ABSTRACT
Continuous biosensors measure concentration-time profiles of biomolecular substances in order to allow for comparisons of measurement data over long periods of time. To make meaningful comparisons of time-dependent data, it is essential to understand how measurement imprecision depends on the time interval between two evaluation points, as the applicable imprecision determines the significance of measured concentration differences. Here, we define a set of measurement imprecisions that relate to different sources of variation and different time scales, ranging from minutes to weeks, and study these using statistical analyses of measurement data. The methodology is exemplified for Biosensing by Particle Motion (BPM), a continuous, affinity-based sensing technology with single-particle and single-molecule resolution. The studied BPM sensor measures specific small molecules (glycoalkaloids) in an industrial food matrix (potato fruit juice). Measurements were performed over several months at two different locations, on nearly 50 sensor cartridges with in total more than 1000 fluid injections. Statistical analyses of the measured signals and concentrations show that the relative residuals are normally distributed, allowing extraction and comparisons of the proposed imprecision parameters. The results indicate that sensor noise is the most important source of variation followed by sample pretreatment. Variations caused by fluidic transport, changes of the sensor during use (drift), and variations due to different sensor cartridges and cartridge replacements appear to be small. The imprecision due to sensor noise is recorded over few-minute time scales and is attributed to stochastic fluctuations of the single-molecule measurement principle, false-positive signals in the signal processing, and nonspecific interactions. The developed methodology elucidates both time-dependent and time-independent factors in the measurement imprecision, providing essential knowledge for interpreting concentration-time profiles as well as for further development of continuous biosensing technologies.
ABSTRACT
Dialysis patients often have inadequate health literacy, affecting self-care and outcomes. This study used LINE app to provide personalized health education to Taiwanese dialysis patients and collected physiological data via wearables. While physical activity levels remained unchanged, participants' disease literacy significantly improved post-intervention. Patients' health literacy will evaluate by Health Literacy Questionnaire for Taiwanese Hemodialysis patients (HLQHD). The findings highlight technology-driven interventions' potential to enhance health literacy and disease management among dialysis patients.
Subject(s)
Health Literacy , Mobile Applications , Patient Education as Topic , Renal Dialysis , Humans , Taiwan , Male , Female , Patient Education as Topic/methods , Middle Aged , Aged , Self CareABSTRACT
BACKGROUND AND OBJECTIVES: Nintedanib, a tyrosine kinase inhibitor, is integral in slowing pulmonary fibrosis progression in chronic fibrotic interstitial lung disease (ILD). However, the occurrence of adverse drug reactions (ADRs) often limits its use, leading to treatment discontinuation, typically within 3-12 months. Discontinuation adversely affects patient outcomes. The study investigated whether aggressive ADR management can prolong nintedanib therapy and improve patient outcomes. METHODS: This retrospective, single-center study enrolled Taiwanese patients with chronic fibrotic ILD who were treated with nintedanib from January 2016 to December 2022 in Kaohsiung Chang Gung Memorial Hospital. Patients were categorized into those who discontinued treatment within 180 days and those continuing beyond. Management of ADRs was identified through concurrent prescriptions for symptoms such as nausea, vomiting, diarrhea, or hepatic dysfunction. Baseline demographics, comorbidities, pulmonary function tests, and instances of acute exacerbation were analyzed. RESULTS: The study enrolled 94 patients, with 71 (75.5%) experiencing ADRs. Among these, 41 (43.6%) discontinued nintedanib within 180 days. The administration of medications for managing nausea/vomiting [17 (41.5%) versus 36 (67.9%), p = 0.0103] and diarrhea [12 (29.3%) versus 33 (62.3%), p = 0.0015] was less frequent in the discontinued group compared with the continued group. Additionally, a higher incidence of acute exacerbation was observed in the discontinued group (34.1% versus 20.8%, p = 0.016). CONCLUSION: Aggressive management of ADRs may enhance patient tolerance to nintedanib, potentially prolonging treatment duration and improving outcomes in chronic fibrotic ILD.
ABSTRACT
Brain oscillations are crucial for perception, memory, and behavior. Parvalbumin-expressing (PV) interneurons are critical for these oscillations, but their population dynamics remain unclear. Using voltage imaging, we simultaneously recorded membrane potentials in up to 26 PV interneurons in vivo during hippocampal ripple oscillations in mice. We found that PV cells generate ripple-frequency rhythms by forming highly dynamic cell assemblies. These assemblies exhibit rapid and significant changes from cycle to cycle, varying greatly in both size and membership. Importantly, this variability is not just random spiking failures of individual neurons. Rather, the activities of other PV cells contain significant information about whether a PV cell spikes or not in a given cycle. This coordination persists without network oscillations, and it exists in subthreshold potentials even when the cells are not spiking. Dynamic assemblies of interneurons may provide a new mechanism to modulate postsynaptic dynamics and impact cognitive functions flexibly and rapidly.
Subject(s)
Interneurons , Parvalbumins , Animals , Parvalbumins/metabolism , Interneurons/physiology , Mice , Hippocampus/physiology , Hippocampus/cytology , Action Potentials/physiology , Brain/physiology , Brain/cytology , Mice, Transgenic , Brain Waves/physiology , MaleABSTRACT
In pursuing sustainable thermal insulation solutions, this study explores the integration of human hair and feather keratin with alginate. The aim is to assess its potential in thermal insulation materials, focusing on the resultant composites' thermal and mechanical characteristics. The investigation uncovers that the type and proportion of keratin significantly influence the composites' porosity and thermal conductivity. Specifically, higher feather keratin content is associated with lesser sulfur and reduced crosslinking due to shorter amino acids, leading to increased porosity and pore sizes. This, in turn, results in a decrease in ß-structured hydrogen bond networks, raising non-ordered protein structures and diminishing thermal conductivity from 0.044 W/(m·K) for pure alginate matrices to between 0.033 and 0.038 W/(m·K) for keratin-alginate composites, contingent upon the specific ratio of feather to hair keratin used. Mechanical evaluations further indicate that composites with a higher ratio of hair keratin exhibit an enhanced compressive modulus, ranging from 60 to 77 kPa, demonstrating the potential for tailored mechanical properties to suit various applications. The research underscores the critical role of sulfur content and the crosslinking index within keratin's structures, significantly impacting the thermal and mechanical properties of the matrices. The findings position keratin-based composites as environmentally friendly alternatives to traditional insulation materials.
Subject(s)
Feathers , Hair , Keratins , Thermal Conductivity , Keratins/chemistry , Feathers/chemistry , Hair/chemistry , Humans , Alginates/chemistry , PorosityABSTRACT
Biosensors based on immobilized antibodies require molecular strategies that (i) couple the antibodies in a stable fashion while maintaining the conformation and functionality, (ii) give outward orientation of the paratope regions of the antibodies for good accessibility to analyte molecules in the biofluid, and (iii) surround the antibodies by antibiofouling molecules. Here, we demonstrate a method to achieve oriented coupling of antibodies to an antifouling poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG) substrate, using glycan remodeling to create antibody-DNA conjugates. The coupling, orientation, and functionality of the antibodies were studied using two analysis methods with single-molecule resolution, namely single-molecule localization microscopy and continuous biosensing by particle motion. The biosensing functionality of the glycan-remodeled antibodies was demonstrated in a sandwich immunosensor for procalcitonin. The results show that glycan-remodeled antibodies enable oriented immobilization and biosensing functionality with low nonspecific binding on antifouling polymer substrates.
Subject(s)
Antibodies, Immobilized , Biosensing Techniques , Polysaccharides , Biosensing Techniques/methods , Polysaccharides/chemistry , Polysaccharides/immunology , Antibodies, Immobilized/immunology , Antibodies, Immobilized/chemistry , Polyethylene Glycols/chemistry , Biofouling/prevention & control , Polylysine/chemistry , Antibodies/immunology , Antibodies/chemistry , Humans , Polymers/chemistrySubject(s)
Cysts , Recurrence , Humans , Cysts/surgery , Liver Diseases/surgery , Male , Gastrostomy/methods , Drainage/methods , Female , Middle AgedABSTRACT
BACKGROUND: Valvular heart disease (VHD) is becoming increasingly important to manage the risk of future complications. Electrocardiographic (ECG) changes may be related to multiple VHDs, and (AI)-enabled ECG has been able to detect some VHDs. We aimed to develop five deep learning models (DLMs) to identify aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation. METHODS: Between 2010 and 2021, 77,047 patients with echocardiography and 12-lead ECG performed within 7 days were identified from an academic medical center to provide DLM development (122,728 ECGs), and internal validation (7,637 ECGs). Additional 11,800 patients from a community hospital were identified to external validation. The ECGs were classified as with or without moderate-to-severe VHDs according to transthoracic echocardiography (TTE) records, and we also collected the other echocardiographic data and follow-up TTE records to identify new-onset valvular heart diseases. RESULTS: AI-ECG adjusted for age and sex achieved areas under the curves (AUCs) of >0.84, >0.80, >0.77, >0.83, and >0.81 for detecting aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation, respectively. Since predictions of each DLM shared similar components of ECG rhythms, the positive findings of each DLM were highly correlated with other valvular heart diseases. Of note, a total of 37.5-51.7% of false-positive predictions had at least one significant echocardiographic finding, which may lead to a significantly higher risk of future moderate-to-severe VHDs in patients with initially minimal-to-mild VHDs. CONCLUSION: AI-ECG may be used as a large-scale screening tool for detecting VHDs and a basis to undergo an echocardiography.
Subject(s)
Artificial Intelligence , Electrocardiography , Heart Valve Diseases , Humans , Electrocardiography/methods , Female , Male , Heart Valve Diseases/diagnosis , Heart Valve Diseases/diagnostic imaging , Heart Valve Diseases/physiopathology , Aged , Middle Aged , Deep Learning , Echocardiography , Aged, 80 and overABSTRACT
Stochastic and deterministic processes are the major themes governing microbial community assembly; however, their roles in bioreactors are poorly understood. Herein, the mechanisms underlying microbial assembly and the effect of rare taxa were studied in biofilters. Phylogenetic tree analysis revealed differences in microbial communities at various stages. Null model analysis showed that stochastic processes shaped the community assembly, and deterministic processes emerged only in the inoculated activated sludge after domestication. This finding indicates the dominant role of stochastic factors (biofilm formation, accumulation, and aging). The Sloan neutral model corroborated the advantages of stochastic processes and mainly attributed these advantages to rare taxa. Cooccurrence networks revealed the importance of rare taxa, which accounted for more than 85% of the keystones. Overall, these results provide good foundations for understanding community assembly, especially the role of rare taxa, and offer theoretical support for future community design and reactor regulation.
Subject(s)
Bioreactors , Phylogeny , Stochastic Processes , Bioreactors/microbiology , Filtration , Sewage/microbiology , Bacteria/metabolism , Bacteria/genetics , Biofilms , Microbiota , RNA, Ribosomal, 16S/geneticsABSTRACT
OBJECTIVE: We describe a rare case of uterine mesothelial cysts mimicking ovarian cysts in a primipara patient with a history of Cesarean section. CASE REPORT: A 39-year-old female patient with history of Cesarean section presented with dysmenorrhea. Sonography revealed that a hypoechoic and anechoic multicystic complex, which was located on the right side of the pelvic cavity, had infiltrated the adjacent posterior wall of the uterus, and it was preoperatively misdiagnosed as ovarian cysts with suspected endometrioma. Laparoscopic surgery revealed multiple cystic lesions filled with clear yellow fluid on the posterior uterine wall instead of the adnexa. Laparoscopic uterine cystectomy was performed, and the patient's recovery was uneventful. Pathohistological and immunohistochemical examinations confirmed the diagnosis of uterine mesothelial cysts. CONCLUSION: Uterine mesothelial cysts should be considered in the differential diagnosis of pelvic lesions. Increasing the awareness of this rare disease can contribute to improved evaluation, decision-making, and disease management.
Subject(s)
Cesarean Section , Cysts , Ovarian Cysts , Humans , Female , Adult , Ovarian Cysts/diagnosis , Ovarian Cysts/surgery , Diagnosis, Differential , Cysts/diagnosis , Cysts/surgery , Ultrasonography , Laparoscopy , Uterine Diseases/diagnosis , Uterine Diseases/surgery , Pregnancy , Endometriosis/diagnosisABSTRACT
Biofilms are widely used and play important roles in biological processes. Low temperature of wastewater inhibits the development of biofilms derived from wastewater activated sludge. However, the specific mechanism of temperature on biofilm development is still unclear. This study explored the mechanism of temperature on biofilm development and found a feasible method to enhance biofilm development at low temperature. The amount of biofilm development decreased by approximately 66 % and 55 % at 4 °C and 15 °C, respectively, as compared to 28 °C. The cyclic dimeric guanosine monophosphate (c-di-GMP) concentration also decreased at low temperature and was positively correlated with extracellular polymeric substance (EPS) content, formation, and adhesion strength. Microbial community results showed that low temperature inhibited the normal survival of most microorganisms, but promoted the growth of some psychrophile bacteria like Sporosarcina, Caldilineaceae, Gemmataceae, Anaerolineaceae and Acidobacteriota. Further analysis of functional genes demonstrated that the abundance of functional genes related to the synthesis of c-di-GMP (K18968, K18967 and K13590) decreased at low temperature. Subsequently, the addition of exogenous spermidine increased the level of intracellular c-di-GMP and alleviated the inhibition effect of low temperature on biofilm development. Therefore, the possible mechanism of low temperature on biofilm development could be the inhibition of the microorganism activity and reduction of the communication level between cells, which is the closely related to the EPS content, formation, and adhesion strength. The enhancement of c-di-GMP level through the exogenous addition of spermidine provides an alternative strategy to enhance biofilm development at low temperatures. The results of this study enhance the understanding of the influence of temperature on biofilm development and provide possible strategies for enhancing biofilm development at low temperatures.
Subject(s)
Bacteria , Biofilms , Cyclic GMP , Bacterial Physiological Phenomena , Cold Temperature , Cyclic GMP/analogs & derivatives , Cyclic GMP/metabolism , Extracellular Polymeric Substance Matrix , Wastewater/microbiologyABSTRACT
BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.
ABSTRACT
Identifying the descriptors for the synergistic catalytic activity of bifunctional oxide-zeolite catalysts constitutes a formidable challenge in realizing the potential of tandem hydrogenation of CO2 to hydrocarbons (HC) for sustainable fuel production. Herein, we combined CH3OH synthesis from CO2 and H2 on In2O3 and methanol-to-hydrocarbons (MTH) conversion on HZSM-5 and discerned the descriptors by leveraging the distance-dependent reactivity of bifunctional In2O3 and HZSM-5 admixtures. We modulated the distance between redox sites of In2O3 and acid sites of HZSM-5 from milliscale (â¼10 mm) to microscale (â¼300 µm) and observed a 3-fold increase in space-time yield of HC and CH3OH (7.5 × 10-5 molC gcat-1 min-1 and 2.5 × 10-5 molC gcat-1 min-1, respectively), due to a 10-fold increased rate of CH3OH advection (1.43 and 0.143 s-1 at microscale and milliscale, respectively) from redox to acid sites. Intriguingly, despite the potential of a three-order-of-magnitude enhanced CH3OH transfer at a nanoscale distance (â¼300 nm), the sole product formed was CH4. Our reactivity data combined with Raman, Fourier transform infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) revealed the occurrence of solid-state-ion-exchange (SSIE) between acid sites and Inδ+ ions, likely forming In2O moieties, inhibiting C-C coupling and promoting CH4 formation through CH3OH hydrodeoxygenation (HDO). Density functional theory (DFT) calculations further revealed that CH3OH adsorption on the In2O moiety with preadsorbed and dissociated H2 forming an H-In-OH-In moiety is the likely reaction mechanism, with the kinetically relevant step appearing to be the hydrogenation of the methyl species. Overall, our study revealed that efficient CH3OH transfer and prevention of ion exchange are the key descriptors in achieving catalytic synergy in bifunctional In2O3/HZSM-5 systems.
ABSTRACT
Upregulation of the multidrug efflux pump ABCB1/MDR1 (P-gp) and the anti-apoptotic protein BIRC5/Survivin promotes multidrug resistance in various human cancers. GDC-0152 is a DIABLO/SMAC mimetic currently being tested in patients with solid tumors. However, it is still unclear whether GDC-0152 is therapeutically applicable for patients with ABCB1-overexpressing multidrug-resistant tumors, and the molecular mechanism of action of GDC-0152 in cancer cells is still incompletely understood. In this study, we found that the potency of GDC-0152 is unaffected by the expression of ABCB1 in cancer cells. Interestingly, through in silico and in vitro analysis, we discovered that GDC-0152 directly modulates the ABCB1-ATPase activity and inhibits ABCB1 multidrug efflux activity at sub-cytotoxic concentrations (i.e., 0.25×IC50 or less). Further investigation revealed that GDC-0152 also decreases BIRC5 expression, induces mitophagy, and lowers intracellular ATP levels in cancer cells at low cytotoxic concentrations (i.e., 0.5×IC50). Co-treatment with GDC-0152 restored the sensitivity to the known ABCB1 substrates, including paclitaxel, vincristine, and YM155 in ABCB1-expressing multidrug-resistant cancer cells, and it also restored the sensitivity to tamoxifen in BIRC5-overexpressing tamoxifen-resistant breast cancer cells in vitro. Moreover, co-treatment with GDC-0152 restored and potentiated the anticancer effects of paclitaxel in ABCB1 and BIRC5 co-expressing xenograft tumors in vivo. In conclusion, GDC-0152 has the potential for use in the management of cancer patients with ABCB1 and BIRC5-related drug resistance. The findings of our study provide essential information to physicians for designing a more patient-specific GDC-0152 clinical trial program in the future.
Subject(s)
ATP Binding Cassette Transporter, Subfamily B , Benzodioxoles , Drug Resistance, Neoplasm , Indolizines , Survivin , Humans , ATP Binding Cassette Transporter, Subfamily B/genetics , ATP Binding Cassette Transporter, Subfamily B/metabolism , Survivin/genetics , Survivin/metabolism , Animals , Drug Resistance, Neoplasm/drug effects , Cell Line, Tumor , Female , Mice, Nude , Mice , Antineoplastic Agents/pharmacology , Xenograft Model Antitumor Assays , Apoptosis Regulatory Proteins/metabolism , Drug Resistance, Multiple/drug effects , Paclitaxel/pharmacology , Mitochondrial Proteins/metabolism , Mitochondrial Proteins/genetics , Mice, Inbred BALB C , Inhibitor of Apoptosis Proteins/metabolism , Inhibitor of Apoptosis Proteins/geneticsABSTRACT
Registered nurses have voluntarily created hand casts for families, providing comfort during challenging moments. Hand casting moves the patient's family and nurses. As requested by parents, staff apply a quick-drying gel to sick children's hands and feet. After preparing the gel mold, alginate molding powder is poured in and hardened for many days. Parents mourn their children with great sensitivity. Every mold and hospital bedside we go to offers closure to the lost child's dying moments. A compelling benefit of a three-dimensional hand-cast is preserving a passing moment.
ABSTRACT
Objective.We aimed to fuse the outputs of different electrocardiogram-derived respiration (EDR) algorithms to create one higher quality EDR signal.Methods.We viewed each EDR algorithm as a software sensor that recorded breathing activity from a different vantage point, identified high-quality software sensors based on the respiratory signal quality index, aligned the highest-quality EDRs with a phase synchronization technique based on the graph connection Laplacian, and finally fused those aligned, high-quality EDRs. We refer to the output as the sync-ensembled EDR signal. The proposed algorithm was evaluated on two large-scale databases of whole-night polysomnograms. We evaluated the performance of the proposed algorithm using three respiratory signals recorded from different hardware sensors, and compared it with other existing EDR algorithms. A sensitivity analysis was carried out for a total of five cases: fusion by taking the mean of EDR signals, and the four cases of EDR signal alignment without and with synchronization and without and with signal quality selection.Results.The sync-ensembled EDR algorithm outperforms existing EDR algorithms when evaluated by the synchronized correlation (γ-score), optimal transport (OT) distance, and estimated average respiratory rate score, all with statistical significance. The sensitivity analysis shows that the signal quality selection and EDR signal alignment are both critical for the performance, both with statistical significance.Conclusion.The sync-ensembled EDR provides robust respiratory information from electrocardiogram.Significance.Phase synchronization is not only theoretically rigorous but also practical to design a robust EDR.
Subject(s)
Respiration , Signal Processing, Computer-Assisted , Software , Respiratory Rate , Algorithms , Electrocardiography/methodsABSTRACT
Post-harvest losses of fruits due to decay and concerns regarding microbial food safety are significant within the produce processing industry. Additionally, maintaining the quality of exported commodities to distant countries continues to pose a challenge. To address these issues, the application of bioactive compounds, such as essential oils, has gained recognition as a means to extend shelf life by acting as antimicrobials. Herein, we have undertaken an innovative approach by nano-encapsulating cinnamon-bark essential oil using whey protein concentrate and imbibing nano-encapsulates into food-grade wax commonly applied on produce surfaces. We have comprehensively examined the physical, chemical, and antimicrobial properties of this hybrid wax to evaluate its efficacy in combatting the various foodborne pathogens that frequently trouble producers and handlers in the post-harvest processing industry. The coatings as applied demonstrated a static contact angle of 85 ± 1.6°, and advancing and receding contact angles of 90 ± 1.1° and 53.0 ± 1.6°, respectively, resembling the wetting properties of natural waxes on apples. Nanoencapsulation significantly delayed the release of essential oil, increasing the half-life by 61 h compared to its unencapsulated counterparts. This delay correlated with statistically significant reductions (p = 0.05) in bacterial populations providing both immediate and delayed (up to 72 h) antibacterial effects as well as expanded fungal growth inhibition zones compared to existing wax technologies, demonstrating promising applicability for high-quality fruit storage and export. The utilization of this advanced produce wax coating technology offers considerable potential for bolstering food safety and providing enhanced protection against bacteria and fungi for produce commodities.
ABSTRACT
Reactive oxygen species (ROS) have been recognized as prevalent contributors to the development of inner retinal injuries including optic neuropathies such as glaucoma, non-arteritic anterior ischemic optic neuropathy, traumatic optic neuropathy, and Leber hereditary optic neuropathy, among others. This underscores the pivotal significance of oxidative stress in the damage inflicted upon retinal tissue. To combat ROS-related challenges, this study focuses on creating an injectable and tissue-adhesive hydrogel with tailored antioxidant properties for retinal applications. GelCA, a gelatin-modified hydrogel with photo-crosslinkable and injectable properties, is developed. To enhance its antioxidant capabilities, curcumin-loaded polydopamine nanoparticles (Cur@PDA NPs) are incorporated into the GelCA matrix, resulting in a multifunctional nanocomposite hydrogel referred to as Cur@PDA@GelCA. This hydrogel exhibits excellent biocompatibility in both in vitro and in vivo assessments, along with enhanced tissue adhesion facilitated by NPs in an in vivo model. Importantly, Cur@PDA@GelCA demonstrates the potential to mitigate oxidative stress when administered via intravitreal injection in retinal injury models such as the optic nerve crush model. These findings underscore its promise in advancing retinal tissue engineering and providing an innovative strategy for acute neuroprotection in the context of inner retinal injuries.
Subject(s)
Antioxidants , Tissue Adhesives , Nanogels , Reactive Oxygen Species , Retina , HydrogelsABSTRACT
Starvation disturbance due to nutrient limitation is a common problem in bioreactors. However, an understanding of how microbial systems respond to starvation remains in its infancy. Here the metabolic response mechanism of a biofilm community to starvation was investigated using a well-controlled gaseous toluene treatment biofilter through interruption of its operation. It was found that metabolic characteristics showed significant differences before and after starvation. The dominant carbon source utilization type shifted from amino acids and carboxylic acids to esters and carbohydrates after starvation, which is more conducive to improving energy production. Metagenomic sequencing analysis supported that the changes in the dominant metabolic substrate, enhanced metabolic stability, and flexibility in the mode of energy metabolism could be the main ways to guarantee functional resilience in ecosystems after starvation. The results highlight the microbial metabolic response to starvation, which would be beneficial to the understanding of functional resilience and bioreactor stability.
Subject(s)
Ecosystem , Resilience, Psychological , Gases , Metagenome , Carbon , BioreactorsABSTRACT
Bacterial communication interruption based on quorum quenching (QQ) has been proven its potential in biofilm formation inhibition and biofouling control. However, it would be more satisfying if QQ could be combined with the efficient degradation of contaminants in environmental engineering. In this study, we engineered a biofilm of Pseudomonas putida through introducing a QQ synthetic gene, which achieved both biofilm formation inhibition and efficient degradation of benzene series in wastewater. The aiiO gene introduced into the P. putida by heat shock method was highly expressed to produce QQ enzyme to degrade AHL-based signal molecules. The addition of this engineered P. putida reduced the AHLs concentration, quorum sensing gene expression, and connections of the microbial community network in activated sludge and therefore inhibited the biofilm formation. Meanwhile, the sodium benzoate degradation assay indicated an enhanced benzene series removal ability of the engineering bacteria on activated sludge. Besides, we also demonstrated a controllable environmental risk of this engineered bacteria through monitoring its abundance and horizontal gene transfer test. Overall, the results of this study suggest an alternative strategy to solve multiple environmental problems through genetic engineering means and provide support for the application of engineered bacteria in environmental biotechnology.