdB was fermented in a 50-L bioreactor, in which the ECB titer reached 2 234.5 mg/L. The findings laid a research foundation for the subsequent metabolic engineering of this strain.
Fermentation ; Aspergillus nidulans/genetics* ; Echinocandins/genetics* ; Bioreactors/microbiology* ; Fungal Proteins/biosynthesis* ; Metabolic Engineering

Compared with conventional transdermal drug delivery systems, dissolving microneedles significantly enhance drug bioavailability by penetrating the stratum corneum barrier and achieving intradermal drug delivery. In order to improve the transdermal bioavailability of dexmedetomidine hydrochloride, in this study, a novel microneedle delivery system was developed for dexmedetomidine hydrochloride based on 3D printing combined with micro-molding. By systematically optimizing the microneedle geometrical parameters, array arrangement, and preparation process parameters, we determined the optimal ratio of drug-carrying matrix as 15% PVP (polyvinyl pyrrolidone) K90. The microneedles exhibited significant drug loading gradients, with mean content of (209.99±27.56) μg/patch, (405.31±30.31) μg/patch, and (621.61±34.43) μg/patch. They showed a regular pyramidal structure under SEM and handheld electron microscopy, and their mechanical strength allowed effective penetration into the stratum corneum. The surface contact angles were all < 90°, indicating excellent hydrophilicity. The microneedles dissolved completely within 10 min after skin insertion, achieving a cumulative release rate of 90% (Higuchi model, r=0.996) during 2 hours of in vitro transdermal permeation. The cytotoxicity test and hemolysis test verified good biocompatibility. Pharmacodynamic evaluation showed that the microneedle group demonstrated pain-relieving effect within 15 min, with the pain threshold at the time point of 60 min being 3 times that in the transdermal cream group. The microneedle system developed in this study not only offers an efficient drug delivery option for patients but also establishes an innovative platform for rapid percutaneous delivery of hydrophilic drugs, demonstrating significant potential in perioperative pain management.
Dexmedetomidine/pharmacokinetics* ; Printing, Three-Dimensional ; Needles ; Drug Delivery Systems/methods* ; Administration, Cutaneous ; Animals ; Microinjections/instrumentation* ; Skin Absorption ; Skin/metabolism*

Hydroxyectoine, a vital compatible solute, is widely utilized in cosmetics, food, pharmaceutical industries, and biologics. However, the current microbial fermentation methods for hydroxyectoine production face challenges including insufficient precursor supply and low yields. Therefore, developing engineering microbial strains capable of efficiently synthesizing hydroxyectoine is of great significance. In this study, we first constructed a high-yield ectoine-producing strain ECT04 by multi-copy integration of the ectoine synthesis genes ectABC into the pseudogene loci of Escherichia coli MG1655(DE3), achieving an ectoine titer of 6.03 g/L. Subsequently, we employed plasmids with varying copy numbers to express ectD from Chromohalobacter salexigens to enable the conversion for hydroxyectoine production. We further investigated the effects of promoter, co-substrate ɑ-ketoglutarate, Fe²⁺ concentration, and dissolved oxygen on hydroxyectoine synthesis. Through fed-batch fermentation in a 7-L bioreactor, we significantly enhanced the hydroxyectoine production efficiency, attaining a final titer of 8.58 g/L and a productivity of 0.24 g/(L·h). This work successfully achieved the de novo synthesis of hydroxyectoine in E. coli, laying a foundation for the efficient bioproduction of this compound.
Escherichia coli/genetics* ; Fermentation ; Amino Acids, Diamino/biosynthesis* ; Bioreactors/microbiology* ; Metabolic Engineering/methods* ; Chromohalobacter/genetics* ; Plasmids/genetics*

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*